rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data
The reference standard for amyloid-PET quantification requires structural MRI (sMRI) for preprocessing in both multi-site research studies and clinical trials. Here we describe rPOP (robust PET-Only Processing), a MATLAB-based MRI-free pipeline implementing non-linear warping and differential smooth...
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-02-01
|
| Series: | NeuroImage |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811921010478 |
| _version_ | 1819283849884991488 |
|---|---|
| author | Leonardo Iaccarino Renaud La Joie Robert Koeppe Barry A. Siegel Bruce E. Hillner Constantine Gatsonis Rachel A. Whitmer Maria C. Carrillo Charles Apgar Monica R. Camacho Rachel Nosheny Gil D. Rabinovici |
| author_facet | Leonardo Iaccarino Renaud La Joie Robert Koeppe Barry A. Siegel Bruce E. Hillner Constantine Gatsonis Rachel A. Whitmer Maria C. Carrillo Charles Apgar Monica R. Camacho Rachel Nosheny Gil D. Rabinovici |
| author_sort | Leonardo Iaccarino |
| collection | DOAJ |
| description | The reference standard for amyloid-PET quantification requires structural MRI (sMRI) for preprocessing in both multi-site research studies and clinical trials. Here we describe rPOP (robust PET-Only Processing), a MATLAB-based MRI-free pipeline implementing non-linear warping and differential smoothing of amyloid-PET scans performed with any of the FDA-approved radiotracers (18F-florbetapir/FBP, 18F-florbetaben/FBB or 18F-flutemetamol/FLUTE). Each image undergoes spatial normalization based on weighted PET templates and data-driven differential smoothing, then allowing users to perform their quantification of choice. Prior to normalization, users can choose whether to automatically reset the origin of the image to the center of mass or proceed with the pipeline with the image as it is. We validate rPOP with n = 740 (514 FBP, 182 FBB, 44 FLUTE) amyloid-PET scans from the Imaging Dementia—Evidence for Amyloid Scanning – Brain Health Registry sub-study (IDEAS-BHR) and n = 1,518 scans from the Alzheimer's Disease Neuroimaging Initiative (n = 1,249 FBP, n = 269 FBB), including heterogeneous acquisition and reconstruction protocols. After running rPOP, a standard quantification to extract Standardized Uptake Value ratios and the respective Centiloids conversion was performed. rPOP-based amyloid status (using an independent pathology-based threshold of ≥24.4 Centiloid units) was compared with either local visual reads (IDEAS-BHR, n = 663 with complete valid data and reads available) or with amyloid status derived from an MRI-based PET processing pipeline (ADNI, thresholds of >20/>18 Centiloids for FBP/FBB). Finally, within the ADNI dataset, we tested the linear associations between rPOP- and MRI-based Centiloid values. rPOP achieved accurate warping for N = 2,233/2,258 (98.9%) in the first pass. Of the N = 25 warping failures, 24 were rescued with manual reorientation and origin reset prior to warping. We observed high concordance between rPOP-based amyloid status and both visual reads (IDEAS-BHR, Cohen's k = 0.72 [0.7–0.74], ∼86% concordance) or MRI-pipeline based amyloid status (ADNI, k = 0.88 [0.87–0.89], ∼94% concordance). rPOP- and MRI-pipeline based Centiloids were strongly linearly related (R2:0.95, p<0.001), with this association being significantly modulated by estimated PET resolution (β= -0.016, p<0.001). rPOP provides reliable MRI-free amyloid-PET warping and quantification, leveraging widely available software and only requiring an attenuation-corrected amyloid-PET image as input. The rPOP pipeline enables the comparison and merging of heterogeneous datasets and is publicly available at https://github.com/leoiacca/rPOP. |
| first_indexed | 2024-12-24T01:38:01Z |
| format | Article |
| id | doaj.art-a97e23c35b074d119a438e7290cb4486 |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-24T01:38:01Z |
| publishDate | 2022-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-a97e23c35b074d119a438e7290cb44862022-12-21T17:22:07ZengElsevierNeuroImage1095-95722022-02-01246118775rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET dataLeonardo Iaccarino0Renaud La Joie1Robert Koeppe2Barry A. Siegel3Bruce E. Hillner4Constantine Gatsonis5Rachel A. Whitmer6Maria C. Carrillo7Charles Apgar8Monica R. Camacho9Rachel Nosheny10Gil D. Rabinovici11Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United StatesMemory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United StatesDepartment of Radiology, University of Michigan, Ann Arbor, MI, United StatesEdward Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis, St Louis, MO, United StatesDepartment of Medicine, Virginia Commonwealth University, Richmond, VA, United StatesCenter for Statistical Sciences, Brown University School of Public Health, Providence, RI, United States; Department of Biostatistics, Brown University School of Public Health, Providence, RI, United StatesDivision of Research, Kaiser Permanente, Oakland, CA, United States; Department of Public Health Sciences, University of California Davis, Davis, CA, United StatesMedical and Scientific Relations Division, Alzheimer's Association, Chicago, IL, United StatesAmerican College