Medical Specialties Commons^™

Federated Learning Enables Big Data For Rare Cancer Boundary Detection, Sarthak Pati, Ujjwal Baid, Brandon Edwards, Micah Sheller, Shih-Han Wang, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Deepthi Karkada, Christos Davatzikos, Chiharu Sako, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J. Preetha, Felix Sahm, Klaus Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey Rudie, Javier Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y. Huang, Ken Chang, Carmen Balaña, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S Alexander, Joseph Lombardo, Joshua D. Palmer, Adam E. Flanders, Adam P. Dicker, Haris I. Sair, Craig K. Jones, Archana Venkataraman, Meirui Jiang, Tiffany Y. So, Cheng Chen, Pheng Ann Heng, Qi Dou, Michal Kozubek, Filip Lux, Jan Michálek, Petr Matula, Miloš Keřkovský, Tereza Kopřivová, Marek Dostál, Václav Vybíhal, Michael A. Vogelbaum, J. Ross Mitchell, Joaquim Farinhas, Joseph A. Maldjian, Chandan Ganesh Bangalore Yogananda, Marco C. Pinho, Divya Reddy, James Holcomb, Benjamin C. Wagner, Benjamin M. Ellingson, Timothy F. Cloughesy, Catalina Raymond, Talia Oughourlian, Akifumi Hagiwara, Chencai Wang, Minh-Son To, Sargam Bhardwaj, Chee Chong, Marc Agzarian, Alexandre Xavier Falcão, Samuel B. Martins, Bernardo C. A. Teixeira, Flávia Sprenger, David Menotti, Diego R. Lucio, Pamela Lamontagne, Daniel Marcus, Benedikt Wiestler, Florian Kofler, Ivan Ezhov, Marie Metz, Rajan Jain, Matthew Lee, Yvonne W. Lui, Richard Mckinley, Johannes Slotboom, Piotr Radojewski, Raphael Meier, Roland Wiest, Derrick Murcia, Eric Fu, Rourke Haas, John Thompson, David Ryan Ormond, Chaitra Badve, Andrew E. Sloan, Vachan Vadmal, Kristin Waite, Rivka R. Colen, Linmin Pei, Murat Ak, Ashok Srinivasan, J. Rajiv Bapuraj, Arvind Rao, Nicholas Wang, Ota Yoshiaki, Toshio Moritani, Sevcan Turk, Joonsang Lee, Snehal Prabhudesai, Fanny Morón, Jacob Mandel, Konstantinos Kamnitsas, Ben Glocker, Luke V. M. Dixon, Matthew Williams, Peter Zampakis, Vasileios Panagiotopoulos, Panagiotis Tsiganos, Sotiris Alexiou, Ilias Haliassos, Evangelia I Zacharaki, Konstantinos Moustakas, Christina Kalogeropoulou, Dimitrios M. Kardamakis, Yoon Seong Choi, Seung-Koo Lee, Jong Hee Chang, Sung Soo Ahn, Bing Luo, Laila Poisson, Ning Wen, Pallavi Tiwari, Ruchika Verma, Rohan Bareja, Ipsa Yadav, Jonathan Chen, Neeraj Kumar, Marion Smits, Sebastian R. Van Der Voort, Ahmed Alafandi, Fatih Incekara, Maarten M. J. Wijnenga, Georgios Kapsas, Renske Gahrmann, Joost W Schouten, Hendrikus J. Dubbink, Arnaud J. P. E. Vincent, Martin J. Van Den Bent, Pim J. French, Stefan Klein, Yading Yuan, Sonam Sharma, Tzu-Chi Tseng, Saba Adabi, Simone P. Niclou, Olivier Keunen, Ann-Christin Hau, Martin Vallières, David Fortin, Martin Lepage, Bennett Landman, Karthik Ramadass, Kaiwen Xu, Silky Chotai, Lola B. Chambless, Akshitkumar Mistry, Reid C. Thompson, Yuriy Gusev, Krithika Bhuvaneshwar, Anousheh Sayah, Camelia Bencheqroun, Anas Belouali, Subha Madhavan, Thomas C. Booth, Alysha Chelliah, Marc Modat, Haris Shuaib, Carmen Dragos, Aly Abayazeed, Kenneth Kolodziej, Michael Hill, Ahmed Abbassy, Shady Gamal, Mahmoud Mekhaimar, Mohamed Qayati, Mauricio Reyes, Ji Eun Park, Jihye Yun, Ho Sung Kim, Abhishek Mahajan, Mark Muzi, Sean Benson, Regina G. H. Beets-Tan, Jonas Teuwen, Alejandro Herrera-Trujillo, Maria Trujillo, William Escobar, Ana Abello, Jose Bernal, Jhon Gómez, Joseph Choi, Stephen Baek, Yusung Kim, Heba Ismael, Bryan Allen, John M. Buatti, Aikaterini Kotrotsou, Hongwei Li, Tobias Weiss, Michael Weller, Andrea Bink, Bertrand Pouymayou, Hassan F. Shaykh, Joel Saltz, Prateek Prasanna, Sampurna Shrestha, Kartik M. Mani, David Payne, Tahsin Kurc, Enrique Pelaez, Heydy Franco-Maldonado, Francis Loayza, Sebastian Quevedo, Pamela Guevara, Esteban Torche, Cristobal Mendoza, Franco Vera, Elvis Ríos, Eduardo López, Sergio A. Velastin, Godwin Ogbole, Mayowa Soneye, Dotun Oyekunle, Olubunmi Odafe-Oyibotha, Babatunde Osobu, Mustapha Shu'aibu, Adeleye Dorcas, Farouk Dako, Amber L. Simpson, Mohammad Hamghalam, Jacob J. Peoples, Ricky Hu, Anh Tran, Danielle Cutler, Fabio Y. Moraes, Michael A. Boss, James Gimpel, Deepak Kattil Veettil, Kendall Schmidt, Brian Bialecki, Sailaja Marella, Cynthia Price, Lisa Cimino, Charles Apgar, Prashant Shah, Bjoern Menze, Jill S. Barnholtz-Sloan, Jason Martin, Spyridon Bakas

