Abstract：
OBJECTIVE: To determine if super-resolution deep learning reconstruction (SR-DLR) improves the depiction of cranial nerves and interobserver agreement when assessing neurovascular conflict in 3D fast asymmetric spin echo (3D FASE) brain MR images, as compared to deep learning reconstruction (DLR).
METHODS: This retrospective study involved reconstructing 3D FASE MR images of the brain for 37 patients using SR-DLR and DLR. Three blinded readers conducted qualitative image analyses, evaluating the degree of neurovascular conflict, structure depiction, sharpness, noise, and diagnostic acceptability. Quantitative analyses included measuring edge rise distance (ERD), edge rise slope (ERS), and full width at half maximum (FWHM) using the signal intensity profile along a linear region of interest across the center of the basilar artery.
RESULTS: Interobserver agreement on the degree of neurovascular conflict of the facial nerve was generally higher with SR-DLR (0.429-0.923) compared to DLR (0.175-0.689). SR-DLR exhibited increased subjective image noise compared to DLR (p ≥ 0.008). However, all three readers found SR-DLR significantly superior in terms of sharpness (p < 0.001); cranial nerve depiction, particularly of facial and acoustic nerves, as well as the osseous spiral lamina (p < 0.001); and diagnostic acceptability (p ≤ 0.002). The FWHM (mm)/ERD (mm)/ERS (mm-1) for SR-DLR and DLR was 3.1-4.3/0.9-1.1/8795.5-10,703.5 and 3.3-4.8/1.4-2.1/5157.9-7705.8, respectively, with SR-DLR\'s image sharpness being significantly superior (p ≤ 0.001).
CONCLUSIONS: SR-DLR enhances image sharpness, leading to improved cranial nerve depiction and a tendency for greater interobserver agreement regarding facial nerve neurovascular conflict.
METHODS: This retrospective study involved reconstructing 3D FASE MR images of the brain for 37 patients using SR-DLR and DLR. Three blinded readers conducted qualitative image analyses, evaluating the degree of neurovascular conflict, structure depiction, sharpness, noise, and diagnostic acceptability. Quantitative analyses included measuring edge rise distance (ERD), edge rise slope (ERS), and full width at half maximum (FWHM) using the signal intensity profile along a linear region of interest across the center of the basilar artery.
RESULTS: Interobserver agreement on the degree of neurovascular conflict of the facial nerve was generally higher with SR-DLR (0.429-0.923) compared to DLR (0.175-0.689). SR-DLR exhibited increased subjective image noise compared to DLR (p ≥ 0.008). However, all three readers found SR-DLR significantly superior in terms of sharpness (p < 0.001); cranial nerve depiction, particularly of facial and acoustic nerves, as well as the osseous spiral lamina (p < 0.001); and diagnostic acceptability (p ≤ 0.002). The FWHM (mm)/ERD (mm)/ERS (mm-1) for SR-DLR and DLR was 3.1-4.3/0.9-1.1/8795.5-10,703.5 and 3.3-4.8/1.4-2.1/5157.9-7705.8, respectively, with SR-DLR\'s image sharpness being significantly superior (p ≤ 0.001).
CONCLUSIONS: SR-DLR enhances image sharpness, leading to improved cranial nerve depiction and a tendency for greater interobserver agreement regarding facial nerve neurovascular conflict.
摘要：
目的：为了确定超分辨率深度学习重建（SR-DLR）在评估3D快速不对称自旋回波（3DFASE）脑MR图像中的神经血管冲突时是否可以改善颅神经的描绘和观察者之间的一致性，与深度学习重建(DLR)相比。
方法：这项回顾性研究涉及使用SR-DLR和DLR重建37例患者的脑部3DFASEMR图像。三名失明的读者进行了定性图像分析，评估神经血管冲突的程度，结构描述，清晰度,噪音,和诊断的可接受性。定量分析包括测量边缘上升距离(ERD)，边缘上升斜率（ERS），和半峰全宽(FWHM),使用沿着基底动脉中心的感兴趣的线性区域的信号强度分布。
结果：与DLR（0.175-0.689）相比，SR-DLR（0.429-0.923）对面神经神经血管冲突程度的观察者共识普遍更高。与DLR相比，SR-DLR表现出增加的主观图像噪声(p≥0.008)。然而,所有三位读者都发现SR-DLR在清晰度方面显著优于(p<0.001)；颅神经描绘，特别是面神经和听觉神经，以及骨螺旋椎板（p<0.001）；和诊断可接受性（p≤0.002）。SR-DLR和DLR的FWHM（mm）/ERD（mm）/ERS（mm-1）分别为3.1-4.3/0.9-1.1/8795.5-10,703.5和3.3-4.8/1.4-2.1/5157.9-7705.8，SR-DLR的图像清晰度明显优于（p≤0.001）。
结论：SR-DLR增强了图像清晰度，导致改善的颅神经描绘和观察者之间关于面神经神经血管冲突的更大共识的趋势。
方法：这项回顾性研究涉及使用SR-DLR和DLR重建37例患者的脑部3DFASEMR图像。三名失明的读者进行了定性图像分析，评估神经血管冲突的程度，结构描述，清晰度,噪音,和诊断的可接受性。定量分析包括测量边缘上升距离(ERD)，边缘上升斜率（ERS），和半峰全宽(FWHM),使用沿着基底动脉中心的感兴趣的线性区域的信号强度分布。
结果：与DLR（0.175-0.689）相比，SR-DLR（0.429-0.923）对面神经神经血管冲突程度的观察者共识普遍更高。与DLR相比，SR-DLR表现出增加的主观图像噪声(p≥0.008)。然而,所有三位读者都发现SR-DLR在清晰度方面显著优于(p<0.001)；颅神经描绘，特别是面神经和听觉神经，以及骨螺旋椎板（p<0.001）；和诊断可接受性（p≤0.002）。SR-DLR和DLR的FWHM（mm）/ERD（mm）/ERS（mm-1）分别为3.1-4.3/0.9-1.1/8795.5-10,703.5和3.3-4.8/1.4-2.1/5157.9-7705.8，SR-DLR的图像清晰度明显优于（p≤0.001）。
结论：SR-DLR增强了图像清晰度，导致改善的颅神经描绘和观察者之间关于面神经神经血管冲突的更大共识的趋势。
