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Eckstein F, Wluka AE, Wirth W, Cicuttini F. 30 Years of MRI-based cartilage & bone morphometry in knee osteoarthritis: From correlation to clinical trials. Osteoarthritis Cartilage 2024; 32:439-451. [PMID: 38331162 DOI: 10.1016/j.joca.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 12/20/2023] [Accepted: 02/01/2024] [Indexed: 02/10/2024]
Abstract
OBJECTIVE The first publication on morphometric analysis of articular cartilage using magnetic resonance imaging (MRI) in 1994 set the scene for a game change in osteoarthritis (OA) research. The current review highlights milestones in cartilage and bone morphometry, summarizing the rapid progress made in imaging, its application to understanding joint (patho-)physiology, and its use in interventional clinical trials. METHODS Based on a Pubmed search of articles from 1994 to 2023, the authors subjectively selected representative work illustrating important steps in the development or application of magnetic resonance-based cartilage and bone morphometry, with a focus on studies in humans, and on the knee. Research on OA-pathophysiology is addressed only briefly, given length constraints. Compositional and semi-quantitative assessment are not covered here. RESULTS The selected articles are presented in historical order as well as by content. We review progress in the technical aspects of image acquisition, segmentation and analysis, advances in understanding tissue growth, physiology, function, and adaptation, and a selection of clinical trials examining the efficacy of interventions on knee cartilage and bone. A perspective is provided of how lessons learned may be applied to future research and clinical management. CONCLUSIONS Over the past 30 years, MRI-based morphometry of cartilage and bone has contributed to a paradigm shift in understanding articular tissue physiology and OA pathophysiology, and to the development of new treatment strategies. It is likely that these technologies will continue to play a key role in the development and (accelerated) approval of therapy, potentially targeted to different OA phenotypes.
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Affiliation(s)
- Felix Eckstein
- Department of Imaging & Functional Musculoskeletal Research, Center of Anatomy and Cell Biology, Paracelsus Medical University (PMU), Salzburg, Austria; Ludwig Boltzmann Institute for Arthritis and Rehabilitation (LBIAR), Paracelsus Medical University, Salzburg, Austria; Chondrometrics GmbH, Freilassing, Bavaria, Germany.
| | - Anita E Wluka
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Wolfgang Wirth
- Department of Imaging & Functional Musculoskeletal Research, Center of Anatomy and Cell Biology, Paracelsus Medical University (PMU), Salzburg, Austria; Ludwig Boltzmann Institute for Arthritis and Rehabilitation (LBIAR), Paracelsus Medical University, Salzburg, Austria; Chondrometrics GmbH, Freilassing, Bavaria, Germany
| | - Flavia Cicuttini
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
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Nekomoto A, Ishikawa M, Tsuji S, Shimamura Y, Kitamura N, Kamei G, Nakata K, Hashiguchi N, Nakamae A, Adachi N. Unique Anatomical Features of the Discoid Lateral Meniscus via Three-Dimensional MRI. Cureus 2023; 15:e46188. [PMID: 37905280 PMCID: PMC10613346 DOI: 10.7759/cureus.46188] [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] [Accepted: 09/29/2023] [Indexed: 11/02/2023] Open
Abstract
Background The discoid lateral meniscus (DLM) is a unique anatomical variant characterized by a larger, thicker lateral meniscus. For clinical diagnosis of DLM, coronal and sagittal slices in two-dimensional (2D) MRI and arthroscopic imaging are typically employed. However, evaluating the entire shape of the DLM is challenging due to the limited views and details provided by these methods. Three-dimensional (3D) visualization with MRI offers a more comprehensive view of the entire meniscus. The purpose of this study was to demonstrate the entire shape of a DLM using 3D images and unveil its unique characteristics. Methods The study population consisted of 31 knees diagnosed with DLM through arthroscopic examination at our hospital between 2017 and 2021. This group comprised 20 males (65%) and 11 females (35%), with ages ranging from 9 to 49 years (mean age, 24.2 years). Furthermore, a control group of 43 knees without DLM was included for comparative analysis. This control group consisted of 22 males (51%) and 21 females (49%), with ages ranging from 9 to 69 years (mean age, 28.5 years). 3D images of the medial meniscus (MM) and lateral meniscus (LM) were reconstructed from 1.5T-MRI images with semi-automatic segmentation using free software. From the coordinate information, the anterior-to-posterior lengths of the MM and LM were obtained, and the medial-to-lateral anterior-to-posterior length (L/M ratio) ratio was calculated and compared with the value of the non-DLM population. Results Our method allows for the detailed delineation of the DLM's unique morphology. The DLM group exhibited a significantly smaller L/M ratio compared to the non-DLM group (DLM: 0.66±0.06, non-DLM: 0.74±0.05, p<0.001). Conclusions Reconstructed 3D images could help to demonstrate the whole morphology of DLM and reveal its unique features, in which DLM shows a significantly smaller L/M ratio as compared to non-DLM.
