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Voronkova E, Melnikov I, Manzhurtsev A, Bozhko O, Vorobyev D, Akhadov T, Menshchikov P. T 2 Mapping of Patellar Cartilage After a Single First-Time Episode of Traumatic Lateral Patellar Dislocation. J Magn Reson Imaging 2024; 59:865-876. [PMID: 37316971 DOI: 10.1002/jmri.28857] [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: 02/27/2023] [Revised: 05/29/2023] [Accepted: 05/30/2023] [Indexed: 06/16/2023] Open
Abstract
BACKGROUND In most cases, lateral patellar dislocation (LPD) is accompanied by chondral injury and may initiate gradual degeneration of patellar cartilage, which might be detected with a T2 mapping, a well-established method for cartilage lesions assessment. PURPOSE To examine short-term consequences of single first-time LPD in teenagers by T2 mapping of the patellar-cartilage state. STUDY TYPE Prospective. POPULATION 95 patients (mean age: 15.1 ± 2.3; male/female: 46/49) with first-time, complete, traumatic LPD and 51 healthy controls (mean age: 14.7 ± 2.2, male/female: 29/22). FIELD STRENGTH/SEQUENCE 3.0 T; axial T2 mapping acquired using a 2D turbo spin-echo sequence. ASSESSMENT MRI examination was conducted 2-4 months after first LPD. T2 values were calculated in manually segmented cartilage area via averaging over three middle level slices in six cartilage regions: deep, intermediate, superficial layers, and medial lateral parts. STATISTICAL TESTS ANOVA analysis with Tukey's multiple comparison test, one-vs.-rest logistic regression analysis. The threshold of significance was set at P < 0.05. RESULTS In lateral patellar cartilage, a significant increase in T2 values was found in deep and intermediate layers in both patient groups with mild (deep: 34.7 vs. 31.3 msec, intermediate: 38.7 vs. 34.6 msec, effect size = 0.55) and severe (34.8 vs. 31.3 msec, 39.1 vs. 34.6 msec, 0.55) LPD consequences as compared to controls. In the medial facet, only severe cartilage damage showed significant prolongation of T2 times in the deep layer (34.3 vs. 30.7 msec, 0.55). No significant changes in T2 values were found in the lateral superficial layer (P = 0.99), whereas mild chondromalacia resulted in a significant decrease of T2 in the medial superficial layer (41.0 vs. 43.8 msec, 0.55). DATA CONCLUSION The study revealed substantial difference in T2 changes after LPD between medial and lateral areas of patellar cartilage. EVIDENCE LEVEL 2 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Elena Voronkova
- Clinical and Research Institute of Emergency Pediatric Surgery and Trauma, Moscow, Russian Federation
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Moscow, Russian Federation
| | - Ilya Melnikov
- Clinical and Research Institute of Emergency Pediatric Surgery and Trauma, Moscow, Russian Federation
| | - Andrei Manzhurtsev
- Clinical and Research Institute of Emergency Pediatric Surgery and Trauma, Moscow, Russian Federation
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Moscow, Russian Federation
| | - Olga Bozhko
- Clinical and Research Institute of Emergency Pediatric Surgery and Trauma, Moscow, Russian Federation
| | - Denis Vorobyev
- Clinical and Research Institute of Emergency Pediatric Surgery and Trauma, Moscow, Russian Federation
| | - Tolib Akhadov
- Clinical and Research Institute of Emergency Pediatric Surgery and Trauma, Moscow, Russian Federation
| | - Petr Menshchikov
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Moscow, Russian Federation
- LLC Philips, Moscow, Russian Federation
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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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Kuhn S, Bustin A, Lamri-Senouci A, Rumac S, Ledoux JB, Colotti R, Bastiaansen JAM, Yerly J, Favre J, Omoumi P, van Heeswijk RB. Improved accuracy and precision of fat-suppressed isotropic 3D T2 mapping MRI of the knee with dictionary fitting and patch-based denoising. Eur Radiol Exp 2023; 7:25. [PMID: 37211577 DOI: 10.1186/s41747-023-00339-8] [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: 12/21/2022] [Accepted: 03/15/2023] [Indexed: 05/23/2023] Open
Abstract
PURPOSE To develop an isotropic three-dimensional (3D) T2 mapping technique for the quantitative assessment of the composition of knee cartilage with high accuracy and precision. METHODS A T2-prepared water-selective isotropic 3D gradient-echo pulse sequence was used to generate four images at 3 T. These were used for three T2 map reconstructions: standard images with an analytical T2 fit (AnT2Fit); standard images with a dictionary-based T2 fit (DictT2Fit); and patch-based-denoised images with a dictionary-based T2 fit (DenDictT2Fit). The accuracy of the three techniques was first optimized in a phantom study against spin-echo imaging, after which knee cartilage T2 values and coefficients of variation (CoV) were assessed in ten subjects in order to establish accuracy and precision in vivo. Data given as mean ± standard deviation. RESULTS After optimization in the phantom, whole-knee cartilage T2 values of the healthy volunteers were 26.6 ± 1.6 ms (AnT2Fit), 42.8 ± 1.8 ms (DictT2Fit, p < 0.001 versus AnT2Fit), and 40.4 ± 1.7 ms (DenDictT2Fit, p = 0.009 versus DictT2Fit). The whole-knee T2 CoV reduced from 51.5% ± 5.6% to 30.5 ± 2.4 and finally to 13.1 ± 1.3%, respectively (p < 0.001 between all). The DictT2Fit improved the data reconstruction time: 48.7 ± 11.3 min (AnT2Fit) versus 7.3 ± 0.7 min (DictT2Fit, p < 0.001). Very small focal lesions were observed in maps generated with DenDictT2Fit. CONCLUSIONS Improved accuracy and precision for isotropic 3D T2 mapping of knee cartilage were demonstrated by using patch-based image denoising and dictionary-based reconstruction. KEY POINTS • Dictionary T2 fitting improves the accuracy of three-dimensional (3D) knee T2 mapping. • Patch-based denoising results in high precision in 3D knee T2 mapping. • Isotropic 3D knee T2 mapping enables the visualization of small anatomical details.
