AI-powered FDG-PET radiomics: a door to better Alzheimer's disease classification?

被引:0
作者
Rakvongthai, Yothin [1 ,2 ]
Patipipittana, Supanuch [1 ,3 ]
机构
[1] Chulalongkorn Univ, Chulalongkorn Univ Biomed Imaging Grp, Fac Med, Dept Radiol, Bangkok, Thailand
[2] Chulalongkorn Univ, Fac Med, Dept Radiol, Div Nucl Med, Bangkok, Thailand
[3] Chulalongkorn Univ, Fac Med, Dept Radiol, Med Phys Program, Bangkok, Thailand
关键词
D O I
10.1007/s00330-025-11381-y
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
引用
收藏
页码:2617 / 2619
页数:3
相关论文
共 10 条
[1]   Machine learning and deep learning methods that use omics data for metastasis prediction [J].
Albaradei, Somayah ;
Thafar, Maha ;
Alsaedi, Asim ;
Van Neste, Christophe ;
Gojobori, Takashi ;
Essack, Magbubah ;
Gao, Xin .
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, 2021, 19 :5008-5018
[2]   Alzheimer's disease [J].
Scheltens, Philip ;
De Strooper, Bart ;
Kivipelto, Miia ;
Holstege, Henne ;
Chetelat, Gael ;
Teunissen, Charlotte E. ;
Cummings, Jeffrey ;
van der Flier, Wiesje M. .
LANCET, 2021, 397 (10284) :1577-1590
[3]   Applications of amyloid, tau, and neuroinflammation PET imaging to Alzheimer's disease and mild cognitive impairment [J].
Chandra, Avinash ;
Valkimadi, Polytimi-Eleni ;
Pagano, Gennaro ;
Cousins, Oliver ;
Dervenoulas, George ;
Politis, Marios .
HUMAN BRAIN MAPPING, 2019, 40 (18) :5424-5442
[4]   A 3D deep learning model to predict the diagnosis of dementia with Lewy bodies, Alzheimer's disease, and mild cognitive impairment using brain 18F-FDG PET [J].
Etminani, Kobra ;
Soliman, Amira ;
Davidsson, Anette ;
Chang, Jose R. ;
Martinez-Sanchis, Begona ;
Byttner, Stefan ;
Camacho, Valle ;
Bauckneht, Matteo ;
Stegeran, Roxana ;
Ressner, Marcus ;
Agudelo-Cifuentes, Marc ;
Chincarini, Andrea ;
Brendel, Matthias ;
Rominger, Axel ;
Bruffaerts, Rose ;
Vandenberghe, Rik ;
Kramberger, Milica G. ;
Trost, Maja ;
Nicastro, Nicolas ;
Frisoni, Giovanni B. ;
Lemstra, Afina W. ;
van Berckel, Bart N. M. ;
Pilotto, Andrea ;
Padovani, Alessandro ;
Morbelli, Silvia ;
Aarsland, Dag ;
Nobili, Flavio ;
Garibotto, Valentina ;
Ochoa-Figueroa, Miguel .
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2022, 49 (02) :563-584
[5]   Using interpretable deep learning radiomics model to diagnose and predict progression of early AD disease spectrum: a preliminary [18F]FDG PET study [J].
Jiang, Jiehui ;
Li, Chenyang ;
Lu, Jiaying ;
Sun, Jie ;
Sun, Xiaoming ;
Yang, Jiacheng ;
Wang, Luyao ;
Zuo, Chuantao ;
Shi, Kuangyu .
EUROPEAN RADIOLOGY, 2025, 35 (05) :2620-2633
[6]   Artificial Intelligence and Black-Box Medical Decisions: Accuracy versus Explainability [J].
London, Alex John .
HASTINGS CENTER REPORT, 2019, 49 (01) :15-21
[7]   Predicting Progression from Normal to MCI and from MCI to AD Using Clinical Variables in the National Alzheimer's Coordinating Center Uniform Data Set Version 3: Application of Machine Learning Models and a Probability Calculator [J].
Pang, Y. ;
Kukull, W. ;
Sano, M. ;
Albin, R. L. ;
Shen, C. ;
Zhou, J. ;
Dodge, Hiroko H. .
JPAD-JOURNAL OF PREVENTION OF ALZHEIMERS DISEASE, 2023, 10 (02) :301-313
[8]  
Petersen Ronald C, 2016, Continuum (Minneap Minn), V22, P404, DOI 10.1212/CON.0000000000000313
[9]   Practice guideline update summary: Mild cognitive impairment: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology [J].
Petersen, Ronald C. ;
Lopez, Oscar ;
Armstrong, Melissa J. ;
Getchius, Thomas S. D. ;
Ganguli, Mary ;
Gloss, David ;
Gronseth, Gary S. ;
Marson, Daniel ;
Pringsheim, Tamara ;
Day, Gregory S. ;
Sager, Mark ;
Stevens, James ;
Rae-Grant, Alexander .
NEUROLOGY, 2018, 90 (03) :126-135
[10]   Towards a future where Alzheimer's disease pathology is stopped before the onset of dementia [J].
van der Flier, Wiesje M. ;
de Vugt, Marjolein E. ;
Smets, Ellen M. A. ;
Blom, Marco ;
Teunissen, Charlotte E. .
NATURE AGING, 2023, 3 (05) :494-505