Bimodal imaging: Detection rate of clinically significant prostate cancer is higher in MRI lesions visible to transrectal ultrasound.

Background: To explore the detection rates of clinically significant prostate cancer (csPCa; ISUP ≥2) in patients with a single MRI lesion that is visible or invisible on transrectal ultrasound (TRUS) during biopsy.

Methods: Retrospective analyses of patients who underwent targeted and systematic biopsy of the prostate for one MRI-visible lesion (PI-RADS score ≥ 3) between 2017 and 2022. TRUS-visibility, PI-RADS score, and clinical parameters were recorded prospectively.

Self-supervised learning for classifying paranasal anomalies in the maxillary sinus.

Purpose: Paranasal anomalies, frequently identified in routine radiological screenings, exhibit diverse morphological characteristics. Due to the diversity of anomalies, supervised learning methods require large labelled dataset exhibiting diverse anomaly morphology. Self-supervised learning (SSL) can be used to learn representations from unlabelled data.

Computer-Aided Diagnosis of Maxillary Sinus Anomalies: Validation and Clinical Correlation.

Objective: Computer aided diagnostics (CAD) systems can automate the differentiation of maxillary sinus (MS) with and without opacification, simplifying the typically laborious process and aiding in clinical insight discovery within large cohorts.

Methods: This study uses Hamburg City Health Study (HCHS) a large, prospective, long-term, population-based cohort study of participants between 45 and 74 years of age. We develop a CAD system using an ensemble of 3D Convolutional Neural Network (CNN) to analyze cranial MRIs, distinguishing MS with opacifications (polyps, cysts, mucosal thickening) from MS without opacifications.

PSA-density, DRE, and PI-RADS 5: potential surrogates for omitting biopsy?

Objective: In contrast to other malignancies, histologic confirmation prior treatment in patients with a high suspicion of clinically significant prostate cancer (csPCA) is common. To analyze the impact of extracapsular extension (ECE), cT-stage defined by digital rectal examination (DRE), and PSA-density (PSA-D) on detection of csPCA in patients with at least one PI-RADS 5 lesion (hereinafter, "PI-RADS 5 patients").

Materials And Methods: PI-RADS 5 patients who underwent MRI/Ultrasound fusion biopsy (Bx) between 2016 and 2020 were identified in our institutional database.

Multiple instance ensembling for paranasal anomaly classification in the maxillary sinus.

Purpose: Paranasal anomalies are commonly discovered during routine radiological screenings and can present with a wide range of morphological features. This diversity can make it difficult for convolutional neural networks (CNNs) to accurately classify these anomalies, especially when working with limited datasets. Additionally, current approaches to paranasal anomaly classification are constrained to identifying a single anomaly at a time.