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Puybasset L, Perlbarg V, Unrug J, Cassereau D, Galanaud D, Torkomian G, Battisti V, Lefort M, Velly L, Degos V, Citerio G, Bayen É, Pelegrini-Issac M. Prognostic value of global deep white matter DTI metrics for 1-year outcome prediction in ICU traumatic brain injury patients: an MRI-COMA and CENTER-TBI combined study. Intensive Care Med 2022; 48:201-212. [PMID: 34904191 DOI: 10.1007/s00134-021-06583-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 11/11/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE A reliable tool for outcome prognostication in severe traumatic brain injury (TBI) would improve intensive care unit (ICU) decision-making process by providing objective information to caregivers and family. This study aimed at designing a new classification score based on magnetic resonance (MR) diffusion metrics measured in the deep white matter between day 7 and day 35 after TBI to predict 1-year clinical outcome. METHODS Two multicenter cohorts (29 centers) were used. MRI-COMA cohort (NCT00577954) was split into MRI-COMA-Train (50 patients enrolled between 2006 and mid-2014) and MRI-COMA-Test (140 patients followed up in clinical routine from 2014) sub-cohorts. These latter patients were pooled with 56 ICU patients (enrolled from 2014 to 2020) from CENTER-TBI cohort (NCT02210221). Patients were dichotomised depending on their 1-year Glasgow outcome scale extended (GOSE) score: GOSE 1-3, unfavorable outcome (UFO); GOSE 4-8, favorable outcome (FO). A support vector classifier incorporating fractional anisotropy and mean diffusivity measured in deep white matter, and age at the time of injury was developed to predict whether the patients would be either UFO or FO. RESULTS The model achieved an area under the ROC curve of 0.93 on MRI-COMA-Train training dataset, and 49% sensitivity for 96.8% specificity in predicting UFO and 58.5% sensitivity for 97.1% specificity in predicting FO on the pooled MRI-COMA-Test and CENTER-TBI validation datasets. CONCLUSION The model successfully identified, with a specificity compatible with a personalized decision-making process in ICU, one in two patients who had an unfavorable outcome at 1 year after the injury, and two-thirds of the patients who experienced a favorable outcome.
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Affiliation(s)
- Louis Puybasset
- Neurosurgical Intensive Care Unit, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France.
- Laboratoire d'Imagerie Biomédicale (LIB), Sorbonne Université, CNRS, INSERM, Paris, France.
- Department of Anesthesiology and Intensive Care, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, 47-83 Boulevard de l'Hôpital, 75013, Paris, France.
- Clinical Research Group 29, Sorbonne Université, Paris, France.
| | | | - Jean Unrug
- Neurosurgical Intensive Care Unit, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
- Laboratoire d'Imagerie Biomédicale (LIB), Sorbonne Université, CNRS, INSERM, Paris, France
| | - Didier Cassereau
- Laboratoire d'Imagerie Biomédicale (LIB), Sorbonne Université, CNRS, INSERM, Paris, France
| | - Damien Galanaud
- Laboratoire d'Imagerie Biomédicale (LIB), Sorbonne Université, CNRS, INSERM, Paris, France
- Department of Neuroradiology, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
| | - Grégory Torkomian
- Neurosurgical Intensive Care Unit, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
| | - Valentine Battisti
- Neurosurgical Intensive Care Unit, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
| | - Muriel Lefort
- Laboratoire d'Imagerie Biomédicale (LIB), Sorbonne Université, CNRS, INSERM, Paris, France
| | - Lionel Velly
- Department of Anesthesiology and Critical Care Medicine, University Hospital Timone, AP-HM, Aix Marseille University, Marseille, France
- CNRS, Institute of Neuroscience Timone, UMR7289, Aix Marseille University, Marseille, France
| | - Vincent Degos
- Clinical Research Group 29, Sorbonne Université, Paris, France
- Department of Anesthesia, Critical Care and Peri-Operative Medicine, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
- INSERM UMR 1141, Paris, France
| | - Guiseppe Citerio
- Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
- Neurointensive Care Unit, Department of Emergency and Urgency, ASST-Monza, San Gerardo Hospital, Monza, Italy
| | - Éléonore Bayen
- Laboratoire d'Imagerie Biomédicale (LIB), Sorbonne Université, CNRS, INSERM, Paris, France
- Rehabilitation Unit, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
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Development of a standard phantom for diffusion-weighted magnetic resonance imaging quality control studies: A review. POLISH JOURNAL OF MEDICAL PHYSICS AND ENGINEERING 2022. [DOI: 10.2478/pjmpe-2022-0020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Abstract
Various materials and compounds have been used in the design of diffusion-weighted magnetic resonance imaging (DWMRI) phantoms to mimic biological tissue properties, including diffusion. This review thus provides an overview of the preparations of the various DW-MRI phantoms available in relation to the limitations and strengths of materials/solutions used to fill them. The narrative review conducted from relevant databases shows that synthesizing all relevant compounds from individual liquids, gels, and solutions based on their identified strengths could contribute to the development of a novel multifunctional DW-MRI phantom. The proposed multifunctional material at varied concentrations, when filled into a multi-compartment Perspex container of cylindrical or spherical geometry, could serve as a standard DW-MRI phantom. The standard multifunctional phantom could potentially provide DW-MRI quality control test parameters in one study session.
