Journal of internal medicine
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Pathology is the cornerstone of cancer care. The need for accuracy in histopathologic diagnosis of cancer is increasing as personalized cancer therapy requires accurate biomarker assessment. The appearance of digital image analysis holds promise to improve both the volume and precision of histomorphological evaluation. ⋯ Furthermore, deep learning models have also been demonstrated to be able to predict status of some molecular markers in lung, prostate, gastric and colorectal cancer based on standard HE slides. Moreover, prognostic (survival outcomes) deep neural network models based on digitized HE slides have been demonstrated in several diseases, including lung cancer, melanoma and glioma. In this review, we aim to present and summarize the latest developments in digital image analysis and in the application of artificial intelligence in diagnostic pathology.
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Aortic pathologies such as aneurysm, dissection and trauma are relatively common and potentially fatal diseases. Over the past two decades, we have experienced unprecedented technical and medical developments in the field. Despite this, there is a great need, and great opportunities, to further explore the area. ⋯ A key limitation of contemporary treatment strategies of AAA is the lack of therapy directed at small AAA, to prevent AAA expansion and need for surgical repair, as well as to reduce the risk for aortic rupture. Currently, the most promising potential drug candidate to slow AAA growth is metformin, and RCTs to verify or reject this hypothesis are warranted. In addition, the role of endovascular treatment for ascending pathologies and for uncomplicated type B aortic dissection needs to be clarified.
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Multiple sclerosis (MS), a chronic inflammatory demyelinating and neurodegenerative disease of the central nervous system, is today a leading cause of unpredictable lifelong disability in young adults. The treatment of patients in progressive stages remains highly challenging, alluding to our limited understanding of the underlying pathological processes. In this review, we provide insights into the mechanisms underpinning MS progression from a perspective of epigenetics, that refers to stable and mitotically heritable, yet reversible, changes in the genome activity and gene expression. ⋯ Despite minor overlap at individual methylation sites, nearly 30% of altered genes reported in peripheral immune cells of progressive MS patients were found in brain tissue, jointly converging on alterations of neuronal functions. We further speculate about the mechanisms underlying shared epigenetic patterns between blood and brain, which likely imply the influence of internal (genetic control) and/or external (e.g. smoking and ageing) factors imprinting a common signature in both compartments. Overall, we propose that epigenetics might shed light on clinically relevant mechanisms involved in disease progression and open new avenues for the treatment of progressive MS patients in the future.
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Abdominal aortic aneurysm (AAA) is a relatively common and potentially fatal disease. The management of AAA has undergone extensive changes in the last two decades. High quality vascular surgical registries were established early and have been found to be instrumental in the evaluation and monitoring of these changes, most notably the wide implementation of minimally invasive endovascular surgical technology. ⋯ By using large-scale data over longer periods of time, the importance of centralization of care to high-volume centres was shown, particularly for open repair. Additionally, large-scale databases can offer an opportunity to assess practice and outcomes in patient subgroups (e.g. treatment of AAA in women and the elderly) as well as in rare aortic pathologies. In this review article, we point out the most important paradigm shifts in AAA management based on vascular registry data.