Publications

JOURNAL PUBLICATIONS

CONFERENCE PROCEEDINGS

  • Radiogenomic characterization of response to chemo-radiation therapy in Glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathways. Niha Beig, Prateek Prasanna, Virginia Hill, Vinay Varadan, Anant Madabhushi, and Pallavi Tiwari. SPIE, Medical Imaging: Computer-Aided Diagnosis (2019).
  • Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI. Sukanya Iyer, Marwa Ismail, Benita Tamrazi, Ramon Correa, Prateek Prasanna, Niha Beig, Ruchika Verma, Kaustav Bera, Volodymyr Statsevych Ashley Margol, Alexander Judkins, Anant Madabhushi, and Pallavi Tiwari. SPIE, Medical Imaging: Computer-Aided Diagnosis (2019).
  • Radiomics of the lesion habitat on pre-treatment MRI to predict response to chemo-radiation therapy in Glioblastoma. Ruchika Verma, Ramon Correa, Virginia Hill, Niha Beig, Abdelkar Mahammedi, Anant Madabhushi, Pallavi Tiwari. SPIE, Medical Imaging: Computer-Aided Diagnosis (2019).
  • Vascular Network organization via Hough transform (VaNgOGH): A novel radiomic biomarker for diagnosis and treatment response. Nathaniel Braman, Prateek Prasanna, Niha Beig, Mehdi Alilou, Anant Madabhushi. Medical Image Computing and Computer Assisted Intervention (MICCAI 2018). Lecture Notes in Computer Science. doi: 10.1007/978-3-030-00934-2_89
  • Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma. Niha Beig, Jay Patel, Prateek Prasanna, Sasan Partovi, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari. Proc. SPIE 10134, Medical Imaging: Computer-Aided Diagnosis (2017). doi:10.1117/12.2255694
  • Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An integrated descriptor for brain tumor prognosis. Prateek Prasanna, Jhimli Mitra, Niha Beig, Sasan Partovi, Gagan Singh, M Pinho, Anant Madabhushi, Pallavi Tiwari. Medical Image Computing and Computer Assisted Intervention (MICCAI 2017)
  • Automatic localization of IASLC-defined mediastinal lymph node stations on CT images using fuzzy models. Monica M. S. Matsumoto, Niha Beig, Jayaram K. Udupa, Steven Archer, Drew A. Torigian. Proc. of SPIE Vol. 9035 90350J-1

