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Simple Summary: A chest CT via central vein enhancement not only eliminates peripheral vein regurgitation but also provides better image quality that facilitates precise clinical staging. A chest CT via central vein enhancement may be considered after tissue proof in order to better discriminate disease severity. The differences in chest computed tomography (CT) image quality may affect the tumor stage. The aim of this study was to compare the image quality and accuracy of chest CT via central vein and peripheral vein enhancement. Fifty consecutive patients were enrolled from a tertiary medical center in Taiwan from May 2016 to March 2019. All the patients received a chest CT via central vein enhancement prior to neoadjuvant concurrent chemoradiation in order to compare the chest CT that was obtained via the peripheral vein. In addition, blind independent central reviews of chest CT via central vein and peripheral vein enhancement were conducted. For T and N stage, chest CT via central vein enhancement had a greater consistency with endoscopic ultrasonography and positron-emission tomography-computed tomography findings (kappa coefficients 0.4471 and 0.5564, respectively). In addition, chest CT via central vein enhancement also showed excellent agreement in the blind independent central review (kappa coefficient 0.9157). The changes in the T and N stage resulted in stage migration in 16 patients. Chest CT via central vein enhancement eliminated peripheral vein regurgitation and also provided more precise clinical staging. This study is registered under the registered NCT number 02887261. [ABSTRACT FROM AUTHOR]

Simple Summary: Molecular target therapy, i.e., antiangiogenesis with bevacizumab, was found to be effective in some patients of epithelial ovarian cancer. Considering the cost, potential adverse effects, including hypertension, proteinuria, bleeding, thromboembolic events, poor wound healing and gastrointestinal perforation, and no confirmed and accessible biomarkers for routine clinical use to direct patient selection for bevacizumab treatment, the identification of new predictive methods remains an urgent unmet medical need. This study identifies an effective biomarker and presents an automatic weakly supervised deep learning framework for patient selection and guiding ovarian cancer treatment. Ovarian cancer is a common malignant gynecological disease. Molecular target therapy, i.e., antiangiogenesis with bevacizumab, was found to be effective in some patients of epithelial ovarian cancer (EOC). Although careful patient selection is essential, there are currently no biomarkers available for routine therapeutic usage. To the authors' best knowledge, this is the first automated precision oncology framework to effectively identify and select EOC and peritoneal serous papillary carcinoma (PSPC) patients with positive therapeutic effect. From March 2013 to January 2021, we have a database, containing four kinds of immunohistochemical tissue samples, including AIM2, c3, C5 and NLRP3, from patients diagnosed with EOC and PSPC and treated with bevacizumab in a hospital-based retrospective study. We developed a hybrid deep learning framework and weakly supervised deep learning models for each potential biomarker, and the experimental results show that the proposed model in combination with AIM2 achieves high accuracy 0.92, recall 0.97, F-measure 0.93 and AUC 0.97 for the first experiment (66% training and 34%testing) and high accuracy 0.86 ± 0.07, precision 0.9 ± 0.07, recall 0.85 ± 0.06, F-measure 0.87 ± 0.06 and AUC 0.91 ± 0.05 for the second experiment using five-fold cross validation, respectively. Both Kaplan-Meier PFS analysis and Cox proportional hazards model analysis further confirmed that the proposed AIM2-DL model is able to distinguish patients gaining positive therapeutic effects with low cancer recurrence from patients with disease progression after treatment (p < 0.005). [ABSTRACT FROM AUTHOR]

This study investigated the clinical outcome of locally advanced cervical esophageal squamous cell carcinoma (ESCC) patients who received curative concurrent chemoradiotherapy (CCRT) and their differences from thoracic ESCC patients. Among 411 enrolled ESCC patients, including 63 with cervical and 348 with thoracic ESCC, 63 thoracic patients were propensity score-matched to the 63 cervical patients. For cervical ESCC, T4b and high tumor grade were independent prognostic factors of a worse overall survival (OS) in univariate and multivariate analyses. The response rates to curative CCRT between cervical and the matched thoracic ESCC groups were similar but cervical ESCC had a better OS than that of the matched thoracic group (21.4 versus 10.1 months, p = 0.012). Better OS was mentioned to be in the patients with complete response (CR), whether in the cervical or matched thoracic ESCC group. For patients without CR, patients who underwent esophagectomy had superior OS than those without operation in the matched thoracic ESCC group (11.6 versus 11.9 months, p = 0.73). Only three patients received operation in the cervical ESCC group, thus the survival difference was not significant. Curative CCRT may be a reasonable treatment for cervical ESCC in clinical practice, and the role of surgery should be considered as salvage therapy if residual disease is evident. [ABSTRACT FROM AUTHOR]