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Shalom ES, Kim H, van der Heijden RA, Ahmed Z, Patel R, Hormuth DA, DiCarlo JC, Yankeelov TE, Sisco NJ, Dortch RD, Stokes AM, Inglese M, Grech-Sollars M, Toschi N, Sahoo P, Singh A, Verma SK, Rathore DK, Kazerouni AS, Partridge SC, LoCastro E, Paudyal R, Wolansky IA, Shukla-Dave A, Schouten P, Gurney-Champion OJ, Jiřík R, Macíček O, Bartoš M, Vitouš J, Das AB, Kim SG, Bokacheva L, Mikheev A, Rusinek H, Berks M, Hubbard Cristinacce PL, Little RA, Cheung S, O'Connor JPB, Parker GJM, Moloney B, LaViolette PS, Bobholz S, Duenweg S, Virostko J, Laue HO, Sung K, Nabavizadeh A, Saligheh Rad H, Hu LS, Sourbron S, Bell LC, Fathi Kazerooni A. The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge. Magn Reson Med 2024; 91:1803-1821. [PMID: 38115695 DOI: 10.1002/mrm.29909] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 08/22/2023] [Accepted: 10/16/2023] [Indexed: 12/21/2023]
Abstract
PURPOSE K trans $$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools forK trans $$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardizeK trans $$ {K}^{\mathrm{trans}} $$ measurement. METHODS A framework was created to evaluateK trans $$ {K}^{\mathrm{trans}} $$ values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines forK trans $$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants'K trans $$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposedOSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. RESULTS Across the 10 received submissions, theOSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability inK trans $$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability withinK trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology.
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Affiliation(s)
- Eve S Shalom
- School of Physics and Astronomy, University of Leeds, Leeds, UK
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Harrison Kim
- Department of Radiology, University of Alabama, Birmingham, Alabama, USA
| | - Rianne A van der Heijden
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Zaki Ahmed
- Corewell Health William Beaumont University Hospital, Royal Oak, Michigan, USA
| | - Reyna Patel
- Department of Radiology, Neuroradiology Division, Mayo Clinic, Scottsdale, Arizona, USA
| | - David A Hormuth
- Oden Institute for Computational Engineering and Sciences, The University of Texas, Austin, Texas, USA
| | - Julie C DiCarlo
- Biomedical Imaging Center, Livestrong Cancer Institutes, University of Texas at Austin, Austin, Texas, USA
| | - Thomas E Yankeelov
- Departments of Biomedical Engineering, Diagnostic Medicine, Oncology, Livestrong Cancer Institutes, Oden Institute for Computational Engineering and Sciences, The University of Texas, Austin, Texas, USA
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, Texas, USA
| | - Nicholas J Sisco
- Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Richard D Dortch
- Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Ashley M Stokes
- Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Marianna Inglese
- Department of Biomedicine and Prevention, University of Rome, Tor Vergata, Italy
- Department of Surgery and Cancer, Imperial College, London, UK
| | - Matthew Grech-Sollars
- Department of Surgery and Cancer, Imperial College, London, UK
- Department of Computer Science, University College London, London, UK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome, Tor Vergata, Italy
- Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, Massachusetts, USA
| | - Prativa Sahoo
- University Medical Center Göttingen, Göttingen, Germany
| | - Anup Singh
- Center for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Sanjay K Verma
- Institute of Bioengineering and Bioimaging, Singapore, Singapore
| | - Divya K Rathore
- Institute of Psychiatry, Psychology & Neuroscience, King's College, London, UK
| | - Anum S Kazerouni
- Department of Radiology, University of Washington, Seattle, Washington, USA
| | | | - Eve LoCastro
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Ivan A Wolansky
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Pepijn Schouten
- Department of Radiology and Nuclear Medicine, University of Amsterdam, Amsterdam, The Netherlands
| | - Oliver J Gurney-Champion
- Department of Radiology and Nuclear Medicine, University of Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
| | - Radovan Jiřík
- Czech Academy of Sciences, Institute of Scientific Instruments, Brno, Czech Republic
| | - Ondřej Macíček
- Czech Academy of Sciences, Institute of Scientific Instruments, Brno, Czech Republic
| | - Michal Bartoš
- Czech Academy of Sciences, Institute of Information Theory and Automation, Praha, Czech Republic
| | - Jiří Vitouš
- Czech Academy of Sciences, Institute of Scientific Instruments, Brno, Czech Republic
| | | | - S Gene Kim
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Louisa Bokacheva
- Department of Radiology, Grossman School of Medicine, New York University, New York, New York, USA
| | - Artem Mikheev
- Department of Radiology, Grossman School of Medicine, New York University, New York, New York, USA
| | - Henry Rusinek
- Department of Radiology, Grossman School of Medicine, New York University, New York, New York, USA
| | - Michael Berks
- Division of Cancer Sciences, University of Manchester, Manchester, UK
| | | | - Ross A Little
- Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - Susan Cheung
- Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - James P B O'Connor
- Division of Cancer Sciences, University of Manchester, Manchester, UK
- Department of Radiology, The Christie Hospital NHS Trust, Manchester, UK
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK
| | - Geoff J M Parker
- Center for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- Bioxydyn Ltd, Manchester, UK
| | - Brendan Moloney
- Advanced Imaging Research Center, Oregon Health & Science Institute, Portland, Oregon, USA
| | - Peter S LaViolette
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Samuel Bobholz
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Savannah Duenweg
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - John Virostko
- Department of Diagnostic Medicine, University of Texas, Austin, Texas, USA
| | - Hendrik O Laue
- Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
| | - Kyunghyun Sung
- Department of Radiological Sciences, University of California, Los Angeles, California, USA
| | - Ali Nabavizadeh
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Center for Data-Driven Discovery, Division of Neurosurgery, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Hamidreza Saligheh Rad
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
- Center for Computational Imaging & Simulation Technologies in Biomedicine, School of Computing/School of Medicine, University of Leeds, Leeds, UK
| | - Leland S Hu
- Neuroradiology Division, Department of Radiology, Mayo Clinic, Phoenix, Arizona, USA
| | - Steven Sourbron
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Laura C Bell
- Clinical Imaging Group, Genentech, Inc., South San Francisco, California, USA
| | - Anahita Fathi Kazerooni
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, USA
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Hubbard Cristinacce PL, Markus JE, Punwani S, Mills R, Lopez MY, Grech-Sollars M, Fasano F, Waterton JC, Thrippleton MJ, Hall MG, O'Connor JPB, Francis ST, Statton B, Murphy K, So PW, Hyare H. Steps on the Path to Clinical Translation: A workshop by the British and Irish Chapter of the ISMRM. Magn Reson Med 2023. [PMID: 37222226 DOI: 10.1002/mrm.29704] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 03/24/2023] [Accepted: 04/24/2023] [Indexed: 05/25/2023]
Abstract
The British and Irish Chapter of the International Society for Magnetic Resonance in Medicine (BIC-ISMRM) held a workshop entitled "Steps on the path to clinical translation" in Cardiff, UK, on 7th September 2022. The aim of the workshop was to promote discussion within the MR community about the problems and potential solutions for translating quantitative MR (qMR) imaging and spectroscopic biomarkers into clinical application and drug studies. Invited speakers presented the perspectives of radiologists, radiographers, clinical physicists, vendors, imaging Contract/Clinical Research Organizations (CROs), open science networks, metrologists, imaging networks, and those developing consensus methods. A round-table discussion was held in which workshop participants discussed a range of questions pertinent to clinical translation of qMR imaging and spectroscopic biomarkers. Each group summarized their findings via three main conclusions and three further questions. These questions were used as the basis of an online survey of the broader UK MR community.
