Literature DB >> 25424691

Model-based iterative reconstruction for detection of subtle hypoattenuation in early cerebral infarction: a phantom study.

Mitsuo Nishizawa1, Hisashi Tanaka, Yoshiyuki Watanabe, Yuuki Kunitomi, Akio Tsukabe, Noriyuki Tomiyama.   

Abstract

PURPOSE: Model-based iterative reconstruction (MBIR) was recently shown to enable dose reduction in computed tomography (CT). The detectability of low-contrast lesions was assessed on CT images reconstructed with MBIR compared with the conventional filtered back-projection (FBP) method.
MATERIALS AND METHODS: A phantom simulating brain gray matter containing small lesions mimicking early cerebral infarctions was scanned at tube currents of 50, 100, 200, and 400 mA. Images were reconstructed by use of both methods. Round regions were cropped from the reconstructed images, half with a lesion, the other half without. Eight radiologists reviewed the images and scored the certainty of lesion detection on a 5-point scale. Overall performance was analyzed by use of a receiver operating characteristic curve.
RESULTS: For the tube currents investigated, the analysis showed that the mean areas under the curves for the reviewers were 0.65, 0.70, 0.82, and 0.83 for FBP and 0.70, 0.76, 0.78, and 0.90 for MBIR. For each current, there was no significant difference between the areas under the curves for the different reconstruction methods (p = 0.32, 0.24, 0.49, and 0.17).
CONCLUSION: For the small, low-contrast lesions in the phantom model used in this study, no significant difference between detectability was observed for MBIR and FBP.

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Year:  2014        PMID: 25424691     DOI: 10.1007/s11604-014-0376-z

Source DB:  PubMed          Journal:  Jpn J Radiol        ISSN: 1867-1071            Impact factor:   2.374


  35 in total

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Authors:  A Korn; M Fenchel; B Bender; S Danz; T K Hauser; D Ketelsen; T Flohr; C D Claussen; M Heuschmid; U Ernemann; H Brodoefel
Journal:  AJNR Am J Neuroradiol       Date:  2011-10-27       Impact factor: 3.825

Review 2.  Computed tomography--an increasing source of radiation exposure.

Authors:  David J Brenner; Eric J Hall
Journal:  N Engl J Med       Date:  2007-11-29       Impact factor: 91.245

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.  Signal, noise power spectrum, and detective quantum efficiency of indirect-detection flat-panel imagers for diagnostic radiology.

Authors:  J H Siewerdsen; L E Antonuk; Y el-Mohri; J Yorkston; W Huang; I A Cunningham
Journal:  Med Phys       Date:  1998-05       Impact factor: 4.071

5.  Vascular diameter measurement in CT angiography: comparison of model-based iterative reconstruction and standard filtered back projection algorithms in vitro.

Authors:  Shigeru Suzuki; Haruhiko Machida; Isao Tanaka; Eiko Ueno
Journal:  AJR Am J Roentgenol       Date:  2013-03       Impact factor: 3.959

6.  How far can the radiation dose be lowered in head CT with iterative reconstruction? Analysis of imaging quality and diagnostic accuracy.

Authors:  Tung-Hsin Wu; Sheng-Che Hung; Jing-Yi Sun; Chung-Jung Lin; Chung-Hsien Lin; Chen Fen Chiu; Min-Jsuan Liu; Michael Mu Huo Teng; Wan-Yuo Guo; Cheng-Yen Chang
Journal:  Eur Radiol       Date:  2013-05-04       Impact factor: 5.315

7.  Contrast-to-noise ratio and low-contrast object resolution on full- and low-dose MDCT: SAFIRE versus filtered back projection in a low-contrast object phantom and in the liver.

Authors:  Mark E Baker; Frank Dong; Andrew Primak; Nancy A Obuchowski; David Einstein; Namita Gandhi; Brian R Herts; Andrei Purysko; Erick Remer; Neil Vachhani; Neil Vachani
Journal:  AJR Am J Roentgenol       Date:  2012-07       Impact factor: 3.959

8.  Iterative reconstruction methods in two different MDCT scanners: physical metrics and 4-alternative forced-choice detectability experiments--a phantom approach.

