Pathology

Morphology-based radiological-histological correlation on ultra-high-resolution energy-integrating detector CT using cadaveric human lungs: nodule and airway analysis.

OBJECTIVES: To evaluate the depiction capability of fine lung nodules and airways using high-resolution settings on ultra-high-resolution energy-integrating detector CT (UHR-CT), incorporating large matrix sizes, thin-slice thickness, and iterative reconstruction (IR)/deep-learning reconstruction (DLR), using cadaveric human lungs and corresponding histological images.

Unraveling the role of perineural invasion in cancer progression across multiple tumor types.

Perineural invasion (PNI) refers to the infiltration of tumor cells into the connective tissue of nerves and is increasingly recognized as a pathological hallmark of multiple cancers, including pancreatic, prostate, colorectal, breast, and head and neck malignancies. PNI is associated with aggressive tumor behavior, an increased risk of recurrence, and poor patient survival. This review consolidat...

Computer Vision Techniques for High-Speed Atomic Force Microscopy of DNA Molecules.

High- speed atomic force microscopy (HSAFM) can produce thousands of topographic, nanoscale images over a small area. One emerging application of this...

Automated Classification of Rheumatoid Arthritis and Knee Synovitis From Hyperspectral Reflectance Data.

Accurate differentiation between rheumatoid arthritis (RA) and knee synovitis (KS) is essential for guiding optimal treatment, yet conventional histop...

Risk Classification of Low-Resolution Whole-Slide Thumbnail Images by Multi-dimensional Feature Reconstruction with Multi-task Deep Learning Network Helps Prioritize Pathology Case Registration.

Contemporary surgical pathology workflows often prioritize slide examination based on case registry order rather than patient risk level. As a result,...

[The application of artificial intelligence in enhancing the safety of pancreatic surgeries].

Pancreatic surgeries have long been considered as challenging procedures due to its complex surgical characteristics. Establishing a surgical safety s...

Deep learning algorithms from histopathological images stratify molecular subtypes for leiomyosarcoma: a proof-and-concept diagnostic study.

BACKGROUND: The leiomyosarocma (LMS) is the most common soft tissue sarcoma, and its molecular subtypes were identified with therapeutic sensitivity a...

Streamlining tuberculosis detection with foundation model-based weakly supervised transformer.

Tuberculosis (TB) remains a major global health challenge, particularly in low- and middle-income countries. Traditional microscopy-based diagnostics ...

Fourier ptychography microscopy for digital pathology.

Fourier ptychography microscopy (FPM) has made significant progress since its invention in 2013, thanks to its adaptable nature, high resolution, and ...

Validation of a Pretrained Artificial Intelligence Model for Pancreatic Cancer Detection on Diagnosis and Prediagnosis Computed Tomography Scans.

PURPOSE: To evaluate PANCANAI, a previously developed AI model for pancreatic cancer (PC) detection, on a longitudinal cohort of patients. In particul...

Machine learning-based construction and validation of an radiomics model for predicting ISUP grading in prostate cancer: a multicenter radiomics study based on [68Ga]Ga-PSMA PET/CT.

PURPOSE: The International Society of Urological Pathology (ISUP) grading of prostate cancer (PCa) is a crucial factor in the management and treatment...

Systematic review of generative adversarial networks (GANs) in cell microscopy: Trends, practices, and impact on image augmentation.

Cell microscopy is the main tool that allows researchers to study microorganisms and plays a key role in observing and understanding the morphology, i...

Patient acceptability of CITOBOT for cervical cancer screening: A mixed-method study.

This study assessed the acceptability of CITOBOT, a device for early cervical cancer screening in a real-world pilot setting as part of a translationa...

Radiomic Model Associated with Tumor Microenvironment Predicts Immunotherapy Response and Prognosis in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma.

No robust biomarkers have been identified to predict the efficacy of programmed cell death protein 1 (PD-1) inhibitors in patients with locoregionall...

GPT-4o and Specialized AI in Breast Ultrasound Imaging: A comparative Study on Accuracy, Agreement, Limitations, and Diagnostic Potential.

OBJECTIVES: This study aimed to evaluate the ability of ChatGPT and Breast Ultrasound Helper, a special ChatGPT-based subprogram trained on ultrasound...

Physiological Response of Tissue-Engineered Vascular Grafts to Vasoactive Agents in an Ovine Model.

Tissue-engineered vascular grafts (TEVGs) are emerging as promising alternatives to synthetic grafts, particularly in pediatric cardiovascular surgery...

Machine learning-based detoxification enzymes-related genes prognosis model in breast cancer: immune landscape and clinical significance.

BACKGROUND: Breast cancer is one of the most common malignant tumors, threatening women's health and life globally. Despite significant treatment adva...

Artificial Intelligence-Driven Proteomics Identifies Plasma Protein Signatures for Diagnosis and Stratification of Behçet's Disease.

The diagnosis of Behçet's disease (BD) predominantly relies on clinical symptoms, indicating an urgent for identifying potential biomarkers for early ...

Classification of primary glomerulonephritis using machine learning models: a focus on IgA nephropathy prediction.

OBJECTIVE: IgA nephropathy (IgAN) is the most common form of glomerulonephritis worldwide, characterized by immune complex deposition in the glomerula...

Fine-tuned large language model for classifying CT-guided interventional radiology reports.

BackgroundManual data curation was necessary to extract radiology reports due to the ambiguities of natural language.PurposeTo develop a fine-tuned la...