Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
169 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Analysis of clinical, dosimetric and radiomic features for predicting local failure after stereotactic radiotherapy of brain metastases in malignant melanoma (2405.20825v2)

Published 31 May 2024 in physics.med-ph and cs.LG

Abstract: Background: This study aimed to predict lesion-specific outcomes after stereotactic radiotherapy (SRT) in patients with brain metastases from malignant melanoma (MBM), using clinical, dosimetric pretherapeutic MRI data. Methods: In this multicenter retrospective study, 517 MBM from 130 patients treated with single-fraction or hypofractionated SRT across three centers were analyzed. From contrast-enhanced T1-weighted MRI, 1576 radiomic features (RF) were extracted per lesion - 788 from the gross tumor volume (GTV), 788 from a 3 mm peritumoral margin. Clinical data, radiation dose and RF from one center were used for feature selection and model development via nested cross-validation; external validation was performed using the other two centers. Results: Local failure occurred in 72 of 517 lesions (13.9%). Predictive models based on clinical data (model 1), RF (model 2), or both (model 3) achieved c-indices of 0.60 +/- 0.15, 0.65 +/- 0.11, and 0.65 +/- 0.12. RF-based models outperformed the clinical model, while dosimetric data alone were not predictive. Most predictive RF came from the peritumoral margin (92%) vs. GTV (76%). On the first external dataset, all models performed similarly (c-index: 0.60-0.63), but showed poor generalization on the second (c-index < 0.50), likely due to differences in patient characteristics and imaging protocols. Conclusions: Information extracted from pretherapeutic MRI, particularly from the peritumoral area, can support accurate prediction of lesion-specific outcomes after SRT in MBM. When combined with clinical data, these imaging-derived markers offer valuable prognostic insights. However, generalizability remains challenging by heterogeneity in patient populations and MRI protocols.

Summary

We haven't generated a summary for this paper yet.