Brain Image Computing (BrIC) Laboratory
Peer-Reviewed Publications
2022
Verma R, Hill V, Statsevych V, Bera K, Correa R, Leo P, Ahluwalia M, Madabhushi A, Tiwari P, Stable-and-discriminatory radiomic features from the tumor and its habitat associated with progression-free survival in Glioblastoma: A multi-institutional study, Submitted to American Journal of Neuroradiology (in press).
Yadav I, Ismail M, Statsevych V, Correa R, Ahluwalia M, Tiwari P, “Distinguishing non-contrast enhancing tumor from vasogenic edema using radiomic analysis on pre-treatment MRI scans”, SPIE Medical Imaging, 2022.
Sandino A, Verma R, Becerra D, Chen Y, Romero E, Tiwari P, “A Hierarchical Deep Learning Approach for Segmentation of Glioblastoma Tumor Niches on Digital Histopathology”, SPIE Medical Imaging, 2022.
Ismail M, Prasanna P, Bera K, Statsevych V, Hill V, Singh G, Partovi S, Beig N, McGarry S, Laviolette P, Ahluwalia M, Madabhushi A, Tiwari P, Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma, IEEE Transactions of Medical Imaging (in press).
Antunes, JT*, Ismail, M, Hossain, I, Wang, Z, Prasanna, P, Madabhushi, A, Tiwari, P, Viswanath, SE, “RADIomic Spatial TexturAl descripTor (RADISTAT): Quantifying spatial organization of textural heterogeneity on imaging associated with tumor response to treatment”, IEEE Journal of Biomedical and Health Informatics (in press).
2021
Pinho, M. C., Bera, K., Beig, N., & Tiwari, P. (2021). MRI Morphometry in Brain Tumors: Challenges and Opportunities in Expert, Radiomic, and Deep-Learning-Based Analyses. In G. Seano (Ed.), Brain Tumors (Vol. 158, pp. 323–368). Springer US.
Tiwari, P., & Verma, R. (2021). The Pursuit of Generalizability to Enable Clinical Translation of Radiomics. Radiology: Artificial Intelligence, 3(1), e200227.
2020
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.
Beig, N., Bera, K., & Tiwari, P. (2020). Introduction to radiomics and radiogenomics in neuro-oncology: Implications and challenges. Neuro-Oncology Advances, 2(Supplement_4), iv3–iv14.
Sadri, A. R., 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.
Verma, R., Correa, R., Hill, V. B., Statsevych, V., Bera, K., Beig, N., Mahammedi, A., Madabhushi, A., Ahluwalia, M., & Tiwari, P. (2020). Tumor Habitat–derived Radiomic Features at Pretreatment MRI That Are Prognostic for Progression-free Survival in Glioblastoma Are Associated with Key Morphologic Attributes at Histopathologic Examination: A Feasibility Study. Radiology: Artificial Intelligence, 2(6), e190168.
Pati, S., Verma, R., Akbari, H., Bilello, M., Hill, V. B., Sako, C., Correa, R., Beig, N., Venet, L., Thakur, S., Serai, P., Ha, S. M., Blake, G. D., Shinohara, R. T., Tiwari, P., & Bakas, S. (2020). Reproducibility analysis of multi‐institutional paired expert annotations and radiomic features of the Ivy Glioblastoma Atlas Project (Ivy GAP) dataset. Medical Physics, 47(12), 6039–6052.
Beig, N., Singh, S., Bera, K., Prasanna, P., Singh, G., Chen, J., Saeed Bamashmos, A., Barnett, A., Hunter, K., Statsevych, V., Hill, V. B., Varadan, V., Madabhushi, A., Ahluwalia, M. S., & Tiwari, P. (2020). Sexually dimorphic radiogenomic models identify distinct imaging and biological pathways that are prognostic of overall survival in glioblastoma. Neuro-Oncology, noaa231.
Beig, N., Bera, K., Prasanna, P., Antunes, J., Correa, R., Singh, S., Saeed Bamashmos, A., Ismail, M., Braman, N., Verma, R., Hill, V. B., Statsevych, V., Ahluwalia, M. S., 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.
Ismail M, Correa R, Bera K, Verma R, Bamashmos AS, Beig N, Antunes J, Prasanna P, Statsevych V, Ahulwalia M, Tiwari P. “Spatial-And-Context aware (SpACe) “virtual biopsy” radiogenomic maps to target tumor mutational status on structural MRI.” MICCAI 2020.
