1,721,109 research outputs found
Pearls, Pitfalls, and Mimics in Pediatric Head and Neck Imaging
No full text: Children present with a spectrum of head and neck pathologies that differ from those found in the adult population, with specific image findings and clinical characteristics. This article reviews the imaging protocols, pearls and pitfalls, and mimics of pediatric head and neck lesions, stressing the combination of key radiological findings, clinical presentation, and anatomic localization necessary to correctly interpret the imaging
Radiomics in Cardiovascular Disease Imaging: from Pixels to the Heart of the Problem
Full text linkPurpose of Review
This review of the literature aims to present potential applications of radiomics in cardiovascular radiology and, in particular, in cardiac imaging.
Recent Findings
Radiomics and machine learning represent a technological innovation which may be used to extract and analyze quantitative features from medical images. They aid in detecting hidden pattern in medical data, possibly leading to new insights in pathophysiology of different medical conditions. In the recent literature, radiomics and machine learning have been investigated for numerous potential applications in cardiovascular imaging. They have been proposed to improve image acquisition and reconstruction, for anatomical structure automated segmentation or automated characterization of cardiologic diseases.
Summary
The number of applications for radiomics and machine learning is continuing to rise, even though methodological and implementation issues still limit their use in daily practice. In the long term, they may have a positive impact in patient management
Facioscapulohumeral muscular dystrophy (FSHD) and multiple sclerosis: a case report
No full text: Facioscapulohumeral muscular dystrophy 1 (FSHD1) is an autosomal dominant neuromuscular disorder, associated with reduction of tandemly arrayed repetitive DNA elements D4Z4 (DRA), at 4q35. Few cases, especially carriers of 1-3 DRA show a syndromic form. Anecdotally the association of FSHD with multiple sclerosis (MS) is reported. Herein we report a 33 years old Caucasian with a molecular diagnosis of FSHD1 with classical phenotype (clinical category A2) and concomitant white matter lesions suggestive of MS. White matter lesions in patients with FSHD have often been described but rarely investigated in order to evaluate a possible diagnosis of MS. We think that MS and FSHD remain clearly distinct diseases, but growing evidences show a widespread and variable activation of the immune system in patients suffering from FSHD probably an hypotheses on a potential common pathogenetic mechanism between these two disorders could should be better investigated
Machine Learning in Oncology: A Clinical Appraisal
No full textMachine learning (ML) is a branch of artificial intelligence centered on algorithms which do not need explicit prior programming to function but automatically learn from available data, creating decision models to complete tasks. ML-based tools have numerous promising applications in several fields of medicine. Its use has grown following the increased availability of patient data due to technological advances such as digital health records and high-volume information extraction from medical images. Multiple ML algorithms have been proposed for applications in oncology. For instance, they have been employed for oncological risk assessment, automated segmentation, lesion detection, characterization, grading and staging, prediction of prognosis and therapy response. In the near future, ML could become essential part of every step of oncological screening strategies and patients' management thus leading to precision medicine
Computed tomography and magnetic resonance imaging in pediatric salivary gland diseases: a guide to the differential diagnosis
No full textSalivary gland pathologies in children are frequent, particularly viral infections, but rarely need cross-sectional imaging. However, when a mass involves the salivary spaces (primarily or as a secondary invasion from other neck spaces) it may pose problems in the differential diagnosis and in immediate management. Infrequently, systemic autoimmune diseases can also involve the salivary parenchyma in children and correctly interpreting the constellation of findings in the whole body is critical for the diagnosis. Distinguishing between cystic and solid masses is the first step for radiologists in order to narrow down the diagnosis. Location and spatial extension are the most important elements differentiating cystic masses, while signal characteristics, internal structure and local invasion help in the differential diagnosis of solid masses
Radiologic diagnosis of non-traumatic paediatric head and neck emergencies
No full textImaging plays a crucial role in evaluating paediatric patients with non-traumatic head and neck lesions in an emergency setting because clinical manifestations of these entities can overlap. For this reason, radiologists must be familiar with the clinical and imaging findings of prevalent paediatric head and neck emergencies. In this review, we present techniques and imaging clues for common complications of pathological processes in the paediatric head and neck, with a focus on the clinical scenario as a starting point for the radiologic approach
Computed tomography and magnetic resonance imaging machine learning applications for renal cell carcinoma
No full textThe aim of this chapter is to offer an overview of the wide range of radiomics and machine learning applications that have been proposed for renal cell carcinoma (RCC) imaging. After describing the epidemiological, clinical, and pathological features of RCC, we explore the crucial role of imaging in the diagnosis, characterization, and follow-up of this disease
Superparamagnetic iron oxide nanocolloids in MRI studies of neuroinflammation
No full textIron oxide (IO) nanocolloids are being increasingly used to image cellular contribution to neuroinflammation using MRI, as these particles are capable of labeling circulating cells with phagocytic activity, allowing to assess cell trafficking from the blood to neuroinflammation sites. The use of IOs relies on the natural phagocytic properties of immune cells, allowing their labeling either in vitro or directly in vivo, following intravenous injection. Despite concerns on the specificity of the latter approach, the widespread availability and relatively low cost of these techniques, coupled to a sensitivity that allows to reach single cell detection, have promoted their use in several preclinical and clinical studies.
In this review, we discuss the results of currently available preclinical and clinical IO-enhanced MRI studies of immune cell trafficking in neuroinflammation, examining the specificity of the existing findings, in view of the different possible mechanisms underlying IO accumulation in the brain. From this standpoint, we assess the implications of the temporal and spatial differences in the enhancement pattern of IOs, compared to gadolinium based contrast agents, a clinically established MRI marker blood-brain barrier breakdown. While concerns on the specificity of cell labeling obtained using the in-vivo labeling approach still need to be fully addressed, these techniques have indeed proved able to provide additional information on neuroinflammatory phenomena, as compared to conventional Gadolinium-enhanced MRI
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