Contributions
Abstract: EP1439
Type: ePoster
Abstract Category: Pathology and pathogenesis of MS - Imaging
Background: Normalization of brain atrophy in MS patients has been proposed as a treatment goal. An ideal image analysis tool for individualized brain volume monitoring would detect important change while minimizing occurrence of false positive changes that could prompt inappropriate treatment changes. EdgeFlow is a novel, in-house developed software tool that is designed to minimize spurious sources of variability in estimates of brain volume.
Hypothesis: When compared with SIENA, we hypothesize EdgeFlow will offer correlated but likely numerically lower measures of brain atrophy in large groups. We expect instances of discordance between the two techniques.
Methods: 421 patients with 882 MRI scans from single and multicenter MRI datasets were analyzed with both SIENA and EdgeFlow. Pearson Correlations were calculated. The dataset includes diversity in patient cohort (Healthy Controls, RRMS, CIS), MRI scanner, slice thickness, image quality, presence of gadolinium and scan interval. Four MS patients with longitudinal data at the same clinic and MRI scanner were also analyzed to look at individual performance.
Results: In studies of RRMS, the estimated Percent Brain Volume Change (PBVC) and standard deviations were generally smaller with EdgeFlow with Pearson Correlations ranging from 0.767 to 0.883. For example, in the largest study of 187 RRMS patients scanned at 66 sites, SIENA and EdgeFlow computed mean PBVCs (SD) over two years of ‑1.32% (1.80) and ‑1.04% (1.23), respectively with a Pearson coefficient of 0.883 (p < 0.00001). In a study of 69 CIS patients scanned at 11 sites, SIENA and EdgeFlow computed mean PBVCs (SD) of ‑0.60% (0.66) and ‑0.53% (0.44) respectively over one year with a Pearson coefficient of 0.636 (p < 0.00001). Discordance between SIENA and EdgeFlow occurred. In 158 scans where the disparity in PBVC was >0.5%, EdgeFlow provided the lower value in 131 scans (83%). In individual patients followed longitudinally, the Pearson correlation between EdgeFlow and SIENA were strong individually (0.61-0.98) and as a group (0.84).
Conclusions: Both EdgeFlow and SIENA can detect significant PBVC changes within 1 year with good agreement. In cohorts, EdgeFlow produces lower estimations of change with a generally narrower standard deviation. Using EdgeFlow rather than SIENA may decrease the chance of reporting false positive changes when monitoring individual patients in clinical practice.
Disclosure:
Philippe Beauchemin: Consulting fees: Novartis, EMD Serono.
Robert Carruthers: Grants/Research Support: Site PI for studies funded by MedImmune, Teva and Guthy Jackson; Speakers Bureau/Honoraria: Speaking fees for unbranded lectures from Biogen, Genzyme and Teva; Consulting Fees: Novartis, EMD Serono, Genzyme.
Roger Tam: Nothing to disclose.
Jon McAusland: Nothing to disclose.
Andrew Riddehough: Nothing to disclose.
David Li: has received research funding from the Canadian Institute of Health Research and Multiple Sclerosis Society of Canada. He is the Director of the UBC MS/MRI Research Group which has been contracted to perform central analysis of MRI scans for therapeutic trials with Novartis, Perceptives, Roche and Sanofi-Aventis. The UBC MS/MRI Research Group has also received grant support for investigator-initiated independent studies from Genzyme, Merck-Serono, Novartis and Roche. He has acted as a consultant to Vertex Pharmaceuticals and served on the Data and Safety Advisory Board for Opexa Therapeutics and Scientific Advisory Boards for Adelphi Group, Novartis and Roche. He has also given lectures which have been supported by non-restricted education grants from Novartis and Biogen.
Rick White: Nothing to disclose.
Anthony Traboulsee: is a consultant for Novartis, Genzyme, Roche and a principal investigator on clinical trials with Biogen, Genzyme, Roche, and Chugai.
EdgeFlow development and BraVo pilot project were funded by Novartis Canada Inc.
