# MRI-Based Differentiation of Tumor Deposits and Lymph Node Metastases in Rectal Cancer: A Systematic Review of Diagnostic Performance

**Authors:** Paul-Andrei Stefan, Roxana-Adelina Stefan, Cosmin Caraiani, Lucian Marginean, Thea Diana Brad, Teodora Mocan, Codruta Gherman-Lencu, Dana-Monica Iancu

PMC · DOI: 10.3390/jcm15041390 · 2026-02-10

## TL;DR

This paper reviews how MRI can help distinguish between tumor deposits and lymph node metastases in rectal cancer, finding that combining multiple MRI techniques improves accuracy.

## Contribution

The study systematically evaluates MRI techniques for differentiating tumor deposits from lymph node metastases in rectal cancer.

## Key findings

- Morphology-based MRI showed moderate diagnostic accuracy (AUC 0.72–0.76).
- DCE-MRI and radiomics models improved performance with AUC up to 0.86.
- Multiparametric approaches combining DWI, DCE, and radiomics yielded the highest accuracy.

## Abstract

Background/Objectives: Preoperative discrimination between tumor deposits (TDs) and lymph node metastases (LNMs) in rectal cancer on MRI is clinically critical but remains challenging. Methods: A systematic review following PRISMA guidelines was conducted, including studies using MRI to differentiate TDs from LNMs with histopathology as reference. Performance metrics such as AUC, sensitivity, and specificity were extracted. Results: Four retrospective studies (n = 344 patients) were included. Morphology-based MRI showed moderate diagnostic accuracy (AUC 0.72–0.76), whereas DCE-MRI and radiomics models demonstrated improved performance (AUC up to 0.86). Combined multiparametric approaches integrating DWI, DCE, and radiomics yielded the highest discriminative values. Conclusions: MRI-based multiparametric models improve discrimination between TDs and LNMs in rectal cancer. Integration of functional and morphologic features may enhance staging precision and guide therapy planning.

## Linked entities

- **Diseases:** rectal cancer (MONDO:0006519)

## Full-text entities

- **Genes:** HIF1A (hypoxia inducible factor 1 subunit alpha) [NCBI Gene 3091] {aka HIF-1-alpha, HIF-1A, HIF-1alpha, HIF1, HIF1-ALPHA, MOP1}, TENM1 (teneurin transmembrane protein 1) [NCBI Gene 10178] {aka ODZ1, ODZ3, TEN-M1, TEN1, TNM, TNM1}
- **Diseases:** LNM (MESH:D008207), gastrointestinal malignancies (MESH:D005770), EMVI (MESH:D009361), nodular (MESH:D008224), injury to (MESH:D014947), disease (MESH:D004194), nodal metastases (MESH:D009362), tumor fibrosis (MESH:D005355), TD (MESH:D000079822), adenocarcinoma (MESH:D000230), Cancer (MESH:D009369), nodal (MESH:D013611), Rectal Cancer (MESH:D012004)
- **Chemicals:** gadolinium (MESH:D005682), DCE (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12941611/full.md

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Source: https://tomesphere.com/paper/PMC12941611