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Affiliation(s)
- Penny L Hubbard Cristinacce
- Quantitative Biomedical Imaging Laboratory, Division of Cancer Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Julia E Markus
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Shonit Punwani
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Rebecca Mills
- University of Oxford, Centre for Clinical Magnetic Resonance Research, The John Radcliffe Hospital, Oxford, UK
| | - Maria Yanez Lopez
- MR Physics Group, Department of Medical Physics and Clinical Engineering, Swansea Bay University Health Board, Singleton Hospital, Swansea, UK
| | - Matthew Grech-Sollars
- Department of Computer Science, University College London, London, UK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | | | - John C Waterton
- Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
- Bioxydyn Limited, Rutherford House, Manchester Science Park, Manchester, UK
| | - Michael J Thrippleton
- Edinburgh Imaging/Centre for Clinical Brain Sciences, University of Edinburgh, The Chancellor's Building, Edinburgh, UK
| | - Matt G Hall
- National Physical Laboratory, Teddington, UK
| | - James P B O'Connor
- Quantitative Biomedical Imaging Laboratory, Division of Cancer Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK
| | - Susan T Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Ben Statton
- MRC London Institute of Medical Sciences, Du Cane Road, Imperial College London, London, UK
| | - Kevin Murphy
- Cardiff University Brain Research Imaging Centre, School of Physics and Astronomy, Cardiff, UK
| | - Po-Wah So
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Harpreet Hyare
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK
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Hubbard Cristinacce PL, Keaveney S, Aboagye EO, Hall MG, Little RA, O'Connor JPB, Parker GJM, Waterton JC, Winfield JM, Jauregui-Osoro M. Clinical translation of quantitative magnetic resonance imaging biomarkers - An overview and gap analysis of current practice. Phys Med 2022; 101:165-182. [PMID: 36055125 DOI: 10.1016/j.ejmp.2022.08.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 08/05/2022] [Accepted: 08/17/2022] [Indexed: 10/14/2022] Open
Abstract
PURPOSE This overview of the current landscape of quantitative magnetic resonance imaging biomarkers (qMR IBs) aims to support the standardisation of academic IBs to assist their translation to clinical practice. METHODS We used three complementary approaches to investigate qMR IB use and quality management practices within the UK: 1) a literature search of qMR and quality management terms during 2011-2015 and 2016-2020; 2) a database search for clinical research studies using qMR IBs during 2016-2020; and 3) a survey to ascertain the current availability and quality management practices for clinical MRI scanners and associated equipment at research institutions across the UK. RESULTS The analysis showed increased use of all qMR methods between the periods 2011-2015 and 2016-2020 and diffusion-tensor MRI and volumetry to be popular methods. However, the "translation ratio" of journal articles to clinical research studies was higher for qMR methods that have evidence of clinical translation via a commercial route, such as fat fraction and T2 mapping. The number of journal articles citing quality management terms doubled between the periods 2011-2015 and 2016-2020; although, its proportion relative to all journal articles only increased by 3.0%. The survey suggested that quality assurance (QA) and quality control (QC) of data acquisition procedures are under-reported in the literature and that QA/QC of acquired data/data analysis are under-developed and lack consistency between institutions. CONCLUSIONS We summarise current attempts to standardise and translate qMR IBs, and conclude by outlining the ideal quality management practices and providing a gap analysis between current practice and a metrological standard.
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Affiliation(s)
| | - Sam Keaveney
- MRI Unit, Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, UK; Division of Radiotherapy and Imaging, The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Eric O Aboagye
- Department of Surgery & Cancer, Division of Cancer, Imperial College London, W12 0NN London, UK
| | - Matt G Hall
- National Physical Laboratory, Hampton Road, Teddington TW11 0LW, UK
| | - Ross A Little
- Division of Cancer Sciences, The University of Manchester, Manchester M13 9PT, UK
| | - James P B O'Connor
- Division of Cancer Sciences, The University of Manchester, Manchester M13 9PT, UK; Division of Radiotherapy and Imaging, The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Geoff J M Parker
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, 90 High Holborn, London WC1V 6LJ, UK; Bioxydyn Ltd, Manchester M15 6SZ, UK
| | - John C Waterton
- Bioxydyn Ltd, Manchester M15 6SZ, UK; Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester M13 9PT, UK
| | - Jessica M Winfield
- MRI Unit, Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, UK; Division of Radiotherapy and Imaging, The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Maite Jauregui-Osoro
- Department of Surgery & Cancer, Division of Cancer, Imperial College London, W12 0NN London, UK
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McHugh DJ, Lipowska‐Bhalla G, Babur M, Watson Y, Peset I, Mistry HB, Hubbard Cristinacce PL, Naish JH, Honeychurch J, Williams KJ, O'Connor JPB, Parker GJM. Diffusion model comparison identifies distinct tumor sub-regions and tracks treatment response. Magn Reson Med 2020; 84:1250-1263. [PMID: 32057115 PMCID: PMC7317874 DOI: 10.1002/mrm.28196] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 01/13/2020] [Accepted: 01/13/2020] [Indexed: 12/11/2022]
Abstract
PURPOSE MRI biomarkers of tumor response to treatment are typically obtained from parameters derived from a model applied to pre-treatment and post-treatment data. However, as tumors are spatially and temporally heterogeneous, different models may be necessary in different tumor regions, and model suitability may change over time. This work evaluates how the suitability of two diffusion-weighted (DW) MRI models varies spatially within tumors at the voxel level and in response to radiotherapy, potentially allowing inference of qualitatively different tumor microenvironments. METHODS DW-MRI data were acquired in CT26 subcutaneous allografts before and after radiotherapy. Restricted and time-independent diffusion models were compared, with regions well-described by the former hypothesized to reflect cellular tissue, and those well-described by the latter expected to reflect necrosis or oedema. Technical and biological validation of the percentage of tissue described by the restricted diffusion microstructural model (termed %MM) was performed through simulations and histological comparison. RESULTS Spatial and radiotherapy-related variation in model suitability was observed. %MM decreased from a mean of 64% at baseline to 44% 6 days post-radiotherapy in the treated group. %MM correlated negatively with the percentage of necrosis from histology, but overestimated it due to noise. Within MM regions, microstructural parameters were sensitive to radiotherapy-induced changes. CONCLUSIONS There is spatial and radiotherapy-related variation in different models' suitability for describing diffusion in tumor tissue, suggesting the presence of different and changing tumor sub-regions. The biological and technical validation of the proposed %MM cancer imaging biomarker suggests it correlates with, but overestimates, the percentage of necrosis.