Authors:  Frédéric A Miéville; François Gudinchet; Francis Brunelle; François O Bochud; Francis R Verdun
Journal:  Phys Med       Date:  2012-01-02       Impact factor: 2.685

9.  Detectability in computed tomographic images.

Authors:  K M Hanson
Journal:  Med Phys       Date:  1979 Sep-Oct       Impact factor: 4.071

10.  Why do commercial CT scanners still employ traditional, filtered back-projection for image reconstruction?

Authors:  Xiaochuan Pan; Emil Y Sidky; Michael Vannier
Journal:  Inverse Probl       Date:  2009-01-01       Impact factor: 2.407

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  9 in total

1.  Comparison of iterative model, hybrid iterative, and filtered back projection reconstruction techniques in low-dose brain CT: impact of thin-slice imaging.

Authors:  Takeshi Nakaura; Yuji Iyama; Masafumi Kidoh; Koichi Yokoyama; Seitaro Oda; Shinichi Tokuyasu; Kazunori Harada; Yasuyuki Yamashita
Journal:  Neuroradiology       Date:  2015-12-29       Impact factor: 2.804

2.  A "one-stop-shop" 4D CTA protocol using 320-row CT for advanced imaging in acute ischemic stroke: a technical note.

Authors:  Julien Ognard; Brieg Dissaux; Karim Haioun; Michel Nonent; Jean-Christophe Gentric; Douraïed Ben Salem
Journal:  Eur Radiol       Date:  2019-02-15       Impact factor: 5.315

3.  "Hyperdense artery sign" in early ischemic stroke: diagnostic value of model-based reconstruction approach in comparison with standard hybrid iterative reconstruction algorithm.

Authors:  Sophie Lombardi; Luca Riva; Mirko Patassini; Paolo Remida; Cristina Capraro; Francesco Canonico; Cammillo Talei Franzesi; Davide Ippolito
Journal:  Neuroradiology       Date:  2018-09-08       Impact factor: 2.804

4.  Enhanced gray-white matter differentiation on non-enhanced CT using a frequency selective non-linear blending.

Authors:  Georg Bier; Malte Niklas Bongers; Hendrik Ditt; Benjamin Bender; Ulrike Ernemann; Marius Horger
Journal:  Neuroradiology       Date:  2016-03-10       Impact factor: 2.804

5.  Diagnostic performance of reduced-dose CT with a hybrid iterative reconstruction algorithm for the detection of hypervascular liver lesions: a phantom study.

Authors:  Atsushi Nakamoto; Yoshikazu Tanaka; Hiroshi Juri; Go Nakai; Shushi Yoshikawa; Yoshifumi Narumi
Journal:  Eur Radiol       Date:  2016-12-12       Impact factor: 5.315

6.  Model-Based Iterative Reconstruction (MBIR) for ASPECT Scoring in Acute Stroke Patients Selection: Comparison to rCBV and Follow-Up Imaging.

Authors:  Brieg Dissaux; Mourad Cheddad El Aouni; Julien Ognard; Jean-Christophe Gentric
Journal:  Tomography       Date:  2022-05-05

7.  Deep Learning-based CT Image Reconstruction: Initial Evaluation Targeting Hypovascular Hepatic Metastases.

Authors:  Yuko Nakamura; Toru Higaki; Fuminari Tatsugami; Jian Zhou; Zhou Yu; Naruomi Akino; Yuya Ito; Makoto Iida; Kazuo Awai
Journal:  Radiol Artif Intell       Date:  2019-10-09

8.  Model-based reconstruction algorithm in the detection of acute trauma-related lesions in brain CT examinations.

Authors:  Andrea De Vito; Cesare Maino; Sophie Lombardi; Maria Ragusi; Cammillo Talei Franzesi; Davide Ippolito; Sandro Sironi
Journal:  Neuroradiol J       Date:  2021-04-19

9.  Thin-slice brain CT with iterative model reconstruction algorithm for small lacunar lesions detection: Image quality and diagnostic accuracy evaluation.

Authors:  Xiaoyi Liu; Lei Chen; Weiwei Qi; Yan Jiang; Ying Liu; Miao Zhang; Nan Hong
Journal:  Medicine (Baltimore)       Date:  2017-12       Impact factor: 1.817

  9 in total

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