Correlation of treatment time to target volume for GammaPod treatments: A simple second calculation

Purpose The GammaPod is a novel device for stereotactic breast treatments that employs 25 rotating Co‐60 sources while the patient is continuously translated in three axes to deliver a highly conformal dose to the target. There is no commercial software available for independent second calculations....

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Veröffentlicht in:Journal of Applied Clinical Medical Physics 2022-04, Vol.23 (4), p.e13524-n/a
Hauptverfasser: Chen, Leah, Becker, Stewart J., McAvoy, Sarah Anne, Nichols, Elizabeth M., Guerrero, Mariana
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container_issue 4
container_start_page e13524
container_title Journal of Applied Clinical Medical Physics
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creator Chen, Leah
Becker, Stewart J.
McAvoy, Sarah Anne
Nichols, Elizabeth M.
Guerrero, Mariana
description Purpose The GammaPod is a novel device for stereotactic breast treatments that employs 25 rotating Co‐60 sources while the patient is continuously translated in three axes to deliver a highly conformal dose to the target. There is no commercial software available for independent second calculations. The purpose of this study is to determine an efficient way to estimate GammaPod treatment times based on target volume and use it as a second calculation for patient‐specific quality assurance. Methods Fifty‐nine GammaPod (Xcision Medical Systems, LLC.) breast cancer patient treatments were used as the fitting dataset for this study. Similar to the Curie‐seconds concept in brachytherapy, we considered dose‐rate × time/(prescribed dose) as a function of target volumes. Using a MATLAB (Mathworks, Natick, MA, USA) script, we generated linear (with 95% confidence interval (CI)) and quadratic fits and tested the resulting equations on an additional set of 30 patients. Results We found a strong correlation between the dose‐rate × time/(prescribed dose) and patients’ target volumes for both the linear and quadratic models. The linear fit was selected for use and using the polyval function in MATLAB, a 95% CI graph was created to depict the accuracy of the prediction for treatment times. Testing the model on 30 additional patients with target volumes ranging from 20 to 188 cc yielded treatment times from 10 to 25 min that in all cases were within the predicted CI. The average absolute difference between the predicted and actual treatment times was 1.0 min (range 0–3.3 min). The average percent difference was 5.8% (range 0%–18.4%). Conclusion This work has resulted in a viable independent calculation for GammaPod treatment times. This method has been implemented as a spreadsheet that is ready for clinical use to predict and verify the accuracy of breast cancer treatment times.
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There is no commercial software available for independent second calculations. The purpose of this study is to determine an efficient way to estimate GammaPod treatment times based on target volume and use it as a second calculation for patient‐specific quality assurance. Methods Fifty‐nine GammaPod (Xcision Medical Systems, LLC.) breast cancer patient treatments were used as the fitting dataset for this study. Similar to the Curie‐seconds concept in brachytherapy, we considered dose‐rate × time/(prescribed dose) as a function of target volumes. Using a MATLAB (Mathworks, Natick, MA, USA) script, we generated linear (with 95% confidence interval (CI)) and quadratic fits and tested the resulting equations on an additional set of 30 patients. Results We found a strong correlation between the dose‐rate × time/(prescribed dose) and patients’ target volumes for both the linear and quadratic models. The linear fit was selected for use and using the polyval function in MATLAB, a 95% CI graph was created to depict the accuracy of the prediction for treatment times. Testing the model on 30 additional patients with target volumes ranging from 20 to 188 cc yielded treatment times from 10 to 25 min that in all cases were within the predicted CI. The average absolute difference between the predicted and actual treatment times was 1.0 min (range 0–3.3 min). The average percent difference was 5.8% (range 0%–18.4%). Conclusion This work has resulted in a viable independent calculation for GammaPod treatment times. This method has been implemented as a spreadsheet that is ready for clinical use to predict and verify the accuracy of breast cancer treatment times.</description><identifier>ISSN: 1526-9914</identifier><identifier>EISSN: 1526-9914</identifier><identifier>DOI: 10.1002/acm2.13524</identifier><identifier>PMID: 35132771</identifier><language>eng</language><publisher>United States: John Wiley &amp; Sons, Inc</publisher><subject>Analysis ; Brachytherapy - methods ; Breast cancer ; Breast Neoplasms - radiotherapy ; Breast Neoplasms - surgery ; Cancer ; Cancer therapies ; Care and treatment ; Confidence intervals ; Female ; GammaPod ; Humans ; Lumpectomy ; Medical equipment ; Patients ; Physiological apparatus ; Radiation ; Radiosurgery - methods ; Radiotherapy Dosage ; Radiotherapy Planning, Computer-Assisted - methods ; second calculation ; Technical Note ; Technical Notes</subject><ispartof>Journal of Applied Clinical Medical Physics, 2022-04, Vol.23 (4), p.e13524-n/a</ispartof><rights>2022 The Authors. published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine</rights><rights>2022 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.