Bone‐composition imaging using coherent‐scatter computed tomography: Assessing bone health beyond bone mineral density

Abstract

Quantitative analysis of bone composition is necessary for the accurate diagnosis and monitoring of metabolic bone diseases. Accurate assessment of the bone mineralization state is the first requirement for a comprehensive analysis. In diagnostic imaging, x-ray coherent scatter depends upon the molecular structure of tissues. Coherent-scatter computed tomography (CSCT) exploits this feature to identify tissue types in composite biological specimens. We have used CSCT to map the distributions of tissues relevant to bone disease (fat, soft tissue, collagen, and mineral) within bone-tissue phantoms and an excised cadaveric bone sample. Using a purpose-built scanner, we have measured hydroxyapatite (bone mineral) concentrations based on coherent-scatter patterns from a series of samples with varying hydroxyapatite content. The measured scatter intensity is proportional to mineral density in true g/cm3. Repeated measurements of the hydroxyapatite concentration in each sample were within, at most, 2% of each other, revealing an excellent precision in determining hydroxyapatite concentration. All measurements were also found to be accurate to within 3% of the known values. Phantoms simulating normal, over-, and under-mineralized bone were created by mixing known masses of pure collagen and hydroxyapatite. An analysis of the composite scatter patterns gave the density of each material. For each composite, the densities were within 2% of the known values. Collagen and hydroxyapatite concentrations were also examined in a bone-mimicking phantom, incorporating other bone constituents (fat, soft tissue). Tomographic maps of the coherent-scatter properties of each specimen were reconstructed, from which material-specific images were generated. Each tissue was clearly distinguished and the collagen-mineral ratio determined from this phantom was also within 2% of the known value. Existing bone analysis techniques cannot determine the collagen-mineral ratio in intact specimens. Finally, to demonstrate the in situ potential of this technique, the mineralization state of an excised normal cadaveric radius was examined. The average collagen-mineral ratio of the cortical bone derived from material-specific images of the radius was 0.53+/-0.04, which is in agreement with the expected value of 0.55 for healthy bones.

Diffuse optical spectroscopy of breast tissue extended to 1100 nm

“…Therefore, we relied on a density value of 1.3 mg/ cm 3 , which was reported for hard tissue. 27 Thus, the low percentage of tissue volume accounted for in our measurements could be due to a wrong estimate of collagen density in breast tissue, and this is the reason why data on tissue composition are presented in Table 1 as absolute values ͑in milligram per cubic centimeter͒ rather than as percentage composition. However, it could also indicate that an appreciable percentage of tissue volume is represented by constituents that do not absorb significantly in the red and near-IR spectral range.…”

An X-ray scatter system for material identification in cluttered objects: A Monte Carlo simulation study

“…In medical applications, several studies [23][24][25][26] have shown that there exist significant differences in the scatter signatures from cancerous and healthy tissue, for example in the blood [2], bone [27] and breast [28]. In addition, studies have shown that scatter imaging can be used to spatially resolve different materials using tomography [29,30] or coded apertures [31].…”

Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE

“…Other potential uses of spectral CT in biomedical imaging include: improved detection of microcalcifications in breast cancer [23,24]; imaging of high Z nanoparticles [22,25,26] potentially bridging the gap between CT and molecular imaging; quantification of materials in tissues such as fat or iron in the liver in the metabolic syndrome [27]; and in vivo imaging of tissue scaffolds [28,29].…”