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The volume estimation of retroperitoneal sarcoma (RPS) is often difficult due to its huge dimensions and irregular shape; thus, it often requires manual segmentation, which is time-consuming and operator-dependent. This study aimed to evaluate two fully automated deep learning networks (ENet and ERFNet) for RPS segmentation. This retrospective study included 20 patients with RPS who received an abdominal computed tomography (CT) examination. Forty-nine CT examinations, with a total of 72 lesions, were included. Manual segmentation was performed by two radiologists in consensus, and automatic segmentation was performed using ENet and ERFNet. Significant differences between manual and automatic segmentation were tested using the analysis of variance (ANOVA). A set of performance indicators for the shape comparison (namely sensitivity), positive predictive value (PPV), dice similarity coefficient (DSC), volume overlap error (VOE), and volumetric differences (VD) were calculated. There were no significant differences found between the RPS volumes obtained using manual segmentation and ENet (p-value = 0.935), manual segmentation and ERFNet (p-value = 0.544), or ENet and ERFNet (p-value = 0.119). The sensitivity, PPV, DSC, VOE, and VD for ENet and ERFNet were 91.54% and 72.21%, 89.85% and 87.00%, 90.52% and 74.85%, 16.87% and 36.85%, and 2.11% and −14.80%, respectively. By using a dedicated GPU, ENet took around 15 s for segmentation versus 13 s for ERFNet. In the case of CPU, ENet took around 2 min versus 1 min for ERFNet. The manual approach required approximately one hour per segmentation. In conclusion, fully automatic deep learning networks are reliable methods for RPS volume assessment. ENet performs better than ERFNet for automatic segmentation, though it requires more time.

We analyzed the clinical and pathological features of renal cell carcinoma (RCC) patients treated with cabozantinib stratified by body mass index (BMI). We retrospectively collected data from 16 worldwide centers involved in the treatment of RCC. Overall survival (OS) and progression-free survival (PFS) were analyzed using Kaplan&ndash, Meier curves. Cox proportional models were used at univariate and multivariate analyses. We collected data from 224 patients with advanced RCC receiving cabozantinib as second- (113, 5%) or third-line (111, 5%) therapy. The median PFS was significantly higher in patients with BMI &ge, 25 (9.9 vs. 7.6 months, p &lt, 0.001). The median OS was higher in the BMI &ge, 25 subgroup (30.7 vs. 11.0 months, p = 0.003). As third-line therapy, both median PFS (9.2 months vs. 3.9 months, p = 0.029) and OS (39.4 months vs. 11.5 months, p = 0.039) were longer in patients with BMI &ge, 25. BMI was a significant predictor for both PFS and OS at multivariate analysis. We showed that a BMI &ge, 25 correlates with longer survival in patients receiving cabozantinib. BMI can be easily assessed and should be included in current prognostic criteria for advanced RCC.

Simple Summary Many bilateral breast cancer patients with increased hereditary susceptibility to breast cancer result negative for BRCA1 or BRCA2 pathogenic variants and, thus, need a further genetic testing through a broader gene panel. Some patients with negative test result for BRCA1/2 pathogenic variants may harbor pathogenic variants in other breast cancer susceptibility genes, including ATM, CHEK2, PALB2, PTEN, TP53. Of course, the use of a multi-gene panel provides clinicians more information through a single test. Therefore, we focused on potential clinical impact of a NGS-based multi-gene panel testing in bilateral breast cancer patients, in order to evaluate the utility of perform a most comprehensive genetic analysis in these subjects, regardless the criteria concerning personal and family history of cancer established by the current guidelines. Our study revealed that the use of a NGS-based multiple-gene panel testing could increase the detection rates of germline alterations in bilateral breast cancer patients. Abstract Patients with unilateral breast cancer (UBC) have an increased risk of developing bilateral breast cancer (BBC). The annual risk of contralateral BC is about 0.5%, but increases by up to 3% in BRCA1 or BRCA2 pathogenic variant (PV) carriers. Our study was aimed to evaluate whether all BBC patients should be offered multi-gene panel testing, regardless their cancer family history and age at diagnosis. We retrospectively collected all clinical information of 139 BBC patients genetically tested for germline PVs in different cancer susceptibility genes by NGS-based multi-gene panel testing. Our investigation revealed that 52 (37.4%) out of 139 BBC patients harbored germline PVs in high- and intermediate-penetrance breast cancer (BC) susceptibility genes including BRCA1, BRCA2, PTEN, PALB2, CHEK2, ATM, RAD51C. Nineteen out of 53 positively tested patients harbored a PV in a known BC susceptibility gene (no-BRCA). Interestingly, in the absence of an analysis performed via multi-gene panel, a significant proportion (14.4%) of PVs would have been lost. Therefore, offering a NGS-based multi-gene panel testing to all BBC patients may significantly increase the detection rates of germline PVs in other cancer susceptibility genes beyond BRCA1/2, avoiding underestimation of the number of individuals affected by a hereditary tumor syndrome.

The desmoid tumor is a locally aggressive proliferative disease within the family of soft-tissue sarcomas. Despite its relatively good prognosis, the clinical management of desmoid tumors requires constant multidisciplinary evaluation due to its highly variable clinical behavior. Recently, active surveillance has being regarded as the appropriate strategy at diagnosis, as indolent persistence or spontaneous regressions are not uncommon. Here, we review the most recent advances in desmoid tumor therapy, including low-dose chemotherapy and treatment with tyrosine kinase inhibitors. We also explore the recent improvements in our knowledge of the molecular biology of this disease, which are leading to clinical trials with targeted agents.