Literature DB >> 29396085

Detection and characterization of focal liver lesions with ultra-low dose computed tomography in neoplastic patients.

A Larbi1, C Orliac2, J Frandon2, F Pereira2, A Ruyer2, J Goupil2, F Macri2, J P Beregi2, J Greffier2.   

Abstract

PURPOSE: The purpose of this study was to evaluate and compare the diagnostic accuracy of ultra-low dose (ULD) computed tomography (CT) with that of standard dose (STD) CT in the detection and characterization of focal liver lesions in neoplastic patients.
MATERIALS AND METHODS: A total of 177 neoplastic patients who underwent two abdominopelvic CT examinations (one with STD and one with ULD protocol) for suspected focal liver lesions were included. There were 103 men and 74 women with a mean age of 64.6±14.4 (SD) (range: 19-93 years). Raw data images were reconstructed with iterative reconstruction. Dose length product (DLP) and effective dose for both protocols were compared. Images were independently evaluated by two radiologists for image-quality, diagnostic quality, and confidence level.
RESULTS: DLP for STD and ULD were respectively 215.4±92.0 (SD) mGy·cm (range: 76-599mGy·cm) and 90.7±37.2 (SD) mGy·cm (range: 32-254mGy·cm). Effective dose for STD and ULD CT were 3.2±1.4 (SD) mSv (range: 1.1-9.0mSv) and 1.4±0.6 (SD) mSv (range: 0.5 to 3.8mSv). A significant 58% dose reduction was found between the two protocols (P<0.05). Noise, signal-to-noise ratio and contrast-to-noise ratio were higher with the ULD protocol compared to the STD protocol. No differences in subjective image quality were found between the two protocols. STD CT revealed focal liver lesions in 80 patients and ULD CT in 70 patients (P<0.05). ULD protocol resulted in a sensitivity of 83.8% and a specificity of 96.9% for the diagnosis of focal liver lesions although it was not able to characterize them properly (Se 62.5%).
CONCLUSION: STD CT helps detect and characterize focal liver lesions. ULD CT offers good performance to detect focal liver lesions but with lower performances for lesion characterization.
Copyright © 2017 Editions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Computed tomography (CT); Focal liver lesion; Iterative reconstruction; Lesion detection; Oncology

Mesh:

Year:  2018        PMID: 29396085     DOI: 10.1016/j.diii.2017.11.003

Source DB:  PubMed          Journal:  Diagn Interv Imaging        ISSN: 2211-5684            Impact factor:   4.026


  6 in total

1.  Optimization of radiation dose for CT detection of lytic and sclerotic bone lesions: a phantom study.

Authors:  J Greffier; J Frandon; F Pereira; A Hamard; J P Beregi; A Larbi; P Omoumi
Journal:  Eur Radiol       Date:  2019-09-10       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.  Comparison of acquisition and iterative reconstruction parameters in abdominal computed tomography-guided procedures: a phantom study.

Authors:  Julien Frandon; Philippe Akessoul; Aymeric Hamard; Edinaud Bezandry; Romaric Loffroy; Takieddine Addala; Martin M Bertrand; Jean-Paul Beregi; Joël Greffier
Journal:  Quant Imaging Med Surg       Date:  2022-01

4.  Effect of a new deep learning image reconstruction algorithm for abdominal computed tomography imaging on image quality and dose reduction compared with two iterative reconstruction algorithms: a phantom study.

Authors:  Joël Greffier; Djamel Dabli; Aymeric Hamard; Asmaa Belaouni; Philippe Akessoul; Julien Frandon; Jean-Paul Beregi
Journal:  Quant Imaging Med Surg       Date:  2022-01

5.  A study of using a deep learning image reconstruction to improve the image quality of extremely low-dose contrast-enhanced abdominal CT for patients with hepatic lesions.

Authors:  Le Cao; Xiang Liu; Jianying Li; Tingting Qu; Lihong Chen; Yannan Cheng; Jieliang Hu; Jingtao Sun; Jianxin Guo
Journal:  Br J Radiol       Date:  2020-12-11       Impact factor: 3.039

6.  A prospective study on the use of ultralow-dose computed tomography with iterative reconstruction for the follow-up of patients liver and renal abscess.

Authors:  Nieun Seo; Mi-Suk Park; Jun Yong Choi; Joon-Sup Yeom; Myeong-Jin Kim; Yong Eun Chung; Nam Su Ku
Journal:  PLoS One       Date:  2021-02-12       Impact factor: 3.240

  6 in total

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