Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
European Radiology
Published in: European Radiology 6/2018

Open Access 01-06-2018 | Computed Tomography

Assessment of image quality in abdominal CT: potential dose reduction with model-based iterative reconstruction

Authors: Bharti Kataria, Jonas Nilsson Althén, Örjan Smedby, Anders Persson, Hannibal Sökjer, Michael Sandborg

Published in: European Radiology | Issue 6/2018

Login to get access

Abstract

Purpose

To estimate potential dose reduction in abdominal CT by visually comparing images reconstructed with filtered back projection (FBP) and strengths of 3 and 5 of a specific MBIR.

Material and methods

A dual-source scanner was used to obtain three data sets each for 50 recruited patients with 30, 70 and 100% tube loads (mean CTDIvol 1.9, 3.4 and 6.2 mGy). Six image criteria were assessed independently by five radiologists. Potential dose reduction was estimated with Visual Grading Regression (VGR).

Results

Comparing 30 and 70% tube load, improved image quality was observed as a significant strong effect of log tube load and reconstruction method with potential dose reduction relative to FBP of 22–47% for MBIR strength 3 (p < 0.001). For MBIR strength 5 no dose reduction was possible for image criteria 1 (liver parenchyma), but dose reduction between 34 and 74% was achieved for other criteria. Interobserver reliability showed agreement of 71–76% (κw 0.201–0.286) and intra-observer reliability of 82–96% (κw 0.525–0.783).

Conclusion

MBIR showed improved image quality compared to FBP with positive correlation between MBIR strength and increasing potential dose reduction for all but one image criterion.