Gupta A, Viswanath S, Tiwari P, Quality assessment of MRI using a dense neural network model, In Proceedings of SPIE Medical Imaging conference, Houston, USA, February, 2020.
Hiremath Y, Ismail M, Verma R, Gupta A, and Tiwari P, Combining Deep and Hand-crafted MRI features for identifying gender-specific differences in ASD versus controls, In Proceedings of SPIE Medical Imaging conference, Houston, USA, February, 2020.
Correa R, Chen J, Yu J, and Tiwari P, Distinguishing Treatment Effects of Radiation Therapy from Recurrent Tumor in Post-Treatment Imaging of Metastatic Tumor, In Proceedings of SPIE Medical Imaging conference, Houston, USA, February, 2020.
2019
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge, arXiv:1811.02629, 2019 (pre-print).
Prasanna, P., L. Rogers, T. C. Lam, M. Cohen, A. Siddalingappa, L. Wolansky, M. Pinho et al. "Disorder in pixel-level edge directions on T1WI is associated with the degree of radiation necrosis in primary and metastatic brain tumors: preliminary findings." American Journal of Neuroradiology 40, no. 3 (2019): 412-417.
Prasanna, P., Karnawat, A., Ismail, M., Madabhushi, A., & Tiwari, P. (2019). Radiomics-based convolutional neural network for brain tumor segmentation on multiparametric magnetic resonance imaging. Journal of Medical Imaging, 6(2), 024005.
Prateek Prasanna, Jhimli Mitra , Niha Beig , Ameya Nayate , Jay Patel , Soumya Ghose , Rajat Thawani , Sasan Partovi , Anant Madabhushi, Pallavi Tiwari, Mass Effect Deformation Heterogeneity (MEDH) on T1-weighted MRI is associated with decreased survival in patients with right cerebral hemisphere Glioblastoma: A feasibility study, Volume 9, no. 1, Article number: 1145 (2019).
Beig N, Prasanna P, Hill V, Verma R, Varadan V, Madabhushi A, Tiwari P, "Radiogenomic characterization of response to chemo-radiation therapy in Glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathways." SPIE Medical Imaging 2019, vol 10951
Iyer S, Ismail M, Tamrazi B, Correa R, Prasanna P, Beig N, Verma R, Bera K, Statsevych V, Margol A, Judkins A, Madabhushi A, Tiwari P, "Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI", The International Society for Optics and Photonics (SPIE) Medical Imaging 2019, vol 10950.
Verma R, Correa R, Hill V, Beig N, Mahammedi A, Madabhushi A, Tiwari P, "Radiomics of the lesion habitat on pre-treatment MRI to predict response to chemo-radiation therapy in Glioblastoma", SPIE Medical Imaging 2019, vol 10950.
2018
Beig, N, Khorrami , M, Alilou, M, Prasanna, P, Braman, N, Orooji, M, Rakshit, S, Bera, K, Rajiah, P, Ginnesburg, J, Donatelli, C, Thawani, R, Yang, M, Jacono, F, Tiwari, P, Velcheti, V, Gilkeson, R, Linden, P, Madabhushi A, A Combination of Intranodular and perinodular radiomic features on non-contrast lung CT distinguishes NSCLC adenocarcinoma from granulomas, Radiology.
Ismail, M, Hill, V, Statsevych, V, Huang, R, Prasanna, P, Correa, R, Singh, G, Bera, K, Beig, N, Thawani, R, Madabhushi, A, Aahluwalia, M, Tiwari, P, Shape features of the lesion habitat to differentiate brain tumor progression from pseudo-progression on routine multi-parametric MRI: A multi-site study, American Journal of Neuro-radiology, 2018.
Penzias G, Singanamalli A, Elliott R, Gollamudi J, Shih N, Feldman M, Stricker P, Delprado W, Tiwari S, Bohm M, Haynes AM, Ponsky L, Fu P, Tiwari P, Viswanath S, Madabhushi A, Identifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary Findings, PlosOne, 2018.