ABSTRACTS

  1. Beig, N, Ismail, M, Saeed Bamashmos, A, Statsevych, V, Hill, Virginia, Anant Madabhushi,A, Ahluwalia,M and Tiwari, P. “Gender-specific probabilistic atlases of glioblastoma reveal impact of tumor location on progression free survival”. Proceedings of the Journal of Neuro-Oncology, 2019. Phoenix, Arizona, USA
  2. Ismail, M, Correa, R, Bera, K, Bamashmos, A, Statsevych, V, Prasanna, P, Beig, N, Madabhushi, A, Ahluwalia, M, and Tiwari, P, “Radiomic features localized to stereotactic biopsy locations can capture EGFR presence in Glioblastoma.” Proceedings of the Journal of Neuro-Oncology, 2019.  Phoenix, Arizona, USA.
  3. Beig, N, Prasanna, P, Ismail, M, Hill, V, Statsevych, V, Varadan, V, Madabhushi, A and Tiwari, P. “Radiogenomic analysis of Glioblastoma on pre-treatment Gd-T1w MRI reveals gender-specific imaging features and signaling pathways”. Proceedings of the Radiologic Society of North America Annual Meeting (RSNA), 2019. Chicago, IL, USA.
  4. Prasanna, P, Beig, N, Gupta, A, Gilkeson, R, and Madabhushi, A. “Radiomic Machine Interpretations Can Improve Lung Nodule Diagnostic Sensitivity for Human Readers: Preliminary findings in a multi-site multi-reader study”. In: Proceedings of the Radiologic Society of North America Annual Meeting (RSNA), 2019. Chicago, IL, USA.
  5. Song, B, Correa, R, Prasanna, P, Beig, N, Madabhushi,A, and Tiwari,P , “Directional-gradient based radiomic descriptors from pre-treatment perfusion DSC-MRI to differentiate long-term from short-term survivors in Glioblastoma: Preliminary findings”, The International Society for Magnetic Resonance in Medicine (ISMRM), 2019.
  6. Verma, R, Correa, R, Hill, V, Beig, N, Mohammedi,A , Ismail, M, Madabhushi, A, and Tiwari, P, “Radiomic features from enhancing tumor on pre-treatment multiparametric MRI scans are predictive of response to chemo-radiation therapy in Glioblastoma and are associated with histological phenotypes”, The International Society for Magnetic Resonance in Medicine (ISMRM), 2019.
  7. Iyer, S, Ismail, M, Tamrazi, B, Margol, A, Correa, R, Prasanna, P, Beig, N, Madabhushi, A, and Tiwari, P, “Gradient-entropy based radiomic features to predict molecular sub-types of pediatric Medulloblastoma on Gadolinium-enhanced T1w MRI”, The International Society for Magnetic Resonance in Medicine (ISMRM), 2019.
  8. Beig, N, Hill, V, Prasanna, P, Varadan, V, Madabhushi, A, and Tiwari, P,“Support vector machine (SVM) classifier based approach for prediction of chemo-radiation therapy response in grade 4 brain tumors on pre-treatment MRI scans”, The 13th Women in Machine Learning (WiML) Workshop, 2018. Montreal, Quebec, Canada.
  9. Beig, N, Ismail, M, Madabhushi, A, Ahluwalia, M, Tiwari, P, “Probabilistic Atlases of Pre-Treatment MRI Reveal Hemispheric and Lobe-Specific Spatial Distributions across Molecular Sub-Types of Diffuse Gliomas”, Proceedings of the Radiological Society of North America Annual Meeting, 2018. Chicago, IL, USA.
  10. Beig, N,  Prasanna,P, Hill,V, Varadan,V, Madabhushi,A, and Tiwari,P, “Radiomic features of Glioblastoma on pre-treatment Gd-T1w MRI are predictive of response to chemo-radiation therapy and associated with AKT and apoptosis pathways”, Proceedings of the Journal of Neuro-Oncology, 2018.  New Orleans, Louisiana, USA.
  11. Beig, N, Braman,N, Prasanna,P, Varadan,V, Madabhushi,A, and Tiwari,P, “Radiogenomic analysis of Glioblastoma reveals textural features from MRI that correlate with genomic immune score and are also predictive of chemo-radiation treatment response”, Proceedings of the Journal of Neuro-Oncology, 2018.  New Orleans, Louisiana, USA.
  12. Braman,N, Prasanna,P, Singh,S, Beig,N, et al.,“Intratumoral and peritumoral MRI signatures of HER2-enriched subtype also predict pathological response to neoadjuvant chemotherapy in HER2+ breast cancers”, San Antonio Breast Cancer Symposium, 2017. San Antonio, TX, USA
  13. Braman,N, Prasanna,P, Singh,S, Beig,N, et al.,“ Radiogenomic analysis of HER2+ breast cancer reveals MRI features correlated with genomic immune index are predictive of neoadjuvant chemotherapy response”, San Antonio Breast Cancer Symposium, 2017. San Antonio, TX, USA
  14. Prasanna P, Mitra J, Beig N, Partovi S, Singh G, Pinho M, Madabhushi A, Tiwari P. “Structural deformation field on T1w MRI in healthy brain parenchyma is associated with overall survival in treatment-naïve glioblastoma multiforme”, Society for Neuro-Oncology 2017. San Francisco, CA, USA
  15. Braman, N, Prasanna, P, Singh, S, Beig, N, Plecha, DM, Gilmore, H, Harris, L, Etesami, M, Bates, D,Gallagher, K, Bloch, N, Varadan, V, Madabhushi, A, ” Texture Entropy Features at 1 Centimeter Outside HER2+ Breast Cancer Lesions Predict Response-Associated Molecular Subtypes on DCE-MRI,” Proceedings of Radiologic Society of North America (RSNA) 2017. Chicago, IL, USA
  16. Beig,N , Correa,R , Thawani,R , Prasanna,P , Badve,C , Gold,D , deBlank,P , Madabhushi,A , and Tiwari,P. “MRI textural features can differentiate pediatric posterior fossa tumors”, SNO Pediatric Neuro-Oncology Basic and Translational Research Conference, 2017. New York City, NY, USA
  17. Beig,N , Correa,R , Prasanna,P , Mitra,J , Nayate,A , Madabhushi,A , and Tiwari,P. “Radiogenomic analysis of distinct tumor sub-compartments on T2 and FLAIR predict distinct molecular subtypes in Lower Grade Gliomas”, The International Society for Magnetic Resonance in Medicine (ISMRM), 2017. Honolulu, HI, USA
  18. Beig,N, Correa,R, Prasanna,P, Mitra,J, Nayate,A, Madabhushi,A, Tiwari,P. ”Predicting IDH mutation status on routine treatment-naïve MRI using radiogenomic features from peritumoral brain parenchyma”, Proceedings Of The Society For Neuro-Oncology, 2016. Scottsdale, AZ, USA
  19. Beig,N , Orooji,M, Rajiah,P , Rakshit,S , Yang,M , Jacono,F , Prasanna,P , Tiwari,P , Velcheti,V ,Gilkeson,R, Linden,P, Madabhushi,A, “Radiomic Features of the Perinodular Habitat on Non-contrast Lung CT Discriminates Adenocarcinoma from Granulomas”, Proceedings of the Radiologic Society of North America, 2016. Chicago, IL, USA
  20. Rakshit,S , Orooji,M , Beig,N , Rajiah,P , Yang,M , Jacono,F , Velcheti,V ,Gilkeson,R, Linden,P , Madabhushi,A, “Evaluation of radiomic features on baseline CT scan to predict clinical benefit for pemetrexed based chemotherapy in metastatic lung adenocarcinoma.” American Society of Clinical Oncology Annual Meeting, 2016. Chicago, IL, USA
  21. Orooji,M , Rakshit,S , Alilou,M, Beig,N , Rajiah,P , Yang,M , Jacono,F , Velcheti,V, Gilkeson,R, Linden,P , Madabhushi,A , “Computerized textural analysis of lung CT to enable quantification of tumor infiltrating lymphocytes in NSCLC.” American Society of Clinical Oncology Annual Meeting, 2016. Chicago, IL, USA

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