Related papers: Analysis of clinical, dosimetric and radiomic features for predicting local failure after stereotactic radiotherapy of brain metastases in malignant melanoma

Analysis of clinical, dosimetric and radiomic features for predicting local failure after stereotactic radiotherapy of brain metastases in malignant melanoma

URL: http://arxiv.org/abs/2405.20825v1
Date: Fri, 31 May 2024 14:18:37 GMT
Title: Analysis of clinical, dosimetric and radiomic features for predicting local failure after stereotactic radiotherapy of brain metastases in malignant melanoma
Authors: Nanna E. Hartong, Ilias Sachpazidis, Oliver Blanck, Lucas Etzel, Jan C. Peeken, Stephanie E. Combs, Horst Urbach, Maxim Zaitsev, Dimos Baltas, Ilinca Popp, Anca-Ligia Grosu, Tobias Fechter,
Abstract summary: The aim of this study was to investigate the role of clinical, dosimetric and pretherapeutic magnetic resonance imaging (MRI) features for lesion-specific outcome prediction.
Score: 1.813829334805839
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: Background: The aim of this study was to investigate the role of clinical, dosimetric and pretherapeutic magnetic resonance imaging (MRI) features for lesion-specific outcome prediction of stereotactic radiotherapy (SRT) in patients with brain metastases from malignant melanoma (MBM). Methods: In this multicenter, retrospective analysis, we reviewed 517 MBM from 130 patients treated with SRT (single fraction or hypofractionated). For each gross tumor volume (GTV) 1576 radiomic features (RF) were calculated (788 each for the GTV and for a 3 mm margin around the GTV). Clinical parameters, radiation dose and RF from pretherapeutic contrast-enhanced T1-weighted MRI from different institutions were evaluated with a feature processing and elimination pipeline in a nested cross-validation scheme. Results: Seventy-two (72) of 517 lesions (13.9%) showed a local failure (LF) after SRT. The processing pipeline showed clinical, dosimetric and radiomic features providing information for LF prediction. The most prominent ones were the correlation of the gray level co-occurrence matrix of the margin (hazard ratio (HR): 0.37, confidence interval (CI): 0.23-0.58) and systemic therapy before SRT (HR: 0.55, CI: 0.42-0.70). The majority of RF associated with LF was calculated in the margin around the GTV. Conclusions: Pretherapeutic MRI based RF connected with lesion-specific outcome after SRT could be identified, despite multicentric data and minor differences in imaging protocols. Image data analysis of the surrounding metastatic environment may provide therapy-relevant information with the potential to further individualize radiotherapy strategies.

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