1. Z. Han, S. K. Ng, M. S. Bhagwat, Y. Lyatskaya, and P. Zygmanski “Evaluation of MatriXX for IMRT and VMAT dose verifications in peripheral dose regions.” Med. Phys. 37: 3704-3714; 2010.
  2. P. Tsiamas, J. Seco, Z. Han, M. Bhagwat, J. Maddox, C. Kappas, K. Theodorou, M. Makrigiorgos, K. J. Marcus, and P. Zygmanski “A modification of flattening filter free linac for IMRT.” Med. Phys. 38: 2342-2352; 2011.
  3. M. S. Bhagwat, Z. Han, and P. Zygmanski “An oscillating sweeping gap test for VMAT quality assurance.” Phys. Med. Biol. 55; 5029-5044; 2010.
  4. M. S Bhagwat, Z. Han, S. Kie. Ng and P. Zygmanski. “An oscillating sweeping gap test for VMAT quality assurance.” Phys. Med. Biol. 55: 5029-5044; 2011.
  5. Y. Wang, J. A. Efstathiou, G. C. Sharp, H. Lu, I. Ciernik, A. Trofimov, “Evaluation of the dosimetric impact of inter-fractional anatomical variations on prostate proton therapy using daily in-room CT images,” Med. Phys. 38: 4623-4633; 2011.
  6.  Trofimov, P. L. Nguyen, J. A. Efstathiou, Y. Wang, H. Lu, M. Engelsman, S.Merrick, C. Cheng, J. R. Wong and A. L. Zietman, “Interfractional variations in the setup of pelvic bony anatomy and soft tissue, and their implications on the delivery of proton therapy for localized prostate cancer,” Int. J. Radiat. Oncol. Biol. Phys. 80: 928-937; 2011.
  7. J. Pursley, P. Risholm, A. Fedorov, K. Tuncali, F. M. Fennessy, W. Wells III, C. M. Tempany, and R. A. Cormack, “A Bayesian non-rigid registration method to enhance intra-operative target definition in image-guided prostate procedures through uncertainty characterization.” Med. Phys. 39 (11), 6858-6867 (2012).
  8. Y. Yuan, O.C. Andronesi, T.R. Bortfeld, C. Richter, R. Wolf, A.S. Guimasraes, T.S. Hong, and J. Seco, “Feasibility study of in vivo MRI based dosimetric verification of proton end-of-range for liver cancer patients,” Radiother. Oncol., Mar; 106(3):378-82; 2013.
  9. P. Mishra, R. Li, S. St. James, R. H. Mak, C. L. Williams, Y. Yue, R. I. Berbeco and J. H. Lewis “Evaluation of 3D fluoroscopic image generation from a single planar treatment image on patient data with a modified XCAT phantom”, Phys Med Biol. 58(4):841-58, 2013
  10. S. St. James, J. Seco, P. Mishra and J. H. Lewis, “A dynamic 4D Monte Carlo framework to quantitatively evaluate limitations of 4D treatment planning in external beam radiation therapy” Submitted to Physics in Medicine and Biology (August 2012).
  11. P. Mishra, S. St. James, W. P. Segars, R. I Berbeco and J. H. Lewis, “Adaptation and applications of a realistic digital phantom based on patient lung tumor trajectories”, Physics in Medicine and Biology, 57(11) 3597 , June 2012.
  12. S. St. James, P. Mishra, R. I. Berbeco and J. H. Lewis, “Quantifying ITV Instabilities Arising from 4DCT: a simulation study using patient data”, March 2012, Physics in Medicine and Biology, 57 L1-L7 (Editor’s Choice Article)
  13. E. Cascio, K. J. Riley, J. McCormack and R.Flanagan “Single Event Effects in Power MOSFETs Due to the Secondary Neutron Environment in a Proton Therapy Center.” IEEE Trans. Nucl. Sci, vol. 59, No. 6, pp 3154-3159, Dec. 2012.
  14. K.J. Riley, J. Seco and P.J. Binns “Measurements of the prompt gamma signal in a clinical proton therapy environment.” Trans. Am. Nucl. Soc. 106: 77-79 2012.
  15. C. L. Williams, P. Mishra, J. Seco, S. St. James, R. Mak, R. Berbeco, and J. Lewis, “A mass-conserving 4D XCAT phantom for dose calculation and accumulation”, Med. Phys. 40 (7)071728-1 – 071728-10,  July 2013.
  16. S. St. James, J. Seco, P. Mishra and J. H. Lewis “Simulations using patient data to evaluate systematic errors that may occur in 4D treatment planning: A proof of concept study” Med. Phys. 40:091706; 2013.
