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Lemainque T, Pridöhl N, Zhang S, Huppertz M, Post M, Yüksel C, Yoneyama M, Prescher A, Kuhl C, Truhn D, Nebelung S. Time-efficient combined morphologic and quantitative joint MRI: an in situ study of standardized knee cartilage defects in human cadaveric specimens. Eur Radiol Exp 2024; 8:66. [PMID: 38834751 DOI: 10.1186/s41747-024-00462-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 03/27/2024] [Indexed: 06/06/2024] Open
Abstract
BACKGROUND Quantitative techniques such as T2 and T1ρ mapping allow evaluating the cartilage and meniscus. We evaluated multi-interleaved X-prepared turbo-spin echo with intuitive relaxometry (MIXTURE) sequences with turbo spin-echo (TSE) contrast and additional parameter maps versus reference TSE sequences in an in situ model of human cartilage defects. METHODS Standardized cartilage defects of 8, 5, and 3 mm in diameter were created in the lateral femora of ten human cadaveric knee specimens (81 ± 10 years old; nine males, one female). MIXTURE sequences providing proton density-weighted fat-saturated images and T2 maps or T1-weighted images and T1ρ maps as well as the corresponding two- and three-dimensional TSE reference sequences were acquired before and after defect creation (3-T scanner; knee coil). Defect delineability, bone texture, and cartilage relaxation times were quantified. Appropriate parametric or non-parametric tests were used. RESULTS Overall, defect delineability and texture features were not significantly different between the MIXTURE and reference sequences (p ≤ 0.47). After defect creation, relaxation times significantly increased in the central femur (T2pre = 51 ± 4 ms [mean ± standard deviation] versus T2post = 56 ± 4 ms; p = 0.002) and all regions combined (T1ρpre = 40 ± 4 ms versus T1ρpost = 43 ± 4 ms; p = 0.004). CONCLUSIONS MIXTURE permitted time-efficient simultaneous morphologic and quantitative joint assessment based on clinical image contrasts. While providing T2 or T1ρ maps in clinically feasible scan time, morphologic image features, i.e., cartilage defects and bone texture, were comparable between MIXTURE and reference sequences. RELEVANCE STATEMENT Equally time-efficient and versatile, the MIXTURE sequence platform combines morphologic imaging using familiar contrasts, excellent image correspondence versus corresponding reference sequences and quantitative mapping information, thereby increasing the diagnostic value beyond mere morphology. KEY POINTS • Combined morphologic and quantitative MIXTURE sequences are based on three-dimensional TSE contrasts. • MIXTURE sequences were studied in an in situ human cartilage defect model. • Morphologic image features, i.e., defect delineabilty and bone texture, were investigated. • Morphologic image features were similar between MIXTURE and reference sequences. • MIXTURE allowed time-efficient simultaneous morphologic and quantitative knee joint assessment.
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Affiliation(s)
- Teresa Lemainque
- Department of Diagnostic and Interventional Radiology, Medical Faculty, RWTH Aachen University, Pauwelsstr. 30, Aachen, 52074, Germany.
| | - Nicola Pridöhl
- Department of Diagnostic and Interventional Radiology, Medical Faculty, RWTH Aachen University, Pauwelsstr. 30, Aachen, 52074, Germany
| | - Shuo Zhang
- Philips GmbH Market DACH, Hamburg, Germany
| | - Marc Huppertz
- Department of Diagnostic and Interventional Radiology, Medical Faculty, RWTH Aachen University, Pauwelsstr. 30, Aachen, 52074, Germany
| | - Manuel Post
- Department of Diagnostic and Interventional Radiology, Medical Faculty, RWTH Aachen University, Pauwelsstr. 30, Aachen, 52074, Germany
| | - Can Yüksel
- Department of Diagnostic and Interventional Radiology, Medical Faculty, RWTH Aachen University, Pauwelsstr. 30, Aachen, 52074, Germany
| | | | - Andreas Prescher
- Institute of Molecular and Cellular Anatomy, RWTH Aachen University, Aachen, 52074, Germany
| | - Christiane Kuhl
- Department of Diagnostic and Interventional Radiology, Medical Faculty, RWTH Aachen University, Pauwelsstr. 30, Aachen, 52074, Germany
| | - Daniel Truhn
- Department of Diagnostic and Interventional Radiology, Medical Faculty, RWTH Aachen University, Pauwelsstr. 30, Aachen, 52074, Germany
| | - Sven Nebelung
- Department of Diagnostic and Interventional Radiology, Medical Faculty, RWTH Aachen University, Pauwelsstr. 30, Aachen, 52074, Germany
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2
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Heydari A, Ahmadi A, Kim TH, Bilgic B. Joint MAPLE: Accelerated joint T 1 and T 2 * $$ {{\mathrm{T}}_2}^{\ast } $$ mapping with scan-specific self-supervised networks. Magn Reson Med 2024; 91:2294-2309. [PMID: 38181183 PMCID: PMC11007829 DOI: 10.1002/mrm.29989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 10/30/2023] [Accepted: 12/11/2023] [Indexed: 01/07/2024]
Abstract
PURPOSE Quantitative MRI finds important applications in clinical and research studies. However, it is encoding intensive and may suffer from prohibitively long scan times. Accelerated MR parameter mapping techniques have been developed to help address these challenges. Here, an accelerated joint T1,T 2 * $$ {{\mathrm{T}}_2}^{\ast } $$ , frequency and proton density mapping technique with scan-specific self-supervised network reconstruction is proposed to synergistically combine parallel imaging, model-based, and deep learning approaches to speed up parameter mapping. METHODS Proposed framework, Joint MAPLE, includes parallel imaging, signal modeling, and data consistency blocks which are optimized jointly in a combined loss function. A scan-specific self-supervised reconstruction is embedded into the framework, which takes advantage of multi-contrast data from a multi-echo, multi-flip angle, gradient echo acquisition. RESULTS In comparison with parallel reconstruction techniques powered by low-rank methods, emerging scan specific networks, and model-basedT 2 * $$ {{\mathrm{T}}_2}^{\ast } $$ estimation approaches, the proposed framework reduces the reconstruction error in parameter maps by approximately two-fold on average at acceleration rates as high as R = 16 with uniform sampling. It can outperform evaluated parallel reconstruction techniques up to four-fold on average in the presence of challenging sub-sampling masks. It is observed that Joint MAPLE performs well at extreme acceleration rates of R = 25 and R = 36 with error values less than 20%. CONCLUSION Joint MAPLE enables higher fidelity parameter estimation at high acceleration rates by synergistically combining parallel imaging and model-based parameter mapping and exploiting multi-echo, multi-flip angle datasets. Utilizing a scan-specific self-supervised reconstruction obviates the need for large data sets for training while improving the parameter estimation ability.
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Affiliation(s)
- Amir Heydari
- Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran
| | - Abbas Ahmadi
- Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran
| | - Tae Hyung Kim
- Department of Computer Engineering, Hongik University, Seoul, Korea
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Radiology, Harvard Medical School, Boston, MA, United States
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Radiology, Harvard Medical School, Boston, MA, United States
- Harvard/MIT Health Sciences and Technology, Cambridge, MA, United States
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Li H, Priest AN, Horvat-Menih I, Huang Y, Li S, Stewart GD, Mendichovszky IA, Francis ST, Gallagher FA. Fast and High-Resolution T 2 Mapping Based on Echo Merging Plus k-t Undersampling with Reduced Refocusing Flip Angles (TEMPURA) as Methods for Human Renal MRI. Magn Reson Med 2024. [PMID: 38730565 DOI: 10.1002/mrm.30115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 03/05/2024] [Accepted: 03/29/2024] [Indexed: 05/13/2024]
Abstract
PURPOSE To develop a highly accelerated multi-echo spin-echo method, TEMPURA, for reducing the acquisition time and/or increasing spatial resolution for kidney T2 mapping. METHODS TEMPURA merges several adjacent echoes into one k-space by either combining independent echoes or sharing one echo between k-spaces. The combined k-space is reconstructed based on compressed sensing theory. Reduced flip angles are used for the refocusing pulses, and the extended phase graph algorithm is used to correct the effects of indirect echoes. Two sequences were developed: a fast breath-hold sequence; and a high-resolution sequence. The performance was evaluated prospectively on a phantom, 16 healthy subjects, and two patients with different types of renal tumors. RESULTS The fast TEMPURA method reduced the acquisition time from 3-5 min to one breath-hold (18 s). Phantom measurements showed that fast TEMPURA had a mean absolute percentage error (MAPE) of 8.2%, which was comparable to a standardized respiratory-triggered sequence (7.4%), but much lower than a sequence accelerated by purely k-t undersampling (21.8%). High-resolution TEMPURA reduced the in-plane voxel size from 3 × 3 to 1 × 1 mm2, resulting in improved visualization of the detailed anatomical structure. In vivo T2 measurements demonstrated good agreement (fast: MAPE = 1.3%-2.5%; high-resolution: MAPE = 2.8%-3.3%) and high correlation coefficients (fast: R = 0.85-0.98; high-resolution: 0.82-0.96) with the standardized method, outperforming k-t undersampling alone (MAPE = 3.3-4.5%, R = 0.57-0.59). CONCLUSION TEMPURA provides fast and high-resolution renal T2 measurements. It has the potential to improve clinical throughput and delineate intratumoral heterogeneity and tissue habitats at unprecedented spatial resolution.
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Affiliation(s)
- Hao Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Andrew N Priest
- Department of Radiology, University of Cambridge, Cambridge, UK
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK
| | | | - Yuan Huang
- Department of Radiology, University of Cambridge, Cambridge, UK
- EPSRC Cambridge Mathematics of Information in Healthcare Hub, University of Cambridge, Cambridge, UK
| | - Shaohang Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Grant D Stewart
- Department of Surgery, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK
| | - Iosif A Mendichovszky
- Department of Radiology, University of Cambridge, Cambridge, UK
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK
| | - Susan T Francis
- Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, UK
| | - Ferdia A Gallagher
- Department of Radiology, University of Cambridge, Cambridge, UK
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK
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Ye Y, Xu J, Zhang Z, Zhang Y, Zhao Q, Xu J, Yuan H. Complex multi-dimensional integration for T 2* and R 2* mapping. Magn Reson Imaging 2024; 108:29-39. [PMID: 38301862 DOI: 10.1016/j.mri.2024.01.018] [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: 09/06/2023] [Revised: 01/21/2024] [Accepted: 01/29/2024] [Indexed: 02/03/2024]
Abstract
A dual Multi-Dimensional Integration (dMDI) method was proposed and demonstrated for T2* and R2* mapping. By constructing and jointly using both the original MDI term and an inversed MDI term, T2* and R2* mapping can be performed independently with intrinsic background noise suppression and spike elimination, allowing for high quantitative accuracy and robustness over a wide range of T2*. dMDI was compared to original MDI and curve fitting methods in terms of quantitative specificity, accuracy, reliability and computational efficiency. All methods were tested and compared via simulation and in vivo data. With high signal-to-noise-ratio (SNR), the proposed dMDI method yielded T2*and R2* values similar to curve fitting methods. For low SNR and background noise signals, the dMDI yielded low T2* and R2* values, thus effectively suppressing all background noise. Virtually zero spikes were observed in dMDI T2* and R2* maps in all simulation and imaging results. The dMDI method has the potential to provide improved and reliable T2* and R2* mapping results in routine and SNR-challenging scenarios.
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Affiliation(s)
- Yongquan Ye
- United Imaging Healthcare, Houston, TX, USA.
| | - Jian Xu
- United Imaging Healthcare, Houston, TX, USA
| | | | - Yan Zhang
- Beijing United Imaging Intelligent Imaging Technology Research Institute, Beijing, China
| | - Qiang Zhao
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Jiajia Xu
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, Beijing, China
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5
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Romascano D, Piredda GF, Caneschi S, Hilbert T, Corredor R, Maréchal B, Kober T, Ledoux JB, Fornari E, Hagmann P, Denervaud S. Normative volumes and relaxation times at 3T during brain development. Sci Data 2024; 11:429. [PMID: 38664431 PMCID: PMC11045735 DOI: 10.1038/s41597-024-03267-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
While research has unveiled and quantified brain markers of abnormal neurodevelopment, clinicians still work with qualitative metrics for MRI brain investigation. The purpose of the current article is to bridge the knowledge gap between case-control cohort studies and individual patient care. Here, we provide a unique dataset of seventy-three 3-to-17 years-old healthy subjects acquired with a 6-minute MRI protocol encompassing T1 and T2 relaxation quantitative sequence that can be readily implemented in the clinical setting; MP2RAGE for T1 mapping and the prototype sequence GRAPPATINI for T2 mapping. White matter and grey matter volumes were automatically quantified. We further provide normative developmental curves based on these two imaging sequences; T1, T2 and volume normative ranges with respect to age were computed, for each ROI of a pediatric brain atlas. This open-source dataset provides normative values allowing to position individual patients acquired with the same protocol on the brain maturation curve and as such provides potentially useful quantitative biomarkers facilitating precise and personalized care.
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Affiliation(s)
- David Romascano
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland.
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern, Switzerland.
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark.
| | - Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Samuele Caneschi
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Signal Processing laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Signal Processing laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Ricardo Corredor
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Signal Processing laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bénédicte Maréchal
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Signal Processing laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Signal Processing laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jean-Baptiste Ledoux
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | | | - Patric Hagmann
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
| | - Solange Denervaud
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
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6
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Campbell GJ, Sneag DB, Queler SC, Lin Y, Li Q, Tan ET. Quantitative double echo steady state T2 mapping of upper extremity peripheral nerves and muscles. Front Neurol 2024; 15:1359033. [PMID: 38426170 PMCID: PMC10902120 DOI: 10.3389/fneur.2024.1359033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 01/29/2024] [Indexed: 03/02/2024] Open
Abstract
Introduction T2 mapping can characterize peripheral neuropathy and muscle denervation due to axonal damage. Three-dimensional double echo steady-state (DESS) can simultaneously provide 3D qualitative information and T2 maps with equivalent spatial resolution. However, insufficient signal-to-noise ratio may bias DESS-T2 values. Deep learning reconstruction (DLR) techniques can reduce noise, and hence may improve quantitation of high-resolution DESS-T2. This study aims to (i) evaluate the effect of DLR methods on DESS-T2 values, and (ii) to evaluate the feasibility of using DESS-T2 maps to differentiate abnormal from normal nerves and muscles in the upper extremities, with abnormality as determined by electromyography. Methods and results Analysis of images from 25 subjects found that DLR decreased DESS-T2 values in abnormal muscles (DLR = 37.71 ± 9.11 msec, standard reconstruction = 38.56 ± 9.44 msec, p = 0.005) and normal muscles (DLR: 27.18 ± 6.34 msec, standard reconstruction: 27.58 ± 6.34 msec, p < 0.001) consistent with a noise reduction bias. Mean DESS-T2, both with and without DLR, was higher in abnormal nerves (abnormal = 75.99 ± 38.21 msec, normal = 35.10 ± 9.78 msec, p < 0.001) and muscles (abnormal = 37.71 ± 9.11 msec, normal = 27.18 ± 6.34 msec, p < 0.001). A higher DESS-T2 in muscle was associated with electromyography motor unit recruitment (p < 0.001). Discussion These results suggest that quantitative DESS-T2 is improved by DLR and can differentiate the nerves and muscles involved in peripheral neuropathies from those uninvolved.