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Affiliation(s)
- Akinori Nekomoto
- Department of Orthopaedic Surgery, Hiroshima University Hospital, Hiroshima, JPN
| | - Masakazu Ishikawa
- Department of Orthopaedic Surgery, Faculty of Medicine, Kagawa University, Takamatsu, JPN
| | - Shunya Tsuji
- Department of Orthopaedic Surgery, Hiroshima University Hospital, Hiroshima, JPN
| | | | | | - Goki Kamei
- Department of Orthopaedic Surgery, Hiroshima University Hospital, Hiroshima, JPN
| | - Kyohei Nakata
- Department of Orthopaedic Surgery, Hiroshima University Hospital, Hiroshima, JPN
| | - Naofumi Hashiguchi
- Department of Orthopaedic Surgery, Hiroshima University Hospital, Hiroshima, JPN
| | - Atsuo Nakamae
- Department of Orthopaedic Surgery, Hiroshima University Hospital, Hiroshima, JPN
| | - Nobuo Adachi
- Department of Orthopaedic Surgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, JPN
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Nakagawa Y, Mori K, Mukai S, Shinya Y, Nakamura R, Takahashi M. Intraoperative Acoustic Evaluation of Living Human Knee Cartilage-Comparison with Respect to Cartilage Degeneration and Aging. Cartilage 2023; 14:261-268. [PMID: 36788438 PMCID: PMC10601570 DOI: 10.1177/19476035231154509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 12/24/2022] [Accepted: 12/26/2022] [Indexed: 02/16/2023] Open
Abstract
OBJECTIVE The objective of the study was to evaluate the mechanical properties of living human knee cartilage using our ultrasonic device, and to compare the measurements with respect to cartilage degeneration and aging. DESIGN A total of 95 knees which had undergone arthroscopic knee surgery, from 88 patients, were included in the study, with informed consent. All procedures were reviewed and approved by the ethical committee of our hospital. In the study group, there were 41 men, 47 women, 39 right knees, and 56 left knees. The conditions primarily included knee osteoarthritis and anterior cruciate ligament rupture. The mean operative age was 44.1 years old (range = 10-83). We compared mechanical properties of the knee cartilage with respect to aging and gender, in comparison with normal cartilage. A P value of <0.05 represented statistical significance. RESULTS In the context of the International Cartilage Repair Society (ICRS) classification of cartilage degeneration (grade 0-3), the signal intensity in grade 0 was significantly larger than that in grade 1, 2, or 3. The thickness in grade 0 was significantly higher than that in grade 1, 2, or 3. Normal cartilage in older women had the lowest signal intensity and the least cartilage thickness among all the groups. CONCLUSION The ultrasonic system we developed was able to detect early degenerative changes in living cartilage in knees. The lowest signal intensity and least cartilage thickness in normal cartilage among older women were correlated to a large prevalence of knee osteoarthritis in women. LEVEL OF EVIDENCE Level IV, case series.
