Literature DB >> 25423129

Detection of pulmonary embolism on computed tomography: improvement using a model-based iterative reconstruction algorithm compared with filtered back projection and iterative reconstruction algorithms.

Seth Kligerman1, Kian Lahiji, Elizabeth Weihe, Cheng Tin Lin, Silanath Terpenning, Jean Jeudy, Annie Frazier, Robert Pugatch, Jeffrey R Galvin, Deepika Mittal, Kunal Kothari, Charles S White.   

Abstract

PURPOSE: The purpose of the study was to determine whether a model-based iterative reconstruction (MBIR) technique improves diagnostic confidence and detection of pulmonary embolism (PE) compared with hybrid iterative reconstruction (HIR) and filtered back projection (FBP) reconstructions in patients undergoing computed tomography pulmonary angiography.
MATERIALS AND METHODS: The study was approved by our institutional review board. Fifty patients underwent computed tomography pulmonary angiography at 100 kV using standard departmental protocols. Twenty-two of 50 patients had studies positive for PE. All 50 studies were reconstructed using FBP, HIR, and MBIR. After image randomization, 5 thoracic radiologists and 2 thoracic radiology fellows graded each study on a scale of 1 (very poor) to 5 (ideal) in 4 subjective categories: diagnostic confidence, noise, pulmonary artery enhancement, and plastic appearance. Readers assessed each study for the presence of PE. Parametric and nonparametric data were analyzed with repeated measures and Friedman analysis of variance, respectively.
RESULTS: For the 154 positive studies (7 readers × 22 positive studies), pooled sensitivity for detection of PE was 76% (117/154), 78.6% (121/154), and 82.5% (127/154) using FBP, HIR, and MBIR, respectively. PE detection was significantly higher using MBIR compared with FBP (P = 0.016) and HIR (P = 0.046). Because of nonsignificant increase in FP studies using HIR and MBIR, accuracy with MBIR (88.6%), HIR (87.1%), and FBP (87.7%) was similar. Compared with FBP, MBIR led to a significant subjective increase in diagnostic confidence, noise, and enhancement in 6/7, 6/7, and 7/7 readers, respectively. Compared with HIR, MBIR led to significant subjective increase in diagnostic confidence, noise, and enhancement in 5/7, 5/7, and 7/7 readers, respectively. MBIR led to a subjective increase in plastic appearance in all 7 readers compared with both FBP and HIR.
CONCLUSIONS: MBIR led to significant increase in PE detection compared with FBP and HIR. MBIR led to qualitative improvements in diagnostic confidence, perceived noise, and perceived enhancement compared with FBP and HIR.

Entities:  

Mesh:

Year:  2015        PMID: 25423129     DOI: 10.1097/RTI.0000000000000122

Source DB:  PubMed          Journal:  J Thorac Imaging        ISSN: 0883-5993            Impact factor:   3.000


  5 in total

1.  Optimization of computed tomography pulmonary angiography protocols using 3D printed model with simulation of pulmonary embolism.

Authors:  Sultan Aldosari; Shirley Jansen; Zhonghua Sun
Journal:  Quant Imaging Med Surg       Date:  2019-01

2.  Patient-specific 3D printed pulmonary artery model with simulation of peripheral pulmonary embolism for developing optimal computed tomography pulmonary angiography protocols.

Authors:  Sultan Aldosari; Shirley Jansen; Zhonghua Sun
Journal:  Quant Imaging Med Surg       Date:  2019-01

3.  Deep Convolutional Neural Network With Adversarial Training for Denoising Digital Breast Tomosynthesis Images.

Authors:  Mingjie Gao; Jeffrey A Fessler; Heang-Ping Chan
Journal:  IEEE Trans Med Imaging       Date:  2021-06-30       Impact factor: 11.037

4.  Influence of model based iterative reconstruction algorithm on image quality of multiplanar reformations in reduced dose chest CT.

Authors:  Heloise Barras; Vincent Dunet; Anne-Lise Hachulla; Jochen Grimm; Catherine Beigelman-Aubry
Journal:  Acta Radiol Open       Date:  2016-08-24

5.  Tradeoff between noise reduction and inartificial visualization in a model-based iterative reconstruction algorithm on coronary computed tomography angiography.

Authors:  Kenichiro Hirata; Daisuke Utsunomiya; Masafumi Kidoh; Yoshinori Funama; Seitaro Oda; Hideaki Yuki; Yasunori Nagayama; Yuji Iyama; Takeshi Nakaura; Daisuke Sakabe; Kenichi Tsujita; Yasuyuki Yamashita
Journal:  Medicine (Baltimore)       Date:  2018-05       Impact factor: 1.889

  5 in total

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