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Affiliation(s)
- Gracyn J. Campbell
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY, United States
| | - Darryl B. Sneag
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY, United States
| | - Sophie C. Queler
- College of Medicine, Downstate Health Sciences University, Brooklyn, NY, United States
| | - Yenpo Lin
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY, United States
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Taoyuan City, Taiwan
| | - Qian Li
- Biostatistics Core, Hospital for Special Surgery, New York, NY, United States
| | - Ek T. Tan
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY, United States
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7
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Omoumi P, Mourad C, Ledoux JB, Hilbert T. Morphological assessment of cartilage and osteoarthritis in clinical practice and research: Intermediate-weighted fat-suppressed sequences and beyond. Skeletal Radiol 2023; 52:2185-2198. [PMID: 37154871 PMCID: PMC10509097 DOI: 10.1007/s00256-023-04343-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 03/28/2023] [Accepted: 04/10/2023] [Indexed: 05/10/2023]
Abstract
Magnetic resonance imaging (MRI) is widely regarded as the primary modality for the morphological assessment of cartilage and all other joint tissues involved in osteoarthritis. 2D fast spin echo fat-suppressed intermediate-weighted (FSE FS IW) sequences with a TE between 30 and 40ms have stood the test of time and are considered the cornerstone of MRI protocols for clinical practice and trials. These sequences offer a good balance between sensitivity and specificity and provide appropriate contrast and signal within the cartilage as well as between cartilage, articular fluid, and subchondral bone. Additionally, FS IW sequences enable the evaluation of menisci, ligaments, synovitis/effusion, and bone marrow edema-like signal changes. This review article provides a rationale for the use of FSE FS IW sequences in the morphological assessment of cartilage and osteoarthritis, along with a brief overview of other clinically available sequences for this indication. Additionally, the article highlights ongoing research efforts aimed at improving FSE FS IW sequences through 3D acquisitions with enhanced resolution, shortened examination times, and exploring the potential benefits of different magnetic field strengths. While most of the literature on cartilage imaging focuses on the knee, the concepts presented here are applicable to all joints. KEY POINTS: 1. MRI is currently considered the modality of reference for a "whole-joint" morphological assessment of osteoarthritis. 2. Fat-suppressed intermediate-weighted sequences remain the keystone of MRI protocols for the assessment of cartilage morphology, as well as other structures involved in osteoarthritis. 3. Trends for further development in the field of cartilage and joint imaging include 3D FSE imaging, faster acquisition including AI-based acceleration, and synthetic imaging providing multi-contrast sequences.
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Affiliation(s)
- Patrick Omoumi
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
| | - Charbel Mourad
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Department of Diagnostic and Interventional Radiology, Hôpital Libanais Geitaoui CHU, Achrafieh, Beyrouth, Lebanon
| | - Jean-Baptiste Ledoux
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tom Hilbert
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- LTS5, École Polytechnique FÉdÉrale de Lausanne (EPFL), Lausanne, Switzerland
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8
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Sneag DB, Abel F, Potter HG, Fritz J, Koff MF, Chung CB, Pedoia V, Tan ET. MRI Advancements in Musculoskeletal Clinical and Research Practice. Radiology 2023; 308:e230531. [PMID: 37581501 PMCID: PMC10477516 DOI: 10.1148/radiol.230531] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 06/01/2023] [Accepted: 06/07/2023] [Indexed: 08/16/2023]
Abstract
Over the past decades, MRI has become increasingly important for diagnosing and longitudinally monitoring musculoskeletal disorders, with ongoing hardware and software improvements aiming to optimize image quality and speed. However, surging demand for musculoskeletal MRI and increased interest to provide more personalized care will necessitate a stronger emphasis on efficiency and specificity. Ongoing hardware developments include more powerful gradients, improvements in wide-bore magnet designs to maintain field homogeneity, and high-channel phased-array coils. There is also interest in low-field-strength magnets with inherently lower magnetic footprints and operational costs to accommodate global demand in middle- and low-income countries. Previous approaches to decrease acquisition times by means of conventional acceleration techniques (eg, parallel imaging or compressed sensing) are now largely overshadowed by deep learning reconstruction algorithms. It is expected that greater emphasis will be placed on improving synthetic MRI and MR fingerprinting approaches to shorten overall acquisition times while also addressing the demand of personalized care by simultaneously capturing microstructural information to provide greater detail of disease severity. Authors also anticipate increased research emphasis on metal artifact reduction techniques, bone imaging, and MR neurography to meet clinical needs.
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Affiliation(s)
- Darryl B. Sneag
- From the Department of Radiology and Imaging, Hospital for Special
Surgery, 535 E 70th St, New York, NY 10021 (D.B.S., F.A., H.G.P., M.F.K.,
E.T.T.); Department of Radiology, New York University Grossman School of
Medicine, New York, NY (J.F.); Department of Radiology, University of California
San Diego, La Jolla, Calif (C.B.C.); Radiology Service, Veterans Affairs San
Diego Healthcare System, La Jolla, Calif (C.B.C.); and Department of Radiology
and Biomedical Imaging, University of California San Francisco, San Francisco,
Calif (V.P.)
| | - Frederik Abel
- From the Department of Radiology and Imaging, Hospital for Special
Surgery, 535 E 70th St, New York, NY 10021 (D.B.S., F.A., H.G.P., M.F.K.,
E.T.T.); Department of Radiology, New York University Grossman School of
Medicine, New York, NY (J.F.); Department of Radiology, University of California
San Diego, La Jolla, Calif (C.B.C.); Radiology Service, Veterans Affairs San
Diego Healthcare System, La Jolla, Calif (C.B.C.); and Department of Radiology
and Biomedical Imaging, University of California San Francisco, San Francisco,
Calif (V.P.)
| | - Hollis G. Potter
- From the Department of Radiology and Imaging, Hospital for Special
Surgery, 535 E 70th St, New York, NY 10021 (D.B.S., F.A., H.G.P., M.F.K.,
E.T.T.); Department of Radiology, New York University Grossman School of
Medicine, New York, NY (J.F.); Department of Radiology, University of California
San Diego, La Jolla, Calif (C.B.C.); Radiology Service, Veterans Affairs San
Diego Healthcare System, La Jolla, Calif (C.B.C.); and Department of Radiology
and Biomedical Imaging, University of California San Francisco, San Francisco,
Calif (V.P.)
| | - Jan Fritz
- From the Department of Radiology and Imaging, Hospital for Special
Surgery, 535 E 70th St, New York, NY 10021 (D.B.S., F.A., H.G.P., M.F.K.,
E.T.T.); Department of Radiology, New York University Grossman School of
Medicine, New York, NY (J.F.); Department of Radiology, University of California
San Diego, La Jolla, Calif (C.B.C.); Radiology Service, Veterans Affairs San
Diego Healthcare System, La Jolla, Calif (C.B.C.); and Department of Radiology
and Biomedical Imaging, University of California San Francisco, San Francisco,
Calif (V.P.)
| | - Matthew F. Koff
- From the Department of Radiology and Imaging, Hospital for Special
Surgery, 535 E 70th St, New York, NY 10021 (D.B.S., F.A., H.G.P., M.F.K.,
E.T.T.); Department of Radiology, New York University Grossman School of
Medicine, New York, NY (J.F.); Department of Radiology, University of California
San Diego, La Jolla, Calif (C.B.C.); Radiology Service, Veterans Affairs San
Diego Healthcare System, La Jolla, Calif (C.B.C.); and Department of Radiology
and Biomedical Imaging, University of California San Francisco, San Francisco,
Calif (V.P.)
| | - Christine B. Chung
- From the Department of Radiology and Imaging, Hospital for Special
Surgery, 535 E 70th St, New York, NY 10021 (D.B.S., F.A., H.G.P., M.F.K.,
E.T.T.); Department of Radiology, New York University Grossman School of
Medicine, New York, NY (J.F.); Department of Radiology, University of California
San Diego, La Jolla, Calif (C.B.C.); Radiology Service, Veterans Affairs San
Diego Healthcare System, La Jolla, Calif (C.B.C.); and Department of Radiology
and Biomedical Imaging, University of California San Francisco, San Francisco,
Calif (V.P.)
| | - Valentina Pedoia
- From the Department of Radiology and Imaging, Hospital for Special
Surgery, 535 E 70th St, New York, NY 10021 (D.B.S., F.A., H.G.P., M.F.K.,
E.T.T.); Department of Radiology, New York University Grossman School of
Medicine, New York, NY (J.F.); Department of Radiology, University of California
San Diego, La Jolla, Calif (C.B.C.); Radiology Service, Veterans Affairs San
Diego Healthcare System, La Jolla, Calif (C.B.C.); and Department of Radiology
and Biomedical Imaging, University of California San Francisco, San Francisco,
Calif (V.P.)
| | - Ek T. Tan
- From the Department of Radiology and Imaging, Hospital for Special
Surgery, 535 E 70th St, New York, NY 10021 (D.B.S., F.A., H.G.P., M.F.K.,
E.T.T.); Department of Radiology, New York University Grossman School of
Medicine, New York, NY (J.F.); Department of Radiology, University of California
San Diego, La Jolla, Calif (C.B.C.); Radiology Service, Veterans Affairs San
Diego Healthcare System, La Jolla, Calif (C.B.C.); and Department of Radiology
and Biomedical Imaging, University of California San Francisco, San Francisco,
Calif (V.P.)
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Zhang Z, Liu J, Wang W, Zhang Y, Qu F, Hilbert T, Kober T, Cheng J, Li S, Zhu J. Feasibility of accelerated T2 mapping for the preoperative assessment of endometrial carcinoma. Front Oncol 2023; 13:1117148. [PMID: 37564932 PMCID: PMC10411727 DOI: 10.3389/fonc.2023.1117148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 07/07/2023] [Indexed: 08/12/2023] Open
Abstract
Objective The application value of T2 mapping in evaluating endometrial carcinoma (EMC) features remains unclear. The aim of the study was to determine the quantitative T2 values in EMC using a novel accelerated T2 mapping, and evaluate them for detection, classification,and grading of EMC. Materials and methods Fifty-six patients with pathologically confirmed EMC and 17 healthy volunteers were prospectively enrolled in this study. All participants underwent pelvic magnetic resonance imaging, including DWI and accelerated T2 mapping, before treatment. The T2 and apparent diffusion coefficient (ADC) values of different pathologic EMC features were extracted and compared. Receiver operating characteristic (ROC) curve analysis was performed to analyze the diagnostic efficacy of the T2 and ADC values in distinguishing different pathological features of EMC. Results The T2 values and ADC values were significantly lower in EMC than in normal endometrium (bothl p < 0.05). The T2 and ADC values were significantly different between endometrioid adenocarcinoma (EA) and non-EA (both p < 0.05) and EMC tumor grades (all p < 0.05) but not for EMC clinical types (both p > 0.05) and depth of myometrial invasion (both p > 0.05). The area under the ROC curve (AUC) was higher for T2 values than for ADC values in predicting grade 3 EA (0.939 vs. 0.764, p = 0.048). When combined T2 and ADC values, the AUC for predicting grade 3 EA showed a significant increase to 0.947 (p = 0.03) compared with those of ADC values. The T2 and ADC values were negatively correlated with the tumor grades (r = -0.706 and r = -0.537, respectively). Conclusion Quantitative T2 values demonstrate potential suitability in discriminating between EMC and normal endometrium, EA and non-EA, grade 3 EA and grade 1/2 EA. Combining T2 and ADC values performs better in predicting the histological grades of EA in comparison with ADC values alone.
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Affiliation(s)
- Zanxia Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jie Liu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Feifei Qu
- Magnetic Resonance Collaboration, Siemens Healthcare Ltd., Beijing, China
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Signal Processing Lab 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Signal Processing Lab 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shujian Li
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jinxia Zhu
- Magnetic Resonance Collaboration, Siemens Healthcare Ltd., Beijing, China
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Zubair AS, Salam S, Dimachkie MM, Machado PM, Roy B. Imaging biomarkers in the idiopathic inflammatory myopathies. Front Neurol 2023; 14:1146015. [PMID: 37181575 PMCID: PMC10166883 DOI: 10.3389/fneur.2023.1146015] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 04/03/2023] [Indexed: 05/16/2023] Open
Abstract
Idiopathic inflammatory myopathies (IIMs) are a group of acquired muscle diseases with muscle inflammation, weakness, and other extra-muscular manifestations. IIMs can significantly impact the quality of life, and management of IIMs often requires a multi-disciplinary approach. Imaging biomarkers have become an integral part of the management of IIMs. Magnetic resonance imaging (MRI), muscle ultrasound, electrical impedance myography (EIM), and positron emission tomography (PET) are the most widely used imaging technologies in IIMs. They can help make the diagnosis and assess the burden of muscle damage and treatment response. MRI is the most widely used imaging biomarker of IIMs and can assess a large volume of muscle tissue but is limited by availability and cost. Muscle ultrasound and EIM are easy to administer and can even be performed in the clinical setting, but they need further validation. These technologies may complement muscle strength testing and laboratory studies and provide an objective assessment of muscle health in IIMs. Furthermore, this is a rapidly progressing field, and new advances are going to equip care providers with a better objective assessment of IIMS and eventually improve patient management. This review discusses the current state and future direction of imaging biomarkers in IIMs.
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Affiliation(s)
- Adeel S. Zubair
- Division of Neuromuscular Diseases, Department of Neurology, Yale University School of Medicine, New Haven, CT, United States
| | - Sharfaraz Salam
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Mazen M. Dimachkie
- Department of Neurology, The University of Kansas Medical Center, Kansas City, KS, United States
| | - Pedro M. Machado
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
- Centre for Rheumatology, Division of Medicine, University College London, London, United Kingdom
| | - Bhaskar Roy
- Division of Neuromuscular Diseases, Department of Neurology, Yale University School of Medicine, New Haven, CT, United States
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Scholand N, Wang X, Roeloffs V, Rosenzweig S, Uecker M. Quantitative MRI by nonlinear inversion of the Bloch equations. Magn Reson Med 2023; 90:520-538. [PMID: 37093980 DOI: 10.1002/mrm.29664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 02/16/2023] [Accepted: 03/20/2023] [Indexed: 04/26/2023]
Abstract
PURPOSE Development of a generic model-based reconstruction framework for multiparametric quantitative MRI that can be used with data from different pulse sequences. METHODS Generic nonlinear model-based reconstruction for quantitative MRI estimates parametric maps directly from the acquired k-space by numerical optimization. This requires numerically accurate and efficient methods to solve the Bloch equations and their partial derivatives. In this work, we combine direct sensitivity analysis and pre-computed state-transition matrices into a generic framework for calibrationless model-based reconstruction that can be applied to different pulse sequences. As a proof-of-concept, the method is implemented and validated for quantitative T 1 $$ {\mathrm{T}}_1 $$ and T 2 $$ {\mathrm{T}}_2 $$ mapping with single-shot inversion-recovery (IR) FLASH and IR bSSFP sequences in simulations, phantoms, and the human brain. RESULTS The direct sensitivity analysis enables a highly accurate and numerically stable calculation of the derivatives. The state-transition matrices efficiently exploit repeating patterns in pulse sequences, speeding up the calculation by a factor of 10 for the examples considered in this work, while preserving the accuracy of native ordinary differential equations solvers. The generic model-based method reproduces quantitative results of previous model-based reconstructions based on the known analytical solutions for radial IR FLASH. For IR bSFFP it produces accurate T 1 $$ {\mathrm{T}}_1 $$ and T 2 $$ {\mathrm{T}}_2 $$ maps for the National Insitute of Standards and Technology (NIST) phantom in numerical simulations and experiments. Feasibility is also shown for human brain, although results are affected by magnetization transfer effects. CONCLUSION By developing efficient tools for numerical optimizations using the Bloch equations as forward model, this work enables generic model-based reconstruction for quantitative MRI.
