Deep learning reconstruction of zero echo time magnetic resonance imaging: diagnostic performance in axial spondyloarthritis.
Authors
Affiliations (8)
Affiliations (8)
- Department of Radiology, Inje University Haeundae Paik Hospital, Busan, Republic of Korea.
- Department of Radiology, Inje University Haeundae Paik Hospital, Busan, Republic of Korea. [email protected].
- Department of Radiology, Yonsei University College of Medicine, Severance Hospital, Seoul, Republic of Korea. [email protected].
- Division of Rheumatology, Department of Internal Medicine, Inje University Haeundae Paik Hospital, Busan, Republic of Korea.
- Department of Radiology, Kosin University Gospel Hospital, Busan, Republic of Korea.
- GE Healthcare Korea, Seoul, Republic of Korea.
- GE Healthcare, Amersham, United Kingdom.
- GE Healthcare, New York, NY, USA.
Abstract
To compare the diagnostic performance of deep learning reconstruction (DLR) of zero echo time (ZTE) MRI for structural lesions in patients with axial spondyloarthritis, against T1WI and ZTE MRI without DLR, using CT as the reference standard. From February 2021 to December 2022, 26 patients (52 sacroiliac joints (SIJ) and 104 quadrants) underwent SIJ MRIs. Three readers assessed overall image quality and structural conspicuity, scoring SIJs for structural lesions on T1WI, ZTE, and ZTE DLR 50%, 75%, and 100%, respectively. Diagnostic performance was evaluated using CT as the reference standard, and inter-reader agreement was assessed using weighted kappa. ZTE DLR 100% showed the highest image quality scores for readers 1 and 2, and the best structural conspicuity scores for all three readers. In readers 2 and 3, ZTE DLR 75% showed the best diagnostic performance for bone sclerosis, outperforming T1WI and ZTE (all p < 0.05). In all readers, ZTE DLR 100% showed superior diagnostic performance for bone erosion compared to T1WI and ZTE (all p < 0.01). For bone sclerosis, ZTE DLR 50% showed the highest kappa coefficients between readers 1 and 2 and between readers 1 and 3. For bone erosion, ZTE DLR 100% showed the highest kappa coefficients between readers. ZTE MRI with DLR outperformed T1WI and ZTE MRI without DLR in diagnosing bone sclerosis and erosion of the SIJ, while offering similar subjective image quality and structural conspicuity. Question With zero echo time (ZTE) alone, small structural lesions, such as bone sclerosis and erosion, are challenging to confirm in axial spondyloarthritis. Findings ZTE deep learning reconstruction (DLR) showed higher diagnostic performance for detecting bone sclerosis and erosion, compared with T1WI and ZTE. Clinical relevance Applying DLR to ZTE enhances diagnostic capability for detecting bone sclerosis and erosion in the sacroiliac joint, aiding in the early diagnosis of axial spondyloarthritis.