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United States (US) Special Operations Forces (SOF) are frequently exposed to explosive blasts in training and combat, but the effects of repeated blast exposure (RBE) on SOF brain health are incompletely understood. Furthermore, there is no diagnostic test to detect brain injury from RBE. As a result, SOF personnel may experience cognitive, physical, and psychological symptoms for which the cause is never identified, and they may return to training or combat during a period of brain vulnerability. In 30 active-duty US SOF, we assessed the relationship between cumulative blast exposure and cognitive performance, psychological health, physical symptoms, blood proteomics, and neuroimaging measures (Connectome structural and diffusion MRI, 7 Tesla functional MRI, [11C]PBR28 translocator protein [TSPO] positron emission tomography [PET]-MRI, and [18F]MK6240 tau PET-MRI), adjusting for age, combat exposure, and blunt head trauma. Higher blast exposure was associated with increased cortical thickness in the left rostral anterior cingulate cortex (rACC), a finding that remained significant after multiple comparison correction. In uncorrected analyses, higher blast exposure was associated with worse health-related quality of life, decreased functional connectivity in the executive control network, decreased TSPO signal in the right rACC, and increased cortical thickness in the right rACC, right insula, and right medial orbitofrontal cortex-nodes of the executive control, salience, and default mode networks. These observations suggest that the rACC may be susceptible to blast overpressure and that a multimodal, network-based diagnostic approach has the potential to detect brain injury associated with RBE in active-duty SOF.
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Traumatismos por Explosión , Personal Militar , Humanos , Traumatismos por Explosión/diagnóstico por imagen , Adulto , Masculino , Estados Unidos , Imagen por Resonancia Magnética , Femenino , Tomografía de Emisión de Positrones , Cognición/fisiología , Encéfalo/diagnóstico por imagen , Encéfalo/metabolismo , Adulto JovenRESUMEN
BACKGROUND: The COVID-19 pandemic posed numerous challenges to health systems around the world. In addressing many of those challenges, Israel responded quite rapidly. While quick action is not an end in it itself, it can be important in responding to disease outbreaks. Some of Israel's rapid responses to the pandemic contributed significantly to population health and provided important learning opportunities for other countries. MAIN BODY: Some of the most prominent Israeli rapid responses were related to vaccination. Israel led the world in the pace of its initial vaccine rollout, and it was also the first country to approve and administer booster vaccines to broad segments of the population. In addition, Israeli scholars published a series of timely reports analyzing vaccination impact, which informed policy in Israel and other countries. Israel was a rapid responder in additional areas of public health. These include the partial closure of its borders, the adoption of physical distancing measures, the use of digital surveillance technology for contact tracing, the use of wastewater surveillance to monitor viral spread, and the use of vaccine certificates ("green passes") to facilitate a return to routine in the face of the ongoing pandemic. Many factors contributed to Israel's capacity to repeatedly respond rapidly to a broad array of COVID-19 challenges. These include a national health insurance system that promotes public-private coordination, a system of universal electronic health records, a high level of emergency preparedness, a culture of focusing on goal attainment, a culture of innovation, and the presence of a strong scientific community which is highly connected internationally. In addition, some of the rapid responses (e.g., the rapid initial vaccination rollout) facilitated rapid responses in related areas (e.g., the analysis of vaccination impact, the administration of boosters, and the adoption of green passes). While rapid response can contribute to population health and economic resilience, it can also entail costs, risks, and limitations. These include making decisions and acting before all the relevant information is available; deciding without sufficient consideration of the full range of possible effects, costs, and benefits; not providing enough opportunities for the involvement of relevant groups in the decision-making process; and depleting non-renewable resources. CONCLUSIONS: Based on our findings, we encourage leaders in the Israeli government to ensure that its emergency response system will continue to have the capacity to respond rapidly to large-scale challenges, whether of a military or civilian nature. At the same time, the emergency response systems should develop mechanisms to include more stakeholders in the fast-paced decision-making process and should improve communication with the public. In addition, they should put into place mechanisms for timely reconsideration, adjustment, and-when warranted-reversal of decisions which, while reasonable when reached, turn out to have been ill-advised in the light of subsequent developments and evidence. These mechanisms could potentially involve any or all branches of government, as well as the public, the press, and professional organizations. Our findings also have implications for health system leaders in other countries. The Israeli experience can help them identify key capacities to develop during non-emergency periods, thus positioning themselves to respond more rapidly in an emergency. Finally, health system leaders in other countries could monitor Israel's rapid responses to future global health emergencies and adopt selected actions in their own countries.
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COVID-19 , Vacunas , Humanos , COVID-19/prevención & control , Israel/epidemiología , Pandemias/prevención & control , Aguas Residuales , Monitoreo Epidemiológico Basado en Aguas ResidualesRESUMEN
Accurate image reconstruction is at the heart of diagnostics in medical imaging. Supervised deep learning-based approaches have been investigated for solving inverse problems including image reconstruction. However, these trained models encounter unseen data distributions that are widely shifted from training data during deployment. Therefore, it is essential to assess whether a given input falls within the training data distribution. Current uncertainty estimation approaches focus on providing an uncertainty map to radiologists, rather than assessing the training distribution fit. In this work, we propose a method based on the local Lipschitz metric to distinguish out-of-distribution images from in-distribution with an area under the curve of 99.94% for True Positive Rate versus False Positive Rate. We demonstrate a very strong relationship between the local Lipschitz value and mean absolute error (MAE), supported by a Spearman's rank correlation coefficient of 0.8475, to determine an uncertainty estimation threshold for optimal performance. Through the identification of false positives, we demonstrate the local Lipschitz and MAE relationship can guide data augmentation and reduce uncertainty. Our study was validated using the AUTOMAP architecture for sensor-to-image Magnetic Resonance Imaging (MRI) reconstruction. We demonstrate our approach outperforms baseline techniques of Monte-Carlo dropout and deep ensembles as well as the state-of-the-art Mean Variance Estimation (MVE) network approach. We expand our application scope to MRI denoising and Computed Tomography (CT) sparse-to-full view reconstructions using UNET architectures. We show our approach is applicable to various architectures and applications, especially in medical imaging, where preserving diagnostic accuracy of reconstructed images remains paramount.
