Although skeletal muscle (SM) is a major body component, whole body measurement methods remain limited and inadequately investigated. The aim of the present study was to evaluate the Burkinshaw in vivo neutron activation analysis (IVNA)-whole body 40K-counting and dual-energy X-ray absorptiometry (DXA) methods of estimating SM by comparison to adipose tissue-free SM measured using multiscan computerized axial tomography (CT). In the Burkinshaw method the potassium-to-nitrogen ratios of SM and non-SM lean tissue are assumed constant; in the DXA method the ratio of appendicular SM to total SM is assumed constant at 0.75. Seventeen healthy men [77.5 +/- 13.8 (SD) kg body wt] and eight men with acquired immunodeficiency syndrome (AIDS; 65.5 +/- 7.6 kg) completed CT, IVNA, and DXA studies. SM measured by CT was 34.4 +/- 6.2 kg for the healthy subjects and 27.2 +/- 4.0 kg for the AIDS patients. Compared with CT, the Burkinshaw method underestimated SM by an average of 6.9 kg (20.1%, P = 0.0001) and 6.3 kg (23.2%, P = 0.01) in the healthy men and the men with AIDS, respectively. The DXA method minimally overestimated SM in both groups (2.0 kg and 5.8% in healthy men, P = 0.001; 1.4 kg and 5.1% in men with AIDS, P = 0.16). This overestimate could be explained by a higher actual than assumed ratio of DXA-measured appendicular SM to total body SM (actual = 0.79 +/- 0.05, assumed = 0.75). The current study results reveal that large errors are present in the Burkinshaw SM method and that substantial refinements in the models that form the basis of this IVNA approach are needed. The model on which the DXA-SM method is based also needs further minor refinements, but this is a promising in vivo approach because of less radiation exposure and lower cost than the IVNA and CT methods.

One hundred sixty-four healthy black and white women aged 24-79 y were studied to determine to what extent bone mass is determined by fat-free mass (FFM). A multicomponent approach to body composition, with techniques that are not interdependent, was used. The measurements included dual x-ray absorptiometry (DXA), prompt gamma-neutron-activation analysis, inelastic neuron scattering, tritiated water dilution, and whole-body counting. Univariate correlations showed significant relationships of all the fat-free measures and most of the fat measures with bone mass measured by total body calcium (TBCa). Data from pre- and postmenopausal women were analyzed separately. The average FFM by itself explained 50-55% of the variability in TBCa whereas the average fat mass by itself explained only 5-18% of the variability. The contribution of fat mass was consistently greater in postmenopausal than in premenopausal women. When stepwise multiple regression with TBCa was performed to determine the influence of adding fat mass, height, and race to the relationship of FFM with TBCa, the variation explained by average FFM was 56% premenopausal, 50% postmenopausal; by height 3% premenopausal, 6% postmenopausal; by race 4% premenopausal, 8% postmenopausal; and average fat mass was not significant. Average values for fat mass and FFM were obtained by averaging all the methods used. In conclusion, in black and white healthy women, although bone mass may be partially influenced by fatness or race, the major determinant of bone mass is FFM. Fat mass may play a more important role in postmenopausal women.

Purpose To investigate the sources of variability in radiotherapy treatment plan output between planners within a single institution. Materials/Methods 40 treatment planners across 5 campuses of the same institution created a plan on copies of the same thoracic esophagus patient CT and structure set. Plans were scored and ranked based on the planner’s adherence to ordered list of target dose coverage and normal tissue evaluation criteria. A runs test was used to identify whether any of the studied planner qualities influenced the ranking. Spearman’s rank correlation was used to investigate whether plan score correlated with years of experience or planned MU. Results The distribution of scores, ranging from 80.24 to 135.89, was negatively skewed (mean = 128.7, median = 131.5). No statistically significant relationship between plan score and campus (p=0.193), job title (p=0.174), previous outside experience (p=0.611), or number of gantry angles (p=0.156) exists. No statistical correlation between plan score and MU or years of experience was found. Conclusion Despite clear and established critical organ dose criteria and well documented planning guidelines, planning variation still occurs, even among members of the same institution. As plan consistency does not seem to significantly correlate with experience, career path, or campus, investigation into alternate methods beyond additional education and training to reduce this variation, such as knowledge based planning or advanced optimization techniques, is necessary.

Background and Purpose We investigate whether knowledge based planning (KBP) can identify systematic variations in intensity modulated radiotherapy (IMRT) plans between multiple campuses of a single institution. Material and Methods A KBP model was constructed from 58 prior main campus (MC) esophagus IMRT radiotherapy plans and then applied to 172 previous patient plans across MC and 4 regional sites (RS). The KBP model predicts DVH bands for each organ at risk which were compared to the previously planned DVH’s for that patient. Results RS1’s plans were the least similar to the model with less heart and stomach sparing, and more variation in liver dose, compared to MC. RS2 produced plans most similar to those expected from the model. RS3 plans displayed more variability from the model prediction but overall, the DVH’s were no worse than those of MC. RS4 did not present any statistically significant results due to the small sample size (n=11). Conclusions KBP can retrospectively highlight subtle differences in planning practices, even between campuses of the same institution. This information can be used to identify areas needing increased consistency in planning output and subsequently improve consistency and quality of care.