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Affiliation(s)
- Damien J. McHugh
- Quantitative Biomedical Imaging LaboratoryThe University of ManchesterManchesterUK
- Division of Cancer SciencesThe University of ManchesterManchesterUK
| | - Grazyna Lipowska‐Bhalla
- Quantitative Biomedical Imaging LaboratoryThe University of ManchesterManchesterUK
- Division of Cancer SciencesThe University of ManchesterManchesterUK
| | - Muhammad Babur
- Division of Pharmacy & OptometryThe University of ManchesterManchesterUK
| | - Yvonne Watson
- Quantitative Biomedical Imaging LaboratoryThe University of ManchesterManchesterUK
| | - Isabel Peset
- Imaging and Flow CytometryCancer Research UK Manchester InstituteManchesterUK
| | - Hitesh B. Mistry
- Division of Cancer SciencesThe University of ManchesterManchesterUK
| | | | - Josephine H. Naish
- Division of Cardiovascular SciencesThe University of ManchesterManchesterUK
- Bioxydyn Ltd.ManchesterUK
| | | | - Kaye J. Williams
- Division of Pharmacy & OptometryThe University of ManchesterManchesterUK
| | - James P. B. O'Connor
- Quantitative Biomedical Imaging LaboratoryThe University of ManchesterManchesterUK
- Division of Cancer SciencesThe University of ManchesterManchesterUK
| | - Geoffrey J. M. Parker
- Bioxydyn Ltd.ManchesterUK
- Division of Neuroscience and Experimental PsychologyThe University of ManchesterManchesterUK
- Centre for Medical Image ComputingUniversity College LondonLondonUK
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Zhou FL, Wu H, McHugh DJ, Wimpenny I, Zhang X, Gough JE, Hubbard Cristinacce PL, Parker GJM. Co-electrospraying of tumour cell mimicking hollow polymeric microspheres for diffusion magnetic resonance imaging. Mater Sci Eng C Mater Biol Appl 2019; 101:217-227. [PMID: 31029314 DOI: 10.1016/j.msec.2019.03.062] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2018] [Revised: 03/08/2019] [Accepted: 03/18/2019] [Indexed: 12/31/2022]
Abstract
Diffusion magnetic resonance imaging (dMRI) is considered as a useful tool to study solid tumours. However, the interpretation of dMRI signal and validation of quantitative measurements of is challenging. One way to address these challenges is by using a standard reference material that can mimic tumour cell microstructure. There is a growing interest in using hollow polymeric microspheres, mainly prepared by multiple steps, as mimics of cells in healthy and diseased tissue. The present work reports on tumour cell-mimicking materials composed of hollow microspheres for application as a standard material in dMRI. These microspheres were prepared via one-step co-electrospraying process. The shell material was poly(d,l-lactic-co-glycolic acid) (PLGA) polymers with different molecule weights and/or ratios of glycolic acid-to-lactic, while the core was polyethylene glycol (PEG) or ethylene glycol. The resultant co-electrosprayed products were characterised by optical microscopy, scanning electron microscopy (SEM) and synchrotron X-ray micro-CT. These products were found to have variable structures and morphologies, e.g. from spherical particles with/without surface hole, through beaded fibres to smooth fibres, which mainly depend on PLGA composition and core materials. Only the shell material of PLGA polymer with ester terminated, Mw 50,000-75,000 g mol-1, and lactide:glycolide 85:15 formed hollow microspheres via the co-electrospraying process using the core material of 8 wt% PEG/chloroform as the core. A water-filled test object (or phantom) was designed and constructed from samples of the material generated from co-electrosprayed PLGA microspheres and tested on a 7 T MRI scanner. The preliminary MRI results provide evidence that hollow PLGA microspheres can restrict/hinder water diffusion as cells do in tumour tissue, implying that the phantom may be suitable for use as a quantitative validation and calibration tool for dMRI.
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Affiliation(s)
- Feng-Lei Zhou
- Division of Neuroscience and Experimental Psychology, The University of Manchester, Manchester M13 9PT, United Kingdom; The School of Materials, The University of Manchester, Manchester M13 9PL, United Kingdom.
| | - HuiHui Wu
- The School of Materials, The University of Manchester, Manchester M13 9PL, United Kingdom; Pan Tianshou Arts and Design Academy, Ningbo University, No.818, Fenghua Road, Ningbo 315200, China
| | - Damien J McHugh
- Division of Neuroscience and Experimental Psychology, The University of Manchester, Manchester M13 9PT, United Kingdom
| | - Ian Wimpenny
- Division of Neuroscience and Experimental Psychology, The University of Manchester, Manchester M13 9PT, United Kingdom; The School of Materials, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Xun Zhang
- Henry Moseley X-ray Imaging Facility, School of Materials, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Julie E Gough
- The School of Materials, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Penny L Hubbard Cristinacce
- Division of Neuroscience and Experimental Psychology, The University of Manchester, Manchester M13 9PT, United Kingdom
| | - Geoff J M Parker
- Division of Neuroscience and Experimental Psychology, The University of Manchester, Manchester M13 9PT, United Kingdom; Bioxydyn Limited, Rutherford House, Manchester Science Park, Pencroft Way, Manchester M15 6SZ, United Kingdom.
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McHugh DJ, Hubbard Cristinacce PL, Naish JH, Parker GJM. Towards a 'resolution limit' for DW-MRI tumor microstructural models: A simulation study investigating the feasibility of distinguishing between microstructural changes. Magn Reson Med 2019; 81:2288-2301. [PMID: 30338871 PMCID: PMC6492139 DOI: 10.1002/mrm.27551] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 09/03/2018] [Accepted: 09/05/2018] [Indexed: 12/14/2022]
Abstract
PURPOSE To determine the feasibility of extracting sufficiently precise estimates of cell radius, R, and intracellular volume fraction, fi , from DW-MRI data in order to distinguish between specific microstructural changes tissue may undergo, specifically focusing on cell death in tumors. METHODS Simulations with optimized and non-optimized clinical acquisitions were performed for a range of microstructures, using a two-compartment model. The ability to distinguish between (i) cell shrinkage with cell density constant, mimicking apoptosis, and (ii) cell size constant with cell density decreasing, mimicking loss of cells, was evaluated based on the precision of simulated parameter estimates. Relationships between parameter precision, SNR, and the magnitude of specific parameter changes, were used to infer SNR requirements for detecting changes. RESULTS Accuracy and precision depended on microstructural properties, SNR, and the acquisition protocol. The main benefit of optimized acquisitions tended to be improved accuracy and precision of R, particularly for small cells. In most cases considered, higher SNR was required for detecting changes in R than for changes in fi . CONCLUSIONS Given the relative changes in R and fi due to apoptosis, simulations indicate that, for a range of microstructures, detecting changes in R require higher SNR than detecting changes in fi , and that such SNR is typically not achieved in clinical data. This suggests that if apoptotic cell size decreases are to be detected in clinical settings, improved SNR is required. Comparing measurement precision with the magnitude of expected biological changes should form part of the validation process for potential biomarkers.
