The purpose of this Tutorial is to highlight the suitability of time-of-flight secondary ion mass spectrometry (ToF-SIMS) and OrbiTrap™ SIMS (Orbi-SIMS) in bone research by introducing fundamentals and best practices of bone analysis with these mass spectrometric imaging (MSI) techniques. The Tutorial includes sample preparation, determination of best-suited measurement settings, data acquisition, and data evaluation, as well as a brief overview of SIMS applications in bone research in the current literature. SIMS is a powerful analytical technique that allows simultaneous analysis and visualization of mineralized and nonmineralized bone tissue, bone marrow as well as implanted biomaterials, and interfaces between bone and implants. Compared to histological staining, which is the standard analytical procedure in bone research, SIMS provides chemical imaging of nonstained bone sections that offers insights beyond what is conventionally obtained. The Tutorial highlights the versatility of ToF- and Orbi-SIMS in addressing important questions in bone research. By illustrating the value of these MSI techniques, it demonstrates how they can contribute to advance progress in bone research.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a mass spectrometric imaging (MSI) technique that provides information about the chemical composition of analyte molecules and their 2D distribution on surfaces by irradiating the sample with an ionized beam and recording the signal of the generated secondary ions (SIs) at different locations.1 ToF-SIMS, thus, enables label-free imaging of different types of bone tissue and can be used for simultaneous analysis of different compounds in numerous areas of bone research. In bone research, besides determining the bone quality and mineral status, research into implant materials for improved bone healing in damaged bone is also of great interest. To meet the challenges of bone healing, especially, in systemically diseased bone, biomaterials for bone defects are often modified with substances that can positively influence bone metabolism and lead to improved regeneration of the bone. Detection of these substances in bone is essential for evaluating the behavior of implant materials in vivo, particularly, with respect to their ability to deliver healing-promoting substances to bone. In addition, the ability to map the chemical composition of cells and tissues in different bone regions may improve the understanding of chemical changes in the bone because of underlying biological processes.2 For example, chemical mapping could allow tracking the spatial distribution of metabolites or lipids in bone. The ability of MSI techniques such as ToF-SIMS to record mass spectra at subcellular resolution offers the potential to exploit these questions in bone research.2 Since ToF-SIMS can detect both organic and inorganic constituents in a sample during the same analysis, it is ideally suited for visualizing and differentiating different areas of mineralized bone based on its chemical composition with high spatial resolution, as well as nonmineralized bone and bone marrow.3–6 To improve mass accuracy, mass resolution, and, thus, enable more precise peak identification, a hybrid SIMS instrument has been developed with the possibility of using an OrbiTrap™ mass analyzer in addition to the ToF analyzer.7–9 

The versatility of ToF- and Orbi-SIMS analyses is valuable for answering important questions in bone research. Thus, these MSI techniques have great potential in bone research and should be considered standard analytical methods in the future. This Tutorial, therefore, provides an overview of why the use of SIMS is particularly relevant in the context of bone research. As an introduction, a brief background on the topic of bone, bone diseases, and biomaterials is first given. This is followed by a presentation of ToF- and Orbi-SIMS working principles and method-specific advantages.

After providing an introduction to SIMS and bone research, the Tutorial aims to guide practical application by briefly explaining the most used sample preparation steps, different measurement methods, as well as data evaluation of SIMS analyses of bone. In the third part of the Tutorial, the main pitfalls of this technique in the context of bone research will be highlighted. Finally, relevant publications on the application of SIMS in bone research are briefly summarized to give the reader an idea of bone research areas in which ToF- and Orbi-SIMS can be used.

In general, bone can be regarded as a natural composite material due to its various components, including bone cells (osteoblasts, osteoclasts, osteocytes, etc.), an organic matrix mainly built of collagen-type I fibers, noncollagenous proteins, lipids, as well as inorganic mineral components.10–14 

At the macroscopic level, there are two types of bone tissue: cortical bone and trabecular bone. Compact, cortical bone forms the outer shell, while trabecular bone is less dense and found inside and at both ends of long bones. Both cortical and trabecular bones are built of lamellae, which are, in general, composed of bundles of collagen-type I fibers. At the lowest hierarchical level, collagen triplet helices and inorganic hydroxyapatite [Ca10(PO4)6(OH)2] nanocrystals are major components of those nanocomposite-forming mineralized collagen fibrils.15,16 In cortical bone, the lamellae are concentric and highly organized, and in their centers, Haversian canals contain nerve fibers and blood vessels, providing oxygen and nutrition. Lamellae of trabecular bone differ in their distribution and arrangement, as they are planar and less organized.15,16

Trabecular, also called cancellous bone, and cortical bone differ from each other not only in the microstructure but also in the surface area to volume ratio (greater in trabecular bone), size of cell-covered surface area, and greater proximity of bone cells to bone marrow in trabecular bone. This contributes to the fact that cancellous bone generally has a higher metabolic activity than cortical bone.16 As a result, bone remodeling, as well as the response to changes in mechanical stress and strain, occur more rapidly in trabecular bone than in cortical bone.15,16

Bone remodeling removes old bone tissue due to resorption by osteoclasts and replaces it with new bone tissue built by osteoblasts. This remodeling cycle continues throughout life and is typically balanced to maintain healthy bone and calcium homeostasis. Moreover, bone remodeling is crucial for successful fracture healing. Any alterations to bone resorption by osteoclasts and bone formation by osteoblasts can result in bone diseases or failed fracture healing. For example, excessive bone resorption by osteoclasts without a corresponding amount of new bone formation by osteoblasts leads to the well-known disease osteoporosis.

Knowledge of bone mineral status as well as the macrostructure and microstructure of bone is an important aspect in bone research. Due to increased life expectancy in many countries, skeletal diseases will affect millions of people sometime in the future. Those diseases can be acute ones, such as fractures, or chronic ones, such as osteoporosis and bone tumors. Both types require treatments that involve the use of cells, growth factors, and bone substitutes, as biomaterials/scaffolds, with biocompatibility, osteoinductive, and osteoconductive properties.

Different areas of bone, which can be chemically imaged by ToF-SIMS, are shown in Fig. 1. ToF-SIMS data for imaging of the vertebrae and trabecular bone were obtained from the study by Henss et al.17 For the humerus, cortical bone, and bone marrow, previously unused datasets from the studies by Kern et al.5,18 were used.

FIG. 1.

At the macroscopic level, long bones or vertebrae, for example, consist of outer cortical bone and inner trabecular bone, with the bone marrow found inside trabecular bone. The microstructure of both cortical and trabecular bone consists of lamellae, which are composed of bundles of mineralized collagen fibers. Whole bone sections as well as microstructure of cortical bone, trabecular bone, and bone marrow can be chemically imaged by ToF-SIMS. ToF-SIMS overlays show mineralized bone (mass signals of HAP, Table S6, Ref. 67) in red, nonmineralized bone (mass signals of collagen, Table S6, Ref. 67) in green, and bone marrow (lipid mass signals, Table S7, Ref. 67) in blue and yellow.

FIG. 1.

At the macroscopic level, long bones or vertebrae, for example, consist of outer cortical bone and inner trabecular bone, with the bone marrow found inside trabecular bone. The microstructure of both cortical and trabecular bone consists of lamellae, which are composed of bundles of mineralized collagen fibers. Whole bone sections as well as microstructure of cortical bone, trabecular bone, and bone marrow can be chemically imaged by ToF-SIMS. ToF-SIMS overlays show mineralized bone (mass signals of HAP, Table S6, Ref. 67) in red, nonmineralized bone (mass signals of collagen, Table S6, Ref. 67) in green, and bone marrow (lipid mass signals, Table S7, Ref. 67) in blue and yellow.

Close modal

In bone research, various in vivo and ex vivo techniques are well established to asses bone quality [e.g., bone mineral density distribution (BMDD)]; determine bone density [e.g., dual-energy x-ray absorptiometry (DEXA), quantitative computed tomography, and x-ray microtomography (μCT)]; or evaluate biological tissue, cell types, cell activity, and bone-implant materials (e.g., histochemical and immunohistochemical stains).4,17,19 However, gaining a better understanding of chemical and structural changes in diseased bone is difficult due to the high complexity of the material composition, especially, when bone implants are present. For this reason, methods are needed that both provide detailed chemical information and allow determination of tissue types, mineral status, and distribution with high sensitivity and high spatial resolution.

ToF-SIMS has proven to be a unique and powerful technique in bone research. It enables the simultaneous detection of organic and inorganic substances, which makes it a tool predestined for analysis of complex tissues such as bone. In addition, SIMS is a mass spectrometric imaging technique and, thus, allows detailed information about the chemical composition of bone tissue with high spatial resolution down to the 50 nm range. As several studies prove, SIMS can be used perfectly for analysis of bone formation during fracture healing, for studying biomaterial incorporation, but also for lipid and bone cell detection.4,5,20

1. Operation principle of ToF- and Orbi-SIMS

In a dual-beam system, both ToF- and Orbi-SIMS essentially have a primary ion source for high-resolution surface mass spectrometry and imaging and an additional sputtering source that allows controlled bulk analysis by ablation of the surface [Fig. 2(a)]. Depending on the operating mode of the instrument, the dual-beam system can, therefore, provide high-resolution mass spectra, 2D ion images, as well as depth profiles and 3D analysis.

FIG. 2.

(a) Schematic of a dual-beam ToF-SIMS. The primary ion gun is for high-resolution surface mass spectra and 2D image analysis. The sputter gun allows depth profiling and 3D imaging analysis. (b) Generation of SIs. The sample surface is bombarded with primary ions whose energy is transferred to the surface target atoms by a collision cascade (orange pathways). Atoms and particles can overcome the surface binding energy and are emitted. A certain number of these sputtered species are positively or negatively charged SI. (c) Principles of ToF and OrbiTrap™ mass analyzers. In a hybrid SIMS instrument, ToF- or Orbi-MS can be selected by an electrostatic 90° deflector, the so-called SI switch. (1) SIs are accelerated through an extractor into the ToF analyzer. High mass resolution is enabled by combination of a field-free drift path and a reflectron. (2) When Orbi-MS is selected, SI packets enter the OrbiTrap™ analyzer, where they spread into oscillating rings around the central electrode. SI oscillations induce image currents that are detected by an amplifier between the two halves of the outer electrode. By Fourier transformation of the amplified currents, each m/z of the SI can be determined from its respective frequency of oscillation.

