Deep residual inception encoder‐decoder network for amyloid PET harmonization
Introduction Multiple positron emission tomography (PET) tracers are available for amyloid imaging, posing a significant challenge to consensus interpretation and quantitative analysis. We accordingly developed and validated a deep learning model as a harmonization strategy. Method A Residual Incept...
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| Veröffentlicht in: | Alzheimer's & dementia Jg. 18; H. 12; S. 2448 - 2457 |
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01.12.2022
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| Abstract | Introduction
Multiple positron emission tomography (PET) tracers are available for amyloid imaging, posing a significant challenge to consensus interpretation and quantitative analysis. We accordingly developed and validated a deep learning model as a harmonization strategy.
Method
A Residual Inception Encoder‐Decoder Neural Network was developed to harmonize images between amyloid PET image pairs made with Pittsburgh Compound‐B and florbetapir tracers. The model was trained using a dataset with 92 subjects with 10‐fold cross validation and its generalizability was further examined using an independent external dataset of 46 subjects.
Results
Significantly stronger between‐tracer correlations (P < .001) were observed after harmonization for both global amyloid burden indices and voxel‐wise measurements in the training cohort and the external testing cohort.
Discussion
We proposed and validated a novel encoder‐decoder based deep model to harmonize amyloid PET imaging data from different tracers. Further investigation is ongoing to improve the model and apply to additional tracers. |
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| AbstractList | Introduction
Multiple positron emission tomography (PET) tracers are available for amyloid imaging, posing a significant challenge to consensus interpretation and quantitative analysis. We accordingly developed and validated a deep learning model as a harmonization strategy.
Method
A Residual Inception Encoder‐Decoder Neural Network was developed to harmonize images between amyloid PET image pairs made with Pittsburgh Compound‐B and florbetapir tracers. The model was trained using a dataset with 92 subjects with 10‐fold cross validation and its generalizability was further examined using an independent external dataset of 46 subjects.
Results
Significantly stronger between‐tracer correlations (P < .001) were observed after harmonization for both global amyloid burden indices and voxel‐wise measurements in the training cohort and the external testing cohort.
Discussion
We proposed and validated a novel encoder‐decoder based deep model to harmonize amyloid PET imaging data from different tracers. Further investigation is ongoing to improve the model and apply to additional tracers. Multiple positron emission tomography (PET) tracers are available for amyloid imaging, posing a significant challenge to consensus interpretation and quantitative analysis. We accordingly developed and validated a deep learning model as a harmonization strategy. A Residual Inception Encoder-Decoder Neural Network was developed to harmonize images between amyloid PET image pairs made with Pittsburgh Compound-B and florbetapir tracers. The model was trained using a dataset with 92 subjects with 10-fold cross validation and its generalizability was further examined using an independent external dataset of 46 subjects. Significantly stronger between-tracer correlations (P < .001) were observed after harmonization for both global amyloid burden indices and voxel-wise measurements in the training cohort and the external testing cohort. We proposed and validated a novel encoder-decoder based deep model to harmonize amyloid PET imaging data from different tracers. Further investigation is ongoing to improve the model and apply to additional tracers. Multiple positron emission tomography (PET) tracers are available for amyloid imaging, posing a significant challenge to consensus interpretation and quantitative analysis. We accordingly developed and validated a deep learning model as a harmonization strategy.INTRODUCTIONMultiple positron emission tomography (PET) tracers are available for amyloid imaging, posing a significant challenge to consensus interpretation and quantitative analysis. We accordingly developed and validated a deep learning model as a harmonization strategy.A Residual Inception Encoder-Decoder Neural Network was developed to harmonize images between amyloid PET image pairs made with Pittsburgh Compound-B and florbetapir tracers. The model was trained using a dataset with 92 subjects with 10-fold cross validation and its generalizability was further examined using an independent external dataset of 46 subjects.METHODA Residual Inception Encoder-Decoder Neural Network was developed to harmonize images between amyloid PET image pairs made with Pittsburgh Compound-B and florbetapir tracers. The model was trained using a dataset with 92 subjects with 10-fold cross validation and its generalizability was further examined using an independent external dataset of 46 