Parametric imaging of [11C]flumazenil binding in the rat brain

I. Lopes Alves; D. Vállez García; A. Parente; J. Doorduin; R. Dierckx; A. M. Marques da Silva; M. Koole; A. T. M. Willemsen; R. Boellaard

doi:10.1177/0271678X17695982

Samenvatting

This study evaluates the performance of several parametric methods for assessing [¹¹C]flumazenil binding distribution in the rat brain.

Dynamic (60 min) PET data with metabolite corrected plasma input function was retrospectively analyzed (male Wistar rats, n = 10). Distribution volume (V_T) images were generated from the basis function method (BFM), the Logan Graphical Analysis (LGA) and the Spectral Analysis (SA). Using the pons as pseudo-reference tissue, binding potential (BP_ND and DVR-1) images were obtained from two receptor parametric imaging algorithms (RPM and SRTM2) and Reference Logan (RLogan). Standardized Uptake Value images (SUV and SUVR) were also computed for different post-injection intervals. From these images, regional averages were extracted based on pre-defined volumes of interest (VOIs). In addition, the corresponding non-linear regression (NLR) version of each method was applied to the time-activity curves extracted of each VOI from the dynamic image. Parametric data was compared to the NLR counterparts as well as to 2TCM based values (previously defined as the model of choice for rats). Parameter agreement was assessed by linear regression analysis and Bland-Altman plots.

All parametric methods correlated strongly to their NLR counterparts (R²> 0.8). However, RPM and SRTM2 overestimated NLR values (slope = 1.1 and slope = 1.3, respectively). Compared to 2TCM V_T, all parametric methods showed excellent correlation (R²≥ 0.9). However, BFM and SRTM2 underestimated V_T and BP_ND respectively (slope = 0.8), while SUVR-1 overestimated BP_ND (slope = 1.2). Bland-Altman plots showed LGA and RPM had the best agreement both to NLR counterparts (−0.20 and 0.03 bias) and to 2TCM values (−0.19 and −0.1 bias), while SA showed a bias of 0.57 to NLR and of −0.49 to 2TCM V_T.

In conclusion, all parametric methods showed good performance, although LGA and RPM outperformed other methods. Yet, BFM and SA are of interest because they also provide K₁ and model order (SA only) images.

Originele taal-2	English
Artikelnummer	PS01-088
Pagina's (van-tot)	152-153
Aantal pagina's	2
Tijdschrift	Journal of Cerebral Blood Flow and Metabolism
Volume	37
Nummer van het tijdschrift	1_suppl
DOI's	https://doi.org/10.1177/0271678X17695982
Status	Published - 1-apr.-2017
Evenement	28th International Symposium on Cerebral Blood Flow, Metabolism and Function / 13th International Conference on Quantification of Brain Function with PET - Berlin, Germany Duur: 1-apr.-2017 → 4-apr.-2017

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Parametric Imaging of [11C]Flumazenil Binding in the Rat Brain
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3 Article

Parametric Imaging of [¹¹C]Flumazenil Binding in the Rat Brain
Lopes Alves, I., Vállez García, D., Parente, A., Doorduin, J., Marques da Silva, A. M., Koole, M., Dierckx, R., Willemsen, A. & Boellaard, R., feb.-2018, In: Molecular Imaging and Biology. 20, 1, blz. 114-123 10 blz.
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Contribution of neuroinflammation to changes in [C-11]flumazenil binding in the rat brain: Evaluation of the inflamed pons as reference tissue
Parente, A., Vállez García, D., Shoji, A., Lopes Alves, I., Maas, B., Zijlma, R., Dierckx, R. A. J. O., Buchpiguel, C. A., de Vries, E. F. J. & Doorduin, J., jun.-2017, In: Nuclear Medicine and Biology. 49, blz. 50-56 7 blz.
Onderzoeksoutput › Academic › peer review
6 Citaten (Scopus)
Pharmacokinetic modeling of [C-11]flumazenil kinetics in the rat brain
Alves, I. L., Vállez García, D., Parente, A., Doorduin, J., Dierckx, R., Marques da Silva, A. M., Koole, M. J. B., Willemsen, A. & Boellaard, R., 22-feb.-2017, In: EJNMMI Research. 7, 17, 12 blz.
Onderzoeksoutput › Academic › peer review

