Advanced Restriction Imaging and Reconstruction Technology for Prostate Magnetic Resonance Imaging (ART-Pro): A Study Protocol for a Multicenter, Multinational Trial Evaluating Biparametric Magnetic Resonance Imaging and Advanced, Quantitative Diffusion Magnetic Resonance Imaging for the Detection of Prostate Cancer.

Multiparametric magnetic resonance imaging (mpMRI) is strongly recommended by current clinical guidelines for improved detection of clinically significant prostate cancer (csPCa). However, the major limitations are the need for intravenous (IV) contrast and dependence on reader expertise. Efforts to address these issues include use of biparametric magnetic resonance imaging (bpMRI) and advanced, quantitative magnetic resonance imaging (MRI) techniques.

Biopsy-based Basal-luminal Subtyping Classifier in High-risk Prostate Cancer: A Combined Analysis of the NRG Oncology/RTOG 9202, 9413, and 9902 Phase 3 Trials.

Background And Objective: Long-term (LT) androgen deprivation therapy (ADT) has been found to be beneficial to patients with high-risk prostate cancer (PCa). However, administration of LT-ADT to all patients with high-risk PCa may lead to overtreatment. Enhanced risk stratification using genomic classifiers (such as the recently developed prostate subtyping classifier [PSC]) might be useful.

Prostate Cancer Risk Stratification in NRG Oncology Phase III Randomized Trials Using Multimodal Deep Learning With Digital Histopathology.

Purpose: Current clinical risk stratification methods for localized prostate cancer are suboptimal, leading to over- and undertreatment. Recently, machine learning approaches using digital histopathology have shown superior prognostic ability in phase III trials. This study aims to develop a clinically usable risk grouping system using multimodal artificial intelligence (MMAI) models that outperform current National Comprehensive Cancer Network (NCCN) risk groups.

The impact of benign tissue within cancerous regions in the prostate: Characterizing sparse and dense prostate cancers on whole-mount histopathology and on multiparametric MRI.

Purpose: To establish the incidence, size, zonal location and Gleason Score(GS)/Gleason Grade Group(GG) of sparse versus dense prostate cancer (PCa) lesions and to identify the imaging characteristics of sparse versus dense cancers on multiparametric MRI (mpMRI).

Methods: Seventy-six men with untreated PCa were scanned prior to prostatectomy with endorectal-coil 3 T MRI including T2-weighted imaging, diffusion-weighted imaging and dynamic contrast-enhanced MRI. Cancerous regions were outlined and graded on the whole-mount, processed specimens, with tissue compositions estimated.

Next-generation sequencing has diagnostic utility in challenging small/flat urothelial lesions.

Small/flat urothelial lesions are challenging and currently available ancillary immunohistochemistry testing often cannot reliably distinguish between reactive lesions and urothelial carcinoma (UCa). UCa has a characteristic molecular profile, but small/flat urothelial lesions are typically considered too small to perform next generation sequencing (NGS). Herein, we present our institution's experience with utilizing comprehensive DNA-based NGS to evaluate small/flat urothelial lesions (n = 13 cases).

Functional architecture of intracellular oscillations in hippocampal dendrites.

Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior.

Morphologic patterns observed in prostate biopsy cases with discrepant grade group and molecular risk classification.

Background: Molecular-based risk classifier tests are increasingly being utilized by urologists and radiation oncologists to guide clinical decision making. The Decipher prostate biopsy test is a 22-gene RNA biomarker assay designed to predict likelihood of high-grade disease at radical prostatectomy and risk of metastasis and mortality. The test provides a risk category of low, intermediate, or high.

Behavioral control through the direct, focal silencing of neuronal activity.

The ability to optically stimulate and inhibit neurons has revolutionized neuroscience research. Here, we present a direct, potent, user-friendly chemical approach for optically silencing neurons. We have rendered saxitoxin (STX), a naturally occurring paralytic agent, transiently inert through chemical protection with a previously undisclosed nitrobenzyl-derived photocleavable group.

Prognostic Significance of Immune Cell Infiltration in Muscle-invasive Bladder Cancer Treated with Definitive Chemoradiation: A Secondary Analysis of RTOG 0524 and RTOG 0712.

Chemoradiation therapy (CRT) is a treatment for muscle-invasive bladder cancer (MIBC). Using a novel transcriptomic profiling panel, we validated prognostic immune biomarkers to CRT using 70 pretreatment tumor samples from prospective trials of MIBC (NRG/RTOG 0524 and 0712). Disease-free survival (DFS) and overall survival (OS) were estimated via the Kaplan-Meier method and stratified by genes correlated with immune cell activation.

Mixed Supervision of Histopathology Improves Prostate Cancer Classification From MRI.

Non-invasive prostate cancer classification from MRI has the potential to revolutionize patient care by providing early detection of clinically significant disease, but has thus far shown limited positive predictive value. To address this, we present a image-based deep learning method to predict clinically significant prostate cancer from screening MRI in patients that subsequently underwent biopsy with results ranging from benign pathology to the highest grade tumors. Specifically, we demonstrate that mixed supervision via diverse histopathological ground truth improves classification performance despite the cost of reduced concordance with image-based segmentation.

Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer.

BACKGROUND: Androgen deprivation therapy (ADT) with radiotherapy can benefit patients with localized prostate cancer. However, ADT can negatively impact quality of life, and there remain no validated predictive models to guide its use. METHODS: We used digital pathology images from pretreatment prostate tissue and clinical data from 5727 patients enrolled in five phase 3 randomized trials, in which treatment was radiotherapy with or without ADT, as our data source to develop and validate an artificial intelligence (AI)–derived predictive patient-specific model that would determine which patients would develop the primary end point of distant metastasis.

