Institute of Radiology and Nuclear Medicine, Hanusch-Hospital, Heinrich-Collin-Strasse 30, A-1140, Vienna, Austria.
Department of Nuclear Medicine with PET-Center, Wilhelminen-Hospital, Vienna, Austria.
BMC Med Imaging. 2020 Feb 24;20(1):22. doi: 10.1186/s12880-020-00424-z.
This study assesses the value of image fusion using 18F-fluoro-L-DOPA (18F-DOPA) positron emission tomography (PET) and magnetic resonance imaging (MRI) for examining patients with neuroendocrine tumors (NETs) and a suspicion of metastasis of the liver.
Eleven patients (five women and six men aged between 20 and 81, with a mean age of 54.6 years) were included in the study. All patients underwent whole-body 18F-DOPA PET examinations and contrast-enhanced MRI with diffusion-weighted sequences (DWS). Image fusion was performed using a semiautomatic voxel-based algorithm. Images obtained using PET and MRI were assessed separately. Side-by-side evaluations of fused PET/MRI images were also performed.
In total, 55 liver lesions (52 liver metastases and 3 benign lesions) were detected in the 11 patients. Sensitivity detection for liver lesions was higher when using PET/CT than when using contrast-enhanced MRI without DWSs and lower than using MRI with DWSs. The sensitivity of PET/MRI image fusion in the detection of liver metastasis was significantly higher than that of MRI with DWSs (P < 0.05).
Images of the liver obtained using PET and MRI in patients with NETs exhibited characteristic features. These findings suggest that an appropriate combination of available imaging modalities can optimize patient evaluations.
本研究评估了使用 18F-氟-L-多巴（18F-DOPA）正电子发射断层扫描（PET）和磁共振成像（MRI）进行神经内分泌肿瘤（NETs）患者和肝脏转移可疑患者检查的图像融合的价值。
研究纳入了 11 名患者（5 名女性和 6 名男性，年龄在 20 至 81 岁之间，平均年龄为 54.6 岁）。所有患者均接受了全身 18F-DOPA PET 检查和增强 MRI 检查，包括弥散加权序列（DWS）。图像融合使用半自动体素基算法完成。分别评估 PET 和 MRI 获得的图像。还对融合的 PET/MRI 图像进行并排评估。
在 11 名患者中，共发现 55 个肝脏病变（52 个肝转移和 3 个良性病变）。与未行 DWS 的增强 MRI 相比，PET/CT 对肝脏病变的检测敏感性更高，而低于 DWS 的 MRI。PET/MRI 图像融合检测肝转移的敏感性明显高于 DWS 的 MRI（P<0.05）。
NETs 患者的 PET 和 MRI 肝脏图像具有特征性表现。这些发现表明，适当结合现有成像方式可以优化患者评估。