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Affiliation(s)
- Simon Kuhn
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Aurélien Bustin
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, France
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, INSERM U1045, Centre de Recherche Cardio-Thoracique de Bordeaux, Université de Bordeaux, Bordeaux, France
| | - Aicha Lamri-Senouci
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Simone Rumac
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Jean-Baptiste Ledoux
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Center for BioMedical Imaging (CIBM), Lausanne, Switzerland
| | - Roberto Colotti
- Biomedical Data Science Center (BDSC), Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Jessica A M Bastiaansen
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Bern University Hospital, University of Bern, Inselspital, Switzerland
- Translation Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Jérôme Yerly
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Center for BioMedical Imaging (CIBM), Lausanne, Switzerland
| | - Julien Favre
- Department of Musculoskeletal Medicine, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- The Sense Innovation and Research Center, Lausanne and Sion, Switzerland
| | - Patrick Omoumi
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Ruud B van Heeswijk
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
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D'Angelo T, Caudo D, Blandino A, Albrecht MH, Vogl TJ, Gruenewald LD, Gaeta M, Yel I, Koch V, Martin SS, Lenga L, Muscogiuri G, Sironi S, Mazziotti S, Booz C. Artificial intelligence, machine learning and deep learning in musculoskeletal imaging: Current applications. JOURNAL OF CLINICAL ULTRASOUND : JCU 2022; 50:1414-1431. [PMID: 36069404 DOI: 10.1002/jcu.23321] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/18/2022] [Accepted: 08/20/2022] [Indexed: 06/15/2023]
Abstract
Artificial intelligence is rapidly expanding in all technological fields. The medical field, and especially diagnostic imaging, has been showing the highest developmental potential. Artificial intelligence aims at human intelligence simulation through the management of complex problems. This review describes the technical background of artificial intelligence, machine learning, and deep learning. The first section illustrates the general potential of artificial intelligence applications in the context of request management, data acquisition, image reconstruction, archiving, and communication systems. In the second section, the prospective of dedicated tools for segmentation, lesion detection, automatic diagnosis, and classification of musculoskeletal disorders is discussed.
