Variations in Demand Across England for the Magnetic Resonance-Linac Technology, Simulated Utilising Local-level Demographic and Cancer Data in the Malthus Project

Overview

Journal Clin Oncol (R Coll Radiol)

Specialty Oncology

Date 2021 Mar 29

PMID 33775495

Citations 1

Authors

T Mee

A J Vickers

R Jena

K J Kirkby

A Choudhury

N F Kirkby

Affiliations

Soon will be listed here.

Abstract

Aims: Cancer incidence varies across England, which affects the local-level demand for treatments. The magnetic resonance-linac (MR-linac) is a new radiotherapy technology that combines imaging and treatment. Here we model the demand and demand variations for the MR-linac across England.

Materials And Methods: Initial clinical indications were provided by the MR-linac consortium and introduced into the Malthus radiotherapy clinical decision trees. The Malthus model contains Clinical Commissioning Group (CCG) population, cancer incidence and stage presentation data (for lung and prostate) and simulated the demand for the MR-linac for all CCGs and Radiotherapy Operational Delivery Networks (RODN) across England.

Results: Based on the initial target clinical indications, the MR-linac could service 16% of England's fraction burden. The simulated fractions/million population demand/annum varies between 3000 and 10 600 fractions/million at the CCG level. Focussing only on the cancer population, the simulated fractions/1000 cancer cases demand/annum ranges from 1028 to 1195 fractions/1000 cases. If a national average for fractions/million demand was then used, at the RODN level, the variation from actual annual demand ranges from an overestimation of 8400 fractions to an underestimation of 5800 fractions. When using the national average fractions/1000 cases, the RODN demand varies from an overestimation of 3200 fractions to an underestimation of 3000 fractions.

Conclusions: Planning cancer services is complex due to regional variations in cancer burden. The variations in simulated demand of the MR-linac highlight the requirement to use local-level data when planning to introduce a new technology.

Citing Articles

Real-time 4D MRI using MR signature matching (MRSIGMA) on a 1.5T MR-Linac system.

Wu C, Murray V, Siddiq S, Tyagi N, Reyngold M, Crane C Phys Med Biol. 2023; 68(18).

PMID: 37619588 PMC: 10513779. DOI: 10.1088/1361-6560/acf3cc.

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