Literature DB >> 30927099

Ultralow-dose CT with knowledge-based iterative model reconstruction (IMR) in evaluation of pulmonary tuberculosis: comparison of radiation dose and image quality.

Chenggong Yan1, Chunyi Liang1, Jun Xu2, Yuankui Wu1, Wei Xiong1, Huan Zheng1, Yikai Xu3.   

Abstract

OBJECTIVES: To evaluate the image quality of ultralow-dose computed tomography (ULDCT) reconstructed with knowledge-based iterative model reconstruction (IMR) in patients with pulmonary tuberculosis (TB).
METHODS: This IRB-approved prospective study enrolled 59 consecutive patients (mean age, 43.9 ± 16.6 years; F:M 18:41) with known or suspected pulmonary TB. Patients underwent a low-dose CT (LDCT) using automatic tube current modulation followed by an ULDCT using fixed tube current. Raw image data were reconstructed with filtered-back projection (FBP), hybrid iterative reconstruction (iDose), and IMR. Objective measurements including CT attenuation, image noise, and contrast-to-noise ratio (CNR) were assessed and compared using repeated-measures analysis of variance. Overall image quality and visualization of normal and pathological findings were subjectively scored on a five-point scale. Radiation output and subjective scores were compared by the paired Student t test and Wilcoxon signed-rank test, respectively.
RESULTS: Compared with FBP and iDose, IMR yielded significantly lower noise and higher CNR values at both dose levels (p < 0.01). Subjective ratings for pathological findings including centrilobular nodules, consolidation, tree-in-bud, and cavity were significantly better with ULDCT IMR images than those with LDCT iDose images (p < 0.01), but blurred edges were observed. With IMR implementation, a 59% reduction of the mean effective dose was achieved with ULDCT (0.28 ± 0.02 mSv) compared with LDCT (0.69 ± 0.15 mSv) without impairing image quality (p < 0.001).
CONCLUSIONS: IMR offers considerable noise reduction and improvement in image quality for patients with pulmonary TB undergoing chest ULDCT at an effective dose of 0.28 mSv. KEY POINTS: • Radiation dose is a major concern for tuberculosis patients requiring repeated follow-up CT. • IMR allows substantial radiation dose reduction in chest CT without compromising image quality. • ULDCT reconstructed with IMR allows accurate depiction of CT features of pulmonary tuberculosis.

Entities:  

Keywords:  Infection; Pulmonary tuberculosis; Radiation dosage; Thorax; Tomography, X-ray computed

Mesh:

Year:  2019        PMID: 30927099     DOI: 10.1007/s00330-019-06129-4

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  27 in total

1.  Pulmonary Emphysema Quantification on Ultra-Low-Dose Computed Tomography Using Model-Based Iterative Reconstruction With or Without Lung Setting.

Authors:  Akinori Hata; Masahiro Yanagawa; Noriko Kikuchi; Osamu Honda; Noriyuki Tomiyama
Journal:  J Comput Assist Tomogr       Date:  2018 Sep/Oct       Impact factor: 1.826

2.  The WHO 2014 global tuberculosis report--further to go.

Authors:  Alimuddin Zumla; Andrew George; Virendra Sharma; Rt Hon Nick Herbert; Aaron Oxley; Matt Oliver
Journal:  Lancet Glob Health       Date:  2015-01       Impact factor: 26.763

Review 3.  Imaging in tuberculosis.

Authors:  Evangelia Skoura; Alimuddin Zumla; Jamshed Bomanji
Journal:  Int J Infect Dis       Date:  2015-03       Impact factor: 3.623

4.  CT pulmonary angiography: dose reduction via a next generation iterative reconstruction algorithm.

Authors:  Andreas Sauter; Thomas Koehler; Bernhard Brendel; Juliane Aichele; Jan Neumann; Peter B Noël; Ernst J Rummeny; Daniela Muenzel
Journal:  Acta Radiol       Date:  2018-06-22       Impact factor: 1.990

5.  Prospective intra-individual comparison of standard dose versus reduced-dose thoracic CT using hybrid and pure iterative reconstruction in a follow-up cohort of pulmonary nodules-Effect of detectability of pulmonary nodules with lowering dose based on nodule size, type and body mass index.

Authors:  Varut Vardhanabhuti; Chun-Lap Pang; Sean Tenant; James Taylor; Christopher Hyde; Carl Roobottom
Journal:  Eur J Radiol       Date:  2017-04-15       Impact factor: 3.528

6.  Ultralow-Dose Abdominal Computed Tomography: Comparison of 2 Iterative Reconstruction Techniques in a Prospective Clinical Study.

Authors:  Ranish Deedar Ali Khawaja; Sarabjeet Singh; Michael Blake; Mukesh Harisinghani; Gary Choy; Ali Karaosmanoglu; Ali Karosmanoglu; Atul Padole; Saravenaz Pourjabbar; Synho Do; Mannudeep K Kalra
Journal:  J Comput Assist Tomogr       Date:  2015 Jul-Aug       Impact factor: 1.826

7.  Lung MRI of invasive fungal infection at 3 Tesla: evaluation of five different pulse sequences and comparison with multidetector computed tomography (MDCT).

Authors:  Chenggong Yan; Xiangliang Tan; Qi Wei; Ru Feng; Caixia Li; Yuankui Wu; Peng Hao; Queenie Chan; Wei Xiong; Jun Xu; Yikai Xu
Journal:  Eur Radiol       Date:  2014-09-18       Impact factor: 5.315

8.  Submillisievert chest CT with filtered back projection and iterative reconstruction techniques.

Authors:  Atul Padole; Sarabjeet Singh; Jeanne B Ackman; Carol Wu; Synho Do; Sarvenaz Pourjabbar; Ranish Deedar Ali Khawaja; Alexi Otrakji; Subba Digumarthy; Jo-Anne Shepard; Mannudeep Kalra
Journal:  AJR Am J Roentgenol       Date:  2014-10       Impact factor: 3.959

9.  Radiation Dose Reduction by Using CT with Iterative Model Reconstruction in Patients with Pulmonary Invasive Fungal Infection.

Authors:  Chenggong Yan; Jun Xu; Chunyi Liang; Qi Wei; Yuankui Wu; Wei Xiong; Huan Zheng; Yikai Xu
Journal:  Radiology       Date:  2018-04-10       Impact factor: 11.105

10.  High-resolution CT for identify patients with smear-positive, active pulmonary tuberculosis.

Authors:  Jun Jun Yeh; Joseph Kwong-Leung Yu; Wen-Bao Teng; Chun-Hsiung Chou; Shih-Peng Hsieh; Tsung-Lung Lee; Ming-Ting Wu
Journal:  Eur J Radiol       Date:  2010-10-27       Impact factor: 3.528

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  1 in total

Review 1.  CT and 18F-FDG PET abnormalities in contacts with recent tuberculosis infections but negative chest X-ray.

Authors:  Soon Ho Yoon; Jin Mo Goo; Jae-Joon Yim; Takashi Yoshiyama; JoAnne L Flynn
Journal:  Insights Imaging       Date:  2022-07-07
  1 in total

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