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Affiliation(s)
- Tommaso D'Angelo
- Department of Biomedical Sciences and Morphological and Functional Imaging, University Hospital Messina, Messina, Italy
- Department of Radiology and Nuclear Medicine, Rotterdam, Netherlands
| | - Danilo Caudo
- Department of Biomedical Sciences and Morphological and Functional Imaging, University Hospital Messina, Messina, Italy
- Department or Radiology, IRRCS Centro Neurolesi "Bonino Pulejo", Messina, Italy
| | - Alfredo Blandino
- Department of Biomedical Sciences and Morphological and Functional Imaging, University Hospital Messina, Messina, Italy
| | - Moritz H Albrecht
- Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Thomas J Vogl
- Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Leon D Gruenewald
- Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Michele Gaeta
- Department of Biomedical Sciences and Morphological and Functional Imaging, University Hospital Messina, Messina, Italy
| | - Ibrahim Yel
- Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Vitali Koch
- Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Simon S Martin
- Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Lukas Lenga
- Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Giuseppe Muscogiuri
- School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy
- Department of Radiology, IRCCS Istituto Auxologico Italiano, San Luca Hospital, Milan, Italy
| | - Sandro Sironi
- School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy
- Department of Radiology, ASST Papa Giovanni XXIII Hospital, Bergamo, Italy
| | - Silvio Mazziotti
- Department of Biomedical Sciences and Morphological and Functional Imaging, University Hospital Messina, Messina, Italy
| | - Christian Booz
- Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany
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Lombardi AF, Ma Y, Jang H, Jerban S, Tang Q, Searleman AC, Meyer RS, Du J, Chang EY. AcidoCEST-UTE MRI Reveals an Acidic Microenvironment in Knee Osteoarthritis. Int J Mol Sci 2022; 23:4466. [PMID: 35457284 PMCID: PMC9027981 DOI: 10.3390/ijms23084466] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 04/08/2022] [Accepted: 04/13/2022] [Indexed: 02/01/2023] Open
Abstract
A relationship between an acidic pH in the joints, osteoarthritis (OA), and pain has been previously demonstrated. Acidosis Chemical Exchange Saturation Transfer (acidoCEST) indirectly measures the extracellular pH through the assessment of the exchange of protons between amide groups on iodinated contrast agents and bulk water. It is possible to estimate the extracellular pH in the osteoarthritic joint using acidoCEST MRI. However, conventional MR sequences cannot image deep layers of cartilage, meniscus, ligaments, and other musculoskeletal tissues that present with short echo time and fast signal decay. Ultrashort echo time (UTE) MRI, on the other hand, has been used successfully to image those joint tissues. Here, our goal is to compare the pH measured in the knee joints of volunteers without OA and patients with severe OA using acidoCEST-UTE MRI. Patients without knee OA and patients with severe OA were examined using acidoCEST-UTE MRI and the mean pH of cartilage, meniscus, and fluid was calculated. Additionally, the relationship between the pH measurements and the Knee Injury and Osteoarthritis Outcome Score (KOOS) was investigated. AcidoCEST-UTE MRI can detect significant differences in the pH of knee cartilage, meniscus, and fluid between joints without and with OA, with OA showing lower pH values. In addition, symptoms and knee-joint function become worse at lower pH measurements.
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Affiliation(s)
- Alecio F. Lombardi
- Research Service, Veterans Affairs San Diego Healthcare System, San Diego, CA 92161, USA; (Q.T.); (E.Y.C.)
- Department of Radiology, University of California San Diego, San Diego, CA 92161, USA; (Y.M.); (H.J.); (S.J.); (A.C.S.); (J.D.)
| | - Yajun Ma
- Department of Radiology, University of California San Diego, San Diego, CA 92161, USA; (Y.M.); (H.J.); (S.J.); (A.C.S.); (J.D.)
| | - Hyungseok Jang
- Department of Radiology, University of California San Diego, San Diego, CA 92161, USA; (Y.M.); (H.J.); (S.J.); (A.C.S.); (J.D.)
| | - Saeed Jerban
- Department of Radiology, University of California San Diego, San Diego, CA 92161, USA; (Y.M.); (H.J.); (S.J.); (A.C.S.); (J.D.)
| | - Qingbo Tang
- Research Service, Veterans Affairs San Diego Healthcare System, San Diego, CA 92161, USA; (Q.T.); (E.Y.C.)
- Department of Radiology, University of California San Diego, San Diego, CA 92161, USA; (Y.M.); (H.J.); (S.J.); (A.C.S.); (J.D.)
| | - Adam C. Searleman
- Department of Radiology, University of California San Diego, San Diego, CA 92161, USA; (Y.M.); (H.J.); (S.J.); (A.C.S.); (J.D.)
| | - Robert Scott Meyer
- Orthopaedic Surgery Service, Veterans Affairs San Diego Healthcare System, San Diego, CA 92161, USA;
| | - Jiang Du
- Department of Radiology, University of California San Diego, San Diego, CA 92161, USA; (Y.M.); (H.J.); (S.J.); (A.C.S.); (J.D.)
| | - Eric Y. Chang
- Research Service, Veterans Affairs San Diego Healthcare System, San Diego, CA 92161, USA; (Q.T.); (E.Y.C.)
- Department of Radiology, University of California San Diego, San Diego, CA 92161, USA; (Y.M.); (H.J.); (S.J.); (A.C.S.); (J.D.)
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El-Liethy NE, Kamal HA. Advanced compositional imaging T2 mapping sequence in detection of stages of medial knee joint compartments articular cartilage degeneration. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2021. [DOI: 10.1186/s43055-020-00395-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
The predictive value of the new imaging sequences, especially T2 mapping in assessment of articular cartilage abnormalities of the medial knee compartments in patients with medial knee pain. The purpose of this study is to evaluate the additional value of T2 mapping over using a baseline standard knee MRI to detect cartilage lesions of the medial compartments in patients representing with medial knee pain.
