Background/Objectives: Neuroendocrine tumors (NETs) of the lung account for about 30% of NETs. In localized and locally advanced forms, radical surgical resection is the standard of care. Although considered indolent tumors, they appear to be susceptible to post-surgical recurrence, with rates differing between typical and atypical carcinoid. Although still debated, several clinicopathologic factors are potentially associated with recurrence. The aim of this retrospective/prospective observational study is to evaluate the predictive role of clinicopathological factors and radiomics features in patients with NET of the lung. Methods: From January 2021 to April 2024, 45 consecutive patients who underwent radical (R0) surgery for lung NET at the ENETS Center of Excellence of the Sant’Andrea Hospital were enrolled, all with at least 12 months of postoperative follow-up and availability of preoperative unenhanced chest CT. Clinicopathologic and radiomic factors were considered (107 radiomic features). Of the individual characteristics, the impact on recurrence was assessed by univariate logistic regression. Results: Among the 45 patients included, 4 patients (8.9%) experienced disease recurrence. Among the clinicopathological features, major age at diagnosis (p= 0.020), atypical carcinoid (p= 0.010), presence of functional syndrome (p= 0.002), advanced stage at diagnosis (p= 0.013), necrosis (p= 0.017) higher Ki-67 (p= 0.001), higher mitotic count (p= 0.006), and pathologic lymph node (p= 0.006) were associated with disease recurrence. Three radiomic features were found to predict recurrence: DependenceEntropy (p= 0.049), DependenceNonUniformityNormalized (p= 0.024), and Elongation (p= 0.039). In this preliminary analysis, multivariate analysis was not performed due to the small sample size. Conclusions: This study has shown that radiomics can be a valuable tool in predicting recurrence. Currently, to our knowledge, no other studies on the possible application of radiomics as prognostic factors in patients with lung NET have been published. These encouraging findings warrant further investigations with larger, multicenter cohorts to validate these results and implement them by constructing a predictive model of recurrence.
背景/目的：肺神经内分泌肿瘤约占所有神经内分泌肿瘤的30%。对于局限性和局部进展期肿瘤，根治性手术切除是标准治疗方案。尽管这类肿瘤通常被认为具有惰性，但术后仍存在复发风险，且典型与非典型类癌的复发率存在差异。尽管存在争议，多项临床病理因素可能与复发相关。本项回顾性/前瞻性观察性研究旨在评估临床病理因素及影像组学特征对肺神经内分泌肿瘤患者的预测价值。 方法：2021年1月至2024年4月期间，连续纳入在圣安德烈医院ENETS卓越中心接受根治性（R0）手术治疗的45例肺神经内分泌肿瘤患者，所有患者均具有至少12个月的术后随访资料及术前平扫胸部CT影像。研究分析了临床病理因素及107项影像组学特征。通过单因素逻辑回归评估各因素对复发的影响。 结果：在纳入的45例患者中，4例（8.9%）出现疾病复发。临床病理特征中，确诊年龄较大（p=0.020）、非典型类癌（p=0.010）、存在功能性综合征（p=0.002）、确诊时分期较晚（p=0.013）、存在坏死（p=0.017）、较高Ki-67指数（p=0.001）、较高核分裂计数（p=0.006）以及病理淋巴结阳性（p=0.006）与疾病复发显著相关。研究发现三项影像组学特征可预测复发：依赖熵（p=0.049）、归一化依赖非均匀性（p=0.024）和伸长性（p=0.039）。由于样本量较小，本次初步分析未进行多变量分析。 结论：本研究表明影像组学可作为预测复发的有效工具。据我们所知，目前尚未见其他关于影像组学作为肺神经内分泌肿瘤预后因素应用的研究发表。这些积极发现值得通过更大规模的多中心队列研究进行验证，并通过构建复发预测模型加以完善。
肿瘤(癌症)患者之家