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- Delgado, Anna Falk, et al.
(författare)
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Glioma Grade Discrimination with MR Diffusion Kurtosis Imaging : A Meta-Analysis of Diagnostic Accuracy
- 2018
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Ingår i: Radiology. - : RADIOLOGICAL SOC NORTH AMERICA. - 0033-8419 .- 1527-1315. ; 287:1, s. 119-127
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To assess the diagnostic test accuracy and sources of heterogeneity for the discriminative potential of diffusion kurtosis imaging (DKI) to differentiate low-grade glioma (LGG) (World Health Organization [WHO] grade II) from high-grade glioma (HGG) (WHO grade III or IV).Materials and Methods: The Cochrane Library, Embase, Medline, and the Web of Science Core Collection were systematically searched by two librarians. Retrieved hits were screened for inclusion and were evaluated with the revised tool for quality assessment for diagnostic accuracy studies (commonly known as QUADAS-2) by two researchers. Statistical analysis comprised a random-effects model with associated heterogeneity analysis for mean differences in mean kurtosis (MK) in patients with LGG or HGG. A bivariate restricted maximum likelihood estimation method was used to describe the summary receiver operating characteristics curve and bivariate meta-regression.Results: Ten studies involving 430 patients were included. The mean difference in MK between LGG and HGG was 0.17 (95% confidence interval [CI]: 0.11, 0.22) with a z score equal to 5.86 (P<.001). The statistical heterogeneity was explained by glioma subtype, echo time, and the proportion of recurrent glioma versus primary glioma. The pooled area under the curve was 0.94 for discrimination of HGG from LGG, with 0.85 (95% CI: 0.74, 0.92) sensitivity and 0.92 (95% CI: 0.81, 0.96) specificity. Heterogeneity was driven by neuropathologic subtype and DKI technique.Conclusion: MK shows high diagnostic accuracy in the discrimination of LGG from HGG.
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| 2. |
- Falk Delgado, Alberto, et al.
(författare)
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Arterial spin labeling MR imaging for differentiation between high- and low-grade glioma - A meta-analysis
- 2018
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Ingår i: Neuro-Oncology. - : Oxford University Press (OUP). - 1522-8517 .- 1523-5866. ; 20:11, s. 1450-1461
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Tidskriftsartikel (refereegranskat)abstract
- Background. Arterial spin labeling is an MR imaging technique that measures cerebral blood flow (CBF) noninvasively. The aim of the study is to assess the diagnostic performance of arterial spin labeling (ASL) MR imaging for differentiation between high-grade glioma and low-grade glioma. Methods. Cochrane Library, Embase, Medline, and Web of Science Core Collection were searched. Study selection ended November 2017. This study was prospectively registered in PROSPERO (CRD42017080885). Two authors screened all titles and abstracts for possible inclusion. Data were extracted independently by 2 authors. Bivariate random effects meta-analysis was used to describe summary receiver operating characteristics. Trial sequential analysis (TSA) was performed. Results. In total, 15 studies with 505 patients were included. The diagnostic performance of ASL CBF for glioma grading was 0.90 with summary sensitivity 0.89 (0.79-0.90) and specificity 0.80 (0.72-0.89). The diagnostic performance was similar between pulsed ASL (AUC 0.90) with a sensitivity 0.85 (0.71-0.91) and specificity 0.83 (0.69- 0.92) and pseudocontinuous ASL (AUC 0.88) with a sensitivity 0.86 (0.79-0.91) and specificity 0.80 (0.65-0.87). In astrocytomas, the diagnostic performance was 0.89 with sensitivity 0.86 (0.79 to 0.91) and specificity 0.79 (0.63 to 0.89). Sensitivity analysis confirmed the robustness of the findings. TSA revealed that the meta-analysis was adequately powered. Conclusion. Arterial spin labeling MR imaging had an excellent diagnostic accuracy for differentiation between high-grade and low-grade glioma. Given its low cost, non-invasiveness, and efficacy, ASL MR imaging should be considered for implementation in the routine workup of patients with glioma.
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| 3. |
- Falk Delgado, Anna, et al.