FIG. 2.

(a) Schematic of a dual-beam ToF-SIMS. The primary ion gun is for high-resolution surface mass spectra and 2D image analysis. The sputter gun allows depth profiling and 3D imaging analysis. (b) Generation of SIs. The sample surface is bombarded with primary ions whose energy is transferred to the surface target atoms by a collision cascade (orange pathways). Atoms and particles can overcome the surface binding energy and are emitted. A certain number of these sputtered species are positively or negatively charged SI. (c) Principles of ToF and OrbiTrap™ mass analyzers. In a hybrid SIMS instrument, ToF- or Orbi-MS can be selected by an electrostatic 90° deflector, the so-called SI switch. (1) SIs are accelerated through an extractor into the ToF analyzer. High mass resolution is enabled by combination of a field-free drift path and a reflectron. (2) When Orbi-MS is selected, SI packets enter the OrbiTrap™ analyzer, where they spread into oscillating rings around the central electrode. SI oscillations induce image currents that are detected by an amplifier between the two halves of the outer electrode. By Fourier transformation of the amplified currents, each m/z of the SI can be determined from its respective frequency of oscillation.

Close modal
a. Generation of SIs

In SIMS instruments, an ion beam is generated and focused on the sample surface [Fig. 2(b)]. When those primary ions hit the surface, a collision cascade is initiated, causing surface atoms, electrons, and molecular compounds to fragment and emit from the surface matrix of the sample.21,22 Although most of the emitted particles are neutrals, the number of sputtered ionized species, the so-called secondary ions (SIs), is sufficient for subsequent mass spectrometric analysis. For the subsequent mass analysis, the positively or negatively charged SIs are then extracted by an electric field into the mass analyzer (ToF or OrbiTrap™).

b. Time-of-flight mass analyzer

SIs generated at the sample surface are accelerated into the ToF analyzer by an electrical field applied between the sample and extractor [Fig. 2(c)(1)]. All ions of identical charge have the same kinetic energy E at the beginning of the flight tube. To have a well-defined starting point, either the primary or the secondary ion beam must be pulsed. The accelerated SIs then drift through a field-free tube, with their constant velocities being inversely dependent on the square root of their mass. Lighter ions, therefore, fly through the analyzer at higher speeds and arrive at the detector first. Heavier ions drift more slowly and arrive later at the detector. Thus, the ions are separated according to their time of flight. In order to be able to achieve a high mass resolution, a combination of a field-free drift section and an ion mirror (reflectron) compensates for small differences in the initial energy and angle of ions of the same mass.21 Alternatively, instead of the flight tube-reflectron setup, a so-called triple ion focusing time-of-flight (TRIFT) analyzer can be used. The TRIFT analyzer is a time-of-flight analyzer with a different design, which offers, i.e., higher surface roughness tolerance.23–25 

c. OrbiTrap™ mass analyzer

When entering the OrbiTrap™ analyzer, an electromagnetic field simultaneously induces orbiting of the SIs around a central spindlelike electrode while oscillating in the axial dimension [FIG. 2(c)(2)]. The frequency of the axial ion oscillation is unique for each m/z ratio. To measure these frequencies, the outer electrode of the OrbiTrap™ is split in two by a dielectric ceramic ring, resulting in left and right outer electrodes. The charged ions move from one outer electrode to the other while oscillating in the axial direction, thus inducing image currents, which are detected by a differential amplifier. By Fourier transformation of these amplified currents, the m/z of each SI can be determined from its respective oscillation frequency. Unlike the ToF analyzer, in OrbiTrap™, all m/z are recorded simultaneously. To prevent ions with different m/z values from colliding with each other when oscillating around the axial electrode, an electric potential ramp is applied, which ensures that ions with lower m/z values are pushed closer to the central electrode. The measurement time is directly proportional to the mass resolution of the resulting spectrum, which means that a longer measurement time leads to better mass resolution. Overall, the mass resolving power in OrbiTrap™ MS (m/Δm > 240 000) is typically higher than the highest available mass resolving power in ToF MS (m/Δm > 30 000), resulting in more accurate mass calibration and signal assignment.22,26,27

1. High sensitivity

Due to the combination of single ion detectors and high transmission of the ToF analyzer, ToF-SIMS is a highly sensitive technique, which can detect chemical species at very low concentrations (<10 ppm). In bone research, this is particularly important for detecting the incorporation of healing-promoting substances into bone tissue since, usually, the concentration of these substances is low. High sensitivity also means that the primary ion dose can mostly be kept < 1012 ions/cm2. This so-called static SIMS condition allows analysis of statistically only the first atomic layer of the sample surface. Thus, the sample surface is hardly destroyed and allows, for example, histological staining after ToF-SIMS analyses.

2. High mass accuracy and mass resolution

Depending on the instrument setting used, with ToF-SIMS, high mass resolution (m/Δm > 30 000) is achievable, which is important for discrimination of SIs with similar masses. The addition of an OrbiTrap™ mass analyzer to an SIMS instrument combines the strength of high mass resolving power (>240 000 at m/z 200), high mass accuracy (<1 ppm), and MS/MS capability of the OrbiTrap™ with high-resolution SIMS imaging.7,28 In particular, the high mass resolution and accuracy achieved with the OrbiTrap™ are ideal for unambiguous signal identification and provide a new level of analysis and discovery of biomarkers, metabolites, or lipids.5,7,8,20,29 Therefore, MSI analysis can function as a first step in multimodal MSI/histological experiments, guiding further histological and/or immunohistochemical experiments of biologically relevant biomarkers.

3. High-resolution imaging analysis

Histologylike high-resolution mass imaging analysis of unstained, label-free bone cross sections can provide important information about different bone areas, bone/implant interfaces, and implanted biomaterials. Depending on the ToF-SIMS setting applied and the sample nature, lateral resolutions < 50 nm can be achieved. An application example of ToF-SIMS imaging in bone research is monitoring of the release and incorporation of bioactive substances from bone-implant biomaterials into bone, which is not possible with histological staining alone. The high spatial resolution achievable with ToF-SIMS allows lateral localization of those substances in various bone components.

4. Parallel acquisition of all chemical information

Both ToF- and Orbi-SIMS enable simultaneous detection of organic and inorganic substances and are thus predestined for use in the analysis of the natural composite bone. Detailed information about the chemical composition of bone in combination with high spatial resolution is possible, even in trace concentrations.3,30,31 Therefore, ToF-SIMS has already been used in numerous studies, not only for the analysis of bone formation in fractures, biomaterial-protein interactions, or implant-tissue interactions but also for the analysis of lipids in bone cells.4,19,32–34

5. Surface and bulk analysis

As mentioned above, static SIMS conditions enable the analysis of the sample surface without noticeably destroying it. Combination with additional sputter guns enables 3D imaging analysis and depth profiling by applying an alternating sequence of analysis and sputtering steps. Due to the high current of the sputter gun, it removes material between the analysis scans, which means that the sample is destroyed in this dynamic SIMS mode. Nevertheless, diffusion experiments of healing-promoting substances into bone tissue can be carried out using depth profiling and 3D analysis, for example.6,18,35,36

6. Analysis of positively and negatively charged SIs

ToF- and Orbi-SIMS can analyze both positively and negatively charged SIs. This enables the detection of species that are more easily ionized positively (e.g., calcium species and collagen fragments) and species that are more easily ionized negatively (e.g., lipids). However, in most commercially available instruments, the two polarities cannot be detected within one analysis and separated measurements are required (Fig. 3).

FIG. 3.

Large overview ToF-SIMS scan of a rat femur, obtained with (a) positive and (b) negative polarity. Calcium signals, which represent mineralized bone (shown in red, Table S6, Ref. 67), are more easily ionized positively. In negative polarity, mineralized bone can be shown by phosphate signals (red, Table S8, Ref. 67). However, since phosphates can originate not only from hydroxyapatite but also from other molecules (e.g., phosphatidylcholine, main component of biological membranes), phosphate signals overlap with signals from cartilage tissue when measured in negative polarity. In both positive and negative polarity, nonmineralized bone tissue is shown as collagen signals in green and cartilage signals are shown in blue (Tables S6 and S8, Ref. 67).

FIG. 3.

Large overview ToF-SIMS scan of a rat femur, obtained with (a) positive and (b) negative polarity. Calcium signals, which represent mineralized bone (shown in red, Table S6, Ref. 67), are more easily ionized positively. In negative polarity, mineralized bone can be shown by phosphate signals (red, Table S8, Ref. 67). However, since phosphates can originate not only from hydroxyapatite but also from other molecules (e.g., phosphatidylcholine, main component of biological membranes), phosphate signals overlap with signals from cartilage tissue when measured in negative polarity. In both positive and negative polarity, nonmineralized bone tissue is shown as collagen signals in green and cartilage signals are shown in blue (Tables S6 and S8, Ref. 67).

Close modal

7. Retrospective analysis

Another advantage of ToF- and Orbi-SIMS is the possibility of retrospective analysis. For example, histological and immunohistochemical staining techniques enable the identification of biological tissue, different cell types, and cell activities. However, the number and combinations of staining and labeling reagents that can be used are limited. This means that each individual staining and immunohistochemical technique is only able to image certain structures in bone tissue. Therefore, these imaging techniques can only be used in a targeted manner and with prior knowledge of the nature of the sample. ToF- and Orbi-SIMS offer an untargeted analytical approach in the form of comprehensive online analysis during the measurement with the possibility of performing retrospective analyses after the measurement is already complete. This is made possible by parallel acquisition of all chemical information from the sample surface during a single measurement. In this way, data can be analyzed again, even years after the actual measurement, when new findings and questions of current research arise.5 

This part of the Tutorial discusses the best practices required to obtain reliable and reproducible data by ToF- and Orbi-SIMS in the context of bone. First, the most used embedding procedures are briefly explained. Second, the most important aspects of SIMS analysis of bone are shown: surface spectrometry and surface imaging, 3D analysis, the use of the OrbiTrap™ as a mass analyzer instead of a ToF, and, finally, data evaluation of SIMS measurements.

