Volume 54, Issue 4 pp. 1200-1211
Original Research

Amide Proton Transfer-Weighted Imaging and Multiple Models Diffusion-Weighted Imaging Facilitates Preoperative Risk Stratification of Early-Stage Endometrial Carcinoma

Nan Meng MD

Nan Meng MD

Department of Medical Imaging, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China

Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China

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Ting Fang MS

Ting Fang MS

Department of Medical Imaging, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China

Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China

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Pengyang Feng MS

Pengyang Feng MS

Department of Medical Imaging, Henan University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China

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Zhun Huang MS

Zhun Huang MS

Department of Medical Imaging, Henan University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China

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Jing Sun MS

Jing Sun MS

Department of Pediatrics, Zhengzhou Central Hospital, Zhengzhou University, Zhengzhou, China

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Xuejia Wang MS

Xuejia Wang MS

Department of MR, the First Affiliated Hospital, Xinxiang Medical University, Weihui, China

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Jie Shang MS

Jie Shang MS

Department of Pathology, the First Affiliated Hospital, Xinxiang Medical University, Weihui, China

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Kaiyu Wang MD

Kaiyu Wang MD

MR Research China, GE Healthcare, Beijing, China

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Dongming Han MS

Dongming Han MS

Department of MR, the First Affiliated Hospital, Xinxiang Medical University, Weihui, China

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Meiyun Wang MD

Corresponding Author

Meiyun Wang MD

Department of Medical Imaging, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China

Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China

Address reprint requests to: M.-Y.W., 7 Weiwu Road, Zhengzhou 450000, China. E-mail: [email protected]

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First published: 15 May 2021
Citations: 18

Nan Meng, Ting Fang, and Pengyang Feng contributed equally to this work and should be considered co-first authors.

Abstract

Background

Endometrial carcinoma (EC) risk stratification is generally based on histological assessment. It would be beneficial to perform risk stratification noninvasively by MRI.

Purpose

To investigate the application of amide proton transfer-weighted imaging (APTWI), monoexponential, biexponential, and stretched exponential intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) for the evaluation of risk stratification in early-stage EC.

Study Type

Prospective.

Population

Eighty patients with early-stage EC (47 classified as low risk, 20 as medium risk, and 13 as high risk by histological grade and International Federation of Gynecology and Obstetrics stage).

Field Strength/Sequence

T1-weighted imaging, T2-weighted imaging, IVIM, APTWI, and DKI MRI at 3 T.

Assessment

The magnetization transfer ratio asymmetry (MTRasym [3.5 ppm]), apparent diffusion coefficient (ADC), diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), water molecular diffusion heterogeneity index (α), mean kurtosis (MK), and mean diffusivity (MD) were calculated and compared between low-risk and non-low-risk groups.

Statistical Tests

Individual sample t test, analysis of variance, and logistic regression. A P-value <0.05 was considered statistically significant.

Results

The α, ADC, D, DDC, and MD were significantly higher and the f, MK, and MTRasym (3.5 ppm) were significantly lower in the low-risk group than in the non-low-risk group. The difference in D* between the two groups was not significant (P = 0.289). MTRasym (3.5 ppm), D, and MK were independent predictors of risk stratification. The combination of these three parameters was better able to identify low- and non-low-risk groups than each individual parameter.

Data Conclusion

The IVIM, DKI, and APTWI parameters have potential as imaging markers for risk stratification in early-stage EC.

Level of Evidence

2

Technical Efficacy

Stage 3

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