OBJECTIVES: The direct acoustic cochlear implant (DACI) is among the latest developments in the field of implantable acoustic prostheses. The surgical procedure requires a mastoidectomy and a posterior-inferior tympanotomy, with access to the facial recess at the level of the oval window, in a complex and lengthy surgical approach. Here, we report a new and considerably shorter surgical approach. METHODS: The new approach involves positioning of artificial incus above the oval window through the superior-anterior tympanotomy. We performed DACI placement in temporal bone specimens (n=5) to assess the feasibility of the new approach. RESULTS: The average time for the DACI implant in the temporal bones was only 112 minutes (range, 94 to 142 minutes) and there was little clinical risk associated with the procedure. Access was easy and drilling was minimal. CONCLUSION: Our approach simplified the surgical procedure and consequently reduced the time required for DACI placement.
Acoustics* ; Cochlear Implants* ; Incus ; Prostheses and Implants ; Temporal Bone*

Purpose: To explore the role of artificial intelligence and machine learning (ML) techniques in oncological urology. In recent years, our group investigated the prostate cancer gene 3 (PCA3) score, prostate-specific antigen (PSA), and free-PSA predictive role for prostate cancer (PCa), using the classical binary logistic regression (LR) modeling. In this research, we approached the same clinical problem by several different ML algorithms, to evaluate their performances and feasibility in a real-world evidence PCa detection trial. Materials and Methods: The occurrence of a positive biopsy has been studied in a large cohort of 1,246 Italian men undergoing first or repeat biopsy. Seven supervised ML algorithms were selected to build biomarkers-based predictive models: generalized linear model, gradient boosting machine, eXtreme gradient boosting machine (XGBoost), distributed random forest/ extremely randomized forest, multilayer artificial Deep Neural Network, naïve Bayes classifier, and an automatic ML ensemble function. Results: All the ML models showed better performances in terms of area under curve (AUC) and accuracy, when compared to LR model. Among them, an XGBoost model tuned by the autoML function reached the best metrics (AUC, 0.830), well overtaking LR results (AUC, 0.738). In the variable importance ranking coming from this XGBoost model (accuracy, 0.824), the PCA3 score importance was 3-fold and 4-fold larger, when compared to that of free-PSA and PSA, respectively. Conclusions The ML approach proved to be feasible and able to achieve good predictive performances with reproducible results: it may thus be recommended, when applied to PCa prediction based on biomarkers fluctuations.

Purpose: To explore the role of artificial intelligence and machine learning (ML) techniques in oncological urology. In recent years, our group investigated the prostate cancer gene 3 (PCA3) score, prostate-specific antigen (PSA), and free-PSA predictive role for prostate cancer (PCa), using the classical binary logistic regression (LR) modeling. In this research, we approached the same clinical problem by several different ML algorithms, to evaluate their performances and feasibility in a real-world evidence PCa detection trial. Materials and Methods: The occurrence of a positive biopsy has been studied in a large cohort of 1,246 Italian men undergoing first or repeat biopsy. Seven supervised ML algorithms were selected to build biomarkers-based predictive models: generalized linear model, gradient boosting machine, eXtreme gradient boosting machine (XGBoost), distributed random forest/ extremely randomized forest, multilayer artificial Deep Neural Network, naïve Bayes classifier, and an automatic ML ensemble function. Results: All the ML models showed better performances in terms of area under curve (AUC) and accuracy, when compared to LR model. Among them, an XGBoost model tuned by the autoML function reached the best metrics (AUC, 0.830), well overtaking LR results (AUC, 0.738). In the variable importance ranking coming from this XGBoost model (accuracy, 0.824), the PCA3 score importance was 3-fold and 4-fold larger, when compared to that of free-PSA and PSA, respectively. Conclusions The ML approach proved to be feasible and able to achieve good predictive performances with reproducible results: it may thus be recommended, when applied to PCa prediction based on biomarkers fluctuations.

