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

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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

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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

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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

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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

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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

Payabvash, S., Falcone, G. J., Sze, G. K., Jain, A., Beslow, L. A., Petersen, N. H., . . . Kimberly, W. T. (2020). Poor Outcomes Related to Anterior Extension of Large Hemispheric Infarction: Topographic Analysis of GAMES-RP Trial MRI Scans. Journal of Stroke and Cerebrovascular Diseases, 29(2), 104488. doi:10.1016/j.jstrokecerebrovasdis.2019.104488

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

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

Payabvash, S., Palacios, E. M., Owen, J. P., Wang, M. B., Tavassoli, T., Gerdes, M., . . . Mukherjee, P. (2019). White Matter Connectome Edge Density in Children with Autism Spectrum Disorders: Potential Imaging Biomarkers Using Machine-Learning Models. Brain Connectivity, 9(2), 209-220. doi:10.1089/brain.2018.0658

Wang, Y., Juliano, J. M., Liew, S., Mckinney, A. M., & Payabvash, S. (2019). Stroke atlas of the brain: Voxel-wise density-based clustering of infarct lesions topographic distribution. NeuroImage: Clinical, 24, 101981. doi:10.1016/j.nicl.2019.101981

Payabvash, S., Palacios, E. M., Owen, J. P., Wang, M. B., Tavassoli, T., Gerdes, M., . . . Mukherjee, P. (2019). Diffusion tensor tractography in children with sensory processing disorder: Potentials for devising machine learning classifiers. NeuroImage: Clinical, 23, 101831. doi:10.1016/j.nicl.2019.101831

Payabvash, S., Brackett, A., Forghani, R., Malhotra, A. (2019). Differentation of lymphotamous, metastatic, and non-malignant lymphadenopathy in the neck with quantitative diffusion-weighted imaging: systematic review and meta-analysis. Neuroradiology, 61(8):897-910. doi: 10.1007/s00234-019-02236-7

Malhotra, A., Wu, X., Payabvash, S., Matouk, C. S., Forman, H.P., Gandhi, D., Sanelli, P., Schindler, J. (2019). Comparative Effectiveness of Endovascular Thrombectomy in Elderly Stroke Patients. Stroke. 2019;50(4):936-969. doi:10.1161/STROKEAHA.119.025031

Payabvash, S. (2018). Quantitative diffusion magnetic resonance imaging in head and neck tumors. Quantitative Imaging in Medicine and Surgery, 8(10), 1052-1065. doi:10.21037/qims.2018.10.14

Payabvash, S., Tihan, T., & Cha, S. (2018). Volumetric voxelwise apparent diffusion coefficient histogram analysis for differentiation of the fourth ventricular tumors. The Neuroradiology Journal, 31(6), 554-564. doi:10.1177/1971400918800803