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Fedeli L, Benelli M, Busoni S, Belli G, Ciccarone A, Coniglio A, Esposito M, Nocetti L, Sghedoni R, Tarducci R, Altabella L, Belligotti E, Bettarini S, Betti M, Caivano R, Carnì M, Chiappiniello A, Cimolai S, Cretti F, Feliciani G, Fulcheri C, Gasperi C, Giacometti M, Levrero F, Lizio D, Maieron M, Marzi S, Mascaro L, Mazzocchi S, Meliadò G, Morzenti S, Niespolo A, Noferini L, Oberhofer N, Orsingher L, Quattrocchi M, Ricci A, Savini A, Taddeucci A, Testa C, Tortoli P, Gobbi G, Gori C, Bernardi L, Giannelli M, Mazzoni LN. Unsupervised clustering analysis-based characterization of spatial profiles of inaccuracy in apparent diffusion coefficient values with varying acquisition plan orientation and diffusion weighting gradient direction - a large multicenter phantom study. Biomed Phys Eng Express 2024; 11:015021. [PMID: 39530644 DOI: 10.1088/2057-1976/ad9156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Accepted: 11/12/2024] [Indexed: 11/16/2024]
Abstract
This large multicenter study of 37 magnetic resonance imaging scanners aimed at characterizing, for the first time, spatial profiles of inaccuracy (namely, Δ-profiles) in apparent diffusion coefficient (ADC) values with varying acquisition plan orientation and diffusion weighting gradient direction, using a statistical approach exploiting unsupervised clustering analysis. A diffusion-weighted imaging (DWI) protocol (b-value: 0-200-400-600-800-1000 s mm-2) with different combinations of acquisition plan orientation (axial/sagittal/coronal) and diffusion weighting gradient direction (anterior-posterior/left-right/feet-head) was acquired on a standard water phantom. For each acquisition setup, Δ-profiles along the 3 main orthogonal directions were characterized by fitting data with a second order polynomial function (ar2+ br + c). Moreover, for each Δ-profile, the maximum minus minimum of the fitting function (δmax) was calculated. The parametersa,b,c, andδmaxshowed some significant variations between scanner systems by different manufacturers or with different static magnetic field strengths, as well as between different acquisition/estimation setups. Unsupervised clustering analysis showed two evident clusters with significantly different values of parametera(p< 0.0001), which can be grouped by acquisition protocol/Δ-profile direction but not scanner system. The results of ∆-profiles confirm an appreciable inter-scanner variability in ADC measurement and corroborate the importance of guarantying the reliability of ADC estimations in clinical or research studies, considering for each scanner system the specific acquisition sequence in terms of acquisition plan orientation and diffusion weighting gradient direction.
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Affiliation(s)
- Luca Fedeli
- Azienda USL Toscana Centro, Department of Hospitals Network, Medical Physics Unit Prato-Pistoia, Italy
| | - Matteo Benelli
- Bioinformatics Unit, Hospital of Prato, A.U.S.L. Toscana Centro, Italy
| | - Simone Busoni
- U.O.C. Fisica Sanitaria, A.O.U. Careggi, Firenze, Italy
| | - Giacomo Belli
- U.O.C. Fisica Sanitaria, A.O.U. Careggi, Firenze, Italy
| | | | | | - Marco Esposito
- S.C. Fisica Sanitaria Firenze-Empoli, A.U.S.L. Toscana Centro, Firenze, Italy
| | - Luca Nocetti
- Servizio di Fisica Medica, A.O.U. Policlinico di Modena, Modena, Italy
| | - Roberto Sghedoni
- Fisica Medica, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | | | - Luisa Altabella
- U.O.C. Fisica Sanitaria, A.O.U. Integrata di Verona, Verona, Italy
| | - Eleonora Belligotti
- Fisica Medica e Alte Tecnologie, A.O. Ospedali Riuniti Marche Nord, Pesaro, Italy
| | | | - Margherita Betti
- Azienda USL Toscana Centro, Department of Hospitals Network, Medical Physics Unit Prato-Pistoia, Italy