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Affiliation(s)
- Nick Scholand
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Göttingen, Germany
| | - Xiaoqing Wang
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Göttingen, Germany
| | - Volkert Roeloffs
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
| | - Sebastian Rosenzweig
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Göttingen, Germany
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
| | - Martin Uecker
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Göttingen, Germany
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
- Cluster of Excellence "Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells" (MBExC), University of Göttingen, Göttingen, Germany
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Brunner R, De Pieri E, Wyss C, Weidensteiner C, Bracht-Schweizer K, Romkes J, Garcia M, Ma N, Rutz E. The Non-Affected Muscle Volume Compensates for the Partial Loss of Strength after Injection of Botulinum Toxin A. Toxins (Basel) 2023; 15:toxins15040267. [PMID: 37104205 PMCID: PMC10141169 DOI: 10.3390/toxins15040267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/18/2023] [Accepted: 03/25/2023] [Indexed: 04/07/2023] Open
Abstract
Local botulinum toxin (BTX-A, Botox®) injection in overactive muscles is a standard treatment in patients with cerebral palsy. The effect is markedly reduced in children above the age of 6 to 7. One possible reason for this is the muscle volume affected by the drug. Nine patients (aged 11.5; 8.7–14.5 years) with cerebral palsy GMFCS I were treated with BTX-A for equinus gait at the gastrocnemii and soleus muscles. BTX-A was administered at one or two injection sites per muscle belly and with a maximum of 50 U per injection site. Physical examination, instrumented gait analysis, and musculoskeletal modelling were used to assess standard muscle parameters, kinematics, and kinetics during gait. Magnetic resonance imaging (MRI) was used to detect the affected muscle volume. All the measurements were carried out pre-, 6 weeks post-, and 12 weeks post-BTX-A. Between 9 and 15% of the muscle volume was affected by BTX-A. There was no effect on gait kinematics and kinetics after BTX-A injection, indicating that the overall kinetic demand placed on the plantar flexor muscles remained unchanged. BTX-A is an effective drug for inducing muscle weakness. However, in our patient cohort, the volume of the affected muscle section was limited, and the remaining non-affected parts were able to compensate for the weakened part of the muscle by taking over the kinetic demands associated with gait, thus not enabling a net functional effect in older children. We recommend distributing the drug over the whole muscle belly through multiple injection sites.
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Affiliation(s)
- Reinald Brunner
- Department of Paediatric Orthopaedics, University Children’s Hospital Basel (UKBB), 4056 Basel, Switzerland
- Laboratory of Movement Analysis, University Children’s Hospital Basel (UKBB), 4056 Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
| | - Enrico De Pieri
- Laboratory of Movement Analysis, University Children’s Hospital Basel (UKBB), 4056 Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
| | - Christian Wyss
- Laboratory of Movement Analysis, University Children’s Hospital Basel (UKBB), 4056 Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
| | - Claudia Weidensteiner
- Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, 4031 Basel, Switzerland
| | - Katrin Bracht-Schweizer
- Laboratory of Movement Analysis, University Children’s Hospital Basel (UKBB), 4056 Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
| | - Jacqueline Romkes
- Laboratory of Movement Analysis, University Children’s Hospital Basel (UKBB), 4056 Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
| | - Meritxell Garcia
- Department of Neuroradiology, University Hospital Zürich, 8091 Zürich, Switzerland
- Division of Neuroradiology, Clinic for Radiology & Nuclear Medicine, University Hospital Basel, 4031 Basel, Switzerland
| | - Norine Ma
- Orthopaedic Department, The Royal Children’s Hospital, Melbourne 3052, Australia
| | - Erich Rutz
- Orthopaedic Department, The Royal Children’s Hospital, Melbourne 3052, Australia
- Murdoch Children’s Research Institute—MCRI, Melbourne 3052, Australia
- Department of Paediatrics, The University of Melbourne, Melbourne 3052, Australia
- Medical Faculty, University of Basel, 4000 Basel, Switzerland
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Gruenebach N, Abello Mercado MA, Grauhan NF, Sanner A, Kronfeld A, Groppa S, Schoeffling VI, Hilbert T, Brockmann MA, Othman AE. Clinical feasibility and validation of the accelerated T2 mapping sequence GRAPPATINI in brain imaging. Heliyon 2023; 9:e15064. [PMID: 37096006 PMCID: PMC10121777 DOI: 10.1016/j.heliyon.2023.e15064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 03/23/2023] [Accepted: 03/27/2023] [Indexed: 04/05/2023] Open
Abstract
Rationale and objectives To prospectively evaluate feasibility and robustness of an accelerated T2 mapping sequence (GRAPPATINI) in brain imaging and to assess its synthetic T2-weighted images (sT2w) in comparison with a standard T2-weighted sequence (T2 TSE). Material and methods Volunteers were included to evaluate the robustness and consecutive patients for morphological evaluation. They were scanned on a 3 T MR-scanner. Healthy volunteers underwent GRAPPATINI of the brain three times (day 1: scan/rescan; day 2: follow-up). Patients between the ages of 18 and 85 years who were able to provide written informed consent and who had no MRI contraindications were included. For morphological comparison two radiologists with 5 and 7 years of experience in brain MRI evaluated image quality using a Likert scale (1 being poor, 4 being excellent) in a blinded and randomized fashion. Results Images were successfully acquired in ten volunteers with a mean age of 25 years (ranging from 22 to 31 years) and 52 patients (23 men/29 women) with a mean age of 55 years (range of 22-83 years). Most brain regions showed repeatable and reproducible T2 values (rescan: CoV 0.75%-2.06%, ICC 69%-92.3%; follow-up: CoV 0.41%-1.59%, ICC 79.4%-95.8%), except for the caudate nucleus (rescan: CoV 7.25%, ICC 66.3%; follow-up: CoV 4.78%, ICC 80.9%). Image quality of sT2w was rated inferior to T2 TSE (median for T2 TSE: 3; sT2w: 1-2), but measurements revealed good interrater reliability of sT2w (lesion counting: ICC 0.85; diameter measure: ICC 0.68 and 0.67). Conclusion GRAPPATINI is a feasible and robust T2 mapping sequence of the brain on intra- and intersubject level. The resulting sT2w depict brain lesions comparable to T2 TSE despite its inferior image quality.
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14
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Wang F, Zhou S, Hou B, Santini F, Yuan L, Guo Y, Zhu J, Hilbert T, Kober T, Zhang Y, Wang Q, Zhao Y, Jin Z. Assessment of idiopathic inflammatory myopathy using a deep learning method for muscle T2 mapping segmentation. Eur Radiol 2023; 33:2350-2357. [PMID: 36396791 PMCID: PMC9672653 DOI: 10.1007/s00330-022-09254-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Revised: 09/19/2022] [Accepted: 10/09/2022] [Indexed: 11/19/2022]
Abstract
OBJECTIVE To investigate the utility of an automatic deep learning (DL) method for segmentation of T2 maps in patients with idiopathic inflammatory myopathy (IIM) against healthy controls, and also the association of quantitative T2 values in patients with laboratory and pulmonary findings. METHODS Structural MRI and T2 mapping of bilateral thigh muscles from patients with IIM and healthy volunteers were segmented using dedicated software based on a pre-trained convolutional neural network. Incremental and federated learning were implemented for continuous adaptation and improvement. Muscle T2 values derived from DL segmentation were compared between patients and healthy controls, and T2 values of patients were further analyzed with serum muscle enzymes, and interstitial lung disease (ILD) which was diagnosed and graded based on chest HRCT. RESULTS Overall, 64 patients (27 patients with dermatomyositis, 29 with polymyositis, and 8 with antisynthetase syndrome (ASS)) and 10 healthy controls were included. By using DL-based muscle segmentation, T2 values generated from T2 maps accurately differentiated patients from those of controls (p < 0.001) with a cutoff value of 36.4 ms (sensitivity 96.9%, and specificity 100%). In patients with IIM, muscle T2 values positively correlated with all the serum muscle enzymes (all p < 0.05). ILD score of patients with ASS was markedly higher than that of those without ASS (p = 0.011), while dissociation between the severity of muscular involvement and ILD was observed (p = 0.080). CONCLUSION Automatic DL could be used to segment thigh muscles and help quantitatively assess muscular inflammation of IIM through T2 mapping. KEY POINTS • Muscle T2 mapping automatically segmented by deep learning can differentiate IIM from healthy controls. • T2 value, an indicator of active muscle inflammation, positively correlates with serum muscle enzymes. • T2 mapping can detect muscle disease in patients with normal muscle enzyme levels.
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Affiliation(s)
- Fengdan Wang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Shuang Zhou
- Department of Rheumatology and Clinical Immunology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Bo Hou
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Francesco Santini
- Department of Research & Analytic Services, University Hospital Basel, Petersgraben 4, CH-4031, Basel, Switzerland.
- Radiological Physics, University Hospital Basel, Basel, Switzerland.
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland.
| | - Ling Yuan
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Ye Guo
- Department of Clinical Laboratory, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Jinxia Zhu
- MR Collaboration, Siemens Healthcare Ltd., Beijing, China
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Yan Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Qian Wang
- Department of Rheumatology and Clinical Immunology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yan Zhao
- Department of Rheumatology and Clinical Immunology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Zhengyu Jin
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
- Department of Radiology, Peking Union Medical College Hospital, No. 1 Shuaifuyuan, Dongcheng District, Beijing, China.
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Rauh SS, Maier O, Gurney-Champion OJ, Hooijmans MT, Stollberger R, Nederveen AJ, Strijkers GJ. Model-based reconstructions for intravoxel incoherent motion and diffusion tensor imaging parameter map estimations. NMR IN BIOMEDICINE 2023:e4927. [PMID: 36932842 DOI: 10.1002/nbm.4927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 01/16/2023] [Accepted: 03/06/2023] [Indexed: 06/18/2023]
Abstract
Intravoxel incoherent motion (IVIM) imaging and diffusion tensor imaging (DTI) facilitate noninvasive quantification of tissue perfusion and diffusion. Both are promising biomarkers in various diseases and a combined acquisition is therefore desirable. This comes with challenges, including noisy parameter maps and long scan times, especially for the perfusion fraction f and pseudo-diffusion coefficient D*. A model-based reconstruction has the potential to overcome these challenges. As a first step, our goal was to develop a model-based reconstruction framework for IVIM and combined IVIM-DTI parameter estimation. The IVIM and IVIM-DTI models were implemented in the PyQMRI model-based reconstruction framework and validated with simulations and in vivo data. Commonly used voxel-wise nonlinear least-squares fitting was used as the reference. Simulations with the IVIM and IVIM-DTI models were performed with 100 noise realizations to assess accuracy and precision. Diffusion-weighted data were acquired for IVIM reconstruction in the liver (n = 5), as well as for IVIM-DTI in the kidneys (n = 5) and lower-leg muscles (n = 6) of healthy volunteers. The median and interquartile range (IQR) values of the IVIM and IVIM-DTI parameters were compared to assess bias and precision. With model-based reconstruction, the parameter maps exhibited less noise, which was most pronounced in the f and D* maps, both in the simulations and in vivo. The bias values in the simulations were comparable between model-based reconstruction and the reference method. The IQR was lower with model-based reconstruction compared with the reference for all parameters. In conclusion, model-based reconstruction is feasible for IVIM and IVIM-DTI and improves the precision of the parameter estimates, particularly for f and D* maps.
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Affiliation(s)
- Susanne S Rauh
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
| | - Oliver Maier
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Oliver J Gurney-Champion
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
| | - Melissa T Hooijmans
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
| | - Rudolf Stollberger
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
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Free-breathing and instantaneous abdominal T 2 mapping via single-shot multiple overlapping-echo acquisition and deep learning reconstruction. Eur Radiol 2023:10.1007/s00330-023-09417-2. [PMID: 36692597 DOI: 10.1007/s00330-023-09417-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 10/12/2022] [Accepted: 01/01/2023] [Indexed: 01/25/2023]
Abstract
OBJECTIVES To develop a real-time abdominal T2 mapping method without requiring breath-holding or respiratory-gating. METHODS The single-shot multiple overlapping-echo detachment (MOLED) pulse sequence was employed to achieve free-breathing T2 mapping of the abdomen. Deep learning was used to untangle the non-linear relationship between the MOLED signal and T2 mapping. A synthetic data generation flow based on Bloch simulation, modality synthesis, and randomization was proposed to overcome the inadequacy of real-world training set. RESULTS The results from simulation and in vivo experiments demonstrated that our method could deliver high-quality T2 mapping. The average NMSE and R2 values of linear regression in the digital phantom experiments were 0.0178 and 0.9751. Pearson's correlation coefficient between our predicted T2 and reference T2 in the phantom experiments was 0.9996. In the measurements for the patients, real-time capture of the T2 value changes of various abdominal organs before and after contrast agent injection was realized. A total of 33 focal liver lesions were detected in the group, and the mean and standard deviation of T2 values were 141.1 ± 50.0 ms for benign and 63.3 ± 16.0 ms for malignant lesions. The coefficients of variance in a test-retest experiment were 2.9%, 1.2%, 0.9%, 3.1%, and 1.8% for the liver, kidney, gallbladder, spleen, and skeletal muscle, respectively. CONCLUSIONS Free-breathing abdominal T2 mapping is achieved in about 100 ms on a clinical MRI scanner. The work paved the way for the development of real-time dynamic T2 mapping in the abdomen. KEY POINTS • MOLED achieves free-breathing abdominal T2 mapping in about 100 ms, enabling real-time capture of T2 value changes due to CA injection in abdominal organs. • Synthetic data generation flow mitigates the issue of lack of sizable abdominal training datasets.
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Abstract
ABSTRACT This review summarizes the existing techniques and methods used to generate synthetic contrasts from magnetic resonance imaging data focusing on musculoskeletal magnetic resonance imaging. To that end, the different approaches were categorized into 3 different methodological groups: mathematical image transformation, physics-based, and data-driven approaches. Each group is characterized, followed by examples and a brief overview of their clinical validation, if present. Finally, we will discuss the advantages, disadvantages, and caveats of synthetic contrasts, focusing on the preservation of image information, validation, and aspects of the clinical workflow.
