ImViA EA 7535, University of Burgundy Franche-Comte, Dijon, France; Department of Nuclear Medicine, Georges-François Leclerc Cancer Centre, Dijon, France.
ImViA EA 7535, University of Burgundy Franche-Comte, Dijon, France.
Phys Med. 2022 Nov;103:98-107. doi: 10.1016/j.ejmp.2022.09.015. Epub 2022 Oct 17.
Assessment of tumour blood flow (BF) heterogeneity using first-pass FDG PET/CT and textural feature (TF) analysis is an innovative concept. We aim to explore the relationship between BF heterogeneity measured with different TFs calculation methods and the response to neoadjuvant chemotherapy (NAC) in patients with newly diagnosed breast cancer (BC).
One hundred and twenty-five patients were enrolled. Dynamic first-pass and delayed FDG PET/CT scans were performed before NAC. Nine TFs were calculated from perfusion and metabolic PET images using relative (RR) or absolute (AR) rescaling strategies with two textural matrix calculation methods. Patients were classified according to presence or absence of a pathologic complete response (pCR) after NAC. The relationship between BF texture features and conventional features were analysed using spearman correlations. The TFs' differences between pCR and non-pCR groups were evaluated using Mann-Whitney tests and descriptive factorial discriminant analysis (FDA).
Relation between tumour BF-based TFs and global BF parameters were globally similar to those observed for tumour metabolism. None of the TFs was significantly different between pCR and non-pCR groups in the Mann-Whitney analysis, after Benjamini-Hochberg correction. Using a RR led to better discriminations between responders and non-responders in the FDA analysis. The best results were obtained by combining all the PET features, including BF ones.
A better differentiation of patients reaching a pCR was observed using a RR. Moreover, BF heterogeneity might bring a useful information when combined with metabolic PET parameters to predict the pCR after neoadjuvant chemotherapy.
使用首过 FDG PET/CT 和纹理特征(TF)分析评估肿瘤血流(BF)异质性是一个创新的概念。我们旨在探讨使用不同 TF 计算方法测量的 BF 异质性与新诊断乳腺癌(BC)患者新辅助化疗(NAC)反应之间的关系。
共纳入 125 例患者。在 NAC 前进行动态首过和延迟 FDG PET/CT 扫描。使用相对(RR)或绝对(AR)重缩放策略以及两种纹理矩阵计算方法,从灌注和代谢 PET 图像中计算 9 个 TF。根据 NAC 后是否存在病理完全缓解(pCR)对患者进行分类。使用 Spearman 相关性分析评估 BF 纹理特征与常规特征之间的关系。使用 Mann-Whitney 检验和描述性因子判别分析(FDA)评估 pCR 和非 pCR 组之间 TF 的差异。
基于肿瘤 BF 的 TF 与肿瘤代谢的全局 BF 参数之间的关系总体上相似。在 Mann-Whitney 分析中,经 Benjamini-Hochberg 校正后,RR 与 AR 之间在 pCR 和非 pCR 组之间没有显著差异。在 FDA 分析中,RR 导致更好地区分了应答者和非应答者。将包括 BF 在内的所有 PET 特征结合使用可获得最佳结果。
RR 观察到更好地区分达到 pCR 的患者。此外,当与代谢 PET 参数结合使用时,BF 异质性可能提供有用的信息,以预测新辅助化疗后的 pCR。