
Selected Publications
2022
Afridi, M., Jain, A., Aboain, M., Payabvash, S. (2022) Brain Tumor Imaging: Applications of Artificial Intelligence. Ultrasound, CT and MRI, Volume 43, Issue 2, Pages 153-169. doi: 10.1053/j.sult.2022.02.005
2021
Mak A, Matouk C, Avery EW, Behind J, Frey D, Madai VI, Vajkoczy P, Malhotra A, Abou Karam A, Sanelli P, Falcone GJ, Petersen NH, Sansing L, Sheth KN, Payabvash S. Similar admission NIHSS may represent larger tissue-at-risk in patients with right-sided versus left-sided large vessel occlusion. Journal of NeuroInterventional Surgery. October 2021. doi: 10.1136/neurintsurg-2021-017785
Haider SP, Qureshi AI, Jain A, Tharmaseelan H, Berson ER, Majidi S, Filippi CG, Mak A, Werring DJ, Acosta JA, Malhotra A, Kim JA, Sansing LH, Falcone GJ, Sheth KN, Payabvash S. The coronal plane maximum diameter of deep intracerebral hemorrhage predicts functional outcome more accurately than hematoma volume. International Journal of Stroke. October 2021. doi:10.1177/17474930211050749
Jain A, Malhotra A, Payabvash S. Imaging of Spontaneous Intracerebral Hemorrhage. Neuroimaging Clin N Am. 2021 May;31(2):193-203. doi: 10.1016/j.nic.2021.02.003
Haider SP, Qureshi AI, Jain A, Tharmaseelan H, Berson ER, Zeevi T, Majidi S, Filippi CG, Iseke S, Gross M, Acosta JN, Malhotra A, Kim JA, Sansing LH, Falcone GJ, Sheth KN, Payabvash S. Admission CT radiomic signatures outperform hematoma volume in predicting baseline clinical severity and functional outcome in the ATACH-2 trial intracerebral hemorrhage population. Eur J Neurol. 2021 Jun 30. doi: 10.1111/ene.15000
Haider, S.P., Sharaf, K., Zeevi, T., Baumeister, P., Reichel, C., Forghani, R., Kann, B.H., Petukhova, A., Judson, B.L., Prasad, M.L., Liu, C., Burtness, B., Mahajan, A., Payabvash, S., 2021. Prediction of post-radiotherapy locoregional progression in HPV-associated oropharyngeal squamous cell carcinoma using machine-learning analysis of baseline PET/CT radiomics. Translational Oncology, 14. doi:/10.1016/j.tranon.2020.100906
2020
Haider, S.P., Zeevi, T., Baumeister, P., Reichel, C., Sharaf, K., Forghani, R., Kann, B.H., Judson, B.L., Prasad, M.L., Burtness, B., Mahajan, A., Payabvash, S., 2020. Potential Added Value of PET/CT Radiomics for Survival Prognostication beyond AJCC 8th Edition Staging in Oropharyngeal Squamous Cell Carcinoma. Cancers, 12(1778). doi:10.3390/cancers12071778
Haider, S. P., Burtness, B., Yarbrough, W. G., & Payabvash, S. (2020). Applications of radiomics in precision diagnosis, prognostication and treatment planning of head and neck squamous cell carcinomas. Cancers of the Head & Neck, 5(1). doi:10.1186/s41199-020-00053-7
Payabvash, S., Aboian, M., Tihan, T., Cha, S., 2020. Machine Learning Decision Tree Models for Differentiation of Posterior Fossa Tumors Using Diffusion Histogram Analysis and Structural MRI Findings. Frontiers in Oncology. doi:10.3389/fonc.2020.00071
Haider SP, Mahajan A, Zeevi T, et al. PET/CT radiomics signature of human papilloma virus association in oropharyngeal squamous cell carcinoma [published online ahead of print, 2020 May 12]. Eur J Nucl Med Mol Imaging. 2020;10.1007/s00259-020-04839-2. doi:10.1007/s00259-020-04839-2
2019
2019
Payabvash, S., Chan, A., Jabehdar Maralani, P., & Malhotra, A. (2019). Quantitative diffusion magnetic resonance imaging for prediction of human papillomavirus status in head and neck squamous-cell carcinoma: A systematic review and meta-analysis. The Neuroradiology Journal, 32(4), 232–240. https://doi.org/10.1177/1971400919849808
2018