Tissue Classification as a Potential Approach for Attenuation Correction in Whole-Body PET/MRI: Evaluation with PET/CT Data
Tissue Classification as a Potential Approach for Attenuation Correction in Whole-Body PET/MRI: Evaluation with PET/CT Data
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DOI：
10.2967/jnumed.108.054726
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发表时间：
2009-04-01
影响因子：
9.3
通讯作者：
Nekolla, Stephan G.
中科院分区：
文献类型：
--
作者：
Martinez-Moeller, Axel;Souvatzoglou, Michael;Nekolla, Stephan G.
PET/MRI组合断层扫描仪中全身PET数据的衰减校正（AC）预计将是一项技术挑战。在这项研究中，提出了一种基于分段衰减图的潜在解决方案，并在临床PET/CT病例中进行了评估。研究方法：假设将衰减图分割为4类（背景、肺、脂肪和软组织）足以用于AC目的。将分割应用于来自35名患者的F-18-FDG PET/CT肿瘤学检查的基于CT的衰减图，其中肺部（n = 15）、骨骼（n = 21）和颈部（n = 16）有52个F-18-FDG-avid病变。病变的标准化摄取值（SUV）由PET图像重建与非分割和分割的衰减图确定，和一个有经验的观察员解释PET图像与衰减图状态的知识。该方法的可行性也进行了评价与2例患者进行PET/CT和MRI。结果如下：使用分段衰减图导致骨病变的平均SUV变化为8% +/- 3%（平均值+/- SD），颈部病变为4% +/- 2%，肺部病变为2% +/- 3%。骨盆病变的最大SUV变化为13.1%。有经验的观察者对两种类型的衰减图的临床解释没有差异。结论：从CT数据中获得的4类分段衰减图对F-18-FDG-avid病变的SUV只有很小的影响，并且没有改变任何患者的解释。这种方法对于基于MRI的AC似乎是实用和有效的。
Attenuation correction (AC) of whole-body PET data in combined PET/MRI tomographs is expected to be a technical challenge. In this study, a potential solution based on a segmented attenuation map is proposed and evaluated in clinical PET/CT cases. Methods: Segmentation of the attenuation map into 4 classes (background, lungs, fat, and soft tissue) was hypothesized to be sufficient for AC purposes. The segmentation was applied to CT-based attenuation maps from F-18-FDG PET/CT oncologic examinations of 35 patients with 52 F-18-FDG-avid lesions in the lungs (n = 15), bones (n = 21), and neck (n = 16). The standardized uptake values (SUVs) of the lesions were determined from PET images reconstructed with nonsegmented and segmented attenuation maps, and an experienced observer interpreted both PET images with no knowledge of the attenuation map status. The feasibility of the method was also evaluated with 2 patients who underwent both PET/CT and MRI. Results: The use of a segmented attenuation map resulted in average SUV changes of 8% +/- 3% (mean +/- SD) for bone lesions, 4% +/- 2% for neck lesions, and 2% +/- 3% for lung lesions. The largest SUV change was 13.1%, for a lesion in the pelvic bone. There were no differences in the clinical interpretations made by the experienced observer with both types of attenuation maps. Conclusion: A segmented attenuation map with 4 classes derived from CT data had only a small effect on the SUVs of F-18-FDG-avid lesions and did not change the interpretation for any patient. This approach appears to be practical and valid for MRI-based AC.