Antti J Luikku, Ossi Nerg, Anne M Koivisto, Tuomo Hänninen, Antti Junkkari, Susanna Kemppainen, Sini-Pauliina Juopperi, Rosa Sinisalo, Alli Pesola, Hilkka Soininen, Mikko Hiltunen, Ville Leinonen, Tuomas Rauramaa, Henna Martiskainen
{"title":"深度学习辅助定量分析特发性正常压力脑积水患者的 Aβ 和小胶质细胞与认知结果的关系。","authors":"Antti J Luikku, Ossi Nerg, Anne M Koivisto, Tuomo Hänninen, Antti Junkkari, Susanna Kemppainen, Sini-Pauliina Juopperi, Rosa Sinisalo, Alli Pesola, Hilkka Soininen, Mikko Hiltunen, Ville Leinonen, Tuomas Rauramaa, Henna Martiskainen","doi":"10.1093/jnen/nlae083","DOIUrl":null,"url":null,"abstract":"<p><p>Neuropathologic changes of Alzheimer disease (AD) including Aβ accumulation and neuroinflammation are frequently observed in the cerebral cortex of patients with idiopathic normal pressure hydrocephalus (iNPH). We created an automated analysis platform to quantify Aβ load and reactive microglia in the vicinity of Aβ plaques and to evaluate their association with cognitive outcome in cortical biopsies of patients with iNPH obtained at the time of shunting. Aiforia Create deep learning software was used on whole slide images of Iba1/4G8 double immunostained frontal cortical biopsies of 120 shunted iNPH patients to identify Iba1-positive microglia somas and Aβ areas, respectively. Dementia, AD clinical syndrome (ACS), and Clinical Dementia Rating Global score (CDR-GS) were evaluated retrospectively after a median follow-up of 4.4 years. Deep learning artificial intelligence yielded excellent (>95%) precision for tissue, Aβ, and microglia somas. Using an age-adjusted model, higher Aβ coverage predicted the development of dementia, the diagnosis of ACS, and more severe memory impairment by CDR-GS whereas measured microglial densities and Aβ-related microglia did not correlate with cognitive outcome in these patients. Therefore, cognitive outcome seems to be hampered by higher Aβ coverage in cortical biopsies in shunted iNPH patients but is not correlated with densities of surrounding microglia.</p>","PeriodicalId":16682,"journal":{"name":"Journal of Neuropathology and Experimental Neurology","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deep learning assisted quantitative analysis of Aβ and microglia in patients with idiopathic normal pressure hydrocephalus in relation to cognitive outcome.\",\"authors\":\"Antti J Luikku, Ossi Nerg, Anne M Koivisto, Tuomo Hänninen, Antti Junkkari, Susanna Kemppainen, Sini-Pauliina Juopperi, Rosa Sinisalo, Alli Pesola, Hilkka Soininen, Mikko Hiltunen, Ville Leinonen, Tuomas Rauramaa, Henna Martiskainen\",\"doi\":\"10.1093/jnen/nlae083\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Neuropathologic changes of Alzheimer disease (AD) including Aβ accumulation and neuroinflammation are frequently observed in the cerebral cortex of patients with idiopathic normal pressure hydrocephalus (iNPH). We created an automated analysis platform to quantify Aβ load and reactive microglia in the vicinity of Aβ plaques and to evaluate their association with cognitive outcome in cortical biopsies of patients with iNPH obtained at the time of shunting. Aiforia Create deep learning software was used on whole slide images of Iba1/4G8 double immunostained frontal cortical biopsies of 120 shunted iNPH patients to identify Iba1-positive microglia somas and Aβ areas, respectively. Dementia, AD clinical syndrome (ACS), and Clinical Dementia Rating Global score (CDR-GS) were evaluated retrospectively after a median follow-up of 4.4 years. Deep learning artificial intelligence yielded excellent (>95%) precision for tissue, Aβ, and microglia somas. Using an age-adjusted model, higher Aβ coverage predicted the development of dementia, the diagnosis of ACS, and more severe memory impairment by CDR-GS whereas measured microglial densities and Aβ-related microglia did not correlate with cognitive outcome in these patients. Therefore, cognitive outcome seems to be hampered by higher Aβ coverage in cortical biopsies in shunted iNPH patients but is not correlated with densities of surrounding microglia.</p>\",\"PeriodicalId\":16682,\"journal\":{\"name\":\"Journal of Neuropathology and Experimental Neurology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Neuropathology and Experimental Neurology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/jnen/nlae083\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Neuropathology and Experimental Neurology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/jnen/nlae083","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Deep learning assisted quantitative analysis of Aβ and microglia in patients with idiopathic normal pressure hydrocephalus in relation to cognitive outcome.
Neuropathologic changes of Alzheimer disease (AD) including Aβ accumulation and neuroinflammation are frequently observed in the cerebral cortex of patients with idiopathic normal pressure hydrocephalus (iNPH). We created an automated analysis platform to quantify Aβ load and reactive microglia in the vicinity of Aβ plaques and to evaluate their association with cognitive outcome in cortical biopsies of patients with iNPH obtained at the time of shunting. Aiforia Create deep learning software was used on whole slide images of Iba1/4G8 double immunostained frontal cortical biopsies of 120 shunted iNPH patients to identify Iba1-positive microglia somas and Aβ areas, respectively. Dementia, AD clinical syndrome (ACS), and Clinical Dementia Rating Global score (CDR-GS) were evaluated retrospectively after a median follow-up of 4.4 years. Deep learning artificial intelligence yielded excellent (>95%) precision for tissue, Aβ, and microglia somas. Using an age-adjusted model, higher Aβ coverage predicted the development of dementia, the diagnosis of ACS, and more severe memory impairment by CDR-GS whereas measured microglial densities and Aβ-related microglia did not correlate with cognitive outcome in these patients. Therefore, cognitive outcome seems to be hampered by higher Aβ coverage in cortical biopsies in shunted iNPH patients but is not correlated with densities of surrounding microglia.
期刊介绍:
Journal of Neuropathology & Experimental Neurology is the official journal of the American Association of Neuropathologists, Inc. (AANP). The journal publishes peer-reviewed studies on neuropathology and experimental neuroscience, book reviews, letters, and Association news, covering a broad spectrum of fields in basic neuroscience with an emphasis on human neurological diseases. It is written by and for neuropathologists, neurologists, neurosurgeons, pathologists, psychiatrists, and basic neuroscientists from around the world. Publication has been continuous since 1942.