(författare)
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Diagnostic value of alternative techniques to gadolinium-based contrast agents in MR neuroimaging : a comprehensive overview
- 2019
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Ingår i: Insights into Imaging. - : Springer Science and Business Media LLC. - 1869-4101. ; 10:1
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Forskningsöversikt (refereegranskat)abstract
- Gadolinium-based contrast agents (GBCAs) increase lesion detection and improve disease characterization for many cerebral pathologies investigated with MRI. These agents, introduced in the late 1980s, are in wide use today. However, some non-ionic linear GBCAs have been associated with the development of nephrogenic systemic fibrosis in patients with kidney failure. Gadolinium deposition has also been found in deep brain structures, although it is of unclear clinical relevance. Hence, new guidelines from the International Society for Magnetic Resonance in Medicine advocate cautious use of GBCA in clinical and research practice. Some linear GBCAs were restricted from use by the European Medicines Agency (EMA) in 2017.This review focuses on non-contrast-enhanced MRI techniques that can serve as alternatives for the use of GBCAs. Clinical studies on the diagnostic performance of non-contrast-enhanced as well as contrast-enhanced MRI methods, both well established and newly proposed, were included. Advantages and disadvantages together with the diagnostic performance of each method are detailed. Non-contrast-enhanced MRIs discussed in this review are arterial spin labeling (ASL), time of flight (TOF), phase contrast (PC), diffusion-weighted imaging (DWI), magnetic resonance spectroscopy (MRS), susceptibility weighted imaging (SWI), and amide proton transfer (APT) imaging.Ten common diseases were identified for which studies reported comparisons of non-contrast-enhanced and contrast-enhanced MRI. These specific diseases include primary brain tumors, metastases, abscess, multiple sclerosis, and vascular conditions such as aneurysm, arteriovenous malformation, arteriovenous fistula, intracranial carotid artery occlusive disease, hemorrhagic, and ischemic stroke.In general, non-contrast-enhanced techniques showed comparable diagnostic performance to contrast-enhanced MRI for specific diagnostic questions. However, some diagnoses still require contrast-enhanced imaging for a complete examination.
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| 4. |
- Falk Delgado, Anna, et al.
(författare)
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Diffusion kurtosis imaging of gliomas grades II and III : a study of perilesional tumor infiltration, tumor grades and subtypes at clinical presentation
- 2017
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Ingår i: Radiology and Oncology. - : Walter de Gruyter GmbH. - 1318-2099 .- 1581-3207. ; 51:2, s. 121-129
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Tidskriftsartikel (refereegranskat)abstract
- Background. Diffusion kurtosis imaging (DKI) allows for assessment of diffusion influenced by microcellular structures. We analyzed DKI in suspected low-grade gliomas prior to histopathological diagnosis. The aim was to investigate if diffusion parameters in the perilesional normal-appearing white matter (NAWM) differed from contralesional white matter, and to investigate differences between glioma malignancy grades II and III and glioma subtypes (astrocytomas and oligodendrogliomas).Patients and methods. Forty-eight patients with suspected low-grade glioma were prospectively recruited to this institutional review board-approved study and investigated with preoperative DKI at 3T after written informed consent. Patients with histologically proven glioma grades II or III were further analyzed (n=35). Regions of interest (ROIs) were delineated on T2FLAIR images and co-registered to diffusion MRI parameter maps. Mean DKI data were compared between perilesional and contralesional NAWM (student's t-test for dependent samples, Wilcoxon matched pairs test). Histogram DKI data were compared between glioma types and glioma grades (multiple comparisons of mean ranks for all groups). The discriminating potential for DKI in assessing glioma type and grade was assessed with receiver operating characteristics (ROC) curves.Results. There were significant differences in all mean DKI variables between perilesional and contralesional NAWM (p=< 0.000), except for axial kurtosis (p=0.099). Forty-four histogram variables differed significantly between glioma grades II (n=23) and III (n=12) (p=0.003-0.048) and 10 variables differed significantly between ACs (n=18) and ODs (n=17) (p=0.011-0.050). ROC curves of the best discriminating variables had an area under the curve (AUC) of 0.657-0.815.Conclusions. Mean DKI variables in perilesional NAWM differ significantly from contralesional NAWM, suggesting altered microstructure by tumor infiltration not depicted on morphological MRI. Histogram analysis of DKI data identifies differences between glioma grades and subtypes.
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