Results
The study included 60 patients presented with medial knee pain, where divided into two groups ; control group (20 volunteers) with age range from 19 to 41 years old 26.80 ± 8.05 (mean ± SD) and patients (40 candidates) with age range from 13 to 57 years old with a mean age 33.00 ± 14.1 (mean ± SD).
Conclusion
On adding T2 mapping sequence to the routine MRI of the knee, the sensitivity for detecting knee cartilage lesions was increased, especially in the detection of early cartilage degeneration at the medial compartment.
Compositional MR imaging including T2 mapping plays an important role in the assessment of early and potentially reversible cartilage damage especially among the young population.
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Dorniak K, Di Sopra L, Sabisz A, Glinska A, Roy CW, Gorczewski K, Piccini D, Yerly J, Jankowska H, Fijałkowska J, Szurowska E, Stuber M, van Heeswijk RB. Respiratory Motion-Registered Isotropic Whole-Heart T 2 Mapping in Patients With Acute Non-ischemic Myocardial Injury. Front Cardiovasc Med 2021; 8:712383. [PMID: 34660714 PMCID: PMC8511642 DOI: 10.3389/fcvm.2021.712383] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 09/06/2021] [Indexed: 11/13/2022] Open
Abstract
Background: T2 mapping is a magnetic resonance imaging technique that can be used to detect myocardial edema and inflammation. However, the focal nature of myocardial inflammation may render conventional 2D approaches suboptimal and make whole-heart isotropic 3D mapping desirable. While self-navigated 3D radial T2 mapping has been demonstrated to work well at a magnetic field strength of 3T, it results in too noisy maps at 1.5T. We therefore implemented a novel respiratory motion-resolved compressed-sensing reconstruction in order to improve the 3D T2 mapping precision and accuracy at 1.5T, and tested this in a heterogeneous patient cohort. Materials and Methods: Nine healthy volunteers and 25 consecutive patients with suspected acute non-ischemic myocardial injury (sarcoidosis, n = 19; systemic sclerosis, n = 2; acute graft rejection, n = 2, and myocarditis, n = 2) were included. The free-breathing T2 maps were acquired as three ECG-triggered T2-prepared 3D radial volumes. A respiratory motion-resolved reconstruction was followed by image registration of the respiratory states and pixel-wise T2 mapping. The resulting 3D maps were compared to routine 2D T2 maps. The T2 values of segments with and without late gadolinium enhancement (LGE) were compared in patients. Results: In the healthy volunteers, the myocardial T2 values obtained with the 2D and 3D techniques were similar (45.8 ± 1.8 vs. 46.8 ± 2.9 ms, respectively; P = 0.33). Conversely, in patients, T2 values did differ between 2D (46.7 ± 3.6 ms) and 3D techniques (50.1 ± 4.2 ms, P = 0.004). Moreover, with the 2D technique, T2 values of the LGE-positive segments were similar to those of the LGE-negative segments (T2LGE-= 46.2 ± 3.7 vs. T2LGE+ = 47.6 ± 4.1 ms; P = 0.49), whereas the 3D technique did show a significant difference (T2LGE- = 49.3 ± 6.7 vs. T2LGE+ = 52.6 ± 8.7 ms, P = 0.006). Conclusion: Respiratory motion-registered 3D radial imaging at 1.5T led to accurate isotropic 3D whole-heart T2 maps, both in the healthy volunteers and in a small patient cohort with suspected non-ischemic myocardial injury. Significantly higher T2 values were found in patients as compared to controls in 3D but not in 2D, suggestive of the technique's potential to increase the sensitivity of CMR at earlier stages of disease. Further study will be needed to demonstrate its accuracy.
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Affiliation(s)
- Karolina Dorniak
- Department of Noninvasive Cardiac Diagnostics, Medical University of Gdansk, Gdansk, Poland
| | - Lorenzo Di Sopra
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Agnieszka Sabisz
- Second Department of Radiology, Medical University of Gdansk, Gdansk, Poland
| | - Anna Glinska
- Second Department of Radiology, Medical University of Gdansk, Gdansk, Poland
| | - Christopher W Roy
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | | | - Davide Piccini
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Hanna Jankowska
- Department of Noninvasive Cardiac Diagnostics, Medical University of Gdansk, Gdansk, Poland
| | - Jadwiga Fijałkowska
- Second Department of Radiology, Medical University of Gdansk, Gdansk, Poland
| | - Edyta Szurowska
- Second Department of Radiology, Medical University of Gdansk, Gdansk, Poland
| | - Matthias Stuber
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Ruud B van Heeswijk
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
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Oei EHG, van Zadelhoff TA, Eijgenraam SM, Klein S, Hirvasniemi J, van der Heijden RA. 3D MRI in Osteoarthritis. Semin Musculoskelet Radiol 2021; 25:468-479. [PMID: 34547812 DOI: 10.1055/s-0041-1730911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Osteoarthritis (OA) is among the top 10 burdensome diseases, with the knee the most affected joint. Magnetic resonance imaging (MRI) allows whole-knee assessment, making it ideally suited for imaging OA, considered a multitissue disease. Three-dimensional (3D) MRI enables the comprehensive assessment of OA, including quantitative morphometry of various joint tissues. Manual tissue segmentation on 3D MRI is challenging but may be overcome by advanced automated image analysis methods including artificial intelligence (AI). This review presents examples of the utility of 3D MRI for knee OA, focusing on the articular cartilage, bone, meniscus, synovium, and infrapatellar fat pad, and it highlights several applications of AI that facilitate segmentation, lesion detection, and disease classification.
