FLT PET Radiomics for Response Prediction to Chemoradiation Therapy in Head and Neck Squamous Cell Cancer

Ethan J Ulrich; Yusuf Menda; Laura L Boles Ponto; Carryn M Anderson; Brian J Smith; John J Sunderland; Michael M Graham; John M Buatti; Reinhard R Beichel

doi:10.18383/j.tom.2018.00038

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FLT PET Radiomics for Response Prediction to Chemoradiation Therapy in Head and Neck Squamous Cell Cancer

Journal article

Open access

Peer reviewed

FLT PET Radiomics for Response Prediction to Chemoradiation Therapy in Head and Neck Squamous Cell Cancer

Ethan J Ulrich, Yusuf Menda, Laura L Boles Ponto, Carryn M Anderson, Brian J Smith, John J Sunderland, Michael M Graham, John M Buatti and Reinhard R Beichel

Tomography (Ann Arbor), Vol.5(1), pp.161-169

03/2019

DOI: 10.18383/j.tom.2018.00038

PMCID: PMC6403029

PMID: 30854454

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Abstract

Radiomics is an image analysis approach for extracting large amounts of quantitative information from medical images using a variety of computational methods. Our goal was to evaluate the utility of radiomic feature analysis from F-fluorothymidine positron emission tomography (FLT PET) obtained at baseline in prediction of treatment response in patients with head and neck cancer. Thirty patients with advanced-stage oropharyngeal or laryngeal cancer, treated with definitive chemoradiation therapy, underwent FLT PET imaging before treatment. In total, 377 radiomic features of FLT uptake and feature variants were extracted from volumes of interest; these features variants were defined by either the primary tumor or the total lesion burden, which consisted of the primary tumor and all FLT-avid nodes. Feature variants included normalized measurements of uptake, which were calculated by dividing lesion uptake values by the mean uptake value in the bone marrow. Feature reduction was performed using clustering to remove redundancy, leaving 172 representative features. Effects of these features on progression-free survival were modeled with Cox regression and -values corrected for multiple comparisons. In total, 9 features were considered significant. Our results suggest that smaller, more homogenous lesions at baseline were associated with better prognosis. In addition, features extracted from total lesion burden had a higher concordance index than primary tumor features for 8 of the 9 significant features. Furthermore, total lesion burden features showed lower interobserver variability.

Squamous Cell Carcinoma of Head and Neck - diagnostic imaging

Chemoradiotherapy - methods

Prognosis

Prospective Studies

Head and Neck Neoplasms - diagnostic imaging

Humans

Image Interpretation, Computer-Assisted - methods

Middle Aged

Squamous Cell Carcinoma of Head and Neck - pathology

Head and Neck Neoplasms - therapy

Male

Treatment Outcome

Positron-Emission Tomography - methods

Dideoxynucleosides

Head and Neck Neoplasms - pathology

Adult

Female

Aged

Squamous Cell Carcinoma of Head and Neck - therapy

Neoplasm Staging

Radiopharmaceuticals

Observer Variation

Details

Title: Subtitle: FLT PET Radiomics for Response Prediction to Chemoradiation Therapy in Head and Neck Squamous Cell Cancer
Creators: Ethan J Ulrich - Biomedical Engineering
Yusuf Menda - Radiology
Laura L Boles Ponto - Radiology
Carryn M Anderson - Radiation Oncology
Brian J Smith - Biostatistics, and
John J Sunderland - Radiology
Michael M Graham - Radiology
John M Buatti - Radiation Oncology
Reinhard R Beichel - Internal Medicine, University of Iowa, Iowa City, IA
Resource Type: Journal article
Publication Details: Tomography (Ann Arbor), Vol.5(1), pp.161-169
DOI: 10.18383/j.tom.2018.00038
PMID: 30854454
PMCID: PMC6403029
NLM abbreviation: Tomography
ISSN: 2379-1381
eISSN: 2379-139X
Publisher: United States
Grant note: U24 CA180918 / NCI NIH HHS R21 CA130281 / NCI NIH HHS UL1 TR002537 / NCATS NIH HHS U01 CA140206 / NCI NIH HHS P30 CA086862 / NCI NIH HHS
Language: English
Date published: 03/2019
Academic Unit: Radiology; Electrical and Computer Engineering; Pharmaceutical Sciences and Experimental Therapeutics; Biostatistics; Physics and Astronomy; Radiation Oncology; Neurosurgery; Otolaryngology; Holden Comprehensive Cancer Center
Record Identifier: 9983997997702771

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