Micro Computer Tomography (µCT) is a sophisticated medical imaging device that allows internal structures of the body to be viewed in 3D . The use of µCT has becomea standard in bone tissue research for diseases such as osteoporosis and scanners are now available for in- vivo and in-vitro resear ch. Although µCT has many strengths such as being nondestructive to tissues, no sample preparation necessary, and providing 3D images with good resolution it has some weaknesses. These include exposing samples to ionizing radiation as well as requires long scanning times, making it a slow process.
Therefore, improvements are needed to make µCT scanners faster while still providing good spatial resolution.
Micro Computed Tomography (µCT) is a form of X-ray imaging very similar to CT scans used in hospitals, but on a small er scale with much higher resolution [1]. This procedure represents a 3D microscopy where images of the internal body are taken nondestructively at a very small scale. It works by emitting X -rays from an X -ray generator, the X-rays pass through the sample, and are recorded by a detector on the oth er side of the sample to produce a radiograph.
During X -r ay exposure, the sample rotates as images at different projection at taken. This process is repeated until the sample is rotated 180 to 360 degrees, producing a series of projection images [2]. After the images are taken, they are processed using a computer software to allow the visualization of the internal structur e of the object . CT scans are limited to a resolution of 1 millimeter, which provides sufficient detail for clinical use.
µ -CT scann ers can work at the level of one micron, which is a thousandth of a millimeter, and smaller. This is important because it can be used to study different diseases at a small scale level.
The history of µ CT began in 1917 when the mathematician Johan Radon proved that there was an n- dimension object that can be reconstructed from its (n -1)- dimensional projections [3]. In the second half of the century, the mathematical basis for the actual CT image reconstruction w as presented in two papers by Allan Corm ack in 1964 and 1965 [3]. This led to the invention of the first CT scanner by the British Electrical E ngineer of Electrical and Musical Instruments Laboratories, Godfrey Hounsfield, in 1972. However, this scanner took hours to obtain the raw data and the reconstruction of a single image took days (see Figure 1 for illustration ). Figure 1: Houns field’s CT prototype [3] By 1975, Hounsfield was able to reconstruct the first full -body CT scanner. This invention was so remarkable that in 1979, Cormack and Hounsfield won the Nobel P rize in Physiology or Medicine.
The standard measurement of radio density is called the “Hounsfield scale” and has remained to this day. The images that were created by the first CT scanner s were only of 2D reconstructions as they relied on X -rays and linear array detectors [4] . It was not unti l the 1980s that the Ford Motor Company physicist, Lee Feldkamp, developed the very first µ CT system. He developed it and used it to assess structural defects of ceramic automotive materials [4] . Feldkamp then considered using the 2D detector s well as an X -ray source and rotate the sample 360 degrees to take images at different projections. From every projection, he developed the cone- beam algorithm to fully reconstruct the image in 3D [4]. The technology of µCT was extended to the research field where images of a small snail were reconstructed in the first µCT system with about 50um size.
Feldkamp collaborated with Steven Goldstein, an Orthopaedic B iomechanician at the University of Michigan and they published the first µC T analysis of bone architecture. The first one was an evaluation of subchondral bone in experimental osteoarthritis followed by another publication on the evaluation of the trabecular bone structure in 3D [4] . Nowadays, bone µ CT has become a standard in bone research and scanners ar e available for in-vivo and in- vitro research. This technology has made a great contribution in studying bone tissue such as osteocyte lacunae, intra- bone vasculature, or micro- cracks and micro-fractures. Additionally, “this technique became available on many different levels of resolution, while always using the exact same physical working principle” [3] .
Process of obtaining an image in Modern µCT Scanners The process of obtaining a µ CT image can be described using four main steps (see Figure 2 for a schematic ). The first step is generating the X -rays. The generation of X- rays starts in the x ray source as shown in Figure 3. Electrons from a metal cathode (i.e. tungsten, copper, etc.) are transferred to a positively charged anode. After the electrons are transferred, they lose kinetic energy by a phenomenon called Bremsstrahlung and X-rays are emitted. The high image resolut ion of µCT can be achieved using very fine electron beam to be focused on the target sample, leading to s mal l er spot size. The emission of X -ray s is diverged from a point to X -rays being emitted in the shape of a cone [2] .
