Prateek Prasanna | Case School of Engineering

Patents Pending

2015, "Co-Occurrence of Local Anisotrophic Gradient Orientations (CoLIAGe)" (USSN) 9,483,822, Anant Madabhushi, Pallavi Tiwari, & Prateek Prasanna.

Publications

Alilou, M., Prasanna, P., Bera, K., Gupta, A., Rajiah, P., Yang, M., Jacono, F., Velcheti, V., Gilkeson, R., Linden, P., & Madabhushi, A. (2021). A Novel Nodule Edge Sharpness Radiomic Biomarker Improves Performance of Lung-RADS for Distinguishing Adenocarcinomas from Granulomas on Non-Contrast CT Scans. Cancers, 13 (11), 2781.

Lu, C., Koyuncu, C., Corredor-Prada, G., Prasanna, P., Leo, P., WAng, X., Janowczyk, A., Bera, K., Lewis, J., Velcheti, V., & Madabhushi, A. (2021). Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers. Medical Image Analysis, 68

Hiremath, A., Shiradkar, R., Merisaari, H., Prasanna, P., Ettala, O., Taimen, P., Aronen, H., Boström, P., Jambor, I., & Madabhushi, A. (2021). Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps. European Radiology, 31 (1), 379-391.

Prasanna, P., Bobba, V., Figueiredo, N., Sevgi, D., Lu, C., Braman, N., Alilou, M., Sharma, S., Srivastava, S., Madabhushi, A., & Others, A. (2021). Radiomics-based assessment of ultra-widefield leakage patterns and vessel network architecture in the PERMEATE study: insights into treatment durability. British Journal of Ophthalmology, 105 (8), 1155--1160.

Ismail, M., Hill, V., Statsevych, V., Mason, E., Correa, R., Prasanna, P., Singh, G., Bera, K., Thawani, R., Ahluwalia, M., Madabhushi, A., & Tiwari, P. (2020). Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma?-A Feasibility Study. Frontiers in Computational Neuroscience, 14 , 563439.

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.

Hiremath, A., Shiradkar, R., Merisaari, H., Li, L., Prasanna, P., Ettala, O., Taimen, P., Aronen, H., Boström, P., Pierce, J., Tirumani, S., Rastinehad, A., Jambor, I., Purysko, A., & Madabhushi, A. (2020). PD57-05 A DEEP LEARNING NETWORK ALONG WITH PIRADS CAN DISTINGUISH CLINICALLY SIGNIFICANT AND INSIGNIFICANT PROSTATE CANCER ON BI-PARAMETRIC MRI: A MULTI-CENTER STUDY. The Journal of Urology, 203

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.

Khorrami, M., Prasanna, P., Gupta, A., Patil, P., Velu, P., Thawani, R., Corredor-Prada, G., Alilou, M., Bera, K., Fu, P., Feldman, M., Velcheti, V., & Madabhushi, A. (2020). Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in NonSmall Cell Lung Cancer. Cancer Immunology Research, 8 (1), 108-119.

Khorrami, M., Prasanna, P., Gupta, A., Patil, P., Velu, P., Thawani, R., Corredor-Prada, G., Alilou, M., Bera, K., Fu, P., & Others, P. (2020). Changes in CT radiomic features associated with lymphocyte distribution predict overall survival and response to immunotherapy in non-small cell lung cancer. Cancer immunology research, 8 (1), 108.

Moosavi, A., Figueiredo, N., Prasanna, P., K. Srivastava, S., Sharma, S., Madabhushi, A., & Ehlers, J. (2020). Imaging Features of Vessels and Leakage Patterns Predict Extended Interval Aflibercept Dosing Using Ultra-Widefield Angiography in Retinal Vascular Disease: Findings from the PERMEATE Study. IEEE Transactions on Biomedical Engineering.

Prasanna, P., Bobba, V., Figueiredo, N., Sevgi, D., Lu, C., Braman, N., Alilou, M., Sharma, S., Srivastava, S., Madabhushi, A., & Others, A. (2020). Radiomics-based assessment of ultra-widefield leakage patterns and vessel network architecture in the PERMEATE study: insights into treatment durability. British Journal of Ophthalmology.

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).

Prasanna, P., Khorrami, M., Gupta, A., Patil, P., Khunger, M., Velu, P., Bera, K., Alilou, M., Velcheti, V., & Madabhushi, A. (2019). Intra and perinodular CT delta radiomic features associated with early response to predict overall survival (OS) in immunotherapy-treated non-small cell lung cancer (NSCLC): A multisite multi-agent study.. Journal of Clinical Oncology, 37 (15_suppl), 2588-2588.

Prasanna, P., Karnawat, A., Ismail, M., & Madabhushi, A. (2019). Radiomics-based convolutional neural network for brain tumor segmentation on multiparametric magnetic resonance imaging. Journal of Medical Imaging, 6 (02).

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.

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).

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).

Patil, P., Bera, K., Vaidya, P., Prasanna, P., Khunger, M., Khunger, A., Velcheti, V., & Madabhushi, A. (2018). Correlation of radiomic features with PD-L1 expression in early stage non-small cell lung cancer (ES-NSCLC) to predict recurrence and overall survival (OS).. Journal of Clinical Oncology, 36 (15_suppl), e24247-e24247.

WAng, X., Barrera, C., Velu, P., Bera, K., Prasanna, P., Khunger, M., Khunger, A., Velcheti, V., & Madabhushi, A. (2018). Computer extracted features of cancer nuclei from H&E stained tissues of tumor predicts response to nivolumab in non-small cell lung cancer.. Journal of Clinical Oncology, 36 (15_suppl), 12061-12061.

Barrera, C., Velu, P., Bera, K., WAng, X., Prasanna, P., Khunger, M., Khunger, A., Velcheti, V., Romero, E., & Madabhushi, A. (2018). Computer-extracted features relating to spatial arrangement of tumor infiltrating lymphocytes to predict response to nivolumab in non-small cell lung cancer (NSCLC).. Journal of Clinical Oncology, 36 (15_suppl), 12115-12115.

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.

Madabhushi, A., Braman, N., Prasanna, P., & Tiwari, P. (2017). Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI. Breast Cancer Research, 19 (1), 57.

Bektik, E., Dennis, A., Prasanna, P., Madabhushi, A., & Fu, J. (2017). Single cell qPCR reveals that additional HAND2 and microRNA-1 facilitate the early reprogramming progress of seven-factor-induced human myocytes. PLoS ONE, 12 (8).

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.

Tiwari, P., Prasanna, P., Wolansky, L., Pinho, M., Cohen, M., Nayate, A., Gupta, A., Singh, G., Hatanpaa, K., Sloan, A., Rogers, L., & Madabhushi, A. (2016). Computer-Extracted Texture Features to Distinguish Cerebral Radionecrosis from Recurrent Brain Tumors on Multiparametric MRI: A Feasibility Study.. AJNR. American journal of neuroradiology, 37 (12), 2231-2236.

Prasanna, P., Tiwari, P., & Madabhushi, A. (2016). Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor.. Scientific reports, 6 , 37241.

Prasanna, P., Patel, J., Partovi, S., Madabhushi, A., & Tiwari, P. (2016). Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings.. European radiology.

Prasanna, P., Tiwari, P., & Madabhushi, A. (2014). Co-occurrence of local anisotropic gradient orientations (CoLIAGe): distinguishing tumor confounders and molecular subtypes on MRI.. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 17 (Pt 3), 73-80.