Dr. Manijeh Beigi | Medical Physics | Best Researcher Award
Dr. Manijeh Beigi is an Assistant Professor in the Radiation Oncology Department at Iran University of Medical Sciences. She specializes in dosimetry, radiotherapy treatment planning, and quality audits, with a focus on using machine learning for radiomics and dosiomics analysis. Dr. Beigi earned her Ph.D. in Medical Physics from Tehran University of Medical Sciences in 2018, where she researched the application of Diffusion Tensor Imaging (DTI) in radiotherapy planning. With over a decade of experience in radiotherapy physics, she has worked in multiple hospitals, including Imam Hosein, Haft-e-Tir, and Pardis Niloo Cancer Center. She is actively involved in research on predicting radiotherapy toxicity and advanced MR imaging applications. Dr. Beigi has mentored numerous students, contributed to high-impact journals, and presented at international conferences. Her research aims to enhance radiotherapy precision and patient safety through cutting-edge imaging and AI-driven models. ππ¬
Profile
Education π
Dr. Manijeh Beigi holds a Ph.D. in Medical Physics (2018) from Tehran University of Medical Sciences, where she developed automated clinical target volume determination for glioma treatment using multiparametric MRI. She completed her M.Sc. in Medical Physics (2010) at Tarbiat Modares University, focusing on radiotherapy dosimetry and quality audits in Varian linear accelerators. Her coursework covered key topics such as radiotherapy physics, radiobiology, MRI, CT, and PET physics, statistical methods, and treatment planning. Throughout her academic journey, she has specialized in advanced imaging techniques, radiomics, and AI-based predictive modeling for radiotherapy applications. Dr. Beigi’s education has provided her with strong expertise in medical physics, treatment planning optimization, and quality assurance, positioning her as a leader in radiation oncology research and innovation. π
Experience π¨βπ«
Dr. Manijeh Beigi has been an Assistant Professor at Iran University of Medical Sciences since 2020, where she focuses on radiotherapy physics, treatment planning, and quality assurance. Previously, she worked as a Radiotherapy Physicist at Imam Hosein Hospital (2010-2016), Haft-e-Tir Hospital (2016-Present), and Pardis Niloo Cancer Center (2019-2021), specializing in 3D conformal radiotherapy, IMRT planning, machine QA, and dosimetry. She was also a Research Assistant (2012-2018) at Tehran University of Medical Sciences, collaborating on quantitative MRI and spectroscopy research. Dr. Beigi has significant experience in mentoring students, managing research projects, and implementing AI-driven radiotherapy solutions. Her work integrates imaging and machine learning to optimize treatment efficacy and minimize patient toxicity. πΌπ¬
Research Interests π¬
Dr. Manijeh Beigi has received several accolades for her contributions to medical physics and radiotherapy research. She has been recognized for her work in AI-driven radiomics and dosiomics at international conferences, including ESTRO and AAPM. Her research on glioma segmentation using DTI and radiotherapy toxicity prediction has been published in top-tier journals. She has also been awarded grants for her studies on advanced MRI applications in radiotherapy planning. Additionally, Dr. Beigi has played a key role in multi-institutional research collaborations, earning recognition for her leadership in medical imaging and quality assurance. πποΈ
Publications π
- Safe bunker designing for the 18 MV Varian 2100 Clinac: a comparison between Monte Carlo simulation based upon data and new protocol recommendations
HG Manije Beigi, Fatemeh Afarandereports of practical oncology and radiotherapy 21, 42-49
- Heterogeneity analysis of diffusion-weighted MRI for prediction and assessment of microstructural changes early after one cycle of induction chemotherapy in nasopharyngealΒ β¦
M Beigi, AF Kazerooni, M Safari, M Alamolhoda, MS Moghdam, …La radiologia medica 123, 36-43
- Shuffle-ResNet: Deep learning for predicting LGG IDH1 mutation from multicenter anatomical MRI sequences
LA Mojtaba Safari , Manjieh Beiki , Ahmad Ameri , Saeed Hosseini Toudeshki …Biomed Phys Eng Express 8 (6)
- Findings ofΒ DTI-pΒ maps in comparison withΒ T2/T2-FLAIRΒ to assess postoperative hyper-signal abnormal regions in patients with glioblastoma
M Beigi, M Safari, A Ameri, MS Moghadam, A Arbabi, M Tabatabaeefar, …Cancer Imaging 18, 1-7
- Intracellular delivery of anticancer agents using dual responsive nanomicelles synthesized via RAFT polymerization
M Esmaeili, S Shahbaz, M Kamankesh, M Shahin, FSM Tekie, P Fadavi, …European Polymer Journal 198, 112417
- Long-term study of vocal dysfunction and quality of life in patients with non-laryngeal head and neck cancers post chemo-radiation therapy: Results of prospective analysis
ZM P Fadavi, S Bagherzadeh, F Torabinezhad, F Goli-Ahmadabad, M Beiki, S …International Journal of Radiation Research 21 (2), 227-232
- Malignancy probability map as a novel imaging biomarker to predict malignancy distribution: employing MRS in GBM patients
M Beigi, K Ghasemi, P Mirzaghavami, M Khanmohammadi, …Journal of Neuro-Oncology 138, 619-625
- 2025: Dosiomics models for prediction of skin toxicity after radiotherapy in breast cancer patients
M Beigi, S Soltani, Z Bagherpour, A Aliasgharzadeh, P Fadavi, M JajroudiRadiotherapy and Oncology 194, S599-S603
- Classification of LGG Tumor IDH1 Gene Mutation Status Using T2/FLAIR MRI Texture Information
M Safari, L Archambault, A Ameri, A Fatemi, M BeigiMEDICAL PHYSICS 47 (6), E356-E356
- Designing and Evaluating a Simple Small Phantom for Dosimetry Intercomparison of Linacs Photon Beams
BH M. Beigi, M. Allahverdi, H. GHiasiJournal of Nuclear Science and Technology