Detecting Aggressive Papillary Thyroid Carcinoma Using Hyperspectral Imaging and Radiomic Features

• Authors: Ka"Toria Leitch, University of Texas Dallas; Martin Halicek, University of Texas Dallas; Maysan Shahedi, University of Texas Dallas; James V Little, Emory University; Amy Chen, Emory University; Baowei Fei, Emory University
• Journal Title: MEDICAL IMAGING 2022: COMPUTER-AIDED DIAGNOSIS
• Volume: Volume 12033
• Publisher: SPIE-INT SOC OPTICAL ENGINEERING | 2022-01-01
• Type of Work: Article | Post-print: After Peer Review
• Publisher DOI: http://doi.org/10.1117/12.2611842
• Subjects: Health Sciences, Radiology
• Keywords: Science & Technology; Technology; Physical Sciences; Life Sciences & Biomedicine; Engineering, Biomedical; Optics; Radiology, Nuclear Medicine & Medical Imaging; Engineering; Head; Neck Cancer; Radiomics; Hyperspectral Imaging; Tissues; Tumor Aggression

Abstract

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.