Abstract
Quantitative measurement of β-amyloid from amyloid PET scans typically relies on localizing target and reference regions by image registration to MRI. In this work, we present a series of simulations where 50 small random perturbations of starting location and orientation were applied to each subject's PET scan, and rigid registration using spm_coreg was performed between each perturbed PET scan and its corresponding MRI. We then measured variation in the output PET-MRI registrations and how this variation affected the resulting SUVR measurements. We performed these experiments using scans of 1196 participants, half using 18F florbetapir and half using 11C PiB. From these experiments, we measured the magnitude of the imprecision in the rigid registration steps used to localize measurement regions, and how this contributes to the overall imprecision in SUVR measurements. Unexpectedly, we found for both tracers that the imprecision in these measurements depends on the degree of amyloid tracer uptake, and thus also indirectly on Alzheimer's disease clinical status. We then examined common choices of reference regions, and we show that SUVR measurements using supratentorial white matter references are relatively resistant to this source of error. We also show that the use of partial volume correction further magnifies the effects of registration imprecision on SUVR measurements. Together, these results suggest that this rigid registration step is an attractive target for future work in improving measurement techniques.
| Original language | English (US) |
|---|---|
| Journal | Human Brain Mapping |
| DOIs | |
| State | Accepted/In press - 2017 |
Fingerprint
Keywords
- Alzheimer disease
- Amyloid
- Computer-assisted
- Florbetapir
- Image processing
- Pittsburgh compound B
- Positron-emission tomography
- Reproducibility of results
ASJC Scopus subject areas
- Anatomy
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging
- Neurology
- Clinical Neurology
Cite this
Contributions of imprecision in PET-MRI rigid registration to imprecision in amyloid PET SUVR measurements. / Schwarz, Christopher; Jones, David T; Gunter, Jeffrey L.; Lowe, Val; Vemuri, Prashanthi D; Senjem, Matthew L.; Petersen, Ronald Carl; Knopman, David S; Jack, Clifford R Jr.
In: Human Brain Mapping, 2017.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Contributions of imprecision in PET-MRI rigid registration to imprecision in amyloid PET SUVR measurements
AU - Schwarz, Christopher
AU - Jones, David T
AU - Gunter, Jeffrey L.
AU - Lowe, Val
AU - Vemuri, Prashanthi D
AU - Senjem, Matthew L.
AU - Petersen, Ronald Carl
AU - Knopman, David S
AU - Jack, Clifford R Jr.
PY - 2017
Y1 - 2017
N2 - Quantitative measurement of β-amyloid from amyloid PET scans typically relies on localizing target and reference regions by image registration to MRI. In this work, we present a series of simulations where 50 small random perturbations of starting location and orientation were applied to each subject's PET scan, and rigid registration using spm_coreg was performed between each perturbed PET scan and its corresponding MRI. We then measured variation in the output PET-MRI registrations and how this variation affected the resulting SUVR measurements. We performed these experiments using scans of 1196 participants, half using 18F florbetapir and half using 11C PiB. From these experiments, we measured the magnitude of the imprecision in the rigid registration steps used to localize measurement regions, and how this contributes to the overall imprecision in SUVR measurements. Unexpectedly, we found for both tracers that the imprecision in these measurements depends on the degree of amyloid tracer uptake, and thus also indirectly on Alzheimer's disease clinical status. We then examined common choices of reference regions, and we show that SUVR measurements using supratentorial white matter references are relatively resistant to this source of error. We also show that the use of partial volume correction further magnifies the effects of registration imprecision on SUVR measurements. Together, these results suggest that this rigid registration step is an attractive target for future work in improving measurement techniques.
AB - Quantitative measurement of β-amyloid from amyloid PET scans typically relies on localizing target and reference regions by image registration to MRI. In this work, we present a series of simulations where 50 small random perturbations of starting location and orientation were applied to each subject's PET scan, and rigid registration using spm_coreg was performed between each perturbed PET scan and its corresponding MRI. We then measured variation in the output PET-MRI registrations and how this variation affected the resulting SUVR measurements. We performed these experiments using scans of 1196 participants, half using 18F florbetapir and half using 11C PiB. From these experiments, we measured the magnitude of the imprecision in the rigid registration steps used to localize measurement regions, and how this contributes to the overall imprecision in SUVR measurements. Unexpectedly, we found for both tracers that the imprecision in these measurements depends on the degree of amyloid tracer uptake, and thus also indirectly on Alzheimer's disease clinical status. We then examined common choices of reference regions, and we show that SUVR measurements using supratentorial white matter references are relatively resistant to this source of error. We also show that the use of partial volume correction further magnifies the effects of registration imprecision on SUVR measurements. Together, these results suggest that this rigid registration step is an attractive target for future work in improving measurement techniques.
KW - Alzheimer disease
KW - Amyloid
KW - Computer-assisted
KW - Florbetapir
KW - Image processing
KW - Pittsburgh compound B
KW - Positron-emission tomography
KW - Reproducibility of results
UR - http://www.scopus.com/inward/record.url?scp=85018654039&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85018654039&partnerID=8YFLogxK
U2 - 10.1002/hbm.23622
DO - 10.1002/hbm.23622
M3 - Article
JO - Human Brain Mapping
JF - Human Brain Mapping
SN - 1065-9471
ER -