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.

项目摘要 颅内压增高（ICH）的识别在儿科神经外科和神经外科手术中至关重要。 评价如果不治疗，可能导致脑损伤，发育迟缓甚至死亡。目前，非- ICH的侵入性评估是基于与之相关性较差的临床症状和影像学 调查结果具有高度可变性和主观性。因此，ICH的非侵入性评价具有挑战性， 不确定此外，有创颅内压监测仪可以帮助识别ICH，但它们通常 避免使用，因为它们通常提供不确定的结果，并具有出血和感染的重要风险。 因此，ICH在人群中仍然诊断不足。在这个项目中，我们的目标是创造非侵入性的 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质减少 矿化，这可以从CT图像量化。这一假设得到了以下临床报告的支持： 血压升高或大脑生长受限的患者，显示颅骨较薄且密度较低，以及 低颅压患者出现颅骨异常增厚。 本课题的主要研究内容包括：（1）建立性别和年龄特异性的颅骨标准化统计模型 使用受试者的大型回顾性CT图像数据集， 无颅骨病理学;（2）量化ICH患者的骨骼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， 释放;和（3）进行试点研究，以确定和量化患者的局部压力升高的迹象， 由颅缝早闭引起的颅骨生长限制。在这个项目完成后，我们将有 建立了颅骨矿化的规范性参考文献，确定并量化了骨矿化 与ICH相关的变更，并创建了自动工具来识别这些变更。此外，如果我们的探索性研究 在颅缝早闭患者中成功，这将促使对这些患者中ICH的存在进行更大规模的临床研究。 患者可以通过及时的临床治疗来大幅改善他们的临床管理， 干预措施，特别是在年龄较大的儿童和复发患者。