Multisite concordance of DSC-MRI analysis for brain tumors

Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project

K. M. Schmainda, M. A. Prah, S. D. Rand, Y. Liu, B. Logan, M. Muzi, S. D. Rane, X. Da, Y. F. Yen, J. Kalpathy-Cramer, T. L. Chenevert, B. Hoff, B. Ross, Y. Cao, M. P. Aryal, Bradley J Erickson, Panagiotis Korfiatis, T. Dondlinger, L. Bell, Leland S Hu & 2 others P. E. Kinahan, C. C. Quarles

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

BACKGROUND AND PURPOSE: Standard assessment criteria for brain tumors that only include anatomic imaging continue to be insufficient. While numerous studies have demonstrated the value of DSC-MR imaging perfusion metrics for this purpose, they have not been incorporated due to a lack of confidence in the consistency of DSC-MR imaging metrics across sites and platforms. This study addresses this limitation with a comparison of multisite/multiplatform analyses of shared DSC-MR imaging datasets of patients with brain tumors. MATERIALS AND METHODS: DSC-MR imaging data were collected after a preload and during a bolus injection of gadolinium contrast agent using a gradient recalled-echo–EPI sequence (TE/TR 30/1200 ms; flip angle 72°). Forty-nine low-grade (n 13) and high-grade (n 36) glioma datasets were uploaded to The Cancer Imaging Archive. Datasets included a predetermined arterial input function, enhancing tumor ROIs, and ROIs necessary to create normalized relative CBV and CBF maps. Seven sites computed 20 different perfusion metrics. Pair-wise agreement among sites was assessed with the Lin concordance correlation coefficient. Distinction of low- from high-grade tumors was evaluated with the Wilcoxon rank sum test followed by receiver operating characteristic analysis to identify the optimal thresholds based on sensitivity and specificity. RESULTS: For normalized relative CBV and normalized CBF, 93% and 94% of entries showed good or excellent cross-site agreement (0.8 Lin concordance correlation coefficient 1.0). All metrics could distinguish low- from high-grade tumors. Optimum thresholds were determined for pooled data (normalized relative CBV 1.4, sensitivity/specificity 90%:77%; normalized CBF 1.58, sensitivity/specificity 86%:77%). CONCLUSIONS: By means of DSC-MR imaging data obtained after a preload of contrast agent, substantial consistency resulted across sites for brain tumor perfusion metrics with a common threshold discoverable for distinguishing low- from high-grade tumors.

Original languageEnglish (US)
Pages (from-to)1008-1016
Number of pages9
JournalAmerican Journal of Neuroradiology
Volume39
Issue number6
DOIs
StatePublished - Jun 1 2018

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National Cancer Institute (U.S.)
Brain Neoplasms
Neoplasms
Nonparametric Statistics
Sensitivity and Specificity
Contrast Media
Perfusion
Perfusion Imaging
Gadolinium
ROC Curve
Glioma
Injections
Datasets

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology

Cite this

Multisite concordance of DSC-MRI analysis for brain tumors : Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project. / Schmainda, K. M.; Prah, M. A.; Rand, S. D.; Liu, Y.; Logan, B.; Muzi, M.; Rane, S. D.; Da, X.; Yen, Y. F.; Kalpathy-Cramer, J.; Chenevert, T. L.; Hoff, B.; Ross, B.; Cao, Y.; Aryal, M. P.; Erickson, Bradley J; Korfiatis, Panagiotis; Dondlinger, T.; Bell, L.; Hu, Leland S; Kinahan, P. E.; Quarles, C. C.

In: American Journal of Neuroradiology, Vol. 39, No. 6, 01.06.2018, p. 1008-1016.

