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Segmented 3D Echo Planar Acquisition for Rapid Susceptibility‐Weighted Imaging: Application to Microhemorrhage Detection in Traumatic Brain Injury
Author(s) -
Wang WenTung,
Li Ningzhi,
Papageorgiou Ioannis,
Chan Leighton,
Pham Dzung L.,
Butman John A.
Publication year - 2022
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.28326
Subject(s) - medicine , susceptibility weighted imaging , nuclear medicine , traumatic brain injury , magnetic resonance imaging , kappa , radiology , linguistics , philosophy , psychiatry
Background Susceptibility‐weighted imaging (SWI) provides superior image contrast of cerebral microhemorrhages (CMBs). It is based on a three‐dimensional (3D) gradient echo (GRE) sequence with a relatively long imaging time. Purpose To evaluate whether an accelerated 3D segmented echo planar imaging SWI is comparable to GRE SWI in detecting CMBs in traumatic brain injury (TBI). Study Type Prospective. Subjects Four healthy volunteers and 46 consecutive subjects (38.0 ± 14.4 years, 16 females; 12 mild, 13 moderate, and 7 severe TBI). Field Strength/Sequence A 3 T scanner/3D gradient echo and 3D segmented echo planar imaging (segEPI). Assessment Brain images were acquired using GRE and segEPI in a single session (imaging time = 9 minutes 47 seconds and 1 minute 30 seconds, respectively). The signal‐to‐noise ratio (SNR) calculated from healthy volunteer thalamus and centrum semiovale were compared. CMBs were counted by three raters blinded to diagnostic information. Statistical Tests A t ‐test was used to assess SNR difference. Pearson correlation and Wilcoxon signed‐rank test were performed using CMB counts. The intermethod agreement was evaluated using Bland–Altman method. Intermethod and interrater reliabilities of image‐based diffuse axonal injury (DAI) diagnoses were evaluated using Cohen's kappa and percent agreement. P ≤ 0.05 was considered statistically significant. Results Thalamus SNRs were 16.9 ± 2.2 and 16.5 ± 3 for GRE and segEPI ( P = 0.84), respectively. Centrum semiovale SNRs were 25.8 ± 4.6 and 21.1 ± 2.7 ( P = 0.13). The correlation coefficient of CMBs was 0.93, and differences were not significant ( P = 0.56–0.85). For DAI diagnoses, Cohen's kappa was 0.62–0.84 and percent agreement was 85%–94%. Data Conclusion CMB counts on segEPI and GRE were highly correlated, and DAI diagnosis was made equally effectively. segEPI SWI can potentially replace GRE SWI in detecting TBI CMBs, especially when time constraints are critical. Evidence Level 1 Technical Efficacy Stage 2