Gelardi Fabrizia, Cavinato Lara, De Sanctis Rita, Ninatti Gaia, Tiberio Paola, Rodari Marcello, Zambelli Alberto, Santoro Armando, Fernandes Bethania, Chiti Arturo, Antunovic Lidija, Sollini Martina
Department of Biomedical Sciences, Humanitas University, 20072 Pieve Emanuele, Italy.
Faculty of Medicine and Surgery, Vita-Salute San Raffaele University, 20132 Milan, Italy.
Diagnostics (Basel). 2024 Oct 17;14(20):2312. doi: 10.3390/diagnostics14202312.
Recently, radiomics has emerged as a possible image-derived biomarker, predominantly stemming from retrospective analyses. We aimed to prospectively assess the predictive role of [F]FDG-PET radiomics in breast cancer (BC).
Patients affected by stage I-III BC eligible for neoadjuvant chemotherapy (NAC) staged with [F]FDG-PET/CT were prospectively enrolled. The pathological response to NAC was assessed on surgical specimens. From each primary breast lesion, we extracted radiomic PET features and their predictive role with respect to pCR was assessed. Uni- and multivariate statistics were used for inference; principal component analysis (PCA) was used for dimensionality reduction.
We analysed 93 patients (53 HER2+ and 40 triple-negative (TNBC)). pCR was achieved in 44/93 cases (24/53 HER2+ and 20/40 TNBC). Age, molecular subtype, Ki67 percent, and stage could not predict pCR in multivariate analysis. In univariate analysis, 10 radiomic indices resulted in < 0.1. We found that 3/22 radiomic principal components were discriminative for pCR. Using a cross-validation approach, radiomic principal components failed to discriminate pCR groups but predicted the stage (mean accuracy = 0.79 ± 0.08).
This study shows the potential of PET radiomics for staging purposes in BC; the possible role of radiomics in predicting the pCR response to NAC in BC needs to be further investigated.
最近，放射组学已成为一种可能的图像衍生生物标志物，主要源于回顾性分析。我们旨在前瞻性评估[F]FDG-PET放射组学在乳腺癌（BC）中的预测作用。
前瞻性纳入符合新辅助化疗（NAC）条件且经[F]FDG-PET/CT分期的I-III期BC患者。对手术标本评估NAC的病理反应。从每个原发性乳腺病变中提取放射组学PET特征，并评估其对pCR的预测作用。使用单变量和多变量统计进行推断；主成分分析（PCA）用于降维。
我们分析了93例患者（53例HER2+和40例三阴性（TNBC））。44/93例患者实现了pCR（24/53例HER2+和20/40例TNBC）。在多变量分析中，年龄、分子亚型、Ki67百分比和分期无法预测pCR。在单变量分析中，10个放射组学指标的P值<0.1。我们发现22个放射组学主成分中有3个对pCR具有判别性。使用交叉验证方法，放射组学主成分未能区分pCR组，但可预测分期（平均准确率=0.79±0.08）。
本研究显示了PET放射组学在BC分期中的潜力；放射组学在预测BC对NAC的pCR反应中的可能作用需要进一步研究。
