Abstract
Background and purpose
Brain tumors are in general treated with a maximal safe resection followed by radiotherapy of remaining tumor including the resection cavity (RC) and chemotherapy. Anatomical changes of the RC during radiotherapy can have impact on the coverage of the target volume. The aim of the current study was to quantify the potential changes of the RC and to identify risk factors for RC changes.
Materials and methods
Sixteen patients treated with pencil beam scanning proton therapy between October 2019 and April 2020 were retrospectively analyzed. The RC was delineated on pre-treatment computed tomography (CT) and magnetic resonance imaging, and weekly CT-scans during treatment. Isotropic expansions were applied to the pre-treatment RC (1–5 mm). The percentage of volume of the RC during treatment within the expanded pre-treatment volumes was quantified. Potential risk factors (volume of RC, time interval surgery-radiotherapy and relationship of RC to the ventricles) were evaluated using Spearman’s rank correlation coefficient.
Results
The average variation in relative RC volume during treatment was 26.1% (SD 34.6%). An expansion of 4 mm was required to cover > 95% of the RC volume in > 90% of patients. There was a significant relationship between the absolute volume of the pre-treatment RC and the volume changes during treatment (Spearman’s ρ = − 0.644; p = 0.007).
Conclusion
RCs are dynamic after surgery. Potentially, an additional margin in brain cancer patients with an RC should be considered, to avoid insufficient target coverage. Future research on local recurrence patterns is recommended.
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Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Abbreviations
- CBCT:
-
Cone-beam computed tomography
- CT:
-
Computed tomography
- CTV:
-
Clinical target volume
- EORTC:
-
European Organization for Research and Treatment of Cancer
- FLAIR:
-
Fluid-attenuated inversion recovery
- GTV:
-
Gross tumor volume
- LGGs:
-
Low-grade glioma
- MRI:
-
Magnetic resonance imaging
- MR-IGRT:
-
Magnetic resonance image-guided radiotherapy
- OARs:
-
Organs-at-risk
- pCT:
-
Pre-treatment computed tomography scan
- pMRI:
-
Pre-treatment magnetic resonance imaging scan
- RC:
-
Resection cavity
- reCT:
-
Repeat computed tomography scan
- SRT:
-
Stereotactic radiotherapy
- WHO:
-
World Health Organization
References
Schiff D et al (2019) Recent developments and future directions in adult lower-grade gliomas: Society for Neuro-Oncology (SNO) and European Association of Neuro-Oncology (EANO) consensus. Neuro Oncol 21(7):837–853. https://doi.org/10.1093/neuonc/noz033
Karschnia P et al (2021) Evidence-based recommendations on categories for extent of resection in diffuse glioma. Eur J Cancer 149:23–33. https://doi.org/10.1016/j.ejca.2021.03.002
Dirven L et al (2019) Impact of radiation target volume on health-related quality of life in patients with low-grade glioma in the 2-year period post treatment: a secondary analysis of the EORTC 22033–26033. Int J Radiat Oncol Biol Phys 104(1):90–100. https://doi.org/10.1016/j.ijrobp.2019.01.003
Verhoef J, Heesters M, Lagerwaard F, Bakker M (2017) Werkafspraak over doseren en doelvolumina bij gliomen. Landelijk Platform Radiotherapie Neuro Oncologie. https://doi.org/10.1016/j.radonc.2020.11.004
van der Weide HL et al (2021) Proton therapy for selected low grade glioma patients in the Netherlands. Radiother Oncol 154:283–290. https://doi.org/10.1016/j.radonc.2020.11.004
Scharl S et al (2020) Is local radiotherapy a viable option for patients with an opening of the ventricles during surgical resection of brain metastases? Radiat Oncol 15(1):276. https://doi.org/10.1186/s13014-020-01725-x
Eekers DB et al (2018) The EPTN consensus-based atlas for CT- and MR-based contouring in neuro-oncology. Radiother Oncol 128(1):37–43. https://doi.org/10.1016/j.radonc.2017.12.013
Anten M et al (2019) Richtlijn gliomen. Nederlandse Vereniging voor Neurologie, Utrecht
Korevaar EW et al (2019) Practical robustness evaluation in radiotherapy—a photon and proton-proof alternative to PTV-based plan evaluation. Radiother Oncol 141:267–274. https://doi.org/10.1016/j.radonc.2019.08.005
Alghamdi M et al (2018) Stereotactic radiosurgery for resected brain metastasis: cavity dynamics and factors affecting its evolution. J Radiosurg SBRT 5(3):191–200
