Whole-body diffusion-weighted imaging for staging lymphoma: are apparent diffusion coefficient derived histogram parameters useful for lesion characterisation?
© De Paepe et al; licensee BioMed Central Ltd. 2014
Published: 9 October 2014
To evaluate apparent diffusion coefficient (ADC) derived histogram parameters for lesion characterization in whole-body diffusion-weighted imaging (WB-DWI) of lymphoma.
Fifteen patients with histopathology proven lymphoma (11 Non-Hodgkin; 4 Hodgkin lymphomas) underwent WB-DWI using 2 b-values (0-1000 s/mm2). On coronal reformatted b1000 WB-DWI images, regions of interest (ROI) were drawn semi-automatically on lymph nodes in all nodal stations (n=267) and in axial and appendicular bone regions (n=53). For each ROI, a histogram was constructed from which volume, mean(ADC), median(ADC), skewness(ADC), and kurtosis(ADC) were calculated. Mann-Whitney-U tests were performed to detect significant differences between malignant and benign ROIs per tissue type. Receiver-operating-characteristic curves (ROC) were constructed from which an optimal threshold was determined as well as sensitivity, specificity and accuracy. PET/CT plus bone marrow biopsy (BMB) served as reference standard.
All parameters were significantly different between malignant and benign lymph nodes (p<0.001) with skewness(ADC) being the most accurate. A positive skewness exceeding 0.3041 mm2/s allowed for detection of malignant lymph nodes with 88% accuracy, 88% sensitivity and 87% specificity compared to 63% accuracy, 61% sensitivity and 64% specificity for mean(ADC). Only kurtosis(ADC) (p<0.001) and skewness(ADC) (p=0.003) were significantly different between malignant bone marrow infiltration and normal bone marrow. Kurtosis(ADC) showed highest accuracy and a threshold exceeding 5.26 allowed for detection of malignant bone marrow infiltration with 89% accuracy, 86% sensitivity and 90% specificity.
ADC histogram analysis is feasible for lesion characterization in WB-DWI of lymphoma. Lymph nodes were most accurately characterized using skewness(ADC) and bone tissue using kurtosis(ADC).
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.