Niha Beig

Publications

Sadri, A., Janowczyk, A., Zhou, R., Verma, R., Beig, N., Antunes, J., Madabhushi, A., Tiwari, P., & Viswanath, S. E. (2020). Technical Note: MRQy — An open-source tool for quality control of MR imaging data. Medical Physics, 47 (12), 6029-6038.
Lu, C., Bera, K., WAng, X., Prasanna, P., Xue, Z., Janowczyk, A., Beig, N., Yang, M., Fu, P., Lewis, J., Choi, H., Schmid, R., Berezowska, S., Schalper, K., Rimm, D., Velcheti, V., & Madabhushi, A. (2020). A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study. The Lancet Digital Health, 2 (11), e594-e606.
Lu, C., Bera, K., WAng, X., Prasanna, P., Xue, Z., Janowczyk, A., Beig, N., Yang, M., Fu, P., Lewis, J., Choi, H., Schmid, R., Berezowska, S., Schalper, K., Rimm, D., Velcheti, V., & Madabhushi, A. (2020). A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study. The Lancet Digital Health, 2 (11), e594-e606.
Beig, N., Singh, S., Bera, K., Prasanna, P., Singh, G., Chen, J., SaeedBamashmos, A., Barnett, A., Hunter, K., Statsevych, V., Hill, V., Varadan, V., Madabhushi, A., Ahluwalia, M., & Tiwari, P. (2020). Sexually dimorphic radiogenomic models identify distinct imaging and biological pathways that are prognostic of overall survival in Glioblastoma. Neuro-Oncology.
Beig, N., Bera, K., Prasanna, P., Antunes, J., Correa, R., Singh, S., Saeed Bamashmos, A., Ismail, M., Braman, N., Verma, R., Hill, V., Statsevych, V., Ahluwalia, M., Varadan, V., Madabhushi, A., & Tiwari, P. (2020). Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma. Clinical Cancer Research, 26 (8), 1866-1876.
Vaidya, P., Bera, K., Gupta, A., WAng, X., Corredor-Prada, G., Fu, P., Beig, N., Prasanna, P., Patil, P., Velu, P., Rajiah, P., Gilkeson, R., Feldman, M., Choi, H., Velcheti, V., & Madabhushi, A. (2020). CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in stage I, II resectable non-small cell lung cancer: a retrospective multicohort study for outcome prediction. The Lancet Digital Health, 2 (3), e116-e128.
Prasanna, P., Mitra, J., Beig, N., Nayate, A., Patel, S., Ghose, S., Thawani, R., Partovi, S., Madabhushi, A., & Tiwari, P. (2019). Mass Effect Deformation Heterogeneity (MEDH) on Gadolinium-contrast T1-weighted MRI is associated with decreased survival in patients with right cerebral hemisphere Glioblastoma: A feasibility study. Scientific Reports, 9 (1).
Braman, N., Prasanna, P., Whitney, J., Singh, S., Beig, N., Etesami, M., Bates, D., Gallagher, K., Bloch, B., Vulchi, M., Turk, P., Bera, K., Abraham, J., Sikov, W., Somlo, G., Harris, L., Gilmore, H., Plecha, D., Varadan, V., & Madabhushi, A. (2019). Association of Peritumoral Radiomics With Tumor Biology and Pathologic Response to Preoperative Targeted Therapy for HER2 (ERBB2) �Positive Breast Cancer. JAMA Network Open, 2 (4), e192561.
Beig, N., Khorrami, M., Alilou, M., Prasanna, P., Braman, N., Orooji, M., Rakshit, S., Bera, K., Rajiah, P., Ginsberg, J., Donatelli, C., Thawani, R., Yang, M., Jacono, F., Tiwari, P., Velcheti, V., Gilkeson, R., Linden, P., & Madabhushi, A. (2019). Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas. Radiology, 290 (3), 783-792.
Alilou, M., Orooji, M., Beig, N., Prasanna, P., Rajiah, P., Donatelli, C., Velcheti, V., Rakshit, S., Yang, M., Jacono, F., Gilkeson, R., Linden, P., & Madabhushi, A. (2018). Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas. Scientific Reports, 8 (1).
Beig, N., Patel, S., Prasanna, P., Hill, V., Gupta, A., Correa, R., Bera, K., Singh, S., Partovi, S., Varadan, V., Ahluwalia, M., Madabhushi, A., & Tiwari, P. (2018). Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma. Scientific Reports, 8 (1).
Orooji, M., Alilou, M., Rakshit, S., Beig, N., Khorrami, M., Rajiah, P., Thawani, R., Ginsberg, J., Donatelli, C., Yang, M., Jacono, F., Gilkeson, R., Velcheti, V., Linden, P., & Madabhushi, A. (2018). Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography. Journal of Medical Imaging, 5 (2).
Thawani, R., McLane, M., Beig, N., Ghose, S., Prasanna, P., Velcheti, V., & Madabhushi, A. (2018). Radiomics and radiogenomics in lung cancer: A review for the clinician. Lung Cancer, 115 , 34-41.
Beig, N., Correa, R., Thawani, R., Prasanna, P., Badve, C., Gold, D., Madabhushi, A., DeBlank, P., & Tiwari, P. (2017). MEDU-48. MRI TEXTURAL FEATURES CAN DIFFERENTIATE PEDIATRIC POSTERIOR FOSSA TUMORS. Neuro-Oncology, 19 (suppl_4), iv47-iv47.