Nuclear Medicine Department and Molecular Imaging Group, Complexo Hospitalario Universitario de Santiago de Compostela CHUS-IDIS, Travesía da Choupana s/n, Santiago de Compostela, 15706, Spain.
Molecular Imaging Group, Department of Radiology, Faculty of Medicine, University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, 15782, Spain.
Eur J Nucl Med Mol Imaging. 2018 Feb;45(2):196-206. doi: 10.1007/s00259-017-3830-1. Epub 2017 Sep 21.
This study aims to determine whether PET textural features measured with a new dedicated breast PET scanner reflect biological characteristics of breast tumors.
One hundred and thirty-nine breast tumors from 127 consecutive patients were included in this analysis. All of them underwent a F-FDG PET scan before treatment. Well-known PET quantitative parameters such as SUV , SUV , metabolically active tumor volume (MATV) and total lesion glycolysis (TLG) were extracted. Together with these parameters, local, regional, and global heterogeneity descriptors, which included five textural features (TF), were computed. Immunohistochemical classification of breast cancer considered five subtypes: luminal A like (LA), luminal B like/HER2 - (LB -), luminal B like/HER2+ (LB+), HER2-positive-non-luminal (HER2pnl), and triple negative (TN). Associations between PET features and tumor characteristics were assessed using non-parametric hypothesis tests.
Along with well-established associations, new correlations were found. HER2-positive tumors had significantly higher uptake (p < 0.001, AUCs > 0.70) and presented different global and regional heterogeneity (p = 0.002, p = 0.016, respectively, AUCs < 0.70). Nine out of ten analyzed features were significantly associated with immunohistochemical subtype. Uptake was lower for LA tumors (p < 0.001) with AUCs ranging from 0.71 to 0.88 for each subgroup comparison. Heterogeneity metrics were significantly associated when comparing LA and LB - (p < 0.01), being regional heterogeneity metrics more discriminative than any other parameter (AUC = 0.80 compared to AUC = 0.71 for SUV). LB+ and HER2pnl tumors also showed more regional heterogeneity than LA tumors (AUCs = 0.79 and 0.84, respectively). After comparison with whole-body PET studies, we observed an overall improvement in the classification ability of both non-heterogeneity metrics and textural features.
PET parameters extracted from high-resolution dedicated breast PET images showed new and stronger correlations with immunohistochemical factors and immunohistochemical subtype of breast cancer compared to whole-body PET.
本研究旨在确定使用新型专用乳腺 PET 扫描仪测量的 PET 纹理特征是否反映乳腺肿瘤的生物学特征。
本分析纳入了 127 例连续患者的 139 个乳腺肿瘤。所有患者在治疗前均进行了 F-FDG PET 扫描。提取了包括 SUVmax、SUVmean、代谢活跃肿瘤体积（MATV）和总病变糖酵解（TLG）在内的知名 PET 定量参数。同时计算了包括 5 个纹理特征（TF）在内的局部、区域和全局异质性描述符。乳腺癌的免疫组织化学分类考虑了 5 个亚型：Luminal A 样（LA）、Luminal B 样/HER2-（LB-）、Luminal B 样/HER2+（LB+）、HER2 阳性非 luminal（HER2pnl）和三阴性（TN）。使用非参数假设检验评估 PET 特征与肿瘤特征之间的关联。
除了已建立的关联外，还发现了新的相关性。HER2 阳性肿瘤摄取明显较高（p<0.001，AUCs>0.70），并且表现出不同的全局和区域异质性（p=0.002，p=0.016，AUCs<0.70）。分析的 10 个特征中有 9 个与免疫组织化学亚型显著相关。LA 肿瘤摄取明显较低（p<0.001），每个亚组比较的 AUC 范围为 0.71 至 0.88。当比较 LA 和 LB-时，异质性指标具有显著相关性（p<0.01），与 SUV 相比，区域异质性指标具有更好的区分能力（AUC=0.80 与 AUC=0.71）。LB+和 HER2pnl 肿瘤的区域异质性也高于 LA 肿瘤（AUCs 分别为 0.79 和 0.84）。与全身 PET 研究比较后，我们观察到非异质性指标和纹理特征的分类能力均有总体提高。
与全身 PET 相比，从高分辨率专用乳腺 PET 图像中提取的 PET 参数与乳腺癌的免疫组织化学因素和免疫组织化学亚型显示出更强的新相关性。