  17. M Zhu, T Botticello, HM Lu, B Winey, “Long-term stability and mechanical characteristics of kV digital imaging system for proton radiotherapy”, Med Phys 41(4), 041706 (2014)
  18. J Liebl, H Paganetti, M Zhu, and B Winey, “The influence of patient positioning uncertainties in proton radiotherapy on proton range and dose distributions”, Med Phys 41(9), 091711 (2014)
  19. Y. Lin, S..J.McMahon, M. Scarpelli, H. Paganetti and J. Schuemann, “Comparing gold nano-particle enhanced radiotherapy with protons, megavoltage photons and kilovoltage photons: a Monte Carlo simulation.” Phys Med Biol 59(24), 7675-7689, 2014. [one of PMB Highlights of 2014 collection]
  20. M. Hurwtiz, C.L. Williams, P. Mishra, J. Rottmann, S. Dhou, M. Wagar, E. Mannarino, R. Mak, J.H. Lewis, “Generation of fluoroscopic 3D images with a respiratory motion model based on an external surrogate signal”, Phys Med Biol, 60(2), 521-536, 2015.
  21. Y. Lin, S. J. McMahon, H. Paganetti, J. Schuemann. “Biological modeling of gold nanoparticle enhanced radiotherapy for proton therapy.” Phys Med Biol, 60(10), 4149-4168,, 2015.
  22. Dhou S, Hurwitz M, Mishra P, Cai WX, Rottmann J, Li R, Williams C, Wagar M, Berbeco R, Ionascu D, Lewis J, “3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models”, Phys Med Biol, 60, 3807-3824,, 2015.
  23. W. CaiM. HurwitzC. Williams, S. Dhou, R. Berbecco, J. Seco, P. Mishra, J. Lewis, “3D delivered dose assessment using a 4DCT-based motion model”, Med Phys, 42(6) 2897-2907, 2015.
  24. Y. Lin, S. J. McMahon, H. Paganetti, J. Schuemann. “Gold nanoparticle induced vasculature damage in radiotherapy: Comparing protons, megavoltage photons, and kilovoltage photons.” Med Phys 42(10), 2015. (Editors Pick Article)
  25. W. Cai, S. Dhou, F. Cifter, M. Myronakis, M. Hurwitz, C. Williams, R. Berbeco, J. Seco, J. Lewis, “4D cone beam CT-based dose assessment for SBRT lung cancer treatment.” Phys Med Biol, 61, 554-568, 2016.
  26. S. Yan, H-M Lu, J. Flanz, J. Adams, A. Trofimov, T. Bortfeld. “Reassessment of the necessity of the proton gantry: analysis of beam orientations from 4332 treatments at the Massachusetts General Hospital (MGH) proton center over the past 10 years.” Int J Radiat Oncol Biol Phys, 95(1), 224-33, 2016.
  27. Huynh E, Coroller TP, Narayan V, Agrawal V, Hou Y, Romano J, Franco I, Mak RH, Aerts HJ. “CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer.” Radiother Oncol 120(2), 258-66, 2016.
  28. Yip SS, Coroller TP, Sanford NN, Huynh E, Mamon H, Aerts HJ, Berbeco RI. “Use of registration-based contour propagation in texture analysis for esophageal cancer pathologic response prediction.” Phys Med Biol, 61(2):906-22, 2016.
  29. Lin Y, Kooy H, Craft D, Depauw N, Flanz J, Clasie B. “A Greedy reassignment algorithm for the PBS minimum monitor unit constraint.” Phys Med Biol. 61(12):4665-78, 2016.
  30. Yip SS, Kim J, Coroller T, Parmar C, Rios Velazquez E, Huynh E, Mak R, Aerts HJ. “Associations between somatic mutations and metabolic imaging phenotypes in non-small cell lung cancer.” J Nucl Med 2016.
  31. Huynh E, Coroller TP, Narayan V, Agrawal V, Romano J, Franco I, Parmar C, Hou Y, Mak RH, Aerts HJ, “Associations of Radiomic Data Extracted from Static and Respiratory-Gated CT Scans with Disease Recurrence in Lung Cancer Patients Treated with SBRT.” PLoS ONE 12(1): e0169172, 2017.
  32. Coroller TP,  Agrawal V, Huynh E, Narayan V, Lee SW, Mak RH, Aerts HJ, Radiomic-based pathological response prediction from primary tumors an lymph nodes in NSCLC.” J Thoracic Oncology, 2017.
