Development of advanced preselection tools to reduce redundant plan comparisons in model-based selection of head and neck cancer patients for proton therapy

Makbule Tambas; Hans P van der Laan; Wouter Rutgers; Johanna G M van den Hoek; Edwin Oldehinkel; Tineke W H Meijer; Arjen van der Schaaf; Daniel Scandurra; Jeffrey Free; Stefan Both; Roel J H M Steenbakkers; Johannes A Langendijk

doi:10.1016/j.radonc.2021.04.012

Development of advanced preselection tools to reduce redundant plan comparisons in model-based selection of head and neck cancer patients for proton therapy

Makbule Tambas^*, Hans P van der Laan, Wouter Rutgers, Johanna G M van den Hoek, Edwin Oldehinkel, Tineke W H Meijer, Arjen van der Schaaf, Daniel Scandurra, Jeffrey Free, Stefan Both, Roel J H M Steenbakkers, Johannes A Langendijk

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

PURPOSE: In the Netherlands, head and neck cancer (HNC) patients are selected for proton therapy (PT) based on estimated normal tissue complication probability differences (ΔNTCP) between photons and protons, which requires a plan comparison (VMAT vs. IMPT). We aimed to develop tools to improve patient selection for plan comparisons.

METHODS: This prospective study consisted of 141 consecutive patients in which a plan comparison was done. IMPT plans of patients not qualifying for PT were classified as 'redundant'. To prevent redundant IMPT planning, 5 methods that were primarily based on regression models were developed to predict IMPT Dmean to OARs, by using data from VMAT plans and volumetric data from delineated targets and OARs. Then, actual and predicted plan comparison outcomes were compared. The endpoint was being selected for proton therapy.

RESULTS: Seventy out of 141 patients (49.6%) qualified for PT. Using the developed preselection tools, redundant IMPT planning could have been prevented in 49-68% of the remaining 71 patients not qualifying for PT (=specificity) when the sensitivity of all methods was fixed to 100%, i.e., no false negative cases (positive predictive value range: 57-68%, negative predictive value: 100%).

CONCLUSION: The advanced preselection tools, which uses volume and VMAT dose data, prevented labour intensive creation of IMPT plans in up to 68% of non-qualifying patients for PT. No patients qualifying for PT would have been incorrectly denied a plan comparison. This method contributes significantly to a more cost-effective model-based selection of HNC patients for PT.

Original language	English
Pages (from-to)	61-68
Number of pages	8
Journal	Radiotherapy and Oncology
Volume	160
Early online date	20-Apr-2021
DOIs	https://doi.org/10.1016/j.radonc.2021.04.012
Publication status	Published - Jul-2021

Keywords

Proton therapy
Head and neck cancer
Patient selection
Preselection
IMPT
Plan comparison
TUBE-FEEDING DEPENDENCE
TREATMENT TIME
RADIOTHERAPY
SURVIVAL
OPTIMIZATION
IMPACT
ORGAN

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Development of advanced preselection tools to reduce redundant plan comparisons in model-based selection of head and neck cancer patients for proton therapyFinal publisher's version, 6.47 MBLicence: CC BY-NC-ND

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Tambas, M., der Laan, H. P. V., Rutgers, W., van den Hoek, J. G. M., Oldehinkel, E., Meijer, T. W. H., van der Schaaf, A., Scandurra, D., Free, J., Both, S., Steenbakkers, R. J. H. M., & Langendijk, J. A. (2021). Development of advanced preselection tools to reduce redundant plan comparisons in model-based selection of head and neck cancer patients for proton therapy. Radiotherapy and Oncology, 160, 61-68. Advance online publication. https://doi.org/10.1016/j.radonc.2021.04.012

@article{841d81fc8d454a7da9635e5aa10a9013,

title = "Development of advanced preselection tools to reduce redundant plan comparisons in model-based selection of head and neck cancer patients for proton therapy",

abstract = "PURPOSE: In the Netherlands, head and neck cancer (HNC) patients are selected for proton therapy (PT) based on estimated normal tissue complication probability differences (ΔNTCP) between photons and protons, which requires a plan comparison (VMAT vs. IMPT). We aimed to develop tools to improve patient selection for plan comparisons.METHODS: This prospective study consisted of 141 consecutive patients in which a plan comparison was done. IMPT plans of patients not qualifying for PT were classified as 'redundant'. To prevent redundant IMPT planning, 5 methods that were primarily based on regression models were developed to predict IMPT Dmean to OARs, by using data from VMAT plans and volumetric data from delineated targets and OARs. Then, actual and predicted plan comparison outcomes were compared. The endpoint was being selected for proton therapy.RESULTS: Seventy out of 141 patients (49.6%) qualified for PT. Using the developed preselection tools, redundant IMPT planning could have been prevented in 49-68% of the remaining 71 patients not qualifying for PT (=specificity) when the sensitivity of all methods was fixed to 100%, i.e., no false negative cases (positive predictive value range: 57-68%, negative predictive value: 100%).CONCLUSION: The advanced preselection tools, which uses volume and VMAT dose data, prevented labour intensive creation of IMPT plans in up to 68% of non-qualifying patients for PT. No patients qualifying for PT would have been incorrectly denied a plan comparison. This method contributes significantly to a more cost-effective model-based selection of HNC patients for PT.",

keywords = "Proton therapy, Head and neck cancer, Patient selection, Preselection, IMPT, Plan comparison, TUBE-FEEDING DEPENDENCE, TREATMENT TIME, RADIOTHERAPY, SURVIVAL, OPTIMIZATION, IMPACT, ORGAN",