To perform reliable analyses of bone, careful sample preparation is essential. Henss et al. were able to demonstrate that embedding of bone is essential since ToF-SIMS analyses of native, nonembedded bone were not reproducible due to the rough surface of the bone.37 Main objective of this part of the Tutorial is, therefore, to give a brief overview of different methods of bone embedding for SIMS analysis. Besides the need for high reproducibility, embedding techniques should also allow cutting of thin and semithin sections with well-preserved morphological details of the mineralized and cellular structure both within the bone mineral matrix and cartilage tissue.

In principle, bone can be embedded in two ways: either non-native, which means that an increasing alcohol series is applied for dehydration, resulting in loss of most of the chemical information of lipids, or native, cryo-based embedding, which preserves lipids and fatty acids. In both cases, before the embedding process, surrounding soft tissue of bone samples must be removed and fixation of bone samples has to be conducted. Fixation is necessary to preserve morphological and molecular structures as good as possible and is, typically, done with formalin or paraformaldehyde.37–40 

1. None-native embedding

Since most embedding resins are hydrophobic, water must be removed from the bone and exchanged with an organic solvent (e.g., xylol or propylene oxide) as an intermediate. Dehydration of bone samples is done in an ascending alcohol series and is important to avoid formation of bead polymers during polymerization.41,42 The necessary dehydration time for each step depends on sample sizes (e.g., small bone samples from rats, mice, rabbits, and large bone samples from sheep). After dehydration, bone samples are infiltrated with liquid resins, for example, epoxy or methacrylate, which are later polymerized. Depending on the embedding substance, polymerization takes place at low or high temperatures and the embedding substance becomes solid without changing the morphological or molecular properties of the bone. In this way, depending on the embedding substance, very thin sections (from a few tens of micrometers to a few tens of nanometers) can be obtained. Furthermore, samples can be preserved over long periods of time.

Further information about non-native embedding procedures of bone can be found in the literature.19,37,38,41–43

2. Native embedding

To preserve lipids and fatty acids of the bone tissue, cryo-based embedding methods can be employed. For this embedding procedure, acetone is added to dry ice in a safe cold tolerant container. A cold tolerant beaker containing hexane is, subsequently, placed in the dry ice-acetone container in a way that hexane in the inside and acetone in the outside of the beaker have the same height. Fixated bone samples are placed in stainless-steel molds together with an embedding medium and submerged into the hexane until the embedding medium completely solidified. To prevent fissures in the tissue, samples must not be overfrozen. Therefore, samples are immersed into the hexane-dry ice mixture in several steps for short times, then are inspected visually for the freezing process, and re-immersed if the freezing is not complete. Once fully frozen, the stainless-steel molds can be removed, and the embedded bone sample blocks can be stored at −80 °C or sectioned using a cryotome.

Further information about non-native embedding procedures of bone can be found in the literature.39,40

3. Sectioning and sample mounting

A prerequisite for reliable ToF-SIMS data with high mass and lateral resolution is a sample surface that is as flat and smooth as possible with as little topography as possible. Furthermore, since ToF-SIMS is highly surface sensitive, surface contamination should be avoided.44 Henss et al. compared ToF-SIMS analyses of grounded and cut bone sections.37 In their study, they were able to show that cut samples produce clean and smooth surfaces and thus best meet the requirements for reproducible measurements. In the preparation of ground specimens, on the other hand, there is the possibility that a layer of embedding material is deposited on the specimen surface of the sample during the grinding process. This complicates the analysis of organic bone compounds and their differentiation from the embedding material since the peaks originating from bone and resin overlap.37 

Typically, embedded bone blocks are sectioned into several micrometer thick sections and are attached to an adhesive tape. For mass spectrometry analysis, polymer embedded bone sections also need to be superficially deplastified (e.g., with 2-methoxyethyl acetate) and then air-dried before further analysis. As shown by Henss et al., the deplastification process seems not to cause chemical alteration to bone samples.37 After cutting, tapes with bone sections are mounted on microscope slides and stored, either at room temperature or, in the case of cryo-embedded samples, at −80 °C until analysis.

Further information about sample preparation procedures for MSI can be found in the literature.1,37,45,46

After bone samples have been prepared, it is necessary to consider what type of SIMS measurements should be carried out. In a dual-beam system, both ToF and Orbi-SIMS essentially have a primary ion source for high-resolution mass spectrometry imaging and a sputter source that allows controlled ablation of the surface. Therefore, depending on the mode of operation, ToF- and Orbi-SIMS can provide high-resolution mass spectra, 2D ion images, depth profiles, and 3D image analysis.21,47 Each measurement mode has different advantages and disadvantages, such as measurement time, maximum achievable lateral or mass resolution, or sample integrity. When choosing the appropriate measurement mode, the area of the sample that is to be measured also plays a role. If, for example, a mass image of an entire bone section is to be recorded, time-consuming measurement settings are less appropriate. In the following, various measurement modes and their respective best use are briefly explained.

1. Surface spectrometry and surface imaging

To acquire a 2D ion image as well as the associated mass spectrum, short primary ion beam pulses are shot at predefined points on the sample surface during surface analysis.21 In this way, the fine-focused primary ion beam rasters over the sample surface pixel by pixel until all pixels within a defined area have been scanned.21 The SIs generated are then analyzed in the corresponding mass analyzer. Thus, a mass spectrum is recorded together with the x, y coordinates of the analyzed pixel.21 In the surface sensitive static SIMS mode, the primary ion dose is low (<1012 ions/cm2) and, statistically, only up to 10% of the top monolayers of the sample surface are eroded.21,31,47 Hence, the sample surface remains sufficiently intact for subsequent studies, such as histological staining.47 Since the primary ion beam pulses are very short and fine-focused, high-resolution mass spectra as well as surface ion images with high lateral resolution are possible, depending on the applied measurement mode.47 As a primary ion gun, usually a liquid metal ion gun (LMIG) is used with Bix+ or a gas cluster ion beam (GCIB) with Arx+ clusters as primary ion species. Typically, the image field of view in ToF-SIMS analyses is in the submillimeter range. Nevertheless, by stitching together a series of images, a larger overview image can be acquired (see Fig. 4).2 

FIG. 4.

Overview scan of a femur section with biomaterial implanted in a defect area, measured in spectrometry mode. The biomaterial is a strontium-modified calcium phosphate cement paste containing mesoporous bioactive glass particles. Overall, the measurement in spectrometry mode took less than 6 h, with a bone section size of 14 × 8.5 mm2. (a) Already in the total ion image, different areas of bone and former bone defect with residual biomaterial can be identified. (b) Mineralized bone in form of calcium signals, nonmineralized bone in the form of (c) collagen and (d) cartilage signals can be displayed individually. Residues of biomaterial as well as the distribution of the active substances in bone can be represented by (e) strontium and (f) silicon signals. By overlaying ion images of different signals, for example, only (g) nonmineralized bone area (collagen in green and cartilage in blue) or (h) mineralized bone with biomaterial (calcium signals in red, strontium signals in purple, silicon signals in yellow) can be displayed. (i) Overlay image of calcium (red), collagen (green), cartilage (blue), strontium (purple), and silicon (yellow) signals shows distribution of mineralized and nonmineralized bone tissue as well as biomaterial residues in one image. All used mass signals are listed in Table S6 (Ref. 67).

FIG. 4.

Overview scan of a femur section with biomaterial implanted in a defect area, measured in spectrometry mode. The biomaterial is a strontium-modified calcium phosphate cement paste containing mesoporous bioactive glass particles. Overall, the measurement in spectrometry mode took less than 6 h, with a bone section size of 14 × 8.5 mm2. (a) Already in the total ion image, different areas of bone and former bone defect with residual biomaterial can be identified. (b) Mineralized bone in form of calcium signals, nonmineralized bone in the form of (c) collagen and (d) cartilage signals can be displayed individually. Residues of biomaterial as well as the distribution of the active substances in bone can be represented by (e) strontium and (f) silicon signals. By overlaying ion images of different signals, for example, only (g) nonmineralized bone area (collagen in green and cartilage in blue) or (h) mineralized bone with biomaterial (calcium signals in red, strontium signals in purple, silicon signals in yellow) can be displayed. (i) Overlay image of calcium (red), collagen (green), cartilage (blue), strontium (purple), and silicon (yellow) signals shows distribution of mineralized and nonmineralized bone tissue as well as biomaterial residues in one image. All used mass signals are listed in Table S6 (Ref. 67).

Close modal

For ToF-SIMS surface spectrometry and imaging analysis, different measurement modes can be used. With common measurement modes, either high lateral resolution (imaging mode) or high mass resolution (spectrometry mode) is provided. Nevertheless, the advantages of high mass and high lateral resolution can be combined using a setup that is copied from matrix assisted laser desorption (MALDI) imaging, the so-called delayed extraction mode.48,49 All three measurement modes are explained briefly in the following. There are alternative options for TRIFT analyzers, which are not discussed here.

a. Spectrometry mode

Elemental as well as molecular information about the chemical composition of the sample surface can be obtained with high mass accuracy and resolution (mm > 30 000). This allows clear signal identification and discrimination between SI with similar masses as well as high SI counts. However, high mass resolution is accompanied by a low lateral resolution (the micrometer range) (Fig. 5, left column). The spectrometry mode is typically used for overview scans of whole bone sections (Fig. 4) as measurements are relatively fast compared to measurement settings with high lateral resolutions.

