Work

Correcting SUVR bias by accounting for radiotracer clearance in tissue: A validation study with [ 18 F]FE-PE2I PET in cross-sectional, test-retest and longitudinal cohorts

Year: 2025

Type: article

Abstract: Quantification of dopamine transporter (DAT) with [ 18 F]FE-PE2I PET is an important progression marker for Parkinson’s disease (PD). This study aimed to validate a novel correction ( SUVR c) for a less-biased estimate of SUVR by accounting for [ 18 F]FE-PE2I clearance-rate, in independent cross-sectional (38 PD, 38 controls), test-retest (9 PD) and longitudinal cohorts (21 PD). SUVR c was calculated as SUVR 1 − β ref k 2 , ref + β tar SUVR k 2 , ref R 1 . β tar and β ref are the clearance rates from the target and reference tissues. Bias relative to DVR , discriminative power, test-retest variability (TRV) and annual longitudinal change (ALC) were used to compare SUVR 50–80 min , SUVR c 50–80 min , SUVR 15–45 min and DVR. SUVR 50–80 min showed high bias across all regions (HC: mean: 48.31 ± 20.49% [range: 28.32–53.80%]; PD: 29.91 ± 13.95% [20.45–39.80%]) that was corrected by SUVR c 50–80 min (HC: −0.80 ± 12.72% [−9.69–11.64%]; PD: −0.13 ± 7.41% [−5.04–2.97%]), p < 0.001 for both groups compared to mean bias of SUVR 50–80 min , similar to SUVR 15–45 min . For the striatum, Cohen’s d was similar for all measures. TRV were 3.2 ± 2.5% ( DVR ), 6.4 ± 5.7% ( SUVR 50–80 min ), 6.8 ± 5.9% ( SUVR c 50–80 min ) and 3.9 ± 3.2% ( SUVR 15–45 min ). Higher TRV of SUVR c 50–80 min was due to TRV of 9.2 ± 5.1% [1.1–19.4] for β tar . ALC was 4.5 ± 4.2% ( DVR ), 5.2 ± 6.5% ( SUVR 50–80 min ), 4.4 ± 4.1% ( SUVR c 50–80 min ) and 4.2 ± 4.1% ( SUVR 15–45 min ). SUVR c 50–80 min reduced bias compared to SUVR 50–80 min , as previously reported. SUVR c 50–80 min was sensitive to small changes of β tar , with higher TRV compared to DVR , but with similar ALC, suggesting that it can reliably assess longitudinal DAT changes.

Source: Journal of Cerebral Blood Flow & Metabolism

DOI: 10.1177/0271678x251322407

Authors: Minyoung Oh, Praveen Honhar, Richard E Carson, Ansel T Hillmer, Andrea Varrone

Institutions: Asan Medical Center, Karolinska Institutet, University of Ulsan, Stockholm Health Care Services, Yale University

Language: English

Topic: Medical Imaging Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,200