DocumentCode :
863144
Title :
Factor analysis in prostate cancer: delineation of organ structures and automatic generation of in- and output functions
Author :
Schiepers, Christiaan ; Hoh, Carl K. ; Nuyts, Johan ; Wu, Hsiao-Ming ; Phelps, Michael E. ; Dahlbom, Magnus
Author_Institution :
Los Angeles Sch. of Medicine, California Univ., Los Angeles, CA, USA
Volume :
49
Issue :
5
fYear :
2002
fDate :
10/1/2002 12:00:00 AM
Firstpage :
2338
Lastpage :
2343
Abstract :
Factor analysis (FA) is used for extracting the properties of dynamic datasets. Objective: FA was applied to dynamic studies using positron emission topography (PET) to create factor images and factor curves from which input and output functions could be derived for kinetic modeling. This noninvasive automated and image-based analysis should permit routine application of quantitative PET in cancer patients. Methods: In nine men with prostate cancer, dynamic PET studies were performed on an ECAT HR+ system. After administration of 13.5 mCi of 11C-labeled acetate, data were acquired for 20 min. Images were reconstructed with iterative algorithms, a maximum a posteriori (MAP) for transmission scans, and ordered subset expectation maximization (OSEM) for emission scans. The body contour was determined with thresholding of the transmission images. All voxels included in the body contour were used for processing. FA extracted the shape of the pure time activity curves (TACs). The factors were used to create functional images, from which a region-of-interest (ROI) could be generated with thresholding techniques. These ROIs were used to create image-based TACs. Results: The automated procedure was successful in eight out of nine patients. Minimal intervention generated reliable factors in the remaining patient. Factors are normalized; their magnitude was adjusted by a scale factor using: (1) reversed normalization and (2) image-based parameters. In principle, the input factor generated by FA has no spillover and produces a pure vascular image and curve. Factor images provided diagnostic information on tumors. The method is operator independent and reproducible. Conclusion: The automated procedure generated factors from dynamic PET data corresponding to vessels and tumor. FA can noninvasively generate input and output functions. This processing tool facilitates PET as a reproducible quantification method in routine oncological applications.
Keywords :
cancer; carbon; diagnostic radiography; iterative methods; medical computing; medical image processing; organic compounds; positron emission tomography; radioactive tracers; 11C; PET; automatic generation; body contour; cancer patients; diagnostic information; emission scans; factor analysis; factor curves; image-based analysis; iterative algorithms; maximum a posteriori; ordered subset expectation maximization; organ structure delineation; positron emission topography; prostate cancer; pure time activity curves; thresholding techniques; transmission scans; vascular image; voxels; Image analysis; Image reconstruction; Iterative algorithms; Kinetic theory; Neoplasms; Positron emission tomography; Prostate cancer; Radioactive decay; Shape; Surfaces;
fLanguage :
English
Journal_Title :
Nuclear Science, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9499
Type :
jour
DOI :
10.1109/TNS.2002.803872
Filename :
1046914
Link To Document :
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