TY - JOUR
T1 - Increasing the accuracy of volume and ADC delineation for heterogeneous tumor on diffusion-weighted MRI
T2 - Correlation with PET/CT
AU - Gong, Nan Jie
AU - Wong, Chun Sing
AU - Chu, Yiu Ching
AU - Guo, Hua
AU - Huang, Bingsheng
AU - Chan, Queenie
PY - 2013/10/1
Y1 - 2013/10/1
N2 - Purpose 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. Methods and Materials 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 (ADCg), 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 (ADCthr) 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 (SUVmax) as the lower threshold, and corresponding mean SUV (SUVmean) was also measured. Results 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). ADCthr correlated significantly and strongly with SUVmean (r=-0.807, P<.001) and SUVmax (r=-0.843, P<.001); both were stronger than those of ADCg. Conclusions 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.
AB - Purpose 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. Methods and Materials 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 (ADCg), 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 (ADCthr) 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 (SUVmax) as the lower threshold, and corresponding mean SUV (SUVmean) was also measured. Results 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). ADCthr correlated significantly and strongly with SUVmean (r=-0.807, P<.001) and SUVmax (r=-0.843, P<.001); both were stronger than those of ADCg. Conclusions 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.
UR - https://www.scopus.com/pages/publications/84882776072
U2 - 10.1016/j.ijrobp.2013.05.026
DO - 10.1016/j.ijrobp.2013.05.026
M3 - 文章
C2 - 23958150
AN - SCOPUS:84882776072
SN - 0360-3016
VL - 87
SP - 407
EP - 413
JO - International Journal of Radiation Oncology Biology Physics
JF - International Journal of Radiation Oncology Biology Physics
IS - 2
ER -