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Affiliation(s)
- Damien J. McHugh
- Division of Informatics, Imaging and Data SciencesThe University of ManchesterManchesterUnited Kingdom
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and ManchesterUnited Kingdom
| | | | - Josephine H. Naish
- Division of Informatics, Imaging and Data SciencesThe University of ManchesterManchesterUnited Kingdom
| | - Geoffrey J. M. Parker
- Division of Informatics, Imaging and Data SciencesThe University of ManchesterManchesterUnited Kingdom
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and ManchesterUnited Kingdom
- Bioxydyn Ltd.ManchesterUnited Kingdom
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Grech-Sollars M, Zhou FL, Waldman AD, Parker GJM, Hubbard Cristinacce PL. Stability and reproducibility of co-electrospun brain-mimicking phantoms for quality assurance of diffusion MRI sequences. Neuroimage 2018; 181:395-402. [PMID: 29936312 DOI: 10.1016/j.neuroimage.2018.06.059] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Revised: 05/23/2018] [Accepted: 06/20/2018] [Indexed: 10/28/2022] Open
Abstract
Grey and white matter mimicking phantoms are important for assessing variations in diffusion MR measures at a single time point and over an extended period of time. This work investigates the stability of brain-mimicking microfibre phantoms and reproducibility of their MR derived diffusion parameters. The microfibres were produced by co-electrospinning and characterized by scanning electron microscopy (SEM). Grey matter and white matter phantoms were constructed from random and aligned microfibres, respectively. MR data were acquired from these phantoms over a period of 33 months. SEM images revealed that only small changes in fibre microstructure occurred over 30 months. The coefficient of variation in MR measurements across all time-points was between 1.6% and 3.4% for MD across all phantoms and FA in white matter phantoms. This was within the limits expected for intra-scanner variability, thereby confirming phantom stability over 33 months. These specialised diffusion phantoms may be used in a clinical environment for intra and inter-site quality assurance purposes, and for validation of quantitative diffusion biomarkers.
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Affiliation(s)
- Matthew Grech-Sollars
- Department of Surgery and Cancer, Imperial College London, London, UK; Department of Imaging, Imperial College Healthcare NHS Trust, London, UK.
| | - Feng-Lei Zhou
- Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, UK; The School of Materials, The University of Manchester, Manchester, United Kingdom.
| | - Adam D Waldman
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK; Department of Medicine, Imperial College London, UK
| | - Geoff J M Parker
- Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, UK; Bioxydyn Limited, Manchester, UK
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8
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McHugh DJ, Zhou F, Wimpenny I, Poologasundarampillai G, Naish JH, Hubbard Cristinacce PL, Parker GJM. A biomimetic tumor tissue phantom for validating diffusion-weighted MRI measurements. Magn Reson Med 2018; 80:147-158. [PMID: 29154442 PMCID: PMC5900984 DOI: 10.1002/mrm.27016] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Revised: 09/22/2017] [Accepted: 10/27/2017] [Indexed: 12/20/2022]
Abstract
PURPOSE To develop a biomimetic tumor tissue phantom which more closely reflects water diffusion in biological tissue than previously used phantoms, and to evaluate the stability of the phantom and its potential as a tool for validating diffusion-weighted (DW) MRI measurements. METHODS Coaxial-electrospraying was used to generate micron-sized hollow polymer spheres, which mimic cells. The bulk structure was immersed in water, providing a DW-MRI phantom whose apparent diffusion coefficient (ADC) and microstructural properties were evaluated over a period of 10 months. Independent characterization of the phantom's microstructure was performed using scanning electron microscopy (SEM). The repeatability of the construction process was investigated by generating a second phantom, which underwent high resolution synchrotron-CT as well as SEM and MR scans. RESULTS ADC values were stable (coefficients of variation (CoVs) < 5%), and varied with diffusion time, with average values of 1.44 ± 0.03 µm2 /ms (Δ = 12 ms) and 1.20 ± 0.05 µm2 /ms (Δ = 45 ms). Microstructural parameters showed greater variability (CoVs up to 13%), with evidence of bias in sphere size estimates. Similar trends were observed in the second phantom. CONCLUSION A novel biomimetic phantom has been developed and shown to be stable over 10 months. It is envisaged that such phantoms will be used for further investigation of microstructural models relevant to characterizing tumor tissue, and may also find application in evaluating acquisition protocols and comparing DW-MRI-derived biomarkers obtained from different scanners at different sites. Magn Reson Med 80:147-158, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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Affiliation(s)
- Damien J. McHugh
- Division of Informatics, Imaging and Data SciencesThe University of ManchesterManchesterUK
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and ManchesterCambridge and ManchesterUK
| | - Feng‐Lei Zhou
- Division of Informatics, Imaging and Data SciencesThe University of ManchesterManchesterUK
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and ManchesterCambridge and ManchesterUK
- The School of MaterialsThe University of ManchesterManchesterUK
| | - Ian Wimpenny
- Division of Informatics, Imaging and Data SciencesThe University of ManchesterManchesterUK
- The School of MaterialsThe University of ManchesterManchesterUK
| | | | - Josephine H. Naish
- Division of Informatics, Imaging and Data SciencesThe University of ManchesterManchesterUK
| | | | - Geoffrey J. M. Parker
- Division of Informatics, Imaging and Data SciencesThe University of ManchesterManchesterUK
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and ManchesterCambridge and ManchesterUK
- Bioxydyn Ltd.ManchesterUK
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9
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Zhou FL, Li Z, Gough JE, Hubbard Cristinacce PL, Parker GJ. Axon mimicking hydrophilic hollow polycaprolactone microfibres for diffusion magnetic resonance imaging. Mater Des 2018; 137:394-403. [PMID: 29307950 PMCID: PMC5727678 DOI: 10.1016/j.matdes.2017.10.047] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Revised: 10/12/2017] [Accepted: 10/14/2017] [Indexed: 06/07/2023]
Abstract
Highly hydrophilic hollow polycaprolactone (PCL) microfibres were developed as building elements to create tissue-mimicking test objects (phantoms) for validation of diffusion magnetic resonance imaging (MRI). These microfibres were fabricated by the co-electrospinning of PCL-polysiloxane-based surfactant (PSi) mixture as shell and polyethylene oxide as core. The addition of PSi had a significant effect on the size of resultant electrospun fibres and the formation of hollow microfibres. The presence of PSi in both co-electrospun PCL microfibre surface and cross-section, revealed by X-ray energy dispersive spectroscopy (EDX), enabled water to wet these fibres completely (i.e., zero contact angle) and remained active for up to 12 months after immersing in water. PCL and PCL-PSi fibres with uniaxial orientation were constructed into water-filled phantoms. MR measurement revealed that water molecules diffuse anisotropically in the PCL-PSi phantom. Co-electrospun hollow PCL-PSi microfibres have desirable hydrophilic properties for the construction of a new generation of tissue-mimicking dMRI phantoms.
