Literature DB >> 24572380

Influence of radiation dose and iterative reconstruction algorithms for measurement accuracy and reproducibility of pulmonary nodule volumetry: A phantom study.

Hyungjin Kim1, Chang Min Park2, Yong Sub Song3, Sang Min Lee4, Jin Mo Goo5.   

Abstract

PURPOSE: To evaluate the influence of radiation dose settings and reconstruction algorithms on the measurement accuracy and reproducibility of semi-automated pulmonary nodule volumetry.
MATERIALS AND METHODS: CT scans were performed on a chest phantom containing various nodules (10 and 12mm; +100, -630 and -800HU) at 120kVp with tube current-time settings of 10, 20, 50, and 100mAs. Each CT was reconstructed using filtered back projection (FBP), iDose(4) and iterative model reconstruction (IMR). Semi-automated volumetry was performed by two radiologists using commercial volumetry software for nodules at each CT dataset. Noise, contrast-to-noise ratio and signal-to-noise ratio of CT images were also obtained. The absolute percentage measurement errors and differences were then calculated for volume and mass. The influence of radiation dose and reconstruction algorithm on measurement accuracy, reproducibility and objective image quality metrics was analyzed using generalized estimating equations.
RESULTS: Measurement accuracy and reproducibility of nodule volume and mass were not significantly associated with CT radiation dose settings or reconstruction algorithms (p>0.05). Objective image quality metrics of CT images were superior in IMR than in FBP or iDose(4) at all radiation dose settings (p<0.05).
CONCLUSION: Semi-automated nodule volumetry can be applied to low- or ultralow-dose chest CT with usage of a novel iterative reconstruction algorithm without losing measurement accuracy and reproducibility.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Keywords:  Computer-assisted image processing; Lung neoplasms; Multidetector computed tomography; Pulmonary nodule; Radiation dosage; Reproducibility of results

Mesh:

Year:  2014        PMID: 24572380     DOI: 10.1016/j.ejrad.2014.01.025

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  14 in total

1.  Knowledge-based iterative model reconstruction: comparative image quality and radiation dose with a pediatric computed tomography phantom.

Authors:  Young Jin Ryu; Young Hun Choi; Jung-Eun Cheon; Seongmin Ha; Woo Sun Kim; In-One Kim
Journal:  Pediatr Radiol       Date:  2015-11-06

2.  Ultra-low-dose CT with model-based iterative reconstruction (MBIR): detection of ground-glass nodules in an anthropomorphic phantom study.

Authors:  Cristiano Rampinelli; Daniela Origgi; Vittoria Vecchi; Luigi Funicelli; Sara Raimondi; Paul Deak; Massimo Bellomi
Journal:  Radiol Med       Date:  2015-02-06       Impact factor: 3.469

3.  Usefulness of model-based iterative reconstruction in semi-automatic volumetry for ground-glass nodules at ultra-low-dose CT: a phantom study.

Authors:  Shuki Maruyama; Yasuhiro Fukushima; Yuta Miyamae; Koji Koizumi
Journal:  Radiol Phys Technol       Date:  2018-02-10

4.  Deep-learning reconstruction for ultra-low-dose lung CT: Volumetric measurement accuracy and reproducibility of artificial ground-glass nodules in a phantom study.

Authors:  Ryoji Mikayama; Takashi Shirasaka; Tsukasa Kojima; Yuki Sakai; Hidetake Yabuuchi; Masatoshi Kondo; Toyoyuki Kato
Journal:  Br J Radiol       Date:  2021-12-15       Impact factor: 3.039

5.  Accuracy of two deep learning-based reconstruction methods compared with an adaptive statistical iterative reconstruction method for solid and ground-glass nodule volumetry on low-dose and ultra-low-dose chest computed tomography: A phantom study.

Authors:  Cherry Kim; Thomas Kwack; Wooil Kim; Jaehyung Cha; Zepa Yang; Hwan Seok Yong
Journal:  PLoS One       Date:  2022-06-23       Impact factor: 3.752

6.  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

7.  Improved repeatability of subsolid nodule measurement in low-dose lung screening with monoenergetic images: a phantom study.

Authors:  Jihang Kim; Kyung Hee Lee; Junghoon Kim; Yoon Joo Shin; Kyung Won Lee
Journal:  Quant Imaging Med Surg       Date:  2019-02

8.  Quantitative assessment of nonsolid pulmonary nodule volume with computed tomography in a phantom study.

Authors:  Marios A Gavrielides; Benjamin P Berman; Mark Supanich; Kurt Schultz; Qin Li; Nicholas Petrick; Rongping Zeng; Jenifer Siegelman
Journal:  Quant Imaging Med Surg       Date:  2017-12

9.  Optimization of imaging parameters in chest CT for COVID-19 patients: an experimental phantom study.

Authors:  Yantao Niu; Shunxing Huang; Huan Zhang; Shuo Li; Xiaoting Li; Zhibin Lv; Shuo Yan; Wei Fan; Yanlong Zhai; Eddy Wong; Kexin Wang; Zongrui Zhang; Budong Chen; Ruming Xie; Junfang Xian
Journal:  Quant Imaging Med Surg       Date:  2021-01

10.  Comparison of virtual non-contrast dual-energy CT and a true non-contrast CT for contouring in radiotherapy of 3D printed lung tumour models in motion: a phantom study.

Authors:  Dominik Alexander Hering; Kai Kröger; Ralf W Bauer; Hans Theodor Eich; Uwe Haverkamp
Journal:  Br J Radiol       Date:  2020-10-01       Impact factor: 3.039

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