Key Points

• MBIR’s main advantage is its de-noising properties, which facilitates dose reduction.
• MBIR allows for potential dose reduction in relation to FBP.
• Visual Grading Regression (VGR) produces direct numerical estimates of potential dose reduction.
• MBIR strengths 3 and 5 dose reductions were 22–34 and 34–74%.
• MBIR strength 5 demonstrates inferior performance for liver parenchyma.
Literature
1.
Mahesh M (2009) MDCT physics the basics technology, image quality and radiation dose. Lippincott Williams & Wilkins, Philadelphia
2.
Moores M (2017) A review of the fundamental principles of radiation protection when applied to the patient in diagnostic radiology. Radiat Prot Dosim 175:1–9
3.
Sun Z, Ng KA, Sarji SA (2010) Is utilisation of computed tomography justified in clinical practice? Part IV: applications of paediatric computed tomography. Singapore Med J 51:457–463PubMed
4.
Report UNSCEAR (2008) Sources and effects of ionizing radiation. United Nations Scientific Committee on the effects of ionizing radiation. Volume 1: Sources. Report to the general assembly Scientific annexes A & B
5.
Le Coultre R, Bize J, Champendal M et al (2016) Exposure of the Swiss population by radiodiagnostics: 2013 review. Radiat Prot Dosim 169:221–224CrossRef
6.
7.
Power SP, Maloney F, Twomey M, James K, O’Connor OJ, Maher MM (2016) Computed tomography and patient risks: facts, perceptions and uncertainties. World J Radiol 8:902–915CrossRefPubMedPubMedCentral
8.
Mayo-Smith WW, Hara AK, Mahesh M, Sahani DV, Pavlicek W (2014) How I do it: managing radiation dose in CT. Radiology 273:657–672CrossRefPubMed
9.
Smith-Bindeman R, Lipson J, Markus R et al (2009) Radiation dose associated with common Computed Tomography examinations and the associated lifetime attributable risk for cancer. Arch Intern Med 169:2078–2086CrossRef
10.
Kalra MK, Sodickson AD, Mayo-Smith WW (2015) CT radiation: key concepts for gentle and wise use. Radiographics 35:1706–1721CrossRefPubMed
11.
Liu L (2014) Model based Iterative Reconstruction: a promising algorithm for today's Computed Tomography Imaging. J Med Radiat Sci 45:131–136CrossRef
12.
Beister M, Kolditz D, Kalender WA (2012) Iterative reconstruction methods in X-ray CT. Phys Medica 28:94–108CrossRef
13.
Solomon J, Mileto A, Ramirez-Giraldo JC, Samei E (2015) Diagnostic Performance of an Advanced Modeled Iterative Reconstruction Algorithm for low-contrast detectability with a third generation Multidetector dual source CT Scanner. Radiology 275:735–745CrossRefPubMed
14.
Nuyts J, De Man B, Fessler JA, Zbijewski W, Beekman FJ (2013) Modelling the physics in iterative reconstruction for transmission computed tomography. Phys Med Biol 58:R63–R96CrossRefPubMedPubMedCentral
15.
Ott JG, Ba A, Racine D et al (2016) Patient exposure optimisation through task-based assessment of a new model-based iterative reconstruction technique. Radiat Prot Dosim 169:68–72CrossRef
16.
Patino M, Fuentes JM, Singh S, Hahn PF, Sahani DV (2015) Iterative reconstruction techniques in abdominopelvic CT: technical concepts and clinical implementation. AJR Am J Roentgenol 205:W19–W31CrossRefPubMed
17.
18.
Smedby Ö, Fredrikson M (2010) Visual grading regression – analysing data from visual grading experiments with regression models. Br J Radiol 83:767–775CrossRefPubMedPubMedCentral
19.
20.
Borgen L, Kalra MK, Laerum F et al (2012) Application of adaptive non-linear 2 D and 3 D post processing filters for reduced dose abdominal CT. Acta Radiol 53:335–34219CrossRefPubMed
21.
Smedby Ö, Fredrikson M, De Geer J, Borgen L, Sandborg M (2013) Quantifying the potential for dose reduction with visual grading regression. Br J Radiol 86:1–6CrossRef
22.
Abraira V, Pérez de Vargas A (1999) Generalization of the Kappa coefficient for ordinal categorical data, multiple observers and incomplete designs. Qüestiió 23:561–571
23.
24.
Kataria B, Smedby Ö (2013) Patient dose and image quality in a low-dose abdominal CT: a comparison between iterative reconstruction and filtered back projection. Acta Radiol 54:540–548CrossRefPubMed
25.
Saffari SE, Löve Á, Fredrikson M, Smedby Ö (2015) Regression models for analyzing radiological visual grading studies – an empirical comparison. BMC Med Imaging 15:1–10CrossRef
26.
Greffier J, Fernandez A, Macri F, Freitag C, Metge L, Beregi JP (2013) Which dose for what image? Iterative reconstruction for CT scan. Diagn Interv Imaging 94:1117–1121CrossRefPubMed
27.
Gordic S, Desbiolles L, Stolzmann P et al (2014) Advanced modelled iterative reconstruction for abdominal CT: qualitative and quantitative evaluation. Clin Radiol 69:497–504CrossRef
28.
Wichmann JL, Hardie AD, Schoepf JU et al (2016) Single- and dual-energy CT of the abdomen: comparison of radiation dose and image quality of 2nd and 3rd generation dual-source CT. Eur Radiol 27:642–650CrossRefPubMed
29.
Larsson J, Båth M, Ledenius K, Caisander H, Thilander-Klang A (2016) Assessment of clinical image quality in paediatric abdominal CT examinations: dependency on the level of adaptive statistical iterative reconstruction (ASiR) and the type of convolution kernel. Radiat Prot Dosimetry 169:123–129CrossRefPubMed
30.
Mieville FA, Berteloot L, Grandjean A et al (2013) Model-based iterative reconstruction in Pediatric chest CT: assessment of image quality in a prospective study of children with cystic fibrosis. Pediatr Radiol 43:558–567CrossRefPubMed
31.
Padole A, Singh S, Lira D et al (2015) Assessment of filtered back projection, adaptive statistical, and model-based iterative reconstruction for reduced dose abdominal computed tomography. J Comput Assist Tomogr 39:462–467CrossRefPubMed
32.
Euler A, Stieltjes B, Szucs-Farkas Z et al. (2017) Impact of model-based iterative reconstruction on low-contrast lesion detection and image quality in abdominal CT: a 12-reader-based comparative phantom study with filtered back projection at different tube voltages. Eur Radiol. https://​doi.​org/​10.​1007/​s00330-017-4825-9
33.
Solomon J, Marin D, Roy Choudhury K, Patel B, Samei E (2017) Effect of radiation dose reduction and reconstruction algorithm on Image noise, contrast, resolution, and detectability of subtle hypoattenuating liver lesions at multidetector CT: filtered back projection versus a commercial model-based iterative reconstruction algorithm. Radiology. https://​doi.​org/​10.​1148/​radiol.​2017161736
34.
Sagara Y, Hara AK, Pavlicek W, Silva AC, Paden RG, Wu Q (2010) Abdominal CT: comparison of low-dose CT with adaptive statistic iterative reconstruction and routine dose CT with filtered back projection in 53 patients. AJR Am J Roentgenol 195:713–719CrossRefPubMed
35.
Drew T, Vo MHL, Olwal A, Jacobson F, Seltzer SE, Wolfe J (2013) Scanners and drillers: characterizing expert visual search through volumetric images. J Vis 13:1–13CrossRef
36.
Birkelo CC, Chamberlain WE, Phelps PS, Schools PE, Zacks D, Yerushalmy J (1947) Tuberculosis case finding. JAMA 133:359–366CrossRef
37.
Chang W, Lee JM, Lee K et al (2013) Assessment of a model-based, iterative reconstruction algorithm (MBIR) regarding image quality and dose reduction in liver computed tomography. Invest Radiol 48:598–606CrossRefPubMed
38.
Hérin E, Gardavaud F, Chiaradia M et al (2015) Use of model-based iterative reconstruction (MBIR) in reduced dose CT for routine follow-up of patients with malignant lymphoma: dose savings, image quality & phantom study. Eur Radiol 25:2362–2370CrossRefPubMed
Metadata
Title
Assessment of image quality in abdominal CT: potential dose reduction with model-based iterative reconstruction
Authors
Bharti Kataria
Jonas Nilsson Althén
Örjan Smedby
Anders Persson
Hannibal Sökjer
Michael Sandborg
Publication date
01-06-2018
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 6/2018
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-017-5113-4

Other articles of this Issue 6/2018

European Radiology 6/2018 Go to the issue

Computed Tomography

Quantifying the effect of slice thickness, intravenous contrast and tube current on muscle segmentation: Implications for body composition analysis

Breast

Prospective study aiming to compare 2D mammography and tomosynthesis + synthesized mammography in terms of cancer detection and recall. From double reading of 2D mammography to single reading of tomosynthesis

Magnetic Resonance

To evaluate the feasibility of magnetic resonance imaging in predicting unusual site ectopic pregnancy: a retrospective cohort study

Head and Neck

Evaluation of pain during high-intensity focused ultrasound ablation of benign thyroid nodules

Magnetic Resonance

Magnetic resonance cholangiopancreatography with GRASE sequence at 3.0T: does it improve image quality and acquisition time as compared with 3D TSE?

Interventional

Pasireotide does not improve efficacy of aspiration sclerotherapy in patients with large hepatic cysts, a randomized controlled trial