Department of Radiology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
United Imaging Healthcare, Shanghai, People's Republic of China.
Eur Radiol. 2023 Nov;33(11):7686-7696. doi: 10.1007/s00330-023-09742-6. Epub 2023 May 23.
To compare examination time and image quality between artificial intelligence (AI)-assisted compressed sensing (ACS) technique and parallel imaging (PI) technique in MRI of patients with nasopharyngeal carcinoma (NPC).
Sixty-six patients with pathologically confirmed NPC underwent nasopharynx and neck examination using a 3.0-T MRI system. Transverse T2-weighted fast spin-echo (FSE) sequence, transverse T1-weighted FSE sequence, post-contrast transverse T1-weighted FSE sequence, and post-contrast coronal T1-weighted FSE were obtained by both ACS and PI techniques, respectively. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and duration of scanning of both sets of images analyzed by ACS and PI techniques were compared. The images from the ACS and PI techniques were scored for lesion detection, margin sharpness of lesions, artifacts, and overall image quality using the 5-point Likert scale.
The examination time with ACS technique was significantly shorter than that with PI technique (p < 0.0001). The comparison of SNR and CNR showed that ACS technique was significantly superior with PI technique (p < 0.005). Qualitative image analysis showed that the scores of lesion detection, margin sharpness of lesions, artifacts, and overall image quality were higher in the ACS sequences than those in the PI sequences (p < 0.0001). Inter-observer agreement was evaluated for all qualitative indicators for each method, in which the results showed satisfactory-to-excellent agreement (p < 0.0001).
Compared with the PI technique, the ACS technique for MR examination of NPC can not only shorten scanning time but also improve image quality.
The artificial intelligence (AI)-assisted compressed sensing (ACS) technique shortens examination time for patients with nasopharyngeal carcinoma, while improving the image quality and examination success rate, which will benefit more patients.
• Compared with the parallel imaging (PI) technique, the artificial intelligence (AI)-assisted compressed sensing (ACS) technique not only reduced examination time, but also improved image quality. • Artificial intelligence (AI)-assisted compressed sensing (ACS) pulls the state-of-the-art deep learning technique into the reconstruction procedure and helps find an optimal balance of imaging speed and image quality.
比较人工智能（AI）辅助压缩感知（ACS）技术与并行成像（PI）技术在鼻咽癌（NPC）患者 MRI 检查中的检查时间和图像质量。
对 66 例经病理证实的 NPC 患者进行鼻咽颈部检查，使用 3.0T MRI 系统。分别采用 ACS 和 PI 技术获得横断 T2 加权快速自旋回波（FSE）序列、横断 T1 加权 FSE 序列、对比后横断 T1 加权 FSE 序列和对比后冠状 T1 加权 FSE 序列。比较 ACS 和 PI 技术分析的两组图像的信噪比（SNR）、对比噪声比（CNR）和扫描时间。使用 5 分制 Likert 量表对 ACS 和 PI 技术的图像进行病变检出、病变边缘锐利度、伪影和整体图像质量评分。
ACS 技术的检查时间明显短于 PI 技术（p<0.0001）。SNR 和 CNR 的比较表明，ACS 技术明显优于 PI 技术（p<0.005）。定性图像分析显示，ACS 序列的病变检出、病变边缘锐利度、伪影和整体图像质量评分均高于 PI 序列（p<0.0001）。对每种方法的所有定性指标进行了观察者间一致性评估，结果显示一致性为满意至极好（p<0.0001）。
与 PI 技术相比，NPC 的 MRI 检查中 ACS 技术不仅可以缩短扫描时间，还可以提高图像质量。
人工智能（AI）辅助压缩感知（ACS）技术可缩短鼻咽癌患者的检查时间，同时提高图像质量和检查成功率，使更多患者受益。
与并行成像（PI）技术相比，人工智能（AI）辅助压缩感知（ACS）技术不仅减少了检查时间，还提高了图像质量。
AI 辅助压缩感知（ACS）将最先进的深度学习技术引入到重建过程中，有助于找到成像速度和图像质量的最佳平衡点。
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