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Updated: Feb 5, 2026

Treatment of Liver Metastases Using an Internal Target Volume Method for Stereotactic Body Radiotherapy
Published on: May 8, 2018
Hypofractionated stereotactic radiotherapy for oligometastatic patients: developing of a response predictive model
Barbara Diletto1,2, Nicola Dinapoli3, Silvia Chiesa3
1Department of Radiation Oncology, Università Cattolica del Sacro Cuore, Largo A. Gemelli, 1, Rome, Italy. barbara.diletto@istitutotumori.mi.it.
Objectives:
Treatment of oligometastatic patients is a current challenge in radiation oncology. Aim of this study is to define a dose-response relationship for hypofractionated radiotherapy of oligometastases.
Methods:
Retrospective analysis of metastases treated by hypofractionated stereotactic radiotherapy was performed. Delivered dose was calculated both as biological effective dose (BED10), and as ratio between BED10 and the logarithm of metastasis volume (BED10 logVolume Ratio, BVR). Two dose-response models were defined by logistic regression. The fitted outcome was the Metastases Complete Response (MCR). Performances of the models were assessed by area under the receiver operating curve (AUC) and by bootstrap calibration of original data. BED10 and BVR impact on survival outcomes has been evaluated.
Results:
Fifty-three patients with 79 metastases were analyzed. AUC and calibration of BVR-based logistic model showed better accuracy in predicting MCR with respect to BED10-based model. No significant difference between the two ROCs was observed (De Long test p value > 0.05), but significant discordance in calibration resulted in the BED10 model (p value < 0.05 in Hosmer-Lemeshow Goodness of fit test). BVR returned also better results in multivariate analyses for survival outcomes.
Conclusions:
The ratio between BED10 and the logarithm of metastasis volume (BVR), as a corrective factor for fitting the probability of metastases response to stereotactic radiotherapy, could be a tool for evaluating and prescribing treatments for oligometastatic disease. BVR can be useful for producing more reliable survival statistics too.
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