Correcting [ <sup>18</sup> F]MK‐6240 <i>SUVR</i> for non‐equilibrium effects using tissue clearance correction method does not improve its performance

Abstract Background Honhar et al. (PMCID:10993874) reported a method for bias and noise correction in standardized‐uptake value ratios ( SUVR , simplified outcome), relative to distribution volume ratios ( DVR , quantitative gold‐standard), without the need for dynamic data outside SUVR time‐window. The method performed well for rapidly‐reversible radiotracers, [ 18 F]FE‐PE2I and [ 11 C]LSN3172176 (i.e., radiotracers kinetics described by 1‐tissue compartment or simplified reference tissue models). Herein, we tested this method on human [ 18 F]MK‐6240 PET data. Methods Dynamic [ 18 F]MK‐6240 PET data (0‐120 min) in 22 human participants (age: 61±18 y, 8 females, 16 cognitively unimpaired controls [HC], 5 mild cognitive impairment [MCI], 1 Alzheimer's disease [AD]) were reanalyzed. Metabolite‐corrected arterial input functions were used to compute regional 2‐tissue compartment model DVR values (reference: eroded cerebellar gray matter). Regional SUVR (80‐100 min and 90‐110 min) values were corrected as: SUVR C = SUVR / [1‐ β ref / k 2 ,ref + β tar SUVR /( R 1 k 2 ,ref )], where SUVR C : corrected SUVR , k 2 ,ref : population‐based rate constant for efflux of the radiotracer from reference region, [ β ref , β tar ]: clearance rates of the radiotracer from the reference and target tissues during SUVR time‐window, R 1 =0.75 (population‐averaged value for ratio of target:reference radiotracer delivery rate). The primary outcome measures were the percent bias (%bias) in SUVR (and SUVR c) relative to DVR , and the standard deviation of %bias. Results Across subjects and selected regions of interest (ROIs, Tables 1‐3), the mean %bias was 0.9% for SUVR 80‐100 min and 1.2% for SUVR 90‐110 min. The variability in %bias was 13.1% for SUVR 80‐100 min and 11.9% for SUVR 90‐110 min. The mean %bias in SUVR c across subjects and ROIs was comparable for SUVR c 80‐100 min (‐1.3%) and SUVR c 90‐110 min (‐0.1%), with similar variability (∼11%) for SUVR c 80‐100 min and SUVR c 90‐110 min. Regional measures for (averaged across subjects) are listed in Tables 1‐2. Similar performance metrics were observed for a subcohort analysis of 5 high‐binding individuals with highest average regional DVR values (1 AD,3 MCI,1 HC). Conclusions [ 18 F]MK‐6240 SUVR in this cohort was already minimally biased; SUVR c did not significantly decrease the variability in SUVR bias. This SUVR correction method might not be beneficial for radiotracers that deviate considerably from its assumption of 1‐tissue compartment model kinetics.

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Journal
Alzheimer s & Dementia
Published
2025-12-01
DOI
https://doi.org/10.1002/alz70856_105725
Primary Topic
Cerebrovascular and Carotid Artery Diseases
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article
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article

Correcting [ 18 F]MK‐6240 SUVR for non‐equilibrium effects using tissue clearance correction method does not improve its performance

Arun Garimella, Praveen Honhar, Julie Price, K. E. Smith et al.
Alzheimer s & Dementia
Cerebrovascular and Carotid Artery Diseases
article

Correcting [ 18 F]MK‐6240 SUVR for non‐equilibrium effects using tissue clearance correction method does not improve its performance

Arun Garimella, Praveen Honhar, Julie Price, K. E. Smith, Jessie Fanglu Fu, Cristina Lois
article en

Abstract

Abstract Background Honhar et al. (PMCID:10993874) reported a method for bias and noise correction in standardized‐uptake value ratios ( SUVR , simplified outcome), relative to distribution volume ratios ( DVR , quantitative gold‐standard), without the need for dynamic data outside SUVR time‐window. The method performed well for rapidly‐reversible radiotracers, [ 18 F]FE‐PE2I and [ 11 C]LSN3172176 (i.e., radiotracers kinetics described by 1‐tissue compartment or simplified reference tissue models). Herein, we tested this method on human [ 18 F]MK‐6240 PET data. Methods Dynamic [ 18 F]MK‐6240 PET data (0‐120 min) in 22 human participants (age: 61±18 y, 8 females, 16 cognitively unimpaired controls [HC], 5 mild cognitive impairment [MCI], 1 Alzheimer's disease [AD]) were reanalyzed. Metabolite‐corrected arterial input functions were used to compute regional 2‐tissue compartment model DVR values (reference: eroded cerebellar gray matter). Regional SUVR (80‐100 min and 90‐110 min) values were corrected as: SUVR C = SUVR / [1‐ β ref / k 2 ,ref + β tar SUVR /( R 1 k 2 ,ref )], where SUVR C : corrected SUVR , k 2 ,ref : population‐based rate constant for efflux of the radiotracer from reference region, [ β ref , β tar ]: clearance rates of the radiotracer from the reference and target tissues during SUVR time‐window, R 1 =0.75 (population‐averaged value for ratio of target:reference radiotracer delivery rate). The primary outcome measures were the percent bias (%bias) in SUVR (and SUVR c) relative to DVR , and the standard deviation of %bias. Results Across subjects and selected regions of interest (ROIs, Tables 1‐3), the mean %bias was 0.9% for SUVR 80‐100 min and 1.2% for SUVR 90‐110 min. The variability in %bias was 13.1% for SUVR 80‐100 min and 11.9% for SUVR 90‐110 min. The mean %bias in SUVR c across subjects and ROIs was comparable for SUVR c 80‐100 min (‐1.3%) and SUVR c 90‐110 min (‐0.1%), with similar variability (∼11%) for SUVR c 80‐100 min and SUVR c 90‐110 min. Regional measures for (averaged across subjects) are listed in Tables 1‐2. Similar performance metrics were observed for a subcohort analysis of 5 high‐binding individuals with highest average regional DVR values (1 AD,3 MCI,1 HC). Conclusions [ 18 F]MK‐6240 SUVR in this cohort was already minimally biased; SUVR c did not significantly decrease the variability in SUVR bias. This SUVR correction method might not be beneficial for radiotracers that deviate considerably from its assumption of 1‐tissue compartment model kinetics.

Alzheimer s & DementiaVol. 21(S2)
Harvard University (US), Massachusetts General Hospital (US), Athinoula A. Martinos Center for Biomedical Imaging (US)
Openalex Percentile: Top 26%
Cerebrovascular and Carotid Artery Diseases
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