Background: Male-carriers of BRCA1/2 gene mutations have an increased risk of prostate cancer (PCa) with a more aggressive phenotype. Current screening-guidelines suggest the use of prostate-specific antigen (PSA) only among BRCA2 carriers. Female carriers have extensive guidelines that include imaging. Our objective was to test the prevalence of PCa among BRCA carriers and examine screening strategies, using PSA and multiparametric magnetic resonance imaging (mpMRI). Patients and methods: We recruited men aged 40e70 years with BRCA1/2 germline mutations and no prior history of prostate biopsy. All men underwent an initial round of screening which included PSA, and prostate mpMRI. PSA was considered elevated using an age-stratified threshold of !1 ng/ml for 40e50 years of age, !2 ng/ml for 50e60 years of age, and 2.5 ng/ml for 60e70 years of age. Men with elevated PSA and/or suspicious lesion on mpMRI were offered a prostate biopsy. PSA levels, MRI findings, PCa incidence, and tumor characteristics were evaluated. Decision curve analysis was used to compare screening strategies. Results: We recruited 188 men (108 BRCA1, 80 BRCA2), mean age 54 years (9.8). One hundred and ten (57%) had either elevated age-stratified PSA (75; 40%), a suspicious MRI lesion (67; 36%), or both (32; 17%). Of these, 92 (85%) agreed to perform a prostate biopsy. Sixteen (8.5%) were diagnosed with PCa; 44% of the tumors were classified as intermediateor high-risk disease. mpMRI-based screening missed only one of the cancers (6%), while age-stratified PSA would have missed five (31%). Decision curve analysis showed that mpMRI screening, regardless of PSA, had the highest net benefit for PCa diagnosis, especially among men younger than 55 years of age. We found no difference in the risk of PCa between BRCA1 and BRCA2 (8.3% versus 8.7%, P ¼ 0.91). Ninety percent had a Jewish founder mutation, thus the results cannot be generalized to all ethnic groups. Conclusions: PCa is prevalent among BRCA carriers. Age may affect screening strategy for PCa in this population. Young carriers could benefit from initial MRI screening. BRCA carriers aged older than 55 years should use PSA and be referred to mpMRI if elevated. Trial registration: ClinicalTrial.gov ID: NCT02053805.

Author Contributions: Drs Fallon and Laird had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

The objective of the study was to compare the outcome measures of patients with endometrial adenocarcinoma diagnosed by endometrial biopsy, uterine curettage, or hysteroscopy. Medical records of 392 women diagnosed with apparent early-stage endometrial adenocarcinoma were reviewed. Data concerning the mode of diagnosis, histologic type and grade, surgical stage, peritoneal washings and lymph nodes status, and patient's outcome were retrieved. During the study period, 99 (25.3%) cases were diagnosed by endometrial biopsy, 193 (49.2%) by uterine curettage, and 100 (25.5%) by hysteroscopy. There were 347 (88.5%) cases of endometrioid adenocarcinoma and 45 (11.5%) of poor histologic types, including serous papillary, clear cell, and small cell cancer. Three hundred and sixteen (80.6%) patients had stage I disease, 8 (2.0%) stage II, and 68 (17.4%) stage III. Peritoneal cytology was positive in only one case. Recurrent disease occurred in 6.9% patients, of which 50% had local recurrence and 50% had distant. Recurrent disease was found in 15.2% patients diagnosed by endometrial biopsy, in 4.7% where uterine curettage was used, and in 5% when hysteroscopy was applied. No statistically significant difference in the survival rate between the different diagnostic methods applied was found, although a higher recurrence rate was noted following endometrial biopsy. After a median follow-up time of 25 months for patients undergoing hysteroscopy, there was no difference in recurrence rates and/or overall survival compared to other diagnostic procedures implying that hysteroscopy can be safely used in the diagnosis of endometrial cancer.