Department of Radiation Oncology Faculty Papers

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically …

Standard Deviations Of Mr Signal Intensities Show A Consistent Trend During Imaging Follow-Ups For Glioblastoma Patients When Corrected For Non-Biological Heterogeneity Due To Hardware And Software Variation, Subhendra N. Sarkar, Rafael Rojas, Evans Lespinasse, Xiang Fu Zhang, Ruth Zeron

Publications and Research

Introduction: Glioblastoma multiforme (GBM) has a poor prognosis in spite of advanced MRI guided treatments today. Routine MRI using conventional T1 or advanced permeability based MRI of GBM often does not adequately represent changing tumor phases or overall survival. In this work, region of interest (ROI) based tissue MR standard deviation (SD) is demonstrated as an important MRI variable that could be a potential biomarker of GBM heterogeneity and radioresistance. Materials and methods: MRI characterization is often qualitative and lacks reproducibility. Using standardized MRI phantoms we have normalized retrospective records of 12 radioresistant GBM patients that underwent radiation therapy (RT) …

Prodrugs Of A 1-Hydroxy-2-Oxopiperidin-3-Yl Phosphonate Enolase Inhibitor For The Treatment Of Eno1-Deleted Cancers, Victoria C Yan, Cong-Dat Pham, Elliot S Ballato, Kristine L Yang, Kenisha Arthur, Sunada Khadka, Yasaman Barekatain, Prakriti Shrestha, Theresa Tran, Anton H Poral, Mykia Washington, Sudhir Raghavan, Barbara Czako, Federica Pisaneschi, Yu-Hsi Lin, Nikunj Satani, Naima Hammoudi, Jeffrey J Ackroyd, Dimitra K Georgiou, Steven W Millward, Florian L Muller

Journal Articles

Cancers harboring homozygous deletion of the glycolytic enzyme enolase 1 (ENO1) are selectively vulnerable to inhibition of the paralogous isoform, enolase 2 (ENO2). A previous work described the sustained tumor regression activities of a substrate-competitive phosphonate inhibitor of ENO2, 1-hydroxy-2-oxopiperidin-3-yl phosphonate (HEX) (5), and its bis-pivaloyoxymethyl prodrug, POMHEX (6), in an ENO1-deleted intracranial orthotopic xenograft model of glioblastoma [Nature Metabolism 2020, 2, 1423-1426]. Due to poor pharmacokinetics of bis-ester prodrugs, this study was undertaken to identify potential non-esterase prodrugs for further development. Whereas phosphonoamidate esters were efficiently bioactivated in ENO1-deleted glioma …

Prodrugs Of A 1-Hydroxy-2-Oxopiperidin-3-Yl Phosphonate Enolase Inhibitor For The Treatment Of Eno1-Deleted Cancers, Victoria C Yan, Cong-Dat Pham, Elliot S Ballato, Kristine L Yang, Kenisha Arthur, Sunada Khadka, Yasaman Barekatain, Prakriti Shrestha, Theresa Tran, Anton H Poral, Mykia Washington, Sudhir Raghavan, Barbara Czako, Federica Pisaneschi, Yu-Hsi Lin, Nikunj Satani, Naima Hammoudi, Jeffrey J Ackroyd, Dimitra K Georgiou, Steven W Millward, Florian L Muller

