Kaustav Bera | Case School of Engineering

Publications

Corredor-Prada, G., Toro, P., Bera, K., Rasmussen, D., Sankar Viswanathan, V., Buzzy, C., Fu, P., Barton, L., Stroberg, E., Duval, E., Gilmore, H., Mukhopadyay, S., & Madabhushi, A. (2021). Computational pathology reveals unique spatial patterns of immune response in H&E images from COVID-19 autopsies: preliminary findings. Journal of Medical Imaging, 8 (Suppl 1), 017501.

Wang, X., Bera, K., Barrera, C., Zhou, Y., Lu, C., Vaidya, P., Yang, M., Schmid, R., Berezowska, S., Choi, H., Velcheti, V., & Madabhushi, A. (2021). A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer. EBioMedicine.

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.

Leo, P., Janowczyk, A., Elliott, R., Janaki, N., Bera, K., Shiradkar, R., Farre, X., Fu, P., El-Fahmawi, A., Shahait, M., Kim, J., Lee, D., Yamoah, K., Rebbeck, T., Khani, F., Robinson, B., Eklund, L., Jambor, I., Merisaari, H., , O., Taimen, P., Aronen, H., Boström, P., Tewari, A., Magi-Galluzzi, C., Klein, E., Purysko, A., Shin, N., Feldman, M., Gupta, S., Lai, P., & Madabhushi, A. (2021). Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study. NPJ Precision Oncology, 5 (1), 35.

Khorrami, M., Bera, K., Thawani, R., Rajiah, P., Gupta, A., Fu, P., Linden, P., Pennell, N., Jacono, F., Gilkeson, R., Velchetii, V., & Madabhushi, A. (2021). Distinguishing granulomas from adenocarcinomas by integrating stable and discriminating radiomic features on non-contrast computed tomography scans. European Journal of Cancer, 148 , 146 - 158.

Leo, P., Chandramouli, S., Farre, X., Elliott, R., Janowczyk, A., Bera, K., Fu, P., Janaki, N., El-Fahmawi, A., Shahait, M., Kim, J., Lee, D., Yamoah, K., Rebbeck, T., Khani, F., Robinson, B., Shih, N., Feldman, M., Gupta, S., McKenney, J., Lai, P., & Madabhushi, A. (2021). Computationally Derived Cribriform Area Index from Prostate Cancer Hematoxylin and Eosin Images Is Associated with Biochemical Recurrence Following Radical Prostatectomy and Is Most Prognostic in Gleason Grade Group 2. European Urology Focus.

Eck, B., Chirra, P., Muchhala, A., Hall, S., Bera, K., Tiwari, P., Madabhushi, A., Seiberlich, N., & Viswanath, S. E. (2021). Prospective Evaluation of Repeatability and Robustness of Radiomic Descriptors in Healthy Brain Tissue Regions In Vivo Across Systematic Variations in T2-Weighted Magnetic Resonance Imaging Acquisition Parameters. Journal of Magnetic Resonance Imaging (JMRI).

Koyuncu, C., Lu, C., Bera, K., Zhang, Z., Xue, Z., Toro, P., Corredor-Prada, G., Chute, D., Fu, P., Thorstad, W., Faraji, F., Bishop, J., Mehrad, M., Castro, P., Sikora, A., Thompson, L., Chernock, R., Lang Kuhs, K., Luo, J., Sandulache, V., Adelstein, D., Koyfman, S., Lewis, Jr, J., & Madabhushi, A. (2021). Computerized tumor multinucleation index (MuNI) is prognostic in p16+ oropharyngeal carcinoma. The Journal of Clinical Investigation, 131 (8), e145488.

Liu, J., Glaser, A., Bera, K., True, L., Reder, N., Eliceiri, K., & Madabhushi, A. (2021). Harnessing non-destructive 3D pathology. Nature Biomedical Engineering, 5 (3), 203 - 218.