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Tolpadi AA, Han M, Calivà F, Pedoia V, Majumdar S. Region of interest-specific loss functions improve T 2 quantification with ultrafast T 2 mapping MRI sequences in knee, hip and lumbar spine. Sci Rep 2022; 12:22208. [PMID: 36564430 PMCID: PMC9789075 DOI: 10.1038/s41598-022-26266-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
MRI T2 mapping sequences quantitatively assess tissue health and depict early degenerative changes in musculoskeletal (MSK) tissues like cartilage and intervertebral discs (IVDs) but require long acquisition times. In MSK imaging, small features in cartilage and IVDs are crucial for diagnoses and must be preserved when reconstructing accelerated data. To these ends, we propose region of interest-specific postprocessing of accelerated acquisitions: a recurrent UNet deep learning architecture that provides T2 maps in knee cartilage, hip cartilage, and lumbar spine IVDs from accelerated T2-prepared snapshot gradient-echo acquisitions, optimizing for cartilage and IVD performance with a multi-component loss function that most heavily penalizes errors in those regions. Quantification errors in knee and hip cartilage were under 10% and 9% from acceleration factors R = 2 through 10, respectively, with bias for both under 3 ms for most of R = 2 through 12. In IVDs, mean quantification errors were under 12% from R = 2 through 6. A Gray Level Co-Occurrence Matrix-based scheme showed knee and hip pipelines outperformed state-of-the-art models, retaining smooth textures for most R and sharper ones through moderate R. Our methodology yields robust T2 maps while offering new approaches for optimizing and evaluating reconstruction algorithms to facilitate better preservation of small, clinically relevant features.
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Affiliation(s)
- Aniket A Tolpadi
- Department of Radiology and Biomedical Imaging, University of California, 1700, 4th Street, San Francisco, CA, 94158, USA.
| | - Misung Han
- Department of Radiology and Biomedical Imaging, University of California, 1700, 4th Street, San Francisco, CA, 94158, USA
| | - Francesco Calivà
- Department of Radiology and Biomedical Imaging, University of California, 1700, 4th Street, San Francisco, CA, 94158, USA
| | - Valentina Pedoia
- Department of Radiology and Biomedical Imaging, University of California, 1700, 4th Street, San Francisco, CA, 94158, USA
| | - Sharmila Majumdar
- Department of Radiology and Biomedical Imaging, University of California, 1700, 4th Street, San Francisco, CA, 94158, USA
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Ouyang B, Yang Q, Wang X, He H, Ma L, Yang Q, Zhou Z, Cai S, Chen Z, Wu Z, Zhong J, Cai C. Single-shot T 2 mapping via multi-echo-train multiple overlapping-echo detachment planar imaging and multitask deep learning. Med Phys 2022; 49:7095-7107. [PMID: 35765150 DOI: 10.1002/mp.15820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 05/02/2022] [Accepted: 06/13/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Quantitative magnetic resonance imaging provides robust biomarkers in clinics. Nevertheless, the lengthy scan time reduces imaging throughput and increases the susceptibility of imaging results to motion. In this context, a single-shot T2 mapping method based on multiple overlapping-echo detachment (MOLED) planar imaging was presented, but the relatively small echo time range limits its accuracy, especially in tissues with large T2 . PURPOSE In this work we proposed a novel single-shot method, Multi-Echo-Train Multiple OverLapping-Echo Detachment (METMOLED) planar imaging, to accommodate a large range of T2 quantification without additional measurements to rectify signal degeneration arisen from refocusing pulse imperfection. METHODS Multiple echo-train techniques were integrated into the MOLED sequence to capture larger TE information. Maps of T2 , B1 , and spin density were reconstructed synchronously from acquired METMOLED data via multitask deep learning. A typical U-Net was trained with 3000/600 synthetic data with geometric/brain patterns to learn the mapping relationship between METMOLED signals and quantitative maps. The refocusing pulse imperfection was settled through the inherent information of METMOLED data and auxiliary tasks. RESULTS Experimental results on the digital brain (structural similarity (SSIM) index = 0.975/0.991/0.988 for MOLED/METMOLED-2/METMOLED-3, hyphenated number denotes the number of echo-trains), physical phantom (the slope of linear fitting with reference T2 map = 1.047/1.017/1.006 for MOLED/METMOLED-2/METMOLED-3), and human brain (Pearson's correlation coefficient (PCC) = 0.9581/0.9760/0.9900 for MOLED/METMOLED-2/METMOLED-3) demonstrated that the METMOLED improved the quantitative accuracy and the tissue details in contrast to the MOLED. These improvements were more pronounced in tissues with large T2 and in application scenarios with high temporal resolution (PCC = 0.8692/0.9465/0.9743 for MOLED/METMOLED-2/METMOLED-3). Moreover, the METMOLED could rectify the signal deviations induced by the non-ideal slice profiles of refocusing pulses without additional measurements. A preliminary measurement also demonstrated that the METMOLED is highly repeatable (mean coefficient of variation (CV) = 1.65%). CONCLUSIONS METMOLED breaks the restriction of echo-train length to TE and implements unbiased T2 estimates in an extensive range. Furthermore, it corrects the effect of refocusing pulse inaccuracy without additional measurements or signal post-processing, thus retaining its single-shot characteristic. This technique would be beneficial for accurate T2 quantification.
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Affiliation(s)
- Binyu Ouyang
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, Fujian, 361005, China
| | - Qizhi Yang
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, Fujian, 361005, China
| | - Xiaoyin Wang
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Lingceng Ma
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, Fujian, 361005, China
| | - Qinqin Yang
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, Fujian, 361005, China
| | - Zihan Zhou
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Shuhui Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, Fujian, 361005, China
| | - Zhong Chen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, Fujian, 361005, China
| | - Zhigang Wu
- MSC Clinical and Technical Solutions, Philips Healthcare, Shenzhen, Guangdong, 518005, China
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, 310058, China.,Department of Imaging Sciences, University of Rochester, Rochester, New York, 14642, USA
| | - Congbo Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, Fujian, 361005, China
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20
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Seginer A, Schmidt R. Phase-based fast 3D high-resolution quantitative T 2 MRI in 7 T human brain imaging. Sci Rep 2022; 12:14088. [PMID: 35982143 PMCID: PMC9388657 DOI: 10.1038/s41598-022-17607-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 07/28/2022] [Indexed: 12/04/2022] Open
Abstract
Magnetic resonance imaging (MRI) is a powerful and versatile technique that offers a range of physiological, diagnostic, structural, and functional measurements. One of the most widely used basic contrasts in MRI diagnostics is transverse relaxation time (T2)-weighted imaging, but it provides only qualitative information. Realizing quantitative high-resolution T2 mapping is imperative for the development of personalized medicine, as it can enable the characterization of diseases progression. While ultra-high-field (≥ 7 T) MRI offers the means to gain new insights by increasing the spatial resolution, implementing fast quantitative T2 mapping cannot be achieved without overcoming the increased power deposition and radio frequency (RF) field inhomogeneity at ultra-high-fields. A recent study has demonstrated a new phase-based T2 mapping approach based on fast steady-state acquisitions. We extend this new approach to ultra-high field MRI, achieving quantitative high-resolution 3D T2 mapping at 7 T while addressing RF field inhomogeneity and utilizing low flip angle pulses; overcoming two main ultra-high field challenges. The method is based on controlling the coherent transverse magnetization in a steady-state gradient echo acquisition; achieved by utilizing low flip angles, a specific phase increment for the RF pulses, and short repetition times. This approach simultaneously extracts both T2 and RF field maps from the phase of the signal. Prior to in vivo experiments, the method was assessed using a 3D head-shaped phantom that was designed to model the RF field distribution in the brain. Our approach delivers fast 3D whole brain images with submillimeter resolution without requiring special hardware, such as multi-channel transmit coil, thus promoting high usability of the ultra-high field MRI in clinical practice.
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Affiliation(s)
| | - Rita Schmidt
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel. .,The Azrieli National Institute for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel.
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21
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Pseudo-T2 mapping for normalization of T2-weighted prostate MRI. MAGMA (NEW YORK, N.Y.) 2022; 35:573-585. [PMID: 35150363 PMCID: PMC9363383 DOI: 10.1007/s10334-022-01003-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 12/22/2021] [Accepted: 01/23/2022] [Indexed: 01/04/2023]
Abstract
Objective Signal intensity normalization is necessary to reduce heterogeneity in T2-weighted (T2W) magnetic resonance imaging (MRI) for quantitative analysis of multicenter data. AutoRef is an automated dual-reference tissue normalization method that normalizes transversal prostate T2W MRI by creating a pseudo-T2 map. The aim of this study was to evaluate the accuracy of pseudo-T2s and multicenter standardization performance for AutoRef with three pairs of reference tissues: fat/muscle (AutoRefF), femoral head/muscle (AutoRefFH) and pelvic bone/muscle (AutoRefPB). Materials and methods T2s measured by multi-echo spin echo (MESE) were compared to AutoRef pseudo-T2s in the whole prostate (WP) and zones (PZ and TZ/CZ/AFS) for seven asymptomatic volunteers with a paired Wilcoxon signed-rank test. AutoRef normalization was assessed on T2W images from a multicenter evaluation set of 1186 prostate cancer patients. Performance was measured by inter-patient histogram intersections of voxel intensities in the WP before and after normalization in a selected subset of 80 cases. Results AutoRefFH pseudo-T2s best approached MESE T2s in the volunteer study, with no significant difference shown (WP: p = 0.30, TZ/CZ/AFS: p = 0.22, PZ: p = 0.69). All three AutoRef versions increased inter-patient histogram intersections in the multicenter dataset, with median histogram intersections of 0.505 (original data), 0.738 (AutoRefFH), 0.739 (AutoRefF) and 0.726 (AutoRefPB). Discussion All AutoRef versions reduced variation in the multicenter data. AutoRefFH pseudo-T2s were closest to experimentally measured T2s. Supplementary Information The online version contains supplementary material available at 10.1007/s10334-022-01003-9.
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Piredda GF, Hilbert T, Ravano V, Canales-Rodríguez EJ, Pizzolato M, Meuli R, Thiran JP, Richiardi J, Kober T. Data-driven myelin water imaging based on T 1 and T 2 relaxometry. NMR IN BIOMEDICINE 2022; 35:e4668. [PMID: 34936147 DOI: 10.1002/nbm.4668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 11/16/2021] [Accepted: 11/30/2021] [Indexed: 06/14/2023]
Abstract
Long acquisition times preclude the application of multiecho spin echo (MESE) sequences for myelin water fraction (MWF) mapping in daily clinical practice. In search of alternative methods, previous studies of interest explored the biophysical modeling of MWF from measurements of different tissue properties that can be obtained in scan times shorter than those required for the MESE. In this work, a novel data-driven estimation of MWF maps from fast relaxometry measurements is proposed and investigated. T1 and T2 relaxometry maps were acquired in a cohort of 20 healthy subjects along with a conventional MESE sequence. Whole-brain quantitative mapping was achieved with a fast protocol in 6 min 24 s. Reference MWF maps were derived from the MESE sequence (TA = 11 min 17 s) and their data-driven estimation from relaxometry measurements was investigated using three different modeling strategies: two general linear models (GLMs) with linear and quadratic regressors, respectively; a random forest regression model; and two deep neural network architectures, a U-Net and a conditional generative adversarial network (cGAN). Models were validated using a 10-fold crossvalidation. The resulting maps were visually and quantitatively compared by computing the root mean squared error (RMSE) between the estimated and reference MWF maps, the intraclass correlation coefficients (ICCs) between corresponding MWF values in different brain regions, and by performing Bland-Altman analysis. Qualitatively, the estimated maps appear to generally provide a similar, yet more blurred MWF contrast in comparison with the reference, with the cGAN model best capturing MWF variabilities in small structures. By estimating the average adjusted coefficient of determination of the GLM with quadratic regressors, we showed that 87% of the variability in the MWF values can be explained by relaxation times alone. Further quantitative analysis showed an average RMSE smaller than 0.1% for all methods. The ICC was greater than 0.81 for all methods, and the bias smaller than 2.19%. It was concluded that this work confirms the notion that relaxometry parameters contain a large part of the information on myelin water and that MWF maps can be generated from T1 /T2 data with minimal error. Among the investigated modeling approaches, the cGAN provided maps with the best trade-off between accuracy and blurriness. Fast relaxometry, like the 6 min 24 s whole-brain protocol used in this work in conjunction with machine learning, may thus have the potential to replace time-consuming MESE acquisitions.
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Affiliation(s)
- Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Veronica Ravano
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | | | - Marco Pizzolato
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Reto Meuli
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jonas Richiardi
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Beirinckx Q, Jeurissen B, Nicastro M, Poot DH, Verhoye M, Dekker AJD, Sijbers J. Model-based super-resolution reconstruction with joint motion estimation for improved quantitative MRI parameter mapping. Comput Med Imaging Graph 2022; 100:102071. [DOI: 10.1016/j.compmedimag.2022.102071] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 04/07/2022] [Accepted: 04/29/2022] [Indexed: 01/18/2023]
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T2 mapping for the characterization of prostate lesions. World J Urol 2022; 40:1455-1461. [PMID: 35357510 PMCID: PMC9166840 DOI: 10.1007/s00345-022-03991-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 03/11/2022] [Indexed: 11/26/2022] Open
Abstract
Purpose Purpose of this study is to evaluate the diagnostic accuracy of quantitative T2/ADC values in differentiating between PCa and lesions showing non-specific inflammatory infiltrates and atrophy, features of chronic prostatitis, as the most common histologically proven differential diagnosis. Methods In this retrospective, single-center cohort study, we analyzed 55 patients suspected of PCa, who underwent mpMRI (3T) including quantitative T2 maps before robot-assisted mpMRI-TRUS fusion prostate biopsy. All prostate lesions were scored according to PI-RADS v2.1. Regions of interest (ROIs) were annotated in focal lesions and normal prostate tissue. Quantitative mpMRI values from T2 mapping and ADC were compared using two-tailed t tests. Receiver operating characteristic curves (ROCs) and cutoff were calculated to differentiate between PCa and chronic prostatitis. Results Focal lesions showed significantly lower ADC and T2 mapping values than normal prostate tissue (p < 0.001). PCa showed significantly lower ADC and T2 values than chronic prostatitis (p < 0.001). ROC analysis revealed areas under the receiver operating characteristic curves (AUCs) of 0.85 (95% CI 0.74–0.97) for quantitative ADC values and 0.84 (95% CI 0.73–0.96) for T2 mapping. A significant correlation between ADC and T2 values was observed (r = 0.70; p < 0.001). Conclusion T2 mapping showed high diagnostic accuracy for differentiating between PCa and chronic prostatitis, comparable to the performance of ADC values. Supplementary Information The online version contains supplementary material available at 10.1007/s00345-022-03991-8.
