I'm a radiation oncologist specializing in the treatment of central nervous system tumors (such as brain metastases, gliomas, and meningiomas) with external beam radiotherapy and Gamma Knife® radiosurgery.
My research focuses on the use of computational and machine learning methods for optimizing treatment planning efficiency, performing oncology outcomes analysis, and discovering new biology in preclinical models.
I actively participate in clinical supervision and didactic education for medical students and residents. In addition, I have mentored trainee research projects that have subsequently earned institutional awards. I remain committed to being a mentor to the next generation of medical practitioners and scientists, including those from disadvantaged backgrounds.
1) Rusthoven CG, Yamamoto M, Bernhardt D, Smith DE, Gao D, Serizawa T, Yomo S, Aiyama H, Higuchi Y, Shuto T, Akabane A, et al. Evaluation of first-line radiosurgery vs whole-brain radiotherapy for small cell lung cancer brain metastases: the FIRE-SCLC cohort study. JAMA Oncology. 2020 Jun 4.
2) Porter E, Fuentes P, Siddiqui Z, Thompson A, Levitin R, Solis D, Myziuk N, Guerrero T. Hippocampus Segmentation on non‐Contrast CT using Deep Learning. Medical Physics. 2020 Feb 17.
3) Siddiqui ZA, Squires BS, Johnson MD, Baschnagel AM, Chen PY, Krauss DJ, Olson RE, Meyer KD, Grills IS. Predictors of radiation necrosis in long-term survivors after Gamma Knife stereotactic radiosurgery for brain metastases. Neuro-Oncology Practice. 2019 Dec 6.
Full Publication List on Pubmed: https://pubmed.ncbi.nlm.nih.gov/?term=Siddiqui%2C+Zaid%5BAuthor%5D
RSNA R&E Foundation Resident Award (RR1867), Role: PI, Mentor: Thomas Guerrero, MD PhD. 07/01/2018 - 06/30/2019
A Deep Learning Framework for Radiotherapy Delivery in Thoracic Oncology