Js. Liow et al., Comparison of voxel- and volume-of-interest-based analyses in FDG PET scans of HIV positive and healthy individuals, J NUCL MED, 41(4), 2000, pp. 612-621
Citations number
23
Categorie Soggetti
Radiology ,Nuclear Medicine & Imaging","Medical Research Diagnosis & Treatment
Abnormal glucose metabolic patterns in the brain have been reported for HIV
-1 seropositive (HIV+) patients when compared with seronegative healthy ind
ividuals. The metabolic covariance pattern obtained from voxel- or volume-o
f-interest (VOI)-based multivariate data analysis techniques can be used to
characterize disease and potentially to detect and monitor disease progres
sion in the early stage of AIDS dementia complex. However, the arbitrary sm
oothing typically applied to PET data during reconstruction and processing
to reduce noise has an unknown effect on the data, especially for the voxel
-based analysis. Methods: To investigate the impact of smoothing on a discr
imination task, we applied principal component analysis with scaled subprof
ile-model preprocessing (SSM/PCA) followed by Fisher discriminant analysis
to FDG PET data that were reconstructed and processed with different degree
s of smoothing. Receiver operating characteristic curves were used to compa
re the ability of derived metabolic covariance patterns to discriminate HIV
+ patients from healthy volunteers. Results: For the voxel-based analysis,
we found that the spatial distribution of voxel weights from the SSM/PCA an
alysis suggested edge effects along major tissue and cerebrospinal fluid bo
undaries, indicative of a disease-specific pattern of cerebral atrophy for
the HIV+ patients. In terms of its discrimination performance, this metabol
ic covariance pattern is stable and insensitive to a wide range of smoothin
g kernels, except for ramp reconstruction and Hanning reconstruction with 7
x 7 x 7 block smoothing. In these reconstructions, the discrimination perf
ormance decreased as a result of high image noise and excessive smoothing,
respectively. Our results also indicated that if sufficient variance from t
he VOI measurements is included, the overall performance of a conventional
VOI-based analysis can be similar to that of the voxel-based analysis for t
he same discrimination task. However, the VOI-based analysis performed poor
ly at low false-positive fraction and is less tolerant to noise in the meta
bolic covariance pattern than the voxel-based analysis. Conclusion: We have
obtained a unique covariance pattern of brain glucose metabolism for HIVpatients compared with healthy volunteers. Discrimination based on this cov
ariance pattern was found to be insensitive to a wide range of image smooth
ness.