This joint project between the JHU CS Department and the JHU Radiation Oncology Department explores the statistical relationship between anatomic shape and treatment planning in radiation oncology. In one current project, our goal is to use a database of previously treated patients to improve radiation therapy planning for new patients. The key idea is that the geometric relationship between the tumor and surrounding critical anatomic structures has a crucial role in determining a dose distribution that treats the tumor while sparing critical structures. We have developed a novel shape descriptor, the Overlap Volume Histogram (OVH) characterizing the proximity of the treatment volume to critical structures. The OVH is then used to as an index into our patient data base. Retrieved information may be used both for plan quality sanity checking and as a means of speeding up the initial stages of treatment planning.

In closely related work, we explore advanced computational methods for radiation therapy treatment planning.

• [Kazhdan 2009] M. Kazhdan, P. Simari, T. McNutt, B. Wu, R. Jacques, M. Chuang, and R. Taylor, “A Shape Relationship Descriptor for Radiation Therapy Planning ”, in Medical Image Computing and Computer-Assisted Intervention - MICCAI, London, September, 2009. pp. 100-108. DOI 10.1007/978-3-642-04271-3_13; PMID Pending
• [Wu 2009] B. Wu, F. Ricchetti, G. Sanguineti, M. Kazhdan, P. Simari, M. Chuang, R. Taylor, R. Jacques, and T. McNutt, “Patient geometry-driven information retrieval for IMRT treatment plan quality control”, Med. Phys., vol. 36- 12, pp. 5497-5505, December, 2009. PMID: 20095262
• [McNutt 2010] T. R. McNutt, K. Evans, B. Wu, M. Kahzdan, P. Simari, G. Sanguineti, J. Herman, R. Taylor, J. Wong, and T. DeWeese, “Oncospace: All Patients on Trial for Analysis of Outcomes, Toxicities, and IMRT Plan Quality”, International Journal of Radiation Oncology*Biology*Physics, vol. 78- 3, Supplement 1,Refereed Abstract, pp. S486-S486, 2010.Refereed Abstract http://www.sciencedirect.com/science/article/B6T7X-514GTCR-1BT/2/bac3e9fc5300aab00ed47526da21039e doi: DOI: 10.1016/j.ijrobp.2010.07.1139
• [Simari 2010] P. Simari, B. Wu, R. Jacques, A. King, T. McNutt, R. Taylor, and M. Kazhdan, “A Statistical Approach for Achievable Dose Querying in IMRT Planning”, in Medical Image Computing and Computer-Assisted Intervention (MICCAI), Beijing, September, 2010. pp. 521-528. DOI: 10.1007/978-3-642-15711-0_65 PMID20879440.
• [Wu 2010a] B. Wu, M. Kazhdan, P. Simari, R. Taylor, and T. McNutt, “A Geometry-Driven Approach for Predicting DVHs of Organs at Risk in IMRT Planning”, in Proceedings of the XVIth Int’l Conf on Computers in Radiotherapy, Amsterdam, June 1, 2010.
• [Wu 2010b] B. Wu, R. Ricchetti, G. Sanguinetti, M. Kazhdan, P. Simari, R. Jacques, R. Taylor, and T. McNutt, “A Data-Driven Approach to Generating Achievable DVH Objectives in IMRT Treatment Planning”, International Journal of Radiation Oncology, Biology, Physics, p. In Press, Epub 26 August, 2010. doi:10.1016/j.ijrobp.2010.05.026 PMID 20800382.
• [Wu 2010c] B. Wu, G. Sanguineti, M. Kazhdan, P. Simari, R. Taylor, and T. Mcnutt, “An OVH-driven Automated IMRT Treatment Planning System”, International Journal of Radiation Oncology*Biology*Physics, vol. 78- 3 - suppl1,Refereed Abstract, p. S187, November 1, 2010.Refereed Abstract http://www.sciencedirect.com/science/article/B6T7X-514GTCR-GV/2/042e944acacb21b1a54f6a00ade774f0 10.1016/j.ijrobp.2010.07.455
• [Wu 2011a] M. Kazhdan, R. Taylor, T. McNutt, B. Wu, and P. Simari, “Comment on “A planning quality evaluation tool for prostate adaptive IMRT based on machine learning”, Medical Physics, vol. 38- 5,Correspondence, p. 719, 2011.Correspondence 10.1118/1.3578612
• [Petit 2011a] S. F. Petit, B. Wu, M. Kazhdan, A. Dekker, P. Simari, R. Kumar, R. H. Taylor, J. M. Herman, and T. McNutt, “The potential of shape-based treatment plan optimization for pancreatic IMRT treatments to spare organs at risk and allow for dose escalation to the tumor PTV.”, J. Clin. Oncol., vol. Suppl 4-,republished abstract from ASCO 2011, p. abstr 316, 2011.republished abstract from ASCO 2011
• [Petit 2011a] B. Wu, T. McNutt, M. Zaburak, M. Kazhdan, P. Simari, D. Pang, R. Taylor, and G. Sanguinetti, “Fully automated IMRT treatment planning is feasible for head-and-neck (H&N) cancer: a prospective study using an overlap volume histogram (OVH)-guided strategy ”, Abstract in proceedings and poster in ASTRO Annual Meeting, Miami, Oct 2-6, 2011. pp. S198, Poster 1087 (Scientific Abstract Award).Abstract in proceedings and poster
• [Wu 2011b] B. Wu, T. McNutt, M. Zahurak, M. Kazhdan, P. Simari, D. Pang, R. Taylor, and G. Sanguinetti, “On the Feasibility of using Overlap Volume Histogram and DVH Data of Prior IMRT Plans to Guide Smart Arc-based Volumetric Modulated Arc Therapy Treatment Planning (Abstract)”, Abstract in Proceedings and Poster in ASTRO Annual Meeting, Miami, Oct 2-6, 2011. p. S827.Abstract in Proceedings and Poster
• [Petit 2011b] S. F. Petit, B. Wu, M. Kazhdan, A. Dekker, P. Simari, R. Kumar, R. Taylor, J. M. Herman, and T. McNutt, “Increased organ sparing using shape-based treatment plan optimization for intensity modulated radiation therapy of pancreatic adenocarcinoma”, Radiotherapy and Oncology, vol. 102- 1, pp. 38-44, Jan, 2012. doi:10.1016/j.radonc.2011.05.025

