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Head and Neck Cancer: Detection of Recurrence with Three-dimensional Principal Components Analysis at Dynamic FDG PET¹

¹ From the Departments of Radiology (Y.A., R.L.W.), Internal Medicine (Nuclear Medicine) (S.M., R.L.W.), and Otolaryngology and Head and Neck Surgery (G.T.W.), the University of Michigan Medical Center, B1G505 University Hospital, 1500 E Medical Center Dr, Ann Arbor, MI 48109-0028. From the 1996 RSNA scientific assembly. Received April 1, 1998; revision requested June 25; revision received October 2; accepted December 16. Supported in part by National Institutes of Health grants CA 52880, MO1RR 00042, CA 53172, and CA 56731, and the High Technology funding initiative of the University of Michigan Medical Center and Clinical Research Center. Address reprint requests to R.L.W. (e-mail: rwahl@umich.edu).

Fully automated principal components analysis (PCA) was applied to dynamic 2-[fluorine-18]fluoro-2-deoxy-D-glucose (FDG) positron emission tomographic (PET) images obtained in 15 patients with previously treated head and neck cancer. PCA with time-activity curves incorporated kinetic information about FDG uptake, which improved tissue characterization on FDG PET images. The combination of standardized uptake value and PCA image sets likely will improve the reliability of tumor detection in head and neck cancers.

Index terms: Head and neck neoplasms, diagnosis, 20.30 • Head and neck neoplasms, emission CT (ECT), 20.12163

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