Changes in apparent diffusion coefficient radiomics features during dose-painted radiotherapy and high dose rate brachytherapy for prostate cancer. (January 2019)

• Record Type: Journal Article
• Authors: Lee, Sangjune Laurence; Lee, Jenny; Craig, Tim; Berlin, Alejandro; Chung, Peter; Ménard, Cynthia; Foltz, Warren D.
• Is Part Of: Physics and imaging in radiation oncology. Volume 9(2019)
• Page Start: 1
• Page End: 6
• Publication Date: 2019-01
• Subjects: Diffusion-weighted MRI -- Apparent diffusion coefficient -- Radiomics -- Prostate cancer -- Dose-painted radiotherapy -- High dose rate brachytherapy; Radiotherapy -- Periodicals; Radiation dosimetry -- Periodicals; Cancer -- Imaging -- Periodicals; Oncology -- Periodicals; 615.842
• DOI: 10.1016/j.phro.2018.11.006
• Languages: English
• ISSNs: 2405-6316

Abstract

Abstract: Background and purpose: Dose escalation has improved cancer outcomes for patients with localized prostate cancer. Targeting subprostatic tumor regions for dose intensification may further improve outcomes. Apparent Diffusion Coefficient (ADC) maps may enable early radiation response assessment and dose adaptation. This study was a proof-of-principle investigation of early changes in ADC radiomics features for patients undergoing radiotherapy with dose escalation to the gross tumor volume (GTV). Materials and methods: Fifty-nine patients were enrolled on a prospective tumor dose-escalation trial. Multi-parametric MRI was performed at baseline and week six, corresponding to the time of peak ADC change. GTV and prostate contours were deformably registered between baseline and week six T2-weighted images, and applied to ADC maps, to account for diminished image contrast post-EBRT and possible differences in prostate gland volume, shape, and orientation. A total of 101 radiomics features were tested for significant change post-EBRT using two-tailed Student's t -test. All ADC features of the prostate and GTV volumes were correlated using Pearson's coefficient (p < 0.00008, based on Bonferroni correction). Results: ADC feature extraction was insensitive to b = 0 s/mm 2 exclusion, and to gradient non-linearity bias. GTV presented predominant changes in first-order features, particularly 10Percentile, and prostate volumes presented predominant changes in second-order features. Changes in both first and second-order features of GTV and prostate ROIs were strongly correlated. Conclusions: Our data confirmed significant changes in numerous GTV and prostate features assessed from ADC and T2-weighted images during radiotherapy; all of which may be potential biomarkers of early radiation response.