Advanced Diffusion MRI in Cervical Cancer: A Comprehensive Review

Advanced diffusion MRI techniques, particularly intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI), have emerged as promising functional imaging tools for improving cervical cancer assessment beyond conventional anatomical MRI. This narrative review summarizes current evidence on the clinical utility of these diffusion-based techniques for tumor characterization, local staging, parametrial invasion, lymph node evaluation, treatment response monitoring, and emerging radiomics applications. Across studies, diffusion-related parameters, especially the apparent diffusion coefficient (ADC) and pure molecular diffusion coefficient (D), tend to be lower in malignant cervical tissues and correlate with increased cellularity, higher tumor grade, and more aggressive disease features. IVIM metrics appear especially useful for differentiating cervical cancer from normal tissue, predicting pelvic lymph node involvement, and detecting early treatment response to chemoradiotherapy or neoadjuvant chemotherapy before substantial morphological regression occurs. In contrast, DTI remains less extensively investigated; however, preliminary findings suggest potential value for evaluating parametrial invasion, stromal disruption, tumor grade, and lymph node metastasis, particularly when integrated with IVIM-derived indices. Although diffusion-derived radiomics may further support risk stratification and treatment-response prediction, the evidence base remains limited by small cohorts, single-center designs, methodological heterogeneity, and insufficient external validation. Overall, IVIM and DTI provide valuable non-invasive insight into cervical cancer biology, but standardized acquisition protocols, reproducible thresholds, and multicenter validation are needed before routine clinical implementation.

Authors

Institutions

Publication Details

Journal
Diagnostics
Published
2026-06-16
DOI
https://doi.org/10.3390/diagnostics16121870
Primary Topic
MRI in cancer diagnosis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Advanced Diffusion MRI in Cervical Cancer: A Comprehensive Review

Ali S. Alyami
Diagnostics
MRI in cancer diagnosis
article

Advanced Diffusion MRI in Cervical Cancer: A Comprehensive Review

Ali S. Alyami
article en

Abstract

Advanced diffusion MRI techniques, particularly intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI), have emerged as promising functional imaging tools for improving cervical cancer assessment beyond conventional anatomical MRI. This narrative review summarizes current evidence on the clinical utility of these diffusion-based techniques for tumor characterization, local staging, parametrial invasion, lymph node evaluation, treatment response monitoring, and emerging radiomics applications. Across studies, diffusion-related parameters, especially the apparent diffusion coefficient (ADC) and pure molecular diffusion coefficient (D), tend to be lower in malignant cervical tissues and correlate with increased cellularity, higher tumor grade, and more aggressive disease features. IVIM metrics appear especially useful for differentiating cervical cancer from normal tissue, predicting pelvic lymph node involvement, and detecting early treatment response to chemoradiotherapy or neoadjuvant chemotherapy before substantial morphological regression occurs. In contrast, DTI remains less extensively investigated; however, preliminary findings suggest potential value for evaluating parametrial invasion, stromal disruption, tumor grade, and lymph node metastasis, particularly when integrated with IVIM-derived indices. Although diffusion-derived radiomics may further support risk stratification and treatment-response prediction, the evidence base remains limited by small cohorts, single-center designs, methodological heterogeneity, and insufficient external validation. Overall, IVIM and DTI provide valuable non-invasive insight into cervical cancer biology, but standardized acquisition protocols, reproducible thresholds, and multicenter validation are needed before routine clinical implementation.

DiagnosticsVol. 16(12)
Jazan University (SA)
Jazan University
Good health and well-being
Openalex Percentile: Top 7%
MRI in cancer diagnosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.