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

WAng, X., Bera, K., Barrera, C., Zhou, Y., Lu, C., Vaidya, P., Fu, P., Yang, M., Schmid, R., Berezowska, S., Choi, H., Velcheti, V., & Madabhushi, A. (2021). A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer. EBIOMEDICINE, 69

Li, H., Bera, K., Toro, P., Fu, P., Zhang, Z., Lu, C., Feldman, M., Ganesan, S., Goldstein, L., Davidson, N., & Others, N. (2021). Collagen fiber orientation disorder from H\&E images is prognostic for early stage breast cancer: clinical trial validation. npj Breast Cancer, 7 (1), 1--10.

Koyuncu, C., Lu, C., Bera, K., Zhang, Z., Xue, Z., Toro, P., Corredor-Prada, G., Chute, D., Fu, P., Thorstad, W., & Others, W. (2021). Computerized tumor multinucleation index (MuNI) is prognostic in p16+ oropharyngeal carcinoma. The Journal of Clinical Investigation, 131 (8).

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.

Antunes, J., Ofshteyn, A., Bera, K., Wang, E., Brady, J., Willis, J., Friedman, K., Marderstein, E., Kalady, M., Stein, S., Purysko, A., Paspulati, R., Gollamudi, J., Madabhushi, A., & Viswanath, S. (2020). Radiomic Features of Primary Rectal Cancers on Baseline T 2 -Weighted MRI Are Associated With Pathologic Complete Response to Neoadjuvant Chemoradiation: A Multisite Study. Journal of Magnetic Resonance Imaging, 52 (5), 1531-1541.

Bera, K., Katz, I., & Madabhushi, A. (2020). Reimagining T Staging Through Artificial Intelligence and Machine Learning Image Processing Approaches in Digital Pathology. JCO clinical cancer informatics, 4 , 1039-1050.

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.

Alvarez-Jimenez, C., Antunes, J., Talasila, N., Bera, K., Brady, J., Gollamudi, J., Marderstein, E., Kalady, M., Purysko, A., Willis, J., Stein, S., Friedman, K., Paspulati, R., Delaney, C., Romero, E., Madabhushi, A., & Viswanath, S. (2020). Radiomic Texture and Shape Descriptors of the Rectal Environment on Post-Chemoradiation T2-Weighted MRI are Associated with Pathologic Tumor Stage Regression in Rectal Cancers: A Retrospective, Multi-Institution Study. Cancers, 12 (8).

Corredor-Prada, G., Lu, C., Koyuncu, C., Bera, K., Toro, P., Fu, P., Koyfman, S., Chute, D., Adelstein, D., Thorstad, W., Bishop, J., Faraji, F., Lewis, J., & Madabhushi, A. (2020). Computerized features of spatial interplay of tumor-infiltrating lymphocytes predict disease recurrence in p16+ oropharyngeal squamous cell carcinoma: A multisite validation study.. Journal of Clinical Oncology, 38 (15_suppl), 6559-6559.

Koyuncu, C., Corredor-Prada, G., Lu, C., Toro, P., Bera, K., Fu, P., Koyfman, S., Chute, D., Adelstein, D., Thorstad, W., Bishop, J., Faraji, F., Lewis, J., & Madabhushi, A. (2020). Combination of tumor multinucleation and spatial arrangement of tumor-infiltrating lymphocytes to predict overall survival in oropharyngeal squamous cell carcinoma: A multisite study.. Journal of Clinical Oncology, 38 (15_suppl), 6566-6566.

Kunte, S., Braman, N., Bera, K., Leo, P., Abraham, J., Montero, A., & Madabhushi, A. (2020). Radiomics risk score (RRS) on CT to predict survival and response to CDK 4/6 inhibitors in hormone receptor (HR) positive metastatic breast cancer (MBC).. Journal of Clinical Oncology, 38 (15_suppl), e13041-e13041.

Azarianpour Esfahani, S., Corredor-Prada, G., Bera, K., Fu, P., Joehlin-Price, A., Mahdi, H., & Madabhushi, A. (2020). Computerized features of spatial arrangement of tumor-infiltrating lymphocytes from H&E images predicts survival and response to checkpoint inhibitors in gynecologic cancers.. Journal of Clinical Oncology, 38 (15_suppl), 6074-6074.

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.

