Characterization of bony anatomic regions in pediatric and adult healthy volunteers using diffuse optical spectroscopic imaging.

SIGNIFICANCE:Diffuse optical spectroscopic imaging (DOSI) measures quantitative functional and molecular information in thick tissue in a noninvasive manner using near-infrared light. DOSI may be useful for diagnosis and prognosis of bone pathologies including osteosarcoma and Ewing's sarcoma, but little is currently known about DOSI-derived parameters in bony anatomic locations where this disease occurs. AIM:Our goal is to quantify the optical characteristics and chromophore content of bony anatomic locations of healthy volunteers and assess differences due to anatomic region, age, sex, ethnicity, race, and body fat. APPROACH:Fifty-five healthy volunteers aged 4 to 72 were enrolled in the study. The optical properties and quantitative tissue concentrations of oxyhemoglobin, deoxyhemoglobin, water, and lipids were assessed at the distal humerus, distal femur, and proximal tibia. Body fat was assessed using skinfold calipers. One volunteer underwent a more comprehensive body scan from neck to foot to explore chromophore distributions within an individual. Regression analysis was used to identify the most important sources of variation in the measured data set. RESULTS:Statistical differences between bony locations were found for scattering, water, and lipids, but not for hemoglobin. All chromophores had statistical differences with sex, but there were no significant age-related correlations. Regression analysis revealed that body fat measured with skinfold calipers was the most important predictor of oxy-, deoxy-, total hemoglobin, and lipids. Hemoglobin and lipid levels were highly correlated (ρ  ≥  0.7) over the subject population and within the single-subject body scan. CONCLUSIONS:DOSI can successfully measure bony anatomic sites where osteosarcomas and Ewing's sarcomas commonly occur. Future studies of bone pathology using DOSI should account for the variation caused by anatomic region, sex, race and ethnicity, and body fat as these cause substantial variations in DOSI-derived metrics.