Liver involvement in patients with COVID-19 infection: A comprehensive overview of diagnostic imaging features

During the first wave of the pandemic, coronavirus disease 2019 (COVID-19) infection has been considered mainly as a pulmonary infection. However, different clinical and radiological manifestations were observed over time, including involvement of abdominal organs. Nowadays, the liver is considered one of the main affected abdominal organs. Hepatic involvement may be caused by either a direct damage by the virus or an indirect damage related to COVID-19 induced thrombosis or to the use of different drugs. After clinical assessment, radiology plays a key role in the evaluation of liver involvement. Ultrasonography (US), computed tomography (CT) and magnetic resonance imaging (MRI) may be used to evaluate liver involvement. US is widely available and it is considered the first-line technique to assess liver involvement in COVID-19 infection, in particular liver steatosis and portal-vein thrombosis. CT and MRI are used as second- and third-line techniques, respectively, considering their higher sensitivity and specificity compared to US for assessment of both parenchyma and vascularization. This review aims to the spectrum of COVID-19 liver involvement and the most common imaging features of COVID-19 liver damage

Active Learning on Medical Image

The development of medical science greatly depends on the increased utilization of machine learning algorithms. By incorporating machine learning, the medical imaging field can significantly improve in terms of the speed and accuracy of the diagnostic process. Computed tomography (CT), magnetic resonance imaging (MRI), X-ray imaging, ultrasound imaging, and positron emission tomography (PET) are the most commonly used types of imaging data in the diagnosis process, and machine learning can aid in detecting diseases at an early stage. However, training machine learning models with limited annotated medical image data poses a challenge. The majority of medical image datasets have limited data, which can impede the pattern-learning process of machine-learning algorithms. Additionally, the lack of labeled data is another critical issue for machine learning. In this context, active learning techniques can be employed to address the challenge of limited annotated medical image data. Active learning involves iteratively selecting the most informative samples from a large pool of unlabeled data for annotation by experts. By actively selecting the most relevant and informative samples, active learning reduces the reliance on large amounts of labeled data and maximizes the model's learning capacity with minimal human labeling effort. By incorporating active learning into the training process, medical imaging machine learning models can make more efficient use of the available labeled data, improving their accuracy and performance. This approach allows medical professionals to focus their efforts on annotating the most critical cases, while the machine learning model actively learns from these annotated samples to improve its diagnostic capabilities.Comment: 12 pages, 8 figures; Acceptance of the chapter for the Springer book "Data-driven approaches to medical imaging

Current diagnostic aspects on acute and chronic pulmonary embolism : MRI in acute pulmonary embolism, CT in chronic thromboembolic pulmonary hypertension and what the radiologists actually know

Background: Acute pulmonary embolism (APE) is a potentially severe medical condition with blood clots obstructing the pulmonary arterial vasculature. In most cases the APE resolves without any sequelae after anticoagulation therapy. In some patients, however, the emboli do not resolve upon treatment and the remnants cause increased vascular resistance, a condition known as chronic thromboembolic pulmonary hypertension (CTEPH). Both APE and CTEPH have a non-specific clinical presentation and imaging is an important part of the diagnosis. In APE computed tomography pulmonary angiography (CTPA) is the diagnostic gold standard, although the method is not suitable for all patients. CTPA has a high specificity for CTEPH, but the sensitivity remains under debate. At present CTPA is not recommended as a first line test among patients with a clinical suspicion of CTEPH. Purpose: To investigate unestablished imaging modalities in the diagnosis of APE (Study I) and CTEPH (Study III) including learning aspects (Study II) and knowledge (Study IV) of theses among radiologists. Regarding APE we studied magnetic resonance imaging (MRI) and in CTEPH we studied CTPA. Material and methods: Studies I-II were based on a prospective collection of 70 unenhanced MRI exams with CTPA as the gold standard. In Studies III-IV we used a retrospective material based on 43 CTPA exams from patients with confirmed CTEPH referred for presurgical assessment at a specialist centre, with a matched control with suspected APE. Results: All MRI exams were of diagnostic quality. Specificity was 100% for both readers and sensitivity 90% and 93% respectively with a nearly perfect inter-reader agreement (kappa 0.97) (Study I). Residents interpreting the MRI exams within the training program reached a clinically acceptable level after approximately 50 examinations and review time was halved during the training program (Study II). The sensitivity for CTEPH on CTPA reviewed by two experts was 100% and the specificity 100% (Study III), while the sensitivity based on the original reports from the same cases was 26% (Study IV). Conclusions: Unenhanced MRI has a high sensitivity and specificity for APE (Study I) and residents can learn to interpret such exams by using a self-directed training program (Study II). Enhanced CTPA has a high sensitivity when reviewed by experienced radiologists (Study III), but among radiologists in general the sensitivity is low (Study IV)

