Melina Wirtz, Saif Salman, Yujia Wei, Vishal Patel, Rohan Sharma, Vikash Gupta, Qiangqiang Gu, Benoit Dherin, Sanjana Reddy, Rabih Tawk, Bradley J Erickson, William David Freeman
{"title":"SAHVAI-3D 和 4D:使用非对比度头部 CT 扫描的新型蛛网膜下腔出血容积自动人工智能(SAHVAI)测量方法","authors":"Melina Wirtz, Saif Salman, Yujia Wei, Vishal Patel, Rohan Sharma, Vikash Gupta, Qiangqiang Gu, Benoit Dherin, Sanjana Reddy, Rabih Tawk, Bradley J Erickson, William David Freeman","doi":"10.1101/2024.08.29.24312799","DOIUrl":null,"url":null,"abstract":"<strong>Objectives</strong> To automate subarachnoid hemorrhage volume (SAHV) calculation (<strong><em>SAHVAI-SAHV A</em></strong><em>rtificial</em> <strong><em>I</em></strong><em>ntelligence)</em> and create 3D volumetric images (SAHVAI-3D) using non-contrast head CT (NCCT) imaging data in aneurysmal subarachnoid hemorrhage (SAH) patients. We also defined SAHVAI-4D, representing SAHV over time. The aim was to compare automated SAHVAI volumes to manual SAHV methods and computation times, explore these imaging biomarkers’ potential in identifying at-risk brain regions for delayed cerebral ischemia (DCI), and explore potential insights in future neurotherapeutic interventions for SAH patient recovery.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"132 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SAHVAI-3D and 4D: A New, Automated Subarachnoid Hemorrhage Volumetric Artificial Intelligence (SAHVAI) Measurement Approach Using Non-Contrast Head CT Scans\",\"authors\":\"Melina Wirtz, Saif Salman, Yujia Wei, Vishal Patel, Rohan Sharma, Vikash Gupta, Qiangqiang Gu, Benoit Dherin, Sanjana Reddy, Rabih Tawk, Bradley J Erickson, William David Freeman\",\"doi\":\"10.1101/2024.08.29.24312799\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Objectives</strong> To automate subarachnoid hemorrhage volume (SAHV) calculation (<strong><em>SAHVAI-SAHV A</em></strong><em>rtificial</em> <strong><em>I</em></strong><em>ntelligence)</em> and create 3D volumetric images (SAHVAI-3D) using non-contrast head CT (NCCT) imaging data in aneurysmal subarachnoid hemorrhage (SAH) patients. We also defined SAHVAI-4D, representing SAHV over time. The aim was to compare automated SAHVAI volumes to manual SAHV methods and computation times, explore these imaging biomarkers’ potential in identifying at-risk brain regions for delayed cerebral ischemia (DCI), and explore potential insights in future neurotherapeutic interventions for SAH patient recovery.\",\"PeriodicalId\":501367,\"journal\":{\"name\":\"medRxiv - Neurology\",\"volume\":\"132 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Neurology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.08.29.24312799\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Neurology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.08.29.24312799","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SAHVAI-3D and 4D: A New, Automated Subarachnoid Hemorrhage Volumetric Artificial Intelligence (SAHVAI) Measurement Approach Using Non-Contrast Head CT Scans
Objectives To automate subarachnoid hemorrhage volume (SAHV) calculation (SAHVAI-SAHV ArtificialIntelligence) and create 3D volumetric images (SAHVAI-3D) using non-contrast head CT (NCCT) imaging data in aneurysmal subarachnoid hemorrhage (SAH) patients. We also defined SAHVAI-4D, representing SAHV over time. The aim was to compare automated SAHVAI volumes to manual SAHV methods and computation times, explore these imaging biomarkers’ potential in identifying at-risk brain regions for delayed cerebral ischemia (DCI), and explore potential insights in future neurotherapeutic interventions for SAH patient recovery.