2017
Beig N, Patel J, Prasanna P, Partovi S, Varadan V, Ahluwalia M, Madabhushi A, Tiwari P, Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma, Nature Scientific Reports, 2017. Download link
Braman, N, Etesami, M, Prasanna, P, Dubchuk, C, Gilmore, H, Tiwari, P, Plecha, D, Madabhushi, A, Intratumoral and peritumoral radiomics for the pre-treatment prediction of pathological complete response to neo-adjuvant chemotherapy from breast DCE-MRI, Breast Cancer Research, 2017. Pubmed
Prasanna P, Mitra J, Beig N, Partovi S, Singh G, Pinho M, Madabhushi A, Tiwari P. Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An integrated descriptor for brain tumor prognosis. MICCAI 2017.
Antunes J, Prasanna P, Madabhushi M, Tiwari P, Viswanath S, RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing intra-tumoral heterogeneity for response and outcome prediction. MICCAI 2017. +Joint last authors.
Beig N, Patel J, Prasanna P, Partovi S, Varadan V, Madabhushi A, Tiwari P, "Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in Glioblastoma", The International Society for Optics and Photonics (SPIE) Medical Imaging, 2017.
2016
Prasanna P, Patel J, Partovi S, Madabhushi A, Tiwari P, “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, p. 1-10 10 p, Oct, 2016. Pubmed
Prasanna P,* Tiwari P*, Madabhushi A, "Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor", Nature Scientific Reports, 37241 (2016) doi:10.1038/srep37241, Download Link
Tiwari P*, Viswanath S*, Lee G*, Madabhushi M, Dimensionality Reduction-based Fusion Approaches for Imaging and Non-imaging Biomedical Data: Concepts, Workflow, and Use-Cases, BME Medical Imaging, 2016 (*Joint first authors) Download Link
Tiwari P, Prasanna P, Wolansky L, Pinho M, Cohen M, Nayate AP, Gupta A, Singh G, Hatanpaa K, Sloan A, Rogers L, Madabhushi A, Can Computer-extracted texture features distinguish Radiation Necrosis from Recurrent Brain Tumors on multi-parametric MRI? – A Feasibility Study, American Journal of Neuro Radiology, 2016 (Top 20 most read AJNR papers in 2016) (Nominated for the annual Lucien Levy Best Research Article Award). Download link
2015
Tiwari P, Danish S, Madabhushi A, Association of computerized texture features on MRI with early treatment response following laser ablation for neuropathic cancer pain: preliminary findings, Journal of Medical Imaging, 2(4), 041008, 2015. Pubmed SPIE Digital Library
2014
Tiwari P, Danish S, Madabhushi A, Identifying MRI Markers Associated with Early Response following Laser Ablation for Neurological Disorders: Preliminary Findings, PlosOne, 2014, Dec 11;9(12):e114293. doi: 10.1371/journal.pone.0114293. eCollection 2014. Pubmed
Tiwari, P*, Prasanna, P*, Madabhushi, A, “Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing tumor confounders and molecular subtypes on MRI,” In Proc of Medical Image Computing and Computer Assisted Interventions (MICCAI), vol. 17[3], pp. 73-80, 2014. (*joint first authors) (Young Scientist Award, runners up, selected as oral presentation, Acceptance rate = 4%) Pubmed
Tiwari, P, Rogers, L, Wolansky, L, Madabhushi, A, “Differentiating recurrent glioblastoma multiforme from radiation induced effects via texture analysis on multi-parametric MRI”, The International Society for Optics and Photonics (SPIE) Medical Imaging, 2014 (Honorable Mention for Best Poster Presentation, Conference on Computer Aided Diagnosis) Pubmed
Tiwari, P, Shabbar, D, Madabhushi, A, “Identifying MRI markers to evaluate early treatment related changes post laser ablation for cancer pain management,” The International Society for Optics and Photonics (SPIE) Medical Imaging, 2014, (Cum Laude for Best Poster Presentation, Conference on Image Guided Interventions) Pubmed.
2013
Tiwari P, Kurhanewicz J, Madabhushi A, Multi-Kernel Graph Embedding for Detection and Gleason Grading of Prostate Cancer In vivo using Multi-Protocol Magnetic Resonance Imaging, MeDIA, 7(2): 219-35, 2013. Pubmed
Tiwari, P, Danish, S, Wong, S, Madabhushi A, “Quantitative Evaluation of Multi-parametric MR Imaging Marker Changes Post-laser Interstitial Ablation Therapy (LITT) for Epilepsy,” The International Society for Optics and Photonics (SPIE) Medical Imaging, 2013 Pubmed.
