AIMC Topic: Biopsy

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Multi-stain deep learning prediction model of treatment response in lupus nephritis based on renal histopathology.

Kidney international
The response of the kidney after induction treatment is one of the determinants of prognosis in lupus nephritis, but effective predictive tools are lacking. Here, we sought to apply deep learning approaches on kidney biopsies for treatment response p...

Prediction of mucinous adenocarcinoma in colorectal cancer with mucinous components detected in preoperative biopsy diagnosis.

Abdominal radiology (New York)
OBJECTIVES: Endoscopic biopsy diagnosis for the preoperative assessment of mucinous components in patients with colorectal cancer is limited. This study investigated a radiomics model and established an explainable prediction model by using machine l...

Stress testing deep learning models for prostate cancer detection on biopsies and surgical specimens.

The Journal of pathology
The presence, location, and extent of prostate cancer is assessed by pathologists using H&E-stained tissue slides. Machine learning approaches can accomplish these tasks for both biopsies and radical prostatectomies. Deep learning approaches using co...

Quantitative fibrosis identifies biliary tract involvement and is associated with outcomes in pediatric autoimmune liver disease.

Hepatology communications
BACKGROUND: Children with autoimmune liver disease (AILD) may develop fibrosis-related complications necessitating a liver transplant. We hypothesize that tissue-based analysis of liver fibrosis by second harmonic generation (SHG) microscopy with art...

Let it shine: Autofluorescence of Papanicolaou-stain improves AI-based cytological oral cancer detection.

Computers in biology and medicine
BACKGROUND AND OBJECTIVES: Oral cancer is a global health challenge. The disease can be successfully treated if detected early, but the survival rate drops significantly for late stage cases. There is a growing interest in a shift from the current st...

Comparison of deep learning schemes in grading non-alcoholic fatty liver disease using B-mode ultrasound hepatorenal window images with liver biopsy as the gold standard.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
BACKGROUND/INTRODUCTION: To evaluate the performance of pre-trained deep learning schemes (DLS) in hepatic steatosis (HS) grading of Non-Alcoholic Fatty Liver Disease (NAFLD) patients, using as input B-mode US images containing right kidney (RK) cort...

Pediatric Liver Transplant Pathology: An Update and Practical Consideration.

Surgical pathology clinics
This review provides a summary of the diagnostic approach to pediatric liver transplantation (LT) pathology. It emphasizes the pathologic features of T-cell-mediated rejection, the most common finding on liver allograft biopsies, and discusses other ...

Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment.

Scientific reports
This bicenter retrospective analysis included 162 patients who had undergone prostate biopsy following prebiopsy MRI, excluding those with PCa identified only in the peripheral zone (PZ). DLR T2WI achieved a 69% reduction in scan time relative to TSE...

Clinical validation of an AI-based pathology tool for scoring of metabolic dysfunction-associated steatohepatitis.

Nature medicine
Metabolic dysfunction-associated steatohepatitis (MASH) is a major cause of liver-related morbidity and mortality, yet treatment options are limited. Manual scoring of liver biopsies, currently the gold standard for clinical trial enrollment and endp...