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利用食管腺癌原发肿瘤的治疗前PET影像组学预测淋巴结转移:一项外部验证研究

Prediction of lymph node metastases using pre-treatment PET radiomics of the primary tumour in esophageal adenocarcinoma: an external validation study.

作者信息

Zhang Chong, Shi Zhenwei, Kalendralis Petros, Whybra Phil, Parkinson Craig, Berbee Maaike, Spezi Emiliano, Roberts Ashley, Christian Adam, Lewis Wyn, Crosby Tom, Dekker Andre, Wee Leonard, Foley Kieran G

机构信息

Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands.

School of Engineering, Cardiff University, Cardiff, UK.

出版信息

Br J Radiol. 2021 Feb 1;94(1118):20201042. doi: 10.1259/bjr.20201042. Epub 2020 Dec 11.

Abstract

OBJECTIVES

To improve clinical lymph node staging (cN-stage) in oesophageal adenocarcinoma by developing and externally validating three prediction models; one with clinical variables only, one with positron emission tomography (PET) radiomics only, and a combined clinical and radiomics model.

METHODS

Consecutive patients with fluorodeoxyglucose (FDG) avid tumours treated with neoadjuvant therapy between 2010 and 2016 in two international centres ( = 130 and = 60, respectively) were included. Four clinical variables (age, gender, clinical T-stage and tumour regression grade) and PET radiomics from the primary tumour were used for model development. Diagnostic accuracy, area under curve (AUC), discrimination and calibration were calculated for each model. The prognostic significance was also assessed.

RESULTS

The incidence of lymph node metastases was 58% in both cohorts. The areas under the curve of the clinical, radiomics and combined models were 0.79, 0.69 and 0.82 in the developmental cohort, and 0.65, 0.63 and 0.69 in the external validation cohort, with good calibration demonstrated. The area under the curve of current cN-stage in development and validation cohorts was 0.60 and 0.66, respectively. For overall survival, the combined clinical and radiomics model achieved the best discrimination performance in the external validation cohort (X = 6.08, df = 1, = 0.01).

CONCLUSION

Accurate diagnosis of lymph node metastases is crucial for prognosis and guiding treatment decisions. Despite finding improved predictive performance in the development cohort, the models using PET radiomics derived from the primary tumour were not fully replicated in an external validation cohort.

ADVANCES IN KNOWLEDGE

This international study attempted to externally validate a new prediction model for lymph node metastases using PET radiomics. A model combining clinical variables and PET radiomics improved discrimination of lymph node metastases, but these results were not externally replicated.

摘要

目的

通过开发并外部验证三个预测模型,提高食管腺癌的临床淋巴结分期(cN分期);一个仅包含临床变量,一个仅包含正电子发射断层扫描(PET)影像组学,还有一个是临床与影像组学相结合的模型。

方法

纳入2010年至2016年间在两个国际中心接受新辅助治疗的连续的氟脱氧葡萄糖(FDG)摄取阳性肿瘤患者(分别为n = 130和n = 60)。四个临床变量(年龄、性别、临床T分期和肿瘤退缩分级)以及原发肿瘤的PET影像组学数据用于模型开发。计算每个模型的诊断准确性、曲线下面积(AUC)、区分度和校准度。还评估了预后意义。

结果

两个队列中淋巴结转移的发生率均为58%。在开发队列中,临床模型、影像组学模型和联合模型的曲线下面积分别为0.79、0.69和0.82,在外部验证队列中分别为0.65、0.63和0.69,显示出良好的校准度。开发队列和验证队列中当前cN分期的曲线下面积分别为0.60和0.66。对于总生存期,临床与影像组学联合模型在外部验证队列中实现了最佳的区分性能(χ² = 6.08,自由度 = 1,P = 0.01)。

结论

准确诊断淋巴结转移对于预后和指导治疗决策至关重要。尽管在开发队列中发现预测性能有所提高,但使用源自原发肿瘤的PET影像组学的模型在外部验证队列中并未完全重复。

知识进展

这项国际研究试图使用PET影像组学对淋巴结转移的新预测模型进行外部验证。结合临床变量和PET影像组学的模型改善了对淋巴结转移的区分度,但这些结果未在外部重复验证。

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