Literature DB >> 34233459

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

Davide Ippolito1, Cesare Maino1, Anna Pecorelli1, Ilaria Salemi1, Davide Gandola1, Luca Riva1, Cammillo Talei Franzesi1, Sandro Sironi2.   

Abstract

OBJECTIVES: To compare image quality and radiation dose of CT images reconstructed with model-based iterative reconstruction (MBIR) and hybrid-iterative (HIR) algorithm in oncologic patients.
METHODS: 125 oncologic patients underwent both contrast-enhanced low- (100 kV), and standard (120 kV) dose CT, were enrolled. Image quality was assessed by using a 4-point Likert scale. CT attenuation values, expressed in Hounsfield unit (HU), were recorded within a regions of interest (ROI) of liver, spleen, paraspinal muscle, aortic lumen, and subcutaneous fat tissue. Image noise, expressed as standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated. Radiation dose were analyzed. Paired Student's t-test was used to compare all continuous variables.
RESULTS: The overall median score assessed as image quality for CT images with the MBIR algorithm was significantly higher in comparison with HIR [4 (range 3-4) vs 3 (3-4), p = 0.017].CT attenuation values and SD were significantly higher and lower, respectively, in all anatomic districts in images reconstructed with MBIR in comparison with HIR ones (all p < 0.001). SNR and CNR values were higher in CT images reconstructed with MBIR, reaching a significant difference in all districts (all p < 0.001). Radiation dose were significantly lower in the MBIR group compared with the HIR group (p < 0.001).
CONCLUSIONS: MBIR combined with low-kV setting allows an important dose reduction in whole-body CT imaging, reaching a better image quality both qualitatively and quantitatively. ADVANCES IN KNOWLEDGE: MBIR with low-dose approach allows a reduction of dose exposure, maintaining high image quality, especially in patients which deserve a longlasting follow-up.

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Year:  2021        PMID: 34233459      PMCID: PMC8764930          DOI: 10.1259/bjr.20201223

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.629


  20 in total

1.  Comparison of iterative model, hybrid iterative, and filtered back projection reconstruction techniques in low-dose brain CT: impact of thin-slice imaging.

Authors:  Takeshi Nakaura; Yuji Iyama; Masafumi Kidoh; Koichi Yokoyama; Seitaro Oda; Shinichi Tokuyasu; Kazunori Harada; Yasuyuki Yamashita
Journal:  Neuroradiology       Date:  2015-12-29       Impact factor: 2.804

2.  Computed tomography (CT) of the chest at less than 1 mSv: an ongoing prospective clinical trial of chest CT at submillisievert radiation doses with iterative model image reconstruction and iDose4 technique.

Authors:  Ranish Deedar Ali Khawaja; Sarabjeet Singh; Matthew Gilman; Amita Sharma; Synho Do; Sarvenaz Pourjabbar; Atul Padole; Diego Lira; Kevin Brown; Jo-Anne O Shepard; Mannudeep K Kalra
Journal:  J Comput Assist Tomogr       Date:  2014 Jul-Aug       Impact factor: 1.826

3.  Model-based iterative reconstruction technique for radiation dose reduction in chest CT: comparison with the adaptive statistical iterative reconstruction technique.

Authors:  Masaki Katsura; Izuru Matsuda; Masaaki Akahane; Jiro Sato; Hiroyuki Akai; Koichiro Yasaka; Akira Kunimatsu; Kuni Ohtomo
Journal:  Eur Radiol       Date:  2012-04-27       Impact factor: 5.315

Review 4.  Computed tomography--an increasing source of radiation exposure.

Authors:  David J Brenner; Eric J Hall
Journal:  N Engl J Med       Date:  2007-11-29       Impact factor: 91.245

5.  Model-based Iterative Reconstruction: A Promising Algorithm for Today's Computed Tomography Imaging.

Authors:  Lu Liu
Journal:  J Med Imaging Radiat Sci       Date:  2014-03-22

6.  Image quality of ct angiography using model-based iterative reconstruction in infants with congenital heart disease: Comparison with filtered back projection and hybrid iterative reconstruction.

Authors:  Qianjun Jia; Jian Zhuang; Jun Jiang; Jiahua Li; Meiping Huang; Changhong Liang
Journal:  Eur J Radiol       Date:  2016-10-17       Impact factor: 3.528

7.  CT scans in childhood and risk of leukaemia and brain tumours.

Authors:  David A Zopf; Glenn E Green
Journal:  Lancet       Date:  2012-11-17       Impact factor: 79.321

8.  Use of Model-Based Iterative Reconstruction (MBIR) in reduced-dose CT for routine follow-up of patients with malignant lymphoma: dose savings, image quality and phantom study.

Authors:  Edouard Hérin; François Gardavaud; Mélanie Chiaradia; Pauline Beaussart; Philippe Richard; Madeleine Cavet; Jean-François Deux; Corinne Haioun; Emmanuel Itti; Alain Rahmouni; Alain Luciani
Journal:  Eur Radiol       Date:  2015-03-08       Impact factor: 5.315

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

Authors:  Ranish Deedar Ali Khawaja; Sarabjeet Singh; Michael Blake; Mukesh Harisinghani; Garry Choy; Ali Karosmangulu; Atul Padole; Synho Do; Kevin Brown; Richard Thompson; Thomas Morton; Nilgoun Raihani; Thomas Koehler; Mannudeep K Kalra
Journal:  Eur J Radiol       Date:  2014-10-13       Impact factor: 3.528

10.  Knowledge-based iterative model reconstruction: Comparative image quality with low tube voltage cerebral CT angiography.

Authors:  Xinrui Wang; Chengcheng Zhu; Jing Li; Andrew J Degnan; Tao Jiang; Jianping Lu
Journal:  Medicine (Baltimore)       Date:  2018-07       Impact factor: 1.889

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  1 in total

1.  Deep Learning-Based Reconstruction vs. Iterative Reconstruction for Quality of Low-Dose Head-and-Neck CT Angiography with Different Tube-Voltage Protocols in Emergency-Department Patients.

Authors:  Marc Lenfant; Pierre-Olivier Comby; Kevin Guillen; Felix Galissot; Karim Haioun; Anthony Thay; Olivier Chevallier; Frédéric Ricolfi; Romaric Loffroy
Journal:  Diagnostics (Basel)       Date:  2022-05-21
  1 in total

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