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Affiliation(s)
- Yasuaki Nakagawa
- Clinical Research Center, National Hospital Organization Kyoto Medical Center, Kyoto, Japan
- Department of Orthopaedic Surgery, Japan Baptist Medical Foundation, Kyoto, Japan
| | - Koji Mori
- Department of Applied Medical Engineering Science, Graduate School of Medicine, Yamaguchi University, Yamaguchi, Japan
| | - Shogo Mukai
- Department of Orthopaedic Surgery, National Hospital Organization Kyoto Medical Center, Kyoto, Japan
| | - Yuki Shinya
- Department of Orthopaedic Surgery, National Hospital Organization Kyoto Medical Center, Kyoto, Japan
| | - Ryota Nakamura
- Department of Orthopaedic Surgery, National Hospital Organization Kyoto Medical Center, Kyoto, Japan
| | - Motoi Takahashi
- Department of Orthopaedic Surgery, National Hospital Organization Kyoto Medical Center, Kyoto, Japan
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4
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Roemer FW, Felson DT, Stefanik JJ, Rabasa G, Wang N, Crema MD, Neogi T, Nevitt MC, Torner J, Lewis CE, Peloquin C, Guermazi A. Heterogeneity of cartilage damage in Kellgren and Lawrence grade 2 and 3 knees: the MOST study. Osteoarthritis Cartilage 2022; 30:714-723. [PMID: 35202808 PMCID: PMC9433455 DOI: 10.1016/j.joca.2022.02.614] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 02/03/2022] [Accepted: 02/14/2022] [Indexed: 02/02/2023]
Abstract
OBJECTIVE Eligibility for clinical trials in osteoarthritis (OA) is usually limited to Kellgren-Lawrence (KL) grades 2 and 3 knees. Our aim was to describe the prevalence and severity of cartilage damage in KL 2 and 3 knees by compartment and articular subregion. DESIGN The Multicenter Osteoarthritis (MOST) study is a cohort study of individuals with or at risk for knee OA. All baseline MRIs with radiographic disease severity KL2 and 3 were included. Knee MRIs were read for cartilage damage in 14 subregions. We determined the frequencies of no, any and widespread full-thickness cartilage damage by knee compartment, and the prevalence of any cartilage damage in 14 articular subregions. RESULTS 665 knees from 665 participants were included (mean age 63.8 ± 7.9 years, 66.5% women). 372 knees were KL2 and 293 knees were KL3. There was no cartilage damage in 78 (21.0%) medial tibio-femoral joint (TFJ), 157 (42.2%) lateral TFJ and 62 (16.7%) patello-femoral joint (PFJ) compartments of KL2 knees, and 17 (5.8%), 115 (39.3%) and 35 (12.0%) compartments, respectively, of KL3 knees. There was widespread full-thickness damage in 94 (25.3%) medial TFJ, 36 (9.7%) lateral TFJ and 176 (47.3%) PFJ compartments of KL2 knees, and 217 (74.1%), 70 (23.9%) and 104 (35.5%) compartments, respectively, of KL3 knees. The subregions most likely to have any damage were central medial femur (80.5%), medial patella (69.8%) and central medial tibia (69.9). CONCLUSIONS KL2 and KL3 knees vary greatly in cartilage morphology. Heterogeneity in the prevalence, severity and location of cartilage damage in in KL2 and 3 knees should be considered when planning disease modifying trials for knee OA.
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Affiliation(s)
- F W Roemer
- Quantitative Imaging Center (QIC), Department of Radiology, Boston University School of Medicine, Boston, MA, USA; Department of Radiology, Friedrich-Alexander University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany.
| | - D T Felson
- Department of Medicine, Section of Rheumatology, Boston University School of Medicine, Boston, MA, USA
| | - J J Stefanik
- Department of Physical Therapy, Movement and Rehabilitation Sciences, Northeastern University, Boston, MA, USA
| | - G Rabasa
- Department of Medicine, Section of Rheumatology, Boston University School of Medicine, Boston, MA, USA
| | - N Wang
- Department of Medicine, Section of Rheumatology, Boston University School of Medicine, Boston, MA, USA
| | - M D Crema
- Quantitative Imaging Center (QIC), Department of Radiology, Boston University School of Medicine, Boston, MA, USA; Institute of Sports Imaging, French National Institute of Sports (INSEP), Paris, France
| | - T Neogi
- Department of Medicine, Section of Rheumatology, Boston University School of Medicine, Boston, MA, USA
| | - M C Nevitt
- Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA, USA
| | - J Torner
- Department of Epidemiology, University of Iowa, Iowa City, IA, USA
| | - C E Lewis
- Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - C Peloquin
- Department of Medicine, Section of Rheumatology, Boston University School of Medicine, Boston, MA, USA
| | - A Guermazi
- Quantitative Imaging Center (QIC), Department of Radiology, Boston University School of Medicine, Boston, MA, USA; Department of Radiology, VA Boston Healthcare System, West Roxbury, MA, USA