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Affiliation(s)
- Edwin H G Oei
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Tijmen A van Zadelhoff
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Susanne M Eijgenraam
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Stefan Klein
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Jukka Hirvasniemi
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rianne A van der Heijden
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
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Arn L, van Heeswijk RB, Stuber M, Bastiaansen JAM. A robust broadband fat-suppressing phaser T 2 -preparation module for cardiac magnetic resonance imaging at 3T. Magn Reson Med 2021; 86:1434-1444. [PMID: 33759208 DOI: 10.1002/mrm.28785] [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: 05/06/2020] [Revised: 03/01/2021] [Accepted: 03/04/2021] [Indexed: 12/25/2022]
Abstract
PURPOSE Designing a new T2 -preparation (T2 -Prep) module to simultaneously provide robust fat suppression and efficient T2 preparation without requiring an additional fat-suppression module for T2 -weighted imaging at 3T. METHODS The tip-down radiofrequency (RF) pulse of an adiabatic T2 -Prep module was replaced by a custom-designed RF-excitation pulse that induces a phase difference between water and fat, resulting in a simultaneous T2 preparation of water signals and the suppression of fat signals at the end of the module (a phaser adiabatic T2 -Prep). Numerical simulations and in vitro and in vivo electrocardiogram (ECG)-triggered navigator-gated acquisitions of the human heart were performed. Blood, myocardium, and fat signal-to-noise ratios and right coronary artery vessel sharpness were compared against previously published adiabatic T2 -Prep approaches. RESULTS Numerical simulations predicted an increased fat-suppression bandwidth and decreased sensitivity to transmit magnetic field inhomogeneities using the proposed approach while preserving the water T2 -Prep capabilities. This was confirmed by the tissue signals acquired in the phantom and the in vivo images, which show similar blood and myocardium signal-to-noise ratio, contrast-to-noise ratio, and significantly reduced fat signal-to-noise ratio compared with the other methods. As a result, the right coronary artery conspicuity was significantly increased. CONCLUSION A novel fat-suppressing T2 -Prep method was developed and implemented that showed robust fat suppression and increased vessel sharpness compared with conventional techniques while preserving its T2 -Prep capabilities.
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Affiliation(s)
- Lionel Arn
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ruud B van Heeswijk
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Center for Biomedical Imaging, Lausanne, Switzerland
| | - Jessica A M Bastiaansen
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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10
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Zi R, Zhu D, Qin Q. Quantitative T 2 mapping using accelerated 3D stack-of-spiral gradient echo readout. Magn Reson Imaging 2020; 73:138-147. [PMID: 32860871 PMCID: PMC7571618 DOI: 10.1016/j.mri.2020.08.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 08/18/2020] [Indexed: 12/15/2022]
Abstract
PURPOSE To develop a rapid T2 mapping protocol using optimized spiral acquisition, accelerated reconstruction, and model fitting. MATERIALS AND METHODS A T2-prepared stack-of-spiral gradient echo (GRE) pulse sequence was applied. A model-based approach joined with compressed sensing was compared with the two methods applied separately for accelerated reconstruction and T2 mapping. A 2-parameter-weighted fitting method was compared with 2- or 3-parameter models for accurate T2 estimation under the influences of noise and B1 inhomogeneity. The performance was evaluated using both digital phantoms and healthy volunteers. Mitigating partial voluming with cerebrospinal fluid (CSF) was also tested. RESULTS Simulations demonstrates that the 2-parameter-weighted fitting approach was robust to a large range of B1 scales and SNR levels. With an in-plane acceleration factor of 5, the model-based compressed sensing-incorporated method yielded around 8% normalized errors compared to references. The T2 estimation with and without CSF nulling was consistent with literature values. CONCLUSION This work demonstrated the feasibility of a T2 quantification technique with 3D high-resolution and whole-brain coverage in 2-3 min. The proposed iterative reconstruction method, which utilized the model consistency, data consistency and spatial sparsity jointly, provided reasonable T2 estimation. The technique also allowed mitigation of CSF partial volume effect.
