4.6 Article

Predicting Grade of Esophageal Squamous Carcinoma: Can Stretched Exponential Model-Based DWI Perform Better Than Bi-Exponential and Mono-Exponential Model?

Journal

FRONTIERS IN ONCOLOGY
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2022.904625

Keywords

esophageal squamous carcinoma; magnetic resonance imaging; stretched exponential model; intravoxel incoherent motion; DWI

Categories

Funding

  1. Academic promotion program of Shandong First Medical University [2019QL017]

Ask authors/readers for more resources

This study evaluated and compared the potential performance of various diffusion parameters obtained from different models in diffusion-weighted imaging (DWI) for grading of esophageal squamous carcinoma (ESC). The results showed that the distributed diffusion coefficient (DDC) derived from the stretched exponential model (SEM) was the most promising diffusion parameter for predicting the grade of ESC.
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 similar to 12,00 s/mm(2)). The apparent diffusion coefficient (ADC) deriving from the MEM; the pure molecular diffusion (ADC(slow)), pseudo-diffusion coefficient (ADC(fast)), perfusion, and fraction (f) deriving from the BEM; and the distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (alpha) 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, ADC(slow), ADC(fast), and DDC in poorly ESC were significantly lower than those in well/moderately differentiated ones. By using only one parameter, ADC(slow), 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 ADC(fast), ADC(slow), and DDC and combining ADC(slow) with ADC(fast) 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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available