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Morozov S, Sergunova K, Petraikin A, Akhmad E, Kivasev S, Semenov D, Blokhin I, Karpov I, Vladzymyrskyy A, Morozov A. Diffusion processes modeling in magnetic resonance imaging. Insights Imaging 2020; 11:60. [PMID: 32346809 PMCID: PMC7188746 DOI: 10.1186/s13244-020-00863-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 03/20/2020] [Indexed: 01/15/2023] Open
Abstract
Background The paper covers modern approaches to the evaluation of neoplastic processes with diffusion-weighted imaging (DWI) and proposes a physical model for monitoring the primary quantitative parameters of DWI and quality assurance. Models of hindered and restricted diffusion are studied. Material and method To simulate hindered diffusion, we used aqueous solutions of polyvinylpyrrolidone with concentrations of 0 to 70%. We created siloxane-based water-in-oil emulsions that simulate restricted diffusion in the intracellular space. To obtain a high signal on DWI in the broadest range of b values, we used silicon oil with high T2: cyclomethicone and caprylyl methicone. For quantitative assessment of our phantom, we performed DWI on 1.5T magnetic resonance scanner with various fat suppression techniques. We assessed water-in-oil emulsion as an extracorporeal source signal by simultaneously scanning a patient in whole-body DWI sequence. Results We developed phantom with control substances for apparent diffusion coefficient (ADC) measurements ranging from normal tissue to benign and malignant lesions: from 2.29 to 0.28 mm2/s. The ADC values of polymer solutions are well relevant to the mono-exponential equation with the mean relative difference of 0.91%. Conclusion The phantom can be used to assess the accuracy of the ADC measurements, as well as the effectiveness of fat suppression. The control substances (emulsions) can be used as a body marker for quality assurance in whole-body DWI with a wide range of b values.
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Affiliation(s)
- Sergey Morozov
- Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, 28-1, ul. Srednyaya Kalitnikovskaya, Moscow, 109029, Russia.
| | - Kristina Sergunova
- Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, 28-1, ul. Srednyaya Kalitnikovskaya, Moscow, 109029, Russia
| | - Alexey Petraikin
- Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, 28-1, ul. Srednyaya Kalitnikovskaya, Moscow, 109029, Russia
| | - Ekaterina Akhmad
- Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, 28-1, ul. Srednyaya Kalitnikovskaya, Moscow, 109029, Russia
| | - Stanislav Kivasev
- Hospital center of polyclinics AO, 1-3, ul. Bakuninskaya, Moscow, 105005, Russia
| | - Dmitry Semenov
- Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, 28-1, ul. Srednyaya Kalitnikovskaya, Moscow, 109029, Russia
| | - Ivan Blokhin
- Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, 28-1, ul. Srednyaya Kalitnikovskaya, Moscow, 109029, Russia
| | - Igor Karpov
- Central Institute of Traumatology and Orthopaedics named after N. N. Priorov, 10, ul. Priorova, Moscow, 127299, Russia
| | - Anton Vladzymyrskyy
- Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, 28-1, ul. Srednyaya Kalitnikovskaya, Moscow, 109029, Russia
| | - Alexander Morozov
- Central Institute of Traumatology and Orthopaedics named after N. N. Priorov, 10, ul. Priorova, Moscow, 127299, Russia
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