Pathology

Spatial-temporal recurrence patterns of grade 4 glioma using deep learning integrated multiparametric MRI and molecular pathology.

Grade 4 glioma is inherently lethal due to inevitable recurrence. Current radiotherapy guidelines recommend uniform target volume margins, disregarding molecular and clinical variables. We hypothesized that spatiotemporal recurrence may be predicted by molecular and phenotypic features present already at diagnosis. We analyzed 390 paired MRIs of grade 4 gliomas from Norwegian multi-centers and TCI...

A weakly supervised deep learning-based recurrence prediction and risk stratification of lung adenocarcinoma from pathology whole-slide images.

BACKGROUND: Accurate prediction of postoperative recurrence in lung adenocarcinoma (LUAD) is essential for guiding clinical decision-making and improving patient outcomes. Although various predictive models have been developed, most rely on complex genomic analyses and high-dimensional clinical data. The complexity of these approaches substantially limits their feasibility for routine clinical use...

Integration of two-dimensional microvascular flow imaging and ultrasound scoring for prediction of placenta accreta spectrum: A prospective study.

OBJECTIVE: This study evaluates the diagnostic performance of two-dimensional (2D) microvascular flow imaging combined with standardized ultrasound ma...

Association Between Amyloid Deposition and Collagen-to-Elastin Ratio in the Ligamentum Flavum: A Machine Learning Histologic Study in Matched Groups.

BACKGROUND AND OBJECTIVES: Amyloid deposition in the ligamentum flavum (LF) occurs in 25% to 45% of patients with lumbar stenosis (LS). Amyloid-positi...

Diagnosing helminth infections in a large reference laboratory in the United States: a 6-month pre- and post-implementation analysis of AI-augmented screening of concentrated fecal wet mounts.

Helminth infections are uncommon in the United States, yet accurate detection remains critical. Conventional ova-and-parasite examinations are labor-i...

Cell-specific multi-target mechanisms of cotinine in cervical cancer oncogenesis and progression.

BACKGROUND: Cervical cancer is the fourth most common malignant tumor in women globally, with tobacco smoke being a major environmental risk factor. T...

Ophiopogon japonicus alleviates pulmonary fibrosis through modulation of HIF1A/TUBB3 axis-associated M2 macrophage polarization and arginine metabolic alterations.

ETHNOPHARMACOLOGICAL RELEVANCE: Ophiopogon japonicus (Thunb.) Ker Gawl. is a traditional Chinese medicinal herb commonly used to "nourish yin and mois...

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lu...

Matrix-assisted laser desorption/ionization mass spectrometry imaging for spatial clinical oncopathology: diagnosis, margins and therapy.

Clinical oncology increasingly depends on molecular information, but many assays still detach analytes from the histological coordinates in which diag...

New Frontiers of Skin Ultrasound in Precision Medicine.

Ultrasound has emerged as a versatile, non-invasive imaging technique in dermatology, offering real-time, high-resolution visualization of cutaneous s...

A multidimensional risk prediction framework for malignant intestinal obstruction based on machine learning: computational model development and clinical validation.

Malignant intestinal obstruction (MIO) is a severe complication of advanced cancer. Traditional static assessment models struggle to capture its dynam...

Early cell-wall stress signatures enable 20-min ATR-FTIR discrimination of MRSA and MSSA.

Rapid identification of methicillin-resistant Staphylococcus aureus (MRSA) is crucial for early optimization of antibiotic treatment, but current rout...

Side-level versus patient-level evaluation in four-view mammography classification: a comprehensive benchmark on the CMMD dataset.

BACKGROUND: Deep learning for mammographic image classification yields impressive performance metrics, but inconsistent evaluation methodologies-speci...

Predicting TP53 Biomarkers from Whole Slide Images across Human Solid Tumors Using Weakly Supervised Learning.

Accurate molecular profiling from routine histopathology slides could transform clinical oncology. A Vision Transformer (ViT)-based model was develope...

GrandQC adaptation as an artificial intelligence tool for quantitative artifact detection in hematoxylin and eosin whole-slide images-Simulation of quality control biopsies day.

INTRODUCTION: Digital pathology continues to transform the daily routine of pathology, in terms of the increasingly automated laboratory and in the di...

A methodological framework for integrating generalisable deep learning and radiomics fusion model for early lung cancer detection across multi-centre imaging datasets.

Early detection of lung cancer remains one of the most effective strategies for improving survival; however, diagnostic performance is limited by vari...

Deep learning-based prediction of gene expression from histopathology identifies NR5A1 as a candidate biomarker and druggable target in high-grade serous ovarian carcinoma.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is the most lethal ovarian cancer subtype, responsible for ~ 70% of ovarian cancer-related deaths...

FSCL-BC: Federated supervised contrastive learning for breast cancer diagnosis with high sensitivity.

BACKGROUND AND OBJECTIVE: Accurate diagnosis of breast cancer in dense breasts requires expert radiologists to examine multiple ultrasound images per ...

MicNet: integrating spatially resolved transcriptomes and pathology images by contrastive deep neural network.

Recent breakthroughs in spatially resolved transcriptomic technologies have enabled molecular characterization of cells while preserving spatial and m...

Wavelet Spectrum in a Multi-Channel Network May Reduce Biopsy Rates on Diagnosis of Breast Tumors with BI-RADS Category 4a or Higher.

OBJECTIVES: BI-RADS 4a+ breast tumors have a high rate of unnecessary biopsies due to ambiguous diagnostic features. This study aims to develop and ev...