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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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Aoki H, Ozeki N, Katano H, Hyodo A, Miura Y, Matsuda J, Takanashi K, Suzuki K, Masumoto J, Okanouchi N, Fujiwara T, Sekiya I. Relationship between medial meniscus extrusion and cartilage measurements in the knee by fully automatic three-dimensional MRI analysis. BMC Musculoskelet Disord 2020; 21:742. [PMID: 33183257 PMCID: PMC7664063 DOI: 10.1186/s12891-020-03768-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 11/03/2020] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND We developed a fully automatic three-dimensional knee MRI analysis software that can quantify meniscus extrusion and cartilage measurements, including the projected cartilage area ratio (PCAR), which represents the ratio of the subject's actual cartilage area to their ideal cartilage area. We also collected 3D MRI knee data from 561 volunteers (aged 30-79 years) from the "Kanagawa Knee Study." Our purposes were to verify the accuracy of the software for automatic cartilage and meniscus segmentation using knee MRI and to examine the relationship between medial meniscus extrusion measurements and cartilage measurements from Kanagawa Knee Study data. METHODS We constructed a neural network for the software by randomly choosing 10 healthy volunteers and 103 patients with knee pain. We validated the algorithm by randomly selecting 108 of these 113 subjects for training, and determined Dice similarity coefficients from five other subjects. We constructed a neural network using all data (113 subjects) for training. Cartilage thickness, cartilage volume, and PCAR in the medial femoral, lateral femoral, medial tibial, and lateral tibial regions were quantified by using the trained software on Kanagawa Knee Study data and their relationship with subject height was investigated. We also quantified the medial meniscus coverage ratio (MMCR), defined as the ratio of the overlapping area between the medial meniscus area and the medial tibial cartilage area to the medial tibial cartilage area. Finally, we examined the relationship between MMCR and PCAR at middle central medial tibial (mcMT) subregion located in the center of nine subregions in the medial tibial cartilage. RESULTS Dice similarity coefficients for cartilage and meniscus were both approximately 0.9. The femoral and tibial cartilage thickness and volume at each region correlated with height, but PCAR did not correlate with height in most settings. PCAR at the mcMT was significantly correlated with MMCR. CONCLUSIONS Our software showed high segmentation accuracy for the knee cartilage and meniscus. PCAR was more useful than cartilage thickness or volume since it was less affected by height. Relations ips were observed between the medial tibial cartilage measurements and the medial meniscus extrusion measurements in our cross-sectional study. TRIAL REGISTRATION UMIN, UMIN000032826 ; 1 September 2018.
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Affiliation(s)
- Hayato Aoki
- Center for Stem Cell and Regenerative Medicine, Department of Applied Regenerative Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan
| | - Nobutake Ozeki
- Center for Stem Cell and Regenerative Medicine, Department of Applied Regenerative Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan
| | - Hisako Katano
- Center for Stem Cell and Regenerative Medicine, Department of Applied Regenerative Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan
| | - Akinobu Hyodo
- Center for Stem Cell and Regenerative Medicine, Department of Applied Regenerative Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan
| | - Yugo Miura
- Center for Stem Cell and Regenerative Medicine, Department of Applied Regenerative Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan
| | - Junpei Matsuda
- Center for Stem Cell and Regenerative Medicine, Department of Applied Regenerative Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan
| | - Kimiko Takanashi
- Center for Stem Cell and Regenerative Medicine, Department of Applied Regenerative Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan
| | | | | | | | - Takeo Fujiwara
- Department of Global Health Promotion, Tokyo Medical and Dental University, Tokyo, Japan
| | - Ichiro Sekiya
- Center for Stem Cell and Regenerative Medicine, Department of Applied Regenerative Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan.
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7
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From classical to deep learning: review on cartilage and bone segmentation techniques in knee osteoarthritis research. Artif Intell Rev 2020. [DOI: 10.1007/s10462-020-09924-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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8
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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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9
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Stoel B. Use of artificial intelligence in imaging in rheumatology - current status and future perspectives. RMD Open 2020; 6:e001063. [PMID: 31958283 PMCID: PMC6999690 DOI: 10.1136/rmdopen-2019-001063] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 01/06/2020] [Accepted: 01/08/2020] [Indexed: 11/06/2022] Open
Abstract
After decades of basic research with many setbacks, artificial intelligence (AI) has recently obtained significant breakthroughs, enabling computer programs to outperform human interpretation of medical images in very specific areas. After this shock wave that probably exceeds the impact of the first AI victory of defeating the world chess champion in 1997, some reflection may be appropriate on the consequences for clinical imaging in rheumatology. In this narrative review, a short explanation is given about the various AI techniques, including 'deep learning', and how these have been applied to rheumatological imaging, focussing on rheumatoid arthritis and systemic sclerosis as examples. By discussing the principle limitations of AI and deep learning, this review aims to give insight into possible future perspectives of AI applications in rheumatology.
