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Related Concept Videos

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...

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Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
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Published on: August 28, 2018

Recognizable phenotypes associated with intracranial calcification.

John H Livingston1, Stavros Stivaros, Marjo S van der Knaap

  • 1Department of Paediatric Neurology, Leeds General Infirmary, Leeds, UK. jh.livingston@leedsth.nhs.uk

Developmental Medicine and Child Neurology
|November 6, 2012
PubMed
Summary
This summary is machine-generated.

A systematic radiological phenotyping approach aids in diagnosing intracranial calcification disorders. This method helps identify characteristic patterns for known conditions and discover new ones.

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Area of Science:

  • Neurology
  • Radiology
  • Genetics

Background:

  • Intracranial calcification is a radiological finding associated with various genetic and acquired disorders.
  • Accurate diagnosis relies on integrating clinical, radiological, and molecular data.
  • A systematic radiological approach can improve diagnostic accuracy and identify novel disease patterns.

Purpose of the Study:

  • To establish a systematic radiological phenotyping method for intracranial calcification disorders.
  • To determine if distinct radiological patterns can aid in diagnosing known conditions.
  • To facilitate the identification of new disorders associated with intracranial calcification.

Main Methods:

  • Development of a cranial imaging-based scoring system using CT and MRI data.
  • Grouping patients into categories with known molecular diagnoses or suspected diagnoses based on clinical and radiological features.
  • Subgrouping patients with unknown etiology based on shared radiological features.

Main Results:

  • Analysis of 244 scans from 119 patients.
  • Specific diagnoses identified in 59 patients, including Aicardi-Goutières syndrome, cerebroretinal microangiopathy with calcification and cysts, and COL4A1-related disease.
  • Subsets with shared characteristics suggestive of specific calcification phenotypes identified in 60 patients with unknown etiology.

Conclusions:

  • A systematic radiological phenotyping approach is valuable for disorders involving intracranial calcification.
  • This methodology aids in the diagnosis of known conditions and the potential discovery of new disorders.
  • Radiological pattern recognition is crucial for advancing the understanding and diagnosis of these complex conditions.