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The diagnostic value of quantitative analysis of ASL, DSC-MRI and DKI in the Grading of Cerebral Gliomas: A Meta-Analysis
Chuanchen Zhang
Shandong First Medical University
Corresponding Author
ORCiD: https://orcid.org/0000-0002-8467-5202
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Radiation Oncology.
Objective: To perform quantitative analysis on the efficacy of using relative cerebral blood flow (rCBF) in arterial spin labeling (ASL), relative cerebral blood volume (rCBV) in dynamic magnetic sensitivity contrast-enhanced magnetic resonance imaging (DSC-MRI), and mean kurtosis (MK) in diffusion kurtosis imaging (DKI) to grade cerebral gliomas.
Methods: Literature regarding ASL, DSC-MRI, or DKI in cerebral gliomas grading in both English and Chinese were searched from PubMed, Embase, Web of Science, CBM, China National Knowledge Infrastructure (CNKI), and Wanfang Database as of 2019. A meta-analysis was performed to evaluate the efficacy of ASL, DSC-MRI, and DKI in the grading of cerebral gliomas.
Result: A total of 54 articles (11 in Chinese and 43 in English) were included. Three quantitative parameters in the grading of cerebral gliomas, rCBF in ASL, rCBV in DSC-MRI, and MK in DKI had the pooled sensitivity of 0.88 [95%CI (0.83,0.92)], 0.92 [95%CI (0.83,0.96)], 0.88 [95%CI (0.82,0.92)], and the pooled specificity of 0.91 [95%CI (0.84,0.94)], 0.81 [95%CI (0.73,0.88)], 0.86 [95%CI (0.78,0.91)] respectively. The pooled area under the curve (AUC) were 0.95 [95%CI (0.93,0.97)], 0.91 [95%CI (0.89,0.94)], 0.93 [95%CI (0.91,0.95)] respectively.
Conclusion: Quantitative parameters rCBF, rCBV and MK have high diagnostic accuracy for preoperative grading of cerebral gliomas.
Keywords
gliomas, grading, MRI, Meta-analysis
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CURRENT STATUS: Published
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On 24 Aug, 2020
No community comments so far
Editorial decision: Accept
On 11 Aug, 2020
Editor assigned
On 10 Aug, 2020
Submission checks complete
On 09 Aug, 2020
Editor invited
On 09 Aug, 2020
No comments provided
Editorial decision: Minor revision
On 30 Jul, 2020
Review #2 received
Received 28 Jul, 2020
Reviewer #2 agreed
On 20 Jul, 2020
Reviewers invited
Invitations sent on 25 Jun, 2020
Reviewer #1 agreed
On 25 Jun, 2020
Review #1 received
Received 25 Jun, 2020
Editor assigned
On 23 Jun, 2020
Submission checks complete
On 22 Jun, 2020
Editor invited
On 22 Jun, 2020
No comments provided
Editorial decision: Major revision
On 27 May, 2020
Review #2 received
Received 21 May, 2020
Reviewer #2 agreed
On 12 May, 2020
Review #1 received
Received 10 May, 2020
Reviewer #1 agreed
On 26 Apr, 2020
Reviewers invited
Invitations sent on 23 Apr, 2020
First submitted
On 16 Apr, 2020
Editor assigned
On 16 Apr, 2020
Submission checks complete
On 15 Apr, 2020
Editor invited
On 15 Apr, 2020
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Subject Areas
Oncology
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This preprint is under consideration at Radiation Oncology. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
The diagnostic value of quantitative analysis of ASL, DSC-MRI and DKI in the Grading of Cerebral Gliomas: A Meta-Analysis
Chuanchen Zhang
Shandong First Medical University
Corresponding Author
ORCiD: https://orcid.org/0000-0002-8467-5202
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 3
Posted 14 Aug, 2020
Published
On 24 Aug, 2020
No community comments so far
Editorial decision: Accept
On 11 Aug, 2020
Editor assigned
On 10 Aug, 2020
Submission checks complete
On 09 Aug, 2020
Editor invited
On 09 Aug, 2020
No comments provided
Editorial decision: Minor revision
On 30 Jul, 2020
Review #2 received
Received 28 Jul, 2020
Reviewer #2 agreed
On 20 Jul, 2020
Reviewers invited
Invitations sent on 25 Jun, 2020
Reviewer #1 agreed
On 25 Jun, 2020
Review #1 received
Received 25 Jun, 2020
Editor assigned
On 23 Jun, 2020
Submission checks complete
On 22 Jun, 2020
Editor invited
On 22 Jun, 2020
No comments provided
Editorial decision: Major revision
On 27 May, 2020
Review #2 received
Received 21 May, 2020
Reviewer #2 agreed
On 12 May, 2020
Review #1 received
Received 10 May, 2020
Reviewer #1 agreed
On 26 Apr, 2020
Reviewers invited
Invitations sent on 23 Apr, 2020
First submitted
On 16 Apr, 2020
Editor assigned
On 16 Apr, 2020
Submission checks complete
On 15 Apr, 2020
Editor invited
On 15 Apr, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Oncology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Radiation Oncology.
Objective: To perform quantitative analysis on the efficacy of using relative cerebral blood flow (rCBF) in arterial spin labeling (ASL), relative cerebral blood volume (rCBV) in dynamic magnetic sensitivity contrast-enhanced magnetic resonance imaging (DSC-MRI), and mean kurtosis (MK) in diffusion kurtosis imaging (DKI) to grade cerebral gliomas.
Methods: Literature regarding ASL, DSC-MRI, or DKI in cerebral gliomas grading in both English and Chinese were searched from PubMed, Embase, Web of Science, CBM, China National Knowledge Infrastructure (CNKI), and Wanfang Database as of 2019. A meta-analysis was performed to evaluate the efficacy of ASL, DSC-MRI, and DKI in the grading of cerebral gliomas.
Result: A total of 54 articles (11 in Chinese and 43 in English) were included. Three quantitative parameters in the grading of cerebral gliomas, rCBF in ASL, rCBV in DSC-MRI, and MK in DKI had the pooled sensitivity of 0.88 [95%CI (0.83,0.92)], 0.92 [95%CI (0.83,0.96)], 0.88 [95%CI (0.82,0.92)], and the pooled specificity of 0.91 [95%CI (0.84,0.94)], 0.81 [95%CI (0.73,0.88)], 0.86 [95%CI (0.78,0.91)] respectively. The pooled area under the curve (AUC) were 0.95 [95%CI (0.93,0.97)], 0.91 [95%CI (0.89,0.94)], 0.93 [95%CI (0.91,0.95)] respectively.
Conclusion: Quantitative parameters rCBF, rCBV and MK have high diagnostic accuracy for preoperative grading of cerebral gliomas.
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