Literature DB >> 29634436

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

Chenggong Yan1, Jun Xu1, Chunyi Liang1, Qi Wei1, Yuankui Wu1, Wei Xiong1, Huan Zheng1, Yikai Xu1.   

Abstract

Purpose To compare the diagnostic quality of reduced radiation dose computed tomography (CT) with iterative model reconstruction (IMR) versus that of conventional low-dose CT in patients with pulmonary invasive fungal infection. Materials and Methods This prospective observational study included 48 patients (mean age ± standard deviation, 39.9 years ± 11.3) known to have or suspected of having pulmonary invasive fungal infection between October 2016 and July 2017. Patients underwent CT with IMR (at 80 kV with 20 mA) immediately after low-dose CT (at 80 kV with automatic exposure control). Images were reconstructed by using a hybrid iterative reconstruction (HIR) algorithm and IMR. Two radiologists independently assessed subjective image quality, noise, and visibility of normal and abnormal findings by using a five-point scale. Objective measurements, including image noise, contrast-to-noise ratio (CNR), and corresponding figure of merit (FOM), were compared by using repeated-measures analysis of variance with Bonferroni post hoc tests for multiple comparisons. Results The mean effective dose was 0.3 mSv ± 0.3 for CT with IMR and 0.7 mSv ± 0.2 for low-dose CT (P < .01). When the image noise and CNR were normalized to the effective dose, CT images obtained with IMR had significantly higher FOM than did other image series (P < .0001). Subjectively, visibility of CT features of invasive fungal infection on CT scans reconstructed with IMR was rated as noninferior to that on low-dose CT scans reconstructed with HIR, except for the halo sign. Conclusion CT with IMR had approximately 60% dose reduction compared with conventional low-dose CT, with reduced noise and improved depiction of abnormal findings, in patients with pulmonary invasive fungal infection. © RSNA, 2018.

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Year:  2018        PMID: 29634436     DOI: 10.1148/radiol.2018172107

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  7 in total

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

Authors:  Chenggong Yan; Chunyi Liang; Jun Xu; Yuankui Wu; Wei Xiong; Huan Zheng; Yikai Xu
Journal:  Eur Radiol       Date:  2019-03-29       Impact factor: 5.315

2.  CT iterative reconstruction algorithms: a task-based image quality assessment.

Authors:  J Greffier; J Frandon; A Larbi; J P Beregi; F Pereira
Journal:  Eur Radiol       Date:  2019-07-29       Impact factor: 5.315

3.  Reduced-Dose Deep Learning Reconstruction for Abdominal CT of Liver Metastases.

Authors:  Corey T Jensen; Shiva Gupta; Mohammed M Saleh; Xinming Liu; Vincenzo K Wong; Usama Salem; Wei Qiao; Ehsan Samei; Nicolaus A Wagner-Bartak
Journal:  Radiology       Date:  2022-01-11       Impact factor: 29.146

4.  Ultra-low-dose multiphase CT angiography derived from CT perfusion data in patients with middle cerebral artery stenosis.

Authors:  Xiaoling Wu; Yuelong Yang; Menghuang Wen; Lijuan Wang; Yunjun Yang; Yuhu Zhang; Zihua Mo; Kun Nie; Biao Huang
Journal:  Neuroradiology       Date:  2019-10-30       Impact factor: 2.804

5.  Improving the image quality of pediatric chest CT angiography with low radiation dose and contrast volume using deep learning image reconstruction.

Authors:  Jihang Sun; Haoyan Li; Jianying Li; Tong Yu; Michelle Li; Zuofu Zhou; Yun Peng
Journal:  Quant Imaging Med Surg       Date:  2021-07

6.  Machine learning-based combined nomogram for predicting the risk of pulmonary invasive fungal infection in severely immunocompromised patients.

Authors:  Chenggong Yan; Peng Hao; Guangyao Wu; Jie Lin; Jun Xu; Tianjing Zhang; Xiangying Li; Haixia Li; Sibin Wang; Yikai Xu; Henry C Woodruff; Philippe Lambin
Journal:  Ann Transl Med       Date:  2022-05

7.  Pragmatic Approaches to Reducing Radiation Dose in Brain Computed Tomography Scan using Scan Parameter Modification.

Authors:  Mohammad Reza Choopani; Iraj Abedi; Fatemeh Dalvand
Journal:  J Med Signals Sens       Date:  2022-07-26
  7 in total

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