Identifying predictors of patient radiation dose during uterine artery embolisation

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Abstract

Introduction

Uterine artery embolisation (UAE) is regarded as a safe and effective treatment for symptomatic uterine fibroids and/or adenomyosis. Dose reduction during UAE is critical for this reproductive‐age patient population to minimise the risks of radiation‐induced effects. The aim of this study was to identify the predictors of radiation dose which can be controlled and optimised for patients during UAE.

Methods

A total of 150 patients between June 2018 and August 2019 were included in this study. Demographic and clinical information such as age, body mass index (BMI), total number of fibroids, total fibroid volume, total uterus volume and dosimetric measurements on Dose Area Product (DAP), Air Kerma (AK) and fluoroscopy time were recorded. Total digital subtraction angiography (DSA), total conventional roadmap (CRM), total last‐image hold (LIH) and total fluoroscopy were calculated from the dose report. Multiple linear regression analysis was used to identify the independent predictor variables of total dose (DAP) using a regression model.

Results

Total DSA, total CRM and total LIH were identified as the determinants of dose for UAE ( P < 0.05) and together accounted for 95.2% of the variance.

Conclusions

This study identified the key imaging predictors of dose for UAE. Total DSA, total CRM and total LIH were shown to have a greater impact on the outcome DAP compared to other demographic or dosimetric measurements. Optimisation of these predictors during future UAE procedures can facilitate radiation dose reduction to the pelvis and reproductive organs.

Abstract

The predictors of patient radiation dose have been identified for the interventional radiology procedure known as uterine artery embolisation (UAE). A regression model entered and identified total digital subtraction angiography (DSA), total conventional roadmap (CRM) and total last‐image hold (LIH) as the determinants of dose over demographic and other angiographic variables. Control of these dose predictors can potentially minimise radiation dose exposure to this reproductive‐age patient population. Dose optimisation can be attained to reduce the risks of tissue effects and/or stochastic effects associated with irradiating the pelvis region.

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Most cited references 30

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Author and article information

Contributors

Don J. Nocum:

ORCID: https://orcid.org/0000-0003-4194-7287

donjohnson.nocum@sah.org.au

Journal

Journal ID (nlm-ta): J Med Radiat Sci

Journal ID (iso-abbrev): J Med Radiat Sci

Journal ID (doi): 10.1002/(ISSN)2051-3909

Journal ID (publisher-id): JMRS

Title: Journal of Medical Radiation Sciences

Publisher: John Wiley and Sons Inc. (Hoboken )

ISSN (Print): 2051-3895

ISSN (Electronic): 2051-3909

Publication date (Electronic): 13 November 2020

Publication date (Print): June 2021

Volume: 68

Issue: 2 ( doiID: 10.1002/jmrs.v68.2 )

Pages: 131-138

Affiliations

[ ¹ ] San Radiology & Nuclear Medicine Sydney Adventist Hospital Wahroonga New South Wales Australia

[ ² ] Discipline of Medical Imaging Science School of Health Sciences, Faculty of Medicine and Health The University of Sydney New South Wales Australia

[ ³ ] Discipline of Exercise and Sports Science School of Health Sciences, Faculty of Medicine and Health The University of Sydney New South Wales Australia

[ ⁴ ] Department of Radiology Sydney Adventist Hospital Clinical School University of Sydney Wahroonga New South Wales Australia

[ ⁵ ] Faculty of Medicine School of Medical Sciences University of New South Wales New South Wales Australia

Author notes

[*] [* ] Correspondence

Don J. Nocum, SAN Radiology & Nuclear Medicine, Sydney Adventist Hospital, 185 Fox Valley Road, Wahroonga 2076, New South Wales, Australia. Tel: +61 02 948 09821; Fax: +61 02 948 09845; Mobile: 0417 949 428.

Email: donjohnson.nocum@ 123456sah.org.au

Author information

Don J. Nocum https://orcid.org/0000-0003-4194-7287

John Robinson https://orcid.org/0000-0001-9357-0990

Mark Halaki https://orcid.org/0000-0002-6721-6354

Eisen Liang https://orcid.org/0000-0003-0306-4133

Nadine Thompson https://orcid.org/0000-0002-7382-2684

Michelle Moscova https://orcid.org/0000-0001-7186-4242

Warren Reed https://orcid.org/0000-0002-8937-2198

Article

Publisher ID: JMRS450

DOI: 10.1002/jmrs.450

PMC ID: 8168071

PubMed ID: 33185033

SO-VID: c981e3d1-622b-4f71-8326-586e8a30527f

Copyright © © 2020 The Authors. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology

License:

This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

History

Date revision received : 20 October 2020

Date received : 06 February 2020

Date accepted : 21 October 2020

Page count

Figures: 1, Tables: 5, Pages: 8, Words: 6234

Custom metadata

source-schema-version-number 2.0

cover-date June 2021

details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.2 mode:remove_FC converted:01.06.2021

Keywords: dose optimisation,interventional radiology,radiation dose,regression analysis,uterine artery embolisation

Data availability:

Keywords: dose optimisation, interventional radiology, radiation dose, regression analysis, uterine artery embolisation

Identifying predictors of patient radiation dose during uterine artery embolisation

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Abstract

Introduction

Methods

Results

Conclusions

Abstract

Related collections

International Journal of Applied Technology in Medical Sciences

Most cited references 30

Validation, updating and impact of clinical prediction rules: a review.

Fluoroscopically guided interventional procedures: a review of radiation effects on patients' skin and hair.

Relationships between body mass index and well-being in young Australian women.

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Contributors

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