Increasing the accuracy of volume and ADC delineation for heterogeneous tumor on diffusion-weighted MRI: correlation with PET/CT.

Abstract

To improve the accuracy of volume and apparent diffusion coefficient (ADC) measurements in diffusion-weighted magnetic resonance imaging (MRI), we proposed a method based on thresholding both the b0 images and the ADC maps. In 21 heterogeneous lesions from patients with metastatic gastrointestinal stromal tumors (GIST), gross lesion were manually contoured, and corresponding volumes and ADCs were denoted as gross tumor volume (GTV) and gross ADC (ADC(g)), respectively. Using a k-means clustering algorithm, the probable high-cellularity tumor tissues were selected based on b0 images and ADC maps. ADC and volume of the tissues selected using the proposed method were denoted as thresholded ADC (ADC(thr)) and high-cellularity tumor volume (HCTV), respectively. The metabolic tumor volume (MTV) in positron emission tomography (PET)/computed tomography (CT) was measured using 40% maximum standard uptake value (SUV(max)) as the lower threshold, and corresponding mean SUV (SUV(mean)) was also measured. HCTV had excellent concordance with MTV according to Pearson's correlation (r=0.984, P<.001) and linear regression (slope = 1.085, intercept = -4.731). In contrast, GTV overestimated the volume and differed significantly from MTV (P=.005). ADC(thr) correlated significantly and strongly with SUV(mean) (r=-0.807, P<.001) and SUV(max) (r=-0.843, P<.001); both were stronger than those of ADC(g). The proposed lesion-adaptive semiautomatic method can help segment high-cellularity tissues that match hypermetabolic tissues in PET/CT and enables more accurate volume and ADC delineation on diffusion-weighted MR images of GIST.