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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

  • Computed Tomography
  • Published:
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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.

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Data availability

Data are available at link https://zenodo.org/record/6491316#.YmgHqNNBy3A.

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Acknowledgements

The authors are grateful to Alessandra Trocino, librarian at the National Cancer Institute of Naples, Italy. Moreover, for the research collaboration, authors are grateful to Paolo Pariante, Giuditta Giannotti, Paola Gargiulo and Concetta Raiano (research support personnel) of Radiology Division, “Istituto Nazionale Tumori IRCCS Fondazione Pascale – IRCCS di Napoli”, Naples, I-80131, Italy

Funding

The authors have not disclosed any funding.

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Authors and Affiliations

  1. Medical Oncology Division, Igea SpA, Napoli, Italy

    Roberta Fusco

  2. Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, Naples, Italy

    Sergio Venanzio Setola, Nicola Raiano, Vincenza Granata & Antonella Petrillo

  3. Health Physics Unit, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, Naples, Italy

    Vincenzo Cerciello

  4. Radioprotection and innovative technologies, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131, Naples, Italy

    Biagio Pecori

Authors
  1. Roberta Fusco
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Correspondence to Biagio Pecori.

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Fusco, R., Setola, S.V., Raiano, N. et al. 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. Radiol med 127, 733–742 (2022). https://doi.org/10.1007/s11547-022-01481-w

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  • DOI: https://doi.org/10.1007/s11547-022-01481-w

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