Literature DB >> 35579854

Analysis of a monocentric computed tomography dosimetric database using a radiation dose index monitoring software: dose levels and alerts before and after the implementation of the adaptive statistical iterative reconstruction on CT images.

Roberta Fusco1, Sergio Venanzio Setola2, Nicola Raiano2, Vincenza Granata2, Vincenzo Cerciello3, Biagio Pecori4, Antonella Petrillo2.   

Abstract

OBJECTIVE: To analyze dosimetric data of a single center by a radiation dose index monitoring software evaluating quantitatively the dose reduction obtained with the implementation of the adaptive statistical iterative reconstruction (ASIR) on Computed Tomography in terms of both the value of the dose length product (DLP) and the alerts provided by the dose tool.
METHODS: Dosimetric quantities were acquired using Qaelum DOSE tool (QAELUM NV, Leuven-Heverlee, Belgium). Dose data pertaining to CT examinations were performed using a General Electric Healthcare CT tomography with 64 detectors. CT dose data were collected over 4 years (January 1, 2017 to December 31, 2020) and included CT dose length product (DLP). Moreover, all CT examinations that triggered a high radiation dose (twice the median for that study description), termed alerts on Dose tool, were retrieved for the analysis. Two radiologists retrospectively assessed CT examinations in consensus for the images quality and for the causes of the alerts issued. A Chi-square test was used to assess whether there were any statistically significant differences among categorical variable while a Kruskal Wallis test was considered to assess differences statistically significant for continuous variables.
RESULTS: Differences statistically significant were found for the DLP median values between the dosimetric data recorded on 2017-2018 versus 2019-2020. The differences were linked to the implementation of ASIR technique at the end of 2018 on the CT scanner. The highest percentage of alerts was reported in the CT study group "COMPLETE ABDOMEN + CHEST + HEAD" (range from 1.26% to 2.14%). A reduction year for year was relieved linked to the CT protocol optimization with a difference statistically significant. The highest percentage of alerts was linked to wrong study label/wrong study protocol selection with a range from 29 to 40%.
CONCLUSIONS: Automated methods of radiation dose data collection allowed for detailed radiation dose analysis according to protocol and equipment over time. The use of CT ASIR technique could determine considerable reduction in radiation dose.
© 2022. Italian Society of Medical Radiology.

Entities:  

Keywords:  ASIR; CT; Dose

Mesh:

Year:  2022        PMID: 35579854     DOI: 10.1007/s11547-022-01481-w

Source DB:  PubMed          Journal:  Radiol Med        ISSN: 0033-8362            Impact factor:   6.313


  4 in total

1.  Cloud-Based CT Dose Monitoring using the DICOM-Structured Report: Fully Automated Analysis in Regard to National Diagnostic Reference Levels.

Authors:  J Boos; A Meineke; C Rubbert; P Heusch; R S Lanzman; J Aissa; G Antoch; P Kröpil
Journal:  Rofo       Date:  2015-12-03

Review 2.  Use of radiation dose index monitoring software in a multicenter environment for CT dose optimization.

Authors:  Lucia Riccardi; Francesca De Monte; Fabiola Cretti; Silvia Pini; Sergio Zucca; Maria Grazia Quattrocchi; Daniela Origgi; Antonella Del Vecchio; Carlo Giordano; Piergiorgio Marini; Francesco Lisciandro; Edoardo Trevisiol; Daniele Zefiro; Claudia Cutaia; Loredana D'Ercole; Michele Gabusi; Alessandro Scaggion; Marta Paiusco
Journal:  Radiol Med       Date:  2018-08-09       Impact factor: 3.469

3.  Reducing Radiation Dose in Adult Head CT using Iterative Reconstruction - A Clinical Study in 177 Patients.

Authors:  D Kaul; J Kahn; L Huizing; E Wiener; U Grupp; G Böning; P Ghadjar; D M Renz; F Streitparth
Journal:  Rofo       Date:  2015-11-03

4.  Benchmarking adult CT-dose levels to regional and national references using a dose-tracking software: a multicentre experience.

Authors:  Lotte Pyfferoen; Tom H Mulkens; Federica Zanca; Timo De Bondt; Paul M Parizel; Jan W Casselman
Journal:  Insights Imaging       Date:  2017-09-07
  4 in total

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