Background Magnetic resonance imaging (MRI) and ultrasound (US) fusion prostate-biopsies can be performed in a transrectal (TR-fusion) or transperineal (TP-fusion) approach. Prospective comparative evidence is limited. In this study we compared the detection rate of clinically-significant prostate-cancer (csPCa) within an index lesion between TR and TP-fusion. Patients and methods This was a prospective, noninferiority, and within-person trial. Men scheduled for MRI-US-fusion with a discrete MRI PI-RRAD ≥ 3 lesion were included. A dominant index lesion was determined for each subject and sampled by TR and TP-fusion during the same session. The order of biopsies was randomized and equipment was reset to avoid chronological and incorporation bias. For each subject, the index lesion was sampled 4-6 times in each approach. All biopsies were performed using Navigo fusion software (UC-Care, Yokneam, Israel). csPCa was defined as: Grade Group ≥ 2 or cancer-core length ≥ 6 mm. We used a noninferiority margin of 10% and a one-sided alpha level of 5%. Results Seventy-seven patients completed the protocol. Median age was 68.2 years (IQR:64.2-72.2), median PSA was 8.9 ng/ml (IQR:6.18-12.2). Ten patients (13%) were biopsy naive, others (87%) had a previous biopsy. csPCa was detected in 32 patients (42%). All of these cases were detected by TP-fusion, while only 20 (26%) by TR-fusion. Absolute difference for csPCa diagnosis was 15.6 (CI 90% 27.9-3.2%) in favor of TP-fusion (p = 0.029). TP-fusion was noninferior to TR-fusion. The lower boundary of the 90% confidence-interval between TP-fusion and TR-fusion was greater than zero, therefore TPfusion was also found to be superior. Exploratory subgroup analyses showed TP-fusion was consistently associated with higher detection rates of csPCa compared with TR-fusion in patient and index-lesion derived subgroups (size, location, PI-RADS, PSA, and biopsy history). Conclusions In this study, TP-fusion biopsies were found to be noninferior and superior to TR-fusion biopsies in detecting csPCa within MRI-visible index lesion. Centers experienced in both TP and TR-fusion should consider these results when choosing biopsy method.

Objectives In the midst of the coronavirus disease 2019 (COVID-19) outbreak, chest X-ray (CXR) imaging is playing an important role in diagnosis and monitoring of patients with COVID-19. We propose a deep learning model for detection of COVID-19 from CXRs, as well as a tool for retrieving similar patients according to the model’s results on their CXRs. For training and evaluating our model, we collected CXRs from inpatients hospitalized in four different hospitals. Methods In this retrospective study, 1384 frontal CXRs, of COVID-19 confirmed patients imaged between March and August 2020, and 1024 matching CXRs of non-COVID patients imaged before the pandemic, were collected and used to build a deep learning classifier for detecting patients positive for COVID-19. The classifier consists of an ensemble of pre-trained deep neural networks (DNNS), specifically, ReNet34, ReNet50¸ ReNet152, and vgg16, and is enhanced by data augmentation and lung segmentation. We further implemented a nearest-neighbors algorithm that uses DNN-based image embeddings to retrieve the images most similar to a given image. Results Our model achieved accuracy of 90.3%, (95% CI: 86.3–93.7%) specificity of 90% (95% CI: 84.3–94%), and sensitivity of 90.5% (95% CI: 85–94%) on a test dataset comprising 15% (350/2326) of the original images. The AUC of the ROC curve is 0.96 (95% CI: 0.93–0.97). Conclusion We provide deep learning models, trained and evaluated on CXRs that can assist medical efforts and reduce medical staff workload in handling COVID-19. Key Points • A machine learning model was able to detect chest X-ray (CXR) images of patients tested positive for COVID-19 with accuracy and detection rate above 90%. • A tool was created for finding existing CXR images with imaging characteristics most similar to a given CXR, according to the model’s image embeddings. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-021-08050-1.