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Roberts M, Hinton G, Wells AJ, Van Der Veken J, Bajger M, Lee G, Liu Y, Chong C, Poonnoose S, Agzarian M, To MS. Imaging evaluation of a proposed 3D generative model for MRI to CT translation in the lumbar spine. Spine J 2023; 23:1602-1612. [PMID: 37479140 DOI: 10.1016/j.spinee.2023.06.399] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 06/22/2023] [Accepted: 06/29/2023] [Indexed: 07/23/2023]
Abstract
BACKGROUND CONTEXT A computed tomography (CT) and magnetic resonance imaging (MRI) are used routinely in the radiologic evaluation and surgical planning of patients with lumbar spine pathology, with the modalities being complimentary. We have developed a deep learning algorithm which can produce 3D lumbar spine CT images from MRI data alone. This has the potential to reduce radiation to the patient as well as burden on the health care system. PURPOSE The purpose of this study is to evaluate the accuracy of the synthetic lumbar spine CT images produced using our deep learning model. STUDY DESIGN A training set of 400 unpaired CTs and 400 unpaired MRI scans of the lumbar spine was used to train a supervised 3D cycle-Gan model. Evaluators performed a set of clinically relevant measurements on 20 matched synthetic CTs and true CTs. These measurements were then compared to assess the accuracy of the synthetic CTs. PATIENT SAMPLE The evaluation data set consisted of 20 patients who had CT and MRI scans performed within a 30-day period of each other. All patient data was deidentified. Notable exclusions included artefact from patient motion, metallic implants or any intervention performed in the 30 day intervening period. OUTCOME MEASURES The outcome measured was the mean difference in measurements performed by the group of evaluators between real CT and synthetic CTs in terms of absolute and relative error. METHODS Data from the 20 MRI scans was supplied to our deep learning model which produced 20 "synthetic CT" scans. This formed the evaluation data set. Four clinical evaluators consisting of neurosurgeons and radiologists performed a set of 24 clinically relevant measurements on matched synthetic CT and true CTs in 20 patients. A test set of measurements were performed prior to commencing data collection to identify any significant interobserver variation in measurement technique. RESULTS The measurements performed in the sagittal plane were all within 10% relative error with the majority within 5% relative error. The pedicle measurements performed in the axial plane were considerably less accurate with a relative error of up to 34%. CONCLUSIONS The computer generated synthetic CTs demonstrated a high level of accuracy for the measurements performed in-plane to the original MRIs used for synthesis. The measurements performed on the axial reconstructed images were less accurate, attributable to the images being synthesized from nonvolumetric routine sagittal T1-weighted MRI sequences. It is hypothesized that if axial sequences or volumetric data were input into the algorithm these measurements would have improved accuracy.
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Affiliation(s)
- Makenze Roberts
- South Australia Medical Imaging, Flinders Medical Centre, Adelaide, South Australia, Australia.
| | - George Hinton
- South Australia Medical Imaging, Flinders Medical Centre, Adelaide, South Australia, Australia
| | - Adam J Wells
- Department of Neurosurgery, Royal Adelaide Hospital, Adelaide, South Australia, Australia; Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Jorn Van Der Veken
- Department of Neurosurgery, Flinders Medical Centre, Adelaide, South Australia, Australia
| | - Mariusz Bajger
- College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
| | - Gobert Lee
- College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
| | - Yifan Liu
- The Australian Institute for Machine Learning, University of Adelaide, Adelaide, South Australia, Australia
| | - Chee Chong
- South Australia Medical Imaging, Flinders Medical Centre, Adelaide, South Australia, Australia
| | - Santosh Poonnoose
- Department of Neurosurgery, Flinders Medical Centre, Adelaide, South Australia, Australia
| | - Marc Agzarian
- South Australia Medical Imaging, Flinders Medical Centre, Adelaide, South Australia, Australia
| | - Minh-Son To
- South Australia Medical Imaging, Flinders Medical Centre, Adelaide, South Australia, Australia; The Australian Institute for Machine Learning, University of Adelaide, Adelaide, South Australia, Australia; Flinders Health and Medical Research Institute, Flinders University, Adelaide, South Australia, Australia
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Chong C, de Leon J, Tan H, Crawford D, Jameson M, Hogan L, Pagulayan C, Jelen U, Biggerstaff K, Chhabra A, Twentyman T, Rahim K, Leong E, Lim M, Batumalai V. MRI Guided Adaptive Radiotherapy (MRgART) in Primary and Metastatic Liver Lesions. Int J Radiat Oncol Biol Phys 2023; 117:e288-e289. [PMID: 37785067 DOI: 10.1016/j.ijrobp.2023.06.1280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) The role of stereotactic body radiotherapy (SBRT) in the management of primary hepatic and metastatic tumors has increased significantly over the past few years. MR-Linac is rapidly gaining evidence in the delivery of ablative doses using MR guided adaptive radiotherapy (MRgART) with improved accuracy and dose coverage to the lesions. We report local control and toxicity of patients with primary and metastatic liver lesions treated with MR guided adaptive SBRT. MATERIALS/METHODS All patients were treated with MRgART on the Unity 1.5T MR Linacs at two institutions and consented to the ADAPT-MRL study (1). A 4DCT and MRI with abdominal compression were obtained at simulation and the primary MRI sequence used for online treatment included a T2 3D navigated scan. A balanced turbo field echo (btFFE) 2D cine motion scan was also acquired at every fraction to determine movement of the tumor to aid in internal target volume margin. All plans were treated with SBRT prescribed to 3-5 alternate daily fractions. Acute toxicity was reported according to Common Terminology Criteria for Adverse Events version 5 (CTCAE) v.5. Patient demographics, prescribed dose fractionation, acute toxicity and clinical response at 6 months were analyzed. Clinical response to treatment was measured according to RECIST criteria 1.1. RESULTS Between February 2021 to January 2023 a total of 30 patients were treated with 149 fractions to the liver. Patients were majority male (70%) with a median age of 66 (range 36-83). 16 patients were treated for primary hepatocellular carcinoma (HCC) of the liver and 14 patients for metastatic liver lesions. The median prescribed dose was 48 Gy (range 30-50Gy) in median 5 fractions (range (3-5 fractions). All patients completed treatment with no interruptions. The mean time from 'patient setup' to 'beam-off' was 52.6 minutes (range 37-73 minutes). Data on acute toxicity at 3 month follow up was available for 28 patients. Of these patients 7/28 (25%) had grade 1 or 2 toxicity and no >/ = grade 3 toxicity was reported. Clinical response at 6 months was available for 18 patients and showed complete response in 44% (8/18), partial response in 22% (4/18), stable disease in 22% (4/18) and progressive disease in 11.1% (2/18). CONCLUSION Our experience on MRgART to the liver has shown good local control and minimal acute toxicity in the treatment of primary and metastatic liver lesions. We continue to collect data on patient reported outcomes, clinical response and toxicity to determine the feasibility and safety of this system.
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Affiliation(s)
- C Chong
- GenesisCare Murdoch, Perth, Western Australia, Australia
| | - J de Leon
- GenesisCare St. Vincent's Clinic, Sydney, NSW, Australia
| | - H Tan
- GenesisCare Murdoch, Perth, Western Australia, Australia; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - D Crawford
- GenesisCare St. Vincent's Clinic, Sydney, NSW, Australia
| | - M Jameson
- GenesisCare St. Vincent's Clinic, Sydney, NSW, Australia
| | - L Hogan
- GenesisCare Murdoch, Perth, Western Australia, Australia
| | - C Pagulayan
- GenesisCare St. Vincent's Clinic, Sydney, NSW, Australia
| | - U Jelen
- GenesisCare St. Vincent's Clinic, Sydney, NSW, Australia
| | - K Biggerstaff
- GenesisCare Murdoch, Perth, Western Australia, Australia
| | - A Chhabra
- GenesisCare Murdoch, Perth, Western Australia, Australia
| | - T Twentyman
- GenesisCare St. Vincent's Clinic, Sydney, NSW, Australia
| | - K Rahim
- GenesisCare Murdoch, Perth, Western Australia, Australia; Fiona Stanley Hospital, Perth, Western Australia, Australia
| | - E Leong
- GenesisCare Murdoch, Perth, Western Australia, Australia; Fiona Stanley Hospital, Perth, Western Australia, Australia
| | - M Lim
- GenesisCare Murdoch, Perth, Western Australia, Australia
| | - V Batumalai
- GenesisCare St. Vincent's Clinic, Sydney, NSW, Australia
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Lee MM, Charalampidis EG, Xing S, Chong C, Kevrekidis PG. Breathers in lattices with alternating strain-hardening and strain-softening interactions. Phys Rev E 2023; 107:054208. [PMID: 37328995 DOI: 10.1103/physreve.107.054208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 03/21/2023] [Indexed: 06/18/2023]
Abstract
This work focuses on the study of time-periodic solutions, including breathers, in a nonlinear lattice consisting of elements whose contacts alternate between strain hardening and strain softening. The existence, stability, and bifurcation structure of such solutions, as well as the system dynamics in the presence of damping and driving, are studied systematically. It is found that the linear resonant peaks in the system bend toward the frequency gap in the presence of nonlinearity. The time-periodic solutions that lie within the frequency gap compare well to Hamiltonian breathers if the damping and driving are small. In the Hamiltonian limit of the problem, we use a multiple scale analysis to derive a nonlinear Schrödinger equation to construct both acoustic and optical breathers. The latter compare very well with the numerically obtained breathers in the Hamiltonian limit.
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Affiliation(s)
- M M Lee
- Mathematics Department, California Polytechnic State University, San Luis Obispo, California 93407-0403, USA
| | - E G Charalampidis
- Mathematics Department, California Polytechnic State University, San Luis Obispo, California 93407-0403, USA
| | - S Xing
- Department of Mechanical Engineering, California Polytechnic State University, San Luis Obispo, California 93407-0403, USA
| | - C Chong
- Department of Mathematics, Bowdoin College, Brunswick, Maine 04011, USA
| | - P G Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, Massachusetts 01003-4515, USA
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Kim BL, Chong C, Hajarolasvadi S, Wang Y, Daraio C. Dynamics of time-modulated, nonlinear phononic lattices. Phys Rev E 2023; 107:034211. [PMID: 37072982 DOI: 10.1103/physreve.107.034211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 02/14/2023] [Indexed: 04/20/2023]
Abstract
The propagation of acoustic and elastic waves in time-varying, spatially homogeneous media can exhibit different phenomena when compared to traditional spatially varying, temporally homogeneous media. In the present work, the response of a one-dimensional phononic lattice with time-periodic elastic properties is studied with experimental, numerical and theoretical approaches in both linear and nonlinear regimes. The system consists of repelling magnetic masses with grounding stiffness controlled by electrical coils driven with electrical signals that vary periodically in time. For small-amplitude excitation, in agreement with linear theoretical predictions, wave-number band gaps emerge. The underlying instabilities associated to the wave-number band gaps are investigated with Floquet theory and the resulting parametric amplification is observed in both theory and experiments. In contrast to genuinely linear systems, large-amplitude responses are stabilized via the nonlinear nature of the magnetic interactions of the system, and results in a family of nonlinear time-periodic states. The bifurcation structure of the periodic states is studied. It is found the linear theory correctly predicts parameter values from which the time-periodic states bifurcate from the zero state. In the presence of an external drive, the parametric amplification induced by the wave-number band gap can lead to bounded and stable responses that are temporally quasiperiodic. Controlling the propagation of acoustic and elastic waves by balancing nonlinearity and external modulation offers a new dimension in the realization of advanced signal processing and telecommunication devices. For example, it could enable time-varying, cross-frequency operation, mode- and frequency-conversion, and signal-to-noise ratio enhancements.