subjects.Significantly stronger between-tracer correlations (P < .001) were observed after harmonization for both global amyloid burden indices and voxel-wise measurements in the training cohort and the external testing cohort.RESULTSSignificantly stronger between-tracer correlations (P < .001) were observed after harmonization for both global amyloid burden indices and voxel-wise measurements in the training cohort and the external testing cohort.We proposed and validated a novel encoder-decoder based deep model to harmonize amyloid PET imaging data from different tracers. Further investigation is ongoing to improve the model and apply to additional tracers.DISCUSSIONWe proposed and validated a novel encoder-decoder based deep model to harmonize amyloid PET imaging data from different tracers. Further investigation is ongoing to improve the model and apply to additional tracers. |
| Author | Su, Yi Ghisays, Valentina Shah, Jay Luo, Ji Chen, Kewei Benzinger, Tammie L.S. Gao, Fei Chen, Yinghua Reiman, Eric M. Wu, Teresa Zhou, Yuxiang Li, Baoxin Lee, Wendy |
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| References | 2019; 9 2018; 286 2009; 46 2019; 5 1991; 12 2020; 63 2019; 11 2015; 521 2015; 11 2019; 15 1991; 82 2020; 16 2008; 15 2013; 169 2011; 10 2020; 79 2020; 12 2015; 107 2012; 367 2013; 8 2012; 11 2012; 53 2004; 55 2018; 19 2012; 2 2006; 67 2015; 313 2013; 54 2009; 50 2013; 34 2003; 46 2019 2019; 179 2011; 68 2020; 24 2015 2011; 69 2014; 17 2014; 6 2010; 51 2018; 14 |
| References_xml | – volume: 17 start-page: 305 year: 2014 end-page: 312 article-title: Deep learning based imaging data completion for improved brain disease diagnosis publication-title: Med Image Comput Comput Assist Interv – start-page: 234 year: 2015 end-page: 241 – volume: 50 start-page: 1251 year: 2009 end-page: 1259 article-title: Phase 1 study of the Pittsburgh compound B derivative 18F‐flutemetamol in healthy volunteers and patients with probable Alzheimer disease publication-title: J Nucl Med – volume: 55 start-page: 306 year: 2004 end-page: 319 article-title: Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound‐B publication-title: Ann Neurol – volume: 46 start-page: 154 year: 2009 end-page: 159 article-title: Reducing between scanner differences in multi‐center PET studies publication-title: Neuroimage – volume: 313 start-page: 1924 year: 2015 end-page: 1938 article-title: Prevalence of cerebral amyloid pathology in persons without dementia: a meta‐analysis publication-title: JAMA – volume: 169 start-page: 737 year: 2013 end-page: 743 article-title: Preclinical trials in autosomal dominant AD: implementation of the DIAN‐TU trial publication-title: Rev Neurol (Paris) – volume: 67 start-page: 446 issue: 3 year: 2006 end-page: 452 article-title: [11C]PIB in a nondemented population: Potential antecedent marker of Alzheimer disease publication-title: Neurology – volume: 11 start-page: 180 year: 2019 end-page: 190 article-title: Comparison of Pittsburgh compound B and florbetapir in cross‐sectional and longitudinal studies publication-title: Alzheimers Dement (Amst) – volume: 6 year: 2014 article-title: The A4 study: stopping AD before symptoms begin? publication-title: Sci Transl Med – start-page: 2242 end-page: 2251 – volume: 10 start-page: 424 issue: 5 year: 2011 end-page: 435 article-title: Cerebral amyloid‐β PET with florbetaben (18F) in patients with Alzheimer's disease and healthy controls: a multicentre phase 2 diagnostic study publication-title: Lancet Neurol – volume: 34 start-page: 457 year: 2013 end-page: 468 article-title: Early clinical PET imaging results with the novel PHF‐tau radioligand [F‐18]‐T807 publication-title: J Alzheimers Dis – volume: 9 start-page: 1952 year: 2019 article-title: For Alzheimer's disease neuroimaging I. Predicting Alzheimer's disease progression using multi‐modal deep learning approach publication-title: Sci Rep – volume: 63 start-page: 139 issue: 11 year: 2020 end-page: 144 article-title: Generative adversarial networks publication-title: Communications of the ACM – volume: 15 start-page: 1376 year: 2008 end-page: 1389 article-title: Automated (11)C‐PiB standardized uptake value ratio publication-title: Acad Radiol – volume: 16 start-page: 1023 year: 2020 end-page: 1030 article-title: Baseline demographic, clinical, and cognitive characteristics of the Alzheimer's Prevention Initiative (API) Autosomal‐Dominant Alzheimer's Disease Colombia Trial publication-title: Alzheimers Dement – volume: 14 start-page: 1565 issue: 12 year: 2018 end-page: 1571 article-title: Standardization of amyloid quantitation with florbetapir standardized uptake value ratios to the Centiloid scale publication-title: Alzheimers Dement – volume: 367 start-page: 795 year: 2012 end-page: 804 article-title: Clinical and biomarker changes in dominantly inherited Alzheimer's disease publication-title: N Engl J Med – volume: 14 start-page: 535 year: 2018 end-page: 562 article-title: NIA‐AA research framework: toward a biological definition of Alzheimer's disease publication-title: Alzheimers Dement – volume: 68 start-page: 1404 year: 2011 end-page: 1411 article-title: Using positron emission tomography and florbetapir F18 