We have designed an environmentally-controlled chamber for near infrared spectroscopic imaging (NIRSI) to monitor changes in cortical bone water content, an emerging biomarker related to bone quality assessment. The chamber is required to ensure repeatable spectroscopic measurements of tissues without the influence of atmospheric moisture. A calibration curve to predict gravimetric water content from human cadaveric cortical bone was created using NIRSI data obtained at six different lyophilization time points. Partial least squares (PLS) models successfully predicted bone water content that ranged from 0–10% (R = 0.96, p < 0.05, root mean square error of prediction (RMSEP) = 7.39%), as well as in the physiologic range of 4–10% of wet tissue weight (R = 0.87, p < 0.05, RMSEP = 14.5%). Similar results were obtained with univariate and bivariate regression models for prediction of water in the 0–10% range. Further, we identified two new NIR bone absorbances, at 6560 cm⁻¹ and 6688 cm⁻¹, associated with water and collagen respectively. Such data will be useful in pre-clinical studies that investigate changes in bone quality with disease, aging and with therapeutic use.

我们设计了一个用于近红外光谱成像（NIRSI）的环境可控腔室，以监视皮质骨含水量的变化，皮质骨含水量是与骨骼质量评估相关的新兴生物标记。需要该腔室以确保组织的可重复光谱测量不受大气湿度的影响。使用在六个不同的冻干时间点获得的NIRSI数据，创建了一条预测曲线，用以预测人体尸体皮质骨的重量水含量。偏最小二乘（PLS）模型成功预测了骨水分含量，范围为0–10％（R = 0.96，p <0.05，预测的均方根误差（RMSEP）= 7.39％），以及湿纸巾重量的4-10％（R = 0.87，p <0.05，RMSEP = 14.5％）。用单变量和双变量回归模型获得的预测水量在0％至10％范围内的结果相似。此外，我们在6560 cm处确定了两个新的NIR骨吸收度^-1和6688 cm ^-1分别与水和胶原蛋白相关。这样的数据将在临床前研究中有用，该研究将研究骨质随疾病，衰老和治疗用途的变化。