FIG. 5.

Comparison of different ToF-SIMS modes using the example of detailed images in the defect area of a rat femur with implanted biomaterial. First row: In RBG, overlay images of all three measurement modes, mineralized bone in form of HAP signals are shown in red, nonmineralized bone tissue is shown as collagen signals in green and cartilage signals are shown in blue. Second row: Ion images of NaO3H+, a cartilage signal. Third row: Mass spectrum for the NaO3H+ signal. In all rows, results of spectrometry measurement are shown on the left, the imaging mode is shown in the middle, and the delayed extraction mode is shown on the right. All used mass signals are listed in Table S6 (Ref. 67).

FIG. 5.

Comparison of different ToF-SIMS modes using the example of detailed images in the defect area of a rat femur with implanted biomaterial. First row: In RBG, overlay images of all three measurement modes, mineralized bone in form of HAP signals are shown in red, nonmineralized bone tissue is shown as collagen signals in green and cartilage signals are shown in blue. Second row: Ion images of NaO3H+, a cartilage signal. Third row: Mass spectrum for the NaO3H+ signal. In all rows, results of spectrometry measurement are shown on the left, the imaging mode is shown in the middle, and the delayed extraction mode is shown on the right. All used mass signals are listed in Table S6 (Ref. 67).

Close modal
b. Imaging mode

In the imaging mode, a well-focused, unbunched primary ion beam is applied with long pulses of 100 ns, resulting in high lateral resolutions of up to 50 nm.49 However, higher lateral resolution comes at the expense of only nominal mass resolution (mm of several hundreds) (Fig. 5, middle column). In addition, due to lower primary ion currents, SI counts are significantly lower compared to the spectrometry mode, leading to longer measurement times (Table I).

TABLE I.

Measurement parameters of Fig. 5. Measurements were performed with a M6 Plus (IONTOF GmbH, Münster, Germany). Additional experimental information can be found in the supplementary material (Ref. 67).

Spectrometry modeImaging modeDelayed extraction mode
Dose density 1.5 × 1012 ions/cm2 1.5 × 1012 ions/cm2 1.7 × 1012 ions/cm2 
Pixels 512 × 512 2048 × 2048 2048 × 2048 
Pixel resolution 780 nm 190 nm 190 nm 
Analysis time 64 min 250 min 375 min 
Mass resolution mm (FWHM) 7862 [at m/z 71.98 (NaO3H+)] 502 [at m/z 71.98 (NaO3H+)] 2832 [at m/z 71.98 (NaO3H+)] 
Spectrometry modeImaging modeDelayed extraction mode
Dose density 1.5 × 1012 ions/cm2 1.5 × 1012 ions/cm2 1.7 × 1012 ions/cm2 
Pixels 512 × 512 2048 × 2048 2048 × 2048 
Pixel resolution 780 nm 190 nm 190 nm 
Analysis time 64 min 250 min 375 min 
Mass resolution mm (FWHM) 7862 [at m/z 71.98 (NaO3H+)] 502 [at m/z 71.98 (NaO3H+)] 2832 [at m/z 71.98 (NaO3H+)] 
c. Delayed extraction

The delayed extraction (DE) mode combines the best of spectrometry and imaging mode. An extraction delay decouples the mass resolution from the length of the primary ion pulse. Extraction delay means that SIs are only extracted after a certain delay time, thus eliminating the time lag in SI production caused by the time lag of incoming primary ions in a nonbunched mode. This results in an improved mass resolution combined with high lateral resolution (Fig. 5, right column). The main disadvantages of this measurement mode are that lower masses are lost during the delay time and the SI yield is decreased. This increases the measurement time for a comparable image from a few minutes to several hours compared to the spectrometry mode (Table I). The extent of the SI yield decreases strongly depending on the applied extraction delay time, which should be kept as small as possible to avoid excessive transmission losses.

Due to its poor mass resolution (Fig. 5, Table I), the imaging mode is only suitable for bone analysis to a limited extent and more commonly used for less complex samples such as purely inorganic ones. In the case of biological samples, the low mass resolution is a problem since, particularly, in the lower mass range, many fragments of different biological molecules have similar m/z and, therefore, cannot be distinguished from one another. Thus, the spectrometry mode is particularly suitable to acquire overview images of entire bone samples (e.g., whole vertebrae, femur, or humerus sections, Fig. 4). Since measurements in this measurement mode are very fast, large sample areas in the millimeter range can be imaged within several hours. Imaging large areas with the delayed extraction or imaging mode, on the other hand, would take days. The delayed extraction mode is particularly suitable for taking detailed images of interesting small areas with a high lateral and high mass resolution, e.g., analyzing the bone microstructure or bone-implant interfaces (Fig. 5).

2. 3D analysis

Using an additional sputter gun (for organic SIMS analysis, typically the GCIB with large argon clusters is used), ToF- and Orbi-SIMS can also provide information about sample composition and distribution of components within the sample bulk. The difference between the surface sensitive static SIMS and surface-eroding dynamic SIMS lies in the applied ion dose of the ion beams.31,47 In dynamic SIMS, the sputter gun ion dose is much higher than that of the primary ion gun, allowing significant material ablation. Alternating use of the primary ion source and the sputtering gun provides spectrometric, imaging, and depth information, enabling both spectrometric depth profiling and spatially resolved 3D analysis.

A typical 3D measurement cycle [Fig. 6(a)] can be described as follows: Surface analysis is performed using the primary ion beam to generate SI, which is then extracted into the analyzer.47 Subsequently, the sputter beam creates a sputter crater by controlled ablation of the sample surface.21 After sputtering, analysis is again performed at the center of this generated crater. Sputtering and analysis steps are repeated sequentially until the desired sample depth is reached. Afterward, the crater depth can be determined by profilometry and used for calibration of the sputter time axis. By selecting interesting signals in the mass spectrum, the respective depth profiles of these ion species as well as the 3D image of their distribution in the analysis volume can be extracted [Fig. 6(b)].31,47

FIG. 6.

Principle of depth profiling in dual-beam ToF-SIMS. (a) The 3D measurement cycle starts with surface analysis. Generated SI (step 1) are extracted into the analyzer (step 2), leading to locally resolved mass spectra and SI images. In the third step, a sputter beam creates a sputter crater by controlled ablation of the sample surface. This measurement cycle is repeated until the desired depth of the sample is reached. (b) By selecting a signal of interest (e.g., Sr+, a bone healing-promoting agent) in the mass spectrum, the depth profile of the selected signal, and its 3D distribution in the analysis volume are obtained.

FIG. 6.

Principle of depth profiling in dual-beam ToF-SIMS. (a) The 3D measurement cycle starts with surface analysis. Generated SI (step 1) are extracted into the analyzer (step 2), leading to locally resolved mass spectra and SI images. In the third step, a sputter beam creates a sputter crater by controlled ablation of the sample surface. This measurement cycle is repeated until the desired depth of the sample is reached. (b) By selecting a signal of interest (e.g., Sr+, a bone healing-promoting agent) in the mass spectrum, the depth profile of the selected signal, and its 3D distribution in the analysis volume are obtained.

Close modal

3D ToF-SIMS measurements enable, for example, the study of the diffusion behavior of specific compounds in bone (e.g., diffusion of strontium in different bone areas, Fig. 7).6,18,35,36

FIG. 7.

3D mass data for strontium diffusion in (a) bone marrow, (b) trabecular bone, and (c) cortical bone. (a) Strontium diffuses faster in bone marrow areas with low lipid content than into areas with high lipid content (Refs. 6 and 18). (b) Individual trabeculae can be identified by the Ca+ signal. Strontium diffuses into both trabecular and nontrabecular areas (Ref. 35). (c) In cortical bone, spatial Ca+ distribution is nearly homogeneous, whereas a concentration gradient with multiple fast diffusion paths can be observed for Sr+ (Ref. 36). All used mass signals are listed in Tables S6 and S7 (Ref. 67).

FIG. 7.

3D mass data for strontium diffusion in (a) bone marrow, (b) trabecular bone, and (c) cortical bone. (a) Strontium diffuses faster in bone marrow areas with low lipid content than into areas with high lipid content (Refs. 6 and 18). (b) Individual trabeculae can be identified by the Ca+ signal. Strontium diffuses into both trabecular and nontrabecular areas (Ref. 35). (c) In cortical bone, spatial Ca+ distribution is nearly homogeneous, whereas a concentration gradient with multiple fast diffusion paths can be observed for Sr+ (Ref. 36). All used mass signals are listed in Tables S6 and S7 (Ref. 67).

Close modal

3. Orbi-SIMS

Due to topography effects, slightly different ion flight times may appear in ToF-SIMS spectra for SIs with the same mass, broadening the ToF-SIMS mass signals. Subsequent calibration of ToF-SIMS mass spectra can also be difficult as both inorganic and organic ion species are of interest in bone analyses (typically, mass spectra are calibrated to either organic or inorganic signals). Therefore, to obtain a mass spectrum with higher mass resolution and better mass accuracy, in hybrid SIMS instruments an OrbiTrap™ analyzer can be used instead of a ToF. OrbiTrap™ mass calibration has to be performed once per day at the beginning of a measurement session on a silver plate, for each polarity (positive and negative). For mass calibration, either LMIG or GCIB are applied in high current long pulses mode as the primary ion gun. For analysis with the OrbiTrap™ analyzer, the microfocused argon GCIB is typically used as the primary ion gun instead of LMIG, permitting spatial resolution of around 2 μm with a mass resolving power of >240 000 at m/z 200.7 

Using an OrbiTrap™ instead of the ToF analyzer allows for high mass accuracy and mass resolution, but at the cost of increased analysis time. Additionally, the maximum achievable lateral resolution is only in the range of the ToF-SIMS spectrometry mode (Fig. 8, Table II). Another disadvantage is the significantly higher ion dose that hits the sample surface. Orbi-SIMS measurements are, therefore, no longer in the static SIMS range. Nevertheless, imaging or spectral Orbi-SIMS measurements are both particularly suitable for the analysis of lipid compositions, e.g., in bone marrow.6,20

FIG. 8.

