Brindle James M, Trindade A Alexandre, Shah Amish P, Jokisch Derek W, Patton Phillip W, Pichardo J Carlos, Bolch Wesley E
Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, Florida, USA.
J Nucl Med. 2006 Nov;47(11):1875-83.
The toxicity of red bone marrow is widely considered to be a key factor in restricting the activity administered in molecular radiotherapy to suboptimal levels. The assessment of marrow toxicity requires an assessment of the dose absorbed by red bone marrow which, in many cases, requires knowledge of the total red bone marrow mass in a given patient. Previous studies demonstrated, however, that a close surrogate-spongiosa volume (combined tissues of trabecular bone and marrow)-can be used to accurately scale reference patient red marrow dose estimates and that these dose estimates are predictive of marrow toxicity. Consequently, a predictive model of the total skeletal spongiosa volume (TSSV) would be a clinically useful tool for improving patient specificity in skeletal dosimetry.
In this study, 10 male and 10 female cadavers were subjected to whole-body CT scans. Manual image segmentation was used to estimate the TSSV in all 13 active marrow-containing skeletal sites within the adult skeleton. The age, total body height, and 14 CT-based skeletal measurements were obtained for each cadaver. Multiple regression was used with the dependent variables to develop a model to predict the TSSV.
Os coxae height and width were the 2 skeletal measurements that proved to be the most important parameters for prediction of the TSSV. The multiple R(2) value for the statistical model with these 2 parameters was 0.87. The analysis revealed that these 2 parameters predicted the estimated the TSSV to within approximately +/-10% for 15 of the 20 cadavers and to within approximately +/-20% for all 20 cadavers in this study.
Although the utility of spongiosa volume in estimating patient-specific active marrow mass has been shown, estimation of the TSSV in active marrow-containing skeletal sites via patient-specific image segmentation is not a simple endeavor. However, the alternate approach demonstrated in this study is fairly simple to implement in a clinical setting, as the 2 input measurements (os coxae height and width) can be made with either pelvic CT scanning or skeletal radiography.
红骨髓毒性被广泛认为是将分子放射治疗中给予的活性限制在次优水平的关键因素。骨髓毒性评估需要评估红骨髓吸收的剂量，在许多情况下，这需要了解特定患者的红骨髓总质量。然而，先前的研究表明，一个密切的替代指标——松质骨体积（小梁骨和骨髓的联合组织）——可用于准确缩放参考患者红骨髓剂量估计值，并且这些剂量估计值可预测骨髓毒性。因此，一个预测全身骨骼松质骨体积（TSSV）的模型将是一种临床上有用的工具，可提高骨骼剂量测定中患者特异性。
在本研究中，对10具男性和10具女性尸体进行了全身CT扫描。使用手动图像分割来估计成人骨骼内所有13个含活跃骨髓的骨骼部位的TSSV。获取了每具尸体的年龄、身高和14项基于CT的骨骼测量值。使用多元回归，以因变量建立一个预测TSSV的模型。
髋骨的高度和宽度是被证明对预测TSSV最重要的两个骨骼测量值。包含这两个参数的统计模型的多重R²值为0.87。分析表明，这两个参数预测的TSSV估计值，在本研究中的20具尸体中，有15具在约±10%以内，所有20具尸体在约±20%以内。
虽然已表明松质骨体积在估计患者特异性活跃骨髓质量方面有用，但通过患者特异性图像分割来估计含活跃骨髓的骨骼部位的TSSV并非易事。然而，本研究中展示的替代方法在临床环境中相当容易实施，因为两个输入测量值（髋骨高度和宽度）可以通过骨盆CT扫描或骨骼X线摄影获得。