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Cao T, Ma S, Wang N, Gharabaghi S, Xie Y, Fan Z, Hogg E, Wu C, Han F, Tagliati M, Haacke EM, Christodoulou AG, Li D. Three-dimensional simultaneous brain mapping of T1, T2, T2∗ and magnetic susceptibility with MR Multitasking. Magn Reson Med 2022; 87:1375-1389. [PMID: 34708438 PMCID: PMC8776611 DOI: 10.1002/mrm.29059] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 09/08/2021] [Accepted: 10/07/2021] [Indexed: 01/24/2023]
Abstract
PURPOSE To develop a new technique that enables simultaneous quantification of whole-brain T1 , T2 , T 2 ∗ , as well as susceptibility and synthesis of six contrast-weighted images in a single 9.1-minute scan. METHODS The technique uses hybrid T2 -prepared inversion-recovery pulse modules and multi-echo gradient-echo readouts to collect k-space data with various T1, T2, and T 2 ∗ weightings. The underlying image is represented as a six-dimensional low-rank tensor consisting of three spatial dimensions and three temporal dimensions corresponding to T1 recovery, T2 decay, and multi-echo behaviors, respectively. Multiparametric maps were fitted from reconstructed image series. The proposed method was validated on phantoms and healthy volunteers, by comparing quantitative measurements against corresponding reference methods. The feasibility of generating six contrast-weighted images was also examined. RESULTS High quality, co-registered T1 , T2 , and T 2 ∗ susceptibility maps were generated that closely resembled the reference maps. Phantom measurements showed substantial consistency (R2 > 0.98) with the reference measurements. Despite the significant differences of T1 (p < .001), T2 (p = .002), and T 2 ∗ (p = 0.008) between our method and the references for in vivo studies, excellent agreement was achieved with all intraclass correlation coefficients greater than 0.75. No significant difference was found for susceptibility (p = .900). The framework is also capable of synthesizing six contrast-weighted images. CONCLUSION The MR Multitasking-based 3D brain mapping of T1 , T2 , T 2 ∗ , and susceptibility agrees well with the reference and is a promising technique for multicontrast and quantitative imaging.
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Affiliation(s)
- Tianle Cao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Sen Ma
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Nan Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Sara Gharabaghi
- Magnetic Resonance Innovations, Inc., Bingham Farms, MI, USA
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Zhaoyang Fan
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Elliot Hogg
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Chaowei Wu
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Fei Han
- Siemens Medical Solutions USA, Inc., Los Angeles, California, USA
| | - Michele Tagliati
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - E. Mark Haacke
- Magnetic Resonance Innovations, Inc., Bingham Farms, MI, USA
- Department of Radiology, Wayne State University School of Medicine, Detroit, MI, USA
- The MRI Institute for Biomedical Research, Bingham Farms, MI, USA
| | - Anthony G. Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, California, USA
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Byanju R, Klein S, Cristobal-Huerta A, Hernandez-Tamames JA, Poot DH. Time efficiency analysis for undersampled quantitative MRI acquisitions. Med Image Anal 2022; 78:102390. [DOI: 10.1016/j.media.2022.102390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 11/12/2021] [Accepted: 02/10/2022] [Indexed: 10/19/2022]
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Klingebiel M, Schimmöller L, Weiland E, Franiel T, Jannusch K, Kirchner J, Hilbert T, Strecker R, Arsov C, Wittsack HJ, Albers P, Antoch G, Ullrich T. Value of T 2 Mapping MRI for Prostate Cancer Detection and Classification. J Magn Reson Imaging 2022; 56:413-422. [PMID: 35038203 DOI: 10.1002/jmri.28061] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 12/21/2021] [Accepted: 12/22/2021] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Currently, multi-parametric prostate MRI (mpMRI) consists of a qualitative T2 , diffusion weighted, and dynamic contrast enhanced imaging. Quantification of T2 imaging might further standardize PCa detection and support artificial intelligence solutions. PURPOSE To evaluate the value of T2 mapping to detect prostate cancer (PCa) and to differentiate PCa aggressiveness. STUDY TYPE Retrospective single center cohort study. POPULATION Forty-four consecutive patients (mean age 67 years; median PSA 7.9 ng/mL) with mpMRI and verified PCa by subsequent targeted plus systematic MR/ultrasound (US)-fusion biopsy from February 2019 to December 2019. FIELD STRENGTH/SEQUENCE Standardized mpMRI at 3 T with an additionally acquired T2 mapping sequence. ASSESSMENT Primary endpoint was the analysis of quantitative T2 values and contrast differences/ratios (CD/CR) between PCa and benign tissue. Secondary objectives were the correlation between T2 values, ISUP grade, apparent diffusion coefficient (ADC) value, and PI-RADS, and the evaluation of thresholds for differentiating PCa and clinically significant PCa (csPCa). STATISTICAL TESTS Mann-Whitney test, Spearman's rank (rs ) correlation, receiver operating curves, Youden's index (J), and AUC were performed. Statistical significance was defined as P < 0.05. RESULTS Median quantitative T2 values were significantly lower for PCa in PZ (85 msec) and PCa in TZ (75 msec) compared to benign PZ (141 msec) or TZ (97 msec) (P < 0.001). CD/CR between PCa and benign PZ (51.2/1.77), respectively TZ (19.8/1.29), differed significantly (P < 0.001). The best T2 -mapping threshold for PCa/csPCa detection was for TZ 81/86 msec (J = 0.929/1.0), and for PZ 110 msec (J = 0.834/0.905). Quantitative T2 values of PCa did not correlate significantly with the ISUP grade (rs = 0.186; P = 0.226), ADC value (rs = 0.138; P = 0.372), or PI-RADS (rs = 0.132; P = 0.392). DATA CONCLUSION Quantitative T2 values could differentiate PCa in TZ and PZ and might support standardization of mpMRI of the prostate. Different thresholds seem to apply for PZ and TZ lesions. However, in the present study quantitative T2 values were not able to indicate PCa aggressiveness. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Maximilian Klingebiel
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Dusseldorf, Germany
| | - Lars Schimmöller
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Dusseldorf, Germany
| | - Elisabeth Weiland
- MR Applications Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Tobias Franiel
- Department of Diagnostic and Interventional Radiology, University Hospital Jena, Jena, Germany
| | - Kai Jannusch
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Dusseldorf, Germany
| | - Julian Kirchner
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Dusseldorf, Germany
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Ralph Strecker
- SHS EMEA ST&BD SP PS&O, Siemens Healthcare GmbH, Eschborn, Germany
| | - Christian Arsov
- Department of Urology, University Dusseldorf, Medical Faculty, Dusseldorf, Germany
| | - Hans-Jörg Wittsack
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Dusseldorf, Germany
| | - Peter Albers
- Department of Urology, University Dusseldorf, Medical Faculty, Dusseldorf, Germany
| | - Gerald Antoch
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Dusseldorf, Germany
| | - Tim Ullrich
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Dusseldorf, Germany
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Comparison of T2 Quantification Strategies in the Abdominal-Pelvic Region for Clinical Use. Invest Radiol 2022; 57:412-421. [PMID: 34999669 DOI: 10.1097/rli.0000000000000852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES The aim of the study was to compare different magnetic resonance imaging (MRI) acquisition strategies appropriate for T2 quantification in the abdominal-pelvic area. The different techniques targeted in the study were chosen according to 2 main considerations: performing T2 measurement in an acceptable time for clinical use and preventing/correcting respiratory motion. MATERIALS AND METHODS Acquisitions were performed at 3 T. To select sequences for in vivo measurements, a phantom experiment was conducted, for which the T2 values obtained with the different techniques of interest were compared with the criterion standard (single-echo SE sequence, multiple acquisitions with varying echo time). Repeatability and temporal reproducibility studies for the different techniques were also conducted on the phantom. Finally, an in vivo study was conducted on 12 volunteers to compare the techniques that offer acceptable acquisition time for clinical use and either address or correct respiratory motion. RESULTS For the phantom study, the DESS and T2-preparation techniques presented the lowest precision (ρ2 = 0.9504 and ρ2 = 0.9849 respectively), and showed a poor repeatability/reproducibility compared with the other techniques. The strategy relying on SE-EPI showed the best precision and accuracy (ρ2 = 0.9994 and Cb = 0.9995). GRAPPATINI exhibited a very good precision (ρ2 = 0.9984). For the technique relying on radial TSE, the precision was not as good as GRAPPATINI (ρ2 = 0.9872). The in vivo study demonstrated good respiratory motion management for all of the selected techniques. It also showed that T2 estimate ranges were different from one method to another. For GRAPPATINI and radial TSE techniques, there were significant differences between all the different types of organs of interest. CONCLUSIONS To perform T2 measurement in the abdominal-pelvic region, one should favor a technique with acceptable acquisition time for clinical use, with proper respiratory motion management, with good repeatability, reproducibility, and precision. In this study, the techniques relying respectively on SE-EPI, radial TSE, and GRAPPATINI appeared as good candidates.
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Keerthivasan MB, Galons JP, Johnson K, Umapathy L, Martin DR, Bilgin A, Altbach MI. Abdominal T2-Weighted Imaging and T2 Mapping Using a Variable Flip Angle Radial Turbo Spin-Echo Technique. J Magn Reson Imaging 2022; 55:289-300. [PMID: 34254382 PMCID: PMC8678192 DOI: 10.1002/jmri.27825] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/22/2021] [Accepted: 06/23/2021] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND T2 mapping is of great interest in abdominal imaging but current methods are limited by low resolution, slice coverage, motion sensitivity, or lengthy acquisitions. PURPOSE Develop a radial turbo spin-echo technique with refocusing variable flip angles (RADTSE-VFA) for high spatiotemporal T2 mapping and efficient slice coverage within a breath-hold and compare to the constant flip angle counterpart (RADTSE-CFA). STUDY TYPE Prospective technical efficacy. SUBJECTS Testing performed on agarose phantoms and 12 patients. Focal liver lesion classification tested on malignant (N = 24) and benign (N = 11) lesions. FIELD STRENGTH/SEQUENCE 1.5 T/RADTSE-VFA, RADTSE-CFA. ASSESSMENT A constrained objective function was used to optimize the refocusing flip angles. Phantom and/or in vivo data were used to assess relative contrast, T2 estimation, specific absorption rate (SAR), and focal liver lesion classification. STATISTICAL TESTS: t-Tests or Mann-Whitney Rank Sum tests were used. RESULTS Phantom data did not show significant differences in mean relative contrast (P = 0.10) and T2 accuracy (P = 0.99) between RADTSE-VFA and RADTSE-CFA. Adding noise caused T2 overestimation predominantly for RADTSE-CFA and low T2 values. In vivo results did not show significant differences in mean spleen-to-liver (P = 0.62) and kidney-to-liver (P = 0.49) relative contrast between RADTSE-VFA and RADTSE-CFA. Mean T2 values were not significantly different between the two techniques for spleen (T2VFA = 109.2 ± 12.3 msec; T2CFA = 110.7 ± 11.1 msec; P = 0.78) and kidney-medulla (T2VFA = 113.0 ± 8.7 msec; T2CFA = 114.0 ± 8.6 msec; P = 0.79). Liver T2 was significantly higher for RADTSE-CFA (T2VFA = 52.6 ± 6.6 msec; T2CFA = 60.4 ± 8.0 msec) consistent with T2 overestimation in the phantom study. Focal liver lesion classification had comparable T2 distributions for RADTSE-VFA and RADTSE-CFA for malignancies (P = 1.0) and benign lesions (P = 0.39). RADTSE-VFA had significantly lower SAR than RADTSE-CFA increasing slice coverage by 1.5. DATA CONCLUSION RADTSE-VFA provided noise-robust T2 estimation compared to the constant flip angle counterpart while generating T2-weighted images with comparable contrast. The VFA scheme minimized SAR improving slice efficiency for breath-hold imaging. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Mahesh B Keerthivasan
- Medical Imaging, University of Arizona, Tucson, Arizona
- Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
| | | | - Kevin Johnson
- Medical Imaging, University of Arizona, Tucson, Arizona
| | - Lavanya Umapathy
- Medical Imaging, University of Arizona, Tucson, Arizona
- Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
| | - Diego R Martin
- Medical Imaging, University of Arizona, Tucson, Arizona
- Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
| | - Ali Bilgin
- Medical Imaging, University of Arizona, Tucson, Arizona
- Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
- Biomedical Engineering, University of Arizona, Tucson, Arizona
| | - Maria I Altbach
- Medical Imaging, University of Arizona, Tucson, Arizona
- Biomedical Engineering, University of Arizona, Tucson, Arizona
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Wiegertjes K, Chan KS, Telgte AT, Gesierich B, Norris DG, Klijn CJ, Duering M, Tuladhar AM, Marques JP, Leeuw FED. Assessing cortical cerebral microinfarcts on iron-sensitive MRI in cerebral small vessel disease. J Cereb Blood Flow Metab 2021; 41:3391-3399. [PMID: 34415209 PMCID: PMC8669205 DOI: 10.1177/0271678x211039609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Recent studies suggest that a subset of cortical microinfarcts may be identifiable on T2* but invisible on T1 and T2 follow-up images. We aimed to investigate whether cortical microinfarcts are associated with iron accumulation after the acute stage. The RUN DMC - InTENse study is a serial MRI study including individuals with cerebral small vessel disease (SVD). 54 Participants underwent 10 monthly 3 T MRIs, including diffusion-weighted imaging, quantitative R1 (=1/T1), R2 (=1/T2), and R2* (=1/T2*) mapping, from which MRI parameters within areas corresponding to microinfarcts and control region of interests (ROIs) were retrieved within 16 participants. Finally, we compared pre- and post-lesional values with repeated measures ANOVA and post-hoc paired t-tests using the mean difference between lesion and control ROI values. We observed 21 acute cortical microinfarcts in 7 of the 54 participants (median age 69 years [IQR 66-74], 63% male). R2* maps demonstrated an increase in R2* values at the moment of the last available follow-up MRI (median [IQR], 5 [5-14] weeks after infarction) relative to prelesional values (p = .08), indicative of iron accumulation. Our data suggest that cortical microinfarcts are associated with increased R2* values, indicative of iron accumulation, possibly due to microhemorrhages, neuroinflammation or neurodegeneration, awaiting histopathological verification.
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Affiliation(s)
- Kim Wiegertjes
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Kwok-Shing Chan
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, the Netherlands
| | - Annemieke Ter Telgte
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Benno Gesierich
- Institute for Stroke and Dementia Research (ISD), University Hospital LMU Munich, Munich, Germany
| | - David G Norris
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, the Netherlands.,Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen, Germany.,MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
| | - Catharina Jm Klijn
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital LMU Munich, Munich, Germany.,Medical Image Analysis Center (MIAC AG), Basel and qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Anil M Tuladhar
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - José P Marques
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, the Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
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Khodarahmi I, Fritz J. The Value of 3 Tesla Field Strength for Musculoskeletal Magnetic Resonance Imaging. Invest Radiol 2021; 56:749-763. [PMID: 34190717 DOI: 10.1097/rli.0000000000000801] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
ABSTRACT Musculoskeletal magnetic resonance imaging (MRI) is a careful negotiation between spatial, temporal, and contrast resolution, which builds the foundation for diagnostic performance and value. Many aspects of musculoskeletal MRI can improve the image quality and increase the acquisition speed; however, 3.0-T field strength has the highest impact within the current diagnostic range. In addition to the favorable attributes of 3.0-T field strength translating into high temporal, spatial, and contrast resolution, many 3.0-T MRI systems yield additional gains through high-performance gradients systems and radiofrequency pulse transmission technology, advanced multichannel receiver technology, and high-end surface coils. Compared with 1.5 T, 3.0-T MRI systems yield approximately 2-fold higher signal-to-noise ratios, enabling 4 times faster data acquisition or double the matrix size. Clinically, 3.0-T field strength translates into markedly higher scan efficiency, better image quality, more accurate visualization of small anatomic structures and abnormalities, and the ability to offer high-end applications, such as quantitative MRI and magnetic resonance neurography. Challenges of 3.0-T MRI include higher magnetic susceptibility, chemical shift, dielectric effects, and higher radiofrequency energy deposition, which can be managed successfully. The higher total cost of ownership of 3.0-T MRI systems can be offset by shorter musculoskeletal MRI examinations, higher-quality examinations, and utilization of advanced MRI techniques, which then can achieve higher gains and value than lower field systems. We provide a practice-focused review of the value of 3.0-T field strength for musculoskeletal MRI, practical solutions to challenges, and illustrations of a wide spectrum of gainful clinical applications.