to image cortical amyloid in patients with mild cognitive impairment or dementia due to Alzheimer disease publication-title: Arch Neurol – volume: 46 start-page: 2740 year: 2003 end-page: 2754 article-title: Synthesis and evaluation of 11C‐labeled 6‐substituted 2‐arylbenzothiazoles as amyloid imaging agents publication-title: J Med Chem – volume: 11 start-page: 757 year: 2015 end-page: 771 article-title: The Alzheimer's Disease Neuroimaging Initiative 2 PET Core: 2015 publication-title: Alzheimers Dement – volume: 15 start-page: 807 year: 2019 end-page: 816 article-title: Comparison of F‐florbetaben quantification results using the standard Centiloid, MR‐based, and MR‐less CapAIBL approaches: validation against histopathology publication-title: Alzheimers Dement – volume: 5 start-page: 216 year: 2019 end-page: 227 article-title: The Alzheimer's Prevention Initiative Generation Program: study design of two randomized controlled trials for individuals at risk for clinical onset of Alzheimer's disease publication-title: Alzheimers Dement (N Y) – volume: 179 start-page: 312 issue: 2 year: 2019 end-page: 339 article-title: Alzheimer disease: an update on pathobiology and treatment strategies publication-title: Cell – volume: 521 start-page: 436 year: 2015 end-page: 444 article-title: Deep learning publication-title: Nature – volume: 51 start-page: 913 year: 2010 end-page: 920 article-title: In vivo imaging of amyloid deposition in Alzheimer disease using the radioligand 18F‐AV‐45 (florbetapir [corrected] F 18) publication-title: J Nucl Med – volume: 11 start-page: 1057 issue: 12 year: 2012 end-page: 1065 article-title: Florbetapir PET analysis of amyloid‐β deposition in the presenilin 1 E280A autosomal dominant Alzheimer's disease kindred: a cross‐sectional study publication-title: Lancet Neurol – volume: 19 start-page: 406 year: 2018 end-page: 416 article-title: Utilizing the Centiloid scale in cross‐sectional and longitudinal PiB PET studies publication-title: Neuroimage Clin – volume: 69 start-page: 181 year: 2011 end-page: 192 article-title: Longitudinal assessment of Aβ and cognition in aging and Alzheimer disease publication-title: Ann Neurol – volume: 8 year: 2013 article-title: Quantitative analysis of PiB‐PET with FreeSurfer ROIs publication-title: PLoS One – volume: 107 start-page: 55 year: 2015 end-page: 64 article-title: Partial volume correction in quantitative amyloid imaging publication-title: Neuroimage – volume: 12 start-page: 22 year: 2020 article-title: Comparison of amyloid PET measured in Centiloid units with neuropathological findings in Alzheimer's disease publication-title: Alzheimers Res Ther – volume: 82 start-page: 239 year: 1991 end-page: 259 article-title: Neuropathological stageing of Alzheimer‐related changes publication-title: Acta Neuropathol – volume: 79 year: 2020 article-title: MedGAN: medical image translation using GANs publication-title: Comput Med Imaging Graph. – volume: 54 start-page: 70 year: 2013 end-page: 77 article-title: Amyloid‐β imaging with Pittsburgh compound B and florbetapir: comparing radiotracers and quantification methods publication-title: J Nucl Med – volume: 53 start-page: 415 year: 2012 end-page: 424 article-title: Clinical validation of 18F‐AZD4694, an amyloid‐β‐specific PET radioligand publication-title: J Nucl Med – volume: 286 start-page: 676 year: 2018 end-page: 684 article-title: Deep learning MR imaging‐based attenuation correction for PET/MR imaging publication-title: Radiology – volume: 11 start-page: 1 year: 2015 end-page: 15.e4 article-title: The Centiloid Project: standardizing quantitative amyloid plaque estimation by PET publication-title: Alzheimers Dement – volume: 12 start-page: 295 year: 1991 end-page: 312 article-title: The distribution of tangles, plaques and related immunohistochemical markers in healthy aging and Alzheimer's disease publication-title: Neurobiol Aging – year: 2019 – start-page: 770 end-page: 778 – volume: 24 start-page: 39 year: 2020 end-page: 49 article-title: Deep residual inception encoder‐decoder network for medical imaging synthesis publication-title: IEEE J Biomed Health Inform – volume: 2 start-page: 975 year: 2012 end-page: 984 article-title: Developing an international network for Alzheimer research: the Dominantly Inherited Alzheimer Network publication-title: Clin Investig (Lond) |
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| Snippet | Introduction
Multiple positron emission tomography (PET) tracers are available for amyloid imaging, posing a significant challenge to consensus interpretation... Multiple positron emission tomography (PET) tracers are available for amyloid imaging, posing a significant challenge to consensus interpretation and... |
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| SubjectTerms | Alzheimer Disease - diagnostic imaging Alzheimer's disease Amyloid - metabolism amyloid PET Amyloidogenic Proteins Aniline Compounds Brain - diagnostic imaging Brain - metabolism Centiloid Humans Positron-Emission Tomography - methods Radiopharmaceuticals |
| Title | Deep residual inception encoder‐decoder network for amyloid PET harmonization |
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