Research output: Contribution to journalArticle

Schmainda, KM, Prah, MA, Rand, SD, Liu, Y, Logan, B, Muzi, M, Rane, SD, Da, X, Yen, YF, Kalpathy-Cramer, J, Chenevert, TL, Hoff, B, Ross, B, Cao, Y, Aryal, MP, Erickson, BJ, Korfiatis, P, Dondlinger, T, Bell, L, Hu, LS, Kinahan, PE & Quarles, CC 2018, 'Multisite concordance of DSC-MRI analysis for brain tumors: Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project', American Journal of Neuroradiology, vol. 39, no. 6, pp. 1008-1016. https://doi.org/10.3174/ajnr.A5675
Schmainda, K. M. ; Prah, M. A. ; Rand, S. D. ; Liu, Y. ; Logan, B. ; Muzi, M. ; Rane, S. D. ; Da, X. ; Yen, Y. F. ; Kalpathy-Cramer, J. ; Chenevert, T. L. ; Hoff, B. ; Ross, B. ; Cao, Y. ; Aryal, M. P. ; Erickson, Bradley J ; Korfiatis, Panagiotis ; Dondlinger, T. ; Bell, L. ; Hu, Leland S ; Kinahan, P. E. ; Quarles, C. C. / Multisite concordance of DSC-MRI analysis for brain tumors : Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project. In: American Journal of Neuroradiology. 2018 ; Vol. 39, No. 6. pp. 1008-1016.
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abstract = "BACKGROUND AND PURPOSE: Standard assessment criteria for brain tumors that only include anatomic imaging continue to be insufficient. While numerous studies have demonstrated the value of DSC-MR imaging perfusion metrics for this purpose, they have not been incorporated due to a lack of confidence in the consistency of DSC-MR imaging metrics across sites and platforms. This study addresses this limitation with a comparison of multisite/multiplatform analyses of shared DSC-MR imaging datasets of patients with brain tumors. MATERIALS AND METHODS: DSC-MR imaging data were collected after a preload and during a bolus injection of gadolinium contrast agent using a gradient recalled-echo–EPI sequence (TE/TR 30/1200 ms; flip angle 72°). Forty-nine low-grade (n 13) and high-grade (n 36) glioma datasets were uploaded to The Cancer Imaging Archive. Datasets included a predetermined arterial input function, enhancing tumor ROIs, and ROIs necessary to create normalized relative CBV and CBF maps. Seven sites computed 20 different perfusion metrics. Pair-wise agreement among sites was assessed with the Lin concordance correlation coefficient. Distinction of low- from high-grade tumors was evaluated with the Wilcoxon rank sum test followed by receiver operating characteristic analysis to identify the optimal thresholds based on sensitivity and specificity. RESULTS: For normalized relative CBV and normalized CBF, 93{\%} and 94{\%} of entries showed good or excellent cross-site agreement (0.8 Lin concordance correlation coefficient 1.0). All metrics could distinguish low- from high-grade tumors. Optimum thresholds were determined for pooled data (normalized relative CBV 1.4, sensitivity/specificity 90{\%}:77{\%}; normalized CBF 1.58, sensitivity/specificity 86{\%}:77{\%}). CONCLUSIONS: By means of DSC-MR imaging data obtained after a preload of contrast agent, substantial consistency resulted across sites for brain tumor perfusion metrics with a common threshold discoverable for distinguishing low- from high-grade tumors.",
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T1 - Multisite concordance of DSC-MRI analysis for brain tumors

T2 - Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project

AU - Schmainda, K. M.

AU - Prah, M. A.

AU - Rand, S. D.

AU - Liu, Y.

AU - Logan, B.

AU - Muzi, M.

AU - Rane, S. D.

AU - Da, X.

AU - Yen, Y. F.

AU - Kalpathy-Cramer, J.

AU - Chenevert, T. L.

AU - Hoff, B.

AU - Ross, B.

AU - Cao, Y.

AU - Aryal, M. P.

AU - Erickson, Bradley J

AU - Korfiatis, Panagiotis

AU - Dondlinger, T.

AU - Bell, L.

AU - Hu, Leland S

AU - Kinahan, P. E.

AU - Quarles, C. C.

PY - 2018/6/1

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N2 - BACKGROUND AND PURPOSE: Standard assessment criteria for brain tumors that only include anatomic imaging continue to be insufficient. While numerous studies have demonstrated the value of DSC-MR imaging perfusion metrics for this purpose, they have not been incorporated due to a lack of confidence in the consistency of DSC-MR imaging metrics across sites and platforms. This study addresses this limitation with a comparison of multisite/multiplatform analyses of shared DSC-MR imaging datasets of patients with brain tumors. MATERIALS AND METHODS: DSC-MR imaging data were collected after a preload and during a bolus injection of gadolinium contrast agent using a gradient recalled-echo–EPI sequence (TE/TR 30/1200 ms; flip angle 72°). Forty-nine low-grade (n 13) and high-grade (n 36) glioma datasets were uploaded to The Cancer Imaging Archive. Datasets included a predetermined arterial input function, enhancing tumor ROIs, and ROIs necessary to create normalized relative CBV and CBF maps. Seven sites computed 20 different perfusion metrics. Pair-wise agreement among sites was assessed with the Lin concordance correlation coefficient. Distinction of low- from high-grade tumors was evaluated with the Wilcoxon rank sum test followed by receiver operating characteristic analysis to identify the optimal thresholds based on sensitivity and specificity. RESULTS: For normalized relative CBV and normalized CBF, 93% and 94% of entries showed good or excellent cross-site agreement (0.8 Lin concordance correlation coefficient 1.0). All metrics could distinguish low- from high-grade tumors. Optimum thresholds were determined for pooled data (normalized relative CBV 1.4, sensitivity/specificity 90%:77%; normalized CBF 1.58, sensitivity/specificity 86%:77%). CONCLUSIONS: By means of DSC-MR imaging data obtained after a preload of contrast agent, substantial consistency resulted across sites for brain tumor perfusion metrics with a common threshold discoverable for distinguishing low- from high-grade tumors.

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