Literature DB >> 28707531

Third version of vendor-specific model-based iterativereconstruction (Veo 3.0): evaluation of CT image quality in the abdomen using new noise reduction presets and varied slice optimization.

Morgan E Telesmanich1, Corey T Jensen2, Jose L Enriquez1, Nicolaus A Wagner-Bartak2, Xinming Liu3, Ott Le2, Wei Wei4, Adam G Chandler3,5, Eric P Tamm2.   

Abstract

OBJECTIVE: To qualitatively and quantitatively compare abdominal CT images reconstructed with a newversion of model-based iterative reconstruction (Veo 3.0; GE Healthcare Waukesha, WI) utilizing varied presetsof resolution preference, noise reduction and slice optimization.
METHODS: This retrospective study was approved by our Institutional Review Board and was Health Insurance Portability and Accountability Act compliant. The raw datafrom 30 consecutive patients who had undergone CT abdomen scanning were used to reconstructfour clinical presets of 3.75mm axial images using Veo 3.0: 5% resolution preference (RP05n), 5%noise reduction (NR05) and 40% noise reduction (NR40) with new 3.75mm "sliceoptimization," as well as one set using RP05 with conventional 0.625mm "slice optimization" (RP05c). The images were reviewed by two independent readers in a blinded, randomized manner using a 5-point Likert scale as well as a 5-point comparative scale. Multiple two-dimensional circular regions of interest were defined for noise and contrast-to-noise ratio measurements. Line profiles were drawn across the 7 lp cm-1 bar pattern of the Catphan 600 phantom for evaluation of spatial resolution.
RESULTS: The NR05 image set was ranked as the best series in overall image quality (mean difference inrank 0.48, 95% CI [0.081-0.88], p = 0.01) and with specific reference to liver evaluation (meandifference 0.46, 95% CI [0.030-0.89], p = 0.03), when compared with the secondbest series ineach category. RP05n was ranked as the best for bone evaluation. NR40 was ranked assignificantly inferior across all assessed categories. Although the NR05 and RP05c image setshad nearly the same contrast-to-noise ratio and spatial resolution, NR05 was generally preferred. Image noise and spatial resolution increased along a spectrum with RP05n the highest and NR40the lowest. Compared to RP05n, the average noise was 21.01% lower for NR05, 26.88%lower for RP05c and 50.86% lower for NR40.
CONCLUSION: Veo 3.0 clinical presets allow for selection of image noise and spatial resolution balance; for contrast-enhanced CT evaluation of the abdomen, the 5% noise reduction preset with 3.75 mm slice optimization (NR05) was generally ranked superior qualitatively and, relative to other series, was in the middle of the spectrum with reference to image noise and spatial resolution. Advances in knowledge: To our knowledge, this is the first study of Veo 3.0 noise reduction presets and varied slice optimization. This study provides insight into the behaviour of slice optimization and documents the degree of noise reduction and spatial resolution changes that users can expect across various Veo 3.0 clinical presets. These results provide important parameters to guide preset selection for both clinical and research purposes.

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Year:  2017        PMID: 28707531      PMCID: PMC5858796          DOI: 10.1259/bjr.20170188

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  23 in total

1.  High-resolution CT with new model-based iterative reconstruction with resolution preference algorithm in evaluations of lung nodules: Comparison with conventional model-based iterative reconstruction and adaptive statistical iterative reconstruction.

Authors:  Koichiro Yasaka; Masaki Katsura; Shouhei Hanaoka; Jiro Sato; Kuni Ohtomo
Journal:  Eur J Radiol       Date:  2016-01-11       Impact factor: 3.528

2.  Comparison of hybrid and pure iterative reconstruction techniques with conventional filtered back projection: dose reduction potential in the abdomen.

