Multiparametric radiomics for predicting the aggressiveness of papillary thyroid carcinoma using hyperspectral images

Ka'Toria Edwards; Martin Halicek; James V. Little; Amy Y. Chen; Baowei Fei

doi:10.1117/12.2582147

Multiparametric radiomics for predicting the aggressiveness of papillary thyroid carcinoma using hyperspectral images

Ka'Toria Edwards, Martin Halicek, James V. Little, Amy Y. Chen, Baowei Fei

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

Papillary thyroid carcinoma (PTC) is primarily treated by surgical resection. During surgery, surgeons often need intraoperative frozen analysis and pathologic consultation in order to detect PTC. In some cases pathologists cannot determine if the tumor is aggressive until the operation has been completed. In this work, we have taken tumor classification a step further by determining the tumor aggressiveness of fresh surgical specimens. We employed hyperspectral imaging (HSI) in combination with multiparametric radiomic features to complete this task. The study cohort includes 72 ex-vivo tissue specimens from 44 patients with pathology-confirmed PTC. A total of 67 features were extracted from this data. Using machine learning classification methods, we were able to achieve an AUC of 0.85. Our study shows that hyperspectral imaging and multiparametric radiomic features could aid in the pathological detection of tumor aggressiveness using fresh surgical spemens obtained during surgery.

Original language	English (US)
Title of host publication	Medical Imaging 2021
Subtitle of host publication	Computer-Aided Diagnosis
Editors	Maciej A. Mazurowski, Karen Drukker
Publisher	SPIE
ISBN (Electronic)	9781510640238
DOIs	https://doi.org/10.1117/12.2582147
State	Published - 2021
Event	Medical Imaging 2021: Computer-Aided Diagnosis - Virtual, Online, United States Duration: Feb 15 2021 → Feb 19 2021

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	11597
ISSN (Print)	1605-7422

Conference

Conference	Medical Imaging 2021: Computer-Aided Diagnosis
Country/Territory	United States
City	Virtual, Online
Period	2/15/21 → 2/19/21

Keywords

Cancer
Head
Hyperspectral Imaging
Neck
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

Access to Document

10.1117/12.2582147

Cite this

Edwards, KT., Halicek, M., Little, J. V., Chen, A. Y., & Fei, B. (2021). Multiparametric radiomics for predicting the aggressiveness of papillary thyroid carcinoma using hyperspectral images. In M. A. Mazurowski, & K. Drukker (Eds.), Medical Imaging 2021: Computer-Aided Diagnosis Article 1159728 (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 11597). SPIE. https://doi.org/10.1117/12.2582147

Multiparametric radiomics for predicting the aggressiveness of papillary thyroid carcinoma using hyperspectral images. / Edwards, Ka'Toria; Halicek, Martin; Little, James V. et al.
Medical Imaging 2021: Computer-Aided Diagnosis. ed. / Maciej A. Mazurowski; Karen Drukker. SPIE, 2021. 1159728 (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 11597).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Edwards, KT, Halicek, M, Little, JV, Chen, AY & Fei, B 2021, Multiparametric radiomics for predicting the aggressiveness of papillary thyroid carcinoma using hyperspectral images. in MA Mazurowski & K Drukker (eds), Medical Imaging 2021: Computer-Aided Diagnosis., 1159728, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 11597, SPIE, Medical Imaging 2021: Computer-Aided Diagnosis, Virtual, Online, United States, 2/15/21. https://doi.org/10.1117/12.2582147

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abstract = "Papillary thyroid carcinoma (PTC) is primarily treated by surgical resection. During surgery, surgeons often need intraoperative frozen analysis and pathologic consultation in order to detect PTC. In some cases pathologists cannot determine if the tumor is aggressive until the operation has been completed. In this work, we have taken tumor classification a step further by determining the tumor aggressiveness of fresh surgical specimens. We employed hyperspectral imaging (HSI) in combination with multiparametric radiomic features to complete this task. The study cohort includes 72 ex-vivo tissue specimens from 44 patients with pathology-confirmed PTC. A total of 67 features were extracted from this data. Using machine learning classification methods, we were able to achieve an AUC of 0.85. Our study shows that hyperspectral imaging and multiparametric radiomic features could aid in the pathological detection of tumor aggressiveness using fresh surgical spemens obtained during surgery.",

keywords = "Cancer, Head, Hyperspectral Imaging, Neck, Radiomics, Tissues, Tumor Aggression",

author = "Ka'Toria Edwards and Martin Halicek and Little, {James V.} and Chen, {Amy Y.} and Baowei Fei",

note = "Funding Information: This research was supported in part by the U.S. National Institutes of Health (NIH) grants (R01CA156775, R01CA204254, R01HL140325, and R21CA231911) and by the Cancer Prevention and Research Institute of Texas (CPRIT) grant RP190588. Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Medical Imaging 2021: Computer-Aided Diagnosis ; Conference date: 15-02-2021 Through 19-02-2021",

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N1 - Funding Information: This research was supported in part by the U.S. National Institutes of Health (NIH) grants (R01CA156775, R01CA204254, R01HL140325, and R21CA231911) and by the Cancer Prevention and Research Institute of Texas (CPRIT) grant RP190588. Publisher Copyright: © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

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N2 - Papillary thyroid carcinoma (PTC) is primarily treated by surgical resection. During surgery, surgeons often need intraoperative frozen analysis and pathologic consultation in order to detect PTC. In some cases pathologists cannot determine if the tumor is aggressive until the operation has been completed. In this work, we have taken tumor classification a step further by determining the tumor aggressiveness of fresh surgical specimens. We employed hyperspectral imaging (HSI) in combination with multiparametric radiomic features to complete this task. The study cohort includes 72 ex-vivo tissue specimens from 44 patients with pathology-confirmed PTC. A total of 67 features were extracted from this data. Using machine learning classification methods, we were able to achieve an AUC of 0.85. Our study shows that hyperspectral imaging and multiparametric radiomic features could aid in the pathological detection of tumor aggressiveness using fresh surgical spemens obtained during surgery.

AB - Papillary thyroid carcinoma (PTC) is primarily treated by surgical resection. During surgery, surgeons often need intraoperative frozen analysis and pathologic consultation in order to detect PTC. In some cases pathologists cannot determine if the tumor is aggressive until the operation has been completed. In this work, we have taken tumor classification a step further by determining the tumor aggressiveness of fresh surgical specimens. We employed hyperspectral imaging (HSI) in combination with multiparametric radiomic features to complete this task. The study cohort includes 72 ex-vivo tissue specimens from 44 patients with pathology-confirmed PTC. A total of 67 features were extracted from this data. Using machine learning classification methods, we were able to achieve an AUC of 0.85. Our study shows that hyperspectral imaging and multiparametric radiomic features could aid in the pathological detection of tumor aggressiveness using fresh surgical spemens obtained during surgery.

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Multiparametric radiomics for predicting the aggressiveness of papillary thyroid carcinoma using hyperspectral images

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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