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Affiliation(s)
- B L Kim
- Department of Mechanical and Civil Engineering, California Institute of Technology, Pasadena, California 91125, USA
| | - C Chong
- Department of Mathematics, Bowdoin College, Brunswick, Maine 04011, USA
| | - S Hajarolasvadi
- Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Y Wang
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Republic of Singapore 6397984
| | - C Daraio
- Department of Mechanical and Civil Engineering, California Institute of Technology, Pasadena, California 91125, USA
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Pati S, Baid U, Edwards B, Sheller M, Wang SH, Reina GA, Foley P, Gruzdev A, Karkada D, Davatzikos C, Sako C, Ghodasara S, Bilello M, Mohan S, Vollmuth P, Brugnara G, Preetha CJ, Sahm F, Maier-Hein K, Zenk M, Bendszus M, Wick W, Calabrese E, Rudie J, Villanueva-Meyer J, Cha S, Ingalhalikar M, Jadhav M, Pandey U, Saini J, Garrett J, Larson M, Jeraj R, Currie S, Frood R, Fatania K, Huang RY, Chang K, Balaña C, Capellades J, Puig J, Trenkler J, Pichler J, Necker G, Haunschmidt A, Meckel S, Shukla G, Liem S, Alexander GS, Lombardo J, Palmer JD, Flanders AE, Dicker AP, Sair HI, Jones CK, Venkataraman A, Jiang M, So TY, Chen C, Heng PA, Dou Q, Kozubek M, Lux F, Michálek J, Matula P, Keřkovský M, Kopřivová T, Dostál M, Vybíhal V, Vogelbaum MA, Mitchell JR, Farinhas J, Maldjian JA, Yogananda CGB, Pinho MC, Reddy D, Holcomb J, Wagner BC, Ellingson BM, Cloughesy TF, Raymond C, Oughourlian T, Hagiwara A, Wang C, To MS, Bhardwaj S, Chong C, Agzarian M, Falcão AX, Martins SB, Teixeira BCA, Sprenger F, Menotti D, Lucio DR, LaMontagne P, Marcus D, Wiestler B, Kofler F, Ezhov I, Metz M, Jain R, Lee M, Lui YW, McKinley R, Slotboom J, Radojewski P, Meier R, Wiest R, Murcia D, Fu E, Haas R, Thompson J, Ormond DR, Badve C, Sloan AE, Vadmal V, Waite K, Colen RR, Pei L, Ak M, Srinivasan A, Bapuraj JR, Rao A, Wang N, Yoshiaki O, Moritani T, Turk S, Lee J, Prabhudesai S, Morón F, Mandel J, Kamnitsas K, Glocker B, Dixon LVM, Williams M, Zampakis P, Panagiotopoulos V, Tsiganos P, Alexiou S, Haliassos I, Zacharaki EI, Moustakas K, Kalogeropoulou C, Kardamakis DM, Choi YS, Lee SK, Chang JH, Ahn SS, Luo B, Poisson L, Wen N, Tiwari P, Verma R, Bareja R, Yadav I, Chen J, Kumar N, Smits M, van der Voort SR, Alafandi A, Incekara F, Wijnenga MMJ, Kapsas G, Gahrmann R, Schouten JW, Dubbink HJ, Vincent AJPE, van den Bent MJ, French PJ, Klein S, Yuan Y, Sharma S, Tseng TC, Adabi S, Niclou SP, Keunen O, Hau AC, Vallières M, Fortin D, Lepage M, Landman B, Ramadass K, Xu K, Chotai S, Chambless LB, Mistry A, Thompson RC, Gusev Y, Bhuvaneshwar K, Sayah A, Bencheqroun C, Belouali A, Madhavan S, Booth TC, Chelliah A, Modat M, Shuaib H, Dragos C, Abayazeed A, Kolodziej K, Hill M, Abbassy A, Gamal S, Mekhaimar M, Qayati M, Reyes M, Park JE, Yun J, Kim HS, Mahajan A, Muzi M, Benson S, Beets-Tan RGH, Teuwen J, Herrera-Trujillo A, Trujillo M, Escobar W, Abello A, Bernal J, Gómez J, Choi J, Baek S, Kim Y, Ismael H, Allen B, Buatti JM, Kotrotsou A, Li H, Weiss T, Weller M, Bink A, Pouymayou B, Shaykh HF, Saltz J, Prasanna P, Shrestha S, Mani KM, Payne D, Kurc T, Pelaez E, Franco-Maldonado H, Loayza F, Quevedo S, Guevara P, Torche E, Mendoza C, Vera F, Ríos E, López E, Velastin SA, Ogbole G, Soneye M, Oyekunle D, Odafe-Oyibotha O, Osobu B, Shu'aibu M, Dorcas A, Dako F, Simpson AL, Hamghalam M, Peoples JJ, Hu R, Tran A, Cutler D, Moraes FY, Boss MA, Gimpel J, Veettil DK, Schmidt K, Bialecki B, Marella S, Price C, Cimino L, Apgar C, Shah P, Menze B, Barnholtz-Sloan JS, Martin J, Bakas S. Author Correction: Federated learning enables big data for rare cancer boundary detection. Nat Commun 2023; 14:436. [PMID: 36702828 PMCID: PMC9879935 DOI: 10.1038/s41467-023-36188-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Affiliation(s)
- Sarthak Pati
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
| | - Ujjwal Baid
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | | | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chiharu Sako
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Satyam Ghodasara
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michel Bilello
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Felix Sahm
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maximilian Zenk
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany
| | - Evan Calabrese
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Jeffrey Rudie
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Javier Villanueva-Meyer
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Soonmee Cha
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Madhura Ingalhalikar
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Manali Jadhav
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Umang Pandey
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - John Garrett
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Matthew Larson
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Robert Jeraj
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Stuart Currie
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Russell Frood
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Kavi Fatania
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ken Chang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | | | - Josep Puig
- Department of Radiology (IDI), Girona Biomedical Research Institute (IdIBGi), Josep Trueta University Hospital, Girona, Spain
| | - Johannes Trenkler
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Josef Pichler
- Department of Neurooncology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Georg Necker
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Andreas Haunschmidt
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Stephan Meckel
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
- Institute of Diagnostic and Interventional Neuroradiology, RKH Klinikum Ludwigsburg, Ludwigsburg, Germany
| | - Gaurav Shukla
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiation Oncology, Christiana Care Health System, Philadelphia, PA, USA
| | - Spencer Liem
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Gregory S Alexander
- Department of Radiation Oncology, University of Maryland, Baltimore, MD, USA
| | - Joseph Lombardo
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joshua D Palmer
- Department of Radiation Oncology, The James Cancer Hospital and Solove Research Institute, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Adam E Flanders
- Department of Radiology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Adam P Dicker
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Haris I Sair
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Craig K Jones
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Archana Venkataraman
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Meirui Jiang
- The Chinese University of Hong Kong, Hong Kong, China
| | - Tiffany Y So
- The Chinese University of Hong Kong, Hong Kong, China
| | - Cheng Chen
- The Chinese University of Hong Kong, Hong Kong, China
| | | | - Qi Dou
- The Chinese University of Hong Kong, Hong Kong, China
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Filip Lux
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Petr Matula
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Tereza Kopřivová
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Marek Dostál
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Václav Vybíhal
- Department of Neurosurgery, Faculty of Medicine, Masaryk University, Brno, and University Hospital and Czech Republic, Brno, Czech Republic
| | - Michael A Vogelbaum
- Department of Neuro Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - J Ross Mitchell
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Joaquim Farinhas
- Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | | | - Marco C Pinho
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Divya Reddy
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James Holcomb
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Talia Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Minh-Son To
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
- Division of Surgery and Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Sargam Bhardwaj
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
| | - Chee Chong
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Marc Agzarian
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Bernardo C A Teixeira
- Instituto de Neurologia de Curitiba, Curitiba, Paraná, Brazil
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Flávia Sprenger
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - David Menotti
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Diego R Lucio
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Pamela LaMontagne
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Daniel Marcus
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Marie Metz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Rajan Jain
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, USA
| | - Matthew Lee
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Yvonne W Lui
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Richard McKinley
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Piotr Radojewski
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Raphael Meier
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Derrick Murcia
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Eric Fu
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Rourke Haas
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - John Thompson
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - David Ryan Ormond
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Chaitra Badve
- Department of Radiology, University Hospitals Cleveland, Cleveland, OH, USA
| | - Andrew E Sloan
- Department of Neurological Surgery, University Hospitals-Seidman Cancer Center, Cleveland, OH, USA
- Case Comprehensive Cancer Center, Cleveland, OH, USA
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Vachan Vadmal
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kristin Waite
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
| | - Rivka R Colen
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linmin Pei
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Murat Ak
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashok Srinivasan
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - J Rajiv Bapuraj
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Arvind Rao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Ota Yoshiaki
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Toshio Moritani
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Sevcan Turk
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Joonsang Lee
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Snehal Prabhudesai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fanny Morón
- Department of Radiology, Baylor College of Medicine, Houston, TX, USA
| | - Jacob Mandel
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Konstantinos Kamnitsas
- Department of Computing, Imperial College London, London, UK
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Ben Glocker
- Department of Computing, Imperial College London, London, UK
| | - Luke V M Dixon
- Department of Radiology, Imperial College NHS Healthcare Trust, London, UK
| | - Matthew Williams
- Computational Oncology Group, Institute for Global Health Innovation, Imperial College London, London, UK
| | - Peter Zampakis
- Department of NeuroRadiology, University of Patras, Patras, Greece
| | | | - Panagiotis Tsiganos
- Clinical Radiology Laboratory, Department of Medicine, University of Patras, Patras, Greece
| | - Sotiris Alexiou
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | - Ilias Haliassos
- Department of Neuro-Oncology, University of Patras, Patras, Greece
| | - Evangelia I Zacharaki
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | | | | | | | | | | | | | - Sung Soo Ahn
- Yonsei University College of Medicine, Seoul, Korea
| | - Bing Luo
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Laila Poisson
- Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | | | - Ruchika Verma
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
- Case Western Reserve University, Cleveland, OH, USA
| | - Rohan Bareja
- Case Western Reserve University, Cleveland, OH, USA
| | - Ipsa Yadav
- Case Western Reserve University, Cleveland, OH, USA
| | | | - Neeraj Kumar
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Sebastian R van der Voort
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Ahmed Alafandi
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Fatih Incekara
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Maarten M J Wijnenga
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Georgios Kapsas
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Renske Gahrmann
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Joost W Schouten
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Hendrikus J Dubbink
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Martin J van den Bent
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Pim J French
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Yading Yuan
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sonam Sharma
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tzu-Chi Tseng
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Saba Adabi
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Simone P Niclou
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Olivier Keunen
- Translation Radiomics, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Ann-Christin Hau
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
- Luxembourg Center of Neuropathology, Laboratoire National De Santé, Luxembourg, Luxembourg
| | - Martin Vallières
- Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - David Fortin
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Division of Neurosurgery and Neuro-Oncology, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Martin Lepage
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Department of Nuclear Medicine and Radiobiology, Sherbrooke Molecular Imaging Centre, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Bennett Landman
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kaiwen Xu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Silky Chotai
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lola B Chambless
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Akshitkumar Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reid C Thompson
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuriy Gusev
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Krithika Bhuvaneshwar
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anousheh Sayah
- Division of Neuroradiology & Neurointerventional Radiology, Department of Radiology, MedStar Georgetown University Hospital, Washington, DC, USA
| | - Camelia Bencheqroun
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anas Belouali
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Department of Neuroradiology, Ruskin Wing, King's College Hospital NHS Foundation Trust, London, UK
| | - Alysha Chelliah
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Haris Shuaib
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Carmen Dragos
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
| | | | | | | | | | - Shady Gamal
- University of Cairo School of Medicine, Giza, Egypt
| | | | | | | | - Ji Eun Park
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Jihye Yun
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Ho Sung Kim
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Abhishek Mahajan
- The Clatterbridge Cancer Centre NHS Foundation Trust Pembroke Place, Liverpool, UK
| | - Mark Muzi
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Sean Benson
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, Netherlands
- GROW School of Oncology and Developmental Biology, Maastricht, Netherlands
| | - Jonas Teuwen
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | | | - William Escobar
- Clínica Imbanaco Grupo Quirón Salud, Cali, Colombia
- Universidad del Valle, Cali, Colombia
| | | | - Jose Bernal
- Universidad del Valle, Cali, Colombia
- The University of Edinburgh, Edinburgh, UK
| | | | - Joseph Choi
- Department of Industrial and Systems Engineering, University of Iowa, Iowa, USA
| | - Stephen Baek
- Department of Industrial and Systems Engineering, Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Yusung Kim
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Heba Ismael
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Bryan Allen
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - John M Buatti
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | | | - Hongwei Li
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Tobias Weiss
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Bertrand Pouymayou
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | | | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Prateek Prasanna
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Sampurna Shrestha
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Kartik M Mani
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Department of Radiation Oncology, Stony Brook University, Stony Brook, NY, USA
| | - David Payne
- Department of Radiology, Stony Brook University, Stony Brook, NY, USA
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Scientific Data Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Enrique Pelaez
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | - Francis Loayza
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | | | | | | | - Franco Vera
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Elvis Ríos
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Eduardo López
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Sergio A Velastin
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
| | - Godwin Ogbole
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mayowa Soneye
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Dotun Oyekunle
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | | | - Babatunde Osobu
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mustapha Shu'aibu
- Department of Radiology, Muhammad Abdullahi Wase Teaching Hospital, Kano, Nigeria
| | - Adeleye Dorcas
- Department of Radiology, Obafemi Awolowo University Ile-Ife, Ile-Ife, Osun, Nigeria
| | - Farouk Dako
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amber L Simpson
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Mohammad Hamghalam
- School of Computing, Queen's University, Kingston, ON, Canada
- Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
| | - Jacob J Peoples
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Ricky Hu
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Anh Tran
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Danielle Cutler
- The Faculty of Arts & Sciences, Queen's University, Kingston, ON, Canada
| | - Fabio Y Moraes
- Department of Oncology, Queen's University, Kingston, ON, Canada
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - James Gimpel
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Deepak Kattil Veettil
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Kendall Schmidt
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Brian Bialecki
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Sailaja Marella
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Cynthia Price
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Lisa Cimino
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Charles Apgar
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | | | - Bjoern Menze
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Jill S Barnholtz-Sloan
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
- Center for Biomedical Informatics and Information Technology, National Cancer Institute (NCI), National Institute of Health, Bethesda, MD, USA
| | | | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Pati S, Baid U, Edwards B, Sheller M, Wang SH, Reina GA, Foley P, Gruzdev A, Karkada D, Davatzikos C, Sako C, Ghodasara S, Bilello M, Mohan S, Vollmuth P, Brugnara G, Preetha CJ, Sahm F, Maier-Hein K, Zenk M, Bendszus M, Wick W, Calabrese E, Rudie J, Villanueva-Meyer J, Cha S, Ingalhalikar M, Jadhav M, Pandey U, Saini J, Garrett J, Larson M, Jeraj R, Currie S, Frood R, Fatania K, Huang RY, Chang K, Balaña C, Capellades J, Puig J, Trenkler J, Pichler J, Necker G, Haunschmidt A, Meckel S, Shukla G, Liem S, Alexander GS, Lombardo J, Palmer JD, Flanders AE, Dicker AP, Sair HI, Jones CK, Venkataraman A, Jiang M, So TY, Chen C, Heng PA, Dou Q, Kozubek M, Lux F, Michálek J, Matula P, Keřkovský M, Kopřivová T, Dostál M, Vybíhal V, Vogelbaum MA, Mitchell JR, Farinhas J, Maldjian JA, Yogananda CGB, Pinho MC, Reddy D, Holcomb J, Wagner BC, Ellingson BM, Cloughesy TF, Raymond C, Oughourlian T, Hagiwara A, Wang C, To MS, Bhardwaj S, Chong C, Agzarian M, Falcão AX, Martins SB, Teixeira BCA, Sprenger F, Menotti D, Lucio DR, LaMontagne P, Marcus D, Wiestler B, Kofler F, Ezhov I, Metz M, Jain R, Lee M, Lui YW, McKinley R, Slotboom J, Radojewski P, Meier R, Wiest R, Murcia D, Fu E, Haas R, Thompson J, Ormond DR, Badve C, Sloan AE, Vadmal V, Waite K, Colen RR, Pei L, Ak M, Srinivasan A, Bapuraj JR, Rao A, Wang N, Yoshiaki O, Moritani T, Turk S, Lee J, Prabhudesai S, Morón F, Mandel J, Kamnitsas K, Glocker B, Dixon LVM, Williams M, Zampakis P, Panagiotopoulos V, Tsiganos P, Alexiou S, Haliassos I, Zacharaki EI, Moustakas K, Kalogeropoulou C, Kardamakis DM, Choi YS, Lee SK, Chang JH, Ahn SS, Luo B, Poisson L, Wen N, Tiwari P, Verma R, Bareja R, Yadav I, Chen J, Kumar N, Smits M, van der Voort SR, Alafandi A, Incekara F, Wijnenga MMJ, Kapsas G, Gahrmann R, Schouten JW, Dubbink HJ, Vincent AJPE, van den Bent MJ, French PJ, Klein S, Yuan Y, Sharma S, Tseng TC, Adabi S, Niclou SP, Keunen O, Hau AC, Vallières M, Fortin D, Lepage M, Landman B, Ramadass K, Xu K, Chotai S, Chambless LB, Mistry A, Thompson RC, Gusev Y, Bhuvaneshwar K, Sayah A, Bencheqroun C, Belouali A, Madhavan S, Booth TC, Chelliah A, Modat M, Shuaib H, Dragos C, Abayazeed A, Kolodziej K, Hill M, Abbassy A, Gamal S, Mekhaimar M, Qayati M, Reyes M, Park JE, Yun J, Kim HS, Mahajan A, Muzi M, Benson S, Beets-Tan RGH, Teuwen J, Herrera-Trujillo A, Trujillo M, Escobar W, Abello A, Bernal J, Gómez J, Choi J, Baek S, Kim Y, Ismael H, Allen B, Buatti JM, Kotrotsou A, Li H, Weiss T, Weller M, Bink A, Pouymayou B, Shaykh HF, Saltz J, Prasanna P, Shrestha S, Mani KM, Payne D, Kurc T, Pelaez E, Franco-Maldonado H, Loayza F, Quevedo S, Guevara P, Torche E, Mendoza C, Vera F, Ríos E, López E, Velastin SA, Ogbole G, Soneye M, Oyekunle D, Odafe-Oyibotha O, Osobu B, Shu'aibu M, Dorcas A, Dako F, Simpson AL, Hamghalam M, Peoples JJ, Hu R, Tran A, Cutler D, Moraes FY, Boss MA, Gimpel J, Veettil DK, Schmidt K, Bialecki B, Marella S, Price C, Cimino L, Apgar C, Shah P, Menze B, Barnholtz-Sloan JS, Martin J, Bakas S. Federated learning enables big data for rare cancer boundary detection. Nat Commun 2022; 13:7346. [PMID: 36470898 PMCID: PMC9722782 DOI: 10.1038/s41467-022-33407-5] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 09/16/2022] [Indexed: 12/12/2022] Open
Abstract
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 targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.
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Affiliation(s)
- Sarthak Pati
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
| | - Ujjwal Baid
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | | | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chiharu Sako
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Satyam Ghodasara
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michel Bilello
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Felix Sahm
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maximilian Zenk
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany
| | - Evan Calabrese
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Jeffrey Rudie
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Javier Villanueva-Meyer
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Soonmee Cha
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Madhura Ingalhalikar
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Manali Jadhav
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Umang Pandey
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - John Garrett
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Matthew Larson
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Robert Jeraj
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Stuart Currie
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Russell Frood
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Kavi Fatania
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ken Chang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | | | - Josep Puig
- Department of Radiology (IDI), Girona Biomedical Research Institute (IdIBGi), Josep Trueta University Hospital, Girona, Spain
| | - Johannes Trenkler
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Josef Pichler
- Department of Neurooncology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Georg Necker
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Andreas Haunschmidt
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Stephan Meckel
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
- Institute of Diagnostic and Interventional Neuroradiology, RKH Klinikum Ludwigsburg, Ludwigsburg, Germany
| | - Gaurav Shukla
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiation Oncology, Christiana Care Health System, Philadelphia, PA, USA
| | - Spencer Liem
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Gregory S Alexander
- Department of Radiation Oncology, University of Maryland, Baltimore, MD, USA
| | - Joseph Lombardo
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joshua D Palmer
- Department of Radiation Oncology, The James Cancer Hospital and Solove Research Institute, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Adam E Flanders
- Department of Radiology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Adam P Dicker
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Haris I Sair
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Craig K Jones
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Archana Venkataraman
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Meirui Jiang
- The Chinese University of Hong Kong, Hong Kong, China
| | - Tiffany Y So
- The Chinese University of Hong Kong, Hong Kong, China
| | - Cheng Chen
- The Chinese University of Hong Kong, Hong Kong, China
| | | | - Qi Dou
- The Chinese University of Hong Kong, Hong Kong, China
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Filip Lux
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Petr Matula
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Tereza Kopřivová
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Marek Dostál
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Václav Vybíhal
- Department of Neurosurgery, Faculty of Medicine, Masaryk University, Brno, and University Hospital and Czech Republic, Brno, Czech Republic
| | - Michael A Vogelbaum
- Department of Neuro Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - J Ross Mitchell
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Joaquim Farinhas
- Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | | | - Marco C Pinho
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Divya Reddy
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James Holcomb
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Talia Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Minh-Son To
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
- Division of Surgery and Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Sargam Bhardwaj
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
| | - Chee Chong
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Marc Agzarian
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Bernardo C A Teixeira
- Instituto de Neurologia de Curitiba, Curitiba, Paraná, Brazil
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Flávia Sprenger
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - David Menotti
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Diego R Lucio
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Pamela LaMontagne
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Daniel Marcus
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Marie Metz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Rajan Jain
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, USA
| | - Matthew Lee
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Yvonne W Lui
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Richard McKinley
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Piotr Radojewski
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Raphael Meier
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Derrick Murcia
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Eric Fu
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Rourke Haas
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - John Thompson
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - David Ryan Ormond
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Chaitra Badve
- Department of Radiology, University Hospitals Cleveland, Cleveland, OH, USA
| | - Andrew E Sloan
- Department of Neurological Surgery, University Hospitals-Seidman Cancer Center, Cleveland, OH, USA
- Case Comprehensive Cancer Center, Cleveland, OH, USA
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Vachan Vadmal
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kristin Waite
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
| | - Rivka R Colen
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linmin Pei
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Murat Ak
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashok Srinivasan
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - J Rajiv Bapuraj
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Arvind Rao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Ota Yoshiaki
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Toshio Moritani
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Sevcan Turk
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Joonsang Lee
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Snehal Prabhudesai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fanny Morón
- Department of Radiology, Baylor College of Medicine, Houston, TX, USA
| | - Jacob Mandel
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Konstantinos Kamnitsas
- Department of Computing, Imperial College London, London, UK
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Ben Glocker
- Department of Computing, Imperial College London, London, UK
| | - Luke V M Dixon
- Department of Radiology, Imperial College NHS Healthcare Trust, London, UK
| | - Matthew Williams
- Computational Oncology Group, Institute for Global Health Innovation, Imperial College London, London, UK
| | - Peter Zampakis
- Department of NeuroRadiology, University of Patras, Patras, Greece
| | | | - Panagiotis Tsiganos
- Clinical Radiology Laboratory, Department of Medicine, University of Patras, Patras, Greece
| | - Sotiris Alexiou
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | - Ilias Haliassos
- Department of Neuro-Oncology, University of Patras, Patras, Greece
| | - Evangelia I Zacharaki
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | | | | | | | | | | | | | - Sung Soo Ahn
- Yonsei University College of Medicine, Seoul, Korea
| | - Bing Luo
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Laila Poisson
- Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | | | - Ruchika Verma
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
- Case Western Reserve University, Cleveland, OH, USA
| | - Rohan Bareja
- Case Western Reserve University, Cleveland, OH, USA
| | - Ipsa Yadav
- Case Western Reserve University, Cleveland, OH, USA
| | | | - Neeraj Kumar
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Sebastian R van der Voort
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Ahmed Alafandi
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Fatih Incekara
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Maarten M J Wijnenga
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Georgios Kapsas
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Renske Gahrmann
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Joost W Schouten
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Hendrikus J Dubbink
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Martin J van den Bent
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Pim J French
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Yading Yuan
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sonam Sharma
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tzu-Chi Tseng
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Saba Adabi
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Simone P Niclou
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Olivier Keunen
- Translation Radiomics, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Ann-Christin Hau
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
- Luxembourg Center of Neuropathology, Laboratoire National De Santé, Luxembourg, Luxembourg
| | - Martin Vallières
- Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - David Fortin
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Division of Neurosurgery and Neuro-Oncology, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Martin Lepage
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Department of Nuclear Medicine and Radiobiology, Sherbrooke Molecular Imaging Centre, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Bennett Landman
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kaiwen Xu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Silky Chotai
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lola B Chambless
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Akshitkumar Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reid C Thompson
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuriy Gusev
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Krithika Bhuvaneshwar
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anousheh Sayah
- Division of Neuroradiology & Neurointerventional Radiology, Department of Radiology, MedStar Georgetown University Hospital, Washington, DC, USA
| | - Camelia Bencheqroun
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anas Belouali
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Department of Neuroradiology, Ruskin Wing, King's College Hospital NHS Foundation Trust, London, UK
| | - Alysha Chelliah
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Haris Shuaib
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Carmen Dragos
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
| | | | | | | | | | - Shady Gamal
- University of Cairo School of Medicine, Giza, Egypt
| | | | | | | | - Ji Eun Park
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Jihye Yun
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Ho Sung Kim
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Abhishek Mahajan
- The Clatterbridge Cancer Centre NHS Foundation Trust Pembroke Place, Liverpool, UK
| | - Mark Muzi
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Sean Benson
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, Netherlands
- GROW School of Oncology and Developmental Biology, Maastricht, Netherlands
| | - Jonas Teuwen
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | | | - William Escobar
- Clínica Imbanaco Grupo Quirón Salud, Cali, Colombia
- Universidad del Valle, Cali, Colombia
| | | | - Jose Bernal
- Universidad del Valle, Cali, Colombia
- The University of Edinburgh, Edinburgh, UK
| | | | - Joseph Choi
- Department of Industrial and Systems Engineering, University of Iowa, Iowa, USA
| | - Stephen Baek
- Department of Industrial and Systems Engineering, Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Yusung Kim
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Heba Ismael
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Bryan Allen
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - John M Buatti
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | | | - Hongwei Li
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Tobias Weiss
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Bertrand Pouymayou
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | | | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Prateek Prasanna
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Sampurna Shrestha
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Kartik M Mani
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Department of Radiation Oncology, Stony Brook University, Stony Brook, NY, USA
| | - David Payne
- Department of Radiology, Stony Brook University, Stony Brook, NY, USA
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Scientific Data Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Enrique Pelaez
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | - Francis Loayza
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | | | | | | | - Franco Vera
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Elvis Ríos
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Eduardo López
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Sergio A Velastin
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
| | - Godwin Ogbole
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mayowa Soneye
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Dotun Oyekunle
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | | | - Babatunde Osobu
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mustapha Shu'aibu
- Department of Radiology, Muhammad Abdullahi Wase Teaching Hospital, Kano, Nigeria
| | - Adeleye Dorcas
- Department of Radiology, Obafemi Awolowo University Ile-Ife, Ile-Ife, Osun, Nigeria
| | - Farouk Dako
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amber L Simpson
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Mohammad Hamghalam
- School of Computing, Queen's University, Kingston, ON, Canada
- Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
| | - Jacob J Peoples
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Ricky Hu
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Anh Tran
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Danielle Cutler
- The Faculty of Arts & Sciences, Queen's University, Kingston, ON, Canada
| | - Fabio Y Moraes
- Department of Oncology, Queen's University, Kingston, ON, Canada
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - James Gimpel
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Deepak Kattil Veettil
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Kendall Schmidt
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Brian Bialecki
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Sailaja Marella
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Cynthia Price
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Lisa Cimino
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Charles Apgar
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | | | - Bjoern Menze
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Jill S Barnholtz-Sloan
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
- Center for Biomedical Informatics and Information Technology, National Cancer Institute (NCI), National Institute of Health, Bethesda, MD, USA
| | | | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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To MS, Lu L, Tran M, Chong C. Preferential reporting of significant p-values in radiology journal abstracts. Clin Radiol 2022; 77:743-748. [PMID: 35810024 DOI: 10.1016/j.crad.2022.05.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 05/04/2022] [Accepted: 05/30/2022] [Indexed: 11/03/2022]
Abstract
AIM To assess the prevalence of publication bias in the radiology literature, data-mining techniques were used to extract p-values in abstracts published in key radiology journals over the past 20 years. MATERIALS AND METHODS A total of 34,699 abstracts published in Radiology, Investigative Radiology, European Radiology, American Journal of Roentgenology, and American Journal of Neuroradiology published between January 2000 and December 2019 were included in the analysis. Automated text mining using regular expressions was used to mine abstracts for p-values. RESULTS The text mining algorithm detected 43,489 p-values, the majority (82.4%) of which were reported as "significant", i.e., p<0.05. There has also been an increased propensity to report more p-values over time. The distribution of p-values showed a step change at the conventional significance threshold of 0.05. The odds ratio of a "significant" p-value being reported in the abstract compared to the full text was calculated to be 2.52 (95% confidence interval 1.78-3.58; p<0.001). Taken together, these results provide strong evidence for selective reporting of significant p-values in abstracts. CONCLUSION Statistically significant p-values are preferentially reported in radiology journal abstracts.