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Affiliation(s)
- Iman Khodarahmi
- From the Division of Musculoskeletal Radiology, Department of Radiology, NYU Grossman School of Medicine, New York, NY
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Li X, Xie Y, Lu R, Zhang Y, Li Q, Kober T, Hilbert T, Tao H, Chen S. Q-Dixon and GRAPPATINI T2 Mapping Parameters: A Whole Spinal Assessment of the Relationship Between Osteoporosis and Intervertebral Disc Degeneration. J Magn Reson Imaging 2021; 55:1536-1546. [PMID: 34664744 DOI: 10.1002/jmri.27959] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 10/02/2021] [Accepted: 10/04/2021] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND The relationship between osteoporosis and intervertebral disc (IVD) degeneration remains controversial. Novel quantitative Dixon (Q-Dixon) and GRAPPATINI T2 mapping techniques have shown potential for evaluating the biochemical components of the spine. PURPOSE To investigate the correlation of osteoporosis with IVD degeneration in postmenopausal women. STUDY TYPE Prospective. SUBJECTS A total of 105 postmenopausal females (mean age, 65 years; mean body mass index, 26 kg/m2 ). FIELD STRENGTH/SEQUENCE 3 T; sagittal; 6-echo Q-Dixon, multiecho spin-echo GRAPPATINI T2 mapping, turbo spin echo (TSE) T1-weighted and TSE T2-weighted sequences. ASSESSMENT The subjects were divided into normal (N = 47), osteopenia (N = 28), and osteoporosis (N = 30) groups according to quantitative computed tomography examination. The Pfirrmann grade of each IVD was obtained. Region of interest analysis was performed separately by two radiologists (X.L., with 10 years of experience, and S.C., with 20 years of experience) on a fat fraction map and T2 map to calculate the bone marrow fat fraction (BMFF) from the L1 to L5 vertebrae and the T2 values of each adjacent IVD separately. STATISTICAL TESTS One-way analysis of variance, post-hoc comparisons, and Kruskal-Wallis H tests were performed to evaluate the differences in the magnetic resonance imaging parameters between the groups. The relationships between BMFF and the IVD features were analyzed using the Spearman correlation analysis and linear regression models. RESULTS There were significant differences in BMFF among the three groups. The osteoporosis group had higher BMFF values (64.5 ± 5.9%). No significant correlation was found between BMFF and Pfirrmann grade (r = 0.251, P = 0.06). BMFF was significantly negatively correlated with the T2 of the adjacent IVD from L1 to L3 (r = -0.731; r = -0.637; r = -0.547), while significant weak correlations were found at the L4 to L5 levels (r = -0.337; r = -0.278). DATA CONCLUSION This study demonstrated that osteoporosis is associated with IVD degeneration. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 4.
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Affiliation(s)
- Xiangwen Li
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, Shanghai, China
| | - Yuxue Xie
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, Shanghai, China
| | - Rong Lu
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, Shanghai, China
| | - Yuyang Zhang
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, Shanghai, China
| | - Qing Li
- MR Collaborations, Siemens Healthineers Ltd., Shanghai, China
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Hongyue Tao
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, Shanghai, China
| | - Shuang Chen
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, Shanghai, China
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Raudner M, Toth DF, Schreiner MM, Hilbert T, Kober T, Juras V, Windhager R, Trattnig S. Synthetic T 2-weighted images of the lumbar spine derived from an accelerated T 2 mapping sequence: Comparison to conventional T 2w turbo spin echo. Magn Reson Imaging 2021; 84:92-100. [PMID: 34562566 DOI: 10.1016/j.mri.2021.09.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 09/16/2021] [Accepted: 09/16/2021] [Indexed: 12/19/2022]
Abstract
OBJECTIVES To evaluate the diagnostic usefulness of synthetic T2-weighted images of the lumbar spine derived from ten-fold undersampled k-space data using GRAPPATINI, a combination of a model-based approach for rapid T2 and M0 quantification (MARTINI) extended by generalized autocalibrating partial parallel acquistion (GRAPPA). MATERIALS AND METHODS Overall, 58 individuals (26 female, mean age 23.3 ± 8.1 years) were examined at 3 Tesla with sagittal and axial T2w turbo spin echo (TSE) sequences compared to synthetic T2-weighted contrasts derived at identical effective echo times and spatial resolutions. Two blinded readers graded disk degeneration and evaluated the lumbar intervertebral disks for present herniation or annular tear. One reader reassessed all studies after four weeks. Weighted kappa statistics were calculated to assess inter-rater and intra-rater agreement. Also, all studies were segmented manually by one reader to compute contrast ratios (CR) and contrast-to-noise ratios (CNR) of the nucleus pulposus and the annulus fibrosus. RESULTS Overall, the CRT2w was 4.45 ± 1.80 and CRT2synth was 4.71 ± 2.14. Both correlated (rsp = 0.768;p < 0.001) and differed (0.26 ± 1.38;p = 0.002) significantly. The CNRT2w was 1.73 ± 0.52 and CNRT2synth was 1.63 ± 0.50. Both correlated (rsp = 0.875;p < 0.001) and differed (-0.10 ± 0.25;p < 0.001) significantly. The inter-rater agreement was substantial to almost perfect (κ = 0.808-0.925) with the intra-rater agreement also substantial to almost perfect (κ = 0.862-0.963). The area under the curve of the receiver operating characteristics assessing disk herniation or annular tear ranged from 0.787 to 0.892. CONCLUSIONS This study concludes that synthetic images derived by GRAPPATINI can be used for clinical routine assessment with inter-rater and intra-rater agreements comparable to conventional T2w TSE.
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Affiliation(s)
- Marcus Raudner
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria; Christian Doppler Laboratory for Clinical Molecular MR Imaging (MOLIMA), High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria.
| | - Daniel F Toth
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria
| | - Markus M Schreiner
- Department of Orthopaedics and Trauma Surgery, Medical University of Vienna, Austria
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; LTS5, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; LTS5, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Vladimir Juras
- Christian Doppler Laboratory for Clinical Molecular MR Imaging (MOLIMA), High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria; Department of Imaging Methods, Institute of Measurement Science, Bratislava, Slovakia
| | - Reinhard Windhager
- Department of Orthopaedics and Trauma Surgery, Medical University of Vienna, Austria
| | - Siegfried Trattnig
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria; Christian Doppler Laboratory for Clinical Molecular MR Imaging (MOLIMA), High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria
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Gu W, Fang S, Hou X, Ma D, Li S. Exploring diagnostic performance of T2 mapping in diffuse glioma grading. Quant Imaging Med Surg 2021; 11:2943-2954. [PMID: 34249625 DOI: 10.21037/qims-20-916] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 03/12/2021] [Indexed: 11/06/2022]
Abstract
Background To evaluate the diagnostic performance of T2 mapping in differentiating WHO grade II glioma from high-grade glioma (HGG). Methods We conducted a single-center, retrospective diagnostic study. Confirmed diffuse glioma (WHO grade II-IV) patients who underwent post-contrast T1-weighted imaging, T2-weighted imaging, and T2 mapping were included. All diagnoses were based on histological and molecular tests. Seventy-five percent of cases were subsampled to generate receiver operating characteristic (ROC) curves and areas under the curve (AUC), while the remaining cases were used to test the accuracy of T2 mapping. Subsampling was repeated four times. Age, T2 relaxation time, and contrast-enhancement status were used to generate a multivariable ROC curve. T2 relaxation time was also used to generate ROC curves to predict the isocitrate dehydrogenase (IDH) status. Results A total of 159 patients were included in the study. After four repeats of subsampling, the AUCs of the T2 mapping ROC curve were 0.801 (95% CI: 0.724-0.879), 0.795 (95% CI: 0.714-0.875), 0.803 (95% CI: 0.723-0.884), and 0.801 (95% CI: 0.716-0.886), with an average sensitivity of 0.753 and an average specificity of 0.767. When applied to the remaining 25% of cases, the accuracy was 75%, 93.75%, 82.50%, and 71.74%. The AUC of the multivariable ROC was 0.927 (95% CI: 0.882-0.971). IDH-mutant and IDH-wildtype gliomas have significantly different T2 relaxation times (146.28 and 124.10 ms, respectively; P=0.001), and the AUC of IDH-mutant prediction was 0.687 (95% CI: 0.585-0.789). Conclusions Quantitative T2 mapping differentiated WHO grade II glioma from HGG with moderate sensitivity and specificity. Given the advantages of short acquisition times and the absence of a contrast agent, our study suggests the application of T2 mapping in pre-operative glioma grading is feasible.
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Affiliation(s)
- Weibin Gu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shiyuan Fang
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xinyi Hou
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ding Ma
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Shaowu Li
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases, Beijing, China
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Ye Y, Lyu J, Sun W, Lan L, Wang L, Zhang W, Xu H. A multi-dimensional integration (MDI) strategy for MR T 2 * mapping. NMR IN BIOMEDICINE 2021; 34:e4529. [PMID: 33982808 DOI: 10.1002/nbm.4529] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 03/20/2021] [Accepted: 04/03/2021] [Indexed: 06/12/2023]
Abstract
MRI signals are intrinsically multi-dimensional, and signal behavior may be orthogonal among different dimensions. Such dimensional orthogonality can be utilized to eliminate unwanted effects and facilitate mathematical simplicity during image processing for improved outcomes. In this work, we will demonstrate and analyze the principles and performance of a newly developed multi-dimensional integration (MDI) strategy in MR T2 * mapping. By constructing a complex signal function to extract the inter-echo signal changes, MDI solves an optimization problem by processing all signal dimensions (eg echoes, flip angles and coil channels) in one integrative step. MDI was compared with routine curve fitting methods on noise behavior, quantification accuracy and computational efficiency. All methods were tested and compared on simulation, phantom and knee data. Monte Carlo simulations were performed on simulation and all MRI data to investigate noise propagation from k space to T2 * maps. For phantom tests, T2 * values in regions of interest were extracted on a voxel-wise basis and analyzed using a paired t-test between scanning parameters and mapping methods, with p < 0.05 being significantly different. MDI facilitated a straightforward processing procedure, yielding homogeneous, high-signal-to-noise-ratio (SNR) and artifact-free T2 * maps without explicit coil combination or additional measures. Compared with routine fitting methods, MDI offered significantly (p < 0.05) improved SNR and quantitative accuracy/robustness, with two to three orders higher computational efficiency. MDI also represented low-SNR signals with low T2 * values, avoiding misinterpretation with long-T2 * species.
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Affiliation(s)
| | | | - Wenbo Sun
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Lan Lan
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Liang Wang
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | | | - Haibo Xu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
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Wang X, Tan Z, Scholand N, Roeloffs V, Uecker M. Physics-based reconstruction methods for magnetic resonance imaging. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2021; 379:20200196. [PMID: 33966457 PMCID: PMC8107652 DOI: 10.1098/rsta.2020.0196] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/01/2021] [Indexed: 05/03/2023]
Abstract
Conventional magnetic resonance imaging (MRI) is hampered by long scan times and only qualitative image contrasts that prohibit a direct comparison between different systems. To address these limitations, model-based reconstructions explicitly model the physical laws that govern the MRI signal generation. By formulating image reconstruction as an inverse problem, quantitative maps of the underlying physical parameters can then be extracted directly from efficiently acquired k-space signals without intermediate image reconstruction-addressing both shortcomings of conventional MRI at the same time. This review will discuss basic concepts of model-based reconstructions and report on our experience in developing several model-based methods over the last decade using selected examples that are provided complete with data and code. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.
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Affiliation(s)
- Xiaoqing Wang
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
- Partner Site Göttingen, German Centre for Cardiovascular Research (DZHK), Göttingen, Germany
| | - Zhengguo Tan
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
- Partner Site Göttingen, German Centre for Cardiovascular Research (DZHK), Göttingen, Germany
| | - Nick Scholand
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
- Partner Site Göttingen, German Centre for Cardiovascular Research (DZHK), Göttingen, Germany
| | - Volkert Roeloffs
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
| | - Martin Uecker
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
- Partner Site Göttingen, German Centre for Cardiovascular Research (DZHK), Göttingen, Germany
- Cluster of Excellence ‘Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells’ (MBExC), University of Göttingen, Göttingen, Germany
- Campus Institute Data Science (CIDAS), University of Göttingen, Göttingen, Germany
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Hüfken T, Arbogast JM, Bracher AK, Beer M, Neubauer H, Rasche V. Accelerated model-based quantitative diffusion MRI: A feasibility study for musculoskeletal application. Z Med Phys 2021; 32:240-247. [PMID: 34175164 PMCID: PMC9948881 DOI: 10.1016/j.zemedi.2021.04.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 03/17/2021] [Accepted: 04/13/2021] [Indexed: 12/25/2022]
Abstract
PURPOSE To develop a model-based reconstruction technique for diffusion quantification based on accelerated two-dimensional echo planar data, obtained with multiple b-weightings. In combination with a dedicated undersampling pattern, acceleration factors above three were proven feasible in a clinical setting. METHODS The proposed model-based method minimizes a cost function considering the l2-norm of the difference between the Fourier transformation of a synthetic diffusion-model-generated k-space and the measured k-space data. Further regularization is performed by introduction of a total variation (TV) constraint to the cost function. Acceleration is achieved by a non-random undersampling pattern using acceleration factors that correspond to the total number of b-values. A rectangular region of variable size, centered in k-space, remains fully sampled for correction of phase variations, introduced by the different diffusion-encoding strengths. RESULTS Qualitative analysis of the resulting images (S0 and ADC) demonstrates the potential of the suggested undersampling pattern in combination with a model-based iterative reconstruction. An edge analysis highlights the preservation of high-frequency information for all investigated undersampling factors. In comparison to a conventional SENSE-accelerated reconstruction, the quantitative analysis of the ADC maps revealed a significantly (P<0.05) superior performance of the suggested technique, enabling acceleration factors of R=3.65 without compromising diffusion data fidelity. CONCLUSION The presented work shows the potential of model-based ADC quantification, which, in combination with a suited undersampling pattern for multiple b-values, enables more than three-fold acceleration using two-dimensional EPI without sacrificing ADC fidelity.
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Affiliation(s)
- Thomas Hüfken
- Department of Internal Medicine II, Ulm University Medical Center, Ulm, BW, Germany
| | - Jannik M. Arbogast
- Department of Internal Medicine II, Ulm University Medical Center, Ulm, BW, Germany
| | | | - Meinrad Beer
- Department of Radiology, Ulm University Medical Center, Ulm, BW, Germany
| | - Henning Neubauer
- Department of Radiology, Ulm University Medical Center, Ulm, BW, Germany
| | - Volker Rasche
- Department of Internal Medicine II, Ulm University Medical Center, Ulm, BW, Germany.