2012
Tiwari P, Viswanath S, Kurhanewicz J, Madabhushi, A, Multimodal Wavelet Embedding Representation for data Combination (MaWERiC): Integrating Magnetic Resonance Imaging and Spectroscopy for Prostate Cancer Detection, NMR in Biomedicine, 25: 607–619, 2012. Pubmed
2011
Toth R, Tiwari P, Rosen M, Madabhushi A, “A Magnetic Resonance Spectroscopy driven Initialization Scheme for Active Shape Model based Prostate Segmentation,” Medical Image Analysis, vol. 15[2], pp. 214-225, 2011 Pubmed.
Tiwari, P, Viswanath, S, Kurhanewicz, J, Madabhushi, A, “Weighted Combination of Multi-parametric MR Imaging markers for Evaluating Radiation Therapy changes in the prostate”, Workshop on Prostate Cancer Imaging, In Conjunction with The Medical Image Computing and Computer Assisted Intervention Society (MICCAI), vol. 2011, pp. 80-91, 2011. Springer
Ginsburg, S, Tiwari, P, Kurhanewicz, J, Madabhushi, A, “Variable Ranking with PCA: Finding Multiparametric MR Imaging Biomarkers for Prostate Cancer Diagnosis and Grading”, Workshop on Prostate Cancer Imaging, In Conjunction with The Medical Image Computing and Computer Assisted Intervention Society (MICCAI), vol. 2011, pp. 146-157, 2011.
Tiwari, P, Viswanath, S, Lee, G, Madabhushi, A, “Multi-modal data fusion schemes for integrated classification of imaging and non-imaging data”, Institute of Electrical and Electronics Engineers (IEEE) International Symposium on Biomedical Imaging, Chicago, IL, pp. 165-168, 2011. IEEE Digital Library
Viswanath, S, Tiwari, P, Chappelow, J, Toth, R, Kurhanewicz, J, Madabhushi, A, “CadOnc©: An Integrated Toolkit for Evaluating Radiation Therapy Related Changes in the Prostate Using Multi-Parametric MRI”, Institute of Electrical and Electronics Engineers (IEEE) International Symposium on Biomedical Imaging, Chicago, IL, vol. 2011, pp. 2095-98, 2011 IEEE Digital Library
2010
Tiwari, P, Rosen, M, Kurhanewicz, J, Madabhushi, A, “Semi Supervised Multi Kernel (SeSMiK) Graph Embedding: Identifying aggressive prostate cancer via Magnetic Resonance Imaging and Spectroscopy”, In Proc of Medical Image Computing and Computer Assisted Interventions (MICCAI), vol. 13[3], pp. 666-673, 2010. (Acceptance rate = 31%) Pubmed
Tiwari, P, Viswanath, S, Rosen, M, Reed, G, Kurhanewicz, J, Madabhushi, A, “Multi-modal Integration of Magnetic Resonance Imaging and Spectroscopy for Detection of Prostate Cancer,” Conference on Biosignal Interpretation, 2009.
Tiwari, P, Rosen, Madabhushi, A, “A Hierarchical Spectral Clustering and Non-linear Dimensionality Reduction Scheme for Detection of Prostate Cancer from Magnetic Resonance Spectroscopy,” Medical Physics, vol. 36[9], pp. 3927-39, 2009 Pubmed
2007-2009
Tiwari, P, Rosen, M, Galen, P, Kurhanewicz, J, Madabhushi, A, “Spectral Embedding based Probabilistic boosting Tree (ScEPTre): Classifying High Dimensional Heterogeneous Biomedical Data,” Medical Image Computing and Computer Assisted Intervention (MICCAI) 2009, vol. 12[2], pp. 844–851, 2009. (Acceptance rate = 31%) Pubmed
Tiwari, P, Rosen, M, Madabhushi, A, “Consensus-Locally Linear Embedding (C-LLE): Application to Prostate Cancer Detection on Magnetic Resonance Spectroscopy,” Medical Image Computing and Computer Assisted Intervention (MICCAI) (1), Vol. 5242 of Lecture Notes in Computer Science, Springer, vol. 11[2], pp. 330-338, 2008. Pubmed
Toth, R, Tiwari, P, Rosen, M, Kalyanpur, A, Pungavkar, S, Madabhushi, A., “An Integrated Multi-modal Prostate Segmentation Scheme by Combining Magnetic Resonance Spectroscopy and Active Shape Models,” The International Society for Optics and Photonics (SPIE) Medical Imaging, vol. 6914(1), pp. 4S1-12, 2008.
