Pathology

An explainable AI workflow integrating automated volumetric body composition analysis for predicting pathological grading of gastroenteropancreatic neuroendocrine neoplasms: a multicenter cohort study.

BACKGROUND: Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are heterogeneous tumors with rising incidence, necessitating precise preoperative grading for treatment planning. Existing imaging techniques and endoscopic biopsies often fall short due to insufficient markers and tissue samples. Body composition influences tumor biology, yet traditional 2D assessments are time-consuming and ...

A Novel Method for Hydrogen Permeation Detection Using Reflective Microscopy and Machine Learning.

Localized detection of hydrogen permeation in steel membranes is crucial for practical applications but remains challenging. We present a reflective microscopy (RM) approach combined with machine learning (ML)-driven image analysis to address this issue. Hydrogen permeation in press-hardened steel alters the Fe(II)/Fe(III) ratio in the surface layer, affecting reflected light intensity due to chan...

Automated deep learning for detection and measurement of adrenal masses in contrast-enhanced abdominal CT.

OBJECTIVES: Adrenal tumors can be functional or malignant, yet they are often overlooked in abdominal CT. This study aimed to develop and validate a f...

Unraveling heterogeneity in LUAD via multi-omics integration: molecular classification and therapeutic implications.

Lung adenocarcinoma (LUAD) displays significant morphological and molecular heterogeneity both within and between tumors. This heterogeneity, coupled ...

Differentiation of focal liver lesions in contrast-enhanced ultrasound using a heuristic-guided hybrid machine-learning framework.

PURPOSE: Sonazoid contrast-enhanced ultrasound (CEUS) offers valuable diagnostic information on hepatic lesions, but it is time-consuming. In this stu...

Non-invasive liquid biopsy based on metabolomic profiling improves diagnosis and early warning of severe acute pancreatitis.

To identify novel diagnostic biomarkers for acute pancreatitis (AP) and facilitate the early prediction of severe AP (SAP), this investigation charact...

HRD-Informed Digital Histology Model for Predicting Platinum Chemo-Response and Prognosis in High-Grade Serous Ovarian Cancer.

Homologous recombination deficiency (HRD) is a critical biomarker in high-grade serous ovarian cancer for the clinical benefit from platinum-based che...

Interpretable machine learning model for predicting 5-Year postoperative recurrence risk in patients with stage III colon cancer using preoperative laboratory tests: a two-centre study.

BACKGROUND: Colorectal cancer (CRC) is one of the most prevalent malignant diseases worldwide and displays significant heterogeneity. The aim of this ...

Accurate classification of ependymomas and medulloblastomas using Raman spectroscopy and pilot transcriptomic profiling.

Raman spectroscopy enabled accurate discrimination of posterior fossa ependymomas and medulloblastomas in both frozen and formalin-fixed, paraffin-emb...

From slides to AI-ready maps: Standardized multi-layer tissue maps as metadata for artificial intelligence in digital pathology.

A Whole Slide Image (WSI) is a high-resolution digital image created by scanning an entire glass slide containing a biological specimen, such as tissu...

Automated 3D body composition analysis on chest CT scans for survival prediction in high-grade extremity soft tissue sarcomas.

INTRODUCTION: High-grade soft tissue sarcomas (STShg) of the extremities are rare cancers with a poor prognosis. Accurate staging at initial evaluatio...

High reliability Ag/Ni/NiO nanowire-based SERS for cancer detection: a study on breast cancer.

Over the past decade, substantial research has focused on identifying cancer biomarkers using Raman spectroscopy. However, no commercial Raman-based d...

The Utility of Face2Gene App for Syndrome Recognition in Indian Children with Dysmorphism.

OBJECTIVES: To determine the accuracy of Face2Gene (F2G) app in the diagnosis of a genetic syndrome as a first correct response, after uploading the i...

Photoplasticity behavior in inorganic semiconductors: unraveling fundamental mechanisms across ionic and covalent systems.

Inorganic semiconductors exhibit photoplasticity, where light exposure alters dislocation-mediated plastic flow based on the material's bonding charac...

Expanding role of cell-free DNA for the early diagnosis and monitoring of pulmonary diseases.

Circulating cell-free DNA (cfDNA) has firmly established itself as a cornerstone of liquid biopsy, advancing the noninvasive diagnosis and monitoring ...

Deep learning-based plaque characterization in hybrid IVUS-OCT images is superior to single-modality deep learning analysis and human experts: head-to-head comparison against histology.

AIMS: Hybrid intravascular ultrasound-optical coherence tomography (IVUS-OCT) can enable more accurate plaque characterization than single-modality in...

Automated Classification of Store-Operated Calcium Entry Activity and Disease Conditions in Murine Skeletal Muscle Images Using Machine Learning.

INTRODUCTION/AIMS: Accurate detection of pathophysiology from tissue images is critical for appropriate diagnoses and treatments of muscular dystrophi...

Urine Proteomics Identifies Biomarkers for Diagnosis and Fibrosis Severity in Pediatric Chronic Pancreatitis.

INTRODUCTION: Reliable biomarkers for the diagnosis of chronic pancreatitis (CP) and pancreatic fibrosis severity are lacking, hindering effective tre...

Multimodal Large Language Models for Cystoscopic Image Interpretation and Bladder Lesion Classification: Comparative Study.

BACKGROUND: Cystoscopy remains the gold standard for diagnosing bladder lesions; however, its diagnostic accuracy is operator dependent and prone to m...

A comprehensive multi-task deep learning model for kidney cancer: histological subtyping, clinical staging, and anatomical complexity grading.

OBJECTIVES: To develop and validate a multi-task deep learning (MTDL) model using multiphase contrast-enhanced CT (CECT) for simultaneously assessing ...