Validation of real time tumor tracking models with four-dimensional magnetic resonance-imaging
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Research
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Start date: 2012-01-01
Length: 36 months
Project abstract
Breathing motion currently limits the use of highly conformal treatments in external beam radiotherapy applied to extra-cranial sites.
The availability of precise dose delivery techniques is frustrated by the uncertainties due to the intrinsic variability in patient breathing. As a result conservative delivery strategies are applied, resulting in sub-optimal normal tissue sparing when delivering curative dose levels.
The purpose of this research project is to explore multimodal imaging methods to quantify breathing motion variability, aiming at the implementation of mathematical models to be used for tumor tracking in real time. Four-dimensional Magnetic Resonance Imaging (4D MRI) is combined with real time surface capture technologies to acquire time-resolved datasets, where volumetric anatomical MRI imaging is merged with dynamic external surface modelling.
Different competitive approaches to imaging are currently being tested, including full volumetric acquisition in specific regions, slice sorting based on variable surface surrogates and slice sorting based on inner anatomy variations.
The generated dataset will be used for the optimization and validation of external/internal correlations models, aiming at accurate real time tumor tracking with non ionizing radiation. Such a dataset will also enable to quantify the actual gain of upcoming MRI image guidance treatment delivery technologies for effective real-time tumor tracking.
The availability of precise dose delivery techniques is frustrated by the uncertainties due to the intrinsic variability in patient breathing. As a result conservative delivery strategies are applied, resulting in sub-optimal normal tissue sparing when delivering curative dose levels.
The purpose of this research project is to explore multimodal imaging methods to quantify breathing motion variability, aiming at the implementation of mathematical models to be used for tumor tracking in real time. Four-dimensional Magnetic Resonance Imaging (4D MRI) is combined with real time surface capture technologies to acquire time-resolved datasets, where volumetric anatomical MRI imaging is merged with dynamic external surface modelling.
Different competitive approaches to imaging are currently being tested, including full volumetric acquisition in specific regions, slice sorting based on variable surface surrogates and slice sorting based on inner anatomy variations.
The generated dataset will be used for the optimization and validation of external/internal correlations models, aiming at accurate real time tumor tracking with non ionizing radiation. Such a dataset will also enable to quantify the actual gain of upcoming MRI image guidance treatment delivery technologies for effective real-time tumor tracking.
Project results
- Paganelli C., Summers P., Bellomi M., Baroni G., Riboldi M. Image-based retrospective 4D MRI for different anatomical orientations. IEEE NUCLEAR SCIENCE SYMPOSIUM & MEDICAL IMAGING CONFERENCE. Seattle, WA (USA), 8-15 November 2014.
- Bert C., Graeff C., Riboldi M., Nill S., Baroni G., Knopf AC. Advances in 4D Treatment Planning for Scanned Particle Beam Therapy - Report of Dedicated Workshops. Technol Cancer Res Treat 2014 Dec; 13: 485-95.
- Fattori G., Saito N., Seregni M., Kaderka R., Pella A., Constantinescu A., Riboldi M., Steidl P., Cerveri P., Bert C., Durante M., Baroni G. Commissioning of an integrated platform for time-resolved treatment delivery in scanned ion beam therapy by means of optical motion monitoring. Technol Cancer Res Treat 2014 Dec;13(6):517-28.
- Fassi A., Schaerer J., Fernandes M., Riboldi M., Sarrut D., Baroni G. Tumor tracking method based on a deformable 4D CT breathing motion model driven by an external surface surrogate. Int J Radiat Oncol Biol Phys 2014 Jan; 88: 182-8.
- Paganelli C., Peroni M., Riboldi M., Sharp G.C., Ciardo D., Alterio D., Orecchia R., Baroni G. Scale invariant feature transform in adaptive radiation therapy: a tool for deformable image registration assessment and re-planning indication. Phys Med Biol 2013 Jan; 58: 287-99.
- Paganelli C., Peroni M., Baroni G., Riboldi M. Quantification of organ motion based on an adaptive image-based scale invariant feature method. Med Phys 2013 40(11): 111701/1-12.
- Paganelli C., Summers P., Baroni G., Bellomi M. and Riboldi M. Image-based retrospective 4D MRI. 4D treatment (planning) workshop, November 28th-29th, 2013, Paul Scherrer Institut, Villigen, Switzerland.
- Seregni M., Kaderka R., Fattori G., Riboldi M., Pella A., Constantinescu A., Saito N., Durante M., Cerveri P., Bert C., Baroni G. Tumor tracking based on correlation models in scanned ion beam therapy: an experimental study. Phys Med Biol 2013 Jul; 58: 4659-78.
- Paganelli C., Peroni M., Pennati F., Baroni G., Summers P., Bellomi M., Riboldi M. Scale Invariant Feature Transform as feature tracking method in 4D imaging: a feasibility study. Conf Proc IEEE Eng Med Biol Soc 2012; 2012: 6543-6.
- Paganelli C., Peroni M., Baroni G., Riboldi M. Validation of deformable registration in adaptive therapy with scale invariant feature transform. Proceedings of the 9th IEEE International Symposium on Biomedical Imaging (ISBI) 2012, p. 680-683.
- Seregni M., Cerveri P., Riboldi M., Pella A., Baroni G. Robustness of external/internal correlation models for real-time tumor tracking to breathing motion variations. Phys Med Biol 2012 Nov; 57: 7053-74.
- Riboldi M., Orecchia R., Baroni G. Real-time tumour tracking in particle therapy: technological developments and future perspectives. Lancet Oncol 2012 Sep; 13: e383-91.