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Granziera C, Wuerfel J, Barkhof F, Calabrese M, De Stefano N, Enzinger C, Evangelou N, Filippi M, Geurts JJG, Reich DS, Rocca MA, Ropele S, Rovira À, Sati P, Toosy AT, Vrenken H, Gandini Wheeler-Kingshott CAM, Kappos L. Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis. Brain 2021; 144:1296-1311. [PMID: 33970206 PMCID: PMC8219362 DOI: 10.1093/brain/awab029] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 10/25/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022] Open
Abstract
Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.
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Affiliation(s)
- Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Wuerfel
- Medical Image Analysis Center, Basel, Switzerland
- Quantitative Biomedical Imaging Group (qbig), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
- UCL Institutes of Healthcare Engineering and Neurology, London, UK
| | - Massimiliano Calabrese
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Neurology, Department of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Christian Enzinger
- Department of Neurology and Division of Neuroradiology, Medical University of Graz, Graz, Austria
| | - Nikos Evangelou
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, multiple sclerosis Center Amsterdam, Neuroscience Amsterdam, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stefan Ropele
- Neuroimaging Research Unit, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Àlex Rovira
- Section of Neuroradiology (Department of Radiology), Vall d'Hebron University Hospital and Research Institute, Barcelona, Spain
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Ahmed T Toosy
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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Godel M, Andrews DS, Amaral DG, Ozonoff S, Young GS, Lee JK, Wu Nordahl C, Schaer M. Altered Gray-White Matter Boundary Contrast in Toddlers at Risk for Autism Relates to Later Diagnosis of Autism Spectrum Disorder. Front Neurosci 2021; 15:669194. [PMID: 34220428 PMCID: PMC8248433 DOI: 10.3389/fnins.2021.669194] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 05/18/2021] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Recent neuroimaging studies have highlighted differences in cerebral maturation in individuals with autism spectrum disorder (ASD) in comparison to typical development. For instance, the contrast of the gray-white matter boundary is decreased in adults with ASD. To determine how gray-white matter boundary integrity relates to early ASD phenotypes, we used a regional structural MRI index of gray-white matter contrast (GWC) on a sample of toddlers with a hereditary high risk for ASD. MATERIALS AND METHODS We used a surface-based approach to compute vertex-wise GWC in a longitudinal cohort of toddlers at high-risk for ASD imaged twice between 12 and 24 months (n = 20). A full clinical assessment of ASD-related symptoms was performed in conjunction with imaging and again at 3 years of age for diagnostic outcome. Three outcome groups were defined (ASD, n = 9; typical development, n = 8; non-typical development, n = 3). RESULTS ASD diagnostic outcome at age 3 was associated with widespread increases in GWC between age 12 and 24 months. Many cortical regions were affected, including regions implicated in social processing and language acquisition. In parallel, we found that early onset of ASD symptoms (i.e., prior to 18-months) was specifically associated with slower GWC rates of change during the second year of life. These alterations were found in areas mainly belonging to the central executive network. LIMITATIONS Our study is the first to measure maturational changes in GWC in toddlers who developed autism, but given the limited size of our sample results should be considered exploratory and warrant further replication in independent and larger samples. CONCLUSION These preliminary results suggest that ASD is linked to early alterations of the gray-white matter boundary in widespread brain regions. Early onset of ASD diagnosis constitutes an independent clinical parameter associated with a specific corresponding neurobiological developmental trajectory. Altered neural migration and/or altered myelination processes potentially explain these findings.
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Affiliation(s)
- Michel Godel
- Department of Psychiatry, University of Geneva School of Medicine, Geneva, Switzerland
| | - Derek S. Andrews
- Department of Psychiatry and Behavioral Sciences, The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, UC Davis School of Medicine, University of California, Davis, Sacramento, CA, United States
| | - David G. Amaral
- Department of Psychiatry and Behavioral Sciences, The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, UC Davis School of Medicine, University of California, Davis, Sacramento, CA, United States
| | - Sally Ozonoff
- Department of Psychiatry and Behavioral Sciences, The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, UC Davis School of Medicine, University of California, Davis, Sacramento, CA, United States
| | - Gregory S. Young
- Department of Psychiatry and Behavioral Sciences, The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, UC Davis School of Medicine, University of California, Davis, Sacramento, CA, United States
| | - Joshua K. Lee
- Department of Psychiatry and Behavioral Sciences, The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, UC Davis School of Medicine, University of California, Davis, Sacramento, CA, United States
| | - Christine Wu Nordahl
- Department of Psychiatry and Behavioral Sciences, The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, UC Davis School of Medicine, University of California, Davis, Sacramento, CA, United States
| | - Marie Schaer
- Department of Psychiatry, University of Geneva School of Medicine, Geneva, Switzerland
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Raudner M, Schreiner MM, Hilbert T, Kober T, Weber M, Szelényi A, Windhager R, Juras V, Trattnig S. Clinical implementation of accelerated T 2 mapping: Quantitative magnetic resonance imaging as a biomarker for annular tear and lumbar disc herniation. Eur Radiol 2021; 31:3590-3599. [PMID: 33274406 PMCID: PMC8128819 DOI: 10.1007/s00330-020-07538-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 10/20/2020] [Accepted: 11/17/2020] [Indexed: 11/26/2022]
Abstract
OBJECTIVES This study evaluates GRAPPATINI, an accelerated T2 mapping sequence combining undersampling and model-based reconstruction to facilitate the clinical implementation of T2 mapping of the lumbar intervertebral disc. METHODS Fifty-eight individuals (26 females, 32 males, age 23.3 ± 8.0 years) were prospectively examined at 3 T. This cohort study consisted of 19 patients, 20 rowers, and 19 volunteers. GRAPPATINI was conducted with the same parameters as a conventional 2D multi-echo spin-echo (MESE) sequence in 02:27 min instead of 13:18 min. Additional T2 maps were calculated after discarding the first echo (T2-WO1ST) and only using even echoes (T2-EVEN). Segmentation was done on the four most central slices. The resulting T2 values were compared for all four measurements. RESULTS T2-GRAPPATINI, T2-MESE, T2-EVEN, and T2-WO1ST of the nucleus pulposus of normal discs differed significantly from those of bulging discs or herniated discs (all p < 0.001). For the posterior annular region, only T2-GRAPPATINI showed a significant difference (p = 0.011) between normal and herniated discs. There was a significant difference between T2-GRAPPATINI, T2-MESE, T2-EVEN, and T2-WO1ST of discs with and without an annular tear for the nucleus pulposus (all p < 0.001). The nucleus pulposus' T2 at different degeneration states showed significant differences between all group comparisons of Pfirrmann grades for T2-GRAPPATINI (p = 0.000-0.018), T2-MESE (p = 0.000-0.015), T2-EVEN (p = 0.000-0.019), and T2-WO1ST (p = 0.000-0.015). CONCLUSIONS GRAPPATINI facilitates the use of T2 values as quantitative imaging biomarkers to detect disc pathologies such as degeneration, lumbar disc herniation, and annular tears while simultaneously shortening the acquisition time from 13:18 to 2:27 min. KEY POINTS • T2-GRAPPATINI, T2-MESE, T2-EVEN, and T2-WO1ST of the nucleus pulposus of normal discs differed significantly from those of discs with bulging or herniation (all p < 0.001). • The investigated T2 mapping techniques differed significantly in discs with and without annular tearing (all p < 0.001). • The nucleus pulposus' T2 showed significant differences between different stages of degeneration in all group comparisons for T2-GRAPPATINI (p = 0.000-0.018), T2-MESE (p = 0.000-0.015), T2-EVEN (p = 0.000-0.019), and T2-WO1ST (p = 0.000-0.015).
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Affiliation(s)
- Marcus Raudner
- Department of Biomedical Imaging and Image-guided Therapy, High Field MR Center, Medical University of Vienna, Lazarettgasse 14, 1090, Vienna, Austria
- Christian Doppler Laboratory for Clinical Molecular MR Imaging (MOLIMA), Department of Biomedical Imaging and Image-guided Therapy, High Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Markus M Schreiner
- Department of Orthopaedics and Trauma Surgery, Medical University of Vienna, Vienna, Austria
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Michael Weber
- Department of Biomedical Imaging and Image-guided Therapy, High Field MR Center, Medical University of Vienna, Lazarettgasse 14, 1090, Vienna, Austria
| | - Anna Szelényi
- Department of Biomedical Imaging and Image-guided Therapy, High Field MR Center, Medical University of Vienna, Lazarettgasse 14, 1090, Vienna, Austria
| | - Reinhard Windhager
- Department of Orthopaedics and Trauma Surgery, Medical University of Vienna, Vienna, Austria
| | - Vladimir Juras
- Christian Doppler Laboratory for Clinical Molecular MR Imaging (MOLIMA), Department of Biomedical Imaging and Image-guided Therapy, High Field MR Center, Medical University of Vienna, Vienna, Austria
- Department of Imaging Methods, Institute of Measurement Science, Bratislava, Slovakia
| | - Siegfried Trattnig
- Department of Biomedical Imaging and Image-guided Therapy, High Field MR Center, Medical University of Vienna, Lazarettgasse 14, 1090, Vienna, Austria.
- Christian Doppler Laboratory for Clinical Molecular MR Imaging (MOLIMA), Department of Biomedical Imaging and Image-guided Therapy, High Field MR Center, Medical University of Vienna, Vienna, Austria.
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Cao X, Wang K, Liao C, Zhang Z, Srinivasan Iyer S, Chen Z, Lo WC, Liu H, He H, Setsompop K, Zhong J, Bilgic B. Efficient T 2 mapping with blip-up/down EPI and gSlider-SMS (T 2 -BUDA-gSlider). Magn Reson Med 2021; 86:2064-2075. [PMID: 34046924 DOI: 10.1002/mrm.28872] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Revised: 05/10/2021] [Accepted: 05/10/2021] [Indexed: 12/22/2022]
Abstract
PURPOSE To rapidly obtain high isotropic-resolution T2 maps with whole-brain coverage and high geometric fidelity. METHODS A T2 blip-up/down EPI acquisition with generalized slice-dithered enhanced resolution (T2 -BUDA-gSlider) is proposed. A RF-encoded multi-slab spin-echo (SE) EPI acquisition with multiple TEs was developed to obtain high SNR efficiency with reduced TR. This was combined with an interleaved 2-shot EPI acquisition using blip-up/down phase encoding. An estimated field map was incorporated into the joint multi-shot EPI reconstruction with a structured low rank constraint to achieve distortion-free and robust reconstruction for each slab without navigation. A Bloch simulated subspace model was integrated into gSlider reconstruction and used for T2 quantification. RESULTS In vivo results demonstrated that the T2 values estimated by the proposed method were consistent with gold standard spin-echo acquisition. Compared to the reference 3D fast spin echo (FSE) images, distortion caused by off-resonance and eddy current effects were effectively mitigated. CONCLUSION BUDA-gSlider SE-EPI acquisition and gSlider-subspace joint reconstruction enabled distortion-free whole-brain T2 mapping in 2 min at ~1 mm3 isotropic resolution, which could bring significant benefits to related clinical and neuroscience applications.
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Affiliation(s)
- Xiaozhi Cao
- Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang, China.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Kang Wang
- Department of Neurology, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Congyu Liao
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Zijing Zhang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China
| | - Siddharth Srinivasan Iyer
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Zhifeng Chen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA.,School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
| | - Wei-Ching Lo
- Siemens Medical Solutions, Boston, Massachusetts, USA
| | - Huafeng Liu
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang, China
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA.,Harvard-MIT Department of Health Sciences and Technology, Cambridge, Massachusetts, USA
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang, China.,Department of Imaging Sciences, University of Rochester, Rochester, New York, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA.,Harvard-MIT Department of Health Sciences and Technology, Cambridge, Massachusetts, USA
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42
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Rowley CD, Campbell JSW, Wu Z, Leppert IR, Rudko DA, Pike GB, Tardif CL. A model-based framework for correcting B 1 + inhomogeneity effects in magnetization transfer saturation and inhomogeneous magnetization transfer saturation maps. Magn Reson Med 2021; 86:2192-2207. [PMID: 33956348 DOI: 10.1002/mrm.28831] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 03/08/2021] [Accepted: 04/16/2021] [Indexed: 01/03/2023]
Abstract
PURPOSE In this work, we propose that Δ B 1 + -induced errors in magnetization transfer (MT) saturation (MTsat ) maps can be corrected with use of an R1 and B 1 + map and through numerical simulations of the sequence. THEORY AND METHODS One healthy subject was scanned at 3.0T using a partial quantitative MT protocol to estimate the relationship between observed R1 (R1,obs ) and apparent bound pool size ( M 0 , a p p B ) in the brain. MTsat values were simulated for a range of B 1 + , R1,obs , and M 0 , a p p B . An equation was fit to the simulated MTsat , then a linear relationship between R1,obs and M 0 , a p p B was generated. These results were used to generate correction factor maps for the MTsat acquired from single-point data. The proposed correction was compared to an empirical correction factor with different MT-preparation schemes. RESULTS M 0 , a p p B was highly correlated with R1,obs (r > 0.96), permitting the use of R1,obs to estimate M 0 , a p p B for B 1 + correction. All B 1 + corrected MTsat maps displayed a decreased correlation with B 1 + compared to uncorrected MTsat and MTsat corrected with an empirical factor in the corpus callosum. There was good agreement between the proposed approach and the empirical correction with radiofrequency saturation at 2 kHz, with larger deviations seen when using saturation pulses further off-resonance and in inhomogeneous (ih) MTsat maps. CONCLUSION The proposed correction decreases the dependence of MTsat on B 1 + inhomogeneities. Furthermore, this flexible framework permits the use of different saturation protocols, making it useful for correcting B 1 + inhomogeneities in ihMT.