| | | | - Marco Carnì
- U.O.D. Fisica Sanitaria, A.O.U. Policlinico Umberto I, Roma, Italy
| | | | - Sara Cimolai
- U.O. Fisica Sanitaria, U.L.S.S. 2 Marca Trevigiana, Treviso, Italy
| | - Fabiola Cretti
- U.S.C. Fisica Sanitaria, A.O. Papa Giovanni XXIII, Bergamo, Italy
| | - Giacomo Feliciani
- Medical Physics Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) 'Dino Amadori', Meldola, Italy
| | | | - Chiara Gasperi
- U.O.S.D. Fisica Sanitaria Arezzo, A.U.S.L. Toscana Sud Est, Arezzo, Italy
| | - Mara Giacometti
- S.O.D. Fisica Sanitaria, A.O.U. Ospedali Riuniti di Ancona, Ancona, Italy
| | - Fabrizio Levrero
- U.O. Fisica Sanitaria, Ospedale Policlinico San Martino, Genova, Italy
| | | | - Marta Maieron
- S.O.C. Fisica Sanitaria, A.S.U.I. Udine S. Maria della Misericordia, Udine, Italy
| | - Simona Marzi
- Medical Physics Laboratory, IRCCS Regina Elena National Cancer Institute, Roma, Italy
| | - Lorella Mascaro
- U.O.C. Fisica Sanitaria, A.S.S.T. Spedali Civili di Brescia, Brescia, Italy
| | - Silvia Mazzocchi
- S.C. Fisica Sanitaria Firenze-Empoli, A.U.S.L. Toscana Centro, Firenze, Italy
| | - Gabriele Meliadò
- U.O.C. Fisica Sanitaria, A.O.U. Integrata di Verona, Verona, Italy
| | | | - Alessandra Niespolo
- U.O.C. Fisica Sanitaria Area Nord, A.U.S.L. Toscana Nord Ovest, Lucca, Italy
| | | | - Nadia Oberhofer
- Servizio Aziendale di Fisica Sanitaria, A.S. dell'Alto Adige, Bolzano, Italy
| | - Laura Orsingher
- U.O.C. Fisica Sanitaria, Azienda Provinciale per i Servizi Sanitari, Trento, Italy
| | | | | | | | | | - Claudia Testa
- Dipartimento di Fisica e Astronomia, Università di Bologna, Bologna, Italy
| | - Paolo Tortoli
- U.O.C. Fisica Sanitaria, A.O.U. Careggi, Firenze, Italy
| | - Gianni Gobbi
- Università degli Studi di Perugia, Perugia, Italy
| | - Cesare Gori
- Università degli Studi di Firenze, Firenze, Italy
| | - Luca Bernardi
- Azienda USL Toscana Centro, Department of Hospitals Network, Medical Physics Unit Prato-Pistoia, Italy
| | - Marco Giannelli
- Unit of Medical Physics, Pisa University Hospital 'Azienda Ospedaliero-Universitaria Pisana', Pisa, Italy
| | - Lorenzo Nicola Mazzoni
- Azienda USL Toscana Centro, Department of Hospitals Network, Medical Physics Unit Prato-Pistoia, Italy
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2
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Abbott NL, Chauvie S, Marcu L, DeJean C, Melidis C, Wientjes R, Gasnier A, Lisbona A, Luzzara M, Mazzoni LN, O'Doherty J, Koutsouveli E, Appelt A, Hansen CR. The role of medical physics experts in clinical trials: A guideline from the European Federation of Organisations for Medical Physics. Phys Med 2024; 126:104821. [PMID: 39361978 DOI: 10.1016/j.ejmp.2024.104821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 08/26/2024] [Accepted: 09/22/2024] [Indexed: 10/05/2024] Open
Abstract
The EFOMP working group on the Role of Medical Physics Experts (MPEs) in Clinical Trials was established in 2010, with experts from across Europe and different areas of medical physics. Their main aims were: (1) To develop a consensus guidance document for the work MPEs do in clinical trials across Europe. (2) Complement the work by American colleagues in AAPM TG 113 and guidance from National Member Organisations. (3) To cover external beam radiotherapy, brachytherapy, nuclear medicine, molecular radiotherapy, and imaging. This document outlines the main output from this working group. Giving guidance to MPEs, and indeed all Medical Physicists (MP) and MP trainees wishing to work in clinical trials. It also gives guidance to the wider multidisciplinary team, advising where MPEs must legally be involved, as well as highlighting areas where MPEs skills and expertise can really add value to clinical trials.
