System and method for predicting vertebral artery dissection

A technique for vertebral artery dissection, applied in the field of systems and methods for predicting vertebral artery dissection

Pending Publication Date: 2022-02-25
TENCENT AMERICA LLC
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] However, these studies were conducted independently on different patient populations

Method used

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  • System and method for predicting vertebral artery dissection
  • System and method for predicting vertebral artery dissection
  • System and method for predicting vertebral artery dissection

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Embodiment Construction

[0017] Embodiments described herein allow multimodality based on imaging data collected from patients (e.g., time-of-flight Magnetic Resonance Imaging (MRI) and black blood Magnetic Resonance Angiography (MRA)) and clinical reports. state data to predict VAD. These embodiments quantify and collect two types of information: biomarkers from patient imaging data, such as vertebral artery geometry, cervical spine deformation, vessel wall stiffness; and information from clinical reports, such as patient age, smoking history and medication information. After quantifying these biomarkers, these embodiments can learn a deep learning model that maps the extracted biomarkers to risk probabilities that indicate the likelihood that a patient will experience VAD in the future.

[0018] Embodiments described herein may involve building a model to predict a patient's risk of experiencing VAD. To quantify biomarkers from images, vessel centerlines and vessel lumens can be extracted from the...

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Abstract

A method of determining a risk probability of vertebral artery dissection (VAD) in a patient, including receiving medical image information of the patient and clinical report information of the patient; extracting at least one biomarker corresponding to a vertebral artery segment included in the medical image information; extracting patient history information from the clinical report information; and determining the risk probability of VAD using a deep learning classification model based on the extracted at least one biomarker and the extracted patient history information.

Description

[0001] Cross References to Related Applications [0002] This application claims priority to US Application Serial No. 16 / 372,996, filed April 2, 2019, the disclosure of which is incorporated herein by reference in its entirety. Background technique [0003] Vertebral Artery Dissection (VAD) is considered to be one of the most common causes of transient ischemic attack and subarachnoid hemorrhage in patients aged 18 to 45 years. VAD is easily missed by clinicians because the associated symptoms are not specific. Therefore, predicting the development of VAD is of great significance for preventing patients from experiencing VAD and for clinicians to conduct accurate diagnosis and treatment. [0004] Many studies have been conducted to investigate different risk factors for VAD. For example, a study of the prevalence of fibromuscular dysplasia among patients with cervical artery dissection (both carotid and vertebral artery dissection) found that fibromuscular dysplasia was ass...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/02G06T7/11G16H50/70
CPCG16H30/40G16H50/30G06T7/0012G06T7/12G06T2207/10088G06T2207/20084G06T2207/30101G06T2207/30172A61B5/7275A61B5/7267A61B5/4872A61B5/02007A61B5/055G06N3/08G06N3/045G06N3/04G06T7/11G06T7/174G06T2207/20076G06T2207/20101G06T2207/20081
Inventor 唐晖杜楠涂旻王堃韩连漪范伟
Owner TENCENT AMERICA LLC
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