UNLABELLED: Active bone marrow is one of the more radiosensitive tissues in the human body and, hence, it is important to predict and possibly avoid myelotoxicity in radionuclide therapies. The MIRD schema currently used to calculate marrow dose generally requires knowledge of the patient's total skeletal active marrow mass -- a value that, at present, cannot be directly measured. Conceptually, the active marrow mass in a given skeletal region may be obtained given knowledge of the trabecular spongiosa volume (SV) of the bone site. A recent study has established a multiple regression model to easily calculate total skeletal SV (or TSSV) based on simple skeletal measurements obtained from a pelvic CT scan or radiograph. This model, based on data from only 20 cadavers, did not account for sex differences in TSSV. This study thus extends this work toward sex-specific models. METHODS: Twenty male and 20 female cadavers were subjected to whole-body CT. Bone sites containing active bone marrow were manually segmented to obtain SV at each site. In addition to age and height, 14 CT-based skeletal measurements were recorded for each cadaver. Multiple linear regression techniques were used to determine the best subset of measurements that allowed an accurate prediction of TSSV. RESULTS: A pooled model (R(2) = 0.76) and a sex-specific model (R(2) = 0.79) are provided. A leave-one-out analysis reveals that these models predict total SV with less than 10% error for 50%-70% of subjects, and with less than 20% error for 70%-90% of subjects. Tables were constructed that provide the percent distribution of SV in active-marrow containing bone sites for both males and females. CONCLUSION: This study provides models that can be used to simply, yet accurately, predict total SV in individuals within the clinical setting. The models require only 2 or 3 skeletal measurements that can be easily measured on a pelvic CT scan. Even though this study does not conclusively determine which model is best at predicting TSSV, the sex-specific model is most consistent at providing reasonable estimates of TSSV. This study also explains how the predictive TSSV model can be used to estimate patient-specific active bone marrow mass under the assumption of reference values of marrow volume fraction and bone marrow cellularity by skeletal site.
UNLABELLED: Active bone marrow is one of the more radiosensitive tissues in the human body and, hence, it is important to predict and possibly avoid myelotoxicity in radionuclide therapies. The MIRD schema currently used to calculate marrow dose generally requires knowledge of the patient's total skeletal active marrow mass -- a value that, at present, cannot be directly measured. Conceptually, the active marrow mass in a given skeletal region may be obtained given knowledge of the trabecular spongiosa volume (SV) of the bone site. A recent study has established a multiple regression model to easily calculate total skeletal SV (or TSSV) based on simple skeletal measurements obtained from a pelvic CT scan or radiograph. This model, based on data from only 20 cadavers, did not account for sex differences in TSSV. This study thus extends this work toward sex-specific models. METHODS: Twenty male and 20 female cadavers were subjected to whole-body CT. Bone sites containing active bone marrow were manually segmented to obtain SV at each site. In addition to age and height, 14 CT-based skeletal measurements were recorded for each cadaver. Multiple linear regression techniques were used to determine the best subset of measurements that allowed an accurate prediction of TSSV. RESULTS: A pooled model (R(2) = 0.76) and a sex-specific model (R(2) = 0.79) are provided. A leave-one-out analysis reveals that these models predict total SV with less than 10% error for 50%-70% of subjects, and with less than 20% error for 70%-90% of subjects. Tables were constructed that provide the percent distribution of SV in active-marrow containing bone sites for both males and females. CONCLUSION: This study provides models that can be used to simply, yet accurately, predict total SV in individuals within the clinical setting. The models require only 2 or 3 skeletal measurements that can be easily measured on a pelvic CT scan. Even though this study does not conclusively determine which model is best at predicting TSSV, the sex-specific model is most consistent at providing reasonable estimates of TSSV. This study also explains how the predictive TSSV model can be used to estimate patient-specific active bone marrow mass under the assumption of reference values of marrow volume fraction and bone marrow cellularity by skeletal site.
Authors: Steve Y Cho; Kenneth L Gage; Ronnie C Mease; Srinivasan Senthamizhchelvan; Daniel P Holt; Akimosa Jeffrey-Kwanisai; Christopher J Endres; Robert F Dannals; George Sgouros; Martin Lodge; Mario A Eisenberger; Ronald Rodriguez; Michael A Carducci; Camilo Rojas; Barbara S Slusher; Alan P Kozikowski; Martin G Pomper Journal: J Nucl Med Date: 2012-12 Impact factor: 10.057
Authors: Erica L Scheller; William P Cawthorn; Aaron A Burr; Mark C Horowitz; Ormond A MacDougald Journal: Trends Endocrinol Metab Date: 2016-04-16 Impact factor: 12.015