Use of Diffusion-Weighted MRI (DW-MRI) in the Management of Gynecological Cancer Patients Treated with EBRT and Brachytherapy  

AbstractPurpose: DW-MRI and their derived apparent diffusion coefficient (ADC) maps have been shown to be beneficial in the diagnosis and treatment of various cancer types. This work determines the potential role of DW-MRI and ADC maps in GTV delineation for gynecological cancer patients undergoing external beam radiation therapy (EBRT) and brachytherapy. Our study also looked at the longitudinal changes in DWI/ADC values during the course of external beam treatments, as well as during the five brachytherapy fractions. Methods: The first aspect of this study involved validating the console-derived DW image sets and ADC maps using an in-house Matlab code designed for this purpose. Next, the b-value, which describes the sensitivity of the imaging sequence to diffusion, was optimized through a quantitative and qualitative analysis. The quantitative analysis involved maximizing the contrast-to-noise ratios between the tumor and various structures, including the endocervical canal, endometrium, myometrium, and gluteal subcutaneous fat. The qualitative analysis had two radiation oncologists ranking different DWI sets at various b-values based on tumor conspicuity and total image quality on a scale of 1-5, 1 being the best and 5 being the worst. After determining the optimal b-value for DW image calculation, an analysis of GTV contouring was performed in Medical Image Merge (MIM). This involved a radiation oncologist contouring GTVs on three image sets; axial T2 MRI, axial T2 MRI fused with DWI at b=1300 s/mm2, and axial T2 MRI fused with ADC at b=0, 1000 s/mm2. This was done for 16 patients, 5 of whom had pre-EBRT and pre-brachytherapy scans and 11 of whom had only pre-brachytherapy scans. The contours between the three sets were compared on each scan using the Hausdorff distance, Jaccard index, DICE coefficient, and mean pixel value, all of which were calculated in MIM. The final portion of this study was a longitudinal look at the CTVHRs throughout the course of brachytherapy. The CTVHRs were analyzed on the axial T2 MRI, DWI, and ADC maps. Results: The contrast-to-noise ratios of the endocervical canal, endometrium, myometrium, and gluteal subcutaneous fat all compared to tumor were optimized at either b=1300, 1600, or 1800 s/mm2. DW images at b=1300s/mm2 were ranked the best by both physicians in terms of total image quality and tumor conspicuity for the qualitative analysis for b-value optimization. For GTN analysis, the volumes of the GTVs contoured with the help of the DW images and with the help of the ADC maps were not significantly different (p=0.23404). The Dice coefficients, Hausdorff distances, and Jaccard indices calculated with respect to the reference GTVs were not significantly different between the GTVs contoured with the help of the DW images and the GTVs contoured with the help of the ADC maps. The p-values were 0.84148, 0.56868, and 0.95216, respectively. The volumes of the reference GTVs compared to the volumes of the GTVs contoured with the help of DWI and ADC maps were not statistically significant with p-values of 0.6672 and 0.42372, respectively. The mean pixel values in the reference GTVs compared to the mean pixel values in the GTVs contoured with the help of DWI and ADC maps were not statistically significant with p-values of 0.17384 and 0.68916. The mean pixel values within the GTV contoured with the help of DWI were almost significantly lower than the mean pixel values within the GTV contoured with the help of the ADC maps (p=0.0536). Looking to artifact quantification, no significant artifacts were seen in the axial T2 MRI, DWI, or ADC map outside of the tandem contour in the ice water phantom experiment. In the longitudinal analysis of the CTVHRs, the percent difference between the largest and smallest average of the mean pixel values in Figure 7 is 17.4% with no apparent trend along fractions. The percent difference between the largest and smallest average of the mean pixel values in Figure 8 and Figure 9 are 27.3% and 6.5%, respectively. There is no apparent trend for the average of the mean pixel values when looking at the ADC maps, but the average of mean pixel values decreases throughout the brachytherapy fractions when looking at the DW images. The average standard deviation of the pixel values within each CTVHR on the axial T2 MR and DW image sets generally decreases throughout the course of brachytherapy, while the average standard deviation on ADC generally increases along fractions. However, the percent difference between the largest and smallest average standard deviation on the axial T2 MR image set, the DW image set, and the ADC maps is 18.5%, 43.4%, and 4.9%, respectively. Therefore, while the standard deviation on the ADC maps is generally increasing, it is to a small extent. Conclusion: The results of this study indicate the potential of using ADC maps in tandem with axial T2 MRI to increase the accuracy of GTV delineation in cervical cancer patients undergoing EBRT and brachytherapy. However, a larger sample size is needed to provide more insight into their use during the contouring workflow.