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Affiliation(s)
- M-S To
- Flinders Health and Medical Research Institute, Bedford Park, SA, Australia; Division of Surgery and Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA, Australia.
| | - L Lu
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
| | - M Tran
- Division of Surgery and Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA, Australia
| | - C Chong
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
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Langhorne B, Lund J, Lutchman I, McGuinness R, Neary M, Pampapathi S, Pang E, Podbicanin S, Rai N, Redhouse White G, Sujith J, Thomas P, Walker I, Winterton R, Anderson P, Barrington M, Bhadra K, Clark G, Fowler G, Gibson C, Hudson S, Kaminskaite V, Lawday S, Longshaw A, MacKrill E, McLachlan F, Murdeshwar A, Nieuwoudt R, Parker P, Randall R, Rawlins E, Reeves SA, Rye D, Sirkis T, Sykes B, Ventress N, Wosinska N, Akram B, Burton L, Coombs A, Long R, Magowan D, Ong C, Sethi M, Williams G, Chan C, Chan LH, Fernando D, Gaba F, Khor Z, Les JW, Mak R, Moin S, Ng Kee Kwong KC, Paterson-Brown S, Tew YY, Bardon A, Burrell K, Coldwell C, Costa I, Dexter E, Hardy A, Khojani M, Mazurek J, Raymond T, Reddy V, Reynolds J, Soma A, Agiotakis S, Alsusa H, Desai N, Peristerakis I, Adcock A, Ayub H, Bennett T, Bibi F, Brenac S, Chapman T, Clarke G, Clark F, Galvin C, Gwyn-Jones A, Henry-Blake C, Kerner S, Kiandee M, Lovett A, Pilecka A, Ravindran R, Siddique H, Sikand T, Treadwell K, Akmal K, Apata A, Barton O, Broad G, Darling H, Dhuga Y, Emms L, Habib S, Jain R, Jeater J, Kan CYP, Kathiravelupillai A, Khatkar H, Kirmani S, Kulasabanathan K, Lacey H, Lal K, Manafa C, Mansoor M, McDonald S, Mittal A, Mustoe S, Nottrodt L, Oliver P, Papapetrou I, Pattinson F, Raja M, Reyhani H, Shahmiri A, Small O, Soni U, Aguirrezabala Armbruster B, Bunni J, Hakim MA, Hawkins-Hooker L, Howell KA, Hullait R, Jaskowska A, Ottewell L, Thomas-Jones I, Vasudev A, Clements B, Fenton J, Gill M, Haider S, Lim AJM, Maguire H, McMullan J, Nicoletti J, Samuel S, Unais MA, White N, Yao PC, Yow L, Boyle C, Brady R, Cheekoty P, Cheong J, Chew SJHL, Chow R, Ganewatta Kankanamge D, Mamer L, Mohammed B, Ng Chieng Hin J, Renji Chungath R, Royston A, Sharrad E, Sinclair R, Tingle S, Treherne K, Wyatt F, Maniarasu VS, Moug S, Appanna T, Bucknall T, Hussain F, Owen A, Parry M, Parry R, Sagua N, Spofforth K, Yuen ECT, Bosley N, Hardie W, Moore T, Regas C, Abdel-Khaleq S, Ali N, Bashiti H, Buxton-Hopley R, Constantinides M, D'Afflitto M, Deshpande A, Duque Golding J, Frisira E, Germani Batacchi M, Gomaa A, Hay D, Hutchison R, Iakovou A, Iakovou D, Ismail E, Jefferson S, Jones L, Khouli Y, Knowles C, Mason J, McCaughan R, Moffatt J, Morawala A, Nadir H, Neyroud F, Nikookam Y, Parmar A, Pinto L, Ramamoorthy R, Richards E, Thomson S, Trainer C, Valetopoulou A, Vassiliou A, Wantman A, Wilde S, Dickinson M, Rockall T, Senn D, Wcislo K, Zalmay P, Adelekan K, Allen K, Bajaj M, Gatumbu P, Hang S, Hashmi Y, Kaur T, Kawesha A, Kisiel A, Woodmass M, Adelowo T, Ahari D, Alhwaishel K, Atherton R, Clayton B, Cockroft A, Curtis Lopez C, Hilton M, Ismail N, Kouadria M, Lee L, MacConnachie A, Monks F, Mungroo S, Nikoletopoulou C, Pearce L, Sara X, Shahid A, Suresh G, Wilcha R, Atiyah A, Davies E, Dermanis A, Gibbons H, Hyde A, Lawson A, Lee C, Leung-Tack M, Li Saw Hee J, Mostafa O, Nair D, Pattani N, Plumbley-Jones J, Pufal K, Ramesh P, Sanghera J, Saram S, Scadding S, See S, Stringer H, Torrance A, Vardon H, Wyn-Griffiths F, Brew A, Kaur G, Soni D, Tickle A, Akbar Z, Appleyard T, Figg K, Jayawardena P, Johnson A, Kamran Siddiqui Z, Lacy-Colson J, Oatham R, Rowlands B, Sludden E, Turnbull C, Allin D, Ansar Z, Azeez Z, Dale VH, Garg J, Horner A, Jones S, Knight S, McGregor C, McKenna J, McLelland T, Packham-Smith A, Rowsell K, Spector-Hill I, Adeniken E, Baker J, Bartlett M, Chikomba L, Connell B, Deekonda P, Dhar M, Elmansouri A, Gamage K, Goodhew R, Hanna P, Knight J, Luca A, Maasoumi N, Mahamoud F, Manji S, Marwaha PK, Mason F, Oluboyede A, Pigott L, Razaq AM, Richardson M, Saddaoui I, Wijeyendram P, Yau S, Atkins W, Liang K, Miles N, Praveen B, Ashai S, Braganza J, Common J, Cundy A, Davies R, Guthrie J, Handa I, Iqbal M, Ismail R, Jones C, Jones I, Lee KS, Levene A, Okocha M, Olivier J, Smith A, Subramaniam E, Tandle S, Wang A, Watson A, Wilson C, Chan XHF, Khoo E, Montgomery C, Norris M, Pugalenthi PP, Common T, Cook E, Mistry H, Shinmar HS, Agarwal G, Bandyopadhyay S, Brazier B, Carroll L, Goede A, Harbourne A, Lakhani A, Lami M, Larwood J, Martin J, Merchant J, Pattenden S, Pradhan A, Raafat N, Rothwell E, Shammoon Y, Sudarshan R, Vickers E, Wingfield L, Ashworth I, Azizi S, Bhate R, Chowdhury T, Christou A, Davies L, Dwaraknath M, Farah Y, Garner J, Gureviciute E, Hart E, Jain A, Javid S, Kankam HK, Kaur Toor P, Kaz R, Kermali M, Khan I, Mattson A, McManus A, Murphy M, Nair K, Ngemoh D, Norton E, Olabiran A, Parry L, Payne T, Pillai K, Price S, Punjabi K, Raghunathan A, Ramwell A, Raza M, Ritehnia J, Simpson G, Smith W, Sodeinde S, Studd L, Subramaniam M, Thomas J, Towey S, Tsang E, Tuteja D, Vasani J, Vio M, Badran A, Adams J, Anthony Wilkinson J, Asvandi S, Austin T, Bald A, Bix E, Carrick M, Chander B, Chowdhury S, Cooper Drake B, Crosbie S, D Portela S, Francis D, Gallagher C, Gillespie R, Gravett H, Gupta P, Ilyas C, James G, Johny J, Jones A, Kinder F, MacLeod C, Macrow C, Maqsood-Shah A, Mather J, McCann L, McMahon R, Mitham E, Mohamed M, Munton E, Nightingale K, O'Neill K, Onyemuchara I, Senior R, Shanahan A, Sherlock J, Spyridoulias A, Stavrou C, Stokes D, Tamang R, Taylor E, Trafford C, Uden C, Waddington C, Yassin D, Zaman M, Bangi S, Cheng T, Chew D, Hussain N, Imani-Masouleh S, Mahasivam G, McKnight G, Ng HL, Ota HC, Pasha T, Ravindran W, Shah K, Vishnu K S, Zaman S, Carr W, Cope S, Eagles EJ, Howarth-Maddison M, Li CY, Reed J, Ridge A, Stubbs T, Teasdaled D, Umar R, Worthington J, Dhebri A, Kalenderov R, Alattas A, Arain Z, Bhudia R, Chia D, Daniel S, Dar T, Garland H, Girish M, Hampson A, Kyriacou H, Lehovsky K, Mullins W, Omorphos N, Vasdev N, Venkatesh A, Waldock W, Bhandari A, Brown G, Choa G, Eichenauer CE, Ezennia K, Kidwai Z, Lloyd-Thomas A, Macaskill Stewart A, Massardi C, Sinclair E, Skajaa N, Smith M, Tan I, Afsheen N, Anuar A, Azam Z, Bhatia P, Davies-kelly N, Dickinson S, Elkawafi M, Ganapathy M, Gupta S, Khoury EG, Licudi D, Mehta V, Neequaye S, Nita G, Tay VL, Zhao S, Botsa E, Cuthbert H, Elliott J, Furlepa M, Lehmann J, Mangtani A, Narayan A, Nazarian S, Parmar C, Shah D, Shaw C, Zhao Z, Beck C, Caldwell S, Clements JM, French B, Kenny R, Kirk S, Lindsay J, McClung A, McLaughlin N, Watson S, Whiteside E, Alyacoubi S, Arumugam V, Beg R, Dawas K, Garg S, Lloyd ER, Mahfouz Y, Manobharath N, Moonesinghe R, Morka N, Patel K, Prashar J, Yip S, Adeeko ES, Ajekigbe F, Bhat A, Evans C, Farrugia A, Gurung C, Long T, Malik B, Manirajan S, Newport D, Rayer J, Ridha A, Ross E, Saran T, Sinker A, Waruingi D, Allen R, Al Sadek Y, Alves do Canto Brum H, Asharaf H, Ashman M, Balakumar V, Barrington J, Baskaran R, Berry A, Bhachoo H, Bilal A, Boaden L, Chia WL, Covell G, Crook D, Dadnam F, Davis L, De Berker H, Doyle C, Fox C, Gruffydd-Davies M, Hafouda Y, Hill A, Hubbard E, Hunter A, Inpadhas V, Jamshaid M, Jandu G, Jeyanthi M, Jones T, Kantor C, Kwak SY, Malik N, Matt R, McNulty P, Miles C, Mohomed A, Myat P, Niharika J, Nixon A, O'Reilly D, Parmar K, Pengelly S, Price L, Ramsden M, Turnor R, Wales E, Waring H, Wu M, Yang T, Ye TTS, Zander A, Zeicu C, Bellam S, Francombe J, Kawamoto N, Rahman MR, Sathyanarayana A, Tang HT, Cheung J, Hollingshead J, Page V, Sugarman J, Wong E, Chiong J, Fung E, Kan SY, Kiang J, Kok J, Krahelski O, Liew MY, Lyell B, Sharif Z, Speake D, Alim L, Amakye NY, Chandrasekaran J, Chandratreya N, Drake J, Owoso T, Thu YM, Abou El Ela Bourquin B, Alberts J, Chapman D, Rehnnuma N, Ainsworth K, Carpenter H, Emmanuel T, Fisher T, Gabrel M, Guan Z, Hollows S, Hotouras A, Ip Fung Chun N, Jaffer S, Kallikas G, Kennedy N, Lewinsohn B, Liu FY, Mohammed S, Rutherfurd A, Situ T, Stammer A, Taylor F, Thin N, Urgesi E, Zhang N, Ahmad MA, Bishop A, Bowes A, Dixit A, Glasson R, Hatta S, Hatt K, Larcombe S, Preece J, Riordan E, Fegredo D, Haq MZ, Li C, McCann G, Stewart D, Baraza W, Bhullar D, Burt G, Coyle J, Deans J, Devine A, Hird R, Ikotun O, Manchip G, Ross C, Storey L, Tan WWL, Tse C, Warner C, Whitehead M, Wu F, Court EL, Crisp E, Huttman M, Mayes F, Robertson H, Rosen H, Sandberg C, Smith H, Al Bakry M, Ashwell W, Bajaj S, Bandyopadhyay D, Browlee O, Burway S, Chand CP, Elsayeh K, Elsharkawi A, Evans E, Ferrin S, Fort-Schaale A, Iacob M, I K, Impelliziere Licastro G, Mankoo AS, Olaniyan T, Otun J, Pereira R, Reddy R, Saeed D, Simmonds O, Singhal G, Tron K, Wickstone C, Williams R, Bradshaw E, De Kock Jewell V, Houlden C, Knight C, Metezai H, Mirza-Davies A, Seymour Z, Spink D, Wischhusen S. Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study. Lancet Digit Health 2022; 4:e520-e531. [PMID: 35750401 DOI: 10.1016/s2589-7500(22)00069-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 01/07/2022] [Accepted: 04/06/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. METHODS We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). FINDINGS In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683-0·717]). INTERPRETATION In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. FUNDING British Journal of Surgery Society.
