Abdominal radiology (New York) · 2026
Deep learning reconstruction versus conventional parallel imaging for sagittal T2-weighted MRI in cervical cancer: a comparison of acceleration factors.
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Zhang Minglei, Lu Yifan, Song Jiacheng, Zhang Aining, Zhai Weiling, Shao Wenhui, Chen Chen, Lu Yuting, Ma Zhanlong, Chen Ting
Аннотация
BACKGROUND: The optimal acceleration strategy for deep learning reconstruction (DLR) in cervical cancer T2-weighted imaging (T2WI) remains unestablished.
METHODS: Forty-eight patients with primary cervical cancer prospectively underwent 3.0T pelvic MRI. Sagittal T2WI was acquired using conventional parallel imaging (Conv) and DLR at acceleration factors (AF) 2 and 3. Two radiologists evaluated quantitative metrics and six qualitative metrics.
RESULTS: Compared to conventional imaging at the same acceleration, DLR significantly improved signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) (DL_AF2 vs. Conv_AF2, adjusted p = 0.005; DL_AF3 vs. Conv_AF3, adjusted p < 0.001). No significant quantitative differences were found between AF2 and AF3 for either reconstruction method. Despite statistically comparable objective metrics between DL_AF2 and DL_AF3, DL_AF2 received significantly higher subjective scores across all six qualitative dimensions (all adjusted p < 0.001), with median scores of 5 for all image quality metrics. DL_AF3 demonstrated significantly lower diagnostic confidence scores, suggesting perceptual over-smoothing at higher acceleration.
CONCLUSION: At equivalent scan times, DLR with moderate acceleration (AF 2) achieves the optimal balance between objective image quality and subjective anatomical fidelity for sagittal T2WI in cervical cancer evaluation.
METHODS: Forty-eight patients with primary cervical cancer prospectively underwent 3.0T pelvic MRI. Sagittal T2WI was acquired using conventional parallel imaging (Conv) and DLR at acceleration factors (AF) 2 and 3. Two radiologists evaluated quantitative metrics and six qualitative metrics.
RESULTS: Compared to conventional imaging at the same acceleration, DLR significantly improved signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) (DL_AF2 vs. Conv_AF2, adjusted p = 0.005; DL_AF3 vs. Conv_AF3, adjusted p < 0.001). No significant quantitative differences were found between AF2 and AF3 for either reconstruction method. Despite statistically comparable objective metrics between DL_AF2 and DL_AF3, DL_AF2 received significantly higher subjective scores across all six qualitative dimensions (all adjusted p < 0.001), with median scores of 5 for all image quality metrics. DL_AF3 demonstrated significantly lower diagnostic confidence scores, suggesting perceptual over-smoothing at higher acceleration.
CONCLUSION: At equivalent scan times, DLR with moderate acceleration (AF 2) achieves the optimal balance between objective image quality and subjective anatomical fidelity for sagittal T2WI in cervical cancer evaluation.