PURPOSE: The purpose of this study was to study the clinical outcome for patients with metastases of the adrenal gland treated with stereotactic body radiation therapy. MATERIALS AND METHODS: Forty-six patients were studied retrospectively. The dose prescription was 40 Gy in four fractions. Dosimetric analysis was performed using the dose volume histograms while clinical outcome was assessed using actuarial analysis with determination of the overall survival (OS) and local control (LC) rates. RESULTS: The planning objectives were met for all patients. With a median follow-up period of 7.6 months, at the last follow-up 42 patients (91.3%) were alive and four had died because of distant progression. The actuarial mean OS was 28.5±1.6 months, the median was not reached. One-year and 2-year OS were 87.6±6.1%. None of the risk factors was significant in univariate analysis. Actuarial mean LC was 14.6±1.8 months (95% confidence interval [CI], 11.0 to 18.2) and median LC was 14.5±2.0 months (95% CI, 10.5 to 18.5). One-year and 2-year LC were 65.5±11.9% and 40.7±15.8%, respectively. A mild profile of toxicity was observed in the cohort of patients. Forty patients (86.9%) showed no complication (grade 0); two patients reported asthenia, six patients (13.1%) reported either pain, nausea, or vomiting. Of these six patients, five patients (10.9%) were scored as grade 1 toxicity while one patient (2.2%) was scored as grade 2. CONCLUSION: Stereotactic body radiation therapy treatment provided an adequate clinical response in the management of adrenal gland metastases.
Actuarial Analysis ; Adrenal Glands ; Asthenia ; Cohort Studies ; Follow-Up Studies ; Humans ; Nausea ; Neoplasm Metastasis* ; Prescriptions ; Radiosurgery ; Radiotherapy, Intensity-Modulated ; Retrospective Studies ; Risk Factors ; Vomiting

OBJECTIVE: Cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) have been recently reported with favorable oncological outcomes as treatment of advanced epithelial ovarian cancer (EOC). The aim of this study was to demonstrate the feasibility of CRS+HIPEC with cisplatin and paclitaxel for the treatment of advanced EOC. METHODS: This is a prospective observational study of 54 patients, from April 2007 to October 2013, with primary or recurrent peritoneal carcinomatosis due to EOC. The mean age was 54.51+/-9.34. Thirty patients (59%) had primary EOC, and 24 patients (41%) had recurrent disease. RESULTS: Mean peritoneal cancer index was 10.11 (range, 0 to 28), complete cytoreduction (CC0) was achieved for 47 patients (87%), CC1 for seven patients (13%). Patients with suboptimal cytoreduction (CC2 and CC3) were not included in the study. The mean stay in intensive care unit was 4.73+/-5.51 days and the mean hospitalization time was 24.0+/-10.03 days. We did not observe any intraoperative death. Seven patients (13%) required additional operations. Three patients (5.6%) died within 30 days from the procedure. Severe complications were seen in 19 patients (35.2%). During the follow-up period, disease recurred in 33 patients (61.1%); the median disease-free survival time was 12.46 months and the median overall survival time was 32.91 months. CONCLUSION: CRS+HIPEC with cisplatin and paclitaxel for advanced EOC is feasible with acceptable morbidity and mortality. Additional follow-up and further studies are needed to determine the effects of HIPEC on long term survival.
Adult ; Antineoplastic Combined Chemotherapy Protocols/administration & dosage/adverse effects/*therapeutic use ; Cisplatin/administration & dosage/adverse effects ; Combined Modality Therapy ; Cytoreduction Surgical Procedures/adverse effects/methods ; Feasibility Studies ; Female ; Humans ; Hyperthermia, Induced/adverse effects/*methods ; Infusions, Parenteral ; Kaplan-Meier Estimate ; Middle Aged ; Neoplasm Recurrence, Local/drug therapy/surgery ; Ovarian Neoplasms/*drug therapy/surgery ; Paclitaxel/administration & dosage/adverse effects ; Prospective Studies ; Treatment Outcome

Objective: Coronavirus disease 2019 (COVID-19) outbreak has correlated with the disruption of screening activities and diagnostic assessments. Endometrial cancer (EC) is one of the most common gynecological malignancies and it is often detected at an early stage, because it frequently produces symptoms. Here, we aim to investigate the impact of COVID-19 outbreak on patterns of presentation and treatment of EC patients. Methods: This is a retrospective study involving 54 centers in Italy. We evaluated patterns of presentation and treatment of EC patients before (period 1: March 1, 2019 to February 29, 2020) and during (period 2: April 1, 2020 to March 31, 2021) the COVID-19 outbreak. Results: Medical records of 5,164 EC patients have been retrieved: 2,718 and 2,446 women treated in period 1 and period 2, respectively. Surgery was the mainstay of treatment in both periods (p=0.356). Nodal assessment was omitted in 689 (27.3%) and 484 (21.2%) patients treated in period 1 and 2, respectively (p<0.001). While, the prevalence of patients undergoing sentinel node mapping (with or without backup lymphadenectomy) has increased during the COVID-19 pandemic (46.7% in period 1 vs. 52.8% in period 2; p<0.001). Overall, 1,280 (50.4%) and 1,021 (44.7%) patients had no adjuvant therapy in period 1 and 2, respectively (p<0.001). Adjuvant therapy use has increased during COVID-19 pandemic (p<0.001). Conclusion Our data suggest that the COVID-19 pandemic had a significant impact on the characteristics and patterns of care of EC patients. These findings highlight the need to implement healthcare services during the pandemic.