Purpose Surgical workflow recognition and context-aware systems could allow better decision making and surgical planning by providing the focused information, which may eventually enhance surgical outcomes. While current developments in computer-assisted surgical systems are mostly focused on recognizing surgical phases, they lack recognition of surgical workflow sequence and other contextual element, e.g., "Instruments." Our study proposes a hybrid approach, i.e., using deep learning and knowledge representation, to facilitate recognition of the surgical workflow. Methods We implemented "Deep-Onto" network, which is an ensemble of deep learning models and knowledge management tools, ontology and production rules. As a prototypical scenario, we chose robot-assisted partial nephrectomy (RAPN). We annotated RAPN videos with surgical entities, e.g., "Step" and so forth. We performed different experiments, including the inter-subject variability, to recognize surgical steps. The corresponding subsequent steps along with other surgical contexts, i.e., "Actions," "Phase" and "Instruments," were also recognized. Results The system was able to recognize 10 RAPN steps with the prevalence-weighted macro-average (PWMA) recall of 0.83, PWMA precision of 0.74, PWMA F1 score of 0.76, and the accuracy of 74.29% on 9 videos of RAPN. Conclusion We found that the combined use of deep learning and knowledge representation techniques is a promising approach for the multi-level recognition of RAPN surgical workflow.

The SARS-CoV-2 vaccine roll-out has been successful around the world. However, there are increasing concerns about adverse events. We report two pediatric cases of Multisystem-Inflammatory-Syndrome (MIS-C) with neurological involvement that occurred after SARS-CoV-2 vaccination and unknown recent SARS-CoV-2 infection. Brain magnetic resonance revealed mild-encephalopathy with reversible-splenial-lesion in both cases and complete resolution within 4 weeks. In conclusion, this report aims to describe rare emerging clinical entities that can help pediatricians to make an early diagnosis and to provide appropriate treatment. Multisystem-Inflammatory-Syndromes following COVID-19 vaccination remain rare events. When a history of a recent contact with SARS-CoV-2 is present, a careful evaluation by the clinicians in charge of immunization activities is suggested prior to proceeding with the vaccination.

Background: We compared multimodality treatment (MMT, defined as robot-assisted radical prostatectomy (RARP) with androgen deprivation therapy (ADT), with or without adjuvant radiotherapy (RT)) vs. ADT alone in oligometastatic prostate cancer (OPC) patients. Methods: From 2010 to 2018, we identified 74 patients affected by cM1a-b OPC (≤5 metastases). Kaplan–Meier (KM) plots depicted cancer-specific mortality (CSM), disease progression, metastatic castration-resistant PC (mCRPC), and time to second-line systemic therapy rates. Multivariable Cox regression models (MCRMs) focused on disease progression and mCRPC. Results: Forty (54.0%) MMT and thirty-four (46.0%) ADT patients were identified. On KM plots, higher CSM (5.9 vs. 37.1%; p = 0.02), mCRPC (24.0 vs. 62.5%; p < 0.01), and second-line systemic therapy (33.3 vs. 62.5%; p < 0.01) rates were recorded in the ADT group. No statistically significant difference was recorded for disease progression. ForMCRMs adjusted for the metastatic site and PSA, a higher mCRPC rate was recorded in the ADT group. No statistically significant difference was recorded for disease progression. Treatment-related adverse events occurred in 5 (12.5%) MMT vs. 15 (44.1%) ADT patients (p < 0.01). Conclusions: MMT was associated with lower CSM, mCRPC, and second-line therapy rates. A lower rate of treatment-related adverse events was recorded for the MMT group.