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Miyazawa Y, Chong C, Kevrekidis PG, Yang J. Rogue and solitary waves in coupled phononic crystals. Phys Rev E 2022; 105:034202. [PMID: 35428101 DOI: 10.1103/physreve.105.034202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 02/04/2022] [Indexed: 06/14/2023]
Abstract
In this work we present an analytical and numerical study of rogue and solitary waves in a coupled one-dimensional nonlinear lattice that involves both axial and rotational degrees of freedom. Using a multiple-scale analysis, we derive a system of coupled nonlinear Schrödinger-type equations in order to approximate solitary waves and rogue waves of the coupled lattice model. Numerical simulations are found to agree with the analytical approximations. We also consider generic initialization data in the form of a Gaussian profile and observe that they can result in the spontaneous formation of rogue-wave-like patterns in the lattice. The solitary and rogue waves in the lattice demonstrate both energy isolation and exchange between the axial and rotational degrees of freedom of the system. This suggests that the studied coupled lattice has the potential to be an efficient energy isolation, transfer, and focusing medium.
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Affiliation(s)
- Y Miyazawa
- Department of Aeronautics and Astronautics, University of Washington, Seattle, Washington 98195, USA
| | - C Chong
- Department of Mathematics, Bowdoin College, Brunswick, Maine 04011, USA
| | - P G Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, Massachusetts 01003-4515, USA
| | - J Yang
- Department of Aeronautics and Astronautics, University of Washington, Seattle, Washington 98195, USA
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Thoo S, Wong T, Chong C, Lim W. Assessing Lung Parenchymal Enhancement on Dual-Energy CT Pulmonary Angiograms: Potential utility of dual-energy technique as an angiographic and parenchymal 'one-stop shop' in the initial workup of patients with pulmonary symptoms. J Med Imaging Radiat Oncol 2021; 66:599-602. [PMID: 34486224 DOI: 10.1111/1754-9485.13323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 08/26/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVE The aim of this study was to assess the enhancement of lung parenchyma on dual-energy (DE) computed tomogram (CT) by comparing attenuation between routine post-contrast and dual-energy generated virtual unenhanced (VU) images. METHODS Patients presenting to the Emergency Department who subsequently underwent DE-CT pulmonary angiogram from the 1st to the 30th of November were enrolled. The DE data set obtained was used to generate VU images. Attenuation in Hounsfield units (HU) was measured at two sites for each patient and compared between VU and routine post-contrast (PC) reconstructions. Statistical analysis was performed using paired-samples t-test. RESULTS There is a statistical difference between lung parenchymal attenuation value between the CV and PC images, denser in the PC dataset and also towards the bases, with a mean HU of -841 and -817 (difference of 24) respectively. CONCLUSIONS This study confirms increased lung parenchymal density when comparing PC and VU reconstructions. Based on results, the paper recommends utilising dual-energy capabilities for VU reconstructions in CTPAs to optimise assessment of lung parenchyma.
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Affiliation(s)
- Sophie Thoo
- Royal Adelaide Hospital, Adelaide, South Australia, Australia
| | - Teresa Wong
- Royal Adelaide Hospital, Adelaide, South Australia, Australia
| | - Chee Chong
- Dr Jones and Partners, Eastwood, South Australia, Australia.,Flinders Medical Centre. Flinders Drive, Bedford Park, South Australia, Australia
| | - Wanyin Lim
- Royal Adelaide Hospital, Adelaide, South Australia, Australia.,Dr Jones and Partners, Eastwood, South Australia, Australia
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Blake C, Jacob J, Chong C, Stub D, Shaw J, Kaye D, Nanayakkara S. 780 A Pilot Project to Assess the Safety of Same Day Discharge for Percutaneous Coronary Intervention. Heart Lung Circ 2020. [DOI: 10.1016/j.hlc.2020.09.787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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12
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Bruand M, Barras D, Mina M, Lanitis E, Chong C, Dorier J, Walton J, Bassani-Sternberg M, Kandalaft L, McNeish I, Swisher E, Delorenzi M, Ren B, Ciriello G, Irving M, Rusakiewicz S, Foukas P, Martinon F, Dangaj D, Coukos G. Immunogenicity of BRCA1-deficient ovarian cancers is driven through DNA sensing and is augmented by PARP inhibition. Ann Oncol 2019. [DOI: 10.1093/annonc/mdz268.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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13
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Brody AA, Jones T, Chong C. TAILORING THE DEMENTIA SYMPTOM MANAGEMENT AT HOME PROGRAM FOR THE HOSPICE INTERDISCIPLINARY TEAM. Innov Aging 2018. [DOI: 10.1093/geroni/igy023.3078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- A A Brody
- New York University Rory Meyers College of Nursing, New York, New York, United States
| | - T Jones
- New York University Silver School of Social Work; New York, NY, USA
| | - C Chong
- Hartford Institute for Geriatric Nursing, New York, NY; New York University Rory Meyers College of Nursing, New York, NY
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14
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Greenberg SA, Chong C, Hartnett E, Berkowitz GS, Schenkel AB, Haber J. EVALUATING INTERPROFESSIONAL STUDENT TRAINING AND COMMUNITY-DWELLING SENIOR ORAL HEALTH KNOWLEDGE. Innov Aging 2018. [DOI: 10.1093/geroni/igy023.3076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- S A Greenberg
- New York University Rory Meyers College of Nursing, New York, New York, United States
| | - C Chong
- The Hartford Institute for Geriatric Nursing, New York, NY, USA; NYU Rory Meyers College of Nursing, New York, NY, USA
| | - E Hartnett
- NYU Rory Meyers College of Nursing, New York, NY, USA
| | - G S Berkowitz
- New York University College of Dentistry, New York, NY, USA
| | - A B Schenkel
- New York University College of Dentistry, New York, NY, USA
| | - J Haber
- New York University Rory Meyers College of Nursing, New York, NY, USA
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Kim H, Kim E, Chong C, Kevrekidis PG, Yang J. Demonstration of Dispersive Rarefaction Shocks in Hollow Elliptical Cylinder Chains. Phys Rev Lett 2018; 120:194101. [PMID: 29799249 DOI: 10.1103/physrevlett.120.194101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Indexed: 06/08/2023]
Abstract
We report an experimental and numerical demonstration of dispersive rarefaction shocks (DRS) in a 3D-printed soft chain of hollow elliptical cylinders. We find that, in contrast to conventional nonlinear waves, these DRS have their lower amplitude components travel faster, while the higher amplitude ones propagate slower. This results in the backward-tilted shape of the front of the wave (the rarefaction segment) and the breakage of wave tails into a modulated waveform (the dispersive shock segment). Examining the DRS under various impact conditions, we find the counterintuitive feature that the higher striker velocity causes the slower propagation of the DRS. These unique features can be useful for mitigating impact controllably and efficiently without relying on material damping or plasticity effects.
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Affiliation(s)
- H Kim
- Aeronautics and Astronautics, University of Washington, Seattle, Washington, 98195-2400, USA
| | - E Kim
- Aeronautics and Astronautics, University of Washington, Seattle, Washington, 98195-2400, USA
- Division of Mechanical System Engineering & Automotive Hi-Technology Research Center, Chonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju, Jeonbuk 54896, Republic of Korea
| | - C Chong
- Department of Mathematics, Bowdoin College, Brunswick, Maine 04011, USA
| | - P G Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003, USA
| | - J Yang
- Aeronautics and Astronautics, University of Washington, Seattle, Washington, 98195-2400, USA
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Abstract
The study of granular crystals, which are nonlinear metamaterials that consist of closely packed arrays of particles that interact elastically, is a vibrant area of research that combines ideas from disciplines such as materials science, nonlinear dynamics, and condensed-matter physics. Granular crystals exploit geometrical nonlinearities in their constitutive microstructure to produce properties (such as tunability and energy localization) that are not conventional to engineering materials and linear devices. In this topical review, we focus on recent experimental, computational, and theoretical results on nonlinear coherent structures in granular crystals. Such structures-which include traveling solitary waves, dispersive shock waves, and discrete breathers-have fascinating dynamics, including a diversity of both transient features and robust, long-lived patterns that emerge from broad classes of initial data. In our review, we primarily discuss phenomena in one-dimensional crystals, as most research to date has focused on such scenarios, but we also present some extensions to two-dimensional settings. Throughout the review, we highlight open problems and discuss a variety of potential engineering applications that arise from the rich dynamic response of granular crystals.
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Affiliation(s)
- C Chong
- Department of Mathematics, Bowdoin College, Brunswick, Maine 04011, United States of America
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Nguyen T, Ong G, Stansborough J, Surikow S, Chong C, Horowitz J. P604Hypotension at admission and extent of release of NT-proBNP and catecholamines are associated with increased medium-term mortality rate in Takotsubo cardiomyopathy. Eur Heart J 2017. [DOI: 10.1093/eurheartj/ehx501.p604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Yasuda H, Chong C, Yang J, Kevrekidis PG. Emergence of dispersive shocks and rarefaction waves in power-law contact models. Phys Rev E 2017; 95:062216. [PMID: 28709347 DOI: 10.1103/physreve.95.062216] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Indexed: 11/07/2022]
Abstract
In the present work, motivated by generalized forms of the Hertzian dynamics associated with granular crystals, we consider the possibility of such models to give rise to both dispersive shock and rarefaction waves. Depending on the value p of the nonlinearity exponent, we find that both of these possibilities are realizable. We use a quasicontinuum approximation of a generalized inviscid Burgers model in order to predict the solution profile up to times near the formation of the dispersive shock, as well as to estimate when it will occur. Beyond that time threshold, oscillations associated with the highly dispersive nature of the underlying model emerge, which cannot be captured by the quasicontinuum approximation. Our analytical characterization of the above features is complemented by systematic numerical computations.
