Image Processing

Method for detecting voxelwise changes in fluorodeoxyglucose-positron emission tomography brain images via background adjustment in cancer clinical trials

[+] Author Affiliations
Lei Qin, Keisha McCall

Dana-Farber Cancer Institute, Department of Imaging, Boston, Massachusetts, United States

Armin Schwartzman

University of California, San Diego, Division of Biostatistics, La Jolla, California, United States

Nezamoddin N. Kachouie

Florida Institute of Technology, Department of Mathematical Sciences, Melbourne, Florida, United States

Jeffrey T. Yap

University of Utah, Huntsman Cancer Institute, Department of Radiology and Imaging Sciences, Salt Lake City, Utah, United States

J. Med. Imag. 4(2), 024006 (Jun 01, 2017). doi:10.1117/1.JMI.4.2.024006
History: Received December 30, 2016; Accepted May 10, 2017
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Abstract.  An important challenge to using fluorodeoxyglucose-positron emission tomography (FDG-PET) in clinical trials of brain tumor patients is to identify malignant regions whose metabolic activity shows significant changes between pretreatment and a posttreatment scans in the presence of high normal brain background metabolism. This paper describes a semiautomated processing and analysis pipeline that is able to detect such changes objectively with a given false detection rate. Image registration and voxelwise comparison of the pre- and posttreatment images were performed. A key step is adjustment of the observed difference by the estimated background change at each voxel, thereby overcoming the confounding effect of spatially heterogeneous metabolic activity in the brain. Components of the proposed method were validated via phantom experiments and computer simulations. It achieves a false response volume accuracy of 0.4% at a significance threshold of 3 standard deviations. It is shown that the proposed methodology can detect lesion response with 100% accuracy with a tumor-to-background-ratio as low as 1.5, and it is not affected by the background brain glucose metabolism change. We also applied the method to FDG-PET patient images from a clinical trial to assess treatment effects of lapatinib, which demonstrated significant changes in metabolism corresponding to tumor regions.

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© 2017 Society of Photo-Optical Instrumentation Engineers

Citation

Lei Qin ; Armin Schwartzman ; Keisha McCall ; Nezamoddin N. Kachouie and Jeffrey T. Yap
"Method for detecting voxelwise changes in fluorodeoxyglucose-positron emission tomography brain images via background adjustment in cancer clinical trials", J. Med. Imag. 4(2), 024006 (Jun 01, 2017). ; http://dx.doi.org/10.1117/1.JMI.4.2.024006


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