</rights><rights>COPYRIGHT 2022 John Wiley &amp; Sons, Inc.</rights><rights>2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c4744-1bac6b60c40f7f0312c79980b1bcc09efdc13a640f124db95bb2636aa50c80c63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8992953/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8992953/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,1417,11562,27924,27925,45574,45575,46052,46476,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35132771$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chen, Leah</creatorcontrib><creatorcontrib>Becker, Stewart J.</creatorcontrib><creatorcontrib>McAvoy, Sarah Anne</creatorcontrib><creatorcontrib>Nichols, Elizabeth M.</creatorcontrib><creatorcontrib>Guerrero, Mariana</creatorcontrib><title>Correlation of treatment time to target volume for GammaPod treatments: A simple second calculation</title><title>Journal of Applied Clinical Medical Physics</title><addtitle>J Appl Clin Med Phys</addtitle><description>Purpose The GammaPod is a novel device for stereotactic breast treatments that employs 25 rotating Co‐60 sources while the patient is continuously translated in three axes to deliver a highly conformal dose to the target. There is no commercial software available for independent second calculations. The purpose of this study is to determine an efficient way to estimate GammaPod treatment times based on target volume and use it as a second calculation for patient‐specific quality assurance. Methods Fifty‐nine GammaPod (Xcision Medical Systems, LLC.) breast cancer patient treatments were used as the fitting dataset for this study. Similar to the Curie‐seconds concept in brachytherapy, we considered dose‐rate × time/(prescribed dose) as a function of target volumes. Using a MATLAB (Mathworks, Natick, MA, USA) script, we generated linear (with 95% confidence interval (CI)) and quadratic fits and tested the resulting equations on an additional set of 30 patients. Results We found a strong correlation between the dose‐rate × time/(prescribed dose) and patients’ target volumes for both the linear and quadratic models. The linear fit was selected for use and using the polyval function in MATLAB, a 95% CI graph was created to depict the accuracy of the prediction for treatment times. Testing the model on 30 additional patients with target volumes ranging from 20 to 188 cc yielded treatment times from 10 to 25 min that in all cases were within the predicted CI. The average absolute difference between the predicted and actual treatment times was 1.0 min (range 0–3.3 min). The average percent difference was 5.8% (range 0%–18.4%). Conclusion This work has resulted in a viable independent calculation for GammaPod treatment times. 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There is no commercial software available for independent second calculations. The purpose of this study is to determine an efficient way to estimate GammaPod treatment times based on target volume and use it as a second calculation for patient‐specific quality assurance. Methods Fifty‐nine GammaPod (Xcision Medical Systems, LLC.) breast cancer patient treatments were used as the fitting dataset for this study. Similar to the Curie‐seconds concept in brachytherapy, we considered dose‐rate × time/(prescribed dose) as a function of target volumes. Using a MATLAB (Mathworks, Natick, MA, USA) script, we generated linear (with 95% confidence interval (CI)) and quadratic fits and tested the resulting equations on an additional set of 30 patients. Results We found a strong correlation between the dose‐rate × time/(prescribed dose) and patients’ target volumes for both the linear and quadratic models. The linear fit was selected for use and using the polyval function in MATLAB, a 95% CI graph was created to depict the accuracy of the prediction for treatment times. Testing the model on 30 additional patients with target volumes ranging from 20 to 188 cc yielded treatment times from 10 to 25 min that in all cases were within the predicted CI. The average absolute difference between the predicted and actual treatment times was 1.0 min (range 0–3.3 min). The average percent difference was 5.8% (range 0%–18.4%). Conclusion This work has resulted in a viable independent calculation for GammaPod treatment times. This method has been implemented as a spreadsheet that is ready for clinical use to predict and verify the accuracy of breast cancer treatment times.</abstract><cop>United States</cop><pub>John Wiley &amp; Sons, Inc</pub><pmid>35132771</pmid><doi>10.1002/acm2.13524</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record>
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subjects Analysis
Brachytherapy - methods
Breast cancer
Breast Neoplasms - radiotherapy
Breast Neoplasms - surgery
Cancer
Cancer therapies
Care and treatment
Confidence intervals
Female
GammaPod
Humans
Lumpectomy
Medical equipment
Patients
Physiological apparatus
Radiation
Radiosurgery - methods
Radiotherapy Dosage
Radiotherapy Planning, Computer-Assisted - methods
second calculation
Technical Note
Technical Notes
title Correlation of treatment time to target volume for GammaPod treatments: A simple second calculation
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