Open Access
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8 Citaten (Scopus)

330 Downloads (Pure)

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@article{95f0f837f9344e98b14434702859d899,

title = "Parametric imaging of [11C]flumazenil binding in the rat brain",

abstract = "This study evaluates the performance of several parametric methods for assessing [11C]flumazenil binding distribution in the rat brain.Dynamic (60 min) PET data with metabolite corrected plasma input function was retrospectively analyzed (male Wistar rats, n = 10). Distribution volume (VT) images were generated from the basis function method (BFM), the Logan Graphical Analysis (LGA) and the Spectral Analysis (SA). Using the pons as pseudo-reference tissue, binding potential (BPND and DVR-1) images were obtained from two receptor parametric imaging algorithms (RPM and SRTM2) and Reference Logan (RLogan). Standardized Uptake Value images (SUV and SUVR) were also computed for different post-injection intervals. From these images, regional averages were extracted based on pre-defined volumes of interest (VOIs). In addition, the corresponding non-linear regression (NLR) version of each method was applied to the time-activity curves extracted of each VOI from the dynamic image. Parametric data was compared to the NLR counterparts as well as to 2TCM based values (previously defined as the model of choice for rats). Parameter agreement was assessed by linear regression analysis and Bland-Altman plots.All parametric methods correlated strongly to their NLR counterparts (R2 > 0.8). However, RPM and SRTM2 overestimated NLR values (slope = 1.1 and slope = 1.3, respectively). Compared to 2TCM VT, all parametric methods showed excellent correlation (R2 ≥ 0.9). However, BFM and SRTM2 underestimated VT and BPND respectively (slope = 0.8), while SUVR-1 overestimated BPND (slope = 1.2). Bland-Altman plots showed LGA and RPM had the best agreement both to NLR counterparts (−0.20 and 0.03 bias) and to 2TCM values (−0.19 and −0.1 bias), while SA showed a bias of 0.57 to NLR and of −0.49 to 2TCM VT.In conclusion, all parametric methods showed good performance, although LGA and RPM outperformed other methods. Yet, BFM and SA are of interest because they also provide K1 and model order (SA only) images.",

author = "{Lopes Alves}, I. and {V{\'a}llez Garc{\'i}a}, D. and A. Parente and J. Doorduin and R. Dierckx and {Marques da Silva}, {A. M.} and M. Koole and Willemsen, {A. T. M.} and R. Boellaard",

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language = "English",

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T1 - Parametric imaging of [11C]flumazenil binding in the rat brain

AU - Lopes Alves, I.

AU - Vállez García, D.

AU - Parente, A.

AU - Doorduin, J.

AU - Dierckx, R.

AU - Marques da Silva, A. M.

AU - Koole, M.

AU - Willemsen, A. T. M.

AU - Boellaard, R.