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The blood-brain barrier (BBB) is a barrier protecting the brain and a milieu of continuous exchanges between blood and brain. There is emerging evidence that the BBB plays a major role in epileptogenesis and drug-resistant epilepsy, through several mechanisms, such as water homeostasis dysregulation, overexpression of drug transporters, and inflammation. Studies have shown abnormal water homeostasis in epileptic tissue and altered aquaporin-4 water channel expression in animal epilepsy models. This review focuses on abnormal water exchange in epilepsy and describes recent non-invasive MRI methods of quantifying water exchange. PLAIN LANGUAGE SUMMARY: Abnormal exchange between blood and brain contribute to seizures and epilepsy. The authors describe why correct water balance is necessary for healthy brain functioning and how it is impacted in epilepsy. This review also presents recent MRI methods to measure water exchange in human brain. These measures would improve our understanding of factors leading to seizures.
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Barrera Hematoencefálica , Epilepsia , Neuroimagen , Barrera Hematoencefálica/metabolismo , Humanos , Epilepsia/metabolismo , Epilepsia/diagnóstico por imagen , Epilepsia/fisiopatología , Animales , Agua/metabolismo , Imagen por Resonancia Magnética , Encéfalo/metabolismo , Encéfalo/diagnóstico por imagen , Encéfalo/fisiopatologíaRESUMEN
Purpose To present results from a literature survey on practices in deep learning segmentation algorithm evaluation and perform a study on expert quality perception of brain tumor segmentation. Materials and Methods A total of 180 articles reporting on brain tumor segmentation algorithms were surveyed for the reported quality evaluation. Additionally, ratings of segmentation quality on a four-point scale were collected from medical professionals for 60 brain tumor segmentation cases. Results Of the surveyed articles, Dice score, sensitivity, and Hausdorff distance were the most popular metrics to report segmentation performance. Notably, only 2.8% of the articles included clinical experts' evaluation of segmentation quality. The experimental results revealed a low interrater agreement (Krippendorff α, 0.34) in experts' segmentation quality perception. Furthermore, the correlations between the ratings and commonly used quantitative quality metrics were low (Kendall tau between Dice score and mean rating, 0.23; Kendall tau between Hausdorff distance and mean rating, 0.51), with large variability among the experts. Conclusion The results demonstrate that quality ratings are prone to variability due to the ambiguity of tumor boundaries and individual perceptual differences, and existing metrics do not capture the clinical perception of segmentation quality. Keywords: Brain Tumor Segmentation, Deep Learning Algorithms, Glioblastoma, Cancer, Machine Learning Clinical trial registration nos. NCT00756106 and NCT00662506 Supplemental material is available for this article. © RSNA, 2023.
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Neoplasias Encefálicas , Aprendizaje Profundo , Glioblastoma , Humanos , Algoritmos , Benchmarking , Neoplasias Encefálicas/diagnóstico por imagen , Glioblastoma/diagnóstico por imagenRESUMEN
OBJECTIVE: To investigate the association between clinical data, white matter lesions and inflammatory cerebrospinal fluid (CSF) findings in HTLV-1 associated myelopathy/tropical spastic paraparesis (HAM/TSP). METHOD: We studied brain and cervical spinal cord on magnetic resonance imaging (MRI) and CSF examinations of 28 Brazilian HAM/TSP patients. RESULTS: The majority of patients had severe neurological incapacity with EDSS median of 6.5 (3-8). The brain MRI showed white matter lesions (75%) and atrophy (14%). The preferential brain location was periventricular. Cervical demyelination lesions occurred in 11% of the cases, and cervical atrophy in 3.5%. One patient had enhancement lesions on T1 cervical spinal cord MRI. Cases with spinal cord lesions had signs of acute CSF inflammation. The brain white matter lesions predominated in the patients with higher age. CONCLUSION: Our data suggest that an active inflammatory process is associated with the cervical spinal cord lesions in HAM/TSP. The brain abnormalities are not related to the clinical picture of HAM/TSP.
OBJETIVO: Analisar a associação entre aspectos clínicos, lesões de substância branca e reação inflamatória aguda no líquido cefalorraquidiano (LCR) na mielopatia associa ao HTLV-1 (HAM/TSP). MÉTODO: Foram estudadas ressonâncias magnéticas (RM) do encéfalo/medula espinhal cervical e exame do LCR de 28 pacientes com HAM/TSP. RESULTADOS: A maioria dos pacientes apresentava grave incapacidade neurológica, com EDSS 6,5 (3-8). A RM revelou lesões da substância branca (75%) com predominância periventricular e atrofia cortical (14%). Lesões desmielinizantes cervicais ocorreram em 11% dos casos e atrofia em 3,5%. Um paciente apresentou lesão cervical na T1 com captação de contraste. Sinais de inflamação aguda no LCR ocorreram em situações de lesão da medula espinhal cervical. As alterações de substância branca do encéfalo predominaram nos indivíduos com maior faixa etária. CONCLUSÃO: Nossos achados sugerem que processo inflamatório com atividade clínica na HAM/TSP está associado a lesões da medula espinhal cervical. As anormalidades da substância branca encefálicas não são relacionadas ao quadro clínico de HAM/TSP.