Computer-Aided Diagnosis

Forecasting new development of tumor areas using spatial and temporal distribution profiles of hemoglobin saturation in a mouse model

[+] Author Affiliations
Miguel R. Ossandon

University of Maryland Baltimore County, Department of Computer Science and Electrical Engineering, 1000 Hilltop Circle, Baltimore, Maryland 21250

National Cancer Institute, 9609 Medical Center Drive, Rockville, Maryland 20850

Dhananjay S. Phatak

University of Maryland Baltimore County, Department of Computer Science and Electrical Engineering, 1000 Hilltop Circle, Baltimore, Maryland 21250

Brian S. Sorg

National Cancer Institute, 9609 Medical Center Drive, Rockville, Maryland 20850

Konstantinos Kalpakis

University of Maryland Baltimore County, Department of Computer Science and Electrical Engineering, 1000 Hilltop Circle, Baltimore, Maryland 21250

J. Med. Imag. 1(1), 014503 (Jun 20, 2014). doi:10.1117/1.JMI.1.1.014503
History: Received November 5, 2013; Revised April 20, 2014; Accepted May 19, 2014
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Abstract.  Features of the tumor microenvironment (TME), such as hemoglobin saturation (HbSat), can provide valuable information on early development and progression of tumors. HbSat correlates with high metabolism and precedes the formation of angiogenic tumors; therefore, changes in HbSat profile can be used as a biomarker for early cancer detection. In this project, we develop a methodology to evaluate HbSat for forecasting early tumor development in a mouse model. We built a delta (δ) cumulative feature that includes spatial and temporal distribution of HbSat for classifying tumor/normal areas. Using a two-class (normal and tumor) logistic regression, the δ feature successfully forecasts tumor areas in two window chamber mice (AUC=0.90 and 0.85). To assess the performance of the logistic regression-based classifier utilizing the δ feature of each region, we conduct a 10-fold cross-validation analysis (AUC of the ROC=0.87). These results show that the TME features based on HbSat can be used to evaluate tumor progression and forecast new occurrences of tumor areas.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Miguel R. Ossandon ; Dhananjay S. Phatak ; Brian S. Sorg and Konstantinos Kalpakis
"Forecasting new development of tumor areas using spatial and temporal distribution profiles of hemoglobin saturation in a mouse model", J. Med. Imag. 1(1), 014503 (Jun 20, 2014). ; http://dx.doi.org/10.1117/1.JMI.1.1.014503


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