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Affiliation(s)
- Berend Stoel
- Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, The Netherlands
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10
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Hayashi D, Roemer FW, Guermazi A. Imaging of Osteoarthritis by Conventional Radiography, MR Imaging, PET–Computed Tomography, and PET–MR Imaging. PET Clin 2019; 14:17-29. [DOI: 10.1016/j.cpet.2018.08.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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11
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Hayashi D, Roemer FW, Guermazi A. Imaging of osteoarthritis-recent research developments and future perspective. Br J Radiol 2018; 91:20170349. [PMID: 29271229 DOI: 10.1259/bjr.20170349] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
In osteoarthritis research, imaging plays an important role in clinical trials and epidemiological observational studies. In this narrative review article, we will describe recent developments in imaging of osteoarthritis in the research arena, mainly focusing on literature evidence published within the past 3 years (2014-2017). We will primarily focus on MRI including advanced imaging techniques that are not currently commonly used in routine clinical practice, although radiography, ultrasound and nuclear medicine (radiotracer) imaging will also be discussed. Research efforts to uncover the disease process of OA as well as to discover a disease modifying OA drug continue. MRI continues to play a large role in these endeavors, while compositional MRI techniques will increasingly become important due to their ability to assess "premorphologic" biochemical changes of articular cartilage and other tissues in and around joints. Radiography remain the primary imaging modality for defining inclusion/exclusion criteria as well as an outcome measure in OA clinical trials, despite known limitations for visualization of OA features. Compositional MRI techniques show promise for predicting structural and clinical outcomes in OA research. Ultrasound can be a useful adjunct to radiography and MRI particularly for evaluation of hand OA. Newer imaging techniques such as hybrid PET/MRI may have a potential but require further research and validation.
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Affiliation(s)
- Daichi Hayashi
- 1 Department of Radiology, Quantitative Imaging Center, Boston University School of Medicine , Boston, MA , USA.,2 Department of Radiology, Stony Brook University School of Medicine , Stony Brook, NY , USA
| | - Frank W Roemer
- 1 Department of Radiology, Quantitative Imaging Center, Boston University School of Medicine , Boston, MA , USA.,3 Department of Radiology, University of Erlangen-Nuremberg , Erlangen , Germany
| | - Ali Guermazi
- 1 Department of Radiology, Quantitative Imaging Center, Boston University School of Medicine , Boston, MA , USA
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12
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Demehri S, Guermazi A, Kwoh CK. Diagnosis and Longitudinal Assessment of Osteoarthritis: Review of Available Imaging Techniques. Rheum Dis Clin North Am 2016; 42:607-620. [PMID: 27742017 DOI: 10.1016/j.rdc.2016.07.004] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Osteoarthritis (OA) is a major chronic and global health care problem. Recent technological advances in imaging and postprocessing techniques have enhanced the understanding and characterization of the pathophysiology of this chronic and prevalent disease. Although plain radiograph remains the modality of choice for initial assessment of OA, recent studies have shown that advanced cross-sectional imaging can improve the early detection, grading, structural damage quantification, and risk stratification of OA. This article discusses the currently available evidence regarding both the conventional and novel imaging modalities that can be used for evaluation of patients with OA and its longitudinal assessment.
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Affiliation(s)
- Shadpour Demehri
- Division of Musculoskeletal Radiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, School of Medicine, 601 North Caroline Street, JHOC 5165, Baltimore, MD 21287, USA.
| | - Ali Guermazi
- Department of Radiology, Quantitative Imaging Center, Boston University School of Medicine, Boston, MA, USA
| | - C Kent Kwoh
- Division of Rheumatology, University of Arizona Arthritis Center, University of Arizona, Tucson, AZ, USA
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