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 颅内高血压（ICH）的鉴定在小儿神经系统和神经外科医学期间至关重要 评估。如果未经治疗，它可能会导致脑损伤，发育延迟甚至死亡。但是，当前的非 - ICH的侵入性评估是基于与之相关的临床症状，成像 发现是高度可变和主观的。因此，对ICH的非侵入性评估是具有挑战性的，并且经常 尚无定论。此外，侵入性颅内压监测器可以帮助识别ICH，但通常是 之所以避免，是因为它们经常提供不确定的结果并承担出血和感染的重要风险。 因此，ICH在人群中仍未诊断。在这个项目中，我们旨在创造非侵入性 使用头部CT图像自动鉴定小儿患者中ICH存在的方法。 该项目的主要假设是颅内压升高导致骨骼减少 矿化，可以从CT图像中量化。该假设得到了关于 压力升高或脑生长限制的患者表现出较薄且密度较小的颅骨，并且 颅内低血压患者的颅骨异常厚。 在此项目中，我们将：（1）创建一个性别和年龄特定的颅骨统计统计模型 使用大型回顾性CT图像数据集，出生到10年之间的厚度和密度 没有颅病； （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 发布; （3）进行试验研究，以识别和量化患者的局部压力升高迹象 由颅突式症引起的颅生长限制。该项目完成后，我们将拥有 确定和定量骨矿化的颅骨矿化的规范性参考 更改与ICH相关的更改，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 在患有颅突的患者中，它将促使对ICH的存在进行更大的临床研究 可以通过及时转化其临床管理的患者 干预措施，尤其是在年龄较大的儿童和复发的患者中。