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18F-FDG PET/CT 评分模型预测恶性胸腔积液的建立与验证。

Derivation and validation of a 18F-FDG PET/CT scoring model to predict malignant pleural effusion.

机构信息

Department of Nuclear Medicine.

Department of Radiologic Diagnosis, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang.

出版信息

Nucl Med Commun. 2022 Feb 1;43(2):177-185. doi: 10.1097/MNM.0000000000001505.

Abstract

OBJECTIVE

To develop an 18F-fluorodeoxyglucose PET/computed tomography (CT) scoring model based on metabolic and radiologic findings of the pleura and fluid to identify malignant pleural effusion.

METHODS

The PET and CT findings from patients with pleural effusion in the derivation dataset were used to develop a scoring model. Then, the diagnostic accuracy of the predictive score was verified by the validation dataset.

RESULTS

Eight parameters independently predicting malignancy were retained in the scoring model, including pleural nodules or masses (4 points), focal pleural thickening (2 points), absence of pleural loculation (2 points), thickness of mediastinal pleura involvement ≥0.5 cm (2 points), maximum standardized uptake value (SUVmax) of mediastinal pleura involvement ≥2.3 (2 points), thickness of nonmediastinal pleura involvement ≥0.5 cm (1 point), SUVmax of nonmediastinal pleura involvement ≥3.0 (1 point) and fluid SUVmax ≥1.6 (1 point). The operating characteristics of the PET/CT score were 0.958 area under the curve (AUC), 88.6% sensitivity, 91.2% specificity, 10.09 positive likelihood ratio and 0.13 negative likelihood ratio, with 6 points as the threshold. These values in the validation dataset were 0.947, 91.7%, 88.4%, 7.91 and 0.094, respectively. No difference was found in AUCs between the derivation and validation datasets (z = 0.517, P = 0.697). The negative predictive value was 99.4% in the score from 0 to 2, and the positive predictive value was 98.3% for patients with score between 9 and 15.

CONCLUSIONS

The PET/CT scoring model is a valuable strategy to help physicians to distinguish malignant-benign pleural effusion and stratify patients who will benefit from invasive procedures.

摘要

目的

开发一种基于胸膜和胸腔积液代谢和影像学表现的 18F-氟脱氧葡萄糖正电子发射断层扫描/计算机断层扫描(PET/CT)评分模型,以识别恶性胸腔积液。

方法

利用胸腔积液患者的 PET 和 CT 发现,在原始数据集开发评分模型。然后,通过验证数据集验证预测评分的诊断准确性。

结果

评分模型中保留了 8 个独立预测恶性肿瘤的参数,包括胸膜结节或肿块(4 分)、局限性胸膜增厚(2 分)、无胸膜分隔(2 分)、纵隔胸膜受累厚度≥0.5cm(2 分)、纵隔胸膜受累最大标准摄取值(SUVmax)≥2.3(2 分)、非纵隔胸膜受累厚度≥0.5cm(1 分)、非纵隔胸膜受累 SUVmax≥3.0(1 分)和胸腔积液 SUVmax≥1.6(1 分)。PET/CT 评分的工作特征曲线下面积(AUC)为 0.958,灵敏度为 88.6%,特异性为 91.2%,阳性似然比为 10.09,阴性似然比为 0.13,以 6 分为界值。验证数据集的相应值分别为 0.947、91.7%、88.4%、7.91 和 0.094。原始数据集和验证数据集的 AUC 无差异(z=0.517,P=0.697)。评分在 0 到 2 之间时,阴性预测值为 99.4%,评分在 9 到 15 之间时,阳性预测值为 98.3%。

结论

PET/CT 评分模型是一种有价值的策略,可以帮助医生区分恶性和良性胸腔积液,并对需要进行有创检查的患者进行分层。

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