Despite the controversial role of radiotherapy (RT) in recurrent ovarian cancer (ROC), there might be a survival benefit irrespective of favorable clinical features according to a preliminary analysis. This prospective study was designed to compare the survival outcomes between standard of care (SOC) with or without stereotactic ablative RT (SABR) to all recurrent sites in ROC.
Methods
Patients with recurrent epithelial ovarian cancer with 10 or less metastatic sites at recurrence based on the number of SABR fields are eligible. Those who have a history of RT, single lesion sized >5 cm, or diffuse peritoneal carcinomatosis are not eligible. Patients will be stratified by factors as the followings; number of favorable factors (absence of ascites, platinum-sensitivity, CA-125, and ECOG performance), location of the lesion (lymph node vs. non-lymph node), and use of PARP inhibitor. Patients will be randomized (1:2) into SOC salvage treatment (arm 1) vs. SOC plus metastasis-directed SABR (arm 2). The primary endpoint is 3-year overall survival rate (58.5% for arm 1 and 74.4% for arm 2). A total of 270 patients will be required.
Current Trial Status
A dummy-run study involving 4 representative clinical scenarios is under progress. To enhance compliance with the protocols, a three-tiered RT quality assurance (QA) process consisting of general credentialing, trial-specific credentialing with dummy run plus phantom QA, and individual case review has been performed. Currently, 32 patients from 16 sites are enrolled as of August 21st, 2023.
Although DCN-based super-resolution (DCN-SR) techniques have shown impressive performance, the working mechanism has not been completely understood and DCN-SR methods still produce some artefacts. In this paper, we analyze the working mechanisms of DCN-SR methods. We derive mathematical formulations of the DCN-SR methods and provide some experimental analyses, which show that the effective receptive fields of the DCN-SR methods are considerably smaller than the theoretical receptive fields. Based on the mathematical formulations, experiments were performed. The results indicates that current DCN-SR methods may have some fundamental problems and new types of DCN structures are needed for reliable super-resolution performance.
Objective: To investigate the role of radiotherapy (RT) in patients who underwent hysterectomy for uterine carcinosarcoma (UCS).Methods: Patients with the International Federation of Gynecology and Obstetrics stage I-IVa UCS who were treated between 1990 and 2012 were identified retrospectively in a multiinstitutional database.Of 235 identified patients, 97 (41.3%) received adjuvant RT.Twentytwo patients with a history of previous pelvic RT were analyzed separately.Survival outcomes were assessed using the Kaplan-Meier method and Cox proportional hazards model.Results: Patients with a previous history of pelvic RT had poor survival outcomes, and 72.6% of these patients experienced locoregional recurrence; however, none received RT after a diagnosis of UCS.Univariate analyses revealed that pelvic lymphadenectomy (PLND) and para-aortic lymph node sampling were significant factors for locoregional recurrence-free survival (LRRFS) and disease-free survival (DFS).Among patients without previous pelvic RT, the percentage of locoregional failure was lower for those who received adjuvant RT than for those who did not (28.5% vs. 17.5%, p=0.107).Multivariate analysis revealed significant correlations between PLND and LRRFS, distant metastasis-free survival, and DFS.In subgroup analyses, RT significantly improved the 5-year LRRFS rate of patients who did not undergo PLND (52.7% vs. 18.7% for non-RT, p<0.001).
We report a case of aggressive ‘nasal type’ natural killer (NK)/T cell lymphoma initially presenting as a testicular tumor in a Korean man, which quickly took a fatal course by widespread dissemination. Histologically, the testicular mass showed a diffuse dense infiltrate of medium-sized and atypical large lymphoid cells with angiocentric and angiodestructive infiltration and areas of coagulative necrosis on hematoxylin-eosin stained sections. Immunophenotyping by immunohistochemistry yielded surface markers consistent with NK/T cell lymphoma. The Epstein-Barr virus genome was detected by in situ hybridization. During involved-field irradiation and chemotherapy following radical orchiectomy, the tumor disseminated shortly to the skin and soft tissue of his anterior chest wall and central nervous system (CNS). Identical lymphoid infiltrates were present in the patient’s skin. CNS involvement was interpreted as having a leptomeningeal seeding. To the best of our knowledge, this is the 9th reported case of confirmed NK/T cell lymphoma arising from the testis. Relevant literature is reviewed, and the clinicopathologic features, natural history, and treatment options for primary testicular NK/T cell lymphoma are discussed.
Deep learning-based models have been actively investigated for various aspects of radiotherapy. However, for cervical cancer, only a few studies dealing with the auto-segmentation of organs-at-risk (OARs) and clinical target volumes (CTVs) exist. This study aimed to train a deep learning-based auto-segmentation model for OAR/CTVs for patients with cervical cancer undergoing radiotherapy and to evaluate the model's feasibility and efficacy with not only geometric indices but also comprehensive clinical evaluation.A total of 180 abdominopelvic computed tomography images were included (training set, 165; validation set, 15). Geometric indices such as the Dice similarity coefficient (DSC) and the 95% Hausdorff distance (HD) were analyzed. A Turing test was performed and physicians from other institutions were asked to delineate contours with and without using auto-segmented contours to assess inter-physician heterogeneity and contouring time.The correlation between the manual and auto-segmented contours was acceptable for the anorectum, bladder, spinal cord, cauda equina, right and left femoral heads, bowel bag, uterocervix, liver, and left and right kidneys (DSC greater than 0.80). The stomach and duodenum showed DSCs of 0.67 and 0.73, respectively. CTVs showed DSCs between 0.75 and 0.80. Turing test results were favorable for most OARs and CTVs. No auto-segmented contours had large, obvious errors. The median overall satisfaction score of the participating physicians was 7 out of 10. Auto-segmentation reduced heterogeneity and shortened contouring time by 30 min among radiation oncologists from different institutions. Most participants favored the auto-contouring system.The proposed deep learning-based auto-segmentation model may be an efficient tool for patients with cervical cancer undergoing radiotherapy. Although the current model may not completely replace humans, it can serve as a useful and efficient tool in real-world clinics.
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