Focused ROI-based ADC assessment is practical, reproducible, contrast-free, and may improve risk stratification, surgical planning, and individualized management, especially where molecular testing is limited.
Abstract
Background/objectives Magnetic resonance imaging (MRI) is essential for preoperative assessment of endometrial carcinoma. Diffusion-weighted imaging (DWI)-derived apparent diffusion coefficient (ADC) values are being explored as quantitative, non-invasive biomarkers of tumor biology and aggressiveness. This study assessed the performance and interobserver reproducibility of ADC measurements for predicting prognostic factors. Methods This study was conducted from June 2023 to June 2025 and included histologically confirmed endometrial carcinoma patients who underwent preoperative pelvic MRI. Patients with 3 T MRI outside the institute or unfit for primary surgery were excluded. Two radiologists independently measured focused-region and whole-lesion ADC values. Interobserver agreement was assessed using paired t-tests and Bland–Altman analysis. Associations with histopathological prognostic factors were assessed using Pearson's coefficient. MRI and histopathological staging concordance was measured using weighted Cohen's kappa. ROC and ANOVA assessed diagnostic performance. Results Fifty-one patients were included, with endometrioid adenocarcinoma being the predominant histological subtype (92.2%). The mean ADC was 747.13 × 10−6 mm2/s. MRI staging showed excellent agreement with histopathology (weighted κ = 0.866). Focused-ROI ADC demonstrated no significant interobserver variability, whereas whole-lesion ADC showed significant interobserver variation. Lower ADC values were associated with serous histology and deep myometrial invasion. ADC significantly differentiated tumor grade, myometrial invasion, and histological subtype. ROC analysis demonstrated good diagnostic performance of focused ADC for tumor grade and pelvic lymph-node involvement. Conclusion Focused ROI-based ADC assessment is practical, reproducible, contrast-free, and may improve risk stratification, surgical planning, and individualized management, especially where molecular testing is limited.
The updated 2023 FIGO staging for endometrial cancer (EC) integrates histopathologic and molecular variables to optimize risk stratification. Preoperative Magnetic resonance imaging (MRI) is the key imaging tool for evaluating key prognostic factors. We aimed to evaluate the performance of diffusion-tensor imaging (DTI...
Asmaa Elshiha, Amir M.Ali, M. Elbakry et al.· The Egyptian Journal of Radi...· 0 citations
The established cutoff reliably distinguishes malignancy, while the inverse correlation between ADC values and tumor grade provides critical preoperative intelligence to guide the extent of surgical staging.
Kamleshwar Ratre, Manish Kumar, Priya Singh et al.· Annals of African medicine· 0 citations
While conventional MRI provides excellent anatomical delineation of brain tumors, it remains fundamentally limited in predicting cellularity or histological grade preoperatively. Apparent diffusion coefficient (ADC) values, derived from diffusion-weighted imaging (DWI), quantify microscopic water mobility, serving as a...
M. Monis, Atul Kumar, Sayeedul Hasan Arif et al.· The Egyptian Journal of Radi...· 0 citations
Background Preoperative differentiation between phyllodes tumors (PTs) and breast cancers (BCs) remains a clinical challenge due to their overlapping imaging characteristics. The aim of this study was to evaluate the diagnostic performance of multiparametric magnetic resonance imaging (MRI), incorporating morphological...
Zi-Fan Wei, Han-Yan Hu, Yun-Shu Dai et al.· Quantitative Imaging in Medi...· 0 citations
OBJECTIVES
To evaluate the performance of nomograms combining clinical factors, apparent diffusion coefficient (ADC), and radiomics features from functional MRI parametric maps in predicting deep myometrial invasion (DMI), high histopathological grade, and lymphovascular space invasion (LVSI) in early endometrial cance...
Ying-Ying Cui, Xuan Yu, Ze-Jun Wen et al.· Magnetic Resonance Imaging· 0 citations
Prostate cancer (PCa) is the second most commonly diagnosed malignancy in men worldwide. Accurate pre-biopsy characterization of prostatic lesions remains a clinical challenge. Multiparametric magnetic resonance imaging (mpMRI), interpreted using Prostate Imaging-Reporting and Data System (PI-RADS) v2.1, has emerge...
Atharva Nitin Deshmukh, Krushna Chandra Biswal, Sangram Panda et al.· Journal of Integrative Medic...· 0 citations
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