Objective: To evaluate prospective associations between elevations in body mass index (BMI) at average age 27 and generalized anxiety disorder (GAD) and major depressive disorder (MDD) at average age 59 in a community sample of women. Design: Three waves of data collected over three decades were drawn from mothers in the Children in the Community (CIC) Study. Binary logistic regression was used to estimate predictive effects of two BMI cutpoints (X30 and X25) on GAD and MDD independent of other risks for psychopathology. Measurements: Information about height and weight was obtained by self-report in face-to-face interviews. GAD and MDD were assessed by structured interview covering DSM-IV diagnostic criteria. Other potential risk factors examined included age, race, education, prior depressive symptoms and marital status, chronic disease, social support and financial strain concurrent with GAD and MDD. Results: A baseline BMI X30 significantly increased the odds for subsequent GAD and MDD by 6.27 and 5.25 times, respectively, after adjusting for other significant risk factors. Odds of GAD also increased significantly given a baseline BMI X25 (by 2.44 times); however this association was not independent of other significant risk factors. Predictive associations between a baseline BMI X30 and MDD were not attenuated by attained BMI assessed at outcome. Conclusion: Findings extend existing evidence of the mental health consequences of obesity in a representative sample of mothers, and suggest that obesity may have long-term implications for mental distress in women at a clinical level over the adult years.

Purpose: Simplifications and reductions in 4D dose accumulation can be achieved using the motion probability density function (PDF) with properly selected weighting and sampling. One scheme to select phase sampling and weighting scheme is to use k‐means clustering from motion PDF. In this study, we investigated the accuracy and feasibility of this method for 4D dose construction. Method and Materials: Respiration curves from 6 patients and 15 static dose profiles were used in the evaluation. Motion PDFs were constructed from respiration curves for dose convolution and phase sampling. Four sampling schemes were compared: (1) Equal phase sampling; (2) Equal amplitude sampling; (3) K‐means clustering based sampling; (4) PDF and dose profile specific optimal sampling. The cumulative 4D dose from different methods were compared to the expected 4D dose. A digital motion phantom was constructed with dose computed at various displacements for 3D dose evaluation on the above methods. Mid phase dose profile through isocenter was used for optimization in method 4. Results: For dose profiles analysis, the residual errors (normalized to the maximum dose) for the method 1 to 4 are: 1.9+1.4%, 2.2±0.59%, 0.88±0.70%, and 0.55%±0.48%. For phantom study, the maximum residual errors are 7.8%, 3.6%, 2.9%, and 3.5%. The 3D gamma analysis passing rates are (dose difference 2%, distance to agreement 2mm, and dose threshold 30% of maximum dose): 96.1%, 99.6%, 99.7%, and 99.6%. Conclusion: K‐means clustering sampling is effective in 4D dose accumulation. Method 4 will be most accurate sampling method for single dose profile analysis, with all the information included for optimization. K‐means sampling has slightly larger residual error in dose profile approximation, but it applies to multiple dose profiles for a given PDF. In 3D dose analysis, k‐means sampling is the most effective and accurate among the four methods.

Purpose: To quantify the spatial distortion of the MRI images in the Elekta Leksell GammaPlan version 9 planning system using different registration methods. Methods: The RPC SRS phantom was imaged using a GE Signa HDxt 1.5Tesla MR scanner and a GE LightSpeed VCT CT scanner. Both the T1 weighted MRI images and the fast imaging employing steady state acquisition (FIESTA) MRI images were acquired, along with the axial and helical CT images. The skull shell and the target in the phantom were contoured in all the four series of images acquired. The MRI images were registered in the planning system in three different ways: 1) using the fiduciary marks in the imaging box; 2) using a global co‐registration with FOV just covering skull shell; 3) using a local co‐registration to max 8.5cm FOV at image center. The target positions in all the four series of images were compared using the software tool in the planning system. Results: The target positions as obtained from the helical and the axial CT images agree within 0.1mm. For the registration method the fiduciary marks, the T1 weighted MRI images are shifted from the CT images 0.9mm in the anterior‐posterior direction, and 0.5mm in both the superior‐inferior and the left‐right directions. The corresponding displacements for the FIESTA images are 0.6mm, 0.5mm and 0.5mm respectively. The shifts of the target positions are significantly reduced in the global co‐registration approach, and all less than 0.2mm in the local co‐registration approach. Conclusions: MRI image distortion in GammaPlan version 9 is in the sub‐millimeter range for the central region of the MRI image. The spatial distortion in the FIESTA images is smaller than that in the T1 weighted images. Co‐registration to the central region of images can reduce MRI imaging distortion effect significantly.