of Radiology, Reston, VA, United StatesSan Francisco VA Medical Center, San Francisco, CA, United States; Northern California Institute for Research and Education (NCIRE), San Francisco, CA, United StatesSan Francisco VA Medical Center, San Francisco, CA, United States; Department of Psychiatry, University of California San Francisco, San Francisco, CA, United StatesMemory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States; Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States; Corresponding author.The reference standard for amyloid-PET quantification requires structural MRI (sMRI) for preprocessing in both multi-site research studies and clinical trials. Here we describe rPOP (robust PET-Only Processing), a MATLAB-based MRI-free pipeline implementing non-linear warping and differential smoothing of amyloid-PET scans performed with any of the FDA-approved radiotracers (18F-florbetapir/FBP, 18F-florbetaben/FBB or 18F-flutemetamol/FLUTE). Each image undergoes spatial normalization based on weighted PET templates and data-driven differential smoothing, then allowing users to perform their quantification of choice. Prior to normalization, users can choose whether to automatically reset the origin of the image to the center of mass or proceed with the pipeline with the image as it is. We validate rPOP with n = 740 (514 FBP, 182 FBB, 44 FLUTE) amyloid-PET scans from the Imaging Dementia—Evidence for Amyloid Scanning – Brain Health Registry sub-study (IDEAS-BHR) and n = 1,518 scans from the Alzheimer's Disease Neuroimaging Initiative (n = 1,249 FBP, n = 269 FBB), including heterogeneous acquisition and reconstruction protocols. After running rPOP, a standard quantification to extract Standardized Uptake Value ratios and the respective Centiloids conversion was performed. rPOP-based amyloid status (using an independent pathology-based threshold of ≥24.4 Centiloid units) was compared with either local visual reads (IDEAS-BHR, n = 663 with complete valid data and reads available) or with amyloid status derived from an MRI-based PET processing pipeline (ADNI, thresholds of >20/>18 Centiloids for FBP/FBB). Finally, within the ADNI dataset, we tested the linear associations between rPOP- and MRI-based Centiloid values. rPOP achieved accurate warping for N = 2,233/2,258 (98.9%) in the first pass. Of the N = 25 warping failures, 24 were rescued with manual reorientation and origin reset prior to warping. We observed high concordance between rPOP-based amyloid status and both visual reads (IDEAS-BHR, Cohen's k = 0.72 [0.7–0.74], ∼86% concordance) or MRI-pipeline based amyloid status (ADNI, k = 0.88 [0.87–0.89], ∼94% concordance). rPOP- and MRI-pipeline based Centiloids were strongly linearly related (R2:0.95, p<0.001), with this association being significantly modulated by estimated PET resolution (β= -0.016, p<0.001). rPOP provides reliable MRI-free amyloid-PET warping and quantification, leveraging widely available software and only requiring an attenuation-corrected amyloid-PET image as input. The rPOP pipeline enables the comparison and merging of heterogeneous datasets and is publicly available at https://github.com/leoiacca/rPOP.http://www.sciencedirect.com/science/article/pii/S1053811921010478 |
| spellingShingle | Leonardo Iaccarino Renaud La Joie Robert Koeppe Barry A. Siegel Bruce E. Hillner Constantine Gatsonis Rachel A. Whitmer Maria C. Carrillo Charles Apgar Monica R. Camacho Rachel Nosheny Gil D. Rabinovici rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data NeuroImage |
| title | rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data |
| title_full | rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data |
| title_fullStr | rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data |
| title_full_unstemmed | rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data |
| title_short | rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data |
| title_sort | rpop robust pet only processing of community acquired heterogeneous amyloid pet data |
| url | http://www.sciencedirect.com/science/article/pii/S1053811921010478 |
| work_keys_str_mv | AT leonardoiaccarino rpoprobustpetonlyprocessingofcommunityacquiredheterogeneousamyloidpetdata AT renaudlajoie rpoprobustpetonlyprocessingofcommunityacquiredheterogeneousamyloidpetdata AT robertkoeppe rpoprobustpetonlyprocessingofcommunityacquiredheterogeneousamyloidpetdata AT barryasiegel rpoprobustpetonlyprocessingofcommunityacquiredheterogeneousamyloidpetdata AT bruceehillner rpoprobustpetonlyprocessingofcommunityacquiredheterogeneousamyloidpetdata AT constantinegatsonis rpoprobustpetonlyprocessingofcommunityacquiredheterogeneousamyloidpetdata AT rachelawhitmer rpoprobustpetonlyprocessingofcommunityacquiredheterogeneousamyloidpetdata AT mariaccarrillo rpoprobustpetonlyprocessingofcommunityacquiredheterogeneousamyloidpetdata AT charlesapgar rpoprobustpetonlyprocessingofcommunityacquiredheterogeneousamyloidpetdata AT monicarcamacho rpoprobustpetonlyprocessingofcommunityacquiredheterogeneousamyloidpetdata AT rachelnosheny rpoprobustpetonlyprocessingofcommunityacquiredheterogeneousamyloidpetdata AT gildrabinovici rpoprobustpetonlyprocessingofcommunityacquiredheterogeneousamyloidpetdata |