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最大标准化摄取值与临床参数相结合以提高区分原发性纵隔淋巴瘤与胸腺上皮肿瘤的准确性。

The combination of maximum standardized uptake value and clinical parameters for improving the accuracy in distinguishing primary mediastinal lymphomas from thymic epithelial tumors.

作者信息

Yan Hui, Wang Lihua, Lei Bei, Ruan Maomei, Chang Cheng, Zhou Mingge, Liu Liu, Xie Wenhui, Wang Yuetao

机构信息

Department of Nuclear Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, China.

Department of Nuclear Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

出版信息

Quant Imaging Med Surg. 2024 Feb 1;14(2):1944-1956. doi: 10.21037/qims-23-496. Epub 2024 Jan 5.

DOI:10.21037/qims-23-496
PMID:38415117
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10895101/
Abstract

BACKGROUND

Anterior mediastinal masses are relatively uncommon, and mediastinal lymphomas are the malignancies most likely to be confused with thymic epithelial tumors (TETs). The aim of this study was to investigate whether the combination of fluorine-fluorodeoxyglucose positron emission tomography-computed tomography (F-FDG PET-CT) findings and clinical parameters is useful in differentiating lymphoma from TETs in anterior mediastinal masses.

METHODS

This retrospective study consecutively included 304 patients with anterior mediastinal masses (244 TETs and 60 lymphomas) who underwent F-FDG PET-CT 1 to 2 weeks before tumor resection or biopsy between August 2016 and March 2022. The correlations between the maximum standardized uptake value (SUVmax) of tumors and clinical parameters of patients with histology subtypes were analyzed. Receiver operating characteristic curve analysis was used to obtain the optimal cutoff values of age, lactate dehydrogenase (LDH), tumor size, and SUVmax to predict lymphoma. Logistic regression analysis was used to identify potential predictive factors for lymphoma.

RESULTS

Lymphoma was significantly associated with younger patient age, higher LDH level, larger tumor size, and higher SUVmax compared to TETs (P<0.001). In the modeling cohort, age ≤40.5 years, LDH level ≥197 U/L, tumor size ≥10.72 cm, and SUVmax ≥11.95 were identified as independent predictors for lymphoma with odds ratios of 20.14 [95% confidence interval (CI): 6.02-67.40; P<0.001], 4.89 (95% CI: 1.27-18.89; P=0.021), 8.82 (95% CI: 2.31-33.69; P=0.001), and 30.01 (95% CI: 6.59-136.72; P<0.001), respectively. The accuracy of age, LDH, tumor size, and SUVmax in predicting lymphoma was 84.8%, 67.8%, 85.2%, and 78.3% respectively. The combination of the four above parameters could improve the predictive accuracy to 89.1%, and in the validation cohort, this combination increased the predictive accuracy to 87.8%.

CONCLUSIONS

SUVmax on F-FDG PET-CT has the potential ability to discriminate lymphomas from TETs in the diagnosis of anterior mediastinal masses, and the combination of SUVmax with clinical parameters can improve the diagnostic accuracy. This combination may therefore may be helpful in avoiding unnecessary operation in patients with anterior mediastinal lymphomas.

摘要

背景

前纵隔肿块相对少见,纵隔淋巴瘤是最容易与胸腺上皮肿瘤(TETs)混淆的恶性肿瘤。本研究的目的是探讨氟脱氧葡萄糖正电子发射断层扫描-计算机断层扫描(F-FDG PET-CT)检查结果与临床参数相结合是否有助于鉴别前纵隔肿块中的淋巴瘤与TETs。

方法

本回顾性研究连续纳入了2016年8月至2022年3月期间在肿瘤切除或活检前1至2周接受F-FDG PET-CT检查的304例前纵隔肿块患者(244例TETs和60例淋巴瘤)。分析了肿瘤的最大标准化摄取值(SUVmax)与组织学亚型患者临床参数之间的相关性。采用受试者操作特征曲线分析获得年龄、乳酸脱氢酶(LDH)、肿瘤大小和SUVmax预测淋巴瘤的最佳截断值。采用逻辑回归分析确定淋巴瘤的潜在预测因素。

结果

与TETs相比,淋巴瘤与患者年龄较小、LDH水平较高、肿瘤较大和SUVmax较高显著相关(P<0.001)。在建模队列中,年龄≤40.5岁、LDH水平≥197 U/L、肿瘤大小≥10.72 cm和SUVmax≥11.95被确定为淋巴瘤的独立预测因素,比值比分别为20.14 [95%置信区间(CI):6.02-67.40;P<0.001]、4.89(95% CI:1.27-18.89;P=0.021)、8.82(95% CI:2.31-33.69;P=0.001)和30.01(95% CI:6.59-136.72;P<0.001)。年龄、LDH、肿瘤大小和SUVmax预测淋巴瘤的准确率分别为84.8%、67.8%、85.2%和78.3%。上述四个参数的组合可将预测准确率提高至89.1%,在验证队列中,该组合将预测准确率提高至87.8%。

结论

F-FDG PET-CT上的SUVmax在诊断前纵隔肿块时具有区分淋巴瘤与TETs的潜在能力,SUVmax与临床参数相结合可提高诊断准确性。因此,这种组合可能有助于避免前纵隔淋巴瘤患者进行不必要的手术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ed9/10895101/5c1914eabd40/qims-14-02-1944-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ed9/10895101/8f262b97cef0/qims-14-02-1944-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ed9/10895101/2e1eb173be0e/qims-14-02-1944-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ed9/10895101/57185ac3a083/qims-14-02-1944-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ed9/10895101/5c1914eabd40/qims-14-02-1944-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ed9/10895101/8f262b97cef0/qims-14-02-1944-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ed9/10895101/2e1eb173be0e/qims-14-02-1944-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ed9/10895101/57185ac3a083/qims-14-02-1944-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ed9/10895101/5c1914eabd40/qims-14-02-1944-f4.jpg

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