Detecting Aggressive Papillary Thyroid Carcinoma Using Hyperspectral Imaging and Radiomic Features

Hyperspectral imaging (HSI) and radiomics have the potential to improve the accuracy of tumor malignancy prediction and assessment. In this work, we extracted radiomic features of fresh surgical papillary thyroid carcinoma (PTC) specimen that were imaged with HSI. A total of 107 unique radiomic features were extracted. This study includes 72 ex-vivo tissue specimens from 44 patients with pathology-confirmed PTC. With the dilated hyperspectral images, the shape feature of least axis length was able to predict the tumor aggressiveness with a high accuracy. The HSI-based radiomic method may provide a useful tool to aid oncologists in determining tumors with intermediate to high risk and in clinical decision making.

Automated summary

This study utilizes hyperspectral imaging (HSI) and radiomics to extract radiomic features of papillary thyroid carcinoma (PTC) specimens, and successfully predicts tumor aggressiveness through shape features. The HSI-based radiomic method provides a useful tool for oncologists to determine tumors with intermediate to high risk and make clinical decisions.