Literature DB >> 24281269

Current knowledge on tumour induction by computed tomography should be carefully used.

Cristian Candela-Juan1, Alegría Montoro, Enrique Ruiz-Martínez, Juan Ignacio Villaescusa, Luis Martí-Bonmatí.   

Abstract

Risks associated to ionising radiation from medical imaging techniques have focused the attention of the medical society and general population. This risk is aimed to determine the probability that a tumour is induced as a result of a computed tomography (CT) examination since it makes nowadays the biggest contribution to the collective dose. Several models of cancer induction have been reported in the literature, with diametrically different implications. This article reviews those models, focusing on the ones used by the scientific community to estimate CT detriments. Current estimates of the probability that a CT examination induces cancer are reported, highlighting its low magnitude (near the background level) and large sources of uncertainty. From this objective review, it is concluded that epidemiological data with more accurate dosimetric estimates are needed. Prediction of the number of tumours that will be induced in population exposed to ionising radiation should be avoided or, if given, it should be accompanied by a realistic evaluation of its uncertainty and of the advantages of CTs. Otherwise they may have a negative impact in both the medical community and the patients. Reducing doses even more is not justified if that compromises clinical image quality in a necessary investigation. Key Points • Predictions of radiation-induced cancer should be discussed alongside benefits of imaging. • Estimates of induced cancers have noticeable uncertainties that should always be highlighted. • There is controversy about the acceptance of the linear no-threshold model. • Estimated extra risks of cancer are close to the background level. • Patients should not be alarmed by potential cancer induction by CT examinations.

Entities:  

Mesh:

Year:  2013        PMID: 24281269     DOI: 10.1007/s00330-013-3047-z

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  52 in total

1.  Falling prey to the sunk cost bias: a potential harm of patient radiation dose histories.

Authors:  Jonathan D Eisenberg; H Benjamin Harvey; Donald A Moore; G Scott Gazelle; Pari V Pandharipande
Journal:  Radiology       Date:  2012-06       Impact factor: 11.105

2.  The 2007 Recommendations of the International Commission on Radiological Protection. ICRP publication 103.

Authors: 
Journal:  Ann ICRP       Date:  2007

Review 3.  Ionizing radiation-induced bystander effects, potential targets for modulation of radiotherapy.

Authors:  Joanna Rzeszowska-Wolny; Waldemar M Przybyszewski; Maria Widel
Journal:  Eur J Pharmacol       Date:  2009-10-14       Impact factor: 4.432

4.  The effect of dose heterogeneity on radiation risk in medical imaging.

Authors:  Ehsan Samei; Xiang Li; Baiyu Chen; Robert Reiman
Journal:  Radiat Prot Dosimetry       Date:  2012-10-31       Impact factor: 0.972

5.  RadRAT: a radiation risk assessment tool for lifetime cancer risk projection.

Authors:  Amy Berrington de Gonzalez; A Iulian Apostoaei; Lene H S Veiga; Preetha Rajaraman; Brian A Thomas; F Owen Hoffman; Ethel Gilbert; Charles Land
Journal:  J Radiol Prot       Date:  2012-07-19       Impact factor: 1.394

Review 6.  Cancer induction caused by radiation due to computed tomography: a critical note.

Authors:  Ernest K J Pauwels; Michel Bourguignon
Journal:  Acta Radiol       Date:  2011-07-08       Impact factor: 1.990

7.  Radiation carcinogenesis at low doses.

Authors:  H H Rossi; A M Kellerer
Journal:  Science       Date:  1972-01-14       Impact factor: 47.728

8.  PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure.

Authors:  Wolfgang Eschner; Matthias Schmidt; Markus Dietlein; Harald Schicha
Journal:  Eur J Nucl Med Mol Imaging       Date:  2010-01       Impact factor: 9.236

9.  Estimating radiation-induced cancer risks at very low doses: rationale for using a linear no-threshold approach.

Authors:  David J Brenner; Rainer K Sachs
Journal:  Radiat Environ Biophys       Date:  2006-02-10       Impact factor: 1.925

10.  Cancer risk in 680,000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 million Australians.

Authors:  John D Mathews; Anna V Forsythe; Zoe Brady; Martin W Butler; Stacy K Goergen; Graham B Byrnes; Graham G Giles; Anthony B Wallace; Philip R Anderson; Tenniel A Guiver; Paul McGale; Timothy M Cain; James G Dowty; Adrian C Bickerstaffe; Sarah C Darby
Journal:  BMJ       Date:  2013-05-21
View more
  5 in total

1.  Imaging the Parasinus Region with a Third-Generation Dual-Source CT and the Effect of Tin Filtration on Image Quality and Radiation Dose.

Authors:  M M Lell; M S May; M Brand; A Eller; T Buder; E Hofmann; M Uder; W Wuest
Journal:  AJNR Am J Neuroradiol       Date:  2015-03-26       Impact factor: 3.825

2.  Evaluation of Effective Dose from CT Scans for Overweight and Obese Adult Patients Using the VirtualDose Software.

Authors:  Baohui Liang; Yiming Gao; Zhi Chen; X George Xu
Journal:  Radiat Prot Dosimetry       Date:  2017-04-25       Impact factor: 0.972

3.  Evaluation of dose reduction and image quality in CT colonography: comparison of low-dose CT with iterative reconstruction and routine-dose CT with filtered back projection.

Authors:  Koichi Nagata; Masanori Fujiwara; Hidenori Kanazawa; Tomohiro Mogi; Nao Iida; Toru Mitsushima; Alan T Lefor; Hideharu Sugimoto
Journal:  Eur Radiol       Date:  2014-08-06       Impact factor: 5.315

4.  Validity of the size-specific dose estimate in adults undergoing coronary CT angiography: comparison with the volume CT dose index.

Authors:  Masafumi Kidoh; Daisuke Utsunomiya; Seitaro Oda; Yoshinori Funama; Hideaki Yuki; Takeshi Nakaura; Noriyuki Kai; Takeshi Nozaki; Yasuyuki Yamashita
Journal:  Int J Cardiovasc Imaging       Date:  2015-10-06       Impact factor: 2.357

5.  The investigation of dose and image quality of chest computed tomography using different combinations of noise index and adaptive statistic iterative reconstruction level.

Authors:  Supawitoo Sookpeng; Colin J Martin; Chitsanupong Butdee
Journal:  Indian J Radiol Imaging       Date:  2019 Jan-Mar
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.