Unbiased longitudinal neuromorphometry for clinical decision support

用于临床决策支持的无偏纵向神经形态测量

• 批准号: 10223528
• 负责人: Douglas N Greve
• 金额: $ 73.34万
• 依托单位: CORTICOMETRICS, LLC
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10223528
• 关键词: Age; Alzheimer' s Disease; Brain; Cell Nucleus; Clinical; Code; Computer software; Data; Disease Progression; Docking; Environment; Feasibility Studies; Future; Goals; Hippocampus (Brain); Human; Huntington Disease; Imaging Device; Individual; Infrastructure; Longitudinal Studies; Magnetic Resonance Imaging; Methods; Monitor; Multiple Sclerosis; Neuroanatomy; Neurologic; Neurology; Nuclear; Pain; Phase; Preparation; Radiology Specialty; Reading; Reporting; Resolution; Risk; Scanning; Schizophrenia; Semantics; Slice; Stream; Structure; System; Testing; Time; Translating; Validation; clinical decision support; design; image processing; improved; longitudinal analysis; migration; neuroimaging; quantitative imaging; radiologist; software development; tool; usability; verification and validation

Project Summary Normal human neuroanatomy is incredibly variable, and increases with age. This impedes the ability of neuroimaging to detect effects in neurological conditions such as Alzheimer's disease (AD), Huntington's disease (HD), multiple sclerosis (MS) and schizophrenia. Most of the recently available state-of-the-art quantitative imaging tools still use cross-sectional methods to analyze repeated scans. These tools lack the sensitivity to monitor subtle progressive changes because such approaches do not account for the large intrinsic variability of normal neuroanatomy. The goal of this project is to commercialize a longitudinal, neuro-morphometric image processing pipeline for use in radiology, neurology and related clinical fields. The successful completion of this project will result in a clinically useful neuro-morphometric longitudinal analysis stream with more statistical power than is currently available commercially. This increase in power will directly translate into an enhanced ability to detect and assess progression at both the individual and group levels. It will also alleviate a major pain point in current longitudinal neuroradiology reading workflows, reducing radiology report turnaround times (RTAT).

项目摘要 正常的人类神经解剖学是令人难以置信的变化，并随着年龄的增长而增加。这阻碍了 神经成像检测神经系统疾病（如阿尔茨海默病）影响的能力 (AD)、亨廷顿病（HD）、多发性硬化（MS）和精神分裂症。大多数最近 现有的最先进的定量成像工具仍然使用横截面方法来分析 重复扫描。这些工具缺乏监测细微渐进变化的灵敏度， 这种方法不能解释正常神经解剖学的大的内在可变性。的 这个项目的目标是商业化的纵向，神经形态图像处理 用于放射学、神经病学和相关临床领域的管道。圆满完成 该项目将产生临床上有用的神经形态测量纵向分析流， 比目前商业上可用的更大的统计能力。这种力量的增强将 直接转化为检测和评估个体进展的增强能力， 组水平。它也将缓解当前纵向神经放射学的一个主要痛点 阅读工作流程，减少放射学报告周转时间（RTAT）。