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Article

Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation

by
Panagiotis Korfiatis
1,
Timothy L. Kline
1,
Zachary S. Kelm
1,
Rickey E. Carter
2,
Leland S. Hu
3 and
Bradley J. Erickson
1,*
1
Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905, USA
2
Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55905, USA
3
Department of Radiology, Mayo Clinic, Scottsdale, Arizona 85259, USA
*
Author to whom correspondence should be addressed.
Tomography 2016, 2(4), 448-456; https://doi.org/10.18383/j.tom.2016.00172
Submission received: 3 September 2016 / Revised: 7 October 2016 / Accepted: 10 November 2016 / Published: 1 December 2016

Abstract

Relative cerebral blood volume (rCBV) is a magnetic resonance imaging biomarker that is used to differentiate progression from pseudoprogression in patients with glioblastoma multiforme, the most common primary brain tumor. However, calculated rCBV depends considerably on the software used. Automating all steps required for rCBV calculation is important, as user interaction can lead to increased variability and possible inaccuracies in clinical decision-making. Here, we present an automated tool for computing rCBV from dynamic susceptibility contrast-magnetic resonance imaging that includes leakage correction. The entrance and exit bolus time points are automatically calculated using wavelet-based detection. The proposed tool is compared with 3 Food and Drug Administration-approved software packages, 1 automatic and 2 requiring user interaction, on a data set of 43 patients. We also evaluate manual and automated white matter (WM) selection for normalization of the cerebral blood volume maps. Our system showed good agreement with 2 of the 3 software packages. The intraclass correlation coefficient for all comparisons between the same software operated by different people was >0.880, except for FuncTool when operated by user 1 versus user 2. Little variability in agreement between software tools was observed when using different WM selection techniques. Our algorithm for automatic rCBV calculation with leakage correction and automated WM selection agrees well with 2 out of the 3 FDA-approved software packages.
Keywords: dynamic susceptibility contrast; glioblastoma; atlas segmentation; white matter dynamic susceptibility contrast; glioblastoma; atlas segmentation; white matter

Share and Cite

MDPI and ACS Style

Korfiatis, P.; Kline, T.L.; Kelm, Z.S.; Carter, R.E.; Hu, L.S.; Erickson, B.J. Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation. Tomography 2016, 2, 448-456. https://doi.org/10.18383/j.tom.2016.00172

AMA Style

Korfiatis P, Kline TL, Kelm ZS, Carter RE, Hu LS, Erickson BJ. Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation. Tomography. 2016; 2(4):448-456. https://doi.org/10.18383/j.tom.2016.00172

Chicago/Turabian Style

Korfiatis, Panagiotis, Timothy L. Kline, Zachary S. Kelm, Rickey E. Carter, Leland S. Hu, and Bradley J. Erickson. 2016. "Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation" Tomography 2, no. 4: 448-456. https://doi.org/10.18383/j.tom.2016.00172

APA Style

Korfiatis, P., Kline, T. L., Kelm, Z. S., Carter, R. E., Hu, L. S., & Erickson, B. J. (2016). Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation. Tomography, 2(4), 448-456. https://doi.org/10.18383/j.tom.2016.00172

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