Journal Articles

Cancers harboring homozygous deletion of the glycolytic enzyme enolase 1 (ENO1) are selectively vulnerable to inhibition of the paralogous isoform, enolase 2 (ENO2). A previous work described the sustained tumor regression activities of a substrate-competitive phosphonate inhibitor of ENO2, 1-hydroxy-2-oxopiperidin-3-yl phosphonate (HEX) (5), and its bis-pivaloyoxymethyl prodrug, POMHEX (6), in an ENO1-deleted intracranial orthotopic xenograft model of glioblastoma [Nature Metabolism2020,2, 1423–1426]. Due to poor pharmacokinetics of bis-ester prodrugs, this study was undertaken to identify potential non-esterase prodrugs for further development. Whereas phosphonoamidate esters were efficiently bioactivated in ENO1-deleted glioma cells, McGuigan prodrugs were …

Tumor Treating Fields With Radiation For Glioblastoma: A Narrative Review, Ryan C. Miller, Muneeb Khan Niazi, Olga Russial, Spencer Poiset, Wenyin Shi

Department of Radiation Oncology Faculty Papers

Background and objective: With a phase 3 clinical trial (EF-32, ClinicalTrials.gov: NCT04471844) currently underway examining the potential benefit of concurrent chemoradiation and tumor treating fields (TTFields) for patients with glioblastoma (GBM), we present the following narrative review to highlight the current evidence that supports this approach. The current management paradigm for GBM includes maximal safe surgical resection followed by concurrent chemoradiation with further temozolomide (TMZ) and TTFields used as maintenance therapy. Despite several treatment advances over the past few decades, the overall prognosis remains poor and new strategies are currently under investigation, including the use of chemoradiation concurrently with …

The Phenomenon Of Multidrug Resistance In Glioblastomas, Alexandr N. Chernov, Diana A. Alaverdian, Elvira S. Galimova, Alessandra Renieri, Elisa Frullanti, Ilaria Meloni, Olga V. Shamova

Hematology/Oncology and Stem Cell Therapy

The most common and aggressive brain tumor in the adult population is glioblastoma (GBM). The lifespan of patients does not exceed 22 months. One of the reasons for the low effectiveness of GBM treatment is its radioresistance and chemoresistance. In the current review, we discuss the phenomenon of multidrug resistance of GBM in the context of the expression of ABC family transporter proteins and the mechanisms of proliferation, angiogenesis, and recurrence. We focused on the search of molecular targets among growth factors, receptors, signal transduction proteins, microRNAs, transcription factors, proto-oncogenes, tumor suppressor genes, and their single-nucleotide polymorphisms.

Case Report: Glioblastoma Tumor Presenting With Mild Changes In Memory, Samuel Thalathoti, Nicholas Palladino, James Espinosa, Alan Lucerna

Rowan-Virtua Research Day

We report a case of a 66-year-old female who presented to the ED with generalized headache and mild confusion, who was diagnosed with high-grade glial neoplasm. The differential diagnosis of headache is vast, but without red flags or symptoms is generally from a benign cause and easily treatable. However, even in the context of a normal neurologic physical exam, symptoms such as confusion, forgetfulness, and behavioral changes should merit imaging in the workup. Glioblastoma is the most common brain tumor, accounting for 47.7% of all cases, with an incidence of 3.21 per 100,000 population. Median age of diagnosis is 64 …

Combined Treatment With Niclosamide And Camptothecin Enhances Anticancer Effect In U87 Mg Human Glioblastoma Cells, Laura Valdez, Benxu Cheng, Daniela Gonzalez, Reanna Rodriguez, Paola Campano, Andrew Tsin, Xiaoqian Fang

School of Medicine Publications and Presentations

Glioblastoma multiforme (GBM) is one of the deadliest cancers of the brain. Its ability to infiltrate healthy brain tissues renders it difficult to remove surgically. Furthermore, it exhibits high rates of radio- and chemoresistance, making the survival rates of patients with GBM poor. Therefore, novel effective therapies for GBM remain urgently in demand. Niclosamide is an anti-helminthic drug and recently it has been receiving attention due to its reported anticancer effects in cancer models, including GBM. Furthermore, camptothecin (CPT) is a naturally-occurring alkaloid and has been previously reported to be a potential chemotherapeutic agent by targeting the nuclear topoisomerase I. …

Modeling Of Cns Cancer With A Focus On The Immune Component, Daniel Zamler

Dissertations & Theses (Open Access)

The knowledge surrounding cancers of the central nervous system remains poorly developed, in particular with regard to the immune component. The works contained in this thesis look at craniopharyngioma, glioblastoma, and several forms of brain metastasis. While some attention is given to the tumor cells themselves, as well as the patient setting which these studies model, the immune component of disease progression and treatment plays a strong role in each and is the primary focus of the works contained.

