Literature DB >> 25458225

Ultra-low dose abdominal MDCT: using a knowledge-based Iterative Model Reconstruction technique for substantial dose reduction in a prospective clinical study.

Ranish Deedar Ali Khawaja1, Sarabjeet Singh2, Michael Blake2, Mukesh Harisinghani2, Garry Choy2, Ali Karosmangulu2, Atul Padole2, Synho Do2, Kevin Brown3, Richard Thompson3, Thomas Morton3, Nilgoun Raihani3, Thomas Koehler4, Mannudeep K Kalra2.   

Abstract

PURPOSE: To assess lesion detection and image quality parameters of a knowledge-based Iterative Model Reconstruction (IMR) in reduced dose (RD) abdominal CT examinations.
MATERIALS AND METHODS: This IRB-approved prospective study included 82 abdominal CT examinations performed for 41 consecutive patients (mean age, 62 ± 12 years; F:M 28:13) who underwent a RD CT (SSDE, 1.5 mGy ± 0.4 [∼ 0.9 mSv] at 120 kV with 17-20 mAs/slice) immediately after their standard dose (SD) CT exam (10 mGy ± 3 [∼ 6 mSv] at 120 kV with automatic exposure control) on 256 MDCT (iCT, Philips Healthcare). SD data were reconstructed using filtered back projection (FBP). RD data were reconstructed with FBP and IMR. Four radiologists used a five-point scale (1=image quality better than SD CT to 5=image quality unacceptable) to assess both subjective image quality and artifacts. Lesions were first detected on RD FBP images. RD IMR and RD FBP images were then compared side-by-side to SD-FBP images in an independent, randomized and blinded fashion. Friedman's test and intraclass correlation coefficient were used for data analysis. Objective measurements included image noise and attenuation as well as noise spectral density (NSD) curves to assess the noise in frequency domain were obtained. In addition, a low-contrast phantom study was performed.
RESULTS: All true lesions (ranging from 32 to 55) on SD FBP images were detected on RD IMR images across all patients. RD FBP images were unacceptable for subjective image quality. Subjective ratings showed acceptable image quality for IMR for organ margins, soft-tissue structures, and retroperitoneal lymphadenopathy, compared to RD FBP in patients with a BMI ≤ 25 kg/m(2) (median-range, 2-3). Irrespective of patient BMI, subjective ratings for hepatic/renal cysts, stones and colonic diverticula were significantly better with RD IMR images (P<0.01). Objective image noise for RD FBP was 57-66% higher, and for RD IMR was 8-56% lower than that for SD-FBP (P<0.01). NSD showed significantly lower noise in the frequency domain with IMR in all patients compared to FBP.
CONCLUSION: IMR considerably improved both objective and subjective image quality parameters of RD abdominal CT images compared to FBP in patients with BMI less than or equal to 25 kg/m(2).
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Abdominal MDCT; Iterative reconstruction technique; Radiation dose reduction

Mesh:

Year:  2014        PMID: 25458225     DOI: 10.1016/j.ejrad.2014.09.022

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


  15 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.  Assessment of sub-milli-sievert abdominal computed tomography with iterative reconstruction techniques of different vendors.

Authors:  Atul Padole; Nisha Sainani; Diego Lira; Ranish Deedar Ali Khawaja; Sarvenaz Pourjabbar; Roberto Lo Gullo; Alexi Otrakji; Mannudeep K Kalra
Journal:  World J Radiol       Date:  2016-06-28

Review 3.  Regularization strategies in statistical image reconstruction of low-dose x-ray CT: A review.

Authors:  Hao Zhang; Jing Wang; Dong Zeng; Xi Tao; Jianhua Ma
Journal:  Med Phys       Date:  2018-09-10       Impact factor: 4.071

4.  Diagnostic performance of reduced-dose CT with a hybrid iterative reconstruction algorithm for the detection of hypervascular liver lesions: a phantom study.

Authors:  Atsushi Nakamoto; Yoshikazu Tanaka; Hiroshi Juri; Go Nakai; Shushi Yoshikawa; Yoshifumi Narumi
Journal:  Eur Radiol       Date:  2016-12-12       Impact factor: 5.315

Review 5.  Imaging in the diagnosis of pediatric urolithiasis.

Authors:  Gabrielle C Colleran; Michael J Callahan; Harriet J Paltiel; Caleb P Nelson; Bartley G Cilento; Michelle A Baum; Jeanne S Chow
Journal:  Pediatr Radiol       Date:  2016-11-04

6.  Determination of optimal imaging settings for urolithiasis CT using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR): a physical human phantom study.

Authors:  Se Y Choi; Seung H Ahn; Jae D Choi; Jung H Kim; Byoung-Il Lee; Jeong-In Kim; Sung B Park
Journal:  Br J Radiol       Date:  2015-11-18       Impact factor: 3.039

7.  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

8.  Improved image quality of low-dose CT combining with iterative model reconstruction algorithm for response assessment in patients after treatment of malignant tumor.

Authors:  Xiaoyan Xin; Jingtao Shen; Shangwen Yang; Song Liu; Anning Hu; Bin Zhu; Yan Jiang; Baoxin Li; Bing Zhang
Journal:  Quant Imaging Med Surg       Date:  2018-08

9.  Application of low-dose CT combined with model-based iterative reconstruction algorithm in oncologic patients during follow-up: dose reduction and image quality.

Authors:  Davide Ippolito; Cesare Maino; Anna Pecorelli; Ilaria Salemi; Davide Gandola; Luca Riva; Cammillo Talei Franzesi; Sandro Sironi
Journal:  Br J Radiol       Date:  2021-07-08       Impact factor: 3.629

10.  Comparison of image quality from filtered back projection, statistical iterative reconstruction, and model-based iterative reconstruction algorithms in abdominal computed tomography.

Authors:  Yu Kuo; Yi-Yang Lin; Rheun-Chuan Lee; Chung-Jung Lin; Yi-You Chiou; Wan-Yuo Guo
Journal:  Medicine (Baltimore)       Date:  2016-08       Impact factor: 1.889

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.