Shah JK, Potts MB, Sneed PK, Aghi MK, McDermott MW (2016) Surgical cavity constriction and local progression between resection and adjuvant radiosurgery for brain metastases. Cureus 8(4):e575. https://doi.org/10.7759/cureus.575
Scharl S et al (2019) Cavity volume changes after surgery of a brain metastasis-consequences for stereotactic radiation therapy. Strahlenther Onkol 195(3):207–217. https://doi.org/10.1007/s00066-018-1387-y
Tan H et al (2022) Inter-fraction dynamics during post-operative 5 fraction cavity hypofractionated stereotactic radiotherapy with a MR LINAC: a prospective serial imaging study. J Neurooncol. https://doi.org/10.1007/s11060-021-03938-w
Jarvis LA et al (2012) Tumor bed dynamics after surgical resection of brain metastases: implications for postoperative radiosurgery. Int J Radiat Oncol Biol Phys 84(4):943–948. https://doi.org/10.1016/j.ijrobp.2012.01.067
Yang Z et al (2016) Intensity-modulated radiotherapy for gliomas:dosimetric effects of changes in gross tumor volume on organs at risk and healthy brain tissue. Onco Targets Ther 9:3545–3554. https://doi.org/10.2147/OTT.S100455
Mehta S et al (2018) Daily tracking of glioblastoma resection cavity, cerebral edema, and tumor volume with MRI-guided radiation therapy. Cureus 10(3):e2346. https://doi.org/10.7759/cureus.2346
Atalar B et al (2013) Cavity volume dynamics after resection of brain metastases and timing of postresection cavity stereotactic radiosurgery. Neurosurgery 72(2):180–185. https://doi.org/10.1227/NEU.0b013e31827b99f3
Ahmed S et al (2014) Change in postsurgical cavity size within the first 30 days correlates with extent of surrounding edema: consequences for postoperative radiosurgery. J Comput Assist Tomogr 38(3):457–460. https://doi.org/10.1097/RCT.0000000000000058
van Herk M, Remeijer P, Rasch C, Lebesque JV (2000) The probability of correct target dosage: dose-population histograms for deriving treatment margins in radiotherapy. Int J Radiat Oncol Biol Phys 47(4):1121–1135. https://doi.org/10.1016/S0360-3016(00)00518-6
Gaito S, Burnet A, Aznar M, Crellin A, Indelicato DJ, Ingram S, Pan S, Price G, Hwang E, France A, Smith E, Whitfield G (2022) Normal tissue complication probability modelling for toxicity prediction and patient selection in proton beam therapy to the central nervous system: a literature review. Clin Oncol 34(6):e225–e237. https://doi.org/10.1016/j.clon.2021.12.015
Gaito S, Hwang EJ, France A, Aznar MC, Burnet N, Crellin A, Holtzman AL, Indelicato DJ, Timmerman B, Whitfield GA, Smith E (2023) Outcomes of patients treated in the UK proton overseas programme: central nervous system group. Clin Oncol (R Coll Radiol) 35(5):238–291. https://doi.org/10.1016/j.clon.2023.01.024
Stewart J et al (2021) Quantitating interfraction target dynamics during concurrent chemoradiation for glioblastoma: a prospective serial imaging study. Int J Radiat Oncol Biol Phys 109(3):736–746. https://doi.org/10.1016/j.ijrobp.2020.10.002
Maziero D et al (2021) MR-guided radiotherapy for brain and spine tumors. Front Oncol 11:626100. https://doi.org/10.3389/fonc.2021.626100
Taasti VT et al (2021) Treatment planning and 4D robust evaluation strategy for proton therapy of lung tumors with large motion amplitude. Med Phys 48(8):4425–4437. https://doi.org/10.1002/mp.15067
Funding
This publication is part of the project “Making radiotherapy sustainable” with project number 10070012010002 of the Highly Specialised Care and Research programme (TZO programme) which is (partly) financed by the Netherlands Organisation for Health Research and Development (ZonMw).
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YW and FV are joint first authors, having contributed equally to the writing of this manuscript. CZ, MU, AS and WE helped with interpretation of the data and review of the manuscript. DE and IC have delineated the GTVs and CTVs for this study, helped with interpretation of the data, and supervised the research. AP, JJ, AR, MA and OT performed critical review of the manuscript. All authors read and approved the final manuscript.
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This research was submitted to the Internal Review Board of the department of radiation oncology Maastricht (Maastro).
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Willems, Y.C.P., Vaassen, F., Zegers, C.M.L. et al. Anatomical changes in resection cavity during brain radiotherapy. J Neurooncol 165, 479–486 (2023). https://doi.org/10.1007/s11060-023-04505-1
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DOI: https://doi.org/10.1007/s11060-023-04505-1