• [Jacques 2007] R. Jacques, J. Glaunès, E. Ford, T. McNutt, R. Taylor, and J. Wong, “SU-FF-I-63: Temporal Constrained Registration of Arbitrary Surface Contours for Use in 4D Radiation Therapy”, Med. Phys, vol. 34- 6, pp. 2352-2352, june, 2007. http://dx.doi.org/10.1118/1.2760440
• [Jacques 2008a] R. Jacques, R. Taylor, J. Wong, and T. McNutt, “Towards Real-Time Radiation Therapy: GPU Accelerated Superposition/Convolution”, in High-Performance Medical Image Computing and Computer Aided Intervention (HP-MICCAI), New York, 2008. p. In electronic proceedings at http://www.cse.buffalo.edu/hpmiccai/.
• [Jacques 2008b] R. Jacques, R. Taylor, J. Wong, and T. McNutt, “SU-GG-T-511: Towards Real-Time Radiation Therapy: Superposition/Convolution at 4fps”, Med. Phys., vol. 35- 6, pp. 2842-2842, June, 2008. http://dx.doi.org/10.1118/1.2962260
• [Jacques 2008c] R. Jacques, R. Taylor, J. Wong, and T. McNutt, “Towards Real-time Radiation Therapy: Superposition/Convolution at Interactive Rates (Abstract)”, in ASTRO 2008 Annual Meeting, 2008.
• [Jacques 2009] R. Jacques, R. Taylor, J. Wong, and T. McNutt, “Towards Real-Time Radiation Therapy: GPU Accelerated Superposition/Convolution”, Computer Methods and Programs in Biomedicine, p. Elec Pub, 2009. http://www.cse.buffalo.edu/hpmiccai/ PMID: 19695731
• [Jacques 2010a] R. Jacques, D. Smith, E. Tryggestad, J. Wong, R. Taylor, and T. McNutt, “GPU Accelerated Real Time KV/MV Dose Computation”, in Proceedings of the XVIth Int’l Conf on Computers in Radiotherapy, June 1, 2010.
• [Jacques 2010b] R. Jacques, R. Taylor, J. Wong, and T. McNutt, “Towards Real-Time Radiation Therapy: GPU Accelerated Superposition/Convolution”, Computer Methods and Programs in Biomedicine, vol. 98- 3, pp. 285-292, June, 2010. http://www.cse.buffalo.edu/hpmiccai/ PMID: 19695731
• [Jacques 2010c] R. Jacques, R. Taylor, J. Wong, and T. McNutt, “SU‐GG‐T‐604: GPU‐Accelerated KV/MV Dose Computation”, Medical Physics, vol. 37- 6,Refereed Abstract, p. 3326, 2010.Refereed Abstract http://online.medphys.org/resource/1/mphya6/v37/i6/p3326_s3
• [Jacques 2011a] R. Jacques, R. Taylor, J. Wong, and T. McNutt, “SU‐E‐T‐719: Multi‐Energetic, GPU‐Accelerated Superposition/Convolution (abstract from AAPM 2011)”, Medical Physics, vol. 38- 6,Published Abstract, p. 3656, 2011.Published Abstract
• [Jacques 2011b] R. Jacques, J. Wong, T. McNutt, and R. Taylor, “Real-time dose computation: GPU-accelerated source modeling and superposition/convolution”, Medical Physics, vol. 38- 1, pp. 294-306, 2011. http://online.medphys.org/resource/1/mphya6/v38/i1/p294_s1 10.1118/1.3483785