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Affiliation(s)
- H Yasuda
- Aeronautics & Astronautics, University of Washington, Seattle, Washington 98195-2400, USA
| | - C Chong
- Department of Mathematics, Bowdoin College, Brunswick, Maine 04011, USA
| | - J Yang
- Aeronautics & Astronautics, University of Washington, Seattle, Washington 98195-2400, USA
| | - P G Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, Massachusetts 01003-4515, USA
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Zhao R, Loh K, Mian M, Chong C, Lim K. Malaena but not coffee ground vomit or bright haematemesis predicts adverse outcomes in acute upper gastro intestinal bleeding. Intern Med J 2017. [DOI: 10.1111/imj.16_13461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- R Zhao
- Austin Hospital
- Northern Hospital
| | - K Loh
- Austin Hospital
- Northern Hospital
| | - M Mian
- Austin Hospital
- Northern Hospital
| | - C Chong
- Austin Hospital
- Northern Hospital
| | - K Lim
- Austin Hospital
- Northern Hospital
- University of Melbourne
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20
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Wallen SP, Lee J, Mei D, Chong C, Kevrekidis PG, Boechler N. Discrete breathers in a mass-in-mass chain with Hertzian local resonators. Phys Rev E 2017; 95:022904. [PMID: 28297872 DOI: 10.1103/physreve.95.022904] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Indexed: 11/07/2022]
Abstract
We report on the existence of discrete breathers in a one-dimensional, mass-in-mass chain with linear intersite coupling and nonlinear, precompressed Hertzian local resonators, which is motivated by recent studies of the dynamics of microspheres adhered to elastic substrates. After predicting theoretically the existence of discrete breathers in the continuum and anticontinuum limits of intersite coupling, we use numerical continuation to compute a family of breathers interpolating between the two regimes in a finite chain, where the displacement profiles of the breathers are localized around one lattice site. We then analyze the frequency-amplitude dependence of the breathers by performing numerical continuation on a linear eigenmode (vanishing amplitude) solution of the system near the upper band gap edge. Finally, we use direct numerical integration of the equations of motion to demonstrate the formation and evolution of the identified localized modes in energy-conserving and dissipative scenarios, including within settings that may be relevant to future experimental studies.
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Affiliation(s)
- S P Wallen
- Department of Mechanical Engineering, University of Washington, Seattle, Washington 98195, USA
| | - J Lee
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA
| | - D Mei
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA
| | - C Chong
- Department of Mathematics, Bowdoin College, Brunswick, Maine 04011, USA
| | - P G Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA
| | - N Boechler
- Department of Mechanical Engineering, University of Washington, Seattle, Washington 98195, USA
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Vlok R, Melhuish TM, Chong C, Ryan T, White LD. Adjuncts to local anaesthetics in tonsillectomy: a systematic review and meta-analysis. J Anesth 2017; 31:608-616. [PMID: 28120104 DOI: 10.1007/s00540-017-2310-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Accepted: 01/14/2017] [Indexed: 10/20/2022]
Abstract
The infiltration of local anaesthetic agents has been shown to reduce post-tonsillectomy pain. A number of recent studies have shown that the addition of agents such as clonidine and dexamethasone improve the efficacy of nerve blocks and spinal anaesthesia. The aim of this review was to determine whether additives to local anaesthetic agents improve post-tonsillectomy outcomes. Four major databases were systematically searched for all relevant studies published up to August 2016. All study designs with a control group receiving local anaesthetic infiltration and an intervention receiving the same infiltration with an added agent were included in this review. These studies were then assessed for level of evidence and risk of bias. The data were then analysed both qualitatively and where appropriate by meta-analysis. We reviewed 11 randomised controlled trial (RCTs) that included 854 patients. Due to inconsistencies in the methods used to report outcomes, both quantitative and qualitative comparisons were required to analyse the extracted data. Overall, we found that dexamethasone, magnesium, pethidine and tramadol reduce post-operative pain and analgesia use, with dexamethasone in particular significantly reducing post-operative nausea and vomiting and magnesium infiltration significantly reducing the incidence of laryngospasm. This systematic review of RCTs provides strong evidence that the use of dexamethasone and magnesium as additives to local anaesthetics reduces post-tonsillectomy pain and analgesia requirement. There is limited evidence that pethidine and tramadol have a similar effect on pain and analgesia requirement. The studies in this pooled analysis are sufficiently strong to make a level one recommendation that the addition of magnesium to local anaesthetics reduces the incidence of laryngospasm, a potentially lethal post-operative complication. Review level of evidence: 1.
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Affiliation(s)
- R Vlok
- Wagga Wagga Rural Referral Hospital, Wagga Wagga, NSW, Australia.,School of Medicine, Sydney, University of Notre Dame, Fremantle, NSW, Australia
| | - T M Melhuish
- Wagga Wagga Rural Referral Hospital, Wagga Wagga, NSW, Australia.,School of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - C Chong
- School of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - T Ryan
- School of Medicine, Sydney, University of Notre Dame, Fremantle, NSW, Australia
| | - Leigh D White
- Wagga Wagga Rural Referral Hospital, Wagga Wagga, NSW, Australia. .,School of Medicine, University of Wollongong, Wollongong, NSW, Australia.
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22
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Mitchell B, Chong C, Lim WK. Medication adherence 1 month after hospital discharge in medical inpatients. Intern Med J 2016; 46:185-92. [PMID: 26602319 DOI: 10.1111/imj.12965] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Revised: 09/28/2015] [Accepted: 11/06/2015] [Indexed: 12/30/2022]
Abstract
BACKGROUND The rate of medication non-adherence has been consistently reported to be between 20 and 50%. The majority of available data comes from international studies, and we hypothesised that a similar rate of adherence may be observed in Australian patients. AIMS To determine the rate of adherence to medications after discharge from acute general hospital admission and identify factors that may be associated with non-adherence. METHODS A prospective cohort study of 68 patients, comparing admission and discharge medication regimens to self-reported regimens 30-40 days after discharge from hospital. Patients were followed up via telephone call and univariate and multivariate binary logistic regression used to determine patient factors associated with non-adherence. RESULTS In all, 27 of 68 patients (39.7%) were non-adherent to one or more regular medications at follow up. Intentional and unintentional non-adherence contributed equally to non-adherence. Using multivariate analysis, presence of a carer responsible for medications was associated with significantly lower non-adherence (odds ratio (OR) 0.20 (0.05-0.83), P = 0.027) when adjusted for age, co-morbidities, chemist blister pack and total number of discharge medications. CONCLUSIONS Non-adherence to prescription medications is suboptimal and consistent with previous overseas studies. Having a carer responsible for medications is associated with significantly lower rates of non-adherence. Understanding patients' preferences and involving them in their healthcare may reduce intentional non-adherence.
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Affiliation(s)
- B Mitchell
- Department of Medicine, Gold Coast University Hospital, Gold Coast, Queensland, Australia
| | - C Chong
- Department of Aged Care, Northern Hospital, Melbourne, Victoria, Australia
| | - W K Lim
- Department of Aged Care, Northern Hospital, Melbourne, Victoria, Australia
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23
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Chong C, Liu S, Sallustio B, Chirkov Y, Horowitz J. Effects of Perhexiline on Insulin and Nitric Oxide Signalling in Diabetics. Heart Lung Circ 2016. [DOI: 10.1016/j.hlc.2016.06.200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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24
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Chong C, Kim E, Charalampidis EG, Kim H, Li F, Kevrekidis PG, Lydon J, Daraio C, Yang J. Nonlinear vibrational-state excitation and piezoelectric energy conversion in harmonically driven granular chains. Phys Rev E 2016; 93:052203. [PMID: 27300876 DOI: 10.1103/physreve.93.052203] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2015] [Indexed: 11/07/2022]
Abstract
This article explores the excitation of different vibrational states in a spatially extended dynamical system through theory and experiment. As a prototypical example, we consider a one-dimensional packing of spherical particles (a so-called granular chain) that is subject to harmonic boundary excitation. The combination of the multimodal nature of the system and the strong coupling between the particles due to the nonlinear Hertzian contact force leads to broad regions in frequency where different vibrational states are possible. In certain parametric regions, we demonstrate that the nonlinear Schrödinger equation predicts the corresponding modes fairly well. The electromechanical model we apply predicts accurately the conversion from the obtained mechanical energy to the electrical energy observed in experiments.
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Affiliation(s)
- C Chong
- Department of Mechanical and Process Engineering (D-MAVT), Swiss Federal Institute of Technology (ETH), 8092 Zürich, Switzerland.,Department of Mathematics, Bowdoin College, Brunswick, Maine 04011, USA
| | - E Kim
- Aeronautics & Astronautics, University of Washington, Seattle, Washington 98195-2400, USA.,Division of Mechanical System Engineering, Automotive Hi-Technology Research Center, Chonbuk National University, 567 Baeje-daero, deokjin-gu, Jeonju-si, Jeollabuk-do,54896, Republic of Korea
| | - E G Charalampidis
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA
| | - H Kim
- Aeronautics & Astronautics, University of Washington, Seattle, Washington 98195-2400, USA
| | - F Li
- Aeronautics & Astronautics, University of Washington, Seattle, Washington 98195-2400, USA
| | - P G Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA
| | - J Lydon
- Department of Mechanical and Process Engineering (D-MAVT), Swiss Federal Institute of Technology (ETH), 8092 Zürich, Switzerland
| | - C Daraio
- Department of Mechanical and Process Engineering (D-MAVT), Swiss Federal Institute of Technology (ETH), 8092 Zürich, Switzerland.,Division of Engineering and Applied Science, California Institute of Technology, Pasadena, California 91125, USA
| | - J Yang
- Aeronautics & Astronautics, University of Washington, Seattle, Washington 98195-2400, USA
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Yasuda H, Chong C, Charalampidis EG, Kevrekidis PG, Yang J. Formation of rarefaction waves in origami-based metamaterials. Phys Rev E 2016; 93:043004. [PMID: 27176382 DOI: 10.1103/physreve.93.043004] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2015] [Indexed: 11/07/2022]
Abstract
We investigate the nonlinear wave dynamics of origami-based metamaterials composed of Tachi-Miura polyhedron (TMP) unit cells. These cells exhibit strain softening behavior under compression, which can be tuned by modifying their geometrical configurations or initial folded conditions. We assemble these TMP cells into a cluster of origami-based metamaterials, and we theoretically model and numerically analyze their wave transmission mechanism under external impact. Numerical simulations show that origami-based metamaterials can provide a prototypical platform for the formation of nonlinear coherent structures in the form of rarefaction waves, which feature a tensile wavefront upon the application of compression to the system. We also demonstrate the existence of numerically exact traveling rarefaction waves in an effective lumped-mass model. Origami-based metamaterials can be highly useful for mitigating shock waves, potentially enabling a wide variety of engineering applications.
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Affiliation(s)
- H Yasuda
- Aeronautics & Astronautics, University of Washington, Seattle, WA 98195-2400, USA
| | - C Chong
- Department of Mechanical and Process Engineering (D-MAVT), Swiss Federal Institute of Technology (ETH), 8092 Zürich, Switzerland.,Department of Mathematics, Bowdoin College, Brunswick, Maine 04011, USA
| | - E G Charalampidis
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA
| | - P G Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA.,Center for Nonlinear Studies and Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87544, USA
| | - J Yang
- Aeronautics & Astronautics, University of Washington, Seattle, WA 98195-2400, USA
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26
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Gogna A, Chong C, Irani F, Tay K, Lo R, Chan S, Damodharan K, Kumar N, Patel A, Tan S, Siew Ping C, Tan B. Randomized controlled trial comparing standard balloon angioplasty, placement of drug-eluting stent versus stent graft for the treatment of cephalic arch stenosis in patients with hemodialysis access stenoses. J Vasc Interv Radiol 2016. [DOI: 10.1016/j.jvir.2015.12.366] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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27
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Chong C, Kevrekidis PG, Ablowitz MJ, Ma YP. Conical wave propagation and diffraction in two-dimensional hexagonally packed granular lattices. Phys Rev E 2016; 93:012909. [PMID: 26871145 DOI: 10.1103/physreve.93.012909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2015] [Indexed: 06/05/2023]
Abstract
Linear and nonlinear mechanisms for conical wave propagation in two-dimensional lattices are explored in the realm of phononic crystals. As a prototypical example, a statically compressed granular lattice of spherical particles arranged in a hexagonal packing configuration is analyzed. Upon identifying the dispersion relation of the underlying linear problem, the resulting diffraction properties are considered. Analysis both via a heuristic argument for the linear propagation of a wave packet and via asymptotic analysis leading to the derivation of a Dirac system suggests the occurrence of conical diffraction. This analysis is valid for strong precompression, i.e., near the linear regime. For weak precompression, conical wave propagation is still possible, but the resulting expanding circular wave front is of a nonoscillatory nature, resulting from the complex interplay among the discreteness, nonlinearity, and geometry of the packing. The transition between these two types of propagation is explored.
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Affiliation(s)
- C Chong
- Department of Mechanical and Process Engineering (D-MAVT), ETH-Zurich, 8092 Zurich, Switzerland
- Department of Mathematics, Bowdoin College, Brunswick, Maine 04011, USA
| | - P G Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA
| | - M J Ablowitz
- Department of Applied Mathematics, University of Colorado, 526 UCB, Boulder, Colorado 80309-0526, USA
| | - Yi-Ping Ma
- Department of Applied Mathematics, University of Colorado, 526 UCB, Boulder, Colorado 80309-0526, USA
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28
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Kim E, Li F, Chong C, Theocharis G, Yang J, Kevrekidis PG. Highly nonlinear wave propagation in elastic woodpile periodic structures. Phys Rev Lett 2015; 114:118002. [PMID: 25839312 DOI: 10.1103/physrevlett.114.118002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2014] [Indexed: 06/04/2023]
Abstract
In the present work, we experimentally implement, numerically compute with, and theoretically analyze a configuration in the form of a single column woodpile periodic structure. Our main finding is that a Hertzian, locally resonant, woodpile lattice offers a test bed for the formation of genuinely traveling waves composed of a strongly localized solitary wave on top of a small amplitude oscillatory tail. This type of wave, called a nanopteron, is not only motivated theoretically and numerically, but is also visualized experimentally by means of a laser Doppler vibrometer. This system can also be useful for manipulating stress waves at will, for example, to achieve strong attenuation and modulation of high-amplitude impacts without relying on damping in the system.