PY - 2017/4/1

Y1 - 2017/4/1

N2 - This study evaluates the performance of several parametric methods for assessing [11C]flumazenil binding distribution in the rat brain.Dynamic (60 min) PET data with metabolite corrected plasma input function was retrospectively analyzed (male Wistar rats, n = 10). Distribution volume (VT) images were generated from the basis function method (BFM), the Logan Graphical Analysis (LGA) and the Spectral Analysis (SA). Using the pons as pseudo-reference tissue, binding potential (BPND and DVR-1) images were obtained from two receptor parametric imaging algorithms (RPM and SRTM2) and Reference Logan (RLogan). Standardized Uptake Value images (SUV and SUVR) were also computed for different post-injection intervals. From these images, regional averages were extracted based on pre-defined volumes of interest (VOIs). In addition, the corresponding non-linear regression (NLR) version of each method was applied to the time-activity curves extracted of each VOI from the dynamic image. Parametric data was compared to the NLR counterparts as well as to 2TCM based values (previously defined as the model of choice for rats). Parameter agreement was assessed by linear regression analysis and Bland-Altman plots.All parametric methods correlated strongly to their NLR counterparts (R2 > 0.8). However, RPM and SRTM2 overestimated NLR values (slope = 1.1 and slope = 1.3, respectively). Compared to 2TCM VT, all parametric methods showed excellent correlation (R2 ≥ 0.9). However, BFM and SRTM2 underestimated VT and BPND respectively (slope = 0.8), while SUVR-1 overestimated BPND (slope = 1.2). Bland-Altman plots showed LGA and RPM had the best agreement both to NLR counterparts (−0.20 and 0.03 bias) and to 2TCM values (−0.19 and −0.1 bias), while SA showed a bias of 0.57 to NLR and of −0.49 to 2TCM VT.In conclusion, all parametric methods showed good performance, although LGA and RPM outperformed other methods. Yet, BFM and SA are of interest because they also provide K1 and model order (SA only) images.

AB - This study evaluates the performance of several parametric methods for assessing [11C]flumazenil binding distribution in the rat brain.Dynamic (60 min) PET data with metabolite corrected plasma input function was retrospectively analyzed (male Wistar rats, n = 10). Distribution volume (VT) images were generated from the basis function method (BFM), the Logan Graphical Analysis (LGA) and the Spectral Analysis (SA). Using the pons as pseudo-reference tissue, binding potential (BPND and DVR-1) images were obtained from two receptor parametric imaging algorithms (RPM and SRTM2) and Reference Logan (RLogan). Standardized Uptake Value images (SUV and SUVR) were also computed for different post-injection intervals. From these images, regional averages were extracted based on pre-defined volumes of interest (VOIs). In addition, the corresponding non-linear regression (NLR) version of each method was applied to the time-activity curves extracted of each VOI from the dynamic image. Parametric data was compared to the NLR counterparts as well as to 2TCM based values (previously defined as the model of choice for rats). Parameter agreement was assessed by linear regression analysis and Bland-Altman plots.All parametric methods correlated strongly to their NLR counterparts (R2 > 0.8). However, RPM and SRTM2 overestimated NLR values (slope = 1.1 and slope = 1.3, respectively). Compared to 2TCM VT, all parametric methods showed excellent correlation (R2 ≥ 0.9). However, BFM and SRTM2 underestimated VT and BPND respectively (slope = 0.8), while SUVR-1 overestimated BPND (slope = 1.2). Bland-Altman plots showed LGA and RPM had the best agreement both to NLR counterparts (−0.20 and 0.03 bias) and to 2TCM values (−0.19 and −0.1 bias), while SA showed a bias of 0.57 to NLR and of −0.49 to 2TCM VT.In conclusion, all parametric methods showed good performance, although LGA and RPM outperformed other methods. Yet, BFM and SA are of interest because they also provide K1 and model order (SA only) images.

U2 - 10.1177/0271678X17695982

DO - 10.1177/0271678X17695982

M3 - Meeting Abstract

SN - 0271-678X

VL - 37

SP - 152

EP - 153

JO - Journal of Cerebral Blood Flow and Metabolism

JF - Journal of Cerebral Blood Flow and Metabolism

IS - 1_suppl

M1 - PS01-088

T2 - 28th International Symposium on Cerebral Blood Flow, Metabolism and Function / 13th International Conference on Quantification of Brain Function with PET

Y2 - 1 April 2017 through 4 April 2017

ER -

Parametric imaging of [11C]flumazenil binding in the rat brain

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Toegang tot document

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Document onder embargo

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Onderzoekersoutput

Parametric Imaging of [11C]Flumazenil Binding in the Rat Brain

Contribution of neuroinflammation to changes in [C-11]flumazenil binding in the rat brain: Evaluation of the inflamed pons as reference tissue

Pharmacokinetic modeling of [C-11]flumazenil kinetics in the rat brain

Citeer dit

Parametric Imaging of [¹¹C]Flumazenil Binding in the Rat Brain