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Affiliation(s)
- Ruoxun Zi
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Dan Zhu
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Qin Qin
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
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11
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Roemer FW, Demehri S, Omoumi P, Link TM, Kijowski R, Saarakkala S, Crema MD, Guermazi A. State of the Art: Imaging of Osteoarthritis—Revisited 2020. Radiology 2020; 296:5-21. [DOI: 10.1148/radiol.2020192498] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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12
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Hügle M, Omoumi P, van Laar JM, Boedecker J, Hügle T. Applied machine learning and artificial intelligence in rheumatology. Rheumatol Adv Pract 2020; 4:rkaa005. [PMID: 32296743 PMCID: PMC7151725 DOI: 10.1093/rap/rkaa005] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 01/07/2020] [Indexed: 12/28/2022] Open
Abstract
Machine learning as a field of artificial intelligence is increasingly applied in medicine to assist patients and physicians. Growing datasets provide a sound basis with which to apply machine learning methods that learn from previous experiences. This review explains the basics of machine learning and its subfields of supervised learning, unsupervised learning, reinforcement learning and deep learning. We provide an overview of current machine learning applications in rheumatology, mainly supervised learning methods for e-diagnosis, disease detection and medical image analysis. In the future, machine learning will be likely to assist rheumatologists in predicting the course of the disease and identifying important disease factors. Even more interestingly, machine learning will probably be able to make treatment propositions and estimate their expected benefit (e.g. by reinforcement learning). Thus, in future, shared decision-making will not only include the patient’s opinion and the rheumatologist’s empirical and evidence-based experience, but it will also be influenced by machine-learned evidence.
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Affiliation(s)
- Maria Hügle
- Department of Computer Science, University of Freiburg, Freiburg, Germany
| | - Patrick Omoumi
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, and University of Lausanne, Lausanne, Switzerland
| | - Jacob M van Laar
- Department of Rheumatology, University Hospital Utrecht, Utrecht, The Netherlands
| | - Joschka Boedecker
- Department of Computer Science, University of Freiburg, Freiburg, Germany
| | - Thomas Hügle
- Department of Rheumatology, Lausanne University Hospital, and University of Lausanne, Lausanne, Switzerland
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13
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Schoormans J, Strijkers GJ, Hansen AC, Nederveen AJ, Coolen BF. Compressed sensing MRI with variable density averaging (CS-VDA) outperforms full sampling at low SNR. ACTA ACUST UNITED AC 2020; 65:045004. [DOI: 10.1088/1361-6560/ab63b7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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14
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Roux M, Hilbert T, Hussami M, Becce F, Kober T, Omoumi P. MRI T2 Mapping of the Knee Providing Synthetic Morphologic Images: Comparison to Conventional Turbo Spin-Echo MRI. Radiology 2019; 293:620-630. [PMID: 31573393 DOI: 10.1148/radiol.2019182843] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Background Use of a T2 mapping sequence in addition to the conventional knee MRI protocol increases sensitivity to early cartilage lesions but is time consuming. Purpose To test the in vitro validity of quantitative data from an accelerated parallel T2 mapping sequence (combined generalized autocalibrating partially parallel acquisition and model-based accelerated relaxometry by iterative nonlinear inversion [GRAPPATINI]) of the knee and to compare in vivo synthetic images generated with this sequence with those generated with conventional morphologic sequences. Materials and Methods T2 estimations with GRAPPATINI were validated in vitro in comparison with T2 estimations with routine multisection multiecho and reference standard single-section single-echo spin-echo T2 mapping sequences by using a Bland-Altman plot. Synthetic morphologic images (intermediate-weighted sequence, 34-msec echo time; T2-weighted sequence, 80-msec echo time) were compared in vivo with corresponding conventional morphologic turbo spin-echo 3-T sequences by three readers in consecutive patients recruited retrospectively from February to May 2018. Synthetic and conventional morphologic images were compared by using rates of interreader agreement, κ statistics, and rates of findings. Results T2 values with GRAPPATINI were accurate compared with those obtained with the reference single-section single-echo sequence, with slight T2 overestimation (2.7 msec). Sixty-one patients (mean age, 43 years ± 16 [standard deviation]; 32 men) were included. The rate of agreement when one reader used synthetic morphologic images and the other used conventional sequences was not inferior to the rate of agreement when all readers used conventional sequences (upper bounds of 95% confidence intervals of differences between rates of agreement ≤ 4.8%). Interreader agreement was similar for the conventional set alone, the synthetic set alone, and when readers used different sets (two-by-two differences between κ values for all items ≤ 0.15). The rates of findings were not different between synthetic and conventional image sets (all P ≥ .07) except for two items (femoral trochlear cartilage [3.0% vs 0.3%, P = .006] and joint effusion [0.3% vs 2.7%, P = .005]). Conclusion This T2 mapping sequence yields, in one acquisition, accurate T2 values and synthetic morphologic images that are comparable with those obtained with conventional turbo spin-echo sequences. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Fritz in this issue.
