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Volume 5
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10.18383/j.tom.2018.00041
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Tomography is published by MDPI from Volume 7 Issue 1 (2021). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with Grapho, LLC.
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Article

Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO)

by
Laura C. Bell
1,*,
Natenael Semmineh
1,
Hongyu An
2,
Cihat Eldeniz
2,
Richard Wahl
2,
Kathleen M. Schmainda
3,
Melissa A. Prah
3,
Bradley J. Erickson
4,
Panagiotis Korfiatis
4,
Chengyue Wu
5,
Anna G. Sorace
5,
Thomas E. Yankeelov
5,
Neal Rutledge
5,
Thomas L. Chenevert
6,
Dariya Malyarenko
6,
Yichu Liu
7,
Andrew Brenner
7,
Leland S. Hu
8,
Yuxiang Zhou
8,
Jerrold L. Boxerman
9,10,
Yi-Fen Yen
11,
Jayashree Kalpathy-Cramer
11,
Andrew L. Beers
11,
Mark Muzi
12,
Ananth J. Madhuranthakam
13,
Marco Pinho
13,
Brian Johnson
13,14 and
C. Chad Quarles
1add Show full author list remove Hide full author list
1
Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ 85013, USA; [email protected]
2
Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
3
Departments of Radiology and Biophysics, Medical College of Wisconsin, Wauwatosa, WI, USA
4
Department of Radiology, Mayo Clinic, Rochester, MN, USA
5
Department of Diagnostic Medicine, University of Texas at Austin, Austin, TX, USA
6
Department of Radiology, University of Michigan, Ann Arbor, MI, USA
7
UT Health San Antonio, San Antonio, TX, USA
8
Department of Radiology, Mayo Clinic, Scottsdale, AZ, USA
9
Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI, USA
10
Alpert Medical School of Brown University, Providence, RI, USA
11
Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
12
Department of Radiology, University of Washington, Seattle, WA, USA
13
UT Southwestern Medical Center, Dallas, TX, USA
14
Philips Healthcare, Gainesville, FL, USA
 
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*
Author to whom correspondence should be addressed.
Tomography 2019, 5(1), 110-117; https://doi.org/10.18383/j.tom.2018.00041
Submission received: 12 December 2018 / Revised: 4 January 2019 / Accepted: 3 February 2019 / Published: 1 March 2019
Versions Notes

Abstract

The use of rCBV as a response metric in clinical trials has been hampered, in part, due to variations in the biomarker consistency and associated interpretation across sites, stemming from differences in image acquisition and post-processing methods. This study leveraged a dynamic susceptibility contrast magnetic resonance imaging digital reference object to characterize rCBV consistency across 12 sites participating in the Quantitative Imaging Network (QIN), specifically focusing on differences in site-specific imaging protocols (IPs; n = 17), and PMs (n = 19) and differences due to site-specific IPs and PMs (n = 25). Thus, high agreement across sites occurs when 1 managing center processes rCBV despite slight variations in the IP. This result is most likely supported by current initiatives to standardize IPs. However, marked intersite disagreement was observed when site-specific software was applied for rCBV measurements. This study's results have important implications for comparing rCBV values across sites and trials, where variability in PMs could confound the comparison of therapeutic effectiveness and/or any attempts to establish thresholds for categorical response to therapy. To overcome these challenges and ensure the successful use of rCBV as a clinical trial biomarker, we recommend the establishment of qualifying and validating site- and trial-specific criteria for scanners and acquisition methods (eg, using a validated phantom) and the software tools used for dynamic susceptibility contrast magnetic resonance imaging analysis (eg, using a digital reference object where the ground truth is known).
Keywords: DSC-MRI; relative cerebral blood volume; standardization; multisite consistency; reproducibility DSC-MRI; relative cerebral blood volume; standardization; multisite consistency; reproducibility

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MDPI and ACS Style

Bell, L.C.; Semmineh, N.; An, H.; Eldeniz, C.; Wahl, R.; Schmainda, K.M.; Prah, M.A.; Erickson, B.J.; Korfiatis, P.; Wu, C.; et al. Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO). Tomography 2019, 5, 110-117. https://doi.org/10.18383/j.tom.2018.00041

AMA Style

Bell LC, Semmineh N, An H, Eldeniz C, Wahl R, Schmainda KM, Prah MA, Erickson BJ, Korfiatis P, Wu C, et al. Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO). Tomography. 2019; 5(1):110-117. https://doi.org/10.18383/j.tom.2018.00041

Chicago/Turabian Style

Bell, Laura C., Natenael Semmineh, Hongyu An, Cihat Eldeniz, Richard Wahl, Kathleen M. Schmainda, Melissa A. Prah, Bradley J. Erickson, Panagiotis Korfiatis, Chengyue Wu, and et al. 2019. "Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO)" Tomography 5, no. 1: 110-117. https://doi.org/10.18383/j.tom.2018.00041

APA Style

Bell, L. C., Semmineh, N., An, H., Eldeniz, C., Wahl, R., Schmainda, K. M., Prah, M. A., Erickson, B. J., Korfiatis, P., Wu, C., Sorace, A. G., Yankeelov, T. E., Rutledge, N., Chenevert, T. L., Malyarenko, D., Liu, Y., Brenner, A., Hu, L. S., Zhou, Y., ... Quarles, C. C. (2019). Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO). Tomography, 5(1), 110-117. https://doi.org/10.18383/j.tom.2018.00041

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