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使用定量SPECT/CT获取的骨骼标准化摄取值,用于检测肺腺癌患者的骨转移。

Skeletal standardized uptake values obtained using quantitative SPECT/CT for the detection of bone metastases in patients with lung adenocarcinoma.

作者信息

Lin Lin, Zheng Rong, Geng Jianhua, Wang Xuejuan, Li Meng, Fan Rong, Zheng Yiqing, Yang Ke

机构信息

Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

出版信息

Front Med (Lausanne). 2023 Feb 2;10:1119214. doi: 10.3389/fmed.2023.1119214. eCollection 2023.

DOI:10.3389/fmed.2023.1119214
PMID:36817798
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9931902/
Abstract

PURPOSE

To assess the utility of skeletal standardized uptake values (SUVs) obtained using quantitative single-photon emission computed tomography/computed tomography (SPECT/CT) in differentiating bone metastases from benign lesions, particularly in patients with lung adenocarcinoma.

METHODS

Patients with lung adenocarcinoma who had undergone whole-body Tc-99m methyl-diphosphonate (Tc-MDP) bone scans and received late phase SPECT/CT were retrospectively analyzed in this study. The maximum SUV (SUVmax); Hounsfield units (HUs); and volumes of osteoblastic, osteolytic, mixed, CT-negative metastatic and benign bone lesions, and normal vertebrae were compared. Receiver operating characteristic curves were used to determine the optimal cutoff SUVmax between metastatic and benign lesions as well as the cutoff SUVmax between CT-negative metastatic lesions and normal vertebrae. The linear correlation between SUVmax and HUs of metastatic lesions as well as that between SUVmax and the volume of all bone lesions were investigated.

RESULTS

A total of 252 bone metastatic lesions, 140 benign bone lesions, and 199 normal vertebrae from 115 patients with lung adenocarcinoma were studied (48 males, 67 females, median age: 59 years). Metastatic lesions had a significantly higher SUVmax (23.85 ± 14.34) than benign lesions (9.67 ± 7.47) and normal vertebrae (6.19 ± 1.46; < 0.0001). The SPECT/CT hotspot of patients with bone metastases could be distinguished from benign lesions using a cutoff SUVmax of 11.10, with a sensitivity of 87.70% and a specificity of 80.71%. The SUVmax of osteoblastic (29.16 ± 16.63) and mixed (26.62 ± 14.97) lesions was significantly greater than that of osteolytic (15.79 ± 5.57) and CT-negative (16.51 ± 6.93) lesions ( < 0.0001, = 0.0003, and 0.002). SUVmax at the cutoff value of 8.135 could distinguish CT-negative bone metastases from normal vertebrae, with a sensitivity of 100.00% and a specificity of 91.96%. SUVmax showed a weak positive linear correlation with HUs in all bone metastases and the volume of all bone lesions.

CONCLUSION

SUVmax of quantitative SPECT/CT is a useful index for distinguishing benign bone lesions from bone metastases in patients with lung adenocarcinoma, particularly in the diagnosis of CT-negative bone metastases, but other factors that may affect SUVmax should be considered.

摘要

目的

评估使用定量单光子发射计算机断层扫描/计算机断层扫描(SPECT/CT)获得的骨骼标准化摄取值(SUV)在鉴别骨转移瘤与良性病变中的效用,尤其是在肺腺癌患者中。

方法

本研究回顾性分析了接受全身锝-99m亚甲基二膦酸盐(Tc-MDP)骨扫描并进行延迟期SPECT/CT检查的肺腺癌患者。比较了最大SUV(SUVmax)、亨氏单位(HU)以及成骨、溶骨、混合、CT阴性转移和良性骨病变及正常椎体的体积。使用受试者工作特征曲线确定转移瘤与良性病变之间以及CT阴性转移瘤与正常椎体之间的最佳SUVmax临界值。研究了转移瘤的SUVmax与HU之间以及SUVmax与所有骨病变体积之间的线性相关性。

结果

共研究了115例肺腺癌患者的252个骨转移瘤、14个良性骨病变和199个正常椎体(男性48例,女性67例,中位年龄:59岁)。转移瘤的SUVmax(23.85±14.34)显著高于良性病变(9.67±7.47)和正常椎体(6.19±1.46;P<0.0001)。骨转移瘤患者的SPECT/CT热点与良性病变可通过SUVmax临界值11.10进行区分,敏感性为87.70%,特异性为80.71%。成骨(29.16±16.63)和混合(26.62±14.97)病变的SUVmax显著大于溶骨(15.79±5.57)和CT阴性(16.51±6.93)病变(P<0.0001、P = 0.0003和P = 0.002)。SUVmax临界值为8.135时可区分CT阴性骨转移瘤与正常椎体,敏感性为100.00%,特异性为91.96%。在所有骨转移瘤中,SUVmax与HU以及所有骨病变体积呈弱正线性相关。

结论

定量SPECT/CT的SUVmax是鉴别肺腺癌患者良性骨病变与骨转移瘤的有用指标,尤其是在CT阴性骨转移瘤的诊断中,但应考虑其他可能影响SUVmax的因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e69/9931902/a1dcebe27528/fmed-10-1119214-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e69/9931902/8bde2dfb99e9/fmed-10-1119214-g0001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e69/9931902/4e7574bb6aef/fmed-10-1119214-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e69/9931902/9a262422bd3e/fmed-10-1119214-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e69/9931902/a1dcebe27528/fmed-10-1119214-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e69/9931902/8bde2dfb99e9/fmed-10-1119214-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e69/9931902/6aeca3b4fb5b/fmed-10-1119214-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e69/9931902/0d965e28d14f/fmed-10-1119214-g0003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e69/9931902/4e7574bb6aef/fmed-10-1119214-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e69/9931902/9a262422bd3e/fmed-10-1119214-g0006.jpg
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