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Affiliation(s)
- Feng-Lei Zhou
- Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester M13 9PT, United Kingdom
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, UK
- The School of Materials, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Zhanxiong Li
- College of Textile and Clothing Engineering, Soochow University, Suzhou 215000, PR China
| | - Julie E. Gough
- The School of Materials, The University of Manchester, Manchester M13 9PL, United Kingdom
| | | | - Geoff J.M. Parker
- Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester M13 9PT, United Kingdom
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, UK
- Bioxydyn Limited, Rutherford House, Manchester Science Park, Pencroft Way, Manchester M15 6SZ, United Kingdom
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Zhou FL, Chirazi A, Gough JE, Hubbard Cristinacce PL, Parker GJM. Hollow Polycaprolactone Microspheres with/without a Single Surface Hole by Co-Electrospraying. Langmuir 2017; 33:13262-13271. [PMID: 28901145 PMCID: PMC5821410 DOI: 10.1021/acs.langmuir.7b01985] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Revised: 09/11/2017] [Indexed: 06/07/2023]
Abstract
We describe the co-electrospraying of hollow microspheres from a polycaprolactone (PCL) shell solution and various core solutions including water, cyclohexane, poly(ethylene oxide) (PEO), and polyethylene glycol (PEG), using different collectors. The morphologies of the resultant microspheres were characterized by scanning electron microscopy (SEM), confocal microscopy, and nano-X-ray computed tomography (nano-XCT). The core/shell solution miscibility played an important role in the co-electrospraying process and the formation of microsphere structures. Spherical particles were more likely to be produced from miscible combinations of core/shell solutions than from immiscible ones. Hollow PCL microspheres with a single hole in their surfaces were produced when an ethanol bath was used as the collector. The mechanism by which the core/shell structure is transformed into single-hole hollow microspheres is proposed to be primarily based on the evaporation through the shell and extraction by ethanol of the core solution and is described in detail. Additionally, we present a 3D macroscopic tubular structure composed of hollow PCL microspheres, directly assembled on a copper wire collector during co-electrospraying. SEM and nano-XCT confirm that microspheres in the 3D bulk structure remain hollow.
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Affiliation(s)
- Feng-Lei Zhou
- Division
of Informatics, Imaging and Data Sciences and School of Psychological Sciences, The University of Manchester, Manchester M13 9PT, United Kingdom
- The School of Materials and Henry Moseley
X-ray Imaging Facility, School
of Materials, The University of Manchester, Manchester M13 9PL, United Kingdom
- CRUK and EPSRC Cancer
Imaging Centre in Cambridge and Manchester, 27 Palatine Road, Manchester M20 3LJ, United Kingdom
| | - Ali Chirazi
- The School of Materials and Henry Moseley
X-ray Imaging Facility, School
of Materials, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Julie E. Gough
- The School of Materials and Henry Moseley
X-ray Imaging Facility, School
of Materials, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Penny L. Hubbard Cristinacce
- Division
of Informatics, Imaging and Data Sciences and School of Psychological Sciences, The University of Manchester, Manchester M13 9PT, United Kingdom
| | - Geoff J. M. Parker
- Division
of Informatics, Imaging and Data Sciences and School of Psychological Sciences, The University of Manchester, Manchester M13 9PT, United Kingdom
- Bioxydyn Limited, Rutherford
House, Manchester Science Park, Pencroft
Way, Manchester M15 6SZ, United Kingdom
- CRUK and EPSRC Cancer
Imaging Centre in Cambridge and Manchester, 27 Palatine Road, Manchester M20 3LJ, United Kingdom
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11
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Skeoch S, Hubbard Cristinacce PL, Dobbs M, Naish J, Woodhouse N, Ho M, Waterton JC, Parker GJM, Bruce IN. Evaluation of non-contrast MRI biomarkers in lupus nephritis. Clin Exp Rheumatol 2017; 35:954-958. [PMID: 28850028] [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] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 03/28/2017] [Indexed: 06/07/2023]
Abstract
OBJECTIVES To investigate the association of novel non-contrast MRI biomarkers with standard measurements of renal function and renal disease activity in lupus. METHODS A pilot study of lupus nephritis (LN) and lupus non-nephritis (LNN) patients, and healthy volunteers (HV), was undertaken. Multi-modal renal MRI was performed including sequences for arterial spin labelling (ASL) measuring blood flow, diffusion tensor imaging (DTI), measuring microstructural disruption, and effective transverse relaxation time (T2*) which is a biomarker of micro-haemorrhage. MRI measurements were compared with urinary protein creatinine ratio (uPCR) and estimated glomerular filtration rate (eGFR) measurements in the whole study population, then differences in imaging measurements between the groups were explored. RESULTS 21 patients (6 LN, 8 LNN and 7 HV) completed the study, although ASL data were not available in 4 subjects. In the whole cohort, eGFR correlated significantly with the apparent diffusion coefficient measurement from DTI in the medulla (r=0.47, p=0.03). uPCR correlated strongly with the fractional anisotropy (FA) DTI measurement in the cortex and moderately with T2* measurements (rho=-0.71, p<0.001 and rho=-0.53, p=0.013, respectively). Delayed blood flow to the medulla was found in LN subjects and there was a trend towards lower FA values in the cortex, suggesting micro-structural disruption (p=0.04 and p=0.07, respectively). CONCLUSIONS This preliminary study demonstrates that non-contrast renal MRI biomarkers are associated with standard measures of disease activity in lupus. The potential utility of these non-invasive biomarkers warrants further investigation, as there is an unmet need for reliable biomarkers of disease activity in lupus nephritis.
