Hybrid Iterative Reconstruction Algorithm Improves Image Quality in Craniocervical CT Angiography.
(2013) In American Journal of Roentgenology: diagnostic imaging and related sciences 201(6). p.861-866- Abstract
- OBJECTIVE. The purpose of this study was to evaluate the potential of a hybrid iterative reconstruction algorithm for improving image quality in craniocervical CT angiography (CTA) and to assess observer performance. SUBJECTS AND METHODS. Thirty patients (mean age, 58 years; range 16-80 years) underwent standard craniocervical CTA (volume CT dose index, 6.8 mGy, 2.8 mSv). Images were reconstructed using both filtered back projection (FBP) and a hybrid iterative reconstruction algorithm. Five neuroradiologists assessed general image quality and delineation of the vessel lumen in seven arterial segments using a 4-grade scale. Interobserver and intraobserver variability were determined. Mean attenuation and noise were measured and... (More)
- OBJECTIVE. The purpose of this study was to evaluate the potential of a hybrid iterative reconstruction algorithm for improving image quality in craniocervical CT angiography (CTA) and to assess observer performance. SUBJECTS AND METHODS. Thirty patients (mean age, 58 years; range 16-80 years) underwent standard craniocervical CTA (volume CT dose index, 6.8 mGy, 2.8 mSv). Images were reconstructed using both filtered back projection (FBP) and a hybrid iterative reconstruction algorithm. Five neuroradiologists assessed general image quality and delineation of the vessel lumen in seven arterial segments using a 4-grade scale. Interobserver and intraobserver variability were determined. Mean attenuation and noise were measured and signal-to-noise and contrast-to-noise ratios calculated. Descriptive statistics are presented and data analyzed using linear mixed-effects models. RESULTS. In pooled data, image quality in iterative reconstruction was graded superior to FBP regarding all five quality criteria (p < 0.0001), with the greatest improvement observed in the vertebral arteries. Iterative reconstruction resulted in elimination of arterial segments graded poor. Interobserver percentage agreement was significantly better (p = 0.024) for iterative reconstruction (69%) than for FBP (66%) but worse than intraobserver percentage agreement (mean, 79%). Noise levels, signal-to-noise ratio, and contrast-to-noise ratio were significantly (p < 0.001) improved in iterative reconstruction at all measured levels. CONCLUSION. The iterative reconstruction algorithm significantly improves image quality in craniocervical CT, especially at the thoracic inlet. Despite careful study design, considerable interobserver and intraobserver variability was noted. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4179026
- author
- Löve, Askell LU ; Siemund, Roger LU ; Höglund, Peter LU ; Ramgren, Birgitta LU ; Undrén, Per and Björkman-Burtscher, Isabella LU
- organization
- publishing date
- 2013
- type
- Contribution to journal
- publication status
- published
- subject
- in
- American Journal of Roentgenology: diagnostic imaging and related sciences
- volume
- 201
- issue
- 6
- pages
- 861 - 866
- publisher
- American Roentgen Ray Society
- external identifiers
-
- wos:000327501500009
- pmid:24261393
- scopus:84888333913
- pmid:24261393
- ISSN
- 1546-3141
- DOI
- 10.2214/AJR.13.10701
- language
- English
- LU publication?
- yes
- id
- 18dba8ca-cb5f-4940-9fcc-c1a0d4c40ab1 (old id 4179026)
- alternative location
- http://www.ncbi.nlm.nih.gov/pubmed/24261393?dopt=Abstract
- date added to LUP
- 2016-04-01 11:06:22
- date last changed
- 2022-04-05 00:11:06
@article{18dba8ca-cb5f-4940-9fcc-c1a0d4c40ab1,
abstract = {{OBJECTIVE. The purpose of this study was to evaluate the potential of a hybrid iterative reconstruction algorithm for improving image quality in craniocervical CT angiography (CTA) and to assess observer performance. SUBJECTS AND METHODS. Thirty patients (mean age, 58 years; range 16-80 years) underwent standard craniocervical CTA (volume CT dose index, 6.8 mGy, 2.8 mSv). Images were reconstructed using both filtered back projection (FBP) and a hybrid iterative reconstruction algorithm. Five neuroradiologists assessed general image quality and delineation of the vessel lumen in seven arterial segments using a 4-grade scale. Interobserver and intraobserver variability were determined. Mean attenuation and noise were measured and signal-to-noise and contrast-to-noise ratios calculated. Descriptive statistics are presented and data analyzed using linear mixed-effects models. RESULTS. In pooled data, image quality in iterative reconstruction was graded superior to FBP regarding all five quality criteria (p < 0.0001), with the greatest improvement observed in the vertebral arteries. Iterative reconstruction resulted in elimination of arterial segments graded poor. Interobserver percentage agreement was significantly better (p = 0.024) for iterative reconstruction (69%) than for FBP (66%) but worse than intraobserver percentage agreement (mean, 79%). Noise levels, signal-to-noise ratio, and contrast-to-noise ratio were significantly (p < 0.001) improved in iterative reconstruction at all measured levels. CONCLUSION. The iterative reconstruction algorithm significantly improves image quality in craniocervical CT, especially at the thoracic inlet. Despite careful study design, considerable interobserver and intraobserver variability was noted.}},
author = {{Löve, Askell and Siemund, Roger and Höglund, Peter and Ramgren, Birgitta and Undrén, Per and Björkman-Burtscher, Isabella}},
issn = {{1546-3141}},
language = {{eng}},
number = {{6}},
pages = {{861--866}},
publisher = {{American Roentgen Ray Society}},
series = {{American Journal of Roentgenology: diagnostic imaging and related sciences}},
title = {{Hybrid Iterative Reconstruction Algorithm Improves Image Quality in Craniocervical CT Angiography.}},
url = {{http://dx.doi.org/10.2214/AJR.13.10701}},
doi = {{10.2214/AJR.13.10701}},
volume = {{201}},
year = {{2013}},
}