Diffusion-weighted MRI for assessment of early cancer treatment response

Abstract

Recent clinical practice for the management for cancer patients has begun to change from a statistical "one-size fits all" approach to medicine to more individualized care. Pre-treatment biomarkers (i.e. genetically and histologically based) have a growing role in providing guidance related to the appropriate therapy and likelihood of response; they do not take into account heterogeneity within the tumor mass. Thus, a biomarker which could be utilized to measure actual tumor response early following treatment initiation would provide an important opportunity to evaluate treatment effects on an individual patient basis. Diffusion weighted magnetic resonance imaging (DW-MRI) offers the opportunity to monitor treatment-associated alterations in tumor microenvironment using quantification of changes in tumor water diffusion values as a surrogate imaging biomarker. Results obtained thus far using DW-MRI have shown that changes in tumor diffusion values can be detected early following treatment initiation which correlate with traditional outcome measures. Sensitive imaging biomarkers are providing for the first time a means of assessing 3 dimensional tumor response early in the treatment cycle. This review highlights the development of DW-MRI and its proposed usefulness in the clinical management of cancer patients. The utility of DW-MRI for assessing therapeutic-induced response is further evaluated on tumors residing in the brain, head and neck and bone.

Figure 1

A schematic of the change in cellularity (left) and increased molecular water mobility measured as an apparent diffusion coefficient (ADC; right) as a tumor responds to treatment (top to bottom). For a tumor responding to therapy, an increase in extracellular space/membrane permeability allows greater water mobility and an increase in the ADC. (Reprint from Ref. [12] with permission from Journal of Clinical Oncology)

Figure 2

Pictorial description of the functional diffusion map (fDM) analytical process. DW-MRI data undergo digital image postprocessing and analysis that involves coregistration of images before and during treatment. Data are used to generate a three-color overlay representing regions in which tumor ADC values are unchanged (green voxels), significantly increased (red voxels), or significantly decreased (blue voxels). This data can also be presented in a scatter plot and percentages assigned to the three defined ADC regions, allowing quantitative assessment of overall changes in tumor ADC values. (Reprint from Ref. [17] with permission from PNAS)

Figure 3

Representative functional diffusion map (fDM) analysis over time. Functional diffusion maps at 1, 3, and 10 weeks for two patients treated with fractionated radiation therapy. The patient on the left was scored as responsive by fDM at 3 weeks but progressive disease by radiologic response at week 10 and had overall survival (OS) of more than 33 months. The patient on the right was scored as nonresponsive by fDM at 3 weeks but stable disease by Macdonald criteria and OS of 7 months. Depicted images are single slices of the T1 postcontrast scans at each time point with a pseudocolor overlay of the fDM. Red voxels indicate regions with a significant rise in apparent diffusion coefficient (ADC) at each time point compared with pretreatment, green regions had unchanged ADC, and blue voxels indicate areas of significant decline in ADC. The scatter plots display data for the entire tumor volume and not just for the depicted slice at each time point, with the pretreatment ADC on the x-axis and post-treatment ADC on the y-axis. The central red line represents unity, and the flanking blue lines represent the 95% CIs. (Reprint from Ref. [30] with permission from Journal of Clinical Oncology)

Figure 4

Representative slices of fDM for patients whose conditions were diagnosed as (A) CR and (B) PR; color-coded VOIs are overlaid on contrast-enhanced T1-weighted MR images before therapy and corresponding scatter plots for quantification and distribution of ADC before and 3 weeks after treatment initiation for the entire tumor volume. Unity and threshold designating significant change in ADC within the scatter plot are presented by red and black lines, respectively. Voxels with significant increased, decreased, or unchanged ADC values were assigned as red, blue, and green, respectively. (Reprint from Ref. [33] with permission from Translational Oncology)

Figure 5

Regional changes of ADC generated from fDM analysis are plotted on the image to provide a visual representation of areas with increased ADC (red voxels), decreased ADC (blue voxels), and areas where ADC did not change significantly (green voxels). fDM analysis of the femoral head lesion at (A) 2 and (B) 8 weeks after treatment initiation revealed distinct regions of red voxels signifying areas with significant increases in ADC (>26 ×10⁵ mm²/s). fDM analysis of the sacral lesion at (C) 2 and (D) 8 weeks after treatment revealed significant regions of increased ADC as depicted by the red voxels. fDM analysis of the ilium lesion at (E) 2 and (F) 8 weeks after treatment show large regions of increased ADC values (red voxels). (Reprint from Ref. [35] with permission from Neoplasia)