Cho Yongwon, Han Yeo Eun, Kim Min Ju, Park Beom Jin, Sim Ki Choon, Sung Deuk Jae, Han Na Yeon, Park Yang Shin
Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul 02841, Republic of Korea; AI Center, Korea University Anam Hospital, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul 02841, Republic of Korea.
Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul 02841, Republic of Korea.
Comput Methods Programs Biomed. 2022 Oct;225:107032. doi: 10.1016/j.cmpb.2022.107032. Epub 2022 Jul 20.
Diagnosis of hepatocellular carcinoma (HCC) on liver MRI needs analysis of multi-sequence images. However, developing computer-aided detection (CAD) for every single sequence requires considerable time and labor for image segmentation. Therefore, we developed CAD for HCC on the hepatobiliary phase (HBP) of gadoxetic acid-enhanced magnetic resonance imaging (MRI) using a convolutional neural network (CNN) and evaluated its feasibility on multi-sequence, multi-unit, and multi-center data.
Patients who underwent gadoxetic acid-enhanced MRI and surgery for HCC in Korea University Anam Hospital (KUAH) and Korea University Guro Hospital (KUGH) were reviewed. Finally, 170 nodules from 155 consecutive patients from KUAH and 28 nodules from 28 patients randomly selected from KUGH were included. Regions of interests were drawn on the whole HCC volume on HBP, T1-weighted (T1WI), T2-weighted (T2WI), and portal venous phase (PVP) images. The CAD was developed from the HBP images of KUAH using customized-nnUNet and post-processed for false-positive reduction. Internal and external validation of the CAD was performed with HBP, T1WI, T2WI, and PVP of KUAH and KUGH.
The figure of merit and recall of the jackknife alternative free-response receiver operating characteristic of the CAD for HBP, T1WI, T2WI, and PVP at false-positive rate 0.5 were (0.87 and 87.0), (0.73 and 73.3), (0.13 and 13.3), and (0.67 and 66.7) in KUAH and (0.86 and 86.0), (0.61 and 53.6), (0.07 and 0.07), and (0.57 and 53.6) in KUGH, respectively.
The CAD for HCC on gadoxetic acid-enhanced MRI developed by CNN from HBP detected HCCs feasibly on HBP, T1WI, and PVP of gadoxetic acid-enhanced MRI obtained from multiple units and centers. This result imply that the CAD developed using single MRI sequence may be applied to other similar sequences and this will reduce labor and time for CAD development in multi-sequence MRI.
肝脏磁共振成像（MRI）上肝细胞癌（HCC）的诊断需要对多序列图像进行分析。然而，为每个单独序列开发计算机辅助检测（CAD）需要花费大量时间和人力进行图像分割。因此，我们使用卷积神经网络（CNN）开发了基于钆塞酸增强磁共振成像（MRI）肝胆期（HBP）的HCC计算机辅助检测方法，并在多序列、多机构和多中心数据上评估了其可行性。
回顾了在韩国大学安岩医院（KUAH）和韩国大学九老医院（KUGH）接受钆塞酸增强MRI检查并接受HCC手术的患者。最后，纳入了KUAH连续155例患者的170个结节以及从KUGH随机选取的28例患者的28个结节。在HBP、T1加权（T1WI）、T2加权（T2WI）和门静脉期（PVP）图像上的整个HCC体积上绘制感兴趣区域。使用定制的nnUNet从KUAH的HBP图像开发CAD，并进行后处理以减少假阳性。使用KUAH和KUGH的HBP、T1WI、T2WI和PVP对CAD进行内部和外部验证。
在KUAH中，CAD针对HBP、T1WI、T2WI和PVP在假阳性率为0.5时的留一法替代自由响应接收器操作特征的品质因数和召回率分别为（0.87和87.0）、（0.73和73.3）、（0.13和13.3）以及（0.67和66.7）；在KUGH中分别为（0.86和86.0）、（0.61和53.6）、（0.07和0.07）以及（0.57和53.6）。
由CNN从HBP开发的基于钆塞酸增强MRI的HCC CAD能够在从多个机构和中心获得的钆塞酸增强MRI的HBP、T1WI和PVP上可靠地检测HCC。这一结果表明，使用单一MRI序列开发的CAD可能适用于其他类似序列，这将减少多序列MRI中CAD开发的人力和时间。
