Detecting aggressive papillary thyroid carcinoma using hyperspectral imaging and radiomic features

Ka'Toria Leitch, Martin Halicek, Maysam Shahedi, James V. Little, Amy Y. Chen, Baowei Fei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2022
Subtitle of host publicationComputer-Aided Diagnosis
EditorsKaren Drukker, Khan M. Iftekharuddin
PublisherSPIE
ISBN (Electronic)9781510649415
DOIs
StatePublished - 2022
Externally publishedYes
EventMedical Imaging 2022: Computer-Aided Diagnosis - Virtual, Online
Duration: Mar 21 2022Mar 27 2022

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume12033
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2022: Computer-Aided Diagnosis
CityVirtual, Online
Period3/21/223/27/22

Keywords

  • Head
  • Hyperspectral Imaging
  • Neck Cancer
  • Radiomics
  • Tissues
  • Tumor Aggression

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

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