Assessment of the correlation between MRI texture analysis findings and histopathological diagnoses in solid liver lesions

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.

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Publication Details

Journal
Marmara medical journal
Published
2026-05-21
DOI
https://doi.org/10.5472/marumj.1953909
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Assessment of the correlation between MRI texture analysis findings and histopathological diagnoses in solid liver lesions

G Zengin, Rabia Ergelen, Burcu Özdemir, Tahsin Aybal et al.
Marmara medical journal
Radiomics and Machine Learning in Medical Imaging
article

Assessment of the correlation between MRI texture analysis findings and histopathological diagnoses in solid liver lesions

G Zengin, Rabia Ergelen, Burcu Özdemir, Tahsin Aybal, Çiğdem Çelikel
article en

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.

Marmara medical journalVol. 39(2)
Dr Lütfi Kırdar Kartal Eğitim ve Araştırma Hastanesi (TR), Marmara University (TR)
Openalex Percentile: Top 5%
Radiomics and Machine Learning in Medical Imaging
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