Imperiale Alessio, Berti Valentina
Nuclear Medicine and Molecular Imaging, ICANS, University Hospitals of Strasbourg, University of Strasbourg, Strasbourg, France; IPHC, UMR 7178, CNRS/Unistra, Strasbourg, France.
Nuclear Medicine Unit, Careggi University Hospital, Florence, Italy; Department of Experimental and Clinical Biomedical Sciences 'Mario Serio', Florence University, Florence, Italy.
Best Pract Res Clin Endocrinol Metab. 2025 Jan;39(1):101926. doi: 10.1016/j.beem.2024.101926. Epub 2024 Aug 23.
Radiomics revolutionizes medical imaging by providing quantitative analysis that complements traditional qualitative assessments through advanced computational techniques. In this narrative review we have investigated the impact of succinate dehydrogenase (SDH) pathogenic variants on the radiomic profile of F-FDG, F-DOPA, and Ga-DOTA-peptides PET in paragangliomas, focusing on head and neck localizations (HNPGLs). This influence manifests in uptake intensity and textural heterogeneity, revealing a complex radiomic landscape that may reflect specific tumor behaviors and mutation statuses. By combining radiomic analysis with genetic data, we will gain new insights into the relationship between PET imaging features and underlying molecular changes. In the future, we envision an approach integrating macroscopic indices, such as lesion location, size, and SUV, with advanced computer-based algorithms. This comprehensive analysis could facilitate in vivo predictions of SDH pathogenic variants, thereby encouraging genetic testing, and ultimately improving patient outcomes.
放射组学通过提供定量分析彻底改变了医学成像，这种定量分析通过先进的计算技术对传统的定性评估起到补充作用。在这篇叙述性综述中，我们研究了琥珀酸脱氢酶（SDH）致病变异对副神经节瘤中F-FDG、F-DOPA和Ga-DOTA肽PET放射组学特征的影响，重点关注头颈部定位（HNPGLs）。这种影响体现在摄取强度和纹理异质性上，揭示了一个复杂的放射组学格局，可能反映特定的肿瘤行为和突变状态。通过将放射组学分析与基因数据相结合，我们将对PET成像特征与潜在分子变化之间的关系获得新的见解。未来，我们设想一种将宏观指标（如病变位置、大小和SUV）与先进的基于计算机的算法相结合的方法。这种全面分析可以促进对SDH致病变异的体内预测，从而鼓励进行基因检测，并最终改善患者的治疗结果。
