Analysis of Serum Cholesterol, Statins and Atherosclerotic Plaque in Ruptured and Unruptured Intracranial Aneurysm

Introduction Intracranial aneurysm (IA) is a major healthcare concern. The use of statin to reduce serum cholesterol has shown evidence to reduce cardiovascular risk in various diseases, but the impact on IA has not been described. This study aims to determine whether statin use, and serum cholesterol levels interfere with outcomes after IA event. Methods A cohort of patients with IA was analyzed. Patients social and demographics data were collected. Modified Rankin scale (mRS) score after 6 months of follow-up was the endpoint. The data regarding statins use, presence or not of atherosclerotic plaque in radiological images and serum cholesterol of 35 patients were included in our study. Linear regression models were used to determine the influence of those 6 variables in the clinical outcome. Results The prevalence of atherosclerotic plaque, high cholesterol and use of statins was 34.3%, 48.5%, and 14.2%, respectively. Statins and serum cholesterol did not impact the overall outcome, measured by mRS after 6 months (p > 0.05), but did show different tendencies when separated by IA rupture status. Serum cholesterol shows an important association with rupture of aneurysm (p = 0.0382). High cholesterol and use of statins show a tendency for worse outcome with ruptured aneurysm, and the opposite is true for unruptured aneurysm. The presence of atherosclerotic plaques was not related with worse outcomes. Conclusions Multiple and opposite mechanisms might be involved in the pathophysiology of IA. Ruptured aneurysms are associated with higher levels of serum cholesterol. Serum cholesterol and statins use were not correlated with worse outcomes, but further studies are important to clarify these relationships.

Are we mindful of nasal dorsal integrity during septal surgery? An imaging study of nasal keystone area

Objectives: Review of radiological images of the keystone area to assess risk of disruption to the nasal dorsum when separating the osseo-cartilaginous junction in septoplasty. Methods: A Cross sectional radiological study of adults who underwent CT scan of paranasal sinuses. Outcome measures included were: The Length of the keystone area (shorter length implies a higher risk of disruption) and a high-risk shape (high risk shape implies shorter keystone area) that can predispose to disruption of nasal dorsal integrity during septoplasty surgery. Certain nasal dimensions were evaluated to determine if they add risk to the dorsum. Results: CT scans of 343 patients were reviewed. The mean keystone area length was initially 10.42 mm that came down to 7.43 mm after adjustment in patients with high-risk shape. 31.5% of subjects were at risk of disruption to the dorsum due to short keystone area length <5 mm. Relatively shorter nasal bones (nasal bone length: overall dorsal length <0.49%) were associated with a shorter keystone area length (P = 0.004). Age, gender, septal deviation are not risk factors as they did not significantly influence keystone area length. Conclusions: One third of our patients (31.5%) had short KSA length < 5mm which carries higher risk of disruption to the dorsum integrity upon complete detachment of osseo-cartilaginous junction. We recommend preoperative CT imaging for thorough evaluation and precise measurement of KSA. Patients with relatively shorter nasal bones detected on examination (and confirmed radiologically), need to be recognized as they are more likely to have shorter KSA

Screening of Radiological Images Suspected of Containing Lung Nodules

This paper presents a study about screening large radiological image streams produced in hospitals for earlier detection of lung nodules. Being one of the most difficult classification tasks in the literature, our objective is to measure how well state-of-the-art classifiers can screen out the images stream to keep as many positive cases as possible in an output stream to be inspected by clinicians. We performed several experiments with different image resolutions and training datasets from different sources, always taking ResNet-152 as the base neural network. Results over existing datasets show that, contrary to other diseases like pneumonia, detecting nodules is a hard task when using only radiographies. Indeed, final diagnosis by clinicians is usually performed with much more precise images like computed tomographies.

Three-Dimensional Virtual Anatomy as a New Approach for Medical Student’s Learning

Most medical and health science schools adopt innovative tools to implement the teaching of anatomy to their undergraduate students. The increase in technological resources for educational purposes allows the use of virtual systems in the field of medicine, which can be considered decisive for improving anatomical knowledge, a requisite for safe and competent medical practice. Among these virtual tools, the Anatomage Table 7.0 represents, to date, a pivotal anatomical device for student education and training medical professionals. This review focuses attention on the potential of the Anatomage Table in the anatomical learning process and clinical practice by discussing these topics based on recent publication findings and describing their trends during the COVID-19 pandemic period. The reports documented a great interest in and a positive impact of the use of this technological table by medical students for teaching gross anatomy. Anatomage allows to describe, with accuracy and at high resolution, organ structure, vascularization, and innervation, as well as enables to familiarize with radiological images of real patients by improving knowledge in the radiological and surgical fields. Furthermore, its use can be considered strategic in a pandemic period, since it ensures, through an online platform, the continuation of anatomical and surgical training on dissecting cadavers.

