Linear energy transfer-inclusive models of brainstem necrosis following proton therapy of paediatric ependymoma

Handeland, Andreas H.; Indelicato, Daniel J.; Fjæra, Lars Fredrik; Ytre-Hauge, Kristian S.; Pettersen, Helge Egil Seime; Muren, L.P.; Lassen‐Ramshad, Yasmin; Stokkevåg, C.H.

doi:10.1016/j.phro.2023.100466

Cited by 3 publications

(1 citation statement)

References 36 publications

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“…Treatment plans, goals, and limitations are usually discussed between patients and physicians, with priorities considered on an individual basis. Despite its advantages, proton therapy introduces planning uncertainties due to high linear energy transfer areas [26] . Even with a tolerant dose map in our group, the absence of adverse events was not guaranteed (one patient experienced grade 5 brainstem injury).…”

Section: Discussionmentioning

confidence: 99%

A single-center experience of the upright proton therapy for skull-base chordomas and chondrosarcomas: Updated results

Lemaeva,

Gulidov,

Smyk

et al. 2024

Clinical and Translational Radiation Oncology

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Section: Discussionmentioning

confidence: 99%

A single-center experience of the upright proton therapy for skull-base chordomas and chondrosarcomas: Updated results

Lemaeva,

Gulidov,

Smyk

et al. 2024

Clinical and Translational Radiation Oncology

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Linear energy transfer-inclusive brainstem necrosis risk models applied to an independent paediatric proton therapy cohort

Handeland,

Lægdsmand,

Toussaint

et al. 2023

Acta Oncologica

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Decoding Patient Heterogeneity Influencing Radiation-Induced Brain Necrosis

Chamseddine,

Shah,

Lee

et al. 2024

Clinical Cancer Research

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Purpose: In radiotherapy (RT) for brain tumors, patient heterogeneity masks treatment effects, complicating the prediction and mitigation of radiation-induced brain necrosis. Therefore, understanding this heterogeneity is essential for improving outcome assessments and reducing toxicity. Experimental Design: We developed a clinically practical pipeline to clarify the relationship between dosimetric features and outcomes by identifying key variables. We processed data from a cohort of 130 patients treated with proton therapy for brain and head and neck tumors, utilizing an expert-augmented Bayesian network to understand variable interdependencies and assess structural dependencies. Critical evaluation involved a 3-level grading system for each network connection and a Markov blanket analysis to identify variables directly impacting necrosis risk. Statistical assessments included log-likelihood ratio (LLR), integrated discrimination index (IDI), net reclassification index (NRI), and receiver operating characteristic (ROC). Results: The analysis highlighted tumor location and proximity to critical structures like white matter and ventricles as major determinants of necrosis risk. The majority of network connections were clinically supported, with quantitative measures confirming the significance of these variables in patient stratification (LLR=12.17, p=0.016; IDI=0.15; NRI=0.74). The ROC curve area was 0.66, emphasizing the discriminative value of non-dosimetric variables. Conclusions: Key patient variables critical to understanding brain necrosis post-RT were identified, aiding the study of dosimetric impacts and providing treatment confounders and moderators. This pipeline aims to enhance outcome assessments by revealing at-risk patients, offering a versatile tool for broader applications in RT to improve treatment personalization in different disease sites.

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Linear energy transfer-inclusive models of brainstem necrosis following proton therapy of paediatric ependymoma

Cited by 3 publications

References 36 publications

A single-center experience of the upright proton therapy for skull-base chordomas and chondrosarcomas: Updated results

A single-center experience of the upright proton therapy for skull-base chordomas and chondrosarcomas: Updated results

Linear energy transfer-inclusive brainstem necrosis risk models applied to an independent paediatric proton therapy cohort

Decoding Patient Heterogeneity Influencing Radiation-Induced Brain Necrosis

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