External Validation of a Digital Pathology-based Multimodal Artificial Intelligence Architecture in the NRG/RTOG 9902 Phase 3 Trial.

Background: Accurate risk stratification is critical to guide management decisions in localized prostate cancer (PCa). Previously, we had developed and validated a multimodal artificial intelligence (MMAI) model generated from digital histopathology and clinical features. Here, we externally validate this model on men with high-risk or locally advanced PCa treated and followed as part of a phase 3 randomized control trial.

The impact of genomic biomarkers on a clinical risk prediction model for upgrading/upstaging among men with favorable-risk prostate cancer.

Background: The challenge of distinguishing indolent from aggressive prostate cancer (PCa) complicates decision-making for men considering active surveillance (AS). Genomic classifiers (GCs) may improve risk stratification by predicting end points such as upgrading or upstaging (UG/US). The aim of this study was to assess the impact of GCs on UG/US risk prediction in a clinicopathologic model.

Optimization-based modeling of Lombard speech articulation: Supraglottal characteristics.

This paper shows that a highly simplified model of speech production based on the optimization of articulatory effort versus intelligibility can account for some observed articulatory consequences of signal-to-noise ratio. Simulations of static vowels in the presence of various background noise levels show that the model predicts articulatory and acoustic modifications of the type observed in Lombard speech. These features were obtained only when the constraint applied to articulatory effort decreases as the level of background noise increases.

High expression of Trop2 is associated with aggressive localized prostate cancer and is a candidate urinary biomarker.

Distinguishing indolent from clinically significant localized prostate cancer is a major clinical challenge and influences clinical decision-making between treatment and active surveillance. The development of novel predictive biomarkers will help with risk stratification, and clinical decision-making, leading to a decrease in over or under-treatment of patients with prostate cancer. Here, we report that Trop2 is a prognostic tissue biomarker for clinically significant prostate cancer by utilizing the Canary Prostate Cancer Tissue Microarray (CPCTA) cohort composed of over 1100 patients from a multi-institutional study.

Large cribriform glands (> 0.25 mm diameter) as a predictor of adverse pathology in men with Grade Group 2 prostate cancer.

Aims: A recent outcome-based, radical prostatectomy study defined > 0.25 mm diameter to distinguish large versus small cribriform glands, with > 0.25 mm associated with worse recurrence-free survival.

First-in-human Evaluation of a Prostate-specific Membrane Antigen-targeted Near-infrared Fluorescent Small Molecule for Fluorescence-based Identification of Prostate Cancer in Patients with High-risk Prostate Cancer Undergoing Robotic-assisted Prostatectomy.

Background: Men with high-risk prostate cancer undergoing surgery likely recur due to failure to completely excise regional and/or local disease.

Objective: The first-in-human evaluation of safety, pharmacokinetics, and exploratory efficacy of IS-002, a novel near-infrared prostate-specific membrane antigen (PSMA)-targeted fluorescence imaging agent, designed for intraoperative prostate cancer visualization.

Design, Setting, And Participants: A phase 1, single-center, dose-escalation study was conducted in 24 men with high-risk prostate cancer scheduled for robotic-assisted radical prostatectomy with (extended) pelvic lymph node dissection using the da Vinci surgical system.

Transcriptomic Heterogeneity of Expansile Cribriform and Other Gleason Pattern 4 Prostate Cancer Subtypes.

Background: Prostate cancers featuring an expansile cribriform (EC) pattern are associated with worse clinical outcomes following radical prostatectomy (RP). However, studies of the genomic characteristics of Gleason pattern 4 subtypes are limited.

Objective: To explore transcriptomic characteristics and heterogeneity within Gleason pattern 4 subtypes (fused/poorly formed, glomeruloid, small cribriform, EC/intraductal carcinoma [IDC]) and the association with biochemical recurrence (BCR)-free survival.

Artificial Intelligence-Based PTEN Loss Assessment as an Early Predictor of Prostate Cancer Metastasis After Surgery: A Multicenter Retrospective Study.

Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and can be measured via immunohistochemistry. The purpose of the study was to establish the clinical application of an in-house developed artificial intelligence (AI) image analysis workflow for automated detection of PTEN loss on digital images for identifying patients at risk of early recurrence and metastasis. Postsurgical tissue microarray sections from the Canary Foundation (n = 1264) stained with anti-PTEN antibody were evaluated independently by pathologist conventional visual scoring (cPTEN) and an automated AI-based image analysis pipeline (AI-PTEN).

The Effect of Zonisamide on Rat Bone Mass, Structure, and Metabolism.

Introduction: Our study aimed to investigate the effect of zonisamide (ZNS) on bone metabolism in the rat model.

Methods: Eight-week-old rats were divided into four groups. The sham-operated control group (SHAM) and the control group after orchidectomy (ORX) received the standard laboratory diet (SLD).

Genomic Classifier Performance in Intermediate-Risk Prostate Cancer: Results From NRG Oncology/RTOG 0126 Randomized Phase 3 Trial.

Purpose: Intermediate-risk prostate cancer is a heterogeneous disease state with diverse treatment options. The 22-gene Decipher genomic classifier (GC) retrospectively has shown to improve risk stratification in these patients. We assessed the performance of the GC in men with intermediate-risk disease enrolled in NRG Oncology/RTOG 01-26 with updated follow-up.