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Yagdiran B, Cakir BT, Cetin H. Diagnostic Contribution of Additional Sequences to the Evaluation of Cord Lesions in Patients with Cervical Spinal Multiple Sclerosis in Turkey: A Retrospective Study. Niger J Clin Pract 2024; 27:272-279. [PMID: 38409158 DOI: 10.4103/njcp.njcp_333_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 01/15/2024] [Indexed: 02/28/2024]
Abstract
BACKGROUND Multiple Sclerosis (MS) is the most common cause of non-traumatic disability in young adults. Spinal cord involvement is observed in 55-75% of patients with MS. AIM To identify the strengths and shortcomings of sagittal phase-sensitive inversion recovery (PSIR), sagittal proton density/T2-weighted (PD/T2W), and axial turbo inversion recovery magnitude (TIRM) sequences in the detection of cervical MS plaques by comparing with routine sequences (axial and sagittal T2W, sagittal T1W, sagittal TIRM, fat-suppressed contrast T1W) and therefore determine their diagnostic contributions. MATERIALS AND METHODS A total of 48 patients in whom additional magnetic resonance imaging (MRI) sequences were obtained for the diagnosis of cervical MS were retrospectively identified and included in the study. A total of 111 MS plaques were analyzed in terms of visibility, number, size, border sharpness, and intensity ratio based on the routine and additional MRI sequences. The evaluation of the images was independently undertaken by two radiologists. RESULTS The highest visibility was provided by sagittal PSIR, sagittal TIRM, and axial TIRM sequences (P < 0.05 for all additional sequences). Seven lesions in PD/T2W and four lesions in axial T2W sequences were unable to be detected. Lesions seen in sagittal and axial TIRM sequences were larger than the others. The sharpest borders were determined in the axial TIRM sequence, and the most diffuse borders in the PD/T2W sequence. In intensity ratio, the sagittal PSIR sequence revealed the most significant contrast difference. CONCLUSION The sagittal PSIR sequence may improve the detection of cervical MS plaques due to the improved visibility and intensity ratios. The axial TIRM sequence may be more useful than routine axial T2W in the evaluation of visibility, border sharpness, and size measurement of MS plaques.
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Affiliation(s)
- B Yagdiran
- Department of Radiology, Başkent University, Faculty of Medicine, Fevzi Çakmak Cd. 10. Sk. No: 45 Bahçelievler/ANKARA, Turkey
| | - B T Cakir
- Department of Radiology, Gülhane Training and Research Hospital, General Dr. Tevfik Sağlam Cd. No: 1 Etlik/Ankara, Turkey
| | - H Cetin
- Department of Radiology, Yildirim Beyazit University, Üniversiteler Mahallesi Bilkent Caddesi No: 1, Çankaya, Ankara, Turkey
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Duvančić T, Škokić S, Erjavec I, Plečko M, Bohaček I, Gajović S, Delimar D. Novel micro-MRI approach for subchondral trabecular bone analysis in patients with hip osteoarthritis is comparable to micro-CT approach. Croat Med J 2022. [PMID: 36597563 PMCID: PMC9837720 DOI: 10.3325/cmj.2022.63.515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
AIM To test the agreement between a newly developed micro-magnetic resonance imaging (MRI) analysis of the subchondral bone and the micro-computed tomography (CT) approach. METHODS Samples obtained from 10 patients with osteoarthritis undergoing total hip arthroplasty were scanned with a 7.0 T micro-MRI. Proton density-weighted images and proton density-weighted images with fat suppression were obtained. The results were validated with a micro-CT device. Micro-MRI and micro-CT scans of the same sample were aligned, and regions of interest were delineated on equal areas of the sample. Bone volume fraction was calculated by using in-house plugins. The agreement between the methods was tested with Bland-Altman analysis. RESULTS The agreement between the methods was good, with average difference of 2.167%. The differences between the methods were not significant (P=0.272, t test). CONCLUSION The novel micro-MRI approach could be used for subchondral bone analysis. With further optimization for clinical MRI machines, the approach can be also used in the diagnostics of hip osteoarthritis.
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Affiliation(s)
- Tea Duvančić
- University of Zagreb School of Medicine, Zagreb, Croatia
| | - Siniša Škokić
- Laboratory for Regenerative Neuroscience – GlowLab, Croatian Institute for Brain Research, University of Zagreb School of Medicine, Zagreb, Croatia
| | - Igor Erjavec
- University of Zagreb School of Medicine, Zagreb, Croatia
| | | | - Ivan Bohaček
- Department of Orthopedic Surgery, University of Zagreb School of Medicine, University Hospital Center Zagreb, Zagreb, Croatia
| | - Srećko Gajović
- University of Zagreb School of Medicine, Zagreb, Croatia
| | - Domagoj Delimar
- Department of Orthopedic Surgery, University of Zagreb School of Medicine, University Hospital Center Zagreb, Zagreb, Croatia
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De Stefano N, Battaglini M, Pareto D, Cortese R, Zhang J, Oesingmann N, Prados F, Rocca MA, Valsasina P, Vrenken H, Gandini Wheeler-Kingshott CAM, Filippi M, Barkhof F, Rovira À. MAGNIMS recommendations for harmonization of MRI data in MS multicenter studies. Neuroimage Clin 2022; 34:102972. [PMID: 35245791 PMCID: PMC8892169 DOI: 10.1016/j.nicl.2022.102972] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 02/22/2022] [Accepted: 02/23/2022] [Indexed: 11/24/2022]
Abstract
Sharing data from cooperative studies is essential to develop new biomarkers in MS. Differences in MRI acquisition, analysis, storage represent a substantial constraint. We review the state of the art and developments in the harmonization of MRI. We provide recommendations to harmonize large MRI datasets in the MS field.
There is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources.
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Affiliation(s)
- Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.
| | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Jian Zhang
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | | | - Ferran Prados
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Center for Medical Imaging Computing, Medical Physics and Biomedical Engineering, UCL, London, WC1V 6LJ, United Kingdom; e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Hugo Vrenken
- Amsterdam Neuroscience, MS Center Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Brain MRI 3T Research Center, C. Mondino National Neurological Institute, Pavia, Italy; Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy; Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Frederik Barkhof
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Center for Medical Imaging Computing, Medical Physics and Biomedical Engineering, UCL, London, WC1V 6LJ, United Kingdom; Amsterdam Neuroscience, MS Center Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
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