Abstract
This study investigated the impact of different ROI placement and analysis methods on the diagnostic performance of simplified IVIM-DWI for differentiating liver lesions. 1.5/3.0-T DWI data from a respiratory-gated MRI sequence (b = 0, 50, 250, 800 s/mm2) were analyzed in patients with malignant (n = 74/54) and benign (n = 35/19) lesions. Apparent diffusion coefficient ADC = ADC(0,800) and IVIM parameters D1′ = ADC(50,800), D2′ = ADC(250,800), f1′ = f(0,50,800), f2′ = f(0,250,800), and D*' = D*(0,50,250,800) were calculated voxel-wise. For each lesion, a representative 2D-ROI, a 3D-ROI whole lesion, and a 3D-ROI from “good” slices were placed, including and excluding centrally deviating areas (CDA) if present, and analyzed with various histogram metrics. The diagnostic performance of 2D- and 3D-ROIs was not significantly different; e.g. AUC (ADC/D1′/f1′) were 0.958/0.902/0.622 for 2D- and 0.942/0.892/0.712 for whole lesion 3D-ROIs excluding CDA at 1.5 T (p > 0.05). For 2D- and 3D-ROIs, AUC (ADC/D1′/D2′) were significantly higher, when CDA were excluded. With CDA included, AUC (ADC/D1′/D2′/f1′/D*') improved when low percentiles were used instead of averages, and was then comparable to the results of average ROI analysis excluding CDA. For lesion differentiation the use of a representative 2D-ROI is sufficient. CDA should be excluded from ROIs by hand or automatically using low percentiles of diffusion coefficients.
Highlights
For quantitative analysis of apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) parameter maps in lesions a region of interest (ROI) based approach is the most commonly u sed[28,29,30]
The main findings of the present study were: (1) No significant differences in diagnostic performance were found between 2D- and 3D-ROIs even if only slices with good image quality were included
(2) Differentiation was more accurate when centrally deviating areas were excluded from ROIs. (3) When such areas were included, diagnostic accuracy of diffusion sensitive parameters was improved by histogram analysis of the ROIs using low percentiles instead of mean values
Summary
For quantitative analysis of ADC and IVIM parameter maps in lesions a region of interest (ROI) based approach is the most commonly u sed[28,29,30]. There are different ROI-placement and analysis strategies, Scientific Reports | (2021) 11:22752. Mostly only investigated for ADC: to place the ROIs into areas with most restricted diffusion (“hot spots”, focused ROIs), to average over multiple small ROIs placed into different regions, to place a large ROI on a central slice of a lesion, or to cover the whole lesion[7,21,23]. The purpose of this study was to investigate whether there are differences in the diagnostic accuracy of ADC and IVIM parameters in the discrimination of liver lesions using different ROI placement and analysis strategies. We compared 2D- and 3D-volume ROIs, inclusion and exclusion of central necrosis, cystic components and scars, and ROI analysis by averaging and histogram metrics
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