Pixel-level tumor margin assessment of surgical specimen with hyperspectral imaging and deep learning classification

Ling Ma, Maysam Shahedi, Ted Shi, Martin Halicek, James V. Little, Amy Y. Chen, Larry L. Myers, Baran D. Sumer, Baowei Fei

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

Abstract

Surgery is a major treatment method for squamous cell carcinoma (SCC). During surgery, insufficient tumor margin may lead to local recurrence of cancer. Hyperspectral imaging (HSI) is a promising optical imaging technique for in vivo cancer detection and tumor margin assessment. In this study, a fully convolutional network (FCN) was implemented for tumor detection and margin assessment in hyperspectral images of SCC. The FCN was trained and tested with hyperspectral images of 25 ex vivo SCC surgical specimens from 20 different patients. The network was evaluated per patient and achieved pixel-level tissue classification with an average AUC of 0.88, 0.83 accuracy, 0.84 sensitivity and 0.70 specificity. The 95% Hausdorff distance of assessed tumor margin in 17 patients was less than 2 mm, and the classification time of each tissue specimen took less than 10 seconds. The proposed method potentially facilitates intraoperative tumor margin assessment and improves surgical outcomes.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2021
Subtitle of host publicationImage-Guided Procedures, Robotic Interventions, and Modeling
EditorsCristian A. Linte, Jeffrey H. Siewerdsen
PublisherSPIE
ISBN (Electronic)9781510640252
DOIs
StatePublished - 2021
EventMedical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling - Virtual, Online
Duration: Feb 15 2021Feb 19 2021

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume11598
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling
CityVirtual, Online
Period2/15/212/19/21

Keywords

  • Classification
  • Hyperspectral imaging
  • Squamous cell carcinoma
  • Tumor margin assessment
  • U-Net

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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