Vessel Wall Imaging in 1.5 T MRI Using Deep Learning Reconstruction: Prospective Evaluation of Interchangeability With Standard 3 T MRI.
Authors
Affiliations (1)
Affiliations (1)
- Department of Neuroradiology, University Medical Center Mainz, Johannes Gutenberg University, Germany Langenbeckstraße 1, Mainz, Germany (A.E.M., H.A., A.B., V.S., S.A., A.O.); Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center Mainz, Johannes Gutenberg University, Germany Langenbeckstraße 1, Mainz, Germany (R.P.); Siemens Healthineers, Erlangen, Germany (D.N., R.S.).
Abstract
Vessel wall magnetic resonance imaging is important in the diagnosis of intracranial vascular diseases. Until now, adequate clinical implementation has required the use of 3 T scanners, which limits wider availability. This study aims to evaluate the interchangeability of a 3D turbo spin echo sequence with variable flip angle MRI sequence (T1 3D Sampling Perfection with Application optimized Contrast using different flip angle Evolution, SPACE) with deep learning image reconstruction for a 1.5 T scanner, with an established sequence (T1 3D SPACE) for a 3 T scanner. In addition, image quality parameters and diagnostic confidence are to be compared. Patients were prospectively examined using a T1-weighted turbo spin echo with variable flip angle at 3 T and a similar newly developed sequence with deep learning-based image reconstruction at 1.5 T. The images were read by 3 experienced radiologists regarding the presence of pathologic enhancement of the vessel wall for the interchangeability analysis. Image quality and diagnostic confidence were evaluated using 5-point Likert scales. Interreader and intrareader reliability were calculated for all parameters. A total of 50 participants (42.6 ± 21.2 y, 26 males) were included. Regarding the presence of pathologic vessel wall enhancement, there was a high interreader agreement [Fleiss kappa = 0.72 (95% CI: 0.62; 0.81) for 1.5T, 0.78 (0.69; 0.88) for 3 T]. The sequences at 1.5 T and 3 T were interchangeable (IEI = 0.008). Image quality at 1.5 T was diagnostic in all cases, but rated superior at 3 T (P < 0.001). Diagnostic confidence was also slightly but significantly higher at 3 T (P < 0.001). The utilization of deep learning reconstruction enables vessel wall imaging in 1.5 T MRI. This new MRI sequence was interchangeable with established sequences at 3 T for the detection of pathologic vessel wall enhancement. This development could significantly improve the availability of vessel wall imaging in the clinical routine.