结合人工智能的结构影像分析对阿尔茨海默病的早期预测及精准诊断研究进展
网络出版日期: 2022-02-25
基金资助
广州市重点领域研发计划(202007030010);广州市科技计划(202206010007)
唐静仪, 余群, 刘军 . 结合人工智能的结构影像分析对阿尔茨海默病的早期预测及精准诊断研究进展[J]. 诊断学理论与实践, 2022 , 21(01) : 12 -17 . DOI: 10.16150/j.1671-2870.2022.01.004
| [1] | Dubois B, Feldman HH, Jacova C, et al. Research criteria for the diagnosis of Alzheimer′s disease: revising the NINCDS-ADRDA criteria[J]. Lancet Neurol, 2007, 6(8):734-746. |
| [2] | Dubois B, Feldman HH, Jacova C, et al. Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria[J]. Lancet Neurol, 2014, 13(6):614-629. |
| [3] | Jack CR Jr, Bennett DA, Blennow K, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer′s disease[J]. Alzheimers Dement, 2018, 14(4):535-562. |
| [4] | Pontecorvo MJ, Devous MD Sr, Navitsky M, et al. Relationships between flortaucipir PET tau binding and amyloid burden, clinical diagnosis, age and cognition[J]. Brain, 2017, 140(3):748-763. |
| [5] | Marcone A, Garibotto V, Moresco RM, et al. [11C]-MP4A PET cholinergic measurements in amnestic mild cognitive impairment, probable Alzheimer′s disease, and dementia with Lewy bodies: a Bayesian method and voxel-based analysis[J]. J Alzheimers Dis, 2012, 31(2):387-399. |
| [6] | Dubois B, Villain N, Frisoni GB, et al. Clinical diagnosis of Alzheimer′s disease: recommendations of the International Working Group[J]. Lancet Neurol, 2021, 20(6):484-496. |
| [7] | Shen L, Saykin AJ, Kim S, et al. Comparison of manual and automated determination of hippocampal volumes in MCI and early AD[J]. Brain Imaging Behav, 2010, 4(1):86-95. |
| [8] | Brewer JB, Magda S, Airriess C, et al. Fully-automated quantification of regional brain volumes for improved detection of focal atrophy in Alzheimer disease[J]. AJNR Am J Neuroradiol, 2009, 30(3):578-580. |
| [9] | Ahdidan J, Raji CA, DeYoe EA, et al. Quantitative Neuroimaging Software for Clinical Assessment of Hippocampal Volumes on MR Imaging[J]. J Alzheimers Dis, 2016, 49(3):723-732. |
| [10] | Abrigo J, Shi L, Luo Y, et al. Standardization of hippocampus volumetry using automated brain structure volumetry tool for an initial Alzheimer′s disease imaging biomarker[J]. Acta Radiol, 2019, 60(6):769-776. |
| [11] | Rathore S, Habes M, Iftikhar MA, et al. A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer′s disease and its prodromal stages[J]. Neuroimage, 2017, 155:530-548. |
| [12] | Hill DLG, Schwarz AJ, Isaac M, et al. Coalition Against Major Diseases/European Medicines Agency biomarker qualification of hippocampal volume for enrichment of clinical trials in predementia stages of Alzheimer′s disease[J]. Alzheimers Dement, 2014, 10(4):421-429,e3. |
| [13] | Jack CR Jr, Knopman DS, Jagust WJ, et al. Hypothetical model of dynamic biomarkers of the Alzheimer′s pathological cascade[J]. Lancet Neurol, 2010, 9(1):119-128. |
| [14] | Desikan RS, Cabral HJ, Hess CP, et al. Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer′s disease[J]. Brain, 2009, 132(Pt 8):2048-2057. |
| [15] | Colliot O, Chételat G, Chupin M, et al. Discrimination between Alzheimer disease, mild cognitive impairment, and normal aging by using automated segmentation of the hippocampus[J]. Radiology, 2008, 248(1):194-201. |
| [16] | Fleisher AS, Sun S, Taylor C, et al. Volumetric MRI vs clinical predictors of Alzheimer disease in mild cognitive impairment[J]. Neurology, 2008, 70(3):191-199. |
| [17] | McEvoy LK, Fennema-Notestine C, Roddey JC, et al. Alzheimer disease: quantitative structural neuroimaging for detection and prediction of clinical and structural changes in mild cognitive impairment[J]. Radiology, 2009, 251(1):195-205. |
| [18] | Sarica A, Vasta R, Novellino F, et al. MRI Asymmetry Index of Hippocampal Subfields Increases Through the Continuum From the Mild Cognitive Impairment to the Alzheimer′s Disease[J]. Front Neurosci, 2018, 12:576. |
| [19] | Yue L, Wang T, Wang J, et al. Asymmetry of Hippocampus and Amygdala Defect in Subjective Cognitive Decline Among the Community Dwelling Chinese[J]. Front Psychiatry, 2018, 9:226. |
| [20] | de Flores R, La Joie R, Chételat G. Structural imaging of hippocampal subfields in healthy aging and Alzheimer′s disease[J]. Neuroscience, 2015, 309:29-50. |
| [21] | Dong M, Xie L, Das SR, et al. DeepAtrophy: Teaching a neural network to detect progressive changes in longitudinal MRI of the hippocampal region in Alzheimer′s disease[J]. Neuroimage, 2021, 243:118514. |
