Object: The aim of this study was to examine tumor volume as a prognostic factor for patients with brain metastases treated with Gamma Knife surgery (GKS). Methods: Two hundred fifty patients with 1–14 brain metastases who had initially undergone GKS alone at a single institution were retrospectively reviewed. Patients who received upfront whole brain radiation therapy were excluded. Survival times were estimated using the Kaplan-Meier method. Univariate and multivariate analyses using Cox proportional hazard regression models were used to determine if various prognostic factors could predict overall survival, distant brain failure, and local control. Results: Median overall survival was 7.1 months and the 1-year local control rate was 91.5%. Median time to distant brain failure was 8.0 months. On univariate analysis an increasing total tumor volume was significantly associated with worse survival (p = 0.031) whereas the number of brain metastases, analyzed as a continuous variable, was not (p = 0.082). After adjusting for age, Karnofsky Performance Scale score, and extracranial disease on multivariate analysis, total tumor volume was found to be a better predictor of overall survival (p = 0.046) than number of brain metastases analyzed as a continuous variable (p = 0.098). A total tumor volume cutoff value of ≥ 2 cm³ (p = 0.008) was a stronger predictor of overall survival than the number of brain metastases (p = 0.098). Larger tumor volume and extracranial disease, but not the number of brain metastases, were predictive of distant brain failure on multivariate analysis. Local tumor control at 1 year was 97% for lesions < 2 cm³ compared with 75% for lesions ≥ 2 cm³ (p < 0.001). Conclusions: After adjusting for other factors, a total brain metastasis volume was a strong and independent predictor for overall survival, distant brain failure, and local control, even when considering the number of metastases.

BACKGROUND: Radiotherapy is the current standard of care for patients with localized squamous cell cancer of the anal canal. The goal of the current study was to evaluate long‐term quality of life (QoL) in patients after this treatment.METHODS: Questionnaires were mailed to 80 patients treated with definitive radiotherapy, with or without concurrent chemotherapy, for anal cancer, with a minimum 2‐year interval after the completion of radiotherapy. The questionnaire included the Functional Assessment of Cancer Therapy‐Colorectal (FACT‐C), the Medical Outcomes Study (MOS) Sexual Problems Scale, and questions regarding demographic characteristics and comorbidities.RESULTS: A total of 32 (40%) patients completed the questionnaire. There were no significant differences noted with regard to clinical and demographic characteristics between the survey responders and nonresponders. Among the 32 responders, the median dose of radiotherapy was 55 Grays (Gy), and 97% had received concurrent chemotherapy. The median interval between radiotherapy and survey participation was 5 years (range, 3‐13 years). The median total FACT‐C score was 108 (range, 47‐128), of a maximum (best possible) score of 136. Patients who reported depression or anxiety and younger patients were found to have significantly lower total FACT‐C scores. The median scores on the Physical, Social/Family, Emotional, Functional, and Colorectal subscales of the FACT‐C were 20, 23, 21, 22, and 21, respectively, of maximum (best possible) scores of 28, 28, 24, 28, and 28, respectively. The median score on the MOS Sexual Problems Scale was 67 (range, 0‐100), of a maximum (worst possible) score of 100.CONCLUSIONS: Patients treated with radiotherapy for anal cancer reported acceptable overall QoL scores, but poor sexual function scores. Investigations are warranted into more modern radiation techniques that could potentially reduce late toxicity from radiotherapy. Cancer 2010. © 2010 American Cancer Society.

Purpose: To develop and evaluate the feasibility of deep learning approaches for MR‐based treatment planning (deepMTP) in brain tumor radiation therapy.Methods and materials: A treatment planning pipeline was constructed using a deep learning approach to generate continuously valued pseudo CT images from MR images. A deep convolutional neural network was designed to identify tissue features in volumetric head MR images training with co‐registered kVCT images. A set of 40 retrospective 3D T1‐weighted head images was utilized to train the model, and evaluated in 10 clinical cases with brain metastases by comparing treatment plans using deep learning generated pseudo CT and using an acquired planning kVCT. Paired‐sample Wilcoxon signed rank sum tests were used for statistical analysis to compare dosimetric parameters of plans made with pseudo CT images generated from deepMTP to those made with kVCT‐based clinical treatment plan (CTTP).Results: deepMTP provides an accurate pseudo CT with Dice coefficients for air: 0.95 ± 0.01, soft tissue: 0.94 ± 0.02, and bone: 0.85 ± 0.02 and a mean absolute error of 75 ± 23 HU compared with acquired kVCTs. The absolute percentage differences of dosimetric parameters between deepMTP and CTTP was 0.24% ± 0.46% for planning target volume (PTV) volume, 1.39% ± 1.31% for maximum dose and 0.27% ± 0.79% for the PTV receiving 95% of the prescribed dose (V95). Furthermore, no significant difference was found for PTV volume (P = 0.50), the maximum dose (P = 0.83) and V95 (P = 0.19) between deepMTP and CTTP.Conclusions: We have developed an automated approach (deepMTP) that allows generation of a continuously valued pseudo CT from a single high‐resolution 3D MR image and evaluated it in partial brain tumor treatment planning. The deepMTP provided dose distribution with no significant difference relative to a kVCT‐based standard volumetric modulated arc therapy plans.

Vorinostat (suberoylanilide hydroxamic acid), a histone deacetylase inhibitor, is currently undergoing clinical evaluation as therapy for cancer. We investigated the effects of vorinostat on tumor cell radiosensitivity in a breast cancer brain metastasis model using MDA-MB-231-BR cells. In vitro radiosensitivity was evaluated using clonogenic assay. Cell cycle distribution and apoptosis was measured using flow cytometry. DNA damage and repair was evaluated using γH2AX. Mitotic catastrophe was measured by immunostaining. Growth delay and intracranial xenograft models were used to evaluate the in vivo tumor radiosensitivity. Cells exposed to vorinostat for 16 hours before and maintained in the medium after irradiation had an increase in radiosensitivity with a dose enhancement factor of 1.57. γH2AX, as an indicator of double-strand breaks, had significantly more foci per cell in the vorinostat plus irradiation group. Mitotic catastrophe, measured at 72 hours, was significantly increased in cells receiving vorinostat plus irradiation. Irradiation of s.c. MDA-MB-231-BR tumors in mice treated with vorinostat resulted in an increase in radiation-induced tumor growth delay. Most importantly, animals with intracranial tumor implants lived the longest after combination treatment. These results indicate that vorinostat enhances tumor cell radiosensitivity in vitro and in vivo. There was a greater than additive improvement in survival in our intracranial model. Combining vorinostat with radiation may be a potential treatment option for patients with breast cancer who develop brain metastases. [Mol Cancer Ther 2009;8(6):1589–95]