Craniopharyngioma is a relatively rare tumor in adults. Although histologically benign, it can be locally aggressive and may require additional therapeutic …

Stem Cell-Based Therapies And Glioblastoma: A Seminal Matter, Kumaria Ashwin, Ashwin Kumaria

Hematology/Oncology and Stem Cell Therapy

No abstract provided.

Differential Microrna Expression In Glioblastoma As A Therapeutic Target Or Potential Biomarker, Drew Hines, Levi Marcum, Aubrey Strong, Ryan Wade

Channels: Where Disciplines Meet

MicroRNA (miRNA) is an epigenetic factor that plays an important role in the post-transcriptional regulation of gene and protein expression. Recent research has shown that in many types of cancer, differentially expressed levels of certain types of miRNA are significantly correlated with the transformation of and ongoing issues caused by cancer cells. Specifically, in Glioblastoma, one of the most lethal and aggressive human cancers, differential levels of miRNAs contribute to the cell’s lack of pro-apoptotic gene presence and its high resistance to current treatments. Results from current studies could provide information about which microRNAs are differentially expressed in glioblastoma when …

Plasma Induced Reactive Oxygen Species-Dependent Cytotoxicity In Glioblastoma 3d Tumourspheres, Janith Wanigasekara, Carlos Barcia, Patrick J. Cullen, Brijesh Tiwari, James F. Curtin

Articles

The aim of this study was to determine the effects of a pin‐to‐plate cold atmospheric plasma (CAP) on U‐251 MG three‐dimensional (3D) glioblastoma spheroids under different conditions. 3D tumorspheres showed higher resistance to the CAP treatment compared to 2D monolayer cells. A single CAP treatment was able to induce cytotoxicity, while multiple CAP treatments augmented this effect. CAP was also able to induce cytotoxicity throughout the tumoursphere, and we identified that reactive oxygen species(ROS) plays a major role, while H2O2plays a partial role in CAP‐induced cytotoxicity in tumour-spheres. We conclude that ROS‐dependent cytotoxicity is induced uniformly throughout glioblastoma and epidermoid …

Uncertainty Estimation In Classification Of Mgnt Using Radiogenomics For Glioblastoma Patients, W. Farzana, Z. A. Shboul, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Glioblastoma Multiforme (GBM) is one of the most malignant brain tumors among all high-grade brain cancers. Temozolomide (TMZ) is the first-line chemotherapeutic regimen for glioblastoma patients. The methylation status of the O6-methylguanine-DNA-methyltransferase (MGMT) gene is a prognostic biomarker for tumor sensitivity to TMZ chemotherapy. However, the standardized procedure for assessing the methylation status of MGMT is an invasive surgical biopsy, and accuracy is susceptible to resection sample and heterogeneity of the tumor. Recently, radio-genomics which associates radiological image phenotype with genetic or molecular mutations has shown promise in the non-invasive assessment of radiotherapeutic treatment. This study proposes a machine-learning framework …

Qu-Brats: Miccai Brats 2020 Challenge On Quantifying Uncertainty In Brain Tumor Segmentation - Analysis Of Ranking Scores And Benchmarking Results, Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard Mckinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil Nalawade, Chandan Ganesh, Ben Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Daza, Catalina Gómez, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Reynaud, Yuan-Han Mo, Elsa Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Lin-Min Pei, Murat Ak, Sarahi Rosas-González, Ilyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Veronica Vilaplana, Hugh Mchugh, Gonzalo Maso Talou, Alan Wang, Jay Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicholas Boutry, Alexis Huard, Lasitha Vidyaratne, Md. Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Elodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Llado, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas Tustison, Craig Meyer, Nisarg A. Shah, Sanjay Talbar, Marc-André Weber, Abhishek Mahajan, Andras Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko1, Daniel Marcus, Aikaterini Kotrotsou, Rivka Colen, John Freymann, Justin Kirby, Christos Davatzikos, Bjoern Menze, Spyridon Bakas, Yarin Gal, Tal Arbel

Electrical & Computer Engineering Faculty Publications

Deep learning (DL) models have provided the state-of-the-art performance in a wide variety of medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e.g., tumor and lesion sub-regions) is particularly challenging, and potential errors hinder the translation of DL models into clinical workflows. Quantifying the reliability of DL model predictions in the form of uncertainties, could enable clinical review of the most uncertain regions, thereby building trust and paving the way towards clinical translation. Recently, a number of uncertainty estimation methods have been introduced for DL medical image segmentation tasks. …