| [22] | Sørensen L, Igel C, Liv Hansen N, et al. Early detection of Alzheimer′s disease using MRI hippocampal texture[J]. Hum Brain Mapp, 2016, 37(3):1148-1161. |
| [23] | Zhao K, Ding Y, Han Y, et al. Independent and reproducible hippocampal radiomic biomarkers for multisite Alzheimer′s disease diagnosis, longitudinal progress and biological basis[J]. Science Bulletin, 2020, 65(13):1103-1113. |
| [24] | Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes[J]. Acta Neuropathol, 1991, 82(4):239-259. |
| [25] | de Toledo-Morrell L, Goncharova I, Dickerson B, et al. From healthy aging to early Alzheimer′s disease: in vivo detection of entorhinal cortex atrophy[J]. Ann N Y Acad Sci, 2000, 911:240-253. |
| [26] | Ryu SY, Lim EY, Na S, et al. Hippocampal and entorhinal structures in subjective memory impairment: a combined MRI volumetric and DTI study[J]. Int Psychogeriatr, 2017, 29(5):785-792. |
| [27] | Devanand DP, Pradhaban G, Liu X, et al. Hippocampal and entorhinal atrophy in mild cognitive impairment: prediction of Alzheimer disease[J]. Neurology, 2007, 68(11):828-836. |
| [28] | deToledo-Morrell L, Stoub TR, Bulgakova M, et al. MRI-derived entorhinal volume is a good predictor of conversion from MCI to AD[J]. Neurobiol Aging, 2004, 25(9):1197-1203. |
| [29] | Killiany RJ, Hyman BT, Gomez-Isla T, et al. MRI measures of entorhinal cortex vs hippocampus in preclinical AD[J]. Neurology, 2002, 58(8):1188-1196. |
| [30] | Stoub TR, Rogalski EJ, Leurgans S, et al. Rate of entorhinal and hippocampal atrophy in incipient and mild AD: relation to memory function[J]. Neurobiol Aging, 2010, 31(7):1089-1098. |
| [31] | Du AT, Schuff N, Kramer JH, et al. Higher atrophy rate of entorhinal cortex than hippocampus in AD[J]. Neurology, 2004, 62(3):422-427. |
| [32] | Nikolenko VN, Oganesyan MV, Rizaeva NA, et al. Amygdala: Neuroanatomical and Morphophysiological Features in Terms of Neurological and Neurodegenerative Diseases[J]. Brain Sci, 2020, 10(8):502. |
| [33] | Basso M, Yang J, Warren L, et al. Volumetry of amygdala and hippocampus and memory performance in Alzheimer′s disease[J]. Psychiatry Res, 2006, 146(3):251-261. |
| [34] | Basso M, Gelernter J, Yang J, et al. Apolipoprotein E epsilon4 is associated with atrophy of the amygdala in Alzheimer′s disease[J]. Neurobiol Aging, 2006, 27(10):1416-1424. |
| [35] | Poulin SP, Dautoff R, Morris JC, et al. Amygdala atrophy is prominent in early Alzheimer′s disease and relates to symptom severity[J]. Psychiatry Res, 2011, 194(1):7-13. |
| [36] | Barnes J, Whitwell JL, Frost C, et al. Measurements of the amygdala and hippocampus in pathologically confirmed Alzheimer disease and frontotemporal lobar degeneration[J]. Arch Neurol, 2006, 63(10):1434-1439. |
| [37] | Cavedo E, Boccardi M, Ganzola R, et al. Local amygdala structural differences with 3T MRI in patients with Alzheimer disease[J]. Neurology, 2011, 76(8):727-733. |
| [38] | Miller MI, Younes L, Ratnanather JT, et al. Amygdalar atrophy in symptomatic Alzheimer′s disease based on diffeomorphometry: the BIOCARD cohort[J]. Neurobiol Aging, 2015, 36(Suppl 1):S3-S10. |
| [39] | Tang X, Holland D, Dale AM, et al. Baseline shape diffeomorphometry patterns of subcortical and ventricular structures in predicting conversion of mild cognitive impairment to Alzheimer′s disease[J]. J Alzheimers Dis, 2015, 44(2):599-611. |
| [40] | Tang X, Holland D, Dale AM, et al. The diffeomorphometry of regional shape change rates and its relevance to cognitive deterioration in mild cognitive impairment and Alzheimer′s disease[J]. Hum Brain Mapp, 2015, 36(6):2093-2117. |
| [41] | Chincarini A, Bosco P, Calvini P, et al. Local MRI analysis approach in the diagnosis of early and prodromal Alzheimer′s disease[J]. Neuroimage, 2011, 58(2):469-480. |
| [42] | Zhao L, Luo Y, Lew D, et al. Risk estimation before progression to mild cognitive impairment and Alzheimer′s disease: an AD resemblance atrophy index[J]. Aging(Albany NY), 2019, 11(16):6217-6236. |
| [43] | Mai Y, Yu Q, Zhu F, et al. AD Resemblance atrophy index as a diagnostic biomarker for Alzheimer′s disease: a retrospective clinical and biological validation[J]. J Alzheimers Dis, 2021, 79(3):1023-1032. |
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