Evidence map›Paper›PMID 41381774›Full record

ArticleEJNMMI research2025

Allometry correction in semi-quantitative analysis of dopamine transporter SPECT.

Thomas Buddenkotte, Ivayla Apostolova, Susanne Klutmann, Ralph Buchert

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Article in EJNMMI research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Thomas Buddenkotte *Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.
Ivayla Apostolova *Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.
Susanne KlutmannDepartment of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.
Ralph BuchertDepartment of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany. r.buchert@uke.de.ORCID http://orcid.org/0000-0002-0945-0724

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStriatal specific binding ratios (SBR) are widely used to support the interpretation of dopamine transporter SPECT scans. Automatic SBR computation often involves using affine transformations to map the individual SPECT images to an anatomical reference space for ROI analysis using predefined standard masks. This does not account for differences in volumetric scaling between brain structures since, by definition, affine transformations preserve volume ratios. However, striatal volume has been reported to scale proportional to (intracranial volume)0.4, indicating particularly pronounced “negative” allometric scaling. This study aimed to investigate the impact of disregarding allometric scaling on putamen SBR, and to propose an easy-to-implement method to avoid this issue. 656 [123I]FP-CIT SPECT (67.2 ± 11.4y, 44.2% females, 52.1/47.9% with reduced/normal striatal signal according to visual interpretation by an expert reader) were spatially normalized by affine transformation to the anatomical reference space of the Montreal Neurological Institute. Unilateral putamen SBR were estimated using hottest voxels analysis in large putamen masks predefined in the reference space. For conventional hottest voxels analysis, the number of hottest voxels was fixed at 1,250 (equivalent to 10 ml, the mean putamen volume in healthy adults). For allometry correction, the number of hottest voxels was determined separately for each subject as 1,250*DET(1−0.4), where DET is the Jacobian determinant of the affine transformation. To characterize the impact of the allometry correction on diagnostic performance, a data-driven Gaussian mixture model was employed.

resultsLinear regression in the visually normal SPECT revealed a positive correlation between uncorrected putamen SBR and DET (Pearson’s R = 0.509, 95%-CI 0.422–0.587). The correlation was significantly (p < 0.00005) weaker when allometry-corrected ROI analysis was used (R = 0.285, 95%-CI 0.180–0.383). The effect size of the distance between reduced and normal putamen SBR as determined by the Gaussian mixture model was significantly larger with than without allometry correction (3.979 versus 3.335, one-sided p < 0.0001). When using the visual expert reading as diagnostic reference standard, the overall accuracy of the dichotomized SBR was significantly improved by allometry correction (from 94.4% to 96.2%, one-sided p = 0.026).

conclusionThe diagnostic performance of semi-quantitative SBR analyses involving affine transformations to an anatomical reference space can be enhanced through the application of the proposed allometry correction.

Indexed as

[123I]FP-CITAllometric scalingAllometryDopamine transporterIoflupanePutamenSemi-quantitative analysisSpatial normalizationSpecific binding ratioSPECT

Identifiers

PMID41381774
PMCPMC12816454

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