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

基本信息

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
项目类别：
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

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

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项目摘要

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。