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MRI-Linac Economics II: Rationalizing Schedules
Objective: Two benefits of MR-guided radiotherapy (MRgRT) are the ability to track target structures while treatment is being delivered and the ability to adapt plans daily for some lesions based on changing anatomy. These unique capacities come at two costs: increased capital for acquisition and gr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8836757/ https://www.ncbi.nlm.nih.gov/pubmed/35160318 http://dx.doi.org/10.3390/jcm11030869 |
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author | Johnstone, Peter A. S. Kerstiens, John Wasserman, Stuart Rosenberg, Stephen A. |
author_facet | Johnstone, Peter A. S. Kerstiens, John Wasserman, Stuart Rosenberg, Stephen A. |
author_sort | Johnstone, Peter A. S. |
collection | PubMed |
description | Objective: Two benefits of MR-guided radiotherapy (MRgRT) are the ability to track target structures while treatment is being delivered and the ability to adapt plans daily for some lesions based on changing anatomy. These unique capacities come at two costs: increased capital for acquisition and greatly decreased workflow. An adaptive gated stereotactic body radiotherapy (MRgART) treatment routinely takes ~90 min to perform and requires the presence of both a physician and a physicist. This may significantly limit daily capacity. We previously described how “simple cases” were necessary for proton facilities to allow for debt management. In this manuscript, we seek to determine the optimal scheduling of different MRgRT plans to recoup capital costs. Materials/Methods: We assumed an MR-linac (MRL) was completely scheduled with patients over workdays of varying duration. Treatment times and reimbursement data from our facility for varying complexities of patients were extrapolated for varying numbers treated daily. We then derived the number of adaptive and non-adaptive patients required daily to optimize the schedules. HOPPS data were used to model reimbursement. Results: A single MRL treating 14 non-gated, non-adaptive IMRT patients over an 8 h workday would take about 4.8 years to cover initial acquisition and installation costs. However, such patients may be more quickly and efficiently treated with a conventional linear accelerator, while MRgART cases may only be treated with an MRL. By treating four of these daily, that same MRL room would cover costs in 2.4 years. Personnel, maintenance costs, and profit further complicate any business case for treating non-adaptive patients or for extending hours. Conclusions: In our previously published paper discussing proton therapy, we noted that debt is not variable with capacity; this remains true with MRgRT. Different from protons, a clinically optimal case load of adaptive patients provides an optimal business case as well. This requires a large patient cadre to ensure continuing throughput. As improvements in MRgRT are brought to the clinic, shorter adaptive and non-adaptive treatment times will help improve the timeframe to recoup costs but will require even more appropriate patients. |
format | Online Article Text |
id | pubmed-8836757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88367572022-02-12 MRI-Linac Economics II: Rationalizing Schedules Johnstone, Peter A. S. Kerstiens, John Wasserman, Stuart Rosenberg, Stephen A. J Clin Med Article Objective: Two benefits of MR-guided radiotherapy (MRgRT) are the ability to track target structures while treatment is being delivered and the ability to adapt plans daily for some lesions based on changing anatomy. These unique capacities come at two costs: increased capital for acquisition and greatly decreased workflow. An adaptive gated stereotactic body radiotherapy (MRgART) treatment routinely takes ~90 min to perform and requires the presence of both a physician and a physicist. This may significantly limit daily capacity. We previously described how “simple cases” were necessary for proton facilities to allow for debt management. In this manuscript, we seek to determine the optimal scheduling of different MRgRT plans to recoup capital costs. Materials/Methods: We assumed an MR-linac (MRL) was completely scheduled with patients over workdays of varying duration. Treatment times and reimbursement data from our facility for varying complexities of patients were extrapolated for varying numbers treated daily. We then derived the number of adaptive and non-adaptive patients required daily to optimize the schedules. HOPPS data were used to model reimbursement. Results: A single MRL treating 14 non-gated, non-adaptive IMRT patients over an 8 h workday would take about 4.8 years to cover initial acquisition and installation costs. However, such patients may be more quickly and efficiently treated with a conventional linear accelerator, while MRgART cases may only be treated with an MRL. By treating four of these daily, that same MRL room would cover costs in 2.4 years. Personnel, maintenance costs, and profit further complicate any business case for treating non-adaptive patients or for extending hours. Conclusions: In our previously published paper discussing proton therapy, we noted that debt is not variable with capacity; this remains true with MRgRT. Different from protons, a clinically optimal case load of adaptive patients provides an optimal business case as well. This requires a large patient cadre to ensure continuing throughput. As improvements in MRgRT are brought to the clinic, shorter adaptive and non-adaptive treatment times will help improve the timeframe to recoup costs but will require even more appropriate patients. MDPI 2022-02-07 /pmc/articles/PMC8836757/ /pubmed/35160318 http://dx.doi.org/10.3390/jcm11030869 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Johnstone, Peter A. S. Kerstiens, John Wasserman, Stuart Rosenberg, Stephen A. MRI-Linac Economics II: Rationalizing Schedules |
title | MRI-Linac Economics II: Rationalizing Schedules |
title_full | MRI-Linac Economics II: Rationalizing Schedules |
title_fullStr | MRI-Linac Economics II: Rationalizing Schedules |
title_full_unstemmed | MRI-Linac Economics II: Rationalizing Schedules |
title_short | MRI-Linac Economics II: Rationalizing Schedules |
title_sort | mri-linac economics ii: rationalizing schedules |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8836757/ https://www.ncbi.nlm.nih.gov/pubmed/35160318 http://dx.doi.org/10.3390/jcm11030869 |
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