Validation of a standardized normalization template for statistical parametric mapping analysis of 123I-FP-CIT images.
Identifieur interne : 000D62 ( PubMed/Corpus ); précédent : 000D61; suivant : 000D63Validation of a standardized normalization template for statistical parametric mapping analysis of 123I-FP-CIT images.
Auteurs : Aurélie Kas ; Pierre Payoux ; Marie-Odile Habert ; Zoulikha Malek ; Yann Cointepas ; Georges El Fakhri ; Philippe Chaumet-Riffaud ; Emmanuel Itti ; Philippe RemySource :
- Journal of nuclear medicine : official publication, Society of Nuclear Medicine [ 0161-5505 ] ; 2007.
English descriptors
- KwdEn :
- Aged, Brain (diagnostic imaging), Brain (metabolism), Data Interpretation, Statistical, Dopamine Plasma Membrane Transport Proteins (metabolism), Essential Tremor (diagnostic imaging), Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Parkinson Disease (diagnostic imaging), Pilot Projects, Radionuclide Imaging, Radiopharmaceuticals, Tropanes.
- MESH :
- chemical , metabolism : Dopamine Plasma Membrane Transport Proteins.
- diagnostic imaging : Brain, Essential Tremor, Parkinson Disease.
- metabolism : Brain.
- Aged, Data Interpretation, Statistical, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Pilot Projects, Radionuclide Imaging, Radiopharmaceuticals, Tropanes.
Abstract
(123)I-FP-CIT ((123)I-N-omega-fluoropropyl-2beta-carbomethoxy-3beta-(4-iodophenyl)nortropane) is a SPECT dopamine transporter (DAT) tracer that probes dopaminergic cell loss in Parkinson's disease (PD). Quantification of (123)I-FP-CIT images is performed at equilibrium using a ratio (BR) of specific (striatal) to nonspecific (occipital) uptake with values obtained from regions of interest drawn manually over these structures. Statistical parametric mapping (SPM) is a fully automated voxel-based statistical approach that has great potential in the context of DAT imaging. However, the accuracy of the spatial normalization provided by SPM has not been validated for (123)I-FP-CIT images. Our first aim was to create an (123)I-FP-CIT template that does not require the acquisition of patient-specific MRI and to validate the spatial normalization procedure. Next, we hypothesized that this customized template could be used by different SPECT centers without affecting the outcomes of imaging analyses.
DOI: 10.2967/jnumed.106.038646
PubMed: 17704252
Links to Exploration step
pubmed:17704252Le document en format XML
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<front><div type="abstract" xml:lang="en">(123)I-FP-CIT ((123)I-N-omega-fluoropropyl-2beta-carbomethoxy-3beta-(4-iodophenyl)nortropane) is a SPECT dopamine transporter (DAT) tracer that probes dopaminergic cell loss in Parkinson's disease (PD). Quantification of (123)I-FP-CIT images is performed at equilibrium using a ratio (BR) of specific (striatal) to nonspecific (occipital) uptake with values obtained from regions of interest drawn manually over these structures. Statistical parametric mapping (SPM) is a fully automated voxel-based statistical approach that has great potential in the context of DAT imaging. However, the accuracy of the spatial normalization provided by SPM has not been validated for (123)I-FP-CIT images. Our first aim was to create an (123)I-FP-CIT template that does not require the acquisition of patient-specific MRI and to validate the spatial normalization procedure. Next, we hypothesized that this customized template could be used by different SPECT centers without affecting the outcomes of imaging analyses.</div>
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<Abstract><AbstractText Label="UNLABELLED">(123)I-FP-CIT ((123)I-N-omega-fluoropropyl-2beta-carbomethoxy-3beta-(4-iodophenyl)nortropane) is a SPECT dopamine transporter (DAT) tracer that probes dopaminergic cell loss in Parkinson's disease (PD). Quantification of (123)I-FP-CIT images is performed at equilibrium using a ratio (BR) of specific (striatal) to nonspecific (occipital) uptake with values obtained from regions of interest drawn manually over these structures. Statistical parametric mapping (SPM) is a fully automated voxel-based statistical approach that has great potential in the context of DAT imaging. However, the accuracy of the spatial normalization provided by SPM has not been validated for (123)I-FP-CIT images. Our first aim was to create an (123)I-FP-CIT template that does not require the acquisition of patient-specific MRI and to validate the spatial normalization procedure. Next, we hypothesized that this customized template could be used by different SPECT centers without affecting the outcomes of imaging analyses.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">The spatial normalization to the customized template created with SPM (template A1) was validated using (123)I-FP-CIT images obtained from 6 subjects with essential tremor (ET) with normal DAT status and 6 PD patients. Variability in BR values due to the normalization was evaluated using striatal volume of interest (VOI). To determine whether different SPECT centers could use a unique (123)I-FP-CIT template, we generated 3 other (123)I-FP-CIT templates using different subjects and image-processing schemes. The interchangeability of these templates was assessed using (a) putamen BR values analyzed with the intraclass correlation coefficient (ICC) and the Bland-Altman graphical analysis, and (b) SPM analysis comparing the results of group comparisons-that is, ET versus PD, obtained after normalization to each of the 4 templates.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">There was no significant difference between pre- and post-normalization striatal BR values in our study. The mean variability calculated with putamen VOI values after normalization to each template was <10%, with the lowest ICC of 98%. Intergroup analyses performed with VOI and SPM approaches provided similar results independently of the template used.</AbstractText>
<AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">SPM normalization was accurate even in subjects with low striatal (123)I-FP-CIT uptake, making it a promising approach for automatic analysis of (123)I-FP-CIT images using a single customized template at different centers.</AbstractText>
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