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Affiliation(s)
- E Kim
- Aeronautics and Astronautics, University of Washington, Seattle, Washington 98195-2400, USA
| | - F Li
- Aeronautics and Astronautics, University of Washington, Seattle, Washington 98195-2400, USA
| | - C Chong
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA
| | - G Theocharis
- Laboratoire d' Acoustique de l' Université du Maine, UMR-CNRS, 6613 Avenue Olivier Messiaen, 72085 Le Mans, France
| | - J Yang
- Aeronautics and Astronautics, University of Washington, Seattle, Washington 98195-2400, USA
| | - P G Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA
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29
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Li F, Chong C, Yang J, Kevrekidis PG, Daraio C. Wave transmission in time- and space-variant helicoidal phononic crystals. Phys Rev E Stat Nonlin Soft Matter Phys 2014; 90:053201. [PMID: 25493894 DOI: 10.1103/physreve.90.053201] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2014] [Indexed: 06/04/2023]
Abstract
We present a dynamically tunable mechanism of wave transmission in one-dimensional helicoidal phononic crystals in a shape similar to DNA structures. These helicoidal architectures allow slanted nonlinear contact among cylindrical constituents, and the relative torsional movements can dynamically tune the contact stiffness between neighboring cylinders. This results in cross-talking between in-plane torsional and out-of-plane longitudinal waves. We numerically demonstrate their versatile wave mixing and controllable dispersion behavior in both wavenumber and frequency domains. Based on this principle, a suggestion toward an acoustic configuration bearing parallels to a transistor is further proposed, in which longitudinal waves can be switched on and off through torsional waves.
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Affiliation(s)
- F Li
- Aeronautics and Astronautics, University of Washington, Seattle, Washington 98195-2400, USA
| | - C Chong
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA and Department of Mechanical and Process Engineering (D-MAVT), Swiss Federal Institute of Technology (ETH), 8092 Zurich, Switzerland
| | - J Yang
- Aeronautics and Astronautics, University of Washington, Seattle, Washington 98195-2400, USA
| | - P G Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA
| | - C Daraio
- Department of Mechanical and Process Engineering (D-MAVT), Swiss Federal Institute of Technology (ETH), 8092 Zurich, Switzerland and Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125, USA
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Abstract
This study describes the dynamic response of a two-dimensional hexagonal packing of uncompressed stainless steel spheres excited by localized impulsive loadings. The dynamics of the system are modeled using the Hertzian normal contact law. After the initial impact strikes the system, a characteristic wave structure emerges and continuously decays as it propagates through the lattice. Using an extension of the binary collision approximation for one-dimensional chains, we predict its decay rate, which compares well with numerical simulations and experimental data. While the hexagonal lattice does not support constant speed traveling waves, we provide scaling relations that characterize the directional power law decay of the wave velocity for various angles of impact. Lastly, we discuss the effects of weak disorder on the directional amplitude decay rates.
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Affiliation(s)
- A. Leonard
- Department of Civil and Mechanical Engineering, California Institute of Technology, Pasadena, CA 91125 USA
| | - C. Chong
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA 01003-4515 USA
| | - P. G. Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA 01003-4515 USA
| | - C. Daraio
- Department of Mechanical and Process Engineering (D-MAVT), ETH-Zurich, 8092 Zurich, Switzerland
- Department of Aerospace Engineering (GALCIT), California Institute of Technology, Pasadena, CA 91125 USA
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31
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Chong C, Li F, Yang J, Williams MO, Kevrekidis IG, Kevrekidis PG, Daraio C. Damped-driven granular chains: an ideal playground for dark breathers and multibreathers. Phys Rev E Stat Nonlin Soft Matter Phys 2014; 89:032924. [PMID: 24730930 DOI: 10.1103/physreve.89.032924] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2013] [Indexed: 06/03/2023]
Abstract
By applying an out-of-phase actuation at the boundaries of a uniform chain of granular particles, we demonstrate experimentally that time-periodic and spatially localized structures with a nonzero background (so-called dark breathers) emerge for a wide range of parameter values and initial conditions. We demonstrate a remarkable control over the number of breathers within the multibreather pattern that can be "dialed in" by varying the frequency or amplitude of the actuation. The values of the frequency (or amplitude) where the transition between different multibreather states occurs are predicted accurately by the proposed theoretical model, which is numerically shown to support exact dark breather and multibreather solutions. Moreover, we visualize detailed temporal and spatial profiles of breathers and, especially, of multibreathers using a full-field probing technology and enable a systematic favorable comparison among theory, computation, and experiments. A detailed bifurcation analysis reveals that the dark and multibreather families are connected in a "snaking" pattern, providing a roadmap for the identification of such fundamental states and their bistability in the laboratory.
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Affiliation(s)
- C Chong
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA
| | - F Li
- Graduate Aerospace Laboratories (GALCIT), California Institute of Technology, Pasadena, California 91125, USA
| | - J Yang
- Aeronautics and Astronautics, University of Washington, Seattle, Washington 98195-2400, USA
| | - M O Williams
- Department of Chemical and Biological Engineering and PACM, Princeton University, Princeton, New Jersey 08544, USA
| | - I G Kevrekidis
- Department of Chemical and Biological Engineering and PACM, Princeton University, Princeton, New Jersey 08544, USA
| | - P G Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA
| | - C Daraio
- Graduate Aerospace Laboratories (GALCIT), California Institute of Technology, Pasadena, California 91125, USA and Department of Mechanical and Process Engineering (D-MAVT), Swiss Federal Institute of Technology (ETH), 8092 Zurich, Switzerland
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Nikolaenko L, Jia Y, Wang C, Diaz-Arjonilla M, Yee JK, French SW, Liu PY, Laurel S, Chong C, Lee K, Lue Y, Lee WNP, Swerdloff RS. Testosterone replacement ameliorates nonalcoholic fatty liver disease in castrated male rats. Endocrinology 2014; 155:417-28. [PMID: 24280056 PMCID: PMC5393315 DOI: 10.1210/en.2013-1648] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Nonalcoholic fatty liver disease is common in developed countries and is associated with obesity, metabolic syndrome, and type 2 diabetes. T deficiency is a risk factor for developing these metabolic deficiencies, but its role in hepatic steatosis has not been well studied. We investigated the effects of T on the pathogenesis of hepatic steatosis in rats fed a high-fat diet (HFD). Adult male rats were randomly placed into four groups and treated for 15 weeks: intact rats on regular chow diet (RCD), intact rats on liquid HFD (I+HFD), castrated rats on HFD (C+HFD), and castrated rats with T replacement on HFD (C+HFD+T). Fat contributed 71% energy to the HFD but only 16% of energy to the RCD. Serum T level was undetectable in castrated rats, and T replacement led to 2-fold higher mean serum T levels than in intact rats. C+HFD rats gained less weight but had higher percentage body fat than C+HFD+T. Severe micro- and macrovesicular fat accumulated in hepatocytes with multiple inflammatory foci in the livers of C+HFD. I+HFD and C+HFD+T hepatocytes demonstrated only mild to moderate microvesicular steatosis. T replacement attenuated HFD-induced hepatocyte apoptosis in castrated rats. Serum glucose and insulin levels were not increased with HFD in any group. Immunoblots showed that insulin-regulated proteins were not changed in any group. This study demonstrates that T deficiency may contribute to the severity of hepatic steatosis and T may play a protective role in hepatic steatosis and nonalcoholic fatty liver disease development without insulin resistance.
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Affiliation(s)
- L Nikolaenko
- Divisions of Endocrinology, Departments of Medicine (L.N., Y.J., C.W., M.D.-A., P.Y.L., S.L., C.C., K.L., Y.L., R.S.S.) and Pediatrics (J.K.Y., W.N.P.L.), and Department of Pathology (S.W.F.) Harbor-UCLA Medical Center and Los Angeles Biomedical Research Institute, Torrance, California 90509
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Chong C, Kevrekidis PG, Theocharis G, Daraio C. Dark breathers in granular crystals. Phys Rev E Stat Nonlin Soft Matter Phys 2013; 87:042202. [PMID: 23679402 DOI: 10.1103/physreve.87.042202] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2012] [Indexed: 06/02/2023]
Abstract
We present a study of the existence, stability, and bifurcation structure of families of dark breathers in a one-dimensional uniform chain of spherical beads under static load. A defocusing nonlinear Schrödinger equation (NLS) is derived for frequencies that are close to the edge of the phonon band and is used to construct targeted initial conditions for numerical computations. Salient features of the system include the existence of large amplitude solutions that emerge from the small amplitude solutions described by the NLS equation, and the presence of a nonlinear instability that, to the best of the authors' knowledge, has not been observed in classical Fermi-Pasta-Ulam lattices. Finally, it is also demonstrated that these dark breathers can be detected in a physically realistic experimental settings by merely actuating the ends of an initially at rest chain of beads and inducing destructive interference between their signals.
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Affiliation(s)
- C Chong
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-9305, USA.
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Nguyen T, Neil C, Chong C, Singh K, Heresztyn T, Chirkov Y, Horowitz J. Can Recurrence of Takotsubo Cardiomyopathy be Predicted? Heart Lung Circ 2013. [DOI: 10.1016/j.hlc.2013.05.170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Chong C, Fong L, Lai R, Lau WKO, Hartmann M, Chia SE. Erratum: The prevalence of lower urinary tract symptoms and treatment-seeking behaviour in males over 40 years in Singapore: a community-based study. Prostate Cancer Prostatic Dis 2012. [DOI: 10.1038/pcan.2012.11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Rao K, Tan Z, Chong C. 93 The Use of Pulse Oximetry as a Quick Screening Tool for Limb Ischemia in the Emergency Department. Ann Emerg Med 2011. [DOI: 10.1016/j.annemergmed.2011.06.119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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Abstract
OBJECTIVES To determine the association between post-operative troponin rises and longer term (2-year) mortality after emergency orthopaedic surgery in patients over 60 years of age. METHODS One hundred and two patients were recruited in 2006 and had inpatient troponin 1 measurements. These patients were followed up by a telephone call annually for complications. RESULTS At 2 years, 29.4% (30/102) of patients had died. Twenty-five patients (25/54 or 49.3%) with a troponin rise were dead at 2 years compared with five patients without a troponin rise (5/48 or 10.4%), which was significantly different P < 0.0001. Patients with a higher troponin level (>0.1 µg/L) were more likely to be dead at 2 years compared with those with a lower level of troponin. However, when adjusted for other comorbidities the association between troponin elevation and death at 2 years did not persist. Using Cox regression multivariate analysis, only one factor, sustaining an in-hospital cardiac event odds ratio 4.3 (95% confidence interval 1.8-10.3, P = 0.001), was associated with 2 years all-cause mortality . Furthermore, patients who sustained a symptomatic troponin rise (P < 0.0001) or asymptomatic troponin rise (P = 0.004) were more likely to have died at 2 years compared with those with no troponin rise. Three factors were significantly associated with a cardiac event during the second year: (i) post-operative troponin rise (P = 0.05); (ii) pre-morbid atrial fibrillation (P = 0.04); and (iii) post-operative renal failure (P < 0.001). CONCLUSION Elevated post-operative troponin levels are predictive of 1-year but not 2-year mortality in older patients undergoing emergency orthopaedic surgery.
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Affiliation(s)
- C Chong
- Department of Aged Care, The Northern Hospital, Epping, Victoria, Australia.
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Linares J, Gindulescu A, Rotaru A, Paez M, Chong C, Nasser J. Monte Carlo for spin crossover compounds. EPJ Web of Conferences 2011. [DOI: 10.1051/epjconf/20111402004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Berry DP, Garcea G, Vanderzon P, Slimani E, Chong C, Dennison AR, Maddern GJ. Augmenting the Ablative Effect of Liver Electrolysis: Using Two Electrodes and the Pringle Maneuver. J INVEST SURG 2009; 17:105-12. [PMID: 15204717 DOI: 10.1080/08941930490422546] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Several methods of liver tumor ablation have been investigated, and these include the novel technique of electrolysis. Electrolysis is slower than other forms of ablative therapy. This study determined methods of increasing the ablative effect of electrolysis. Domestic white pigs were divided. One group received electrolysis using two electrode catheters, and in the other group a concurrent intermittent Pringle maneuver was performed to induce intermittent ischemia. The effect of two electrode catheters versus a single electrode catheter was compared, and the effect of the Pringle maneuver versus no Pringle was examined with two electrode catheters. The livers were harvested, and the volume of each lesion was calculated. There was a linear relationship between the volume of hepatic necrosis and the electrolytic dose in (p <.005) in both the single-electrode-catheter and two-electrode-catheter groups. Comparison between the single- and multiple-electrode groups showed a highly significant difference in the dose response (p <.0000002) when more than one electrode was used. Use of the Pringle maneuver during electrolysis produced larger volumes of hepatic necrosis over all doses when using two electrode catheters. Rates of necrosis were 3.8 cm(3)/100 C for a single electrode catheter, 5.46 cm(3)/100 C for two electrode catheters without Pringle, and 6.17 cm(3)/100 C for electrolysis with two electrode catheters coupled with intermittent Pringle maneuver. Thus, electrolysis was both reliable and predictable in producing hepatic necrosis in a dose-dependent manner. The time delay in achieving tumor ablation via electrolysis can be overcome by using two electrodes combined with the Pringle maneuver to increase the volume of the lesion produced.
