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  • Title: Predicting Grade of Esophageal Squamous Carcinoma: Can Stretched Exponential Model-Based DWI Perform Better Than Bi-Exponential and Mono-Exponential Model?
    Author: Yang H, Ge X, Zheng X, Li X, Li J, Liu M, Zhu J, Qin J.
    Journal: Front Oncol; 2022; 12():904625. PubMed ID: 35912203.
    Abstract:
    BACKGROUND: To evaluate and compare the potential performance of various diffusion parameters obtained from mono-exponential model (MEM)-, bi-exponential model (BEM)-, and stretched exponential model (SEM)-based diffusion-weighted imaging (DWI) in grading of esophageal squamous carcinoma (ESC). METHODS: Eighty-two patients with pathologically confirmed ESC without treatment underwent multi-b-value DWI scan with 13 b values (0~12,00 s/mm2). The apparent diffusion coefficient (ADC) deriving from the MEM; the pure molecular diffusion (ADCslow), pseudo-diffusion coefficient (ADCfast), perfusion, and fraction (f) deriving from the BEM; and the distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) deriving from the SEM were calculated and compared between poorly differentiated and well/moderately differentiated ESC, respectively. The prediction parameters and diagnostic efficiency were compared by drawing receiver operating characteristic (ROC) curves. RESULTS: The ADC, ADCslow, ADCfast, and DDC in poorly ESC were significantly lower than those in well/moderately differentiated ones. By using only one parameter, ADCslow, DDC had the moderate diagnostic efficiency and the areas under the curve (AUC) were 0.758 and 0.813 in differentiating ESC. The DDC had the maximum AUC with sensitivity (88.00%) and specificity (68.42%). Combining ADC with ADCfast, ADCslow, and DDC and combining ADCslow with ADCfast can provide a higher diagnostic accuracy with AUC ranging from 0.756, 0.771, 0.816, and 0.793, respectively. CONCLUSION: Various parameters derived from different DWI models including MEM, BEM, and SEM were potentially helpful in grading ESC. DDC obtained from SEM was the most promising diffusion parameter for predicting the grade of ESC.
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