Iliopectineal line: A valuable radiological reference for spino-pelvic parameters

Objectives: Spinopelvic parameters are crucial to address sagittal spinal imbalance; such measurements require standardized lateral radiographs that include spine and hips, which are neither always available, nor readily feasible intra-operatively. The aim of this study was to describe pelvic radiological reference points that could provide reliable sagittal balance estimates from conventional lumbosacral lateral radiographs. Methods: A descriptive, cross-sectional, radiological-based study was conducted. Readings were taken from institute’s digital radiology library, blinded to personal and clinical data. The correlation was made to conventional pelvic incidence (CPI), conventional pelvic tilt (CPT), and sacral slope (SS), measured for the same patients, and from the same standardized standing radiographs that included femoral heads. Results: Radiological images for 140 adult subjects, with suspected or established spine problems were studied. The average lumbar lordosis (LL) of 3 readers was 47 ± 13 (13–81) with an interclass agreement of 0.9, SS was 41 ± 9 with an interclass agreement of 0.9, CPI was 53 ± 10 with an interclass agreement of 0.8, CPT was 14 ± 8 with an interclass agreement of 0.9, iliopectineal inclination (IPI) of 4 readers was 64 ± 8 with an interclass agreement of 0.7 and iliopectineal tilt (IPT) was 24 ± 8 with an interclass agreement of 0.8 LL was with 6° of CPI and 16° of IPI. The CPI was equal to (CPI = SS + [CPT + 1.2]) and (IPI = SS + [IPT + 0.6]). The IPI was negatively correlated with CPI –0.2 P = 0.006, and IPI was negatively correlated with CPT –0.333 P < 0.001. Conclusion: Iliopectineal line provides reproducible readings, closer values to LL, and addresses the center of mass displacement.

Hemorrhagic Transformation After Ischemic Stroke: Mechanisms and Management

Symptomatic hemorrhagic transformation (HT) is one of the complications most likely to lead to death in patients with acute ischemic stroke. HT after acute ischemic stroke is diagnosed when certain areas of cerebral infarction appear as cerebral hemorrhage on radiological images. Its mechanisms are usually explained by disruption of the blood-brain barrier and reperfusion injury that causes leakage of peripheral blood cells. In ischemic infarction, HT may be a natural progression of acute ischemic stroke and can be facilitated or enhanced by reperfusion therapy. Therefore, to balance risks and benefits, HT occurrence in acute stroke settings is an important factor to be considered by physicians to determine whether recanalization therapy should be performed. This review aims to illustrate the pathophysiological mechanisms of HT, outline most HT-related factors after reperfusion therapy, and describe prevention strategies for the occurrence and enlargement of HT, such as blood pressure control. Finally, we propose a promising therapeutic approach based on biological research studies that would help clinicians treat such catastrophic complications.

Comparison of GANs for Covid-19 X-ray classification

Image classification has been applied to several real problems. However, getting labeled data is a costly task, since it demands time, resources and experts. Furthermore, some domains like disease detection suffer from unbalanced classes. These scenarios are challenging and degrade the performance of machine learning algorithms. In these cases, we can use Data Augmentation (DA) approaches to increase the number of labeled examples in a dataset. The objective of this work is to analyze the use of Generative Adversarial Networks (GANs) as DA, which are capable of synthesizing artificial data from the original data, under an adversarial process of two neural networks. The GANs are applied in the classification of unbalanced Covid-19 radiological images. Increasing the number of images led to better accuracy for all the GANs tested, especially in the multi-label dataset, mitigating the bias for unbalanced classes.

PneumoniaNet: Automated Detection and Classification of Pediatric Pneumonia Using Chest X-ray Images and CNN Approach

Pneumonia is an inflammation of the lung parenchyma that is caused by a variety of infectious microorganisms and non-infective agents. All age groups can be affected; however, in most cases, fragile groups are more susceptible than others. Radiological images such as Chest X-ray (CXR) images provide early detection and prompt action, where typical CXR for such a disease is characterized by radiopaque appearance or seemingly solid segment at the affected parts of the lung due to inflammatory exudate formation replacing the air in the alveoli. The early and accurate detection of pneumonia is crucial to avoid fatal ramifications, particularly in children and seniors. In this paper, we propose a novel 50 layers Convolutional Neural Network (CNN)-based architecture that outperforms the state-of-the-art models. The suggested framework is trained using 5852 CXR images and statistically tested using five-fold cross-validation. The model can distinguish between three classes: viz viral, bacterial, and normal; with 99.7% ± 0.2 accuracy, 99.74% ± 0.1 sensitivity, and 0.9812 Area Under the Curve (AUC). The results are promising, and the new architecture can be used to recognize pneumonia early with cost-effectiveness and high accuracy, especially in remote areas that lack proper access to expert radiologists, and therefore, reduces pneumonia-caused mortality rates.