Back to the list
Congress: ECR25
Poster Number: C-10894
Type: Poster: EPOS Radiologist (scientific)
Authorblock: Y. J. Heo; Busan/KR
Disclosures:
Young Jin Heo: Nothing to disclose
Keywords: CNS, MR, Imaging sequences, Neoplasia
Purpose This study aimed to evaluate the diagnostic performance of Deep learning based super-resolution in iterative denoising of post-contrast T1-weighted VIBE (DL-VIBE) for evaluating intracranial enhancing lesions compared with standard 3D-MPRAGE.
Read more Methods and materials Post-contrast 3D T1 weighted sequences (T1WI) showed excellent soft tissue contrast and contrast enhancing effect after contrast injection and widely used in brain MRI for evaluation of pathologies. However, high-resolution isotropic T1WI usually require long scan time and might increase motion artifact and patient anxiety, which can compromise image quality. Parallel imaging is the most commonly used acceleration method for decreasing the scan time with reducing the k-space line. However, parallel imaging with a high acceleration factor usually results in increased...
Read more Results Although DL-VIBE showed significantly lower inferior image quality and anatomic delineation, DL-VIBE showed significantly higher CNR lesion/parenchyma and fewer flow-related artifacts compared with MPRAGE (P< .0001). Furthermore, DL-VIBE did not show significant difference in conspicuity of enhancing lesions and the number of enhancing lesion compared with MPRAGE (P> .05). 
Read more Conclusion DL-VIBE showed comparable diagnostic performance for intracranial enhancing lesions with shorter scan time compared with standard 3D-MPRAGE, although it was limited by lower image quality. Therefore, DL-VIBE may be a viable option for clinical setting with technical development of Deep learning based reconstruction in the future.
Read more References Almansour H, Gassenmaier S, Nickel D, Kannengiesser S, Afat S, Weiss J, et al. Deep learning-based superresolution reconstruction for upper abdominal magnetic resonance imaging: an analysis of image quality, diagnostic confidence, and lesion conspicuity. Investigative radiology. 2021;56(8):509-16. Chaika M, Afat S, Wessling D, Afat C, Nickel D, Kannengiesser S, et al. Deep learning-based super-resolution gradient echo imaging of the pancreas: Improvement of image quality and reduction of acquisition time. Diagn Interv Imaging. 2023;104(2):53-9. Almansour H, Herrmann J, Gassenmaier S, Lingg A, Nickel...
Read more
GALLERY