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Affiliation(s)
- Sarah Skeoch
- Arthritis Res. Ctr. Epidemiology, Musculoskeletal Res. & Dermatological Sciences, Academic Health Science Ctr., Univ.of Manchester; and The Kellgren Ctr. for Rheumatology, NIHR Manchester Musculoskeletal Biomed. Res. Ctr., Central Manchester Univ., UK
| | - Penny L Hubbard Cristinacce
- Centre for Imaging Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, UK
| | - Mark Dobbs
- Centre for Imaging Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, UK
| | - Josephine Naish
- Centre for Imaging Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, UK
| | - Neil Woodhouse
- Department of Radiology, Blackpool Teaching Hospitals NHS Foundation Trust, Blackpool, UK; formerly AstraZeneca R & D, Alderley Park, Macclesfield, UK
| | - Meilien Ho
- formerly AstraZeneca R & D, Alderley Park, Macclesfield, UK
| | - John C Waterton
- Centre for Imaging Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester; formerly AstraZeneca R & D, Alderley Park, Macclesfield, UK
| | - Geoff J M Parker
- Centre for Imaging Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester; and Bioxydyn Limited, Rutherford House, Pencroft Way, Manchester, UK
| | - Ian N Bruce
- Arthritis Res. Ctr. Epidemiology, Musculoskeletal Res. & Dermatological Sciences, Academic Health Science Ctr., Univ.of Manchester; and The Kellgren Ctr. for Rheumatology, NIHR Manchester Musculoskeletal Biomed. Res. Ctr., Central Manchester Univ., UK
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Zhou FL, Hubbard Cristinacce PL, Eichhorn SJ, Parker GJM. Preparation and characterization of polycaprolactone microspheres by electrospraying. Aerosol Sci Technol 2016; 50:1201-1215. [PMID: 27928195 PMCID: PMC5111097 DOI: 10.1080/02786826.2016.1234707] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2016] [Accepted: 08/22/2016] [Indexed: 05/28/2023]
Abstract
The ability to reproducibly produce and effectively collect electrosprayed polymeric microspheres with controlled morphology and size in bulk form is challenging. In this study, microparticles were produced by electrospraying polycaprolactone (PCL) of various molecular weights and solution concentrations in chloroform, and by collecting materials on different substrates. The resultant PCL microparticles were characterized by optical and electron microscopy to investigate the effect of molecular weight, solution concentration, applied voltage, working distance, and flow rate on their morphology and size. The work demonstrates the key role of a moderate molecular weight and/or solution concentration in the formation of spherical PCL particles via an electrospraying process. Increasing the applied voltage was found to produce smaller and more uniform PCL microparticles. There was a relatively low increase in the particle average size with an increase in the working distance and flow rate. Four types of substrates were adopted to collect electrosprayed PCL particles: a glass slide, aluminium foil, liquid bath, and copper wire. Unlike 2D bulk structures collected on the other substrates, a 3D tubular structure of microspheres was formed on the copper wire which could find application in the construction of 3D tumor mimics.
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Affiliation(s)
- Feng-Lei Zhou
- Centre for Imaging Sciences, The University of Manchester, Manchester, United Kingdom
- The School of Materials, The University of Manchester, Manchester, United Kingdom
| | | | - Stephen J. Eichhorn
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
| | - Geoff J. M. Parker
- Centre for Imaging Sciences, The University of Manchester, Manchester, United Kingdom
- Bioxydyn Limited, Rutherford House, Manchester Science Park, Manchester, United Kingdom
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13
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Alamidi DF, Kindvall SSI, Hubbard Cristinacce PL, McGrath DM, Young SS, Naish JH, Waterton JC, Wollmer P, Diaz S, Olsson M, Hockings PD, Lagerstrand KM, Parker GJM, Olsson LE. T1 Relaxation Time in Lungs of Asymptomatic Smokers. PLoS One 2016; 11:e0149760. [PMID: 26958856 PMCID: PMC4784914 DOI: 10.1371/journal.pone.0149760] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2015] [Accepted: 02/04/2016] [Indexed: 12/02/2022] Open
Abstract
Purpose Interest in using T1 as a potential MRI biomarker of chronic obstructive pulmonary disease (COPD) has recently increased. Since tobacco smoking is the major risk factor for development of COPD, the aim for this study was to examine whether tobacco smoking, pack-years (PY), influenced T1 of the lung parenchyma in asymptomatic current smokers. Materials and Methods Lung T1 measurements from 35 subjects, 23 never smokers and 12 current smokers were retrospectively analyzed from an institutional review board approved study. All 35 subjects underwent pulmonary function test (PFT) measurements and lung T1, with similar T1 measurement protocols. A backward linear model of T1 as a function of FEV1, FVC, weight, height, age and PY was tested. Results A significant correlation between lung T1 and PY was found with a negative slope of -3.2 ms/year (95% confidence interval [CI] [-5.8, -0.6], p = 0.02), when adjusted for age and height. Lung T1 shortens with ageing among all subjects, -4.0 ms/year (95%CI [-6.3, -1.7], p = 0.001), and among the never smokers, -3.7 ms/year (95%CI [-6.0, -1.3], p = 0.003). Conclusions A correlation between lung T1 and PY when adjusted for both age and height was found, and T1 of the lung shortens with ageing. Accordingly, PY and age can be significant confounding factors when T1 is used as a biomarker in lung MRI studies that must be taken into account to detect underlying patterns of disease.
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Affiliation(s)
- Daniel F. Alamidi
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- * E-mail:
| | - Simon S. I. Kindvall
- Department of Medical Physics, Lund University, Translational Sciences, Malmö, Sweden
| | - Penny L. Hubbard Cristinacce
- Centre for Imaging Sciences and Biomedical Imaging Institute, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, United Kingdom
| | - Deirdre M. McGrath
- Centre for Imaging Sciences and Biomedical Imaging Institute, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, United Kingdom
| | | | - Josephine H. Naish
- Centre for Imaging Sciences and Biomedical Imaging Institute, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, United Kingdom
| | - John C. Waterton
- Centre for Imaging Sciences and Biomedical Imaging Institute, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, United Kingdom
| | - Per Wollmer
- Department of Translational Medicine, Lund University, Malmö, Sweden
| | - Sandra Diaz
- Department of Translational Medicine, Lund University, Malmö, Sweden
| | | | - Paul D. Hockings
- Medtech West, Chalmers University of Technology, Gothenburg, Sweden
- Antaros Medical, BioVenture Hub, Mölndal, Sweden
| | - Kerstin M. Lagerstrand
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Geoffrey J. M. Parker
- Centre for Imaging Sciences and Biomedical Imaging Institute, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, United Kingdom
- Bioxydyn Ltd, Manchester, United Kingdom
| | - Lars E. Olsson
- Department of Medical Physics, Lund University, Translational Sciences, Malmö, Sweden
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Affiliation(s)
- Irvin Teh
- Division of Cardiovascular Medicine; Radcliffe Department of Medicine; University of Oxford; Oxford UK
| | - Feng-Lei Zhou
- Centre for Imaging Sciences, Manchester Academic Health Sciences Centre, University of Manchester; Manchester UK
- The School of Materials, University of Manchester; Manchester UK
| | - Penny L. Hubbard Cristinacce
- Centre for Imaging Sciences, Manchester Academic Health Sciences Centre, University of Manchester; Manchester UK
- Biomedical Imaging Institute; University of Manchester; Manchester UK
| | - Geoffrey J.M. Parker
- Centre for Imaging Sciences, Manchester Academic Health Sciences Centre, University of Manchester; Manchester UK
- Biomedical Imaging Institute; University of Manchester; Manchester UK
| | - Jürgen E. Schneider
- Division of Cardiovascular Medicine; Radcliffe Department of Medicine; University of Oxford; Oxford UK
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15
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Teh I, Zhou FL, Hubbard Cristinacce PL, Parker GJM, Schneider JE. Biomimetic phantom for cardiac diffusion MRI. J Magn Reson Imaging 2016; 43:594-600. [PMID: 26213152 PMCID: PMC4762200 DOI: 10.1002/jmri.25014] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Accepted: 07/06/2015] [Indexed: 11/09/2022] Open
Abstract
PURPOSE Diffusion magnetic resonance imaging (MRI) is increasingly used to characterize cardiac tissue microstructure, necessitating the use of physiologically relevant phantoms for methods development. Existing phantoms are generally simplistic and mostly simulate diffusion in the brain. Thus, there is a need for phantoms mimicking diffusion in cardiac tissue. MATERIALS AND METHODS A biomimetic phantom composed of hollow microfibers generated using co-electrospinning was developed to mimic myocardial diffusion properties and fiber and sheet orientations. Diffusion tensor imaging was carried out at monthly intervals over 4 months at 9.4T. 3D fiber tracking was performed using the phantom and compared with fiber tracking in an ex vivo rat heart. RESULTS The mean apparent diffusion coefficient and fractional anisotropy of the phantom remained stable over the 4-month period, with mean values of 7.53 ± 0.16 × 10(-4) mm(2) /s and 0.388 ± 0.007, respectively. Fiber tracking of the 1st and 3rd eigenvectors generated analogous results to the fiber and sheet-normal direction respectively, found in the left ventricular myocardium. CONCLUSION A biomimetic phantom simulating diffusion in the heart was designed and built. This could aid development and validation of novel diffusion MRI methods for investigating cardiac microstructure, decrease the number of animals and patients needed for methods development, and improve quality control in longitudinal and multicenter cardiac diffusion MRI studies.
