2020
DOI: 10.1101/2020.07.25.20162172
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Voxel-level Classification of Prostate Cancer Using a Four-Compartment Restriction Spectrum Imaging Model

Abstract: Purpose: Diffusion MRI is integral to detection of prostate cancer (PCa), but conventional ADC cannot capture the complexity of prostate tissues. A four-compartment restriction spectrum imaging (RSI4) model was recently found to optimally characterize pelvic diffusion signals, and the model coefficient for the slowest diffusion compartment, RSI4-C1, yielded greatest tumor conspicuity. In this study, RSI4-C1 was evaluated as a quantitative voxel-level classifier of PCa. Methods: This was a retrospective analy… Show more

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Cited by 4 publications
(7 citation statements)
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“…A modeling study showed that the four-compartment RSI model used here yielded optimal explanation of diffusion signals within the pelvis and increased conspicuity of prostate cancer tumors 19 . Voxel-level accuracy of RSI rs was superior to that of ADC 20 . Other work established the potential utility of RSI for cancer 17 , found voxel-wise correlation of RSI with Gleason pattern 18 , and better discrimination of PCa from normal tissue than ADC 25 .…”
Section: Discussionmentioning
confidence: 82%
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“…A modeling study showed that the four-compartment RSI model used here yielded optimal explanation of diffusion signals within the pelvis and increased conspicuity of prostate cancer tumors 19 . Voxel-level accuracy of RSI rs was superior to that of ADC 20 . Other work established the potential utility of RSI for cancer 17 , found voxel-wise correlation of RSI with Gleason pattern 18 , and better discrimination of PCa from normal tissue than ADC 25 .…”
Section: Discussionmentioning
confidence: 82%
“…Moving toward quantitative imaging biomarkers is a stated aim of major imaging organizations and research funders, who have noted a paucity of validation studies 13,27 . The RSI approach adopted in the present work incorporates steps toward reproducibility, including distortion correction and normalization 20,28 . We have also demonstrated here the performance of a quantitative metric for cancer detection in a completely independent dataset from that used to develop the model.…”
Section: Discussionmentioning
confidence: 99%
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“…1 ). RSI rs gives improved cancer conspicuity and voxel-level PCa detection compared with the current clinical standard for quantitative DWI, the apparent diffusion coefficient (ADC) [17] , [18] .
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Section: Introductionmentioning
confidence: 99%