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Affiliation(s)
- Natalie Louise Abbott
- King George V Building, St. Bartholomews Hospital, West Smithfield, London EC1A 7BE, UK; National RTTQA Group, Cardiff & London, UK.
| | - Stephane Chauvie
- Medical Physics Division, Santa Croce e Carle Hospital, Cuneo, Italy
| | - Loredana Marcu
- Faculty of Informatics and Science, University of Oradea, Oradea 410087, Romania; UniSA Allied Health & Human Performance, University of South Australia, Adelaide SA 5001, Australia
| | | | - Christos Melidis
- CAP Santé, Radiation Therapy, Clinique Maymard. Bastia, France; milliVolt.eu, a Health Physics Company. Bastia, France
| | | | - Anne Gasnier
- Department of Radiation Oncology, Henri Becquerel Cancer Centre, Rouen, France
| | - Albert Lisbona
- MP emeritus, Institut de Cancérologie de l'Ouest, Saint Herblain, France
| | | | | | - Jim O'Doherty
- Siemens Medical Solutions, Malvern, PA, United States; Radiography & Diagnostic Imaging, University College Dublin, Dublin, Ireland; Department of Radiology & Radiological Sciences, Medical University of South Carolina, Charleston, SC, United States
| | - Efi Koutsouveli
- Department of Medical Physics, Hygeia Hospital, Athens, Greece
| | - Ane Appelt
- Leeds Institution of Medical Research at St James's, University of Leeds, Leeds, UK; Department of Medical Physics, Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Christian Rønn Hansen
- Institute of Clinical Research, University of Southern Denmark, Denmark; Danish Center of Particle Therapy, Aarhus University Hospital, Denmark; Department of Oncology, Odense University Hospital, Denmark
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Radunsky D, Solomon C, Stern N, Blumenfeld-Katzir T, Filo S, Mezer A, Karsa A, Shmueli K, Soustelle L, Duhamel G, Girard OM, Kepler G, Shrot S, Hoffmann C, Ben-Eliezer N. A comprehensive protocol for quantitative magnetic resonance imaging of the brain at 3 Tesla. PLoS One 2024; 19:e0297244. [PMID: 38820354 PMCID: PMC11142522 DOI: 10.1371/journal.pone.0297244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Accepted: 01/01/2024] [Indexed: 06/02/2024] Open
Abstract
Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools. The total scan time is under 50 minutes and includes eight pulse-sequences, which produce range of quantitative maps including T1, T2, and T2* relaxation times, magnetic susceptibility, water and macromolecular tissue fractions, mean diffusivity and fractional anisotropy, magnetization transfer ratio (MTR), and inhomogeneous MTR. Practical tips and limitations of using the protocol are also provided and discussed. Application of the protocol is presented on a cohort of 28 healthy volunteers and 12 brain regions-of-interest (ROIs). Quantitative values agreed with previously reported values. Statistical analysis revealed low variability of qMRI parameters across subjects, which, compared to intra-ROI variability, was x4.1 ± 0.9 times higher on average. Significant and positive linear relationship was found between right and left hemispheres' values for all parameters and ROIs with Pearson correlation coefficients of r>0.89 (P<0.001), and mean slope of 0.95 ± 0.04. Finally, scan-rescan stability demonstrated high reproducibility of the measured parameters across ROIs and volunteers, with close-to-zero mean difference and without correlation between the mean and difference values (across map types, mean P value was 0.48 ± 0.27). The entire quantitative data and postprocessing scripts described in the manuscript are publicly available under dedicated GitHub and Figshare repositories. The quantitative maps produced by the presented protocol can promote longitudinal and multi-center studies, and improve the biological interpretability of qMRI by integrating multiple metrics that can reveal information, which is not apparent when examined using only a single contrast mechanism.
