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A multi‐Gaussian model for apparent diffusion coefficient histogram analysis of Wilms’ tumour subtype and response to chemotherapy
Author(s) -
Hales Patrick W.,
Olsen Øystein E.,
Sebire Neil J.,
PritchardJones Kathy,
Clark Chris A.
Publication year - 2015
Publication title -
nmr in biomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 114
eISSN - 1099-1492
pISSN - 0952-3480
DOI - 10.1002/nbm.3337
Subject(s) - effective diffusion coefficient , stromal cell , medicine , chemotherapy , histopathology , wilms tumour , nephrectomy , pathology , diffusion mri , proportional hazards model , wilms' tumor , nuclear medicine , oncology , radiology , magnetic resonance imaging , kidney
Wilms’ tumours (WTs) are large heterogeneous tumours, which typically consist of a mixture of histological cell types, together with regions of chemotherapy‐induced regressive change and necrosis. The predominant cell type in a WT is assessed histologically following nephrectomy, and used to assess the tumour subtype and potential risk. The purpose of this study was to develop a mathematical model to identify subregions within WTs with distinct cellular environments in vivo , determined using apparent diffusion coefficient (ADC) values from diffusion‐weighted imaging (DWI). We recorded the WT subtype from the histopathology of 32 tumours resected in patients who received DWI prior to surgery after pre‐operative chemotherapy had been administered. In 23 of these tumours, DWI data were also available prior to chemotherapy. Histograms of ADC values were analysed using a multi‐Gaussian model fitting procedure, which identified ‘subpopulations’ with distinct cellular environments within the tumour volume. The mean and lower quartile ADC values of the predominant viable tissue subpopulation (ADC 1MEAN , ADC 1LQ ), together with the same parameters from the entire tumour volume (ADC 0MEAN , ADC 0LQ ), were tested as predictors of WT subtype. ADC 1LQ from the multi‐Gaussian model was the most effective parameter for the stratification of WT subtype, with significantly lower values observed in high‐risk blastemal‐type WTs compared with intermediate‐risk stromal, regressive and mixed‐type WTs ( p < 0.05). No significant difference in ADC 1LQ was found between blastemal‐type and intermediate‐risk epithelial‐type WTs. The predominant viable tissue subpopulation in every stromal‐type WT underwent a positive shift in ADC 1MEAN after chemotherapy. Our results suggest that our multi‐Gaussian model is a useful tool for differentiating distinct cellular regions within WTs, which helps to identify the predominant histological cell type in the tumour in vivo . This shows potential for improving the risk‐based stratification of patients at an early stage, and for guiding biopsies to target the most malignant part of the tumour. Copyright © 2015 John Wiley & Sons, Ltd.