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Automated Assessment of Cerebral Arterial Perforator Function on 7T MRI
Author(s) -
Arts Tine,
Siero Jeroen C.W.,
Biessels Geert Jan,
Zwanenburg Jaco J.M.
Publication year - 2021
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.27304
Subject(s) - medicine , ghosting , intraclass correlation , censoring (clinical trials) , confidence interval , nuclear medicine , neuroradiology , magnetic resonance imaging , radiology , computer science , pathology , artificial intelligence , neurology , clinical psychology , psychiatry , psychometrics
Background Blood flow velocity and pulsatility of small cerebral perforating arteries can be measured using 7T quantitative 2D phase contrast (PC) MRI. However, ghosting artifacts arising from subject movement and pulsating large arteries cause false positives when applying a previously published perforator detection method. Purpose To develop a robust, automated method to exclude perforators located in ghosting artifacts. Study Type Retrospective. Subjects Fifteen patients with vascular cognitive impairment or carotid occlusive disease and 10 healthy controls. Field Strength/Sequence 7T/cardiac‐gated 2D PC MRI . Assessment Perforators were automatically excluded from ghosting regions, which were defined as bands in the phase‐encoding direction of large arteries. As reference, perforators were manually excluded by two raters (T.A., J.J.M.Z.), based on perforator location with respect to visible ghosting artifacts. The performance of both censoring methods was assessed for the number of (N included ), mean velocity (V mean ), and pulsatility index (PI) of the included perforators. Statistical Tests For within‐method comparisons, inter‐ and intrarater reliability were assessed for the manual method, and test–retest reliability was assessed for both methods from repeated 2D PC scans (without repositioning). Intraclass correlation coefficients (ICCs) and their 95% confidence intervals (CIs) were determined for N included , V mean , and PI for all within‐method comparisons. The ICC to compare between the two methods was determined with the use of both (test–retest) scans using a multilevel nonlinear mixed model. Results The automated censoring method showed a moderate to good ICC (95% CI) vs. manual censoring for N included (0.73 [0.58–0.87]) and V mean (0.90 [0.84–0.96]), and a moderate ICC for PI (0.57 [0.37–0.76]). The test–retest reliability of the manual censoring method was considerably lower than the interrater and intrarater reliability, indicating that scanner noise dominates the uncertainty of the analysis. Data Conclusion The proposed automated censoring method can reliably exclude small perforators affected by ghosting artifacts. Level of Evidence 3. Technical Efficacy Stage 1.