Evidence map›Paper›PMID 42380989›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2026

MRI-based perfusion-diffusion habitat analysis for characterizing intratumoral heterogeneity in rectal adenocarcinoma.

Cui Tang, Jingwen Zhang, Jie Kuang, Wenying Mou, Hua Hao, Dongmei Wu, Yongming Dai

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Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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7 authors.

Cui TangDepartment of Radiology, Yangpu Hospital, School of Medicine, Tongji University, Shanghai, China.
Jingwen ZhangDepartment of Radiology, Yangpu Hospital, School of Medicine, Tongji University, Shanghai, China.
Jie KuangDepartment of Radiology, Yangpu Hospital, School of Medicine, Tongji University, Shanghai, China.
Wenying MouDepartment of Radiology, Yangpu Hospital, School of Medicine, Tongji University, Shanghai, China.
Hua HaoDepartment of Pathology, Yangpu Hospital, School of Medicine, Tongji University, Shanghai, China.
Dongmei WuShanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China.
Yongming DaiDepartment of Radiology, Yangpu Hospital, School of Medicine, Tongji University, Shanghai, China. dymdym118@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to evaluate whether MRI-based perfusion-diffusion habitat imaging derived from dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI) can characterize intratumoral heterogeneity and evaluate associations with pathologic stage, synchronous distant metastasis, and exploratory survival outcomes in rectal adenocarcinoma.

methodsThis retrospective study included 73 patients with pathologically confirmed rectal adenocarcinoma who underwent preoperative DCE-MRI and DWI scans. The volume transfer constant (Ktrans) and apparent diffusion coefficient (ADC) maps were generated from DCE and DWI data, respectively. After manual tumor segmentation and image co-registration, voxel-wise Ktrans and ADC values were clustered using a k-means algorithm to identify distinct spatial habitats. Quantitative metrics extracted from each habitat were compared across pathologic subgroups and entered into multivariable logistic regression models for T staging and association with synchronous distant metastasis.

resultsThree reproducible habitats were identified: Habitat 1, hyper-vasopermeability; Habitat 2, hypo-vasopermeability with hypo-cellularity; and Habitat 3, hypo-vasopermeability with hyper-cellularity. Compared with T1-2 tumors, T3-4 lesions showed significantly higher mean Ktrans and the extracellular-extravascular volume fraction (Ve) in Habitats 1 and 2 and lower mean ADC in Habitats 2 and 3. Multiple perfusion metrics from Habitat 1 significantly correlated with distant metastasis. The optimized logistic regression models achieved AUCs of 0.81 for T staging and 0.78 for distant metastasis prediction.

conclusionCombined DCE-MRI and DWI habitat imaging enables voxel-level assessment of intratumoral heterogeneity in rectal cancer and may provide a noninvasive imaging biomarker for preoperative T staging and assessment of tumor heterogeneity and systemic disease-associated imaging features.

Indexed as

AdenocarcinomaDiffusion Magnetic Resonance ImagingRectal NeoplasmsAgedContrast MediaDynamic Contrast Enhanced Magnetic Resonance ImagingFemaleHumansMaleMiddle AgedNeoplasm StagingPerfusion Magnetic Resonance ImagingRetrospective StudiesContrast MediaDiffusion-weighted imagingDynamic contrast-enhanced perfusionHabitat analysisIntratumoral heterogeneityRectal cancer

Identifiers

PMID42380989
PMCPMC13587470

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