Human-centered CT-based CADx Tools for Traumatic Torso Hemorrhage

以人为中心、基于 CT 的 CADx 工具，用于治疗躯干外伤出血

基本信息

批准号：
10566836
负责人：
David Dreizin
金额：
$ 37.64万
依托单位：
UNIVERSITY OF MARYLAND BALTIMORE
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-01 至 2027-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10566836
关键词：
Abdomen Acceleration Acidosis Admission activity Affect Age Algorithms American Angiography Artificial Intelligence Behavior Big Data Blood Blood Coagulation Disorders Blood Pressure Body Regions Cessation of life Chest Classification Clinical Collaborations Computer-Assisted Diagnosis Consumption Data Data Set Databases Decision Making Decision Support Systems Delphi Study Detection Development Diagnosis Diagnostic Errors Early Intervention Engineering Ensure Expert Opinion Extravasation Failure Fatigue Feedback Future Goals Heart Rate Hematoma Hemorrhage Hemostatic Agents Hemothorax Hour Human Image Image Analysis Injury Intervention Knowledge Label Laceration Life Liquid substance Measurement Medical Imaging Modality Monitor Multi-Institutional Clinical Trial Operative Surgical Procedures Organ Outcome Patient Triage Patients Pelvis Performance Peritoneal Physiological Pleural Population Population Heterogeneity Prevalence Process Protocols documentation Provider Radiology Specialty Reader Reading Recommendation Reporting Research Resources Rest Resuscitation Risk Safety Sampling Screening procedure Severities Shock Software Design Solid Source Speed Standardization System Task Performances Testing Time Transfusion Trauma Trust United States Validation Visualization Work algorithm development body system classification algorithm clinical decision-making clinically actionable clinically relevant cohort computer aided detection computer center design diagnostic tool disorder risk distraction hemodynamics human centered design human-in-the-loop image processing improved indexing large datasets mortality natural hypothermia novel organ injury pelvis fracture personalized decision personalized diagnostics point of care predict clinical outcome preference prevent preventable death rapid detection resilience screening tool trauma care trauma centers

项目摘要

Trauma is responsible for 180,000 deaths annually in the United States and accounts for 59% of deaths in the population younger than 45 years. 86% of preventable deaths are related to sequalae of massive torso hemorrhage. Rapid precision diagnostic tools are needed to triage patients for early activation of massive transfusion protocols and urgent surgical or angiographic hemostatic intervention to circumvent the vicious cycle of acidosis, coagulopathy, hypothermia, and death resulting from exsanguination. Whole-body CT angiography (WBCTA) is the workhorse screening and surgical planning modality for torso hemorrhage. Lethal but preventable hemorrhage typically arises from pelvic fractures and solid organ lacerations, manifesting on WBCTA as foci of contrast extravasation and pooled cavitary hemorrhage (e.g., pelvic hematoma, hemothorax, or hemoperitoneum). Rapid assessment of WBCTA can result in earlier intervention, with associated survival benefit, but reader fatigue, study volume, reading room distractions, and injuries involving multiple body regions remain sources of diagnostic error and interpretation delays. Assessment of organ injury severity, pelvic fracture severity, and overall hemorrhage burden remains reader dependent and subjective. Clinical tools including the Shock Index have many confounders that impede forecasting of actionable hemorrhage- related outcomes. Automated WBCTA computer aided diagnosis (CADx) tools that detect bleeding pelvic fractures and organ lacerations, classify severity grade, and deliver precise voxelwise volumetric measurements of multicavitary hemorrhage burden will greatly accelerate and standardize image analysis, reduce turnaround time for reporting of critical results, improve the accuracy and objectivity of clinical decision making, and ultimately reduce time to life-saving hemorrhage control interventions. To capitalize on the benefits of automated point-of-care CT-based CADx tools in the fast-paced, and safety critical trauma care setting, such tools must be rapid, accurate, generalizable, and elicit a high level of end-user trust. To minimize bias, ensure clinical utility, and maximize robustness for turn-key deployment in future multicenter clinical trials, the tools must scale to large diverse populations, and achieve human factors engineering goals established through expert target user input. Our team will bring to bear combined technical and clinical expertise in trauma radiology, medical image processing, and human-centered software design to create an orchestrated suite of rapid, accurate, clinically relevant, and user-centered CADx tools for torso hemorrhage. In Aim 1, we will curate and annotate a uniquely large dataset of consecutively selected admission trauma WBCTAs. In Aim 2, we will use this big data approach and human-centered design principles to develop a suite of interactive high-trust CADx tools. In Aim 3, we will assess generalizability with a large out-of-sample dataset and assess user acceptance with simulated deployment. The work will result in rapid, robust, and human-centered CADx tools for detection, precision diagnostics, and personalized decision support for hemorrhage-control interventions.

创伤每年在美国造成180,000人死亡，占死亡人数的59％年龄在45岁以下的人口。 86％的可预防死亡与巨大躯干的序列有关出血。需要快速的精度诊断工具来分类患者以早期激活大规模激活输血方案以及紧急手术或血管造影止血干预措施，以规避恶性酸中毒，凝血病，体温过低和死亡的循环。全身CT 血管造影（WBCTA）是躯干出血的主力筛查和手术计划方式。致命但是可预防的出血通常是由骨盆裂缝和固体器官撕裂引起的 WBCTA作为对比度外部和合并的空穴出血的灶或hemoperitoneum）。对WBCTA的快速评估可能会导致较早的干预，并与之相关的生存受益，但读者疲劳，学习量，阅读室的分心以及涉及多个身体的伤害区域仍然是诊断错误和解释延迟的来源。评估器官损伤严重程度，骨盆骨折的严重程度和总体出血负担仍然是读者依赖和主观的。临床包括冲击指数在内的工具具有许多混杂因素，这些混杂因素会预测可行的出血 - 相关结果。自动化WBCTA计算机辅助诊断（CADX）工具，可检测出血骨盆裂缝和器官撕裂，对严重程度分类并提供精确的紫og弹体积多腔出血负担的测量将极大地加速和标准化图像分析，减少报告关键结果的周转时间，提高临床决策的准确性和客观性制作并最终减少挽救生命的出血控制干预措施的时间。利用快速节奏和安全性创伤护理中自动化点的基于CT的CT工具的好处设置，这样的工具必须快速，准确，可推广并引起高水平的最终用户信任。最小化在未来的多中心临床试验中，偏见，确保临床实用性并最大程度地提高旋转键部部署的鲁棒性，工具必须扩展到大量种群，并实现建立的人为因素工程目标通过专家目标用户输入。我们的团队将带来创伤的综合技术和临床专业知识放射学，医学图像处理和以人为本的软件设计，以创建精心策划的套件快速，准确，临床相关且以用户为中心的CADX工具用于躯干出血。在AIM 1中，我们将策划并注释一个独特的大型数据集，该数据集是连续选择的入院创伤WBCTA的。在AIM 2中，我们将使用这种大数据方法和以人为本的设计原理来开发一套交互式高信任 CADX工具。在AIM 3中，我们将使用大型的样本外数据集评估可推广性并评估用户通过模拟部署接受。这项工作将导致快速，健壮和以人为本的CADX工具用于检测，精确诊断和为出血控制干预的个性化决策支持。