Weiquan Luo, Davneet S Minhas, Ethan D Rubenstein, David N Situ, Sarah K Royse, Beau M Ances, Bradley T Christian, Ann D Cohen, Benjamin L Handen, William E Klunk, Dana L Tudorascu, Shahid Zaman, Charles M Laymon, Alzheimer's Biomarkers Consortium–Down Syndrome (ABC-DS) Investigators
{"title":"唐氏综合症数据的Centiloid方法图像预处理管道的开发与评价","authors":"Weiquan Luo, Davneet S Minhas, Ethan D Rubenstein, David N Situ, Sarah K Royse, Beau M Ances, Bradley T Christian, Ann D Cohen, Benjamin L Handen, William E Klunk, Dana L Tudorascu, Shahid Zaman, Charles M Laymon, Alzheimer's Biomarkers Consortium–Down Syndrome (ABC-DS) Investigators","doi":"10.1002/alz.70712","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> BACKGROUND</h3>\n \n <p>Centiloid provides a standardized process to quantify brain amyloid in which a subject's T1 magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) scans are registered and warped to Montreal Neurological Institute 152 space using prescribed procedures. The method has a high failure rate in Down syndrome (DS) subjects from the Neurodegeneration in Aging Down Syndrome (NiAD) project. We evaluate imaging preprocessing methods (PMs) to improve the DS success rate.</p>\n </section>\n \n <section>\n \n <h3> METHODS</h3>\n \n <p>PMs were constructed from combinations of image origin reset, filtering, MRI bias correction, and MRI skull stripping. Centiloid results were evaluated for adherence to standards using The Global Alzheimer's Association Interactive Network dataset. PMs were also evaluated using the NiAD dataset to judge their suitability for the DS population. DS PM evaluation procedures were developed corresponding to those specified for non-DS populations.</p>\n </section>\n \n <section>\n \n <h3> RESULTS</h3>\n \n <p>Five accepted PMs improved the Centiloid-processing success rate in the DS cohort from 61.3% to 95.6%.</p>\n </section>\n \n <section>\n \n <h3> DISCUSSION</h3>\n \n <p>The identified combinations of preprocessing steps substantially improved the success rate of Centiloid processing in DS.</p>\n </section>\n \n <section>\n \n <h3> Highlights</h3>\n \n <div>\n <ul>\n \n <li>Image preprocessing pipeline is proposed for Centiloid analysis of DS.</li>\n \n <li>Preprocessing pipelines are evaluated for adherence to Centiloid standards.</li>\n \n <li>Pipelines are evaluated for improvement in yield of usable imaging data.</li>\n \n <li>Preprocessing of amyloid imaging data resulted in a large yield improvement.</li>\n </ul>\n </div>\n </section>\n </div>","PeriodicalId":7471,"journal":{"name":"Alzheimer's & Dementia","volume":"21 10","pages":""},"PeriodicalIF":11.1000,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://alz-journals.onlinelibrary.wiley.com/doi/epdf/10.1002/alz.70712","citationCount":"0","resultStr":"{\"title\":\"Development and evaluation of image preprocessing pipelines for the Centiloid method on Down Syndrome data\",\"authors\":\"Weiquan Luo, Davneet S Minhas, Ethan D Rubenstein, David N Situ, Sarah K Royse, Beau M Ances, Bradley T Christian, Ann D Cohen, Benjamin L Handen, William E Klunk, Dana L Tudorascu, Shahid Zaman, Charles M Laymon, Alzheimer's Biomarkers Consortium–Down Syndrome (ABC-DS) Investigators\",\"doi\":\"10.1002/alz.70712\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> BACKGROUND</h3>\\n \\n <p>Centiloid provides a standardized process to quantify brain amyloid in which a subject's T1 magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) scans are registered and warped to Montreal Neurological Institute 152 space using prescribed procedures. The method has a high failure rate in Down syndrome (DS) subjects from the Neurodegeneration in Aging Down Syndrome (NiAD) project. We evaluate imaging preprocessing methods (PMs) to improve the DS success rate.