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Affiliation(s)
- Christopher D Rowley
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Jennifer S W Campbell
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Zhe Wu
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.,Techna Institute, University Health Network, Toronto, Ontario, Canada
| | - Ilana R Leppert
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - David A Rudko
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.,Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Gilbert Bruce Pike
- Hotchkiss Brain Institute and Departments of Radiology and Clinical Neuroscience, University of Calgary, Calgary, Canada
| | - Christine L Tardif
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.,Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
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Weidensteiner C, Madoerin P, Deligianni X, Haas T, Bieri O, Akinci D'Antonoli T, Bracht-Schweizer K, Romkes J, De Pieri E, Santini F, Rutz E, Brunner R, Garcia M. Quantification and Monitoring of the Effect of Botulinum Toxin A on Paretic Calf Muscles of Children With Cerebral Palsy With MRI: A Preliminary Study. Front Neurol 2021; 12:630435. [PMID: 33935939 PMCID: PMC8085320 DOI: 10.3389/fneur.2021.630435] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 03/01/2021] [Indexed: 11/23/2022] Open
Abstract
Background: Muscles from patients with cerebral palsy (CP) are often spastic and form contractures that limit the range of motion. Injections of botulinum toxin A (BTX) into the calf muscles are an important treatment for functional equinus; however, improvement in gait function is not always achieved. BTX is also used to test muscle weakening for risk evaluation of muscle lengthening surgery. Our aim was to assess the effect of BTX over time on calf muscle properties in pediatric CP patients with MRI. Material and Methods: Six toe-walking CP patients (mean age 11.6 years) with indication for lengthening surgery were prospectively enrolled and received BTX injections into the gastrocnemius and soleus muscles. MRI scans at 3T of the lower legs and clinical examinations were performed pre-BTX, 6 weeks (6w), and 12 weeks (12w) post-BTX. A fat-suppressed 2D multi-spin-echo sequence was used to acquire T2 maps and for segmentation. Fat fraction maps were calculated from 3D multi-echo Dixon images. Diffusion tensor imaging (DTI) with a 2D echo-planar imaging (EPI) sequence yielded maps of the mean apparent diffusion coefficient (ADC) and of the fractional anisotropy (FA). Hyperintense regions of interest (ROIs) on the T2-weighted (T2w) images at 6w were segmented in treated muscles. Mean values of T2, fat fraction, ADC, and FA were calculated in hyperintense ROIs and in reference ROIs in non-treated muscles. Results: Hyperintensity on T2w scans and increased T2 (group mean ± standard deviation: 35 ± 1 ms pre-BTX, 45 ± 2 ms at 6w, and 44 ± 2 ms at 12w) were observed in all patients at the injection sites. The T2 increase was spatially limited to parts of the injected muscles. FA increased (0.30 ± 0.03 pre-BTX, 0.34 ± 0.02 at 6w, and 0.36 ± 0.03 at 12w) while ADC did not change in hyperintense ROIs, indicating a BTX-induced increase in extracellular space and a simultaneous decrease of muscle fiber diameter. Fat fraction showed a trend for increase at 12w. Mean values in reference ROIs remained unchanged. Conclusion: MRI showed limited spatial distribution of the BTX-induced effects in pediatric CP patients. It could be a promising non-invasive tool for future studies to test BTX treatment protocols.
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Affiliation(s)
- Claudia Weidensteiner
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Philipp Madoerin
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland
| | - Xeni Deligianni
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Tanja Haas
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland
| | - Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Tugba Akinci D'Antonoli
- Department of Radiology, University Hospital of Basel, Basel, Switzerland.,Department of Radiology, University Children's Hospital Basel, Basel, Switzerland
| | | | - Jacqueline Romkes
- Laboratory for Movement Analysis, University Children's Hospital Basel, Basel, Switzerland
| | - Enrico De Pieri
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland.,Laboratory for Movement Analysis, University Children's Hospital Basel, Basel, Switzerland
| | - Francesco Santini
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Erich Rutz
- Murdoch Children's Research Insitute, The University of Melbourne, Pediatric Orthopedic Department, The Royal Children's Hospital, Parkville, VIC, Australia.,Faculty of Medicine, The University of Basel, Basel, Switzerland
| | - Reinald Brunner
- Laboratory for Movement Analysis, University Children's Hospital Basel, Basel, Switzerland.,Department of Orthopedic Surgery, University Children's Hospital Basel, Basel, Switzerland
| | - Meritxell Garcia
- Department of Radiology, Division of Neuroradiology, University Hospital of Basel, Basel, Switzerland
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Rapid Musculoskeletal MRI in 2021: Clinical Application of Advanced Accelerated Techniques. AJR Am J Roentgenol 2021; 216:718-733. [DOI: 10.2214/ajr.20.22902] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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45
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Hu H, Chen HH, Chen W, Wu Q, Chen L, Zhu H, Shi HB, Xu XQ, Wu FY. Thyroid-Associated Ophthalmopathy: Preliminary Study Using T2 Mapping to Characterize Intraorbital Optic Nerve Changes Before Dysthyroid Optic Neuropathy. Endocr Pract 2021; 27:191-197. [PMID: 33630733 DOI: 10.1016/j.eprac.2020.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 08/25/2020] [Accepted: 09/15/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE To evaluate the performance of T2 mapping in detecting intraorbital optic nerve (ON) changes in patients with thyroid-associated ophthalmopathy (TAO) before the onset of dysthyroid optic neuropathy (DON). METHODS Thirty-five patients with TAO and without DON (21 active, 14 inactive) and 21 healthy controls (HCs) were enrolled. Magnetic resonance imaging-derived parameters of T2 relaxation time (T2RT) at the intraorbital ON, extraocular muscle (EOM), orbital fat, exophthalmos, summed thickness of EOMs, orbital fat thickness, and clinical variables were compared. Correlations between T2RT at the ON and other variables were assessed. RESULTS Patients with TAO showed significantly higher T2RTs at the intraorbital ON than HCs (P < .001). Patients with active TAO had significantly higher T2RTs than those with inactive TAO and HCs (P < .001). Differences between patients with inactive TAO and HCs were insignificant (P > .05/3). T2RT at the intraorbital ON was positively correlated with clinical activity score, modified NOSPECS score, T2RT at EOM, exophthalmos, and summed thickness of EOMs in the TAO group (P ≤ .003) and negatively correlated with visual acuity (P = .033) and visual field indices (P = .030) in patients with active TAO. A T2RT cutoff of 82.9 ms for the intraorbital ON distinguished active TAO and healthy eyes optimally (area under the curve, 0.800; sensitivity, 85.7%; specificity, 64.3%). CONCLUSION T2RT detects disturbance in the intraorbital ON in patients with TAO, especially active TAO, before DON develops. T2 mapping has a potential for noninvasive evaluation of ON changes in patients with TAO.
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Affiliation(s)
- Hao Hu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Huan-Huan Chen
- Department of Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Wen Chen
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qian Wu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Lu Chen
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hui Zhu
- Department of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hai-Bin Shi
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiao-Quan Xu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
| | - Fei-Yun Wu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
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Crombé A, Buy X, Han F, Toupin S, Kind M. Assessment of Repeatability, Reproducibility, and Performances of T2 Mapping-Based Radiomics Features: A Comparative Study. J Magn Reson Imaging 2021; 54:537-548. [PMID: 33594768 DOI: 10.1002/jmri.27558] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 01/26/2021] [Accepted: 01/26/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Magnetic resonance imaging (MRI)-based radiomics features (RFs) quantify tumors radiological phenotypes but are sensitive to postprocessing parameters, including the intensity harmonization technique (IHT), while mappings enable objective quantitative assessment. PURPOSE To investigate whether T2 mapping could improve repeatability, reproducibility, and performances of radiomics compared to conventional T2-weighted imaging (T2WI). STUDY TYPE Prospective. SUBJECTS Twenty-six healthy adults. FIELD STRENGTH/SEQUENCE Respiratory-trigged radial turbo spin echo (TSE) multiecho T2 mapping (prototype) and conventional TSE T2WI of the abdomen were acquired twice at 1.5 T. ASSESSMENT T2 maps were reconstructed using a two-parameter exponential fitting model. Volumes-of-interest (VOIs) were manually drawn in six tissues: liver, kidney, pancreas, muscle, bone, and spleen. After co-registration, conventional T2WIs were processed with two IHTs (standardization [std] and histogram-matching [HM]) resulting in four paired input image types: initial T2WI, T2WIstd , T2WIHM , and T2-map. VOIs were propagated to extract 45 RFs from MRI-1 and MRI-2 of each image type (LIFEx, v5.10). STATISTICAL TESTS Influence of the input data type on RF values was evaluated with analysis of variance. RFs test-retest repeatability and reproducibility over multiple segmentations were evaluated with intra-class correlation coefficient (ICC). Correlations between k-means clusters and the six tissues depending on the RFs dataset were investigated with adjusted-Rand-index (ARI). RESULTS About 41 of 45 (91.1%) RFs were significantly influenced by the input image type (P values < 0.05), which was the most influential factor on repeatability of RFs (P-value < 0.05). Repeatability ICCs from T2-map displayed intermediate values between the initial T2WI (range: 0.407-0.736) and the T2WIHM (range: 0.724-0.817). The number of RFs with interobserver and intraobserver reproducibility ICCs ≥ 0.90 was 37/45 (82.2%) for T2WIHM , 33/45 (73.3%) for T2WIstd , 31/45 (68.9%) for T2 map, and 25/45 (55.6%) for the initial T2WI. T2 map provided the best tissue discrimination (ARI = 0.414 vs. 0.157 with T2WIHM ). DATA CONCLUSION T2 mapping provided RFs with moderate to substantial repeatability and reproducibility ICCs, along with the most preserved discriminative information. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: 1.
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Affiliation(s)
- Amandine Crombé
- Department of Oncologic Imaging, Institut Bergonié, Comprehensive Cancer Center of Nouvelle-Aquitaine, Bordeaux, France.,Bordeaux University, Bordeaux, France.,Modelisation in Oncology (MOnc) Team, INRIA Bordeaux-Sud-Ouest, CNRS UMR 5251, Talence, France
| | - Xavier Buy
- Department of Oncologic Imaging, Institut Bergonié, Comprehensive Cancer Center of Nouvelle-Aquitaine, Bordeaux, France
| | - Fei Han
- Siemens Medical Solutions USA, Los Angeles, California, USA
| | | | - Michèle Kind
- Department of Oncologic Imaging, Institut Bergonié, Comprehensive Cancer Center of Nouvelle-Aquitaine, Bordeaux, France
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Argentieri EC, Tan ET, Whang JS, Queler SC, Feinberg JH, Lin B, Sneag DB. Quantitative T 2 -mapping magnetic resonance imaging for assessment of muscle motor unit recruitment patterns. Muscle Nerve 2021; 63:703-709. [PMID: 33501678 DOI: 10.1002/mus.27186] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 01/17/2021] [Accepted: 01/24/2021] [Indexed: 12/21/2022]
Abstract
INTRODUCTION In this study, we aimed to determine whether muscle transverse relaxation time (T2 ) magnetic resonance (MR) mapping results correlate with motor unit loss, as defined by motor unit recruitment patterns on electromyography (EMG). METHODS EMG and 3-Tesla MRI exams were acquired no more than 31 days apart in subjects referred for peripheral nerve MRI. Two musculoskeletal radiologists qualitatively graded T2 -weighted, fat-suppressed sequences for severity of muscle edema-like patterns and manually placed regions of interest within muscles to obtain T2 values from T2 -mapping sequences. Concordance was calculated between qualitative and quantitative MR grades and EMG recruitment categories (none, discrete, decreased) as well as interobserver agreement for both MR grades. RESULTS Thirty-four muscles (21 abnormal, 13 control) were assessed in 13 subjects (5 females and 8 males; mean age, 46 years) with 14 EMG-MRI pairs. T2 -relaxation times were significantly (P < .001) increased in all EMG recruitment categories compared with control muscles. T2 differences were not significant between EMG grades of motor unit recruitment (P = .151-.702). T2 and EMG score concordance was acceptable (Harrell's concordance index [c index]: rater A, 0.71; 95% confidence interval [CI], 0.51-0.87; rater B, 0.77; 95% CI, 0.57-0.91). Qualitative MRI and EMG score concordance was poor to acceptable (c index: rater A, 0.60; 95% CI, 0.50-0.79; rater B, 0.72; 95% CI, 0.55-0.89). T2 values had moderate-to-substantial ability to distinguish between absent vs incomplete (ie, decreased or discrete) motor unit recruitment (c index: rater A, 0.78; 95% CI, 0.50-1.00; rater B, 0.86; 95% CI, 0.57-1.00). DISCUSSION Quantitative T2 MR muscle mapping is a promising tool for noninvasive evaluation of the degree of motor unit recruitment loss.
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Affiliation(s)
- Erin C Argentieri
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, New York, USA
| | - Ek Tsoon Tan
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, New York, USA
| | - Jeremy S Whang
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, New York, USA
| | - Sophie C Queler
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, New York, USA
| | - Joseph H Feinberg
- Departments of Physiatry and Sports Medicine, Hospital for Special Surgery, New York, New York, USA
| | - Bin Lin
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, New York, USA
| | - Darryl B Sneag
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, New York, USA
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Sneag DB, Tan ET. Can Quantitative MRI Be Used to Differentiate Physiologic Changes Behind Muscle Weakness in Type 2 Diabetes Mellitus? Radiology 2020; 297:620-621. [PMID: 33064035 PMCID: PMC7706872 DOI: 10.1148/radiol.2020203768] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 09/22/2020] [Accepted: 09/24/2020] [Indexed: 11/11/2022]
Affiliation(s)
- Darryl B. Sneag
- From the MRI Laboratory, Hospital for Special Surgery, 535 E 70th St, New York, NY 10021
| | - Ek T. Tan
- From the MRI Laboratory, Hospital for Special Surgery, 535 E 70th St, New York, NY 10021
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Alessandrino F. Editorial for: “Novel
T2
Mapping for Evaluating Cervical Cancer Features by Providing Quantitative
T2
Maps and Synthetic Morphologic Images: A Preliminary Study”. J Magn Reson Imaging 2020; 52:1870-1871. [DOI: 10.1002/jmri.27296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 06/05/2020] [Indexed: 11/07/2022] Open
Affiliation(s)
- Francesco Alessandrino
- Department of Radiology Brigham and Women's Hospital, Harvard Medical School Boston Massachusetts USA
- Department of Diagnostic Radiology University of Miami Health System, Leonard M. Miller School of Medicine Miami Florida USA
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Chen W, Hu H, Chen HH, Su GY, Yang T, Xu XQ, Wu FY. Utility of T2 mapping in the staging of thyroid-associated ophthalmopathy: efficiency of region of interest selection methods. Acta Radiol 2020; 61:1512-1519. [PMID: 32053002 DOI: 10.1177/0284185120905032] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Discriminating the stage of thyroid-associated ophthalmopathy (TAO) is crucial for the treatment strategy and prognosis prediction. Utility of conventional magnetic resonance imaging in the disease staging is limited. PURPOSE To investigate the performance of T2 mapping based on different region of interest (ROI) selection methods in the staging of TAO. MATERIAL AND METHODS Thirty-two patients with TAO were retrospectively enrolled. Two radiologists independently measured the T2 relaxation time (T2RT) of extraocular muscles using two different ROIs (hotspot [ROIHS]: T2RT-hot; single-slice [ROISS]: T2RT-mean, T2RT-max, T2RT-min). Independent-samples t test, Wilcoxon signed rank test, Spearman correlation analysis, receiver operating characteristic (ROC) curves analyses, multiple ROC comparisons, and intra-class correlation coefficient (ICC) were used for statistical analyses. RESULTS No significant difference was found in the measuring time between ROIHS and ROISS methods (P = 0.066). T2RT-mean demonstrated the highest ICC for measurement, followed by T2RT-max and T2RT-min, and T2RT-hot showed the poorest reproducibility. Active TAOs showed significantly higher values for all the T2RTs than inactive mimics (all P < 0.001). Significant positive correlations were found between T2RTs and CAS (all P < 0.005). T2RT-hot and T2RT-max showed significantly higher areas under the curve than that of T2RT-mean (P = 0.013 and 0.024, respectively), while the difference between T2RT-hot and T2RT-max was not significant (P = 0.970). CONCLUSION The T2RTs derived from both ROI selection methods could be useful for the staging of TAO. The results of measuring time, reproducibility, and diagnostic performance suggest that T2RT-max would be the optimal indicator for staging.
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Affiliation(s)
- Wen Chen
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Hao Hu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Huan-Huan Chen
- Department of Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Guo-Yi Su
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Tao Yang
- Department of Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Xiao-Quan Xu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Fei-Yun Wu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
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