Radiotranscriptomics in papillary thyroid carcinoma complement current noninvasive risk stratification system.

Area of Science:

• Oncology
• Radiology
• Medical Imaging

Background:

• Papillary thyroid carcinoma (PTC) often has a good prognosis, but overtreatment is common due to a lack of noninvasive risk assessment tools.
• Accurate preoperative risk stratification is crucial for optimizing patient management and avoiding unnecessary interventions.

Purpose of the Study:

• To develop and validate a radiomics-based approach for enhancing the preoperative assessment and risk stratification of papillary thyroid carcinoma.
• To identify reliable noninvasive tools for distinguishing between indolent and aggressive PTC subtypes.

Main Methods:

• Analysis of imaging features from 255 PTC patients using unsupervised clustering to identify distinct tumor groups.
• Construction and validation of a radiomics score using internal and external datasets.
• Transcriptomic analysis to investigate molecular profiles of identified tumor clusters.

Main Results:

• Three distinct tumor clusters were identified, with Cluster 2 showing favorable clinical and molecular characteristics.
• The radiomics score achieved high diagnostic accuracy (AUC=0.98) in predicting favorable features and treatment responses.
• Transcriptomic analysis revealed immune activation and survival-related gene expression in the favorable cluster.

Conclusions:

• A validated radiomics score offers a precise, noninvasive tool for preoperative risk stratification in PTC.
• This approach can aid in identifying patients suitable for active surveillance, potentially reducing overtreatment.
• The findings may complement existing diagnostic frameworks for personalized thyroid cancer management.