Focal Therapy of Prostate Cancer Index Lesion With Irreversible Electroporation. A Prospective Study With a Median Follow-up of 3 Years.

PURPOSE: Our aim was to assess oncologic, safety, and quality of life-related outcomes of focal therapy with irreversible electroporation in men with localized prostate cancer. MATERIALS AND METHODS: This was a single-center, phase II study. INCLUSION CRITERIA: prostate cancer International Society of Urological Pathology grade 1-2, prostate specific antigen ≤15 ng/ml, ≤cT2b. Patients were selected based on multiparametric magnetic resonance imaging and transperineal systematic and targeted magnetic resonance imaging-ultrasound fusion-guided biopsy. Ablation of index lesions with safety margin was performed. Primary end point was cancer control, defined as the absence of any biopsy-proven tumor. A control transperineal biopsy was planned at 12 months and when suspected based on prostate specific antigen and/or multiparametric magnetic resonance imaging information. Quality of life was assessed using Expanded Prostate Cancer Index Composite Urinary Continence domain, International Index of Erectile Function, and International Prostate Symptom Score. RESULTS: From November 2014 to July 2021, 41 consecutive patients were included with a median follow-up of 36 months. Thirty patients (73%) had International Society of Urological Pathology grade 1 tumors, 10 (24%) grade 2, and 1 (2.4%) grade 3. Recurrence was observed in 16 of 41 (39%) of the whole cohort, and 16 of 33 (48.4%) who underwent biopsy. In-field recurrence was detected in 5 (15%) and out-of-field in 11 (33.3%). Ten of 41 (24.6%) including 3 of 5 (60%) with in-field recurrences had significant tumors (Gleason pattern 4-5; more than 1 core or any >5 mm involved). Median recurrence-free survival was 32 months (95% CI 6.7-57.2). Twenty-six patients (63.4%) were free from salvage treatment. All patients preserved urinary continence. Potency was maintained in 91.8%. CONCLUSIONS: Irreversible electroporation can achieve satisfactory 3-year in-field tumor control with excellent quality of life results in selected patients.

Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT.

The main objective of this work is to develop and evaluate an artificial intelligence system based on deep learning capable of automatically identifying, quantifying, and characterizing COVID-19 pneumonia patterns in order to assess disease severity and predict clinical outcomes, and to compare the prediction performance with respect to human reader severity assessment and whole lung radiomics. We propose a deep learning based scheme to automatically segment the different lesion subtypes in nonenhanced CT scans. The automatic lesion quantification was used to predict clinical outcomes. The proposed technique has been independently tested in a multicentric cohort of 103 patients, retrospectively collected between March and July of 2020. Segmentation of lesion subtypes was evaluated using both overlapping (Dice) and distance-based (Hausdorff and average surface) metrics, while the proposed system to predict clinically relevant outcomes was assessed using the area under the curve (AUC). Additionally, other metrics including sensitivity, specificity, positive predictive value and negative predictive value were estimated. 95% confidence intervals were properly calculated. The agreement between the automatic estimate of parenchymal damage (%) and the radiologists' severity scoring was strong, with a Spearman correlation coefficient (R) of 0.83. The automatic quantification of lesion subtypes was able to predict patient mortality, admission to the Intensive Care Units (ICU) and need for mechanical ventilation with an AUC of 0.87, 0.73 and 0.68 respectively. The proposed artificial intelligence system enabled a better prediction of those clinically relevant outcomes when compared to the radiologists' interpretation and to whole lung radiomics. In conclusion, deep learning lesion subtyping in COVID-19 pneumonia from noncontrast chest CT enables quantitative assessment of disease severity and better prediction of clinical outcomes with respect to whole lung radiomics or radiologists' severity score.

ESGO/ISUOG/IOTA/ESGE Consensus Statement on pre-operative diagnosis of ovarian tumors.

The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group, and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the pre-operative diagnosis of ovarian tumors, including imaging techniques, biomarkers, and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the pre-operative diagnosis of ovarian tumors and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when a consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the pre-operative diagnosis of ovarian tumors and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.

[Pulmonary sclerosing hemangioma in a patient with Cowden syndrome]. / Hemangioma esclerosante pulmonar en un paciente con síndrome de Cowden.

We describe the case of an 18-year-old female with Cowden syndrome in whom a simple x-ray detected a solitary pulmonary nodule that was identified as a sclerosing hemangioma. Pulmonary sclerosing hemangioma is an unusual lung neoplasm which typically presents as a solitary peripheral nodule in asymptomatic women. Although the histology of this entity is well defined, its origin and treatment is debated. One of the main diagnostic problems is to histologically differentiate a pulmonary sclerosing hemangioma from a papillary lung carcinoma.