Focal Spot, Winter 2008/2009

https://digitalcommons.wustl.edu/focal_spot_archives/1110/thumbnail.jp

Quantification of atherosclerotic plaque in the elderly with positron emission tomography/computed tomography

L'athérosclérose est une maladie cardiovasculaire inflammatoire qui est devenue la première cause de morbidité et de mortalité dans les pays développés et parmi les principales causes d’invalidité au monde. Elle se caractérise par l’épaississement de la paroi vasculaire artérielle suite à l'accumulation de lipides et le dépôt d'autres substances au niveau de l’intima (endothélium) pour former la plaque d’athérome. Avec l'âge, cette plaque peut grossir, se calcifier et ainsi rétrécir le calibre de l'artère pour diminuer son débit et à un stade avancé de la maladie, elle peut se rompre et obstruer les petites artères dans n'importe quelle partie du corps causant des complications aigues, y compris la mort soudaine. L'objectif de cette thèse est de pouvoir détecter l'inflammation de la plaque athérosclérotique quantitativement avec la TEP/TDM dans le but de prévenir son détachement. Les mesures avec la TDM et la TEP avec le 18F-FDG ont été acquises chez des sujets humains âgés de 65 à 85 ans. Des analyses quantitatives ont été conduites sur les images de TDM en fonction de l'intensité et des étendues des calcifications, et sur les images de la TEP pour évaluer le métabolisme des plaques. L'effet des traitements par les statines a aussi été étudié. Au-delà la couverture de cette étude de façon détaillée au niveau physiologique en corrélant différents paramètres des plaques, et au niveau méthodologique en utilisant de nouvelles approches pour l'analyse pharmacocinétique, il en ressort principalement la suggestion de la détection de la vulnérabilité de la plaque artérielle par la TDM, plus disponible et moins coûteuse, en remplacement des analyses biochimiques, surtout la protéine C-réactive (CRP) considérée être la méthode standard.Abstract : Atherosclerosis is an inflammatory cardiovascular disease considered the leading cause of morbidity and mortality in developed countries and among the leading causes of disability worldwide. It is characterized by the thickening of the arterial vascular wall due to the accumulation of lipids and the deposition of other substances in the intima (endothelium) to form atheroma plaque. With age, this plaque can grow larger, calcify and thus narrow the size of the artery to decrease blood flow and at an advanced stage of the disease, it can rupture, be transported by blood and block the small arteries in any part of the body causing acute complications, including sudden death. The objective of this thesis was to be able to detect the inflammation of the atherosclerotic plaque quantitatively with PET/CT in order to prevent its detachment. Measurements with CT and PET with 18F-FDG were acquired in human subjects aged 65 to 85 years. Quantitative analyzes were performed on CT images based on the intensity and extent of calcifications, and on PET images to assess plaque metabolism. The effect of statin treatments has also been studied. Beyond the coverage of this study in a detailed manner at the physiological level by correlating different parameters of the plaques, and at the methodological level by using new approaches for pharmacokinetic analysis, it mainly emerges the suggestion for the detection of the vulnerability of the arterial plaque by CT alone, more available and less expensive, replacing biochemical analyzes, especially Creactive protein (CRP) considered to be the standard method