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- Ramos-Llordén, Gabriel, et al.
(författare)
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NOVIFAST : A Fast Algorithm for Accurate and Precise VFA MRIT1Mapping
- 2018
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Ingår i: IEEE Transactions on Medical Imaging. - : IEEE. - 0278-0062 .- 1558-254X. ; 37:11, s. 2414-2427
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Tidskriftsartikel (refereegranskat)abstract
- In quantitative magnetic resonance T 1 mapping, the variable flip angle (VFA) steady state spoiled gradient recalled echo (SPGR) imaging technique is popular as it provides a series of high resolution T 1 weighted images in a clinically feasible time. Fast, linear methods that estimate T 1 maps from these weighted images have been proposed, such as DESPOT1 and iterative re-weighted linear least squares. More accurate, non-linear least squares (NLLS) estimators are in play, but these are generally much slower and require careful initialization. In this paper, we present NOVIFAST, a novel NLLS-based algorithm specifically tailored to VFA SPGR T 1 mapping. By exploiting the particular structure of the SPGR model, a computationally efficient, yet accurate and precise T 1 map estimator is derived. Simulation and in vivo human brain experiments demonstrate a twenty-fold speed gain of NOVIFAST compared with conventional gradient-based NLLS estimators while maintaining a high precision and accuracy. Moreover, NOVIFAST is eight times faster than the efficient implementations of the variable projection (VARPRO) method. Furthermore, NOVIFAST is shown to be robust against initialization.
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- Vande Vyvere, Thijs, et al.
(författare)
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Central versus Local Radiological Reading of Acute Computed Tomography Characteristics in Multi-Center Traumatic Brain Injury Research
- 2019
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Ingår i: Journal of Neurotrauma. - : Mary Ann Liebert Inc. - 0897-7151 .- 1557-9042. ; 36:7, s. 1080-1092
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Tidskriftsartikel (refereegranskat)abstract
- Observer variability in local radiological reading is a major concern in large-scale multi-center traumatic brain injury (TBI) studies. A central review process has been advocated to minimize this variability. The aim of this study is to compare central with local reading of TBI imaging datasets and to investigate the added value of central review. A total of 2050 admission computed tomography (CT) scans from subjects enrolled in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study were analyzed for seven main CT characteristics. Kappa statistics were used to calculate agreement between central and local evaluations and a center-specific analysis was performed. The McNemar test was used to detect whether discordances were significant. Central interobserver and intra-observer agreement was calculated in a subset of patients. Good agreement was found between central and local assessment for the presence or absence of structural pathology (CT+, CT-, κ = 0.73) and most CT characteristics (κ = 0.62 to 0.71), except for traumatic axonal injury lesions (κ = 0.37). Despite good kappa values, discordances were significant in four of seven CT characteristics (i.e., midline shift, contusion, traumatic subarachnoid hemorrhage, and cisternal compression; p = 0.0005). Central reviewers showed substantial to excellent interobserver and intra-observer agreement (κ = 0.73 to κ = 0.96), contrasted by considerable variability in local radiological reading. Compared with local evaluation, a central review process offers a more consistent radiological reading of acute CT characteristics in TBI. It generates reliable, reproducible data and should be recommended for use in multi-center TBI studies.
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- Vande Vyvere, Thijs, et al.
(författare)
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Prognostic Validation of the NINDS Common Data Elements for the Radiologic Reporting of Acute Traumatic Brain Injuries : A CENTER-TBI Study.
- 2020
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Ingår i: Journal of Neurotrauma. - : Mary Ann Liebert. - 0897-7151 .- 1557-9042. ; 37:11, s. 1269-1282
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this study is to investigate the prognostic value of using the National Institute of Neurological Disorders and Stroke (NINDS) standardized imaging-based pathoanatomic descriptors for the evaluation and reporting of acute traumatic brain injury (TBI) lesions. For a total of 3392 patients (2244 males and 1148 females, median age = 51 years) enrolled in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we extracted 96 Common Data Elements (CDEs) from the structured reports, spanning all three levels of pathoanatomic information (i.e., 20 "basic," 60 "descriptive," and 16 "advanced" CDE variables per patient). Six-month clinical outcome scores were dichotomized into favorable (Glasgow Outcome Scale Extended [GOS-E] = 5-8) versus unfavorable (GOS-E = 1-4). Regularized logistic regression models were constructed and compared using the optimism-corrected area under the curve (AUC). An abnormality was reported for the majority of patients (64.51%). In 79.11% of those patients, there was at least one coexisting pathoanatomic lesion or associated finding. An increase in lesion severity, laterality, and volume was associated with more unfavorable outcomes. Compared with the full set of pathoanatomic descriptors (i.e., all three categories of information), reporting "basic" CDE information provides at least equal discrimination between patients with favorable versus unfavorable outcome (AUC = 0.8121 vs. 0.8155, respectively). Addition of a selected subset of "descriptive" detail to the basic CDEs could improve outcome prediction (AUC = 0.8248). Addition of "advanced" or "emerging/exploratory" information had minimal prognostic value. Our results show that the NINDS standardized-imaging based pathoanatomic descriptors can be used in large-scale studies and provide important insights into acute TBI lesion patterns. When used in clinical predictive models, they can provide excellent discrimination between patients with favorable and unfavorable 6-month outcomes. If further validated, our findings could support the development of structured and itemized templates in routine clinical radiology.
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- Vande Vyvere, Thijs, et al.
(författare)
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Prognostic Validation of the NINDS Standardized Pathoanatomic Terms and Definitions for the Reporting of Acute Traumatic Brain Injuries : A CENTER-TBI study
- 2020
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Ingår i: Journal of Neurotrauma. - : Mary Ann Liebert. - 0897-7151 .- 1557-9042. ; 37:11, s. 1269-1282
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: To aim of this study is to investigate the prognostic value of using the NINDS standardized imaging-based pathoanatomic descriptors for the evaluation and reporting of acute TBI lesions.METHODS: For a total of 3,392 patients (2,244 males and 1,148 females, Median = 51 years) enrolled in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we extracted 96 CDEs from the structured reports, spanning all three levels of pathoanatomic information (i.e. 20 "basic", 60 "descriptive" and 16 "advanced" CDE variables per patient). 6-month clinical outcome scores were dichotomized into favorable (GOS-E = 5-8) versus unfavorable (GOS-E = 1-4). Regularized logistic regression models were constructed and compared using the optimism-corrected AUC.RESULTS: An abnormality was reported for the majority of patients (64.51%). In 79.11% of those patients, there was at least one coexisting pathoanatomic lesion or associated finding. An increase in lesion severity, laterality and volume was associated with more unfavorable outcomes. Compared to the full set of pathoanatomic descriptors (i.e. all three categories of information), reporting "basic" CDE information provides at least equal discrimination between patients with favorable versus unfavorable outcome (AUC = 0.8121 vs. 0.8155, respectively). Addition of a selected subset of "descriptive" detail (i.e. location and volume) to specific basic CDEs could improve outcome prediction (AUC = 0.8248). Addition of "advanced" or "emerging" information had minimal prognostic value.CONCLUSION: Our results show that the NINDS standardized-imaging based pathoanatomic descriptors can be used in large-scale studies and provide important insights into acute TBI lesion patterns. When used in clinical predictive models, they can provide excellent discrimination between patients with favorable and unfavorable 6-month outcomes. If further validated, our findings could support the development of structured and itemized templates in routine clinical radiology. Key words: Traumatic Brain Injury, Computed Tomography, Common Data Elements, Structured Reporting.
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