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Affiliation(s)
- Dvir Radunsky
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | - Chen Solomon
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | - Neta Stern
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | | | - Shir Filo
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Aviv Mezer
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Anita Karsa
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | | | | | | | - Gal Kepler
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- School of Neurobiology, Biochemistry and Biophysics, Faculty of Life Science, Tel Aviv University, Tel Aviv, Israel
| | - Shai Shrot
- Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel
- Department of Diagnostic Imaging, Sheba Medical Center, Ramat-Gan, Israel
| | - Chen Hoffmann
- Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel
- Department of Diagnostic Imaging, Sheba Medical Center, Ramat-Gan, Israel
| | - Noam Ben-Eliezer
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Center for Advanced Imaging Innovation and Research (CAI2R), New-York University Langone Medical Center, New York, NY, United States of America
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4
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Chauvie S, Mazzoni LN, O’Doherty J. A Review on the Use of Imaging Biomarkers in Oncology Clinical Trials: Quality Assurance Strategies for Technical Validation. Tomography 2023; 9:1876-1902. [PMID: 37888741 PMCID: PMC10610870 DOI: 10.3390/tomography9050149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 10/10/2023] [Accepted: 10/13/2023] [Indexed: 10/28/2023] Open
Abstract
Imaging biomarkers (IBs) have been proposed in medical literature that exploit images in a quantitative way, going beyond the visual assessment by an imaging physician. These IBs can be used in the diagnosis, prognosis, and response assessment of several pathologies and are very often used for patient management pathways. In this respect, IBs to be used in clinical practice and clinical trials have a requirement to be precise, accurate, and reproducible. Due to limitations in imaging technology, an error can be associated with their value when considering the entire imaging chain, from data acquisition to data reconstruction and subsequent analysis. From this point of view, the use of IBs in clinical trials requires a broadening of the concept of quality assurance and this can be a challenge for the responsible medical physics experts (MPEs). Within this manuscript, we describe the concept of an IB, examine some examples of IBs currently employed in clinical practice/clinical trials and analyze the procedure that should be carried out to achieve better accuracy and reproducibility in their use. We anticipate that this narrative review, written by the components of the EFOMP working group on "the role of the MPEs in clinical trials"-imaging sub-group, can represent a valid reference material for MPEs approaching the subject.
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Affiliation(s)
- Stephane Chauvie
- Medical Physics Division, Santa Croce e Carle Hospital, 12100 Cuneo, Italy;
| | | | - Jim O’Doherty
- Siemens Medical Solutions, Malvern, PA 19355, USA;
- Department of Radiology & Radiological Sciences, Medical University of South Carolina, Charleston, SC 20455, USA
- Radiography & Diagnostic Imaging, University College Dublin, D04 C7X2 Dublin, Ireland
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5
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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: 1.7] [Reference Citation Analysis] [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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6
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New developments in MRI: System characterization, technical advances and radiotherapy applications. Phys Med 2021; 90:50-52. [PMID: 34537500 DOI: 10.1016/j.ejmp.2021.09.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 09/03/2021] [Indexed: 11/20/2022] Open
Abstract
A Special Issue of Physica Medica - European Journal of Medical Physics, focused on some important points of contact between the world of magnetic resonance and that of medical physics, was published during 2021. This Editorial describes and comments on the content of this Focus Issue, which contains articles from leading groups invited by the Guest Editors.
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Pang Y, Malyarenko DI, Amouzandeh G, Barberi E, Cole M, Vom Endt A, Peeters J, Tan ET, Chenevert TL. Empirical validation of gradient field models for an accurate ADC measured on clinical 3T MR systems in body oncologic applications. Phys Med 2021; 86:113-120. [PMID: 34107440 PMCID: PMC8268998 DOI: 10.1016/j.ejmp.2021.05.030] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 04/28/2021] [Accepted: 05/21/2021] [Indexed: 12/20/2022] Open
Abstract
PURPOSE To empirically corroborate vendor-provided gradient nonlinearity (GNL) characteristics and demonstrate efficient GNL bias correction for human brain apparent diffusion coefficient (ADC) across 3T MR systems and spatial locations. METHODS Spatial distortion vector fields (DVF) were mapped in 3D using a surface fiducial array phantom for individual gradient channels on three 3T MR platforms from different vendors. Measured DVF were converted into empirical 3D GNL tensors and compared with their theoretical counterparts derived from vendor-provided spherical harmonic (SPH) coefficients. To illustrate spatial impact of GNL on ADC, diffusion weighted imaging using three orthogonal gradient directions was performed on a volunteer brain positioned at isocenter (as a reference) and offset superiorly by 10-17 cm (>10% predicted GNL bias). The SPH tensor-based GNL correction was applied to individual DWI gradient directions, and derived ADC was compared with low-bias reference for human brain white matter (WM) ROIs. RESULTS Empiric and predicted GNL errors were comparable for all three studied 3T MR systems, with <1.0% differences in the median and width of spatial histograms for individual GNL tensor elements. Median (±width) of ADC (10-3mm2/s) histograms measured at isocenter in WM reference ROIs from three MR systems were: 0.73 ± 0.11, 0.71 ± 0.14, 0.74 ± 0.17, and at off-isocenters (before versus after GNL correction) were respectively 0.63 ± 0.14 versus 0.72 ± 0.11, 0.53 ± 0.16 versus 0.74 ± 0.18, and 0.65 ± 0.16 versus 0.76 ± 0.18. CONCLUSION The phantom-based spatial distortion measurements validated vendor-provided gradient fields, and accurate WM ADC was recovered regardless of spatial locations and clinical MR platforms using system-specific tensor-based GNL correction for routine DWI.