This is beneficial because it can capture a larger volume of the sample in a single rotation of the scan. Figure 2: schematic of µCT image production [2] Figure 3 : µCT X -ray source schematic [2] Th e second step is transmitting X -rays through the sample. After X -rays are generated, partial absorption of the photons in the tissues are crucial. This means that the photons must interact with the tissues where some are absorbed and some are transmitted to the detector. The denser the material (i.e. bon e), the more X -ray photons are absorbed by the tissues whereas s ofter tissues are less dense therefore, they absorb less X -rays [2] . Additionally, differential absorption produces contrast which gives contrast in the different tissues, a llowing the person who is examining the image to differentiate between the different tissues and makes it clear er to visualize.
The third step in µ CT image processing is rotating the sample to obtain a series of image projections. depending on the application, either the sample is rotated (ex vivo imaging) or the X -ray source and detector rotate while the sample stays fixed (in vivo imaging). After a project ion image is taken, the sample is rotated approximately 0.5 degrees and another image projection is taken. This process is repeated until a 360 degree rotation is completed. Finally, the projection images are reconstructed to produce virtual slices to allo w for 3D visualization. For example, Figure 4 shows the cross sectional images of snow leopard skull . These cross sections allow the view of the internal features in 3D. Figure 4: Cross sectional images of snow leopard skull [2] .
µCT technology has played a major role in the study of structure and quality of bone for diseases such as osteoporosis and osteoarthritis . The use of µCT allows for analysis of high resolution 3D imaging of microstructural characteristics from trabecular bone arc hitecture to cortical porosity [4] . Factors such as age, gender, or disease have great effect on the microstructural properties of cortical and trabecular bone and these can be evaluated quantitatively by µ CT as shown in Figure 5 ).
Since the technology of µCT is capable of reconstructing microstructural features, it has become a great help with the analysis of finite element (FE) modeling to evaluate biomechanical behavior under complex loading conditions. Non- linear local constitutive models have been used along with µ CT-based FE models to ” predict local plasticity and macroscopic failure of trabecular bone and to relate bone microarchitectural features with appar ent-level mechanical behavior” [4]. Figure 5 : µ CT reconstruction of cortical and trabecular bone. A) trabecular bone from femoral neck of 51 year old male (left) and 84 year old female (right). B) Diaphyseal femoral cortical bone of 18 year old male (left) and 73 year old female (right) [4] . µ CT -based FE modeling has been widely used in evaluation of bone quality, microdamage and failure [5] as well as the effects of mechanical stimuli on bone regeneration [6].
It is also an ideal technology to be used for longitudinal evaluation of disuse and mechanical load- induced bone remodeling and adaptation [4]. A few published studies have used µCT and FE analysis in a mouse tail vertebra model to longitudinally assess the effect of compressiv e loading and unloading on bone formation and resorption as shown in Figure 6 . Bone formation and resorption in the different locations correlated with sites of high and low strain energy density, respectively [7] . Figure 6 : correlation of local tissue strains with regions of bone formation and resorption by longitudinal in vivo µCT and FE analysis. A) serial, co- registered µCT scans were analyzed to determine locations of bone formation and resorption. B) correlated locations of high/low strain energy density (SED) calculated by FE analysis [4].
µ CT technology has changed the world of research and disease diagnosis along with making it possible for research teams to study bone structure and morphology. µ CT is highly sensitive to bone and lung tissue, p rovides high resolution images, and allows for the use of contrast agents to be further enhanced, increasing the resolution of the image [8]. Other strengths of µ CT include not being destructive to target tissues , easy image reconstruction and analysis, as well as allowing for result interpret ation to be in 2D or 3D. I n addition, µ CT is inexpensive compared to other imaging systems which isa great advantage because it can be obtained by research labs a lot easier .