Viswanath, S, Tiwari, P, Madabhushi, A, Rosen, M, “Quantitative Integration of Magnetic Resonance Spectroscopy and Magnetic Resonance Imaging In Vivo for Computer-aided Diagnosis of Prostate Cancer,” The International Society for Optics and Photonics (SPIE) Medical Imaging, vol. 6915(1), pp. 3D1-12, 2008 (Honorable Mention).
Tiwari, P, Madabhushi, A, Rosen, M, “A Hierarchical Unsupervised Spectral Clustering Scheme for Detection of Prostate Cancer from Magnetic Resonance Spectroscopy (MRS),” Medical Image Computing and Computer Assisted Intervention (MICCAI), vol. 4792, pp. 278-86, 2007 (Runner Up Award for Best Young Scientist Paper, selected as oral presentation, Acceptance rate 4%) Pubmed.
Editorials and invited articles
Madabhushi, A, Viswanath, S, Lee, G, Tiwari, P, “Medical Image Informatics for Personalized Medicine,” Critical Values, pp. 30-32, July 2013.
Peer Reviewed Abstracts
Niha Beig, Marwa Ismail, Anas Saeed Bamashmos, Volodymyr Statsevych, Virginia Hill, Anant Madabhushi, Manmeet Ahluwalia and Pallavi Tiwari. “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.
Marwa Ismail, Ramon Correa, Kaustav Bera, Anas Saeed Bamashmos, Volodymyr Statsevych, Prateek Prasanna, Niha Beig, Anant Madabhushi, Manmeet Ahluwalia, and Pallavi Tiwari, “Radiomic features localized to stereotactic biopsy locations can capture EGFR presence in Glioblastoma.” Society of Neuro-oncology, 2019. Phoenix, Arizona, USA.
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.
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.
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.
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.
Beig, N, Prasanna, P, Verma, R, 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.
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.
Ismail, M, Hill, V, Statsevych, V, Huang, R, Correa, R, Singh, G, Bera, K, Thawani, R, Madabhushi, A, Ahluwalia, M, and Tiwari, P, “Spatial distribution atlases of post-treatment MRI scans reveal distinct hemispheric distribution of Glioblastoma recurrence from pseudo-progression”, Society of Neuro-Oncology Annual Meeting, November 2018.
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 Radiologic Society of North America Annual Meeting, 2018.
Ismail*, M, Prasanna*, P, Huang, R, Singh, G, Thawani, R, Madabhushi, A, Tiwari, P, “Compactness of peritumoral edema on routine MRI appears to distinguish tumor recurrence from pseudo-progression in primary brain tumors: Preliminary findings.” Proceedings of the Radiologic Society of North America (RSNA) 2017.
Ismail, M, Prasanna, P, Huang, R, Singh, G, Thawani, R, Madabhushi, A, Aahluwalia, M, Tiwari, P, “Shape attributes of enhancing lesion boundaries can differentiate tumor recurrence from pseudoprogression on routine brain MRI scans: Preliminary findings.” Society of Neuro-oncology 2017.
Karnawat, A, Prasanna, P, Madabhushi, A, Tiwari, P, Use of textural radiomic maps in a 3D convolutional neural network framework can augment glioma lesion segmentation, Society of Neurooncology, 2017.
Beig N , Correa R , Thawani R , Prasanna P , Badve C , Gold D , DeBlank P , 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
DiCamillo PA, Shvarts MB, Patel RB , Mitra J, Tiwari P, Cook SD, Cadavid D, Naismith RT , Lancia S, Wolansky LJ. Characterization of Gadolinium Deposition in the Brain Manifest as T2-hypointensity and T1-hyperintensity Associated with Repeat Monthly Triple-Dose Gadopentetate Dimeglumine Administration for 2 years in the BECOME Trial. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM). 2017 Apr; 25(1): 5636.