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Affiliation(s)
- D P Berry
- Hepatobiliary Unit, Leicester General Hospital, Leicester, United Kingdom
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40
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Lee J, Chong C, Seah J, Tan S. 0221 Locally advanced breast cancer in Asian women. Breast 2009. [DOI: 10.1016/s0960-9776(09)70238-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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41
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Chong C, Purvis P, Lumis G, Holbein BE, Voroney RP, Zhou H, Liu HW, Alam MZ. Using mushroom farm and anaerobic digestion wastewaters as supplemental fertilizer sources for growing container nursery stock in a closed system. Bioresour Technol 2008; 99:2050-60. [PMID: 17481890 DOI: 10.1016/j.biortech.2007.02.047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2006] [Revised: 02/12/2007] [Accepted: 02/12/2007] [Indexed: 05/15/2023]
Abstract
Wastewaters from farm and composting operations are often rich in select nutrients that potentially can be reutilized in crop production. Liners of silverleaf dogwood (Cornus alba L. 'Argenteo-marginata'), common ninebark [Physocarpus opulifolius (L.) Maxim.], and Anthony Waterer spirea (Spiraeaxbumalda Burvénich 'Anthony Waterer') were grown in 6L containers filled with a bark-based commercial mix. Plants were fertigated daily via a computer-controlled multi-fertilizer injector with three recirculated fertilizer treatments: (1) a stock (control) solution with complete macro- and micro-nutrients, electrical conductivity (EC) 2.2 dS m(-1); (2) wastewater from a mushroom farm; and (3) process wastewater from anaerobic digestion of municipal solid waste. The wastewaters used in both treatments 2 and 3 were diluted with tap water, and the computer was programmed to amend, dispense and recirculate nutrients based on the same target EC as in treatment 1. For comparison, there was a traditional controlled-release fertilizer treatment [Nutryon 17-5-12 (17N-2P-10K) plus micro-nutrients topdressed at a rate of 39 g/plant, nutrients not recirculated]. All three species responded similarly to the three recirculated fertilizer treatments. Growth with the recirculated treatments was similar and significantly higher than that obtained with controlled-release fertilizer. Throughout the study, the EC measured in wastewater-derived nutrient solutions, and also in the container substrate, were similar or close to those of the control treatment, although there were small to large differences among individual major nutrients. There was no sign of nutrient deficiency or toxicity symptoms to the plants. Small to moderate excesses in concentrations of SO(4), Na, and/or Cl were physiologically tolerable to the species.
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Affiliation(s)
- C Chong
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada.
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43
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Abstract
Severe Acute Respiratory Syndrome (SARS) is a highly infectious disease caused by a coronavirus. Screening to detect potential SARS-infected subjects with elevated body temperature plays an important role in preventing the spread of SARS. Thermography is being used with ANN/AI to analyse the data collected from the designated SARS hospital in Singapore, and conclusive results are drawn. The current work evaluates the correlations (and classifications) between facial skin temperatures, including eye range and forehead, to aural temperature using a neural network (NN) approach, namely training backpropagation (BP) and Kohonen self-organizing map (SOM), to confirm the suitability of thermal imagers for human temperature screening. Both BP and SOM can form an opinion about the type of network that is better able to complement thermogram technology in fever diagnosis. This can produce better parameters for reducing the size of the NN classifier, while maintaining good classification accuracy. We observe that BP performs better than SOM NN. Confusion matrix (CM), an alternative display instrument, is able to process a high volume of input data and show the clustered output rapidly and accurately. The current research application will remain an interesting and useful reference for both local and overseas manufacturers of thermal scanners, users and various government and private establishments. As the elevation of body temperature is a common presenting symptom for many illnesses, including infectious diseases such as SARS, thermal imagers are useful and essential tools for mass screening of body temperature. This is true not only for SARS but also during other public health crises where widespread transmission of infection such as the danger of avian flu pandemic is a concern, in particular at places like hospitals and cross-border checkpoints.
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Affiliation(s)
- E Y K Ng
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore.
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Chen J, Chong C, Hsieh W, Fu D, Lemas V, Liu JO, Ambinder RF. Screening a library of FDA-approved drugs identifies agents that induce lytic viral infection in EBV-associated tumors. J Clin Oncol 2006. [DOI: 10.1200/jco.2006.24.18_suppl.2002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
2002 Background: Epstein-Barr virus (EBV) is associated with a variety of tumors including AIDS lymphoma, Burkitt’s lymphoma, nasopharyngeal carcinoma and Hodgkin’s lymphoma. We hypothesized that drugs used in practice might alter viral gene expression in tumor cells in ways that might be important to understand. For example induction of lytic viral gene expression leads to expression of immunodominant CD8 T cell antigens and expression of the viral thymidine kinase (which phosphorylates ganciclovir and other nucleotide analogues). Methods: A library of FDA-approved drugs that includes 2720 agents was screened to identify those that upregulated EBV lytic gene expression. The screen involved a Burkitt’s cell line with a recombinant GFP-EBV that assayed the impact of agents on replication of the complete viral genome, and assay of a lytic promoter reporter construct. Results: The assay identified 146 agents in the whole virus replication assay, 195 agents in the promoter assay, and 54 agents that were active in both assays. Agents with activity could be grouped into 4 families: anti-tubulin drugs, glucocorticoid and other steroid hormones, DNA damaging agents and nucleotide analogues (including cytarabine and gemcitabine), and the proteasome inhibitor bortezomib. Anti-tubulin drugs and nucleotide analogues were less active in thes whole virus assay than the promoter assay whereas bortezomib showed similar activity in both assays. Followup studies confirmed that bortezomib is a potent viral lytic activator that increases expression of the viral thymidine kinase and virion production in several different Burkitt’s lymphoma and primary effusion lymphoma cell lines. Although bortezomib decreases NFKB levels, in vitro investigations with an IKB repressor suggests that inhibition of NFKB alone does not account for lytic activation. Conclusions: Many cancer chemotherapeutic agents are upregulators of EBV lytic expression. Bortezomib is among the most potent. As strategies for using lytic induction therapeutically evolve, these agents may have an important role to play. No significant financial relationships to disclose.
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Affiliation(s)
- J. Chen
- Johns Hopkins School of Medicine, Baltimore, MD; Johns Hopkins Singapore, Singapore, Singapore
| | - C. Chong
- Johns Hopkins School of Medicine, Baltimore, MD; Johns Hopkins Singapore, Singapore, Singapore
| | - W. Hsieh
- Johns Hopkins School of Medicine, Baltimore, MD; Johns Hopkins Singapore, Singapore, Singapore
| | - D. Fu
- Johns Hopkins School of Medicine, Baltimore, MD; Johns Hopkins Singapore, Singapore, Singapore
| | - V. Lemas
- Johns Hopkins School of Medicine, Baltimore, MD; Johns Hopkins Singapore, Singapore, Singapore
| | - J. O. Liu
- Johns Hopkins School of Medicine, Baltimore, MD; Johns Hopkins Singapore, Singapore, Singapore
| | - R. F. Ambinder
- Johns Hopkins School of Medicine, Baltimore, MD; Johns Hopkins Singapore, Singapore, Singapore
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45
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Affiliation(s)
- B L Tan
- Division of Obstetrics and Gynaecology, KK Women's and Children's Hospital, Singapore.
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Abstract
Ninety-seven elderly patients with stable angina were included in a 28-week, randomized, double-blind, parallel-group comparison of amlodipine 5-10 mg and isosorbide mononitrate 25-50 mg once daily. The total exercise time, as limited by angina, was recorded together with the median incidence per week of angina attacks and glyceryl trinitrate consumption. Safety was assessed by adverse event frequency, measurement of vital signs and laboratory parameters, and quality of life. At the final visit, the total exercise time was significantly greater relative to baseline with amlodipine than isosorbide mononitrate (final/baseline difference: 112.2 vs. 32.2, p = 0.016). There were no statistically significant differences between the groups in relation to the incidence of adverse events. Once daily amlodipine provides significantly better control of stable angina than isosorbide mononitrate in this elderly population.
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Affiliation(s)
- R Hall
- Department of Cardiology, Hammersmith Hospital, London, UK.
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Suzuki S, Sakata K, Gonndou G, Kanno H, Miyahara K, Chong C, Yamamoto I. [Successful treatment of a patient with low pressure syndrome associated with gait disturbance]. No Shinkei Geka 2001; 29:843-9. [PMID: 11596468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/21/2023]
Abstract
The authors report an unusual case of low intracranial pressure (ICP) syndrome that was successfully treated by the placement of an anti-siphon device (ASD). This 36-year-old male had suffered suprasellar germinoma with hydrocephalus and had had a V-P shunt following radiotherapy. Sixteen years later he developed gait disturbance and somnolence and MRI demonstrated a small lateral ventricle as well as a diffuse dural enhancement. A lumbar tap revealed a low ICP of 12 mmH2O. Because of this, an ASD was placed in the patient. Postoperatively, his symptoms of gait and consciousness disturbance improved. Typical clinical findings of low ICP syndrome such as headache were not observed in this case. To our knowledge, no symptom of gait disturbance with low ICP has been reported previously. We present an interesting case of low ICP syndrome with gait disturbance and discuss the mechanism of the symptoms. Symptoms of this patient were due at first to brain ischemia. After convulsion and consciousness disturbance due to low intracranial pressure, the symptoms increased in strength until gait disturbance occurred. The possibility is suggested that gait disturbance in this patient was due both to brain ischemia and low intracranial pressure.
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Affiliation(s)
- S Suzuki
- Department of Neurosurgery, Yokohama City University School of Medicine, 3-9 Fukuura, Kanazaw-ku, Yokohama-city, Kanagawa 236-0004, Japan
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Gandhi NS, Jizhang C, Khoshnood K, Fuying X, Shanwen L, Yaoruo L, Bin Z, Haechou X, Chongjin T, Yan W, Wensen W, Dungxing H, Chong C, Shuhua X, Hawdon JM, Hotez PJ. Epidemiology of Necator americanus hookworm infections in Xiulongkan Village, Hainan Province, China: high prevalence and intensity among middle-aged and elderly residents. J Parasitol 2001; 87:739-43. [PMID: 11534635 DOI: 10.1645/0022-3395(2001)087[0739:eonahi]2.0.co;2] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Hookworm is highly endemic to Hainan Province, an island located in the South China Sea. To investigate the prevalence and intensity of infection in the area, the village of Xiulongkan was surveyed between April and July 1998. A cross-sectional study was conducted in which fecal samples of 80% of the village residents (631 individuals) were tested for the presence of helminth eggs. Hookworm was the predominant intestinal helminth in Xiulongkan, where it was determined that 60% of those tested were infected. Necator americanus was the predominant species of hookworm in this population. The prevalence of hookworm increased with age, and then leveled to a plateau for ages 41 yr and up. This observation was in contrast to infections with Ascaris lumbricoides, where the highest prevalences occurred among school-aged children. Women had a significantly higher prevalence of hookworm than men and this difference emerged in early adulthood. The intensity of hookworm infection also significantly increased with age, with the highest intensity infections occurring among middle-aged and elderly residents. Females were more likely to have moderate or heavy infections, whereas males were more likely to have light infections. The rates of hookworm transmission are particularly high among the middle-aged and elderly residents of Xiulongkan.
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Affiliation(s)
- N S Gandhi
- Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, Connecticut 06520, USA
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Chong C, Tan L, Lim L, Manser E. The mechanism of PAK activation. Autophosphorylation events in both regulatory and kinase domains control activity. J Biol Chem 2001; 276:17347-53. [PMID: 11278486 DOI: 10.1074/jbc.m009316200] [Citation(s) in RCA: 193] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
The p21-activated kinases (PAKs), in common with many kinases, undergo multiple autophosphorylation events upon interaction with appropriate activators. The Cdc42-induced phosphorylation of PAK serves in part to dissociate the kinase from its partners PIX and Nck. Here we investigate in detail how autophosphorylation events affect the catalytic activity of PAK by altering the autophosphorylation sites in both alpha- and betaPAK. Both in vivo and in vitro analyses demonstrate that, although most phosphorylation events in the PAK N-terminal regulatory domain play no direct role in activation, a phosphorylation of alphaPAK serine 144 or betaPAK serine 139, which lie in the kinase inhibitory domain, significantly contribute to activation. By contrast, sphingosine-mediated activation is independent of this residue, indicating a different mode of activation. Thus two autophosphorylation sites direct activation while three others control association with focal complexes via PIX and Nck.
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Affiliation(s)
- C Chong
- Glaxo-IMCB Group, Institute of Molecular and Cell Biology, 30 Medical Dr., Singapore 117609
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