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International Journal of Computer Assisted Radiology and Surgery

Erschienen in:

01.07.2014 | Original Article

Fully automatic model-based calcium segmentation and scoring in coronary CT angiography

verfasst von: Dov Eilot, Roman Goldenberg

Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 4/2014

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Abstract

Purpose

The paper presents new methods for automatic coronary calcium detection, segmentation and scoring in coronary CT angiography (cCTA) studies.

Methods

Calcium detection and segmentation are performed by modeling image intensity profiles of coronary arteries. The scoring algorithm is based on a simulated unenhanced calcium score (CS) CT image, constructed by virtually removing the contrast media from cCTA. The methods are implemented as part of a fully automatic system for CS assessment from cCTA.

Results

The system was tested in two independent clinical trials on 263 studies and demonstrated 0.95/0.91 correlation between the CS computed from cCTA and the standard Agatston score derived from unenhanced CS CT. The mean absolute percent difference (MAPD) of 36/39 % between the two scores lies within the error range of the standard CS CT (15–65 %).

Conclusions

High diagnostic performance, combined with the benefits of the fully automatic solution, suggests that the proposed technique can be used to eliminate the need in a separate CS CT scan as part of the cCTA examination, thus reducing the radiation exposure and simplifying the procedure.

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The described method for calcium segmentation is patent pending.

The described method for calcium scoring is patent pending.

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Titel: Fully automatic model-based calcium segmentation and scoring in coronary CT angiography
verfasst von: Dov Eilot
Roman Goldenberg
Publikationsdatum: 01.07.2014
Verlag: Springer Berlin Heidelberg
Erschienen in: International Journal of Computer Assisted Radiology and Surgery / Ausgabe 4/2014
Print ISSN: 1861-6410
Elektronische ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-013-0955-y

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Abstract

Purpose

Methods

Results

Conclusions

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