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Affiliation(s)
- Yuxi Pang
- Radiology, University of Michigan, Ann Arbor, MI, United States.
| | | | | | - Enzo Barberi
- Modus Medical Devices Inc., London, ON, CA, Canada
| | - Michael Cole
- Modus Medical Devices Inc., London, ON, CA, Canada
| | | | | | - Ek T Tan
- Radiology and Imaging, Hospital for Special Surgery, New York, NY, United States
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8
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Fedeli L, Benelli M, Busoni S, Belli G, Ciccarone A, Coniglio A, Esposito M, Nocetti L, Sghedoni R, Tarducci R, Altabella L, Belligotti E, Bettarini S, Betti M, Caivano R, Carnì M, Chiappiniello A, Cimolai S, Cretti F, Fulcheri C, Gasperi C, Giacometti M, Levrero F, Lizio D, Maieron M, Marzi S, Mascaro L, Mazzocchi S, Meliadò G, Morzenti S, Niespolo A, Noferini L, Oberhofer N, Orsingher L, Quattrocchi M, Ricci A, Savini A, Taddeucci A, Testa C, Tortoli P, Gobbi G, Gori C, Bernardi L, Giannelli M, Mazzoni LN. On the dependence of quantitative diffusion-weighted imaging on scanner system characteristics and acquisition parameters: A large multicenter and multiparametric phantom study with unsupervised clustering analysis. Phys Med 2021; 85:98-106. [PMID: 33991807 DOI: 10.1016/j.ejmp.2021.04.020] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 03/31/2021] [Accepted: 04/23/2021] [Indexed: 11/25/2022] Open
Abstract
PURPOSE The purpose of this multicenter phantom study was to exploit an innovative approach, based on an extensive acquisition protocol and unsupervised clustering analysis, in order to assess any potential bias in apparent diffusion coefficient (ADC) estimation due to different scanner characteristics. Moreover, we aimed at assessing, for the first time, any effect of acquisition plan/phase encoding direction on ADC estimation. METHODS Water phantom acquisitions were carried out on 39 scanners. DWI acquisitions (b-value = 0-200-400-600-800-1000 s/mm2) with different acquisition plans (axial, coronal, sagittal) and phase encoding directions (anterior/posterior and right/left, for the axial acquisition plan), for 3 orthogonal diffusion weighting gradient directions, were performed. For each acquisition setup, ADC values were measured in-center and off-center (6 different positions), resulting in an entire dataset of 84 × 39 = 3276 ADC values. Spatial uniformity of ADC maps was assessed by means of the percentage difference between off-center and in-center ADC values (Δ). RESULTS No significant dependence of in-center ADC values on acquisition plan/phase encoding direction was found. Ward unsupervised clustering analysis showed 3 distinct clusters of scanners and an association between Δ-values and manufacturer/model, whereas no association between Δ-values and maximum gradient strength, slew rate or static magnetic field strength was revealed. Several acquisition setups showed significant differences among groups, indicating the introduction of different biases in ADC estimation. CONCLUSIONS Unsupervised clustering analysis of DWI data, obtained from several scanners using an extensive acquisition protocol, allows to reveal an association between measured ADC values and manufacturer/model of scanner, as well as to identify suboptimal DWI acquisition setups for accurate ADC estimation.
