False positive rates in positron emission tomography (PET) voxelwise analyses

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

False positive rates in positron emission tomography (PET) voxelwise analyses. / Ganz, Melanie; Nørgaard, Martin; Beliveau, Vincent; Svarer, Claus; Knudsen, Gitte M; Greve, Douglas N.

In: Journal of Cerebral Blood Flow and Metabolism, Vol. 41, No. 7, 01.07.2021, p. 1647-1657.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Ganz, M, Nørgaard, M, Beliveau, V, Svarer, C, Knudsen, GM & Greve, DN 2021, 'False positive rates in positron emission tomography (PET) voxelwise analyses', Journal of Cerebral Blood Flow and Metabolism, vol. 41, no. 7, pp. 1647-1657. https://doi.org/10.1177/0271678X20974961

APA

Ganz, M., Nørgaard, M., Beliveau, V., Svarer, C., Knudsen, G. M., & Greve, D. N. (2021). False positive rates in positron emission tomography (PET) voxelwise analyses. Journal of Cerebral Blood Flow and Metabolism, 41(7), 1647-1657. https://doi.org/10.1177/0271678X20974961

Vancouver

Ganz M, Nørgaard M, Beliveau V, Svarer C, Knudsen GM, Greve DN. False positive rates in positron emission tomography (PET) voxelwise analyses. Journal of Cerebral Blood Flow and Metabolism. 2021 Jul 1;41(7):1647-1657. https://doi.org/10.1177/0271678X20974961

Author

Ganz, Melanie ; Nørgaard, Martin ; Beliveau, Vincent ; Svarer, Claus ; Knudsen, Gitte M ; Greve, Douglas N. / False positive rates in positron emission tomography (PET) voxelwise analyses. In: Journal of Cerebral Blood Flow and Metabolism. 2021 ; Vol. 41, No. 7. pp. 1647-1657.

Bibtex

@article{975fe5c7922a43a3aa250b822b1bf9c6,
title = "False positive rates in positron emission tomography (PET) voxelwise analyses",
abstract = "Issues with inflated false positive rates (FPRs) in brain imaging have recently received significant attention. However, to what extent FPRs present a problem for voxelwise analyses of Positron Emission Tomography (PET) data remains unknown. In this work, we evaluate the FPR using real PET data under group assignments that should yield no significant results after correcting for multiple comparisons. We used data from 159 healthy participants, imaged with the serotonin transporter ([11C]DASB; N = 100) or the 5-HT4 receptor ([11C]SB207145; N = 59). Using this null data, we estimated the FPR by performing 1,000 group analyses with randomly assigned groups of either 10 or 20, for each tracer, and corrected for multiple comparisons using parametric Monte Carlo simulations (MCZ) or non-parametric permutation testing. Our analyses show that for group sizes of 10 or 20, the FPR for both tracers was 5-99% using MCZ, much higher than the expected 5%. This was caused by a heavier-than-Gaussian spatial autocorrelation, violating the parametric assumptions. Permutation correctly controlled the FPR in all cases. In conclusion, either a conservative cluster forming threshold and high smoothing levels, or a non-parametric correction for multiple comparisons should be performed in voxelwise analyses of brain PET data.",
author = "Melanie Ganz and Martin N{\o}rgaard and Vincent Beliveau and Claus Svarer and Knudsen, {Gitte M} and Greve, {Douglas N}",
year = "2021",
month = jul,
day = "1",
doi = "10.1177/0271678X20974961",
language = "English",
volume = "41",
pages = "1647--1657",
journal = "Journal of Cerebral Blood Flow and Metabolism",
issn = "0271-678X",
publisher = "SAGE Publications",
number = "7",

}

RIS

TY - JOUR

T1 - False positive rates in positron emission tomography (PET) voxelwise analyses

AU - Ganz, Melanie

AU - Nørgaard, Martin

AU - Beliveau, Vincent

AU - Svarer, Claus

AU - Knudsen, Gitte M

AU - Greve, Douglas N

PY - 2021/7/1

Y1 - 2021/7/1

N2 - Issues with inflated false positive rates (FPRs) in brain imaging have recently received significant attention. However, to what extent FPRs present a problem for voxelwise analyses of Positron Emission Tomography (PET) data remains unknown. In this work, we evaluate the FPR using real PET data under group assignments that should yield no significant results after correcting for multiple comparisons. We used data from 159 healthy participants, imaged with the serotonin transporter ([11C]DASB; N = 100) or the 5-HT4 receptor ([11C]SB207145; N = 59). Using this null data, we estimated the FPR by performing 1,000 group analyses with randomly assigned groups of either 10 or 20, for each tracer, and corrected for multiple comparisons using parametric Monte Carlo simulations (MCZ) or non-parametric permutation testing. Our analyses show that for group sizes of 10 or 20, the FPR for both tracers was 5-99% using MCZ, much higher than the expected 5%. This was caused by a heavier-than-Gaussian spatial autocorrelation, violating the parametric assumptions. Permutation correctly controlled the FPR in all cases. In conclusion, either a conservative cluster forming threshold and high smoothing levels, or a non-parametric correction for multiple comparisons should be performed in voxelwise analyses of brain PET data.

AB - Issues with inflated false positive rates (FPRs) in brain imaging have recently received significant attention. However, to what extent FPRs present a problem for voxelwise analyses of Positron Emission Tomography (PET) data remains unknown. In this work, we evaluate the FPR using real PET data under group assignments that should yield no significant results after correcting for multiple comparisons. We used data from 159 healthy participants, imaged with the serotonin transporter ([11C]DASB; N = 100) or the 5-HT4 receptor ([11C]SB207145; N = 59). Using this null data, we estimated the FPR by performing 1,000 group analyses with randomly assigned groups of either 10 or 20, for each tracer, and corrected for multiple comparisons using parametric Monte Carlo simulations (MCZ) or non-parametric permutation testing. Our analyses show that for group sizes of 10 or 20, the FPR for both tracers was 5-99% using MCZ, much higher than the expected 5%. This was caused by a heavier-than-Gaussian spatial autocorrelation, violating the parametric assumptions. Permutation correctly controlled the FPR in all cases. In conclusion, either a conservative cluster forming threshold and high smoothing levels, or a non-parametric correction for multiple comparisons should be performed in voxelwise analyses of brain PET data.

U2 - 10.1177/0271678X20974961

DO - 10.1177/0271678X20974961

M3 - Journal article

C2 - 33241770

VL - 41

SP - 1647

EP - 1657

JO - Journal of Cerebral Blood Flow and Metabolism

JF - Journal of Cerebral Blood Flow and Metabolism

SN - 0271-678X

IS - 7

ER -

ID: 252543554