Arnold D Gomez, Andrew K Knutsen, Dzung L Pham, Philip V Bayly, Jerry L Prince
{"title":"基于mri的脑碰撞生物力学运动估计的定量验证。","authors":"Arnold D Gomez, Andrew K Knutsen, Dzung L Pham, Philip V Bayly, Jerry L Prince","doi":"10.1007/978-3-030-15923-8_5","DOIUrl":null,"url":null,"abstract":"<p><p>Head impact can cause traumatic brain injury (TBI) through axonal overstretch or subsequent inflammation and understanding the biomechanics of the impact event is useful for TBI prevention research. Tagged magnetic resonance imaging (MRI) acquired during a mild-acceleration impact has enabled measurement and visualization of brain deformation in vivo. However, measurements using MRI are subject to error, and having independent validation while imaging in vivo is very difficult. Thus, characterizing the accuracy of these measurements needs to be done in a separate experiment using a phantom where a gold standard is available. This study describes a method for error quantification using a calibration phantom compatible with MRI and high-speed video (the gold standard). During linear acceleration, the maximum shear strain (MSS) in the phantom ranged from 0 to 12%, which is similar to in vivo brain deformation at a similar acceleration. The mean displacement error against video was 0.3±0.3 mm, and the MSS error was 1.4±0.3%. To match resolutions, video data was filtered temporally using an averaging filter. Compared to the unfiltered results, resolution matching improved the agreement between MRI and video results by 15%. In conclusion, tagged MRI analysis compares well to video data provided that resolutions are matched-a finding that is also applicable when using MRI to validate simulations.</p>","PeriodicalId":72659,"journal":{"name":"Computational biomechanics for medicine. Personalisation, validation and therapy","volume":"2020 ","pages":"61-71"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/978-3-030-15923-8_5","citationCount":"1","resultStr":"{\"title\":\"Quantitative Validation of MRI-Based Motion Estimation for Brain Impact Biomechanics.\",\"authors\":\"Arnold D Gomez, Andrew K Knutsen, Dzung L Pham, Philip V Bayly, Jerry L Prince\",\"doi\":\"10.1007/978-3-030-15923-8_5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Head impact can cause traumatic brain injury (TBI) through axonal overstretch or subsequent inflammation and understanding the biomechanics of the impact event is useful for TBI prevention research. Tagged magnetic resonance imaging (MRI) acquired during a mild-acceleration impact has enabled measurement and visualization of brain deformation in vivo. However, measurements using MRI are subject to error, and having independent validation while imaging in vivo is very difficult. Thus, characterizing the accuracy of these measurements needs to be done in a separate experiment using a phantom where a gold standard is available. This study describes a method for error quantification using a calibration phantom compatible with MRI and high-speed video (the gold standard). During linear acceleration, the maximum shear strain (MSS) in the phantom ranged from 0 to 12%, which is similar to in vivo brain deformation at a similar acceleration. The mean displacement error against video was 0.3±0.3 mm, and the MSS error was 1.4±0.3%. To match resolutions, video data was filtered temporally using an averaging filter. Compared to the unfiltered results, resolution matching improved the agreement between MRI and video results by 15%. In conclusion, tagged MRI analysis compares well to video data provided that resolutions are matched-a finding that is also applicable when using MRI to validate simulations.</p>\",\"PeriodicalId\":72659,\"journal\":{\"name\":\"Computational biomechanics for medicine. Personalisation, validation and therapy\",\"volume\":\"2020 \",\"pages\":\"61-71\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1007/978-3-030-15923-8_5\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational biomechanics for medicine. Personalisation, validation and therapy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/978-3-030-15923-8_5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational biomechanics for medicine. Personalisation, validation and therapy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/978-3-030-15923-8_5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
头部撞击可通过轴突过度拉伸或随后的炎症引起创伤性脑损伤,了解撞击事件的生物力学对创伤性脑损伤的预防研究有重要意义。在轻度加速撞击期间获得的标记磁共振成像(MRI)使体内脑变形的测量和可视化成为可能。然而,使用MRI进行测量是有误差的,并且在体内成像时进行独立验证是非常困难的。因此,表征这些测量的准确性需要在一个单独的实验中完成,使用一个可用的金标准。本研究描述了一种使用与MRI和高速视频(金标准)兼容的校准幻影进行误差量化的方法。在线性加速过程中,脑幻影的最大剪切应变(MSS)范围为0 ~ 12%,与类似加速度下的活体脑变形相似。对视频的平均位移误差为0.3±0.3 mm, MSS误差为1.4±0.3%。为了匹配分辨率,使用平均滤波器对视频数据进行临时过滤。与未过滤的结果相比,分辨率匹配使MRI和视频结果之间的一致性提高了15%。总之,在分辨率匹配的情况下,标记MRI分析与视频数据相比效果更好,这一发现也适用于使用MRI验证模拟。
Quantitative Validation of MRI-Based Motion Estimation for Brain Impact Biomechanics.
Head impact can cause traumatic brain injury (TBI) through axonal overstretch or subsequent inflammation and understanding the biomechanics of the impact event is useful for TBI prevention research. Tagged magnetic resonance imaging (MRI) acquired during a mild-acceleration impact has enabled measurement and visualization of brain deformation in vivo. However, measurements using MRI are subject to error, and having independent validation while imaging in vivo is very difficult. Thus, characterizing the accuracy of these measurements needs to be done in a separate experiment using a phantom where a gold standard is available. This study describes a method for error quantification using a calibration phantom compatible with MRI and high-speed video (the gold standard). During linear acceleration, the maximum shear strain (MSS) in the phantom ranged from 0 to 12%, which is similar to in vivo brain deformation at a similar acceleration. The mean displacement error against video was 0.3±0.3 mm, and the MSS error was 1.4±0.3%. To match resolutions, video data was filtered temporally using an averaging filter. Compared to the unfiltered results, resolution matching improved the agreement between MRI and video results by 15%. In conclusion, tagged MRI analysis compares well to video data provided that resolutions are matched-a finding that is also applicable when using MRI to validate simulations.