Leo, P., Elliott, R., Janowczyk, A., Janaki, N., Bera, K., Shiradkar, R., El-Fahmawi, A., Kim, J., Shahait, M., Shah, A., Thulasidass, H., Tewari, A., Gupta, S., Shih, N., Feldman, M., Lal, P., Lee, D., & Madabhushi, A. (2020). PD52-02 COMPUTER-EXTRACTED FEATURES OF GLAND MORPHOLOGY FROM DIGITAL TISSUE IMAGES IS COMPARABLE TO DECIPHER FOR PROGNOSIS OF BIOCHEMICAL RECURRENCE RISK POST-SURGERY. The Journal of Urology, 203 , e1089-e1090.

Khorrami, M., Bera, K., Leo, P., Vaidya, P., Patil, P., Thawani, R., Velu, P., Rajiah, P., Alilou, M., Choi, H., Feldman, M., Gilkeson, R., Linden, P., Fu, P., Pass, H., Velcheti, V., & Madabhushi, A. (2020). Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study. Lung Cancer, 142 , 90-97.

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., & 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.

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.

Vaidya, P., Bera, K., Patil, P., Gupta, A., Jain, P., Alilou, M., Khorrami, M., Velcheti, V., & Madabhushi, A. (2020). Novel, non-invasive imaging approach to identify patients with advanced non-small cell lung cancer at risk of hyperprogressive disease with immune checkpoint blockade. Journal for immunotherapy of cancer, 8 (2).

Khorrami, M., Bera, K., Leo, P., Vaidya, P., Patil, P., Thawani, R., Velu, P., Rajiah, P., Alilou, M., Choi, H., & Others, H. (2020). Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study. Lung Cancer, 142 , 90--97.

Bera, K., Schalper, K., Rimm, D., Velcheti, V., & Madabhushi, A. (2019). Artificial intelligence in digital pathology � new tools for diagnosis and precision oncology. Nature Reviews Clinical Oncology, 16 (11), 703-715.

Li, H., Whitney, J., Bera, K., Gilmore, H., Thorat, M., Badve, S., & Madabhushi, A. (2019). Quantitative nuclear histomorphometric features are predictive of Oncotype DX risk categories in ductal carcinoma in situ: preliminary findings. Breast Cancer Research, 21 (1), 114.

Khorrami, M., Jain, P., Bera, K., Alilou, M., Thawani, R., Patil, P., Ahmad, U., Murthy, S., Stephans, K., Fu, P., Velcheti, V., & Madabhushi, A. (2019). Corrigendum to �Predicting pathologic response to neoadjuvant chemoradiation in resectable stage III non-small cell lung cancer patients using computed tomography radiomic features� [Lung Cancer 135 (September) (2019) 1�9]. Lung Cancer, 136

Khorrami, M., Jain, P., Bera, K., Alilou, M., Thawani, R., Patil, P., Ahmad, U., Murthy, S., Stephans, K., Fu, P., Velcheti, V., & Madabhushi, A. (2019). Predicting pathologic response to neoadjuvant chemoradiation in resectable stage III non-small cell lung cancer patients using computed tomography radiomic features. Lung Cancer, 135 , 1-9.

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.

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.

Khorrami, M., Khunger, M., Zagouras, A., Patil, P., Thawani, R., Bera, K., Rajiah, P., Fu, P., Velcheti, V., & Madabhushi, A. (2019). Combination of Peri- and Intratumoral Radiomic Features on Baseline CT Scans Predicts Response to Chemotherapy in Lung Adenocarcinoma. Radiology: Artificial Intelligence, 1 (2).

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).

Bera, K., Velcheti, V., & Madabhushi, A. (2018). Novel Quantitative Imaging for Predicting Response to Therapy: Techniques and Clinical Applications. American Society of Clinical Oncology Educational Book.

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.

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.

Antunes, J., Selvam, A., Bera, K., Brady, J., Willis, J., Paspulati, R., Madabhushi, A., Delaney, C., & Viswanath, S. E. (2018). 857 - Machine Learning Analysis of the Whole Rectal Wall on Post-Neoadjuvant Chemoradiation MRI may offer Accurate Identifiction of Rectal Cancer Patients Needing more Aggressive Follow-Up or Surgery. Gastroenterology, 154 (6).