Prospects for prediction - Ethics analysis of neuroimaging in Alzheimer's disease

被引:23
|
作者
Illes, J.
Rosen, A.
Greicius, M.
Racine, E.
机构
[1] Stanford Ctr Biomed Eth, Program Neuroeth, Stanford, CA 94304 USA
[2] Dept Radiol, Program Neuoeth, Stanford, CA 94304 USA
[3] Stanford Univ, Dept Psychiat & Behav Sci, Stanford, CA 94305 USA
[4] Palo Alto VA Healthcare Syst, Mental Illness Res Educ & Clin Ctr, Palo Alto, CA USA
[5] Stanford Univ, Dept Neurol & Neurol Sci, Stanford, CA 94305 USA
来源
IMAGING AND THE AGING BRAIN | 2007年 / 1097卷
关键词
neuroimaging; Alzheimer's disease; aging; prediction; neuroethics;
D O I
10.1196/annals.1379.030
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
This article focuses on the prospects and ethics of using neuroimaging to predict Alzheimer's disease (AD). It is motivated by consideration of the historical roles of science in medicine and society, and considerations specifically contemporary of capabilities in imaging and aging, and the benefits and hope they bring. A general consensus is that combinations of imaging methods will ultimately be most fruitful in predicting disease. Their roll-out into translational practice will not be free of complexity, however, as culture and values differ in terms of what defines benefit and risk, who will benefit and who is at risk, what methods must be in place to assure the maximum safety, comfort, and protection of subjects and patients, and educational and policy needs. Proactive planning for the ethical and societal implications of predicting diseases of the aging brain is critical and will benefit all stakeholders-researchers, patients and families, health care providers, and policy makers.
引用
收藏
页码:278 / 295
页数:18
相关论文
共 50 条
  • [21] Neuroimaging in Alzheimer's disease: An overview
    Masdeu, J
    REVISTA DE NEUROLOGIA, 2004, 38 (12) : 1156 - 1165
  • [22] Explainable Artificial Intelligence in Neuroimaging of Alzheimer's Disease
    Khosroshahi, Mahdieh Taiyeb
    Morsali, Soroush
    Gharakhanlou, Sohrab
    Motamedi, Alireza
    Hassanbaghlou, Saeid
    Vahedi, Hadi
    Pedrammehr, Siamak
    Kabir, Hussain Mohammed Dipu
    Jafarizadeh, Ali
    DIAGNOSTICS, 2025, 15 (05)
  • [23] Functional neuroimaging in Alzheimer's disease
    Hiroshi Matsuda
    Radiation Medicine, 2006, 24 (4): : 302 - 308
  • [24] The role of neuroimaging in Alzheimer's disease
    Colliot, O.
    Chupin, M.
    Sarazin, M.
    Habert, M. -O.
    Dormont, D.
    Lehericy, S.
    PSN-PSYCHIATRIE SCIENCES HUMAINES NEUROSCIENCES, 2008, 6 (02): : 68 - 75
  • [25] Molecular Neuroimaging in Alzheimer's Disease
    Matsuda, Hiroshi
    Imabayashi, Etsuko
    NEUROIMAGING CLINICS OF NORTH AMERICA, 2012, 22 (01) : 57 - +
  • [26] Progress in neuroimaging of Alzheimer's disease
    Matsuda, Hiroshi
    PSYCHOGERIATRICS, 2007, 7 (03) : 118 - 124
  • [27] A review of artificial intelligence methods for Alzheimer's disease diagnosis: Insights from neuroimaging to sensor data analysis
    Bazarbekov, Ikram
    Razaque, Abdul
    Ipalakova, Madina
    Yoo, Joon
    Assipova, Zhanna
    Almisreb, Ali
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2024, 92
  • [28] Differential atrophy along the longitudinal hippocampal axis in Alzheimer's disease for the Alzheimer's Disease Neuroimaging Initiative
    Morais-Ribeiro, Rafaela
    Almeida, Francisco C.
    Coelho, Ana
    Oliveira, Tiago Gil
    EUROPEAN JOURNAL OF NEUROSCIENCE, 2024, 59 (12) : 3376 - 3388
  • [29] Biomarkers and phenotypic expression in Alzheimer’s disease: exploring the contribution of frailty in the Alzheimer’s Disease Neuroimaging Initiative
    Marco Canevelli
    Ivan Arisi
    Ilaria Bacigalupo
    Andrea Arighi
    Daniela Galimberti
    Nicola Vanacore
    Mara D’Onofrio
    Matteo Cesari
    Giuseppe Bruno
    GeroScience, 2021, 43 : 1039 - 1051
  • [30] Neuroimaging studies of acupuncture on Alzheimer’s disease: a systematic review
    Zihan Yin
    Ziqi Wang
    Yaqin Li
    Jun Zhou
    Zhenghong Chen
    Manze Xia
    Xinyue Zhang
    Jiajing Wu
    Ling Zhao
    Fanrong Liang
    BMC Complementary Medicine and Therapies, 23