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Affiliation(s)
- Irvin Teh
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Feng-Lei Zhou
- Centre for Imaging Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
- The School of Materials, University of Manchester, Manchester, UK
| | - Penny L Hubbard Cristinacce
- Centre for Imaging Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
- Biomedical Imaging Institute, University of Manchester, Manchester, UK
| | - Geoffrey J M Parker
- Centre for Imaging Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
- Biomedical Imaging Institute, University of Manchester, Manchester, UK
| | - Jürgen E Schneider
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
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Zhou FL, Parker GJ, Eichhorn SJ, Hubbard Cristinacce PL. Production and cross-sectional characterization of aligned co-electrospun hollow microfibrous bulk assemblies. Mater Charact 2015; 109:25-35. [PMID: 26702249 PMCID: PMC4659418 DOI: 10.1016/j.matchar.2015.09.010] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2015] [Accepted: 09/13/2015] [Indexed: 05/05/2023]
Abstract
The development of co-electrospun (co-ES) hollow microfibrous assemblies of an appreciable thickness is critical for many practical applications, including filtration membranes and tissue-mimicking scaffolds. In this study, thick uniaxially aligned hollow microfibrous assemblies forming fiber bundles and strips were prepared by co-ES of polycaprolactone (PCL) and polyethylene oxide (PEO) as shell and core materials, respectively. Hollow microfiber bundles were deposited on a fixed rotating disc, which resulted in non-controllable cross-sectional shapes on a macroscopic scale. In comparison, fiber strips were produced with tuneable thickness and width by additionally employing an x-y translation stage in co-ES. Scanning electron microscopy (SEM) images of cross-sections of fiber assemblies were analyzed to investigate the effects of production time (from 0.5 h to 12 h), core flow rate (from 0.8 mL/h to 2.0 mL/h) and/or translation speed (from 0.2 mm/s to 5 mm/s) on the pores and porosity. We observed significant changes in pore size and shape with core flow rate but the influence of production time varied; five strips produced under the same conditions had reasonably good size and porosity reproducibility; pore sizes didn't vary significantly from strip bottom to surface, although the porosity gradually decreased and then returned to the initial level.
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Affiliation(s)
- Feng-Lei Zhou
- Centre for Imaging Sciences, The University of Manchester, Manchester M13 9PT, UK
- The School of Materials, The University of Manchester, Manchester M13 9PL, UK
- CRUK-EPSRC Cancer Imaging Centre in Cambridge and Manchester, UK
| | - Geoff J.M. Parker
- Centre for Imaging Sciences, The University of Manchester, Manchester M13 9PT, UK
- CRUK-EPSRC Cancer Imaging Centre in Cambridge and Manchester, UK
| | - Stephen J. Eichhorn
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, UK
| | - Penny L. Hubbard Cristinacce
- Centre for Imaging Sciences, The University of Manchester, Manchester M13 9PT, UK
- School of Psychological Sciences, University of Manchester, Manchester M13 9PT, UK
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Alamidi DF, Morgan AR, Hubbard Cristinacce PL, Nordenmark LH, Hockings PD, Lagerstrand KM, Young SS, Naish JH, Waterton JC, Maguire NC, Olsson LE, Parker GJ. COPD Patients Have Short Lung Magnetic ResonanceT1Relaxation Time. COPD 2015; 13:153-9. [DOI: 10.3109/15412555.2015.1048851] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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Zhang WJ, Hubbard Cristinacce PL, Bondesson E, Nordenmark LH, Young SS, Liu YZ, Singh D, Naish JH, Parker GJM. MR Quantitative Equilibrium Signal Mapping: A Reliable Alternative to CT in the Assessment of Emphysema in Patients with Chronic Obstructive Pulmonary Disease. Radiology 2015; 275:579-88. [DOI: 10.1148/radiol.14132953] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Zhou FL, Hubbard Cristinacce PL, Eichhorn SJ, Parker GJM. Co-electrospun Brain Mimetic Hollow Microfibres Fibres for Diffusion Magnetic Resonance Imaging. Electrospinning for High Performance Sensors 2015. [DOI: 10.1007/978-3-319-14406-1_12] [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] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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McHugh DJ, Zhou F, Cristinacce PLH, Naish JH, Parker GJM. Ground Truth for Diffusion MRI in Cancer: A Model-Based Investigation of a Novel Tissue-Mimetic Material. Inf Process Med Imaging 2015; 24:179-90. [PMID: 26223047 DOI: 10.1007/978-3-319-19992-4_14] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/14/2023]
Abstract
This work presents preliminary results on the development, characterisation, and use of a novel physical phantom designed as a simple mimic of tumour cellular structure, for diffusion-weighted magnetic resonance imaging (DW-MRI) applications. The phantom consists of a collection of roughly spherical, micron-sized core-shell polymer 'cells', providing a system whose ground truth microstructural properties can be determined and compared with those obtained from modelling the DW-MRI signal. A two-compartment analytic model combining restricted diffusion inside a sphere with hindered extracellular diffusion was initially investigated through Monte Carlo diffusion simulations, allowing a comparison between analytic and simulated signals. The model was then fitted to DW-MRI data acquired from the phantom over a range of gradient strengths and diffusion times, yielding estimates of 'cell' size, intracellular volume fraction and the free diffusion coefficient. An initial assessment of the accuracy and precision of these estimates is provided, using independent scanning electron microscope measurements and bootstrap-style simulations. Such phantoms may be useful for testing microstructural models relevant to the characterisation of tumour tissue.
