Toward an individualized target motion management for IMRT of cervical cancer based on model-predicted cervix-uterus shape and position

Background and Purpose: To design and evaluate a 3D patient-specific model to predict the cervix-uterus shape and position. Methods and Materials: For 13 patients lying in prone position, 10 variable bladder filling CT-scans were acquired, 5 at planning and 5 after 40 Gy. The delineated cervix-uterus volumes in 2-5 pre-treatment CT-scans were used to generate patient-specific models that predict the cervix-uterus geometry by bladder volume. Model predictions were compared to delineations, excluding those used for model construction. The prediction error was quantified by the margin required around the predicted volumes to accommodate 95% of the delineated volume and by the predicted-to-delineated surface distance. Results: The prediction margin was significantly smaller (average 50%) than the margin encompassing the cervix-uterus motion. The prediction margin could be decreased (from 7 to 5 mm at planning and from 10 to 8 mm after 40 Gy) by increasing (from 2 to 5) the number of CT-scans used for the model construction. Conclusion: For most patients, even with a model based on only two CT-scans, the prediction error was well below the margin encompassing the cervix-uterus motion. The described approach could be used to create prior to treatment, an individualized treatment strategy.