www.mrinrt.org
New paper using CaliberMRI’s Breast Phantom: “Initial experience in implementing quantitative DCE-MRI to predict breast cancer therapy response in a multi-center and multi-vendor platform setting”
As we get ready for ISMRM in Hawaii, we’re highlighting the amazing work from the past year by researchers using our phantoms. Today, please see the following November 2024 paper in Frontiers : “Initial experience in implementing quantitative DCE-MRI to predict breast cancer therapy response in a multi-center and multi-vendor platform setting” by @Brendan Moloney, @Xin Li, Michael Hirano, Assim Saad Eddin, MD, @Jeong Youn Lim, Debosmita Biswas, Anum K., Alina Tudorica, @Isabella Li, Mary Lynn Bryant, @Courtney Wille, Chelsea Pyle, @Habib Rahbar, Su Jin Kim Hsieh, @Travis Rice-Stitt, @Suzanne Dintzis, @Amani Bashir, @Evthokia Hobbs, @Alexandra Zimmer, @Jennifer Specht, Sneha Phadke, @Nicole Fleege, James Holmes, Savannah Partridge, @Wei Huang.
In case you missed it, we are sharing some interesting abstracts from the MRinRT conference held in NY last month. Reach out directly to the authors on their work!
Titles listed in order as they appear in program book:
“Longitudinal Diffusion-Weighted MRI for Treatment Response Assessment in Locally Advanced Rectal Cancer Patients Undergoing Short-Course Radiotherapy” by Jonathan Pham, Huiming Dong, PhD, Ann Raldow, and X. Sharon Qi – UCLA
“Implementation of Quantitative MRI-Guided Adaptive Radiotherapy on MRLINAC” by Jie Deng, @Yan Dai, Yen-Peng Liao, @Junjie Wu, @Chris Kabat, Jill B. De Vis, @Fan-Chi Su, Mu-han Lin, and Andrew Godley – UT Southwestern Medical Center.
“MRIdian Multiparametric MRI Working Group Assessment of DiffusionWeighted Imaging Protocols on the 0.35 T MRI-Linear Accelerator” by Natalia Lutsik, @Sungheon Gene Kim , Gage Redler, Joe Weygand, @ Matteo Nardini, Ryan Pennell, Siamak Nejad-Davarani, PhD, DABR, Tess Armstrong, and Eric Mellon.
“Correcting k-space trajectory errors and slice profile imperfections to improve the accuracy of T1 and T2 mapping with MR fingerprinting on a 1.5 T MR-Linac” by @Magali Nuixe, Rosie Goodburn , Bastien L., @Prashant Nair, and Andreas Wetscherek.
“Computed diffusion-weighted imaging and apparent diffusion coefficient for monitoring treatment response in prostate cancer: an MR-Linac feasibility study” Satomi Higuchi, @Jonathan Goodwin, Hilary Byrne, Michael Jameson, and Jeremy de Leon.
Questions about the phantoms used? Please reach out directly.
Warm regards,
The CaliberMRI team
https://lnkd.in/gQ9dYMQb
Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Weill Cornell Medicine, Geisel School of Medicine at Dartmouth, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, H. LEE MOFFITT CANCER CENTER AND RESEARCH INSTITUTE, INC, The Royal Marsden NHS Foundation Trust GenesisCare, University of Wollongong, University of Newcastle
MRinRT 2025