Identification of histological features of endometrioid adenocarcinoma based on amide proton transfer-weighted imaging and multimodel diffusion-weighted imaging

Quantitative Imaging in Medicine and Surgery

article

Fangfang Fu¹  Nan Meng¹  Zhun Huang⁴  Jing Sun⁵  Xuejia Wang³  Jie Shang⁶  Ting Fang¹  Pengyang Feng⁴  Kaiyu Wang⁷  Dongming Han³  Meiyun Wang¹ 

[1] Department of Medical Imaging , Henan Provincial People’s Hospital & Zhengzhou University People’s Hospital;Academy of Medical Sciences , Zhengzhou University;Department of MR, the First Affiliated Hospital, Xinxiang Medical University;Department of Medical Imaging , Henan University People’s Hospital & Henan Provincial People’s Hospital;Department of Pediatrics, Zhengzhou Central Hospital , Zhengzhou University;Department of Pathology, the First Affiliated Hospital, Xinxiang Medical University;MR Research China , GE Healthcare

关键词: Amide proton transfer-weighted imaging (APTWI);    endometrial adenocarcinoma (EA);    diffusion-weighted imaging (DWI);   

DOI  :  10.21037/qims-21-189

学科分类：外科医学

来源: AME Publications

【 摘 要 】

Background: Noninvasive identification of the histological features of endometrioid adenocarcinoma is necessary. This study aimed to investigate whether amide proton transfer-weighted imaging (APTWI) and multimodel (monoexponential, biexponential, and stretched exponential) diffusion-weighted imaging (DWI) could predict the histological grade of endometrial adenocarcinoma (EA). In addition, we analyzed the correlation between each parameter and the Ki-67 index. Methods: A total of 90 EA patients who received pelvic magnetic resonance imaging (MRI) were enrolled. 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), and water molecular diffusion heterogeneity index (α) were measured and compared. Correlation coefficients between each parameter and histological grade and the Ki-67 index were calculated. Statistical methods included the independent samples t test, Spearman’s correlation, and logistic regression. Results: MTRasym (3.5 ppm) [(3.72%±0.31%) vs. (3.27%±0.48%)], f [(3.15%±0.36%) vs. (2.69%±0.83%)], and α [(0.89±0.05) vs. (0.81±0.09)] were higher and ADC [(0.82±0.08) vs. (0.89±0.10) ×10−3 mm2/s], D [(0.67±0.09) vs. (0.81±0.11) ×10−3 mm2/s], and DDC [(1.04±0.09) vs. (1.13±0.13) ×10−3 mm2/s] were lower in high-grade EA than in low-grade EA (P<0.05). MTRasym (3.5 ppm) and D were independent predictors for the histological grade of EA. The combination of MTRasym (3.5 ppm) and D were better able to identify high- and low-grade EA than was each parameter. MTRasym (3.5 ppm) and α were moderately and weakly positively correlated, respectively, with histological grade and the Ki-67 index (r=0.528, r=0.514, r=0.395, and r=0.367; P<0.05). D was moderately negatively correlated with histological grade and the Ki-67 index (r=–0.540 and r=–0.529; P<0.05). DDC was weakly and moderately negatively correlated with histological grade and the Ki-67 index, respectively (r=–0.473 and r=–0.515; P<0.05). ADC was weakly negatively correlated with histological grade and the Ki-67 index (r=–0.417 and r=–0.427; P<0.05). f was weakly positively correlated with histological grade and the Ki-67 index (r=0.294 and r=0.355; P<0.05). Conclusions: Our study found that both multimodel DWI and APTWI could be used to estimate the histological grade and Ki-67 index of EA, and the combination of high MTRasym (3.5 ppm) and low D may be an effective imaging marker for predicting the grade of EA.

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