Vita-Salute San Raffaele University.
Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute.
Nucl Med Commun. 2020 Sep;41(9):896-905. doi: 10.1097/MNM.0000000000001236.
To explore the potentiality of radiomics analysis, performed on Ga-DOTATOC and fluorine-18-fluorodeoxyglucose (F-FDG) PET/computed tomography (CT) images, in predicting tumour aggressiveness and outcome in patients candidate to surgery for pancreatic neuroendocrine neoplasms (PanNENs).
Retrospective study including 61 patients who underwent Ga-DOTATOC and F-FDG PET/CT before surgery for PanNEN. Semiquantitative variables [SUVmax and somatostatin receptor density (SRD) for Ga-DOTATOC PET; SUVmax and MTV for F-FDG PET] and texture features [intensity variability, size zone variability (SZV), zone percentage, entropy; homogeneity, dissimilarity and coefficient of variation (Co-V)] have been analysed to evaluate their possible role in predicting tumour characteristics. Principal component analysis (PCA) was firstly performed and then multiple regression analyses were performed by using the extracted principal components.
Regarding Ga-DOTATOC PET, SZV, entropy, intensity variability and SRD were predictive for tumour dimension. Regarding F-FDG PET, intensity variability, SZV, homogeneity, SUVmax and MTV were predictive for tumour dimension. Four principal components were extracted from PCA: PC1 correlated with all F-FDG variables, while PC2, PC3 and PC4 with Ga-DOTATOC variables. PC1 was the only significantly predicting angioinvasion (P = 0.0222); PC4 was the only one significantly predicting lymph nodal involvement (P = 0.0151). All principal components except PC4 significantly predicted tumour dimension (P <0.0001 for PC1, P = 0.0016 for PC2 and P < 0.0001 for PC3). Co-V from Ga-DOTATOC PET/CT was predictive of the outcome.
Specific texture features derived from preoperative Ga-DOTATOC and F-FDG PET/CT could noninvasively predict specific tumour characteristics and patients' outcome, delineating the potential role of dual tracer technique and texture analysis in the risk assessment of patients with PanNENs.
探讨基于镓- DOTATOC 和氟-18-氟代脱氧葡萄糖（F-FDG）PET/CT 图像的放射组学分析在预测接受胰腺神经内分泌肿瘤（PanNENs）手术的患者肿瘤侵袭性和预后方面的潜力。
这项回顾性研究纳入了 61 例在手术前接受镓-DOTATOC 和 F-FDG PET/CT 检查的 PanNEN 患者。对半定量变量[Ga-DOTATOC PET 的 SUVmax 和生长抑素受体密度（SRD）；F-FDG PET 的 SUVmax 和 MTV]和纹理特征[强度变异性、大小区变异性（SZV）、区百分比、熵；同质性、非相似性和变异系数（Co-V）]进行了分析，以评估它们在预测肿瘤特征方面的可能作用。首先进行主成分分析（PCA），然后使用提取的主成分进行多元回归分析。
在 Ga-DOTATOC PET 方面，SZV、熵、强度变异性和 SRD 可预测肿瘤大小。在 F-FDG PET 方面，强度变异性、SZV、同质性、SUVmax 和 MTV 可预测肿瘤大小。从 PCA 中提取了四个主成分：PC1 与所有 F-FDG 变量相关，而 PC2、PC3 和 PC4 与 Ga-DOTATOC 变量相关。PC1 是唯一显著预测血管侵犯的因素（P=0.0222）；PC4 是唯一显著预测淋巴结受累的因素（P=0.0151）。除 PC4 外，所有主成分均显著预测肿瘤大小（PC1，P<0.0001；PC2，P=0.0016；PC3，P<0.0001）。Ga-DOTATOC PET/CT 的 Co-V 可预测结果。
来自术前 Ga-DOTATOC 和 F-FDG PET/CT 的特定纹理特征可无创性预测特定的肿瘤特征和患者的预后，描绘了双示踪剂技术和纹理分析在评估 PanNEN 患者风险方面的潜在作用。