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) 25th Annual Meeting , 2017. Honolulu, HI, USA
Mitra, M, DiCamillo, PA., Cook, SD, Cadavid, D, Wolansky, LJ, Tiwari, P, "Frequency of Gadolinium (Gd) deposition in the dentate nucleus after 13 monthly triple-doses of Gd", 102th Proceedings of the Radiologic Society of North America, 2016.
Prasanna, P, Nayate, A, Gupta, A, Rogers, L,Wolansky, L, Singh, G, Pinho, M, Hatanpaa, K, Madabhushi, A, Tiwari, P, Human-Machine Performance Comparison Study in Distinguishing Radiation Necrosis from Brain Tumor Recurrence on Routine MRI , Proceedings of the Radiologic Society of North America, 2016.
Prasanna, P, Rogers, L, Cohen, M, Singh, G, Badve, C, Wolansky, Madabhushi, A, Tiwari, P, Computer extracted Texture Descriptors on MRI that Distinguish Radiation, Necrosis and Tumor Recurrence Post-Radiotherapy in Primary Neoplasms are Associated with Vascular, Necrotic and Demyelinating changes, Proceedings of the Radiologic Society of North America, 2016.
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.
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”, Annual Meeting Society for Neuro-Oncology (SNO), 2016.
Mitra, J, Nayate, A, Madabhushi, A, Tiwari, P, Impact on remote functional areas due to tumor mass effect is prognostic of overall survival in Glioblastoma Multiforme, Annual Meeting Society for Neuro-Oncology, 2016.
Prasanna, P, Nayate, A, Gupta, A, Rogers, L, Singh, G, Wolansky, L, Pinho, M, Hatanpaa, K, Madabhushi, A, Tiwari, P, Distinguishing radiation necrosis from brain tumor recurrence on routine MRI: A preliminary human-machine reader comparison study, Society of Neurooncology, 2016.
Prasanna, P, Rogers, L, Cohen, M, Singh, G, Badve, C, Wolansky, Madabhushi, A, Tiwari, P, Features of local gradient disorder on MRI that distinguish radiation necrosis and tumor recurrence post-radiotherapy are associated with zonal necrosis, vessel wall thickening, hyalinization and demyelination: A preliminary study in brain tumors, Society of Neurooncology, 2016.
Wolansky, L, Mitra, J, DiCamillo, PA, Cook, S, Cadavid, D, Richards, T, Naismith, RT, Lancia, S, Tiwari, P, "A MRI-pharmacokinetic study of gadolinium deposition in the dentate nucleus in multiple sclerosis patients receiving serial triple-doses of Gd for 14 consecutive months", ECTRIMS, London, Sept 2016.
Hanson, G, Prasanna, P, Patel, J, Madabhushi, A, Tiwari, P, "Cerebrospinal fluid compression in cerebellum on treatment-naïve MRI might be an early indicator of poor survival in Glioblastoma: A preliminary study”, The International Society for Magnetic Resonance in Medicine (ISMRM) 24th Annual Meeting, Singapore, May 2016.
Prasanna, P, Rose, A, Singh, G, Huang, R, Madabhushi, A and Tiwari, P, "Radiomic features from the necrotic region on post-treatment Gadolinium T1w MRI appear to differentiate pseudo-progression from true tumor progression in primary brain tumors", The International Society for Magnetic Resonance in Medicine (ISMRM) 24th Annual Meeting, Singapore, May 2016.
Algohary, A, Prasanna, P, Zhou, Y, Tiwari, P, Viswanath, S, Madabhushi, A, "RadiomicsVizTM: A Software tool for visualization of novel radiomic representations", The International Society for Optics and Photonics (SPIE) Medical Imaging, 2016.
Tiwari, P, Prasanna, P, Patel, J, Madabhushi, A, “Computer extracted texture descriptors from different tissue compartments within the tumor habitat on treatment-naïve MRI predict clinical survival in glioblastoma patients”, Society of Neurooncology, 2015.
Prasanna, P, Siddalingappa, A, Wolansky, L, Rogers, L, Tai-Chung Lam, V, Madabhushi, A, Tiwari, P, “Morphologic heterogeneity at a pixel-level captured via entropy of gradient orientations on T1-post contrast MRI enables discrimination of tumor recurrence from cerebral radiation necrosis”, Society of Neurooncology, 2015.