Comparison of Orbi-SIMS and ToF-SIMS imaging analysis of bone marrow. For ToF-SIMS high-resolution imaging analysis in the delayed extraction mode (ToF-SIMS DE), 30 keV Bi3+ cluster primary ions were used. For OrbiTrap™ imaging analysis, 20 keV Ar3000+ cluster primary ions were applied. In overlay images of both ToF- and Orbi-SIMS measurements, phosphatidylcholine (major component of biological cell membranes) signals are shown in blue and lipid signals are shown in orange. Based on the mass signal of a phosphatidylcholine fragment, C5H14NO+, the significantly improved mass resolution of Orbi-SIMS analysis compared to ToF-SIMS DE analysis can be seen. All used mass signals are listed in Tables S7 and S9 (Ref. 67).

FIG. 8.

Comparison of Orbi-SIMS and ToF-SIMS imaging analysis of bone marrow. For ToF-SIMS high-resolution imaging analysis in the delayed extraction mode (ToF-SIMS DE), 30 keV Bi3+ cluster primary ions were used. For OrbiTrap™ imaging analysis, 20 keV Ar3000+ cluster primary ions were applied. In overlay images of both ToF- and Orbi-SIMS measurements, phosphatidylcholine (major component of biological cell membranes) signals are shown in blue and lipid signals are shown in orange. Based on the mass signal of a phosphatidylcholine fragment, C5H14NO+, the significantly improved mass resolution of Orbi-SIMS analysis compared to ToF-SIMS DE analysis can be seen. All used mass signals are listed in Tables S7 and S9 (Ref. 67).

Close modal
TABLE II.

Measurement parameters of Orbi-SIMS and ToF-SIMS imaging analysis of Fig. 8. Measurements were performed with a M6 Hybrid SIMS (IONTOF GmbH, Münster, Germany). Additional experimental information can be found in the supplementary material (Ref. 67).

Orbi-SIMSDE ToF-SIMS
Primary ion species 20 keV Ar3000+ 30 keV Bi3+ 
Primary ion current 60.00 pA 0.60 pA 
Delay time — 150 ns 
Dose density 3.37 × 1014 ions/cm2 1.27 × 1012 ions/cm2 
Pixels 40 × 40 512 × 512 
Pixel resolution 10 μm 980 nm 
Analysis time 23 min 14 min 
Mass resolution mm (FWHM) 349 897 [at m/z 104.11 (C5H14NO+)] 4551 [at m/z 104.11 (C5H14NO+)] 
Orbi-SIMSDE ToF-SIMS
Primary ion species 20 keV Ar3000+ 30 keV Bi3+ 
Primary ion current 60.00 pA 0.60 pA 
Delay time — 150 ns 
Dose density 3.37 × 1014 ions/cm2 1.27 × 1012 ions/cm2 
Pixels 40 × 40 512 × 512 
Pixel resolution 10 μm 980 nm 
Analysis time 23 min 14 min 
Mass resolution mm (FWHM) 349 897 [at m/z 104.11 (C5H14NO+)] 4551 [at m/z 104.11 (C5H14NO+)] 

4. Data evaluation

The first step of data evaluation is the calibration of the mass spectrum, which contains masses of all molecular and elemental SIs detected during the analysis. As mentioned above, in Orbi-SIMS, calibration is done before the measurements once a day and cannot be adjusted afterward in the recorded datasets. Therefore, if different Orbi-SIMS spectra obtained on different days are to be compared with each other, it is imperative that for each Orbi-SIMS calibration, the same calibration peaks are selected to ensure comparable MS spectra. For ToF-SIMS, every mass spectrum of every measurement must be calibrated manually, either during the measurement or afterward. Generally, several mass peaks should be selected for calculation of the mass scale, and mass accuracy can be improved by selecting peaks from higher mass ranges. Each peak in the mass spectrum is defined by a mass interval (initial and final mass of the peak) and can be added to a peak list used for mass imaging and depth profiling.

Static SIMS analysis provides a large amount of information and enables various types of evaluation procedures. Selection of regions of interest (ROI) within the obtained total ion image, e.g., based on optical structures of interest, gives information about which ionic fragments can be detected in these areas [Fig. 9(a)]. The ROIs act as filters and only mass signals from regions within the ROI are displayed in the corresponding mass spectrum. Thus, for example, chemical composition of areas of mineralized bone and bone marrow can be compared with one another.

FIG. 9.

Basic principles of surface imaging and spectrometry. (a) Regions of interest (ROI) analysis, chosen from the total ion image, allows to study mass spectra in specific areas of the sample surface. (b) Individual SI images are obtained by selecting different ion masses in the mass spectrum. (c) SI images can also be assigned to different colors and merged into an overlay image (here, three SI images in red, green, blue are merged). (Scale bars = 2 mm.) All used mass signals are listed in Table S6 (Ref. 67).

FIG. 9.

Basic principles of surface imaging and spectrometry. (a) Regions of interest (ROI) analysis, chosen from the total ion image, allows to study mass spectra in specific areas of the sample surface. (b) Individual SI images are obtained by selecting different ion masses in the mass spectrum. (c) SI images can also be assigned to different colors and merged into an overlay image (here, three SI images in red, green, blue are merged). (Scale bars = 2 mm.) All used mass signals are listed in Table S6 (Ref. 67).

Close modal

It is also possible to obtain individual ion images, e.g., of calcium, to visualize the mineralized part of the bone, or signals from amino acid fragments to image nonmineralized bone. To do this, individual ions are selected in the mass spectrum of the total area [Fig. 9(b)]. The mass spectrometric information of each detected SI in the mass spectrum is coupled with the position of the mass in the defined analysis region. This capability enables imaging of the spatial distribution of a specific ion on the surface of the sample. Additionally, it allows for the simultaneous visualization of multiple ions' lateral distribution within a single image. For example, if there is a need to display the distribution of mineralized and nonmineralized bone in one image, ion images of different secondary ions can be chosen and merged into an overlay image. Each ion can be assigned a distinct color for easy differentiation and comprehensive analysis [Fig. 9(c)].

Data evaluation of ToF- or Orbi-SIMS mass spectra is often very complex since masses of all molecular and elementary SIs detected during a measurement are contained in them. For this reason, multivariate statistical analysis (MVSA) methods can be applied to reduce complexity in a data set (Fig. 10). In MVSA methods [e.g, principal component analysis (PCA), maximum autocorrelation factor (MAF), or multivariate curve resolution (MCR)], the relationships between several variables are examined simultaneously by reducing the number of variables, without compromising the essential information. Correlation or dependency structures between variables can be detected in the process. In Fig. 10, the results of applying different multivariate analysis methods [PCA (first row), MAF (second row), MCR (third row)] to evaluate a 2D ToF-SIMS measurement are shown in comparison with a manual evaluation (fourth row).

FIG. 10.

Results of the application of different multivariate analysis methods [PCA (1st row), MAF (2nd row), MCR (3rd row)] for evaluation of a 2D ToF-SIMS measurement. A high-resolution detailed image of the bone section from Fig. 4 in the area of the implanted bone material was examined. Four factors could be distinguished in all multivariate analysis methods. Overlay images for each MVSA method show factor 1 in green, factor 2 in red, factor 3 in blue, and factor 4 in yellow. Comparison of the MVSA results with manually selected signals (4th row) shows that the factors correspond to the lateral distributions of collagen (factor 1), calcium (factor 2), strontium (factor 3), and silicon (factor4) signals. Overlay of the manual analysis show collagen in green, calcium signals in red, strontium signals in blue, and silicon signals in yellow. All used mass signals are listed in Table S6 (Ref. 67).

FIG. 10.

Results of the application of different multivariate analysis methods [PCA (1st row), MAF (2nd row), MCR (3rd row)] for evaluation of a 2D ToF-SIMS measurement. A high-resolution detailed image of the bone section from Fig. 4 in the area of the implanted bone material was examined. Four factors could be distinguished in all multivariate analysis methods. Overlay images for each MVSA method show factor 1 in green, factor 2 in red, factor 3 in blue, and factor 4 in yellow. Comparison of the MVSA results with manually selected signals (4th row) shows that the factors correspond to the lateral distributions of collagen (factor 1), calcium (factor 2), strontium (factor 3), and silicon (factor4) signals. Overlay of the manual analysis show collagen in green, calcium signals in red, strontium signals in blue, and silicon signals in yellow. All used mass signals are listed in Table S6 (Ref. 67).

Close modal
a. Principal component analysis (PCA)

PCA examines the variance in a dataset, highlighting the largest difference. Mathematically, it is a matrix transformation in which the matrix consists of samples (rows: in ToF- and Orbi-SIMS data spectra, data points of a depth profile, or image pixels) and variables (column: peak intensities). Through orthogonal transformation, PCA analysis transforms this matrix of possibly correlated variables into a set of values of linearly uncorrelated variables, the principal components, ordered according to the explained variance in the dataset. PCA can be applied to all types of ToF-SIMS data (spectra, 2D and 3D images, and depth profiles) and helps us to identify the most characteristic peaks that explain the variance. An example of the results of a PCA analysis of a ToF-SIMS 2D image is shown in the first row of Fig. 10.

b. Maximum autocorrelation factor (MAF)

This matrix transformation is very similar to PCA but instead of looking for the variance in the dataset, MAF tries to maximize the autocorrelation between neighboring observations (i.e., pixels or data points). The assumption is that the signal of interest has high autocorrelation while the noise has low autocorrelation. The application of MAF is mainly limited to images (Fig. 10, second row).

c. Multivariate curve resolution (MCR)

The aim of MCR is to reveal and describe the underlying chemistry of samples. For this, MCR tries to resolve spectra of chemical mixtures present in a sample into contributions from the individual components that make up the mixtures. MCR results are similar to SIMS results, making them easier to interpret, and they can be applied to all types of ToF-SIMS data (spectra, 2D and 3D images, and depth profiles). An example of the results of an MCR image analysis is shown in the third row of Fig. 10.

