Purpose

To investigate the [⁶⁸Ga]DOTATOC PET radiomic profile of head and neck paragangliomas (HNPGLs) and identify radiomic characteristics useful as predictors of succinate dehydrogenase genes (SDHx) pathogenic variants.

Methods

Sporadic and SDHx HNPGL patients, who underwent [⁶⁸Ga]DOTATOC PET/CT, were retrospectively included. HNPGLs were analyzed using LIFEx software, and extracted features were harmonized to correct for batch effects and confronted testing for multiple comparison. Stepwise discriminant analysis was conducted to remove redundancy and identify best discriminating features. ROC analysis was used to define optimal cut-offs. Multivariate decision-tree analysis was performed using CHAID method.

Results

34 patients harboring 60 HNPGLs (51 SDHx in 25 patients) were included. Three sporadic and nine SDHx HNPGLs were metastatic. At stepwise discriminant analysis, both GLSZM-Zone Size Non-Uniformity (ZSNU, reflecting tumor heterogeneity) and IB-TLSRE (total lesion somatostatin receptor expression) were independent predictors of genetic status, with 96.4% of lesions and 91.6% of patients correctly classified after cross validation (p < 0.001). Among non-metastatic patients, GLSZM-ZSNU and IB-TLSRE were significantly higher in sporadic than SDHx HNPGLs (p < 0.001). No differences were revealed in metastatic patients. Decision-tree analysis highlights multifocality and IB-TLSRE as useful variables, correctly identifying 6/9 sporadic and 24/25 SDHx patients. Model failed to classify one SDHA and three sporadic patients (2 metastatic).

Conclusion

Radiomics features GLSZM-ZSNU and IB-TLSRE appear to reflect HNPGLs SDHx status and tumor behavior (metastatic vs. non-metastatic). If validated, especially IB-TLSRE might represent a simple and time-efficient radiomic index for SDHx variants early screening and prediction of tumor behavior in HNPGL cases.

中文翻译：

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[68Ga]DOTATOC PET 衍生放射组学预测头颈部副神经节瘤的遗传背景：一项试点研究

目的

研究头颈副神经节瘤 (HNPGL) 的[ ^{68 Ga]DOTATOC PET 放射组学特征，并确定可用作琥珀酸脱氢酶基因 (} SDHx ) 致病变异预测因子的放射组学特征。

方法

^{回顾性纳入接受[ 68} Ga]DOTATOC PET/CT治疗的散发性和SDHx HNPGL 患者。使用 LIFEx 软件对 HNPGL 进行分析，并对提取的特征进行协调以纠正批次效应，并进行多重比较测试。进行逐步判别分析以消除冗余并识别最佳判别特征。 ROC 分析用于定义最佳截止值。使用CHAID方法进行多变量决策树分析。

结果

包括34 名携带 60 个 HNPGL 的患者（25 名患者中有 51 个SDHx ）。三个散发的和九个SDHx HNPGL 是转移性的。在逐步判别分析中，GLSZM-区域大小不均匀性（ZSNU，反映肿瘤异质性）和 IB-TLSRE（总病变生长抑素受体表达）都是遗传状态的独立预测因子，96.4% 的病变和 91.6% 的患者被正确分类交叉验证后（p < 0.001）。在非转移性患者中，散发性患者的 GLSZM-ZSNU 和 IB-TLSRE 显着高于SDHx HNPGL（p < 0.001）。转移性患者中没有发现差异。决策树分析强调多焦点和 IB-TLSRE 作为有用的变量，正确识别 6/9 散发患者和 24/25 SDHx患者。模型未能对 1 名SDHA 患者和 3 名散发患者（2 名转移性患者）进行分类。

结论

放射组学特征 GLSZM-ZSNU 和 IB-TLSRE 似乎反映了 HNPGLs SDHx状态和肿瘤行为（转移性与非转移性）。如果经过验证，特别是 IB-TLSRE 可能代表一种简单且省时的放射组学指数，用于SDHx变异的早期筛查和 HNPGL 病例中肿瘤行为的预测。