Authors:  Sarabjeet Singh; Mannudeep K Kalra; Synho Do; Jean Baptiste Thibault; Homer Pien; Owen J O'Connor; Owen O J Connor; Michael A Blake
Journal:  J Comput Assist Tomogr       Date:  2012 May-Jun       Impact factor: 1.826

3.  A three-dimensional statistical approach to improved image quality for multislice helical CT.

Authors:  Jean-Baptiste Thibault; Ken D Sauer; Charles A Bouman; Jiang Hsieh
Journal:  Med Phys       Date:  2007-11       Impact factor: 4.071

4.  Assessment of the dose reduction potential of a model-based iterative reconstruction algorithm using a task-based performance metrology.

Authors:  Ehsan Samei; Samuel Richard
Journal:  Med Phys       Date:  2015-01       Impact factor: 4.071

5.  Effect of Model-Based Iterative Reconstruction on CT Number Measurements Within Small (10-29 mm) Low-Attenuation Renal Masses.

Authors:  Kimberly L Shampain; Matthew S Davenport; Richard H Cohan; Mitchell M Goodsitt; James H Ellis; Joel F Platt
Journal:  AJR Am J Roentgenol       Date:  2015-07       Impact factor: 3.959

6.  Evaluation of Abdominal Computed Tomography Image Quality Using a New Version of Vendor-Specific Model-Based Iterative Reconstruction.

Authors:  Corey T Jensen; Morgan E Telesmanich; Nicolaus A Wagner-Bartak; Xinming Liu; John Rong; Janio Szklaruk; Aliya Qayyum; Wei Wei; Adam G Chandler; Eric P Tamm
Journal:  J Comput Assist Tomogr       Date:  2017-01       Impact factor: 1.826

7.  Assessment of a model-based, iterative reconstruction algorithm (MBIR) regarding image quality and dose reduction in liver computed tomography.

Authors:  Won Chang; Jeong Min Lee; Kyunghee Lee; Jeong Hee Yoon; Mi Hye Yu; Joon Koo Han; Byung Ihn Choi
Journal:  Invest Radiol       Date:  2013-08       Impact factor: 6.016

8.  Low-tube-voltage, high-tube-current multidetector abdominal CT: improved image quality and decreased radiation dose with adaptive statistical iterative reconstruction algorithm--initial clinical experience.

Authors:  Daniele Marin; Rendon C Nelson; Sebastian T Schindera; Samuel Richard; Richard S Youngblood; Terry T Yoshizumi; Ehsan Samei
Journal:  Radiology       Date:  2010-01       Impact factor: 11.105

9.  A noise power spectrum study of a new model-based iterative reconstruction system: Veo 3.0.

Authors:  Guang Li; Xinming Liu; Cristina T Dodge; Corey T Jensen; X John Rong
Journal:  J Appl Clin Med Phys       Date:  2016-09-08       Impact factor: 2.102

10.  Performance evaluation of iterative reconstruction algorithms for achieving CT radiation dose reduction - a phantom study.

Authors:  Cristina T Dodge; Eric P Tamm; Dianna D Cody; Xinming Liu; Corey T Jensen; Wei Wei; Vikas Kundra; X John Rong
Journal:  J Appl Clin Med Phys       Date:  2016-03-08       Impact factor: 2.102

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  2 in total

1.  Detection of Colorectal Hepatic Metastases Is Superior at Standard Radiation Dose CT versus Reduced Dose CT.

Authors:  Corey T Jensen; Nicolaus A Wagner-Bartak; Lan N Vu; Xinming Liu; Bharat Raval; David Martinez; Wei Wei; Yuan Cheng; Ehsan Samei; Shiva Gupta
Journal:  Radiology       Date:  2018-11-27       Impact factor: 11.105

2.  Metal artifacts reduction in computed tomography: A phantom study to compare the effectiveness of metal artifact reduction algorithm, model-based iterative reconstruction, and virtual monochromatic imaging.

Authors:  Takuya Ishikawa; Shigeru Suzuki; Shingo Harashima; Rika Fukui; Masafumi Kaiume; Yoshiaki Katada
Journal:  Medicine (Baltimore)       Date:  2020-12-11       Impact factor: 1.817

  2 in total

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