SIMS measurements can only be performed on ex vivo bone samples, and the quality of the measurements depends significantly on sample preparation (e.g., embedding material, sample cutting, and storage). For this reason, comparisons of results with other methods, such as μCT, histomorphometry, DEXA, etc., are necessary. However, if bone samples are prepared for histological staining anyway, SIMS measurements are ideal complements, especially, in the field of investigation of implanted biomaterials.

During surface spectrometry and imaging analysis, besides positively or negatively charged SIs, neutral particles and electrons are also emitted from the sample surface and cause charge build-up on insulators (such as organic samples). This charge build-up on the sample surface can lead to significant signal suppression, which results in severe secondary ion yield reduction. By using an electron source, the sample surface is flooded with low-energetic electrons in a pulsed mode, which ensures the necessary charge equalization.50,51 In addition to using an electron flood gun, the analyzer settings should be adjusted with respect to the sample surface potential on electrical insulators like bone. To further improve charge compensation during 2D analysis, a random scanning raster of the primary ion beam can be selected to avoid charging interferences between adjacent pixels. Charging effects on the same pixel can be minimized by applying less primary ion shots per pixel per scan. Furthermore, a reduction of the primary ion current and/or an increase of the cycle time can improve charge compensation. Finally, the use of gas flooding (e.g., O2 or Ar) towards the sample surface in the main chamber can also be helpful.

During 3D analysis of insulators, not only the primary and secondary ions generate a sample charge-up on the surface but also the sputtering beam, which has a high current density. Since the electron flood gun cannot compensate for this charge, it is necessary to separate analysis and sputtering steps by inserting a pause sequence in between. During this pause, only the electron source is activated. This ensures that sufficient electrons are supplied to the sample surface for charge equalization after each sputtering step. The duration of this pause can be adapted to the respective sample system.

To evaluate the quantification potential of SIMS analyses, we need to look at the basic SIMS equation for SI emission [Eq. (1)],
I s x = I p C x S x γ F ,
(1)
where I s x is the secondary ion current of species x (i.e., measured SI count of x),

I p is the primary ion current,

C x is the fractional concentration of species x,

S x is the sputter ion yield of x,

γ is the ionization efficiency (probability of the detected species x forming ions), and

F is the transmission of the analysis system.

Since the concentration C x of the measured species x is directly proportional to the measured secondary ion count I s x, one could expect that quantification is easily possible.21 However, in SIMS analyses, the so-called matrix effect must be considered. The matrix effect means that the ionization probability of a species depends on and is influenced by its immediate chemical environment (matrix) and states that the ion yield of the same analyte can vary in different chemical environments.21,52 Therefore, although the measured SI signal depends on the concentration of the analyte, the chemical state of its environment also influences the SI count. As a result, quantification of SIMS analyses is not readily possible. One way to carry out quantifications with the knowledge of the existing matrix effect is to use suitable standards with known compositions and a concentration series of the analyte to be examined. The matrix of such standards must be as homogeneous as possible and their composition must be as identical as possible to that of the material in which the concentration of the analyte is to be determined.21 In the case of biological samples, this method is therefore very complex, since compositions of biological samples vary greatly, and it is, therefore, difficult to produce corresponding standards.53 

Mass spectrometric data of biological samples obtained by SIMS analyses are typically very complex. This is due to the ionization process. When the focused beam of high-energy primary ions hits the sample surface, the energy of the primary ions is transferred to the target atoms in and around the sample surface within a collision cascade. At the center of the impact point of the primary ions, the transferred energy is the highest, leading to extensive fragmentation of the molecules and, thus, desorption of small fragments or even elements.50 With increasing distance from the collision impact point, the transferred energy decreases, which also allows emission of larger molecular fragments.21 Overall, the collision cascade results in biomolecules such as lipids or proteins generally forming fragments in the lower mass range (m/z < 300), which are not very specific to the biomolecules of interest. It should also be noted that the SIs detected in the mass spectrum are generally not necessarily present in this form in the sample.5 Rather, the detected SIs are fragments of the compounds present within the sample surface and sometimes only formed during the collision cascade and by associated effects, e.g., material recombination or mixing. However, there is a strong correlation of detected fragments with the chemical composition of the sample, and by combination with other methods, e.g., histological staining, conclusions about the chemical environment can be drawn from the local fragment distributions.5 While metal cluster ion species such as Bix+ primarily enable the analysis of low molecular weight biomolecules such as metabolites, fatty acids, or peptides, using Arx+ clusters as the primary ion species reduces fragmentation of large biomolecules such as proteins, enabling the measurement of high molecular weight ions.1 However, the lateral resolution, which can be achieved with Arx+ clusters as primary ion species, is lower than that of Bix+ cluster species.

ToF- and Orbi-SIMS measurements are performed in a high-vacuum environment, which can be a problem considering highly volatile and semivolatile biomolecules, such as free fatty acids. Application of a cryogenic workflow in both ToF- and Orbi-SIMS enables detection of such biomolecules.6,9,18,54,55 Furthermore, the ionization yield of lipids and biomolecules can be boosted by measuring under cryogenic conditions and ion-beam induced fragmentation can be decreased.9 When performing cryo-SIMS measurements, it is important to avoid frost deposition or ice sublimation of frozen samples.9,56

The potential of ToF-SIMS and Orbi-SIMS as analytical methods in bone research has been demonstrated in many studies in recent years and a brief overview of different studies is given in Table III. The main applications of SIMS analytics reported in bone research include

TABLE III.

Overview of studies using ToF- and/or Orbi-IMS as analytical method in bone research. The studies are sorted according to their year of publication within their fields of application (sample preparation, bone mineral composition, microstructure analysis, drug distribution, implant materials, and lipidomics).