</p>\\n </section>\\n \\n <section>\\n \\n <h3> METHODS</h3>\\n \\n <p>PMs were constructed from combinations of image origin reset, filtering, MRI bias correction, and MRI skull stripping. Centiloid results were evaluated for adherence to standards using The Global Alzheimer's Association Interactive Network dataset. PMs were also evaluated using the NiAD dataset to judge their suitability for the DS population. DS PM evaluation procedures were developed corresponding to those specified for non-DS populations.</p>\\n </section>\\n \\n <section>\\n \\n <h3> RESULTS</h3>\\n \\n <p>Five accepted PMs improved the Centiloid-processing success rate in the DS cohort from 61.3% to 95.6%.</p>\\n </section>\\n \\n <section>\\n \\n <h3> DISCUSSION</h3>\\n \\n <p>The identified combinations of preprocessing steps substantially improved the success rate of Centiloid processing in DS.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Highlights</h3>\\n \\n <div>\\n <ul>\\n \\n <li>Image preprocessing pipeline is proposed for Centiloid analysis of DS.</li>\\n \\n <li>Preprocessing pipelines are evaluated for adherence to Centiloid standards.</li>\\n \\n <li>Pipelines are evaluated for improvement in yield of usable imaging data.</li>\\n \\n <li>Preprocessing of amyloid imaging data resulted in a large yield improvement.</li>\\n </ul>\\n </div>\\n </section>\\n </div>\",\"PeriodicalId\":7471,\"journal\":{\"name\":\"Alzheimer's & Dementia\",\"volume\":\"21 10\",\"pages\":\"\"},\"PeriodicalIF\":11.1000,\"publicationDate\":\"2025-10-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://alz-journals.onlinelibrary.wiley.com/doi/epdf/10.1002/alz.70712\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Alzheimer's & Dementia\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz.70712\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Alzheimer's & Dementia","FirstCategoryId":"3","ListUrlMain":"https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz.70712","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Development and evaluation of image preprocessing pipelines for the Centiloid method on Down Syndrome data
BACKGROUND
Centiloid provides a standardized process to quantify brain amyloid in which a subject's T1 magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) scans are registered and warped to Montreal Neurological Institute 152 space using prescribed procedures. The method has a high failure rate in Down syndrome (DS) subjects from the Neurodegeneration in Aging Down Syndrome (NiAD) project. We evaluate imaging preprocessing methods (PMs) to improve the DS success rate.
METHODS
PMs were constructed from combinations of image origin reset, filtering, MRI bias correction, and MRI skull stripping. Centiloid results were evaluated for adherence to standards using The Global Alzheimer's Association Interactive Network dataset. PMs were also evaluated using the NiAD dataset to judge their suitability for the DS population. DS PM evaluation procedures were developed corresponding to those specified for non-DS populations.
RESULTS
Five accepted PMs improved the Centiloid-processing success rate in the DS cohort from 61.3% to 95.6%.
DISCUSSION
The identified combinations of preprocessing steps substantially improved the success rate of Centiloid processing in DS.
Highlights
Image preprocessing pipeline is proposed for Centiloid analysis of DS.
Preprocessing pipelines are evaluated for adherence to Centiloid standards.
Pipelines are evaluated for improvement in yield of usable imaging data.
Preprocessing of amyloid imaging data resulted in a large yield improvement.
期刊介绍:
Alzheimer's & Dementia is a peer-reviewed journal that aims to bridge knowledge gaps in dementia research by covering the entire spectrum, from basic science to clinical trials to social and behavioral investigations. It provides a platform for rapid communication of new findings and ideas, optimal translation of research into practical applications, increasing knowledge across diverse disciplines for early detection, diagnosis, and intervention, and identifying promising new research directions. In July 2008, Alzheimer's & Dementia was accepted for indexing by MEDLINE, recognizing its scientific merit and contribution to Alzheimer's research.