Prospective study assessing the validity of accelerated 2D Fast Spin Echo (2D FSE) based high-resolution knee MRI and...

A routine fast spin-echo (FSE) MRI protocol is widely used to evaluate structural injuries of the knee. While adding a T2 mapping sequence to this protocol increases sensitivity for detecting early cartilage lesions, it is time-consuming. Deep learning reconstruction (DLR) can provide accelerated, high-quality imaging but requires further clinical validation. This study aimed to evaluate the image quality and diagnostic performance of an accelerated, high-resolution 2D FSE protocol using DLR. Additionally, it sought to determine whether a routine MR imaging protocol combining an accelerated T2 mapping sequence with DLR could improve diagnostic performance for the detection of cartilage lesions, using arthroscopy as the reference standard.

A total of 92 patients underwent 2D FSE based routine knee imaging on 3.0T MRI, 39 of whom also underwent sagittal T2 mapping with different k-space-based acceleration factor of 2 or 3 and then reconstructed using conventional and deep learning reconstruction algorithms as FSE_O, FSE_DLR, T2_{O - ARC=2,3}, and T2_{DLR - ARC=2,3} and arthroscopy of the knee joint. Two radiologists subjectively and objectively evaluated both FSE_O and FSE_DLR. The inter-reader agreement for each pathology and image quality score was assessed using Cohen's κ. The objective metrics (SNR/CNR) between sequences was analyzed using paired t-test or Wilcoxon signed-rank test according to data normality. A two-sided p-value of less than 0.05 was considered statistically significant. Additionally, diagnostic performance of routine knee MR images and DLR or non-DLR T2 measurements respectively for grading knee cartilage were also compared. Articular cartilage was categorized according to International Cartilage Repair Society (ICRS). Each articular surface was then evaluated at arthroscopy. Receiver operating characteristic curve (ROC) was used to analyze diagnostic performance using arthroscopic results as reference.

Inter-reader agreement of subjective assessment ranged from 0.70 (95% CI: 0.46-0.94,) to 0.89 (95% CI: 0.79-0.99,) and higher score on FSE_DLR than FSE_O. Sharpness for FSE_DLR was rated to be excellent (median Likert score, 5; range, 5-5), higher compared to FSE_O (median Likert score, 5; range,4-5),(P < 0.001)). Both SNR and CNR of FSE_DLR were higher than those of FSE_O (P < 0.001). Inter-reader agreement was almost perfect, withκvalues between 0.94 (95% CI: 0.85-1.0) to 1.00 (95% CI: 1.0-1.0) for the detection of internal derangement and substantial to almost perfect between 0.70 (95% CI:0.52-0.88) and 0.93 (95% CI:0.85-1.0) for the assessment of cartilage defects. FSE_DLR (Reader 1 AUC, 0.77; 95% CI: 0.69-0.84 and Reader 2 AUC, 0.86; 95% CI: 0.78-0.91) had higher diagnostic performance than FSE_O (Reader 1 AUC, 0.74; 95% CI: 0.66-0.81 and Reader 2 AUC, 0.80; 95% CI: 0.72-0.86; P = 0.005) for articular cartilage lesions. Moreover, Reader 1 achieved the higher diagnostic efficacy (AUC, 0.84; 95% CI: 0.76-0.90) in differentiating normal-appearing from injury-visible cartilage when using both routine FSE_DLR images and T2_{DLR - ARC=2,}while Reader 2 achieved an AUC of 0.86 (95% CI: 0.78-0.91) with routine FSE_DLR images.

Our preliminary results indicate that the accelerated DLR FSE protocol provided diagnostic performance equivalent to the standard protocol for internal derangement, with potential improvement for the detection of cartilage lesions, while delivering higher image quality and quantitative T2 data within a clinically feasible scan time. These findings suggest its potential value for a comprehensive and efficient assessment of knee injury.