Development of CT image-based cranial bone markers of intra-cranial hypertension

基于CT图像的颅内高压颅骨标志物的开发

• 批准号: 10590419
• 负责人: Antonio Reyes Porras Perez
• 金额: $ 21.17万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10590419
• 关键词: Affect; Age; Anatomy; Area; Birth; Bone Density; Bone Development; Bone Resorption; Brain; Brain Injuries; Calvaria; Cephalic; Cessation of life; Child; Childhood; Chronic; Clinical; Clinical Management; Clinical Research; Copper; Craniosynostosis; Data Set; Deposition; Development; Developmental Delay Disorders; Diagnosis; Early identification; Evaluation; Growth; Head; Headache; Hemorrhage; Hydrocephalus; Hypertension; Image; Image Analysis; Infection; Intervention; Intracranial Hypertension; Intracranial Hypotension; Intracranial Pressure; Intracranial Sinus Thrombosis; Lesion; Live Birth; Location; Magnetic Resonance Imaging; Measurement; Methods; Minerals; Modeling; Monitor; Neurologic; Normal Range; Operative Surgical Procedures; Parietal bone structure; Pathology; Patients; Pattern; Physiologic Ossification; Physiologic calcification; Pilot Projects; Population; Reporting; Reproducibility; Risk; Spinal Tap; Statistical Models; Surgical sutures; Symptoms; Thick; Thinness; Time; Training; Translating; Validation; Venous; Vomiting; X-Ray Computed Tomography; bone; cranium; density; imaging Segmentation; imaging biomarker; impression; improved; machine learning method; machine learning model; neurosurgery; pediatric patients; pressure; prevent; quantitative imaging; radiological imaging; relapse patients; repaired; sex; skull base; suture fusion; tool

Project summary The identification of intracranial hypertension (ICH) is essential during pediatric neurological and neurosurgical evaluation. If untreated, it may lead to brain injury, developmental delay or even death. However, current non- invasive evaluation of ICH is based on clinical symptoms that have poor correlation with it, and imaging findings are highly variable and subjective. Hence, non-invasive evaluation of ICH is challenging and often inconclusive. Additionally, invasive intracranial pressure monitors can help identify ICH but they are usually avoided because they often offer inconclusive results and carry important risks of hemorrhage and infections. Consequently, ICH remains underdiagnosed in the population. In this project, we aim to create non-invasive methods to automatically identify the presence of ICH in pediatric patients using CT images of the head. The main hypothesis of this project is that an elevated intracranial pressure results into a decrease of bone mineralization, which can be quantified from CT images. This hypothesis is supported by clinical reports of patients with elevated pressure or brain growth constraints showing thinner and less dense cranial bones, and of patient with intracranial hypotension presenting an abnormally thick cranial bone. During this project, we will: (1) create a sex- and age-specific normative statistical model of cranial bone thickness and density between birth and 10 years using a large retrospective CT image dataset of subjects without cranial pathology; (2) quantify bone abnormalities in patients with ICH and create machine learning models to identify them using a retrospective dataset of patients who required surgical treatment for pressure release; and (3) perform a pilot study to identify and quantify local signs of elevated pressure in patients with cranial growth constraints caused by craniosynostosis. Upon completion of this project, we will have established normative references of cranial bone mineralization, identified and quantified bone mineralization changes associated with ICH, and created automatic tools to identify them. In addition, if our exploratory study in patients with craniosynostosis succeeds, it will prompt a larger clinical study of the presence of ICH in these patients that could translate in a substantial improvement of their clinical management through timely interventions, especially in older children and relapsing patients.

项目概要 颅内高压 (ICH) 的识别在儿科神经内科和神经外科手术中至关重要 评估。如果不及时治疗，可能会导致脑损伤、发育迟缓甚至死亡。然而，目前非 ICH的侵入性评估基于与其相关性较差的临床症状，而影像学检查 研究结果变化很大且主观。因此，ICH 的非侵入性评估具有挑战性，而且常常 尚无定论。此外，侵入性颅内压监测仪可以帮助识别脑出血，但它们通常 避免这样做是因为它们通常会提供不确定的结果，并带来出血和感染的重大风险。 因此，人群中的 ICH 仍然未被充分诊断。在这个项目中，我们的目标是创建非侵入性的 使用头部 CT 图像自动识别儿科患者是否存在 ICH 的方法。 该项目的主要假设是颅内压升高导致骨量减少 矿化作用，可以通过 CT 图像进行量化。这一假设得到了临床报告的支持 压力升高或大脑生长受限的患者颅骨较薄且密度较低，并且 颅内低血压患者的颅骨异常厚。 在这个项目中，我们将：（1）创建一个性别和年龄特定的颅骨规范统计模型 使用受试者的大型回顾性 CT 图像数据集计算出生至 10 年间的厚度和密度 无颅脑病变； (2) 量化 ICH 患者的骨异常并创建机器学习 使用需要手术治疗压力的患者的回顾性数据集来识别它们的模型 发布; (3) 进行一项试点研究，以识别和量化患有以下疾病的患者的局部压力升高迹象： 颅缝早闭引起的颅骨生长受限。该项目完成后，我们将拥有 建立颅骨矿化的规范参考，识别和量化骨矿化 与 ICH 相关的变化，并创建了自动工具来识别它们。此外，如果我们的探索性研究 在颅缝早闭患者中取得成功，将促使对这些患者中是否存在 ICH 进行更大规模的临床研究 通过及时的治疗可以显着改善患者的临床管理 干预措施，特别是针对年龄较大的儿童和复发患者。