Tiwari, P, Patel, J, Partovi, S, Prasanna, P, Madabhushi, A, “Computer extracted texture descriptors from different tissue compartments within the tumor habitat on treatment-naïve MRI predict clinical survival in glioblastoma patients”, Proceedings of the Radiologic Society of North America, 2015.
Prasanna, P, Tiwari, P, Siddalingappa, A, Wolansky, L, Rogers, L, Lam, TC, To, V, and Madabhushi, A, Study of contrast-enhanced T1-w MRI markers of cerebral radiation necrosis manifested in head-and-neck cancers, primary, and metastatic brain tumors: Preliminary findings, Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, Canada, 2015.
Tiwari, P, Prasanna, P, Barholtz-Sloan, J, Sloan, A, Ostrom, Q, Jiang, B, Madabhushi, A, “Quantitative texture descriptors on baseline-MRI can predict patient survival in newly diagnosed glioblastoma multiforme patients,” Annual Society for Neuro-oncology Scientific Meeting, 2014.
Tiwari, P, Prasanna, P, Rogers, L, Wolansky, Leo, Madabhushi, A, “Computer extracted oriented texture features on T1-Gadolinium MRI for distinguishing radiation necrosis from recurrent brain tumors,” Annual Society for Neuro-oncology Scientific Meeting, 2014.
Patel, J, Prasanna, P, Tiwari, P, Madabhushi, A, “Identifying MRI Markers On Newly Diagnosed Glioblastoma Multiforme To Distinguish Patients With Long And Short Term Survival,” Biomedical Engineering Society (BMES), 2014.
Tiwari, P, Danish, S, Madabhushi, A, “How long does the hippocampus take to settle down after MRI-guided laser ablation for refractory epilepsy? Proof of concept using a multi-parametric analysis of MRI markers,” Annual Meeting of the American Epilepsy Society, 2013.
Tiwari, P, Rogers, L, Wolansky, L, Madabhushi, A, “Computerized image analysis of texture descriptors in multi-parametric MRI to distinguish recurrent glioblastoma multiforme from radiation necrosis”, 4th Quadrennial Meeting of the World Federation of Neuro-Oncology held in conjunction with the 2013 Scientific Meeting and Education Day of the Society for Neuro-Oncology, San Francisco, CA, November 2013.
Tiwari, P, Shabbar, D, Wong, S, Madabhushi, A, “Quantitative Study of changes in multi-parametric MRI markers post-laser interstitial ablation therapy (LITT) for epilepsy,” The International Society for Magnetic Resonance in Medicine (ISMRM), 2013.
Tiwari, P, Kurhanewicz, J, Madabhushi, A, “A quantitative framework to study MRI related treatment changes in the prostate post-IMRT,” The International Society for Magnetic Resonance in Medicine (ISMRM), 2013.
Tiwari, P, Kurhanewicz, J, Madabhushi, A, “Computerized quantitative data integration of multi-protocol MRI for identification of high grade prostate cancer in vivo,” in Proc. International Society for Magnetic Resonance in Medicine (ISMRM), pp. 2640, 2011.
Viswanath, S, Chappelow, J, Tiwari, P, Kurhanewicz, J, Madabhushi, A, "CADOnc: A Computerized Decision Support System for Quantifying Radiation Therapy Changes in the Prostate via Multi-Parametric MRI,” in Proc. International Society for Magnetic Resonance in Medicine (ISMRM), pp. 2647, 2011.
Tiwari, P, Kurhanewicz, J, Madabhushi, A, “Multimodal Integration of Magnetic Resonance Imaging and Spectroscopy for Detection of Aggressive Prostate Cancer,” Innovative Minds in Prostate Cancer Today (IMPaCT), 2011.
Tiwari, P, Rosen, M, Madabhushi, A, “Automated detection of prostate cancer from high resolution in vivo MRS,” The International Society for Magnetic Resonance in Medicine (ISMRM), 2008.
Madabhushi, A, Chappelow, J, Viswanath, S, Toth, R, Tiwari, P, “Multi-protocol Prostate MR Image Analysis: Image Segmentation, Registration, and Computer-aided Diagnosis,” Workshop on Prostate Image Analysis, In Conjunction with The Medical Image Computing and Computer Assisted Intervention Society (MICCAI), 2008.