Evidence map›Paper›PMID 39641783›Full record

ArticleAbdominal radiology (New York)2025

ZOOMit diffusion kurtosis imaging combined with diffusion weighted imaging for the assessment of microsatellite instability in endometrial cancer.

Fang Wang, Yafei Wang, Chenjiao Ran, Jing Liang, Lisha Qi, Chen Zhang, Zhaoxiang Ye

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Article in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Fang WangTianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Yafei WangTianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Chenjiao RanTianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Jing LiangTianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Lisha QiTianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Chen ZhangSiemens Healthcare, Beijing, China.
Zhaoxiang YeTianjin Medical University Cancer Institute and Hospital, Tianjin, China. zye@tmu.edu.cn.

Funding

Chinese National Key Research and Development Project 2021 YFC2500400Tianjin Key Medical Discipline (Specialty) Construction Project TJYXZDXK-009A
6 · The paper itself

Abstract

purposeDetecting microsatellite instability (MSI) plays a key role in the management of endometrial cancer (EC), as it is a critical predictive biomarker for Lynch syndrome or immunotherapy response. A pressing need exists for cost-efficient, broadly accessible tools to aid patient for universal testing. Herein, we investigate the value of ZOOMit diffusion kurtosis imaging (DKI) and diffusion weighted imaging (DWI) based on preoperative pelvic magnetic resonance imaging (MRI) images in assessing MSI in EC.

methodsPreoperative MRI examination including ZOOMit DKI and DWI of 81 EC patients were retrospectively analyzed. The apparent diffusion coefficient (ADC), mean kurtosis (MK), mean diffusivity (MD) and the largest tumor size based on MRI images, as well as patients' clinicopathological features were compared and analyzed according to different microsatellite statuses.

resultsOf the 81 patients, 59 (72.8%) who were microsatellite stability (MSS) and 22 (27.2%) who were MSI. Interobserver agreement for the quantitative parameter measurements was excellent (ICC 0.78-0.98). The ADC and MD values were significantly lower, while Ki-67 proliferation level and MK values were significantly higher in the MSI group compared to those of the MSS group. The parameters of MD and MK were independent predictors for determining MSI, and their combination showed better diagnostic efficacy with an area under the receiver operating characteristic curve (AUROC) of 0.860 (95% confidence interval, 0.765, 0.927), although there was no significant difference compared to each individual parameter.

conclusionThe microstructural heterogeneity assessment of ZOOMit DKI allowed for characterizing MSI status in EC. Within the current universal MSI testing paradigm, DKI may provide added value as a potential noninvasive imaging biomarker for preoperative assessment of MSI tumors, thereby facilitating clinical decision-making.

Indexed as

Diffusion Magnetic Resonance ImagingEndometrial NeoplasmsMicrosatellite InstabilityAdultAgedAged, 80 and overFemaleHumansMiddle AgedRetrospective StudiesDiffusion magnetic resonance imagingEndometrial cancerMicrosatellite instability

Identifiers

PMID39641783

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.