Abstract: EP1439
Type: ePoster
Abstract Category: Pathology and pathogenesis of MS - Imaging
Background: Normalization of brain atrophy in MS patients has been proposed as a treatment goal. An ideal image analysis tool for individualized brain volume monitoring would detect important change while minimizing occurrence of false positive changes that could prompt inappropriate treatment changes. EdgeFlow is a novel, in-house developed software tool that is designed to minimize spurious sources of variability in estimates of brain volume.
Hypothesis: When compared with SIENA, we hypothesize EdgeFlow will offer correlated but likely numerically lower measures of brain atrophy in large groups. We expect instances of discordance between the two techniques.
Methods: 421 patients with 882 MRI scans from single and multicenter MRI datasets were analyzed with both SIENA and EdgeFlow. Pearson Correlations were calculated. The dataset includes diversity in patient cohort (Healthy Controls, RRMS, CIS), MRI scanner, slice thickness, image quality, presence of gadolinium and scan interval. Four MS patients with longitudinal data at the same clinic and MRI scanner were also analyzed to look at individual performance.
Results: In studies of RRMS, the estimated Percent Brain Volume Change (PBVC) and standard deviations were generally smaller with EdgeFlow with Pearson Correlations ranging from 0.767 to 0.883. For example, in the largest study of 187 RRMS patients scanned at 66 sites, SIENA and EdgeFlow computed mean PBVCs (SD) over two years of ‑1.32% (1.80) and ‑1.04% (1.23), respectively with a Pearson coefficient of 0.883 (p < 0.00001). In a study of 69 CIS patients scanned at 11 sites, SIENA and EdgeFlow computed mean PBVCs (SD) of ‑0.60% (0.66) and ‑0.53% (0.44) respectively over one year with a Pearson coefficient of 0.636 (p < 0.00001). Discordance between SIENA and EdgeFlow occurred. In 158 scans where the disparity in PBVC was >0.5%, EdgeFlow provided the lower value in 131 scans (83%). In individual patients followed longitudinally, the Pearson correlation between EdgeFlow and SIENA were strong individually (0.61-0.98) and as a group (0.84).
Conclusions: Both EdgeFlow and SIENA can detect significant PBVC changes within 1 year with good agreement. In cohorts, EdgeFlow produces lower estimations of change with a generally narrower standard deviation. Using EdgeFlow rather than SIENA may decrease the chance of reporting false positive changes when monitoring individual patients in clinical practice.
Disclosure:
Philippe Beauchemin: Consulting fees: Novartis, EMD Serono.
Robert Carruthers: Grants/Research Support: Site PI for studies funded by MedImmune, Teva and Guthy Jackson; Speakers Bureau/Honoraria: Speaking fees for unbranded lectures from Biogen, Genzyme and Teva; Consulting Fees: Novartis, EMD Serono, Genzyme.
Roger Tam: Nothing to disclose.
Jon McAusland: Nothing to disclose.
Andrew Riddehough: Nothing to disclose.
David Li: has received research funding from the Canadian Institute of Health Research and Multiple Sclerosis Society of Canada. He is the Director of the UBC MS/MRI Research Group which has been contracted to perform central analysis of MRI scans for therapeutic trials with Novartis, Perceptives, Roche and Sanofi-Aventis. The UBC MS/MRI Research Group has also received grant support for investigator-initiated independent studies from Genzyme, Merck-Serono, Novartis and Roche. He has acted as a consultant to Vertex Pharmaceuticals and served on the Data and Safety Advisory Board for Opexa Therapeutics and Scientific Advisory Boards for Adelphi Group, Novartis and Roche. He has also given lectures which have been supported by non-restricted education grants from Novartis and Biogen.
Rick White: Nothing to disclose.
Anthony Traboulsee: is a consultant for Novartis, Genzyme, Roche and a principal investigator on clinical trials with Biogen, Genzyme, Roche, and Chugai.
EdgeFlow development and BraVo pilot project were funded by Novartis Canada Inc.