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Affiliation(s)
- Luca Fedeli
- S.O.C. Fisica Sanitaria Pistoia-Prato, A.U.S.L. Toscana Centro, Italy
| | - Matteo Benelli
- Bioinformatics Unit, Hospital of Prato, A.U.S.L. Toscana Centro, Italy
| | - Simone Busoni
- U.O.C. Fisica Sanitaria, A.O.U. Careggi, Firenze, Italy
| | - Giacomo Belli
- U.O.C. Fisica Sanitaria, A.O.U. Careggi, Firenze, Italy
| | | | - Angela Coniglio
- Department of Medical Physics, P.O. S. Filippo Neri, Roma, Italy
| | - Marco Esposito
- S.C. Fisica Sanitaria Firenze-Empoli, A.U.S.L. Toscana Centro, Firenze, Italy
| | - Luca Nocetti
- Servizio di Fisica Medica, A.O.U. Policlinico di Modena, Modena, Italy
| | - Roberto Sghedoni
- Fisica Medica, Azienda USL - IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | | | - Luisa Altabella
- Medical Physics Department, Hospital of Trento, APSS, Trento, Italy
| | - Eleonora Belligotti
- Fisica Medica ed Alte Tecnologie, A.O. Ospedali Riuniti Marche Nord, Pesaro, Italy
| | - Silvia Bettarini
- U.O.C. Fisica Sanitaria, A.O.U. Careggi, Firenze, Italy; Università degli Studi di Firenze, Firenze, Italy
| | - Margherita Betti
- S.O.C. Fisica Sanitaria Pistoia-Prato, A.U.S.L. Toscana Centro, Italy
| | - Rocchina Caivano
- U.O. Radioterapia Oncologica e Fisica Sanitaria, I.R.C.C.S. CROB, Rionero in Vulture (PZ), Italy
| | - Marco Carnì
- U.O.D. Fisica Sanitaria, A.O.U. Policlinico Umberto I, Roma, Italy
| | | | - Sara Cimolai
- U.O. Fisica Sanitaria, U.L.S.S. 2 Marca Trevigiana, Treviso, Italy
| | - Fabiola Cretti
- U.S.C. Fisica Sanitaria, A.O. Papa Giovanni XXIII, Bergamo, Italy
| | | | - Chiara Gasperi
- U.O.S.D. Fisica Sanitaria Arezzo, A.U.S.L. Toscana Sud Est, Arezzo, Italy
| | - Mara Giacometti
- S.O.D. Fisica Sanitaria, A.O.U. Ospedali Riuniti di Ancona, Ancona, Italy
| | - Fabrizio Levrero
- U.O. Fisica Sanitaria, Ospedale Policlinico San Martino, Genova, Italy
| | - Domenico Lizio
- Fisica Sanitaria, A.S.S.T. Grande Ospedale Metropolitano Niguarda, Milano, Italy
| | - Marta Maieron
- S.O.C. Fisica Sanitaria, A.S.U.I. Udine S. Maria della Misericordia, Udine, Italy
| | - Simona Marzi
- S.C. Laboratorio di Fisica Medica e Sistemi Esperti, Istituto Nazionale Tumori Regina Elena, Roma, Italy
| | - Lorella Mascaro
- U.O.C. Fisica Sanitaria, A.S.S.T. Spedali Civili, Brescia, Italy
| | - Silvia Mazzocchi
- S.C. Fisica Sanitaria Firenze-Empoli, A.U.S.L. Toscana Centro, Firenze, Italy
| | - Gabriele Meliadò
- U.O.C. Fisica Sanitaria, A.O.U. Integrata di Verona, Verona, Italy
| | | | - Alessandra Niespolo
- U.O.C. Fisica Sanitaria Area Nord, A.U.S.L. Toscana Nord Ovest, Lucca, Italy
| | | | - Nadia Oberhofer
- Servizio Aziendale di Fisica Sanitaria, A.S. dell'Alto Adige, Bolzano, Italy
| | - Laura Orsingher
- U.O. Fisica Sanitaria, U.L.S.S. 2 Marca Trevigiana, Treviso, Italy
| | | | | | - Alessandro Savini
- Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, Italy
| | | | - Claudia Testa
- Dipartimento di Fisica e Astronomia, Università di Bologna, Bologna, Italy
| | - Paolo Tortoli
- U.O.C. Fisica Sanitaria, A.O.U. Careggi, Firenze, Italy; Università degli Studi di Firenze, Firenze, Italy
| | - Gianni Gobbi
- Università degli Studi di Perugia, Perugia, Italy
| | - Cesare Gori
- Università degli Studi di Firenze, Firenze, Italy
| | - Luca Bernardi
- S.O.C. Fisica Sanitaria Pistoia-Prato, A.U.S.L. Toscana Centro, Italy
| | - Marco Giannelli
- Unit of Medical Physics, Pisa University Hospital "Azienda Ospedaliero-Universitaria Pisana", Pisa, Italy.
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