Why the study?
There were no previous reports on the 3D-SNAP MRI sequence to diagnose intracranial artery dissection, prompting investigation into its ability to improve diagnostic accuracy and elucidate pathological features.
Does 3D-SNAP MRI improve the diagnostic accuracy for intracranial artery dissection in patients with suspected IAD?
Does 3D-SNAP MRI improve the diagnostic accuracy for intracranial artery dissection in patients with suspected IAD?
3D-SNAP MRI, particularly when combined with 3D-T1WCE, is a highly effective non-invasive method for diagnosing intracranial artery dissection.
BACKGROUND: There was no previous report on the three-dimensional simultaneous non-contrast angiography and intra-plaque hemorrhage (3D-SNAP) magnetic resonance imaging (MRI) sequence to diagnose intracranial artery dissection (IAD). PURPOSE: To improve the diagnostic accuracy and guide the clinical treatment for IAD by elucidating its pathological features using 3D-SNAP MRI. MATERIAL AND METHODS: From January 2015 to September 2018, 113 patients with suspected IAD were analyzed. They were divided into IAD and non-IAD groups according to the spontaneous coronary artery dissection (SCAD) criteria. All patients underwent 3D-SNAP, 3D-TOF, T2W imaging, 3D-PD, 3D-T1W-VISTA, and 3D-T1WCE) using 3.0-T MRI; clinical data were collected. The IAD imaging findings (intramural hematoma, double lumen, intimal flap, aneurysmal dilatation, stenosis, or occlusion) in every sequence were analyzed. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic efficiency of each sequence. The 3D-SNAP and 3D-T1WCE sequences were most sensitive for diagnosing intramural hematoma and displaying double-lumen signs, respectively. The diagnostic efficiency of the 3D-SNAP sequence combined with 3D-T1WCE was the highest (area under the curve [AUC] 0.966). The AUC value of the 3D-SNAP sequence (AUC 0.897) was slightly inferior to that of 3D-T1W enhancement (AUC 0.903). CONCLUSION: 3D-SNAP MRI is a non-invasive and effective method and had the greatest potential among those methods tested for improving the diagnostic accuracy for IAD.
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Tang et al. (2021) studied this question.
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