Sample and speciesResearch areaSummaryType of SIMS analysisReference
Rat vertebrae Sample preparation/ bone mineral composition Identification of mineral composition of bone matrix in correlation with immunohistochemical experiments. Evaluation of a new technique for decalcifying undecalcified bone sections after embedding. 2D large area imaging/2D imaging 19  
Human femoral heads Sample preparation Investigation of the applicability of technovit and epoxy as embedding materials for ToF-SIMS analysis. 2D imaging/PCA analysis 37  
Hamster bone Bone mineral composition Identification of high mass hydroxyapatite fragments with ToF-SIMS that reflect the unit cell structure of hydroxyapatite (HAP). Surface spectra 57  
Rat tibia Bone mineral composition Investigation of mineralization process within implant-tissue interface and implant healing of titanium implants in rat tibia using ToF-SIMS. 2D imaging 58  
Rat vertebrae/trabeculae Bone mineral composition Analysis of bone sections with focus on (a) Ca content of mineralized bone tissue and (b) identification of ion fragments characteristic for collagen. 2D large area imaging/2D high resolution imaging/semiquantitative analysis 4  
Rat vertebrae Bone mineral composition Quantitative mapping of calcium distribution in bone cross sections using calcium hydroxyapatite collagen scaffolds as standards. Surface spectra/2D imaging/quantitative analysis 53  
Sheep vertebrae Bone mineral composition/microstructure analysis Analysis of trabecular structure as well as mineral and collagen distribution. 2D large area imaging/2D imaging 17  
Rat femur Microstructure analysis/drug distribution/implant materials Application examples of SIMS in different bone research areas: (a) incorporation/distribution of components released from bone cements (b) identification of biomarkers for newly formed cartilage tissue (c) microstructure analysis of cortical bone. 2D large area imaging/2D high resolution imaging/Orbi-SIMS analysis 5  
Rat femur Drug distribution/Implant materials Analysis of strontium release from different biomaterials. Release of strontium into bone tissue/implant interface region and incorporation of strontium in bone could be demonstrated. Depth profiling/2D large area imaging/2D high resolution imaging/PCA analysis 59  
Rat femur Drug distribution/implant materials Determination of strontium diffusion in trabecular bone. Depth profiling/2D large area imaging/3D imaging 35  
Rat femur Drug distribution/implant materials Determination of strontium diffusion in cortical bone. Quantification of strontium in cortical and trabecular bone. Depth profiling/2D large area imaging/3D imaging/Quantitative analysis 36  
Bovine bone marrow Drug distribution/implant materials Characterization of rapid strontium diffusion in water-containing highly viscous bone marrow. Depth profiling/2D&3D high resolution imaging (cryogenic conditions) 18  
Rat bone marrow Drug distribution/implant materials Analysis of strontium mobility in different areas of bone marrow. Depth profiling/2D large area imaging/2D&3D high resolution imaging/Orbi-SIMS analysis (cryogenic conditions) 6  
Rabbit femur Implant materials Analysis of interfaces between a strontium-containing bone cement with trabecular and cortical bone. 2D imaging 60  
Rabbit tibia Implant materials Chemical mapping of bone-implant interface. 2D large area imaging/2D imaging 61  
Rat femur Implant materials Detection of strontium release from implant materials as well as chemical mapping of calcium and collagen distribution in a fracture defect. 2D large area imaging 32  
Rat tibia Implant materials Study of the effect of implanting MgO paste into tibia bone marrow. Surface spectra 62  
Rat tibia Implant materials Analysis of the influence of MgO implants on bone healing. Surface spectra 2D imaging 63  
Rat tibia Implant materials Use of argon GCIB for analysis of bone-implant interface. Surface spectra/depth profiling 64  
Rat femur Implant materials Investigation of material degradation and bone regeneration upon implantation of calcium/strontium phosphate cement pastes in rat bone defects. OrbiTrap™ analyzer enabled identification of mass signals which could be assigned to proteoglycans. 2D large area imaging/Orbi-SIMS analysis 65  
Human cranial explant Implant materials Investigation of the cell content of macrophages in a human cranial sample. 2D&3D imaging/2D high resolution imaging/PCA analysis 66  
Human bone sections Lipidomics Imaging of lipids in both bone and bone marrow using different MSI techniques. 2D large area imaging/2D high resolution imaging/Orbi-SIMS analysis 20  
Sample and speciesResearch areaSummaryType of SIMS analysisReference
Rat vertebrae Sample preparation/ bone mineral composition Identification of mineral composition of bone matrix in correlation with immunohistochemical experiments. Evaluation of a new technique for decalcifying undecalcified bone sections after embedding. 2D large area imaging/2D imaging 19  
Human femoral heads Sample preparation Investigation of the applicability of technovit and epoxy as embedding materials for ToF-SIMS analysis. 2D imaging/PCA analysis 37  
Hamster bone Bone mineral composition Identification of high mass hydroxyapatite fragments with ToF-SIMS that reflect the unit cell structure of hydroxyapatite (HAP). Surface spectra 57  
Rat tibia Bone mineral composition Investigation of mineralization process within implant-tissue interface and implant healing of titanium implants in rat tibia using ToF-SIMS. 2D imaging 58  
Rat vertebrae/trabeculae Bone mineral composition Analysis of bone sections with focus on (a) Ca content of mineralized bone tissue and (b) identification of ion fragments characteristic for collagen. 2D large area imaging/2D high resolution imaging/semiquantitative analysis 4  
Rat vertebrae Bone mineral composition Quantitative mapping of calcium distribution in bone cross sections using calcium hydroxyapatite collagen scaffolds as standards. Surface spectra/2D imaging/quantitative analysis 53  
Sheep vertebrae Bone mineral composition/microstructure analysis Analysis of trabecular structure as well as mineral and collagen distribution. 2D large area imaging/2D imaging 17  
Rat femur Microstructure analysis/drug distribution/implant materials Application examples of SIMS in different bone research areas: (a) incorporation/distribution of components released from bone cements (b) identification of biomarkers for newly formed cartilage tissue (c) microstructure analysis of cortical bone. 2D large area imaging/2D high resolution imaging/Orbi-SIMS analysis 5  
Rat femur Drug distribution/Implant materials Analysis of strontium release from different biomaterials. Release of strontium into bone tissue/implant interface region and incorporation of strontium in bone could be demonstrated. Depth profiling/2D large area imaging/2D high resolution imaging/PCA analysis 59  
Rat femur Drug distribution/implant materials Determination of strontium diffusion in trabecular bone. Depth profiling/2D large area imaging/3D imaging 35  
Rat femur Drug distribution/implant materials Determination of strontium diffusion in cortical bone. Quantification of strontium in cortical and trabecular bone. Depth profiling/2D large area imaging/3D imaging/Quantitative analysis 36  
Bovine bone marrow Drug distribution/implant materials Characterization of rapid strontium diffusion in water-containing highly viscous bone marrow. Depth profiling/2D&3D high resolution imaging (cryogenic conditions) 18  
Rat bone marrow Drug distribution/implant materials Analysis of strontium mobility in different areas of bone marrow. Depth profiling/2D large area imaging/2D&3D high resolution imaging/Orbi-SIMS analysis (cryogenic conditions) 6  
Rabbit femur Implant materials Analysis of interfaces between a strontium-containing bone cement with trabecular and cortical bone. 2D imaging 60  
Rabbit tibia Implant materials Chemical mapping of bone-implant interface. 2D large area imaging/2D imaging 61  
Rat femur Implant materials Detection of strontium release from implant materials as well as chemical mapping of calcium and collagen distribution in a fracture defect. 2D large area imaging 32  
Rat tibia Implant materials Study of the effect of implanting MgO paste into tibia bone marrow. Surface spectra 62  
Rat tibia Implant materials Analysis of the influence of MgO implants on bone healing. Surface spectra 2D imaging 63  
Rat tibia Implant materials Use of argon GCIB for analysis of bone-implant interface. Surface spectra/depth profiling 64  
Rat femur Implant materials Investigation of material degradation and bone regeneration upon implantation of calcium/strontium phosphate cement pastes in rat bone defects. OrbiTrap™ analyzer enabled identification of mass signals which could be assigned to proteoglycans. 2D large area imaging/Orbi-SIMS analysis 65  
Human cranial explant Implant materials Investigation of the cell content of macrophages in a human cranial sample. 2D&3D imaging/2D high resolution imaging/PCA analysis 66  
Human bone sections Lipidomics Imaging of lipids in both bone and bone marrow using different MSI techniques. 2D large area imaging/2D high resolution imaging/Orbi-SIMS analysis 20  

ToF-SIMS is ideally suited for evaluating different bone embedding methods and sample preparation routines. This is an important aspect in bone research, as optimal sample preparation should also allow SIMS analyses to be combined with other techniques such as transmission electron microscopy (TEM), histomorphometry, or histology.

Knowledge of bone mineral status and bone microstructure is an important aspect of bone research, especially regarding bone diseases such as osteoporosis, which affects bone mineral status. ToF-SIMS can be used to image mineralized bone tissue at high resolution and can help to determine the mineral status of, for example, osteoporotic animal models.

Biomaterials play a particularly important role in the research on novel implants for systemically damaged bones. Healing-promoting as well as antibacterial substances are often added to these implants, which are released in the bone defect and are intended to promote bone healing. Detection of the drug distribution of these substances is essential for the evaluation of the newly developed implants, and this is exactly what ToF- and Orbi-SIMS analyses make possible.

The primary objective of this Tutorial is to highlight the significance of ToF-SIMS and Orbi-SIMS as important analytical methods for bone research. The Tutorial aims to demonstrate best practices for SIMS analyses, highlight the advantages, challenges, and technical features of these MSI methods. It covers sample preparation procedures, selection of measurement settings for different types of SIMS analysis of bone, and examples of data evaluation. By offering a brief overview of how to prepare bone samples for ToF- or Orbi-SIMS analysis and showcasing the range of possible analyses, this Tutorial serves as a valuable resource for researchers in this field.

Simultaneous acquisition of all chemical information from the sample surface by SIMS analysis allows visualization of the distribution of both organic and inorganic materials in 2D, by combination with a sputter gun also in 3D. This enables analysis of mineralized bone, nonmineralized bone, bone marrow, and implanted biomaterials, as well as bone-implant interfaces within one measurement, thus making ToF- and Orbi-SIMS particularly attractive for use in bone research. In addition, release of healing-promoting as well as antibacterial substances from implant materials and incorporation of these substances into bone can be studied. This is not possible with conventional histological techniques and demonstrates that ToF- and Orbi-SIMS are important, but so far not standardized, analytical techniques for bone research.

SIMS offers an additional advantage over histological and immunohistochemical staining techniques, which are limited in number and combination of available stains. Unlike these techniques, which can only visualize specific structures in bone tissue individually, ToF- and Orbi-SIMS allow for the simultaneous analysis of multiple structures in an untargeted analytical approach in the form of a comprehensive online analysis. This also allows the performance of retrospective analyses. Furthermore, high resolution and high mass accuracy achievable with Orbi-SIMS analyses enable unambiguous peak identification. This provides a new level of SIMS information on biological samples, which is particularly interesting in terms of searching for and identification of new biomarkers.

This work was funded by the German Research Foundation (DFG, Collaborative Research Centre Transregio 79). The authors gratefully acknowledge the financial support within this project. M.R. thanks the DFG for funding the Hybrid-SIMS (M6 Hybrid SIMS, IONTOF GmbH, Muenster, Germany) under Grant No. INST 162/544-1 FUGG.

The authors have no conflicts to disclose.

The study for ToF-SIMS images of vertebrae and trabecular bone from Fig. 1 was conducted in strict accordance with the European Union legislation for the protection of animals used for scientific purposes and approved by the districts Animal Ethics Committee “government presidium of Darmstadt, Germany; permit no. Gen. Nr. F31/36.” Animal experiments for ToF- and Orbi-SIMS images from Figs. 1, 3, 4, 5, 7, 8, 9, and 10 were approved by and in full compliance with the institutional and German protection laws and the local animal welfare committee [Reference No.: V 54-19 c 20-15 (1) GI 20/28 No. 108/2011].

Christine Kern: Conceptualization (equal); Data curation (equal); Formal analysis (equal); Investigation (equal); Visualization (lead); Writing – original draft (lead). Stefanie Kern: Data curation (equal); Investigation (equal); Writing – original draft (equal). Anja Henss: Data curation (equal); Investigation (equal); Writing – review & editing (supporting). Marcus Rohnke: Conceptualization (lead); Funding acquisition (lead); Project administration (lead); Resources (equal); Supervision (lead); Writing – review & editing (supporting).

The data that support the findings of this study are available from the corresponding author upon reasonable request.