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Morgan AR, Parker GJM, Roberts C, Buonaccorsi GA, Maguire NC, Hubbard Cristinacce PL, Singh D, Vestbo J, Bjermer L, Jögi J, Taib Z, Sarv J, Bruijnzeel PLB, Olsson LE, Bondesson E, Nihlén U, McGrath DM, Young SS, Waterton JC, Nordenmark LH. Feasibility assessment of using oxygen-enhanced magnetic resonance imaging for evaluating the effect of pharmacological treatment in COPD. Eur J Radiol 2014; 83:2093-101. [PMID: 25176287 DOI: 10.1016/j.ejrad.2014.08.004] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [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: 02/27/2014] [Revised: 06/21/2014] [Accepted: 08/07/2014] [Indexed: 10/24/2022]
Abstract
OBJECTIVES Oxygen-enhanced MRI (OE-MRI) biomarkers have potential value in assessment of COPD, but need further evaluation before treatment-induced changes can be interpreted. The objective was to evaluate how OE-MRI parameters of regional ventilation and oxygen uptake respond to standard pharmacological interventions in COPD, and how the response compares to that of gold standard pulmonary function tests. MATERIALS AND METHODS COPD patients (n=40), mean FEV1 58% predicted normal, received single-dose inhaled formoterol 9μg, or placebo, followed by 8 weeks treatment bid with a combination of budesonide and formoterol Turbuhaler(®) 320/9μg or formoterol Turbuhaler(®). OE-MRI biomarkers were obtained, as well as X-ray computed tomography (CT) biomarkers and pulmonary function tests, in a two-center study. An ANCOVA statistical model was used to assess effect size of intervention measurable in OE-MRI parameters of lung function. RESULTS OE-MRI data were successfully acquired at both study sites. 8-week treatment with budesonide/formoterol significantly decreased lung wash-out time by 31% (p<0.01), decreased the change in lung oxygen level upon breathing pure oxygen by 13% (p<0.05) and increased oxygen extraction from the lung by 58% (p<0.01). Single-dose formoterol increased both lung wash-out time (+47%, p<0.05) and lung oxygenation time (+47%, p<0.05). FEV1 was improved by single-dose formoterol (+12%, p<0.001) and 8 weeks of budesonide/formoterol (+ 18%, p<0.001), consistent with published studies. CONCLUSIONS In COPD, OE-MRI parameters showed response to both single-dose bronchodilatory effects of a β2-agonist, formoterol, and 8-week treatment with an inhaled corticosteroid, budesonide, and the measurements are feasible in a small-scale multi-center trial setting.
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Affiliation(s)
- Alexandra R Morgan
- Bioxydyn Ltd, Manchester, UK; Centre for Imaging Sciences and Biomedical Imaging Institute, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.
| | - Geoff J M Parker
- Bioxydyn Ltd, Manchester, UK; Centre for Imaging Sciences and Biomedical Imaging Institute, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | - Caleb Roberts
- Bioxydyn Ltd, Manchester, UK; Centre for Imaging Sciences and Biomedical Imaging Institute, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | | | | | - Penny L Hubbard Cristinacce
- Centre for Imaging Sciences and Biomedical Imaging Institute, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | - Dave Singh
- University of Manchester, Medicines Evaluation Unit, Manchester Academic Health Sciences Centre, University Hospital of South Manchester, Manchester, UK
| | - Jørgen Vestbo
- University of Manchester, Medicines Evaluation Unit, Manchester Academic Health Sciences Centre, University Hospital of South Manchester, Manchester, UK
| | - Leif Bjermer
- Department of Respiratory Medicine & Allergology, Skåne University Hospital, Lund, Sweden
| | - Jonas Jögi
- Department of Clinical Physiology, Skåne University Hospital and Lund University, Lund, Sweden
| | | | | | | | | | | | - Ulf Nihlén
- Department of Respiratory Medicine & Allergology, Skåne University Hospital, Lund, Sweden; AstraZeneca R&D, Mölndal, Sweden
| | - Deirdre M McGrath
- Centre for Imaging Sciences and Biomedical Imaging Institute, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | | | - John C Waterton
- Centre for Imaging Sciences and Biomedical Imaging Institute, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK; AstraZeneca R&D, Alderley Park, UK
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22
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Ye AQ, Hubbard Cristinacce PL, Zhou FL, Yin Z, Parker GJ, Magin RL. Diffusion tensor MRI phantom exhibits anomalous diffusion. Annu Int Conf IEEE Eng Med Biol Soc 2014; 2014:746-9. [PMID: 25570066 PMCID: PMC4605561 DOI: 10.1109/embc.2014.6943698] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
This paper reports diffusion weighted MRI measurements of cyclohexane in a novel diffusion tensor MRI phantom composed of hollow coaxial electrospun fibers (average diameter 10.2 μm). Recent studies of the phantom demonstrated its potential as a calibration standard at low b values (less than 1000 s/mm<;sup>2<;/sup>) for mean diffusivity and fractional anisotropy. In this paper, we extend the characterization of cyclohexane diffusion in this heterogeneous, anisotropic material to high b values (up to 5000 s/mm<;sup>2<;/sup>), where the apparent diffusive motion of the cyclohexane exhibits anomalous behavior (i.e., the molecular mean squared displacement increases with time raised to the fractional power 2α/β). Diffusion tensor MRI was performed at 9.4 T using an Agilent imaging scanner and the data fit to a fractional order Mittag-Leffler (generalized exponential) decay model. Diffusion along the fibers was found to be Gaussian (2α/β=l), while diffusion across the fibers was sub-diffusive (2α/β<;l). Fiber tract reconstruction of the data was consistent with scanning electron micrograph images of the material. These studies suggest that this phantom material may be used to calibrate MR systems in both the normal (Gaussian) and anomalous diffusion regimes.
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Affiliation(s)
- Allen Q. Ye
- University of Illinois at Chicago, Chicago, IL 60607 USA
| | - Penny L. Hubbard Cristinacce
- CRUK-EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester M13 9PT, United Kingdom
| | - Feng-Lei Zhou
- CRUK-EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester M13 9PT, United Kingdom
| | - Ziying Yin
- University of Illinois at Chicago, Chicago, IL 60607 USA
| | - Geoff J.M. Parker
- CRUK-EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester M13 9PT, United Kingdom
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