Finally, µCT requires no sample preparation, no need for staining, or slicing compared to other imaging procedures. After the scan is ove r, the sample stays intact [1] . µ CT system is definitely not perfect and has some weaknesses. The biggest weakness is the use of radiation which can be harm ful to animals at high doses. The exposure to radiation can affect the size of tumors and hence alter results [8] . Other weaknesses include the unavailability of stains for some type of tissues and may not be suitable for distinguishing similar types of tissues [8]. Finally, µCT may require long scanning time and can become a slow process along with being labor intensive.
New and improved µ CT scanners are continually being produced to solve the limitations of µCT systems. The SKYSCAN 1276 is a relatively new in vivo µCT used for mouse or rat imaging for res earch applications (see Figure 7). This machine allows for animals to be put under anesthesia and be scanned at different time points to study disease progression. This scanner is different than previous scanners because it has i mpr oved imaging performance and requires shorter scanning time with higher resolution. Addition ally, it has the ability to continually adjust magnification and s how larger fields of view [9].
This is a great advantage because it gives the researcher more flexibility to select the appropriate image resolution, pixel size, and field of view. This mircoCT system also has improved synchronized imaging. This means that image acquisition during breathing and cardiac cycles of the animal where several images per rotation are combined with monitoring information about breathing or heartbeat have better quality and spatial resolution. This device can be used in a variety of healthcare fields. For example, to study diabetes, the capability to obtain a scan of the entire mouse improves the quality of body composition data such as fat fraction and lean tissue volume . In addition, “the high resolutions that are possible and the 2.8- micron pixel size will be very valuable in the bone field, in the study of morphometry of mouse and rat trabecular bone” as seen in Figure 8 [9].
Because one of the weaknesses of µ CT is that it is time consuming and requires the operator to switch between different applications, it makes the entire image generation slow as well as causes user errors. Recently, a research team has introduced automation to make the process of µ CT imaging more efficient and less labor intensive. This project, Xamflow, was in collaboration between five different companies and institutes and was co -funded from the national budgets of 36 partnering states and countries. When automation is introduced into the imaging process, the system would be capable of controlling t he workflow of scanning process. This can be from measurements and reconstructions to image pro duction with statistical analysis and advanced imaging [10] .
Another advantage of this software is that it can handle datasets of up to 100GB very efficiently. This software works by using artificial intelligence to identify the different tissues and struc tures and combines the imaging hardware with the visualization of differe nt image processing techniques [10] . “When you examine and scan humans and animals, one of the most important things is to outline the internal organs and abnormalities like tumors in a process called segmentation,” says Hildebrand, a partner owner for the project [10]. The process of segmentation requires the processing of many scans to tr ain the system to identify the different samples of tissue. This project is continuing to improve its image processing to enable it to identify 3D structures for research and clinical applications .
Future improvements in µCT are important to solve the weaknesses that are still present in the system. This is related to increasing the system’s speed, increasing spatial resolution, and developing new imaging modes. To improve imaging mode, phase contrast µ CT could become a great possibility. This is achieved by having photon absorption and phase shift be measured simultaneously. This technique allows fora high contrast of soft tissue, which allows for clearer visualization and more accurate disease diagnosis. Improving the speed can be achieved with Free- Electron Lasers (FEL). These lasers can provide very “intense ly and tightly focused X -ray beams with pulses as short as 10 femtoseconds (1 femtosecond = 1 quadrillionth of a second, that is approximately the duration of a molecular vibration) and wavelengths down to 0.1nm” [3]. FELs shown in Figure 9 offer the most advanced synchrotron light sources , which is critical for evaluations of small samples in µCT .
µCT scanners have become an important medical imaging tool to for the view of internal tissue structures in 3D specifically in bone tissue research. Although it exposes tissues to ionizing radiation, requires long scanning time, and may become a slow and labor intensive process, it is able to provide 3D images with good spatial res olution and no destruction to tissues. Improvements such as automation or the use of FEL to improve the speed of µCT scanners.
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