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Affiliation(s)
- Marion Roux
- From the Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011 Lausanne, Switzerland (M.R., T.H., M.H., F.B., T.K., P.O.); Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.H., T.K.); and LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland (T.H., T.K.)
| | - Tom Hilbert
- From the Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011 Lausanne, Switzerland (M.R., T.H., M.H., F.B., T.K., P.O.); Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.H., T.K.); and LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland (T.H., T.K.)
| | - Mahmoud Hussami
- From the Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011 Lausanne, Switzerland (M.R., T.H., M.H., F.B., T.K., P.O.); Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.H., T.K.); and LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland (T.H., T.K.)
| | - Fabio Becce
- From the Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011 Lausanne, Switzerland (M.R., T.H., M.H., F.B., T.K., P.O.); Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.H., T.K.); and LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland (T.H., T.K.)
| | - Tobias Kober
- From the Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011 Lausanne, Switzerland (M.R., T.H., M.H., F.B., T.K., P.O.); Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.H., T.K.); and LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland (T.H., T.K.)
| | - Patrick Omoumi
- From the Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011 Lausanne, Switzerland (M.R., T.H., M.H., F.B., T.K., P.O.); Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.H., T.K.); and LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland (T.H., T.K.)
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Keerthivasan MB, Saranathan M, Johnson K, Fu Z, Weinkauf CC, Martin DR, Bilgin A, Altbach MI. An efficient 3D stack-of-stars turbo spin echo pulse sequence for simultaneous T2-weighted imaging and T2 mapping. Magn Reson Med 2019; 82:326-341. [PMID: 30883879 DOI: 10.1002/mrm.27737] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Revised: 02/01/2019] [Accepted: 02/21/2019] [Indexed: 01/16/2023]
Abstract
PURPOSE To design a pulse sequence for efficient 3D T2-weighted imaging and T2 mapping. METHODS A stack-of-stars turbo spin echo pulse sequence with variable refocusing flip angles and a flexible pseudorandom view ordering is proposed for simultaneous T2-weighted imaging and T2 mapping. An analytical framework is introduced for the selection of refocusing flip angles to maximize relative tissue contrast while minimizing T2 estimation errors and maintaining low specific absorption rate. Images at different echo times are generated using a subspace constrained iterative reconstruction algorithm. T2 maps are obtained by modeling the signal evolution using the extended phase graph model. The technique is evaluated using phantoms and demonstrated in vivo for brain, knee, and carotid imaging. RESULTS Numerical simulations demonstrate an improved point spread function with the proposed pseudorandom view ordering compared to golden angle view ordering. Phantom experiments show that T2 values estimated from the stack-of-stars turbo spin echo pulse sequence with variable refocusing flip angles have good concordance with spin echo reference values. In vivo results show the proposed pulse sequence can generate qualitatively comparable T2-weighted images as conventional Cartesian 3D SPACE in addition to simultaneously generating 3D T2 maps. CONCLUSION The proposed stack-of-stars turbo spin echo pulse sequence with pseudorandom view ordering and variable refocusing flip angles allows high resolution isotropic T2 mapping in clinically acceptable scan times. The optimization framework for the selection of refocusing flip angles improves T2 estimation accuracy while generating T2-weighted contrast comparable to conventional Cartesian imaging.
