Assessment of the correlation between MRI texture analysis findings and histopathological diagnoses in solid liver lesions
Year: 2026
Type: article
Study design: Observational Study
Abstract: Objective: To evaluate the diagnostic value of texture analysis in differentiating benign and malignant liver lesions, as well asdistinguishing primary malignant liver tumors from metastases using pre-contrast magnetic resonance imaging (MRI) sequences.Materials and Methods: This retrospective study included 101 liver lesions from 100 patients who underwent upper abdominal MRIfollowed by biopsy or surgical resection. Texture analysis was performed on pre-contrast T1-weighted (T1W), T2-weighted (T2W),and apparent diffusion coefficient (ADC) sequences using first-order (histogram-based) and second-order (gray level co-occurrencematrix (GLCM)-based) statistical parameters. Group comparisons were conducted using Mann-Whitney U test, with a significancethreshold of p < 0.05. Receiver operating characteristic (ROC) analysis was used to demonstrate the success of texture analysisparameters in distinguishing lesion subtypes.Results: Among 101 lesions, 90 were malignant and 11 were benign. Pre-contrast T1W, first-order parameters—mean, 50th, 90th,and 99th percentiles were significantly lower in malignant lesions compared to benign lesions. Primary malignant tumors andhepatocellular carcinoma (HCC) exhibited higher first-order values than metastatic lesions. Certain second-order parameters frompre-contrast T1W images also showed statistical significance, while ADC and T2W sequences revealed fewer differences.Conclusions: Texture analysis of pre-contrast MRI provides quantitative and objective evaluation of liver lesions, aiding differentiationbetween benign and malignant lesions and between primary and metastatic tumors. Pre-contrast T1W sequences were the mostinformative, highlighting the potential utility of texture analysis for patients unable to receive contrast agents.
Source: Marmara medical journal
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7161983806