Modeling of salivary production recovery after radiotherapy using mixed models: determination of optimal dose constraint for IMRT planning and construction of convenient tools to predict salivary function.

PURPOSE: The mathematical relationship between the dose to the parotid glands and salivary gland production needs to be elucidated. This study, which included data from patients included in a French prospective study assessing the benefit of intensity-modulated radiotherapy (RT), sought to elaborate a convenient and original model of salivary recovery. METHODS AND MATERIALS: Between January 2001 and December 2004, 44 patients were included (35 with oropharyngeal and 9 with nasopharyngeal cancer). Of the 44 patients, 24 were treated with intensity-modulated RT, 17 with three-dimensional conformal RT, and 2 with two-dimensional RT. Stimulated salivary production was collected for 40 Gy. CONCLUSION: The results of this study show that the recommendation of a dose constraint for intensity-modulated RT planning should be established at the volume of the contralateral parotid gland receiving >40 Gy rather than the mean dose. For complete salivary production recovery after 24 months, the volume of the contralateral parotid gland receiving >40 Gy should be <33%. Our results permitted us to establish two convenient tools to predict the saliva production recovery function according to the dose received by the contralateral parotid gland.

Automatic three-dimensional model for protontherapy of the eye: preliminary results.

Recently, radiotherapy possibilities have been dramatically increased by software and hardware developments. Improvements in medical imaging devices have increased the importance of three-dimensional (3D) images as the complete examination of these data by a physician is not possible. Computer techniques are needed to present only the pertinent information for clinical applications. We describe a technique for an automatic 3D reconstruction of the eye and CT scan merging with fundus photographs (retinography). The final result is a "virtual eye" to guide ocular tumor protontherapy. First, we make specific software to automatically detect the position of the eyeball, the optical nerve, and the lens in the CT scan. We obtain a 3D eye reconstruction using this automatic method. Second, we describe the retinography and demonstrate the projection of this modality. Then we combine retinography with a reconstructed eye, using a CT scan to get a virtual eye. The result is a computer 3D scene rendering a virtual eye into a skull reconstruction. The virtual eye can be useful for the simulation, the planning, and the control of ocular tumor protontherapy. It can be adapted to treatment planning to automatically detect eye and organs at risk position. It should be highlighted that all the image processing is fully automatic to allow the reproduction of results, this is a useful property to conduct a consistent clinical validation. The automatic localization of the organ at risk in a CT scan or an MRI by automatic software could be of great interest for radiotherapy in the future for comparison of one patient at different times, the comparison of different treatments centers, the possibility of pooling results of different treatments centers, the automatic generation of doses-volumes histograms, the comparison between different treatment planning for the same patient and the comparison between different patients at the same time. It will also be less time consuming.