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Affiliation(s)
- Mahesh Bharath Keerthivasan
- Medical Imaging, University of Arizona, Tucson, Arizona.,Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
| | - Manojkumar Saranathan
- Medical Imaging, University of Arizona, Tucson, Arizona.,Electrical and Computer Engineering, University of Arizona, Tucson, Arizona.,Biomedical Engineering, University of Arizona, Tucson, Arizona
| | - Kevin Johnson
- Medical Imaging, University of Arizona, Tucson, Arizona
| | - Zhiyang Fu
- 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
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16
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Pang Y, Palmieri-Smith RM, Malyarenko DI, Swanson SD, Chenevert TL. A unique anisotropic R 2 of collagen degeneration (ARCADE) mapping as an efficient alternative to composite relaxation metric (R 2 -R 1 ρ ) in human knee cartilage study. Magn Reson Med 2019; 81:3763-3774. [PMID: 30793790 DOI: 10.1002/mrm.27621] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Revised: 10/11/2018] [Accepted: 11/09/2018] [Indexed: 12/19/2022]
Abstract
PURPOSE Anisotropic transverse R2 (1/T2 ) relaxation of water proton is sensitive to cartilage degenerative changes. The purpose is to develop an efficient method to extract this relaxation metric in clinical studies. METHODS Anisotropic R2 can be measured inefficiently by standard R2 mapping after removing an isotropic contribution obtained from R1 ρ mapping. In the proposed method, named as a unique anisotropic R2 of collagen degeneration (ARCADE) mapping, an assumed uniform isotropic R2 was estimated at magic angle locations in the deep cartilage, and an anisotropic R2 was thus isolated in a single T2W sagittal image. Five human knees from 4 volunteers were studied with standard R2 and R1 ρ mappings at 3T, and anisotropic R2 derived from ARCADE on the T2W (TE = 48.8 ms) image from R2 mapping was compared with the composite relaxation (R2 - R1 ρ ) using statistical analysis including Student's t-test and Pearson's correlation coefficient. RESULTS Anisotropic R2 (1/s) from ARCADE was highly positively correlated with but not significantly different from standard R2 - R1 ρ (1/s) in the segmented deep (r = 0.83 ± 0.06; 8.3 ± 2.9 vs. 7.3 ± 1.9, P = .50) and the superficial (r = 0.82 ± 0.05; 3.5 ± 2.4 vs. 4.5 ± 1.6, P = .39) zones. However, after eliminating systematic errors by the normalization in terms of zonal contrast, anisotropic R2 was significantly higher (60.2 ± 18.5% vs. 38.4 ± 16.6%, P < .01) than R2 - R1 ρ as predicted. CONCLUSION The proposed anisotropic R2 mapping could be an efficient alternative to the conventional approach, holding great promise in providing both high-resolution morphological and more sensitive transverse relaxation imaging from a single T2W scan in a clinical setting.
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Affiliation(s)
- Yuxi Pang
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - Riann M Palmieri-Smith
- School of Kinesiology, University of Michigan, Ann Arbor, Michigan.,Department of Orthopedic Surgery, University of Michigan, Ann Arbor, Michigan
| | | | - Scott D Swanson
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
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17
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Colotti R, Omoumi P, van Heeswijk RB, Bastiaansen JAM. Simultaneous fat-free isotropic 3D anatomical imaging and T 2 mapping of knee cartilage with lipid-insensitive binomial off-resonant RF excitation (LIBRE) pulses. J Magn Reson Imaging 2018; 49:1275-1284. [PMID: 30318667 DOI: 10.1002/jmri.26322] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2018] [Revised: 08/13/2018] [Accepted: 08/13/2018] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Improved knee cartilage morphological delineation and T2 mapping precision necessitates isotropic 3D high-resolution and efficient fat suppression. PURPOSE To develop and assess an isotropic 3D lipid-insensitive T2 mapping technique of the knee for improved cartilage delineation and precise measurement of T2 relaxation times. STUDY TYPE Prospective. PHANTOM/SUBJECTS Phantoms (n = 6) used in this study were designed to mimic the T1 and T2 relaxation times of cartilage and fat. The study cohort comprised healthy volunteers (n = 7) for morphometry and T2 relaxation time measurements. FIELD STRENGTH/SEQUENCE A high-resolution isotropic 3D T2 mapping technique that uses sequential T2 -prepared segmented gradient-recalled echo (Iso3DGRE) images and lipid-insensitive binomial off-resonant radiofrequency (RF) excitation (LIBRE) at 3T. ASSESSMENT Numerical simulations and phantom experiments were performed to optimize the LIBRE pulse. Phantom studies were carried out to test the accuracy of the technique against reference standard spin-echo (SE) T2 mapping. Subsequently, T2 maps with and without LIBRE pulses were acquired in knees of healthy volunteers and the T2 relaxation time values in different cartilage compartments were compared. STATISTICAL TESTS A two-tailed paired Student's t-test was used to compare the average T2 values and the relative standard deviations (inverse measurement of the precision) obtained with and without LIBRE pulses. RESULTS A LIBRE pulse of 1 msec suppressed fat with an RF excitation frequency offset of 1560 Hz and optimal RF excitation angle of 35°. These results were corroborated by phantom and knee experiments. Robust and homogeneous fat suppression was obtained (a fat signal-to-noise ratio (SNR) decrease of 86.4 ± 2.4%). In phantoms, T2 values were found in good agreement when comparing LIBRE-Iso3DGRE with SE (slope 0.93 ± 0.04, intercept 0.11 ± 1.6 msec, R2 >0.99). In vivo, LIBRE excitation resulted in more precise T2 estimation (23.7 ± 7.4%) than normal excitation (30.5 ± 9.9%, P < 0.0001). DATA CONCLUSION Homogeneous LIBRE fat signal suppression was achieved with a total RF pulse duration of 1 msec, allowing for the removal of chemical shift artifacts and resulting in improved cartilage delineation and precise T2 values. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:1275-1284.
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Affiliation(s)
- Roberto Colotti
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Patrick Omoumi
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Ruud B van Heeswijk
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Centre for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Jessica A M Bastiaansen
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
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