author = "Makbule Tambas and {der Laan}, {Hans P van} and Wouter Rutgers and {van den Hoek}, {Johanna G M} and Edwin Oldehinkel and Meijer, {Tineke W H} and {van der Schaaf}, Arjen and Daniel Scandurra and Jeffrey Free and Stefan Both and Steenbakkers, {Roel J H M} and Langendijk, {Johannes A}",

year = "2021",

month = jul,

doi = "10.1016/j.radonc.2021.04.012",

language = "English",

volume = "160",

pages = "61--68",

journal = "Radiotherapy and Oncology",

issn = "0167-8140",

publisher = "ELSEVIER IRELAND LTD",

}

Tambas, M , der Laan, HPV , Rutgers, W , van den Hoek, JGM , Oldehinkel, E, Meijer, TWH, van der Schaaf, A, Scandurra, D, Free, J , Both, S , Steenbakkers, RJHM & Langendijk, JA 2021, 'Development of advanced preselection tools to reduce redundant plan comparisons in model-based selection of head and neck cancer patients for proton therapy', Radiotherapy and Oncology, vol. 160, pp. 61-68. https://doi.org/10.1016/j.radonc.2021.04.012

TY - JOUR

T1 - Development of advanced preselection tools to reduce redundant plan comparisons in model-based selection of head and neck cancer patients for proton therapy

AU - Tambas, Makbule

AU - der Laan, Hans P van

AU - Rutgers, Wouter

AU - van den Hoek, Johanna G M

AU - Oldehinkel, Edwin

AU - Meijer, Tineke W H

AU - van der Schaaf, Arjen

AU - Scandurra, Daniel

AU - Free, Jeffrey

AU - Both, Stefan

AU - Steenbakkers, Roel J H M

AU - Langendijk, Johannes A

PY - 2021/7

Y1 - 2021/7

N2 - PURPOSE: In the Netherlands, head and neck cancer (HNC) patients are selected for proton therapy (PT) based on estimated normal tissue complication probability differences (ΔNTCP) between photons and protons, which requires a plan comparison (VMAT vs. IMPT). We aimed to develop tools to improve patient selection for plan comparisons.METHODS: This prospective study consisted of 141 consecutive patients in which a plan comparison was done. IMPT plans of patients not qualifying for PT were classified as 'redundant'. To prevent redundant IMPT planning, 5 methods that were primarily based on regression models were developed to predict IMPT Dmean to OARs, by using data from VMAT plans and volumetric data from delineated targets and OARs. Then, actual and predicted plan comparison outcomes were compared. The endpoint was being selected for proton therapy.RESULTS: Seventy out of 141 patients (49.6%) qualified for PT. Using the developed preselection tools, redundant IMPT planning could have been prevented in 49-68% of the remaining 71 patients not qualifying for PT (=specificity) when the sensitivity of all methods was fixed to 100%, i.e., no false negative cases (positive predictive value range: 57-68%, negative predictive value: 100%).CONCLUSION: The advanced preselection tools, which uses volume and VMAT dose data, prevented labour intensive creation of IMPT plans in up to 68% of non-qualifying patients for PT. No patients qualifying for PT would have been incorrectly denied a plan comparison. This method contributes significantly to a more cost-effective model-based selection of HNC patients for PT.

AB - PURPOSE: In the Netherlands, head and neck cancer (HNC) patients are selected for proton therapy (PT) based on estimated normal tissue complication probability differences (ΔNTCP) between photons and protons, which requires a plan comparison (VMAT vs. IMPT). We aimed to develop tools to improve patient selection for plan comparisons.METHODS: This prospective study consisted of 141 consecutive patients in which a plan comparison was done. IMPT plans of patients not qualifying for PT were classified as 'redundant'. To prevent redundant IMPT planning, 5 methods that were primarily based on regression models were developed to predict IMPT Dmean to OARs, by using data from VMAT plans and volumetric data from delineated targets and OARs. Then, actual and predicted plan comparison outcomes were compared. The endpoint was being selected for proton therapy.RESULTS: Seventy out of 141 patients (49.6%) qualified for PT. Using the developed preselection tools, redundant IMPT planning could have been prevented in 49-68% of the remaining 71 patients not qualifying for PT (=specificity) when the sensitivity of all methods was fixed to 100%, i.e., no false negative cases (positive predictive value range: 57-68%, negative predictive value: 100%).CONCLUSION: The advanced preselection tools, which uses volume and VMAT dose data, prevented labour intensive creation of IMPT plans in up to 68% of non-qualifying patients for PT. No patients qualifying for PT would have been incorrectly denied a plan comparison. This method contributes significantly to a more cost-effective model-based selection of HNC patients for PT.

KW - Proton therapy

KW - Head and neck cancer

KW - Patient selection

KW - Preselection

KW - IMPT

KW - Plan comparison

KW - TUBE-FEEDING DEPENDENCE

KW - TREATMENT TIME

KW - RADIOTHERAPY

KW - SURVIVAL

KW - OPTIMIZATION

KW - IMPACT

KW - ORGAN

U2 - 10.1016/j.radonc.2021.04.012

DO - 10.1016/j.radonc.2021.04.012

M3 - Article

C2 - 33892024

SN - 0167-8140

VL - 160

SP - 61

EP - 68

JO - Radiotherapy and Oncology

JF - Radiotherapy and Oncology

ER -