  33. Lin Y, Clasie B, Lu HM, Flanz J, Shen T, Jee KW, “Impacts of gantry angle dependent scanning beam properties on proton PBS treatment.” Phys Med Biol 62(2): 344-357, 2017.
  34. Myronakis M, Cai W, Dhou S, Cifter F, Hurwitz M, Segars P, Berbeco RI and Lewis JH, “A graphical User Interface for XCAT phantom configuration, generation and processing,” Biomed. Phys. Eng. Express 3(1), 017003 (2017).
  35. Jee K-W, Zhang R, Bentefour E, Doolan PJ, Cascio E, Sharp G, Flanz J, Lu H-M, Investigation of time-resolved proton radiography using x-ray flat-panel imaging system.  Phys. Med. Biol. 62(5): 1905–1919, 2017.
  36. Zhang R, Baer E, Sharp GC, Flanz J, Jee KW, Lu HM, Investigation of real tissue water equivalent path lengths using an efficient dose extinction method.  Phys. Med. Biol. 62(14): 5640-5651, 2017.
  37. Yip SS, Parmar C, Kim J, Huynh E, Mak R, Aerts HJ, Impact of experimental design on PET radiomics in predicting somatic mutation status. Eur J Radiol 97: 8-15, 2017.
  38. Coroller TP, Bi WL, Huynh E, Abedalthagafi M, Aizer AA, Greenwald NF, Parmar C, Narayan V, Wu WW, Miranda de Moura S, Gupta S, Beroukhim R, Wen PY, Al-Mefty O, Dunn IF, Santagata S, Alexander BM, Huang RY, Aerts HJ, Radiographic prediction of meningioma grade by semantic and radiomic features, PLoS One 12(11): e0187908, 2017.
  39. Zhang R, Jee KW, Cascio EW, Sharp GC, Flanz JB, Lu HM.  Improvement of single detector proton radiography by incorporating intensity of time-resolved dose rate functions. Phys. Med. Biol 63(1) 2017.
  40. Baer E, Lalonde A, Zhang R, Jee KW, Yang K, Sharp G, Liu B, Royle G, Bouchard H, Lu HM, Experimental validation of two dual-energy CT methods for proton therapy using heterogeneous tissue samples. Med Phys, 45(1):48-59, 2017.
  41. Lin Y, Bentefour H, Flanz J, Kooy H, Clasie, B. Design of a QA method to characterize submillimeter-sized PBS beam properties using a 3D ionization chamber array. Phys Med Biol 63(10) 105007, 2018.
  42. Hueso-Gonzalez F, Rabe M, Ruggieri T, Bortfeld T, Verburg JM.  A full-scale clinical prototype for proton range verification using prompt gamma-ray spectroscopy.  Phys Med Biol 63(18) 185019, 2018. (Featured Article)
  43. Dou TH, Coroller TP, van Griethuysen JJM, Mak RH, Aerts HJWL. Peritumoral radiomics features predict distant metastasis in locally advanced NSCLC. PLoS ONE 13(11): e0206108, 2018.
  44. Cai W, Oesten H, Clasie B, Winey B, Jee K-W.  Semi-automated IGRT QA using a cone-shaped scintillator screen detector for proton pencil beam scanning treatments.  Phys Med Biol 64(8) 085004, 2019.
  45. Xu Y, Hosny A, Zeleznik R, Parmar C, Coroller T, Franco I, Mak RH and Aerts HJWL. Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging.  Clinical Cancer Research 2019.
  46. Grassberger C, McClatchy DM, Geng C, Kamran SC, Fintelmann F, Maruvka YE, Z Piotrowska, H Willers, LV Sequist, AN Hata and H Paganetti. Patient-specific tumor growth trajectories determine persistent and resistant cancer cell populations during treatment with targeted therapies. Cancer Res 2019;79:3776–88.
  47. D Brivio, S. Albert, E. Freund, M. P. Gagne, E. Sajo, P. Zygmanski.  Self‐powered nano‐porous aerogel x‐ray sensor employing fast electron current. Med. Phys. 46 (9), 4233-4240, 2019.
  48. D Brivio, L. Naumann, S. Albert, E. Sajo, P. Zygmanski. 3D printing for prototyping of low-Z, low-density thin radiation sensor arrays. Med. Phys. 46 (12), 5770-5779, 2019.
  49. Guthier CV, Devlin PM., Harris TC., O’Farrell DA, Cormack RA. and Buzurovic I., Development and clinical implementation of semi‐automated treatment planning including 3D printable applicator holders in complex skin brachytherapy. accepted for publication in Med. Phys, 2020.