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Proceedings Paper

Developing a low cost image marker to identify lymph node metastasis for cervical cancer patients: an initial study
Author(s): Wei Liu; Shiyu Pei; Xuxin Chen; Theresa C. Thai; Tara Castellano; Camille C. Gunderson; Kathleen Moore; Robert S. Mannel; Hong Liu; Bin Zheng; Yuchen Qiu
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Paper Abstract

This study aims to utilize the primary tumor characteristics from CT images to detect lymph node (LN) metastasis for accurately categorizing locally advanced cervical cancer patients (LACC). In clinical practice, LN metastasis is a critical indicator for patients’ prognostic assessment, which is usually investigated by PET/CT (i.e., positron emission tomography/computed tomography) examination. However, the high cost of the PET/CT imaging modality limits its application and also leads to heavy financial burden on patients. Thus it is clinically imperative to develop an economic solution for the LN metastasis identification. For this purpose, a novel image marker was developed, which is based on the primary cervical tumors segmented from CT images. Accordingly, a total of 99 handcrafted features were computed, and an optimal feature set was determined by Laplacian Score (LS) method. Next, a logistic regression model was applied on the optimal feature set to generate a likelihood score for the identification of LN metastasis. Using a retrospective dataset that contains a total of 82 LACC patients, this new model was trained and optimized by leave one out cross validation (LOOCV) strategy. The marker performance was assessed by receiver operator characteristic curve (ROC). The results indicate that the area under the ROC curve (AUC) of this identification model was 0.774±0.050, which demonstrates its strong discriminative power. This study may be able to provide gynecologic oncologists a CT image based low cost clinical marker to identify LN metastasis occurred on LACC patients.

Paper Details

Date Published: 3 March 2020
PDF: 6 pages
Proc. SPIE 11241, Biophotonics and Immune Responses XV, 112410Y (3 March 2020); doi: 10.1117/12.2548669
Show Author Affiliations
Wei Liu, Xi’an Univ. of Posts and Telecommunications (China)
Univ. of Oklahoma (United States)
Shiyu Pei, Xi’an Univ. of Posts and Telecommunications (China)
Xuxin Chen, The Univ. of Oklahoma (United States)
Theresa C. Thai, The Univ. of Oklahoma Health Sciences Ctr. (United States)
Tara Castellano, The Univ. of Oklahoma Health Sciences Ctr. (United States)
Camille C. Gunderson, The Univ. of Oklahoma Health Sciences Ctr. (United States)
Kathleen Moore, The Univ. of Oklahoma Health Sciences Ctr. (United States)
Robert S. Mannel, The Univ. of Oklahoma Health Sciences Ctr. (United States)
Hong Liu, The Univ. of Oklahoma (United States)
Bin Zheng, The Univ. of Oklahoma (United States)
Yuchen Qiu, The Univ. of Oklahoma (United States)


Published in SPIE Proceedings Vol. 11241:
Biophotonics and Immune Responses XV
Wei R. Chen, Editor(s)

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