Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
470-08-134 ISMRM Abstract

Toward the evaluation of Aβ plaque load in human brain with MRI at 3T

Primary: Analysis Methods - Segmentation and Detection
Secondary: Acquisition & Reconstruction - Image Reconstruction: Non-AI
470-08-134 · Analysis: Neuro · Tuesday, 12 May, 4:00 PM–4:55 PM · Traditional Posters | Exhibition Hall
Keywords: Alzheimer's Disease Mild cognitive impairment Amyloid PET 3T MRI T2-star
Accepted
Yutong Mao1, Xiao Liu1, Jianli Wang2, Rommy Elyan2, Prasanna Karunanayaka2, Deepak Kalra3, Paul Eslinger3, Katie Geesey2, Sangam Kanekar 2, William Jens3, Senal D Peiris2,4, Anupa Ekanayake2,5, Qing Yang 6
1Biomedical Engineering, Penn State university, Hershey, United States of America
2Radiology, The Pennsylvania State University, Hershey, Pennsylvania, United States of America
3Neurology, The Pennsylvania State University, Hershey, Pennsylvania, United States of America
4Penn State university, Hershey, United States of America
5Radiology, Penn State university, Hershey, United States of America
6Neurosurgery, The Pennsylvania State University, Hershey, Pennsylvania, United States of America
Presenting Author: Qing Yang

Synopsis

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References

1. Meadowcroft, M. D., Connor, J. R., Smith, M. B., & Yang, Q. X. (2009). MRI and histological analysis of beta-amyloid plaques in both human Alzheimer's disease and APP/PS1 transgenic mice. Journal of magnetic resonance imaging : JMRI, 29(5), 997–1007. https://doi.org/10.1002/jmri.21731 [doi]
2. Bulk, M., Kenkhuis, B., van der Graaf, L. M., Goeman, J. J., Natté, R., & van der Weerd, L. (2018). Postmortem T2*- Weighted MRI Imaging of Cortical Iron Reflects Severity of Alzheimer's Disease. Journal of Alzheimer's disease : JAD, 65(4), 1125–1137. https://doi.org/10.3233/JAD-180317 [doi]
3. Yang, Q. X., Demeure, R. J., Dardzinski, B. J., Arnold, B. W., & Smith, M. B. (1999). Multiple echo frequency-domain image contrast: improved signal-to-noise ratio and T2 (T2*) weighting. Magnetic resonance in medicine, 41(2), 423–428. https://doi.org/10.1002/(sici)1522-2594(199902)41:2<423::aid-mrm30>3.0.co;2-m [doi]
4. Fischl B. (2012). FreeSurfer. NeuroImage, 62(2), 774–781. https://doi.org/10.1016/j.neuroimage.2012.01.021 [doi]
5. Routier, A., Burgos, N., Díaz, M., Bacci, M., Bottani, S., El-Rifai, O., Fontanella, S., Gori, P., Guillon, J., Guyot, A., Hassanaly, R., Jacquemont, T., Lu, P., Marcoux, A., Moreau, T., Samper-González, J., Teichmann, M., Thibeau-Sutre, E., Vaillant, G., Wen, J., … Colliot, O. (2021). Clinica: An Open-Source Software Platform for Reproducible Clinical Neuroscience Studies. Frontiers in neuroinformatics, 15, 689675. https://doi.org/10.3389/fninf.2021.689675 [doi]
6. Kim, J. Y., Suh, H. Y., Ryoo, H. G., Oh, D., Choi, H., Paeng, J. C., Cheon, G. J., Kang, K. W., Lee, D. S., & Alzheimer’s Disease Neuroimaging Initiative (2019). Amyloid PET Quantification Via End-to-End Training of a Deep Learning. Nuclear medicine and molecular imaging, 53(5), 340–348. https://doi.org/10.1007/s13139-019-00610-0. [doi]
7. Royse, S. K., Minhas, D. S., Lopresti, B. J., Murphy, A., Ward, T., Koeppe, R. A., Bullich, S., DeSanti, S., Jagust, W. J., Landau, S. M., & Alzheimer’s Disease Neuroimaging Initiative (2021). Validation of amyloid PET positivity thresholds in centiloids: a multisite PET study approach. Alzheimer's research & therapy, 13(1), 99. https://doi.org/10.1186/s13195-021-00836-1 [doi]
8. Dumurgier, J., Sabia, S., Zetterberg, H., Teunissen, C. E., Hanseeuw, B., Orellana, A., Schraen, S., Gabelle, A., Boada, M., Lebouvier, T., Willemse, E. A. J., Cognat, E., Ruiz, A., Hourregue, C., Lilamand, M., Bouaziz-Amar, E., Laplanche, J. L., Lehmann, S., Pasquier, F., Scheltens, P., … Alzheimer's Disease Neuroimaging Initiative (2022). A Pragmatic, Data-Driven Method to Determine Cutoffs for CSF Biomarkers of Alzheimer Disease Based on Validation Against PET Imaging. Neurology, 99(7), e669–e678. https://doi.org/10.1212/WNL.0000000000200735 [doi]
9. Schreiber, S., Landau, S. M., Fero, A., Schreiber, F., Jagust, W. J., & Alzheimer's Disease Neuroimaging Initiative (2015). Comparison of Visual and Quantitative Florbetapir F 18 Positron Emission Tomography Analysis in Predicting Mild Cognitive Impairment Outcomes. JAMA neurology, 72(10), 1183–1190. https://doi.org/10.1001/jamaneurol.2015.1633 [doi]
10. Thal, D. R., Rüb, U., Orantes, M., & Braak, H. (2002). Phases of A beta-deposition in the human brain and its relevance for the development of AD. Neurology, 58(12), 1791–1800. https://doi.org/10.1212/wnl.58.12.1791 [doi]
11. Hampel, H., Hardy, J., Blennow, K., Chen, C., Perry, G., Kim, S. H., Villemagne, V. L., Aisen, P., Vendruscolo, M., Iwatsubo, T., Masters, C. L., Cho, M., Lannfelt, L., Cummings, J. L., & Vergallo, A. (2021). The Amyloid-β Pathway in Alzheimer's Disease. Molecular psychiatry, 26(10), 5481–5503. https://doi.org/10.1038/s41380-021-01249-0 [doi]

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http://echo.ismrm.org/p/ISMRM2026/470-08-134