Literature DB >> 25554696

Three-dimensional quantification and visualization of aortic calcification by multidetector-row computed tomography: a simple approach using a volume-rendering method.

Shumpei Mori1, Tomofumi Takaya2, Mitsuo Kinugasa2, Tatsuro Ito2, Sachiko Takamine2, Sei Fujiwara2, Tatsuya Nishii3, Atsushi K Kono3, Takeshi Inoue4, Seimi Satomi-Kobayashi2, Yoshiyuki Rikitake5, Yutaka Okita4, Ken-ichi Hirata2.   

Abstract

OBJECTIVE: Three-dimensional (3-D) visualization and quantification of vascular calcification (VC) are important to accelerate the multidisciplinary investigation of VC. Agatston scoring is the standard approach for evaluating coronary artery calcification. However, regarding aortic calcification (AC), quantification methods appear to vary among studies. The aim of this study was to introduce a simple technique of simultaneous quantification and 3-D visualization of AC and provide validation data.
METHODS: The main study comprised of 126 patients who underwent the thoracoabdominal plain computed tomography scan as preoperative general evaluation. AC was quantified using a volume-rendering (VR) method (VR AC volume) by extracting the volume with a density ≥130 HU within the total aorta. The concordance and reproducibility of the VR AC volume were validated in comparison with the conventional slice-by-slice voxel-based AC quantification (volumetric AC score) using the Agatston scoring software.
RESULTS: Excellent concordance between the VR AC volume and volumetric AC score was confirmed (Spearman correlation coefficient = 0.9997, mean difference = -0.05 ± 0.23 mL, p <0.0001). Excellent intraobserver and interobserver reliabilities were demonstrated using the Bland-Altman analysis as the mean intraobserver difference was 0.00 mL (p = 0.9863) and the mean interobserver difference was -0.01 mL (p = 0.6612).
CONCLUSION: The VR method was validated to be feasible. This simple approach could overcome the limitation of the current method based on slice-by-slice pixel or voxel summation, which lacks 3-D visual information. Accordingly, this approach would be promising for accelerating the investigation of VC.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Agatston score; Aortic calcification; Multidetector-row computed tomography; Vascular calcification; Volume-rendering method

Mesh:

Year:  2014        PMID: 25554696     DOI: 10.1016/j.atherosclerosis.2014.12.041

Source DB:  PubMed          Journal:  Atherosclerosis        ISSN: 0021-9150            Impact factor:   5.162


  4 in total

1.  Relationship between ectopic calcifications and bone fragility depicted on computed tomography scan in 70 patients with systemic sclerosis.

Authors:  Marine Fauny; Elodie Bauer; Edem Allado; Eliane Albuisson; Joëlle Deibener; François Chabot; Damien Mandry; Olivier Huttin; Isabelle Chary-Valckenaere; Damien Loeuille
Journal:  J Scleroderma Relat Disord       Date:  2022-06-28

Review 2.  Anatomical References to Evaluate Thoracic Aorta Calcium by Computed Tomography.

Authors:  Jesiana Ferreira Pedrosa; Sandhi Maria Barreto; Márcio Sommer Bittencourt; Antonio Luiz Pinho Ribeiro
Journal:  Curr Atheroscler Rep       Date:  2019-11-20       Impact factor: 5.113

3.  Detection of left ventricular wall motion abnormalities from volume rendering of 4DCT cardiac angiograms using deep learning.

Authors:  Zhennong Chen; Francisco Contijoch; Gabrielle M Colvert; Ashish Manohar; Andrew M Kahn; Hari K Narayan; Elliot McVeigh
Journal:  Front Cardiovasc Med       Date:  2022-07-28

4.  Abdominal aorta calcification predicts cardiovascular but not non-cardiovascular outcome in patients receiving peritoneal dialysis: A prospective cohort study.

Authors:  Cheng-Hsuan Tsai; Lian-Yu Lin; Yen-Hung Lin; I-Jung Tsai; Jenq-Wen Huang
Journal:  Medicine (Baltimore)       Date:  2020-09-11       Impact factor: 1.817

  4 in total

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