1.
S.
Yoon
and
T. G.
Lee
,
Nano Convergence
5
,
24
(
2018
).
2.
L. J.
Gamble
,
D. J.
Graham
,
B.
Bluestein
,
N. P.
Whitehead
,
D.
Hockenbery
,
F.
Morrish
, and
P.
Porter
,
Biointerphases
10
,
019008
(
2015
).
3.
P.
Malmberg
and
H.
Nygren
,
Proteomics
8
,
3755
(
2008
).
4.
A.
Henss
,
M.
Rohnke
,
T.
El Khassawna
,
P.
Govindarajan
,
G.
Schlewitz
,
C.
Heiss
, and
J.
Janek
,
J. R. Soc. Interface
10
,
20130332
(
2013
).
5.
C.
Kern
,
S.
Ray
,
M.
Gelinsky
,
A. T.
Bellew
,
A.
Pirkl
, and
M.
Rohnke
,
Biointerphases
15
,
031005
(
2020
).
6.
C.
Kern
,
R.
Jamous
,
T.
El Khassawna
, and
M.
Rohnke
,
Analyst
147
,
4141
(
2022
).
7.
M. K.
Passarelli
et al,
Nat. Methods
14
,
1175
(
2017
).
8.
A. M.
Kotowska
,
G. F.
Trindade
,
P. M.
Mendes
,
P. M.
Williams
,
J. W.
Aylott
,
A. G.
Shard
,
M. R.
Alexander
, and
D. J.
Scurr
,
Nat. Commun.
11
,
5832
(
2020
).
9.
C. L.
Newell
,
J.-L.
Vorng
,
J. I.
MacRae
,
I. S.
Gilmore
, and
A. P.
Gould
,
Angew. Chem. Int. Ed.
59
,
18194
(
2020
).
10.
M. J.
Glimcher
,
Anatom. Record
224
,
139
(
1989
).
11.
B.
Clarke
,
Clin. J. Am. Soc. Nephrol.
3
,
S131
(
2008
).
12.
M. D.
McKee
and
W. G.
Cole
, “Bone matrix and mineralization,” in
Pediatric Bone
, 2nd ed., edited by F. H. Glorieux, J. M. Pettifor,
H.
Jüppner
(Academic Press, Boston, MA,
2012
), Chap. 2, pp.
9
37
.
13.
N.
Reznikov
,
R.
Shahar
, and
S.
Weiner
,
Acta Biomater.
10
,
3815
(
2014
).
14.
A. J.
Freemont
,
Int. J. Exp. Pathol.
74
(4),
411
–416 (
1993
).
15.
P. A.
Downey
and
M. I.
Siegel
,
Phys. Therapy
86
,
77
(
2006
).
16.
J. A.
Buckwalter
,
M. J.
Glimcher
,
R. R.
Cooper
, and
R.
Recker
,
J. Bone Joint Surg.
77
,
1256
(
1995
).
17.
R.
Mueller
et al,
J. R. Soc. Interface
16
,
20180793
(
2019
).
18.
C.
Kern
,
A.
Pauli
, and
M.
Rohnke
,
Rapid Commun. Mass Spectrometry
36
,
e9300
(
2022
).
19.
T.
El Khassawna
et al,
Biomed Res. Int.
2017
,
1
(
2017
).
21.
S.
Fearn
,
An Introduction to Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) and its Application to Materials Science
(
Morgan & Claypool, IOP Concise Physics
, San Rafael, CA,
2015
).
22.
A. M.
Haag
,
Adv. Experimental Med. Biol.
919
,
157
(
2016
).
23.
B.
Schueler
,
P.
Sander
, and
D. A.
Reed
,
Vacuum
41
,
1661
(
1990
).
24.
B. W.
Schueler
,
Microsc. Microanal. Microstruct.
3
,
119
(
1992
).
25.
G. L.
Fisher
,
A. L.
Bruinen
,
N.
Ogrinc Potočnik
,
J. S.
Hammond
,
S. R.
Bryan
,
P. E.
Larson
, and
R. M. A.
Heeren
,
Anal. Chem.
88
,
6433
(
2016
).
26.
J. P.
Savaryn
,
T. K.
Toby
, and
N. L.
Kelleher
,
Proteomics
16
,
2435
(
2016
).
27.
R. A.
Zubarev
and
A.
Makarov
,
Anal. Chem.
85
,
5288
(
2013
).
28.
29.
J.
Meurs
,
D. J.
Scurr
,
A.
Lourdusamy
,
L. C. D.
Storer
,
R. G.
Grundy
,
M. R.
Alexander
,
R.
Rahman
, and
D.-H.
Kim
,
Anal. Chem.
93
,
6947
(
2021
).
30.
J. S.
Fletcher
and
J. C.
Vickerman
,
Anal. Chem.
85
,
610
(
2013
).
33.
K.
Schaepe
,
J.
Kokesch-Himmelreich
,
M.
Rohnke
,
A.-S.
Wagner
,
T.
Schaaf
,
S.
Wenisch
, and
J.
Janek
,
Biointerphases
10
,
019016
(
2015
).
34.
K.
Schaepe
,
J.
Werner
,
K.
Glenske
,
T.
Bartges
,
A.
Henss
,
M.
Rohnke
,
S.
Wenisch
, and
J.
Janek
,
Anal. Bioanal. Chem.
409
,
4425
(
2017
).
35.
M.
Rohnke
et al,
J. Controll. Release
262
,
159
(
2017
).
36.
C.
Kern
,
M.
Quade
,
S.
Ray
,
J.
Thomas
,
M.
Schumacher
,
T.
Gemming
,
M.
Gelinsky
,
V.
Alt
, and
M.
Rohnke
,
J. R. Soc. Interface
16
,
20180638
(
2019
).
37.
A.
Henss
,
A.
Hild
,
M.
Rohnke
,
S.
Wenisch
, and
J.
Janek
,
Biointerphases
11
,
02a302
(
2016
).
38.
R.
Buijs
and
A. A.
Dogterom
,
Stain Technol.
58
,
135
(
1983
).
39.
T.
Kawamoto
and
K.
Kawamoto
,
Methods Mol. Biol.
1130
,
149
(
2014
).
40.
P.
Ticha
,
I.
Pilawski
,
X.
Yuan
,
J.
Pan
,
U. S.
Tulu
,
B. R.
Coyac
,
W.
Hoffmann
, and
J. A.
Helms
,
Sci. Rep.
10
,
19510
(
2020
).
41.
G. H.
Kenner
,
L.
Henricks
,
G.
Gimenez
,
W.
Barb
, and
J. B.
Park
,
Stain Technol.
57
,
121
(
1982
).
42.
E.
Willbold
and
F.
Witte
,
Acta Biomater.
6
,
4447
(
2010
).
43.
M.
Maglio
,
F.
Salamanna
,
S.
Brogini
,
V.
Borsari
,
S.
Pagani
,
N.
Nicoli Aldini
,
G.
Giavaresi
, and
M.
Fini
,
BioMed Res. Int.
2020
,
1
(
2020
).
44.
D. J.
Graham
and
L. J.
Gamble
,
Biointerphases
18
, 021201 (
2023
).
45.
S. H.
Kim
,
J.
Kim
,
Y. J.
Lee
,
T. G.
Lee
, and
S.
Yoon
,
J. Am. Soc. Mass Spectrometry
28
,
1729
(
2017
).
46.
E. M.
Weaver
and
A. B.
Hummon
,
Adv. Drug Delivery Rev.
65
,
1039
(
2013
).
48.
Q. P.
Vanbellingen
,
N.
Elie
,
M. J.
Eller
,
S.
Della-Negra
,
D.
Touboul
, and
A.
Brunelle
,
Rapid Commun. Mass Spectrometry
29
,
1187
(
2015
).
49.
A.
Henss
,
S.-K.
Otto
,
K.
Schaepe
,
L.
Pauksch
,
K. S.
Lips
, and
M.
Rohnke
,
Biointerphases
13
,
03B410
(
2018
).
50.
V.
Mazel
and
P.
Richardin
, “
ToF-SIMS study of organic materials in cultural heritage: Identification and chemical imaging
,” in Organic Mass Spectrometry in Art and Archaeology, edited by M. P. Colombinni and F. Modugo (John Wiley & Sons, Chichester, 2009).
51.
T. J.
Barnes
,
I. M.
Kempson
, and
C. A.
Prestidge
,
Int. J. Pharmaceut.
417
,
61
(
2011
).
52.
J. C.
Vickerman
, Surface Analysis—The Principal Techniques (John Wiley & Sons, Chichester, 2009), pp. 113–205.
55.
A.
Akbari
,
A.
Galstyan
,
R. E.
Peterson
,
H. F.
Arlinghaus
, and
B. J.
Tyler
,
Anal. Bioanal. Chem.
415
,
991
(
2023
).
56.
D.
Aoki
,
Y.
Matsushita
, and
K.
Fukushima
,
Holzforschung
76
,
145
(
2022
).
57.
P.
Malmberg
,
U.
Bexell
,
C.
Eriksson
,
H.
Nygren
, and
K.
Richter
,
Rapid Commun. Mass Spectrom.
21
,
745
(
2007
).
58.
C.
Eriksson
,
P.
Malmberg
, and
H.
Nygren
,
Rapid Commun. Mass Spectrom.
22
,
943
(
2008
).
59.
M.
Rohnke
,
A.
Henss
,
J.
Kokesch-Himmelreich
,
M.
Schumacher
,
S.
Ray
,
V.
Alt
,
M.
Gelinsky
, and
J.
Janek
,
Anal. Bioanal. Chem.
405
,
8769
(
2013
).
60.
G. X.
Ni
,
W. W.
Lu
,
B.
Xu
,
K. Y.
Chiu
,
C.
Yang
,
Z. Y.
Li
,
W. M.
Lam
, and
K. D. K.
Luk
,
Biomaterials
27
,
5127
(
2006
).
61.
A.
Palmquist
,
L.
Emanuelsson
, and
P.
Sjövall
,
Appl. Surf. Sci.
258
,
6485
(
2012
).
62.
H.
Nygren
,
M.
Chaudhry
,
S.
Gustafsson
,
G.
Kjeller
,
P.
Malmberg
, and
K.-E.
Johansson
,
J. Funct. Biomater.
5
,
158
(
2014
).
63.
H.
Nygren
,
N.
Bigdeli
,
L.
Ilver
, and
P.
Malmberg
,
Biointerphases
12
,
02C407
(
2017
).
64.
P.
Malmberg
,
N.
Bigdeli
,
J.
Jensen
, and
H.
Nygren
,
Biointerphases
12
,
041002
(
2017
).
66.
P.
Malmberg
,
V. R.
Lopes
,
G. H.
Billström
,
S.
Gallinetti
,
C.
Illies
,
L. K. B.
Linder
, and
U.
Birgersson
,
ACS Appl. Bio Mater.
4
,
6791
(
2021
).
67.
See supplementary material online for detailed descriptions of ToF- and Orbi-SIMS analyses, mass lists for mineralized bone, nonmineralized bone, strontium and silicon signals shown in this paper..
Published open access through an agreement withTechnische Informationsbibliothek

Supplementary Material