Objective: To assess the value of non-contrast MRI features for characterisation of uterine leiomyosarcoma (LMS) and differentiation from atypical benign leiomyomas.
Methods: This study included 57 atypical leiomyomas and 16 LMS which were referred pre-operatively for management review to the specialist gynaeoncology multidisciplinary team meeting. Non-contrast MRIs were retrospectively reviewed by five independent readers (three senior, two junior) and a 5-level Likert score (1-low/5-high) was assigned to each mass for likelihood of LMS. Evaluation of qualitative and quantitative MRI features was done using uni- and multivariable regression analysis. Inter-reader reliability for the assessment of MRI features was calculated by using Cohen's κ values.
Results: In the univariate analysis, interruption of the endometrial interface and irregular tumour shape had the highest odds ratios (ORs) (64.00, < 0.001 and 12.00, = 0.002, respectively) for prediction of LMS. Likert score of the mass was significant in prediction (OR, 3.14; < 0.001) with excellent reliability between readers (ICC 0.86; 95% CI, 0.76-0.92). The post-menopausal status, interruption of endometrial interface and thickened endometrial stripe were the most predictive independent variables in multivariable estimation of the risk of leiomyosarcoma with an accuracy of 0.88 (95%CI, 0.78-0.94).
Conclusion: At any level of expertise as a radiologist reader, the loss of the normal endometrial stripe (either thickened or not seen) in a post-menopausal patient with a myometrial mass was highly likely to be LMS.
Advances In Knowledge: This study demonstrates the potential utility of non-contrast MRI features in characterisation of LMS over atypical leiomyomas, and therefore influence on optimal management of these cases.
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http://dx.doi.org/10.1259/bjr.20210115 | DOI Listing |
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Vanderbilt University Medical Center, Nashville, TN, USA.
Background: We report the case of a 79-year-old woman with Alzheimer's disease who enrolled in a clinical study of lecanemab. After the third, biweekly infusion she suffered a seizure followed by aphasia and progressive encephalopathy. Magnetic resonance imaging revealed multifocal cerebral edema and an increased burden of cerebral microhemorrhages compared to pre-trial imaging.
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December 2024
Inserm, Sorbonne Université, Centre de Recherche Saint-Antoine, Immune System and Neuroinflammation Laboratory, Hôpital Saint-Antoine, Paris, France.
Background: Chronic innate neuroinflammation mediated by microglia and astrocytes in response to Aβ and pathological Tau species is a cardinal feature of AD that contributes to disease pathogenesis. Accumulating evidence now also highlight an instrumental role of T cells and peripheral-central immune crosstalk in the pathophysiology of AD. Both preclinical and clinical reports suggest the potential therapeutic interest of peripheral immunomodulatory approaches aimed at amplifying regulatory T cells (Tregs), e.
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December 2024
Department of Psychology & Language Sciences, University College London, London, United Kingdom.
Background: Dysphagia is an important feature of neurodegenerative diseases and potentially life-threatening in primary progressive aphasia (PPA), but remains poorly characterised in these syndromes. We hypothesised that dysphagia would be more prevalent in nonfluent/agrammatic variant (nfv)PPA than other PPA syndromes, predicted by accompanying motor features and associated with atrophy affecting regions implicated in swallowing control.
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Alzheimers Dement
December 2024
National University, Muscat, Muscat, Oman.
Background: This study explores Alzheimer's prediction through brain MRI images, utilizing Convolutional Neural Networks (CNNs) and Lime interpretability. Based on an extensive ADNI MRI dataset, we demonstrate promising results in predicting Alzheimer's disease. Local Interpretable Model Agnostic Explanations (LIME) shed light on decision-making processes, enhancing transparency.
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December 2024
Alzheimer's Disease Neuroimaging Initiative, http://adni.loni.usc.edu/, CA, USA.
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