SIGNIFICANCE, MIDTERM RESULTS AND EXPERIENCES OF THE BUDAPEST ONCOLOGY CT AND MR WAITING LISTS REDUCTION PROGRAM

BACKGROUND – High-value medical imaging diagnostic procedures are key elements of the diagnostic process of patients with suspected oncological disease and in determining the effectiveness of the initiated therapy. In Hungary, due to the high diagnostic demands, diagnostic waiting lists for computed tomography (CT) or magnetic resonance imaging (MR) are usually long and result in less transparent reporting times, even in the case of individuals who are potentially suspected of having a malignant disease, or in the case of the follow-up of effectiveness of treatment of diagnosed cancer patients. THE AIM OF THE PRESENT STUDY – Midterm analysis of the onco-diagnostic Program in Budapest implemented within the framework of the Healthy Budapest Program (HBP), gain experiences and presentation of underlying health policy processes. RESULTS – From November 2020 till 31st of December 2022 within the framework of the Program, the Municipality of Budapest has reimbursed 5437 contrast-enhanced CT and 2948 MR examinations with "C” or "D” disease diagnosis. Examinations has been financed in a sector-neutral manner to public and private healthcare providers in the so-called ‘BP' reimbursement category. The report undertaken by Semmelweis University has found, that in Budapest Municipality funded patients, radiological examinations were performed on average 15.2 days sooner (16.1 vs. 31.1 days), than in the case of the National Health Insurance Fund funded patients, the mean waiting time for CT/MR examination was shortened by 13.0 days (4.2 vs. 17.2 days, respectively). In 86% of cases, patients used the Program once, in 14% twice or more. Utilization of the Program shows a significant difference by the different districts of the Capital: the number of cases – originally planned based on demographic, prevalence and incidence data, broken down by district – was utilized between 3-45% for CT, and 8-37% for MR cases, respectively, by district residents mainly referred by district outpatient clinic specialists, between the period of November 2020 and August 2022. CONCLUSION – The Program has been utilised in a smaller scale, than it was originally planned before COVID, in terms of its cases. The program has achieved its aim through the reduction of CT and MR diagnostic waiting times and waiting lists, and it has an indirect effect in generally reducing waiting times at medical imaging. However, this is not sufficient to speed up and provide more efficient service for the entire oncology diagnostic process. Therefore, we wish to further develop the Program in the direction of adding additional diagnostic examinations and developing a patient pathway management module. © 2023 Literatura Medica Publishing House. All rights reserved.

SIGNIFICANCE, MIDTERM RESULTS AND EXPERIENCES OF THE BUDAPEST ONCOLOGY CT AND MR WAITING LISTS REDUCTION PROGRAM

BACKGROUND – High-value medical imaging diagnostic procedures are key elements of the diagnostic process of patients with suspected oncological disease and in determining the effectiveness of the initiated therapy. In Hungary, due to the high diagnostic demands, diagnostic waiting lists for computed tomography (CT) or magnetic resonance imaging (MR) are usually long and result in less transparent reporting times, even in the case of individuals who are potentially suspected of having a malignant disease, or in the case of the follow-up of effectiveness of treatment of diagnosed cancer patients. THE AIM OF THE PRESENT STUDY – Midterm analysis of the onco-diagnostic Program in Budapest implemented within the framework of the Healthy Budapest Program (HBP), gain experiences and presentation of underlying health policy processes. RESULTS – From November 2020 till 31st of December 2022 within the framework of the Program, the Municipality of Budapest has reimbursed 5437 contrast-enhanced CT and 2948 MR examinations with "C” or "D” disease diagnosis. Examinations has been financed in a sector-neutral manner to public and private healthcare providers in the so-called ‘BP' reimbursement category. The report undertaken by Semmelweis University has found, that in Budapest Municipality funded patients, radiological examinations were performed on average 15.2 days sooner (16.1 vs. 31.1 days), than in the case of the National Health Insurance Fund funded patients, the mean waiting time for CT/MR examination was shortened by 13.0 days (4.2 vs. 17.2 days, respectively). In 86% of cases, patients used the Program once, in 14% twice or more. Utilization of the Program shows a significant difference by the different districts of the Capital: the number of cases – originally planned based on demographic, prevalence and incidence data, broken down by district – was utilized between 3-45% for CT, and 8-37% for MR cases, respectively, by district residents mainly referred by district outpatient clinic specialists, between the period of November 2020 and August 2022. CONCLUSION – The Program has been utilised in a smaller scale, than it was originally planned before COVID, in terms of its cases. The program has achieved its aim through the reduction of CT and MR diagnostic waiting times and waiting lists, and it has an indirect effect in generally reducing waiting times at medical imaging. However, this is not sufficient to speed up and provide more efficient service for the entire oncology diagnostic process. Therefore, we wish to further develop the Program in the direction of adding additional diagnostic examinations and developing a patient pathway management module. © 2023 Literatura Medica Publishing House. All rights reserved.

Low‐Altitude UAV Imaging Accurately Quantifies Eelgrass Wasting Disease From Alaska to California

Declines in eelgrass, an important and widespread coastal habitat, are associated with wasting disease in recent outbreaks on the Pacific coast of North America. This study presents a novel method for mapping and predicting wasting disease using Unoccupied Aerial Vehicle (UAV) with low‐altitude autonomous imaging of visible bands. We conducted UAV mapping and sampling in intertidal eelgrass beds across multiple sites in Alaska, British Columbia, and California. We designed and implemented a UAV low‐altitude mapping protocol to detect disease prevalence and validated against in situ results. Our analysis revealed that green leaf area index derived from UAV imagery was a strong and significant (inverse) predictor of spatial distribution and severity of wasting disease measured on the ground, especially for regions with extensive disease infection. This study highlights a novel, efficient, and portable method to investigate seagrass disease at landscape scales across geographic regions and conditions.Alternate abstract:Plain Language SummaryDiseases of marine organisms are increasing in many regions worldwide, therefore, efficient time‐series monitoring is critical for understanding the dynamics of disease and examining its progression in time to implement management interventions. In the first study of its kind, we use high‐resolution Unoccupied Aerial Vehicle (UAV) imagery collected to detect disease at 12 sites across the North‐East Pacific coast of North America spanning 18 degrees of latitude. The low altitude UAV visible‐bands imagery achieved 1.5 cm spatial resolution, and analysis was performed at the seagrass leaf scale based on object‐oriented image analysis. Our findings suggest that drone mapping of coastal plants may substantially increase the scale of disease risk assessments in nearshore habitats and further our understanding of seagrass meadow spatial‐temporal dynamics. These can be scaled up by searching for environmental signals of the pathogen, for example, with surveillance of wastewater for signs of Covid in human populations. This application could easily apply to other areas to construct a high‐resolution monitoring network for seagrass conservation.

Impact based on quarantine psychology: analysis of left and right brain hemispheres

Brain, the most powerful object in the universe, consumes only a few watts of energy. To replicate it, a nuclear power plant will be necessary, and this powerhouse is the sole controller of the human body. Normally, the brain is divided into two parts, with the left and right hemispheres working independently. The right half of the brain tends to cause mental tension and anxiety, exacerbating the present physiological condition like the current COVID-19 outbreak. A survey was done in the Durg district of Chhattisgarh, which is one of the hardest hit epicenters of the COVID-19 second wave in India. According to this survey, the majority of women of all ages are right brained, meaning their right hemisphere predominates over their left. They are more likely to suffer from mental illnesses than men because they are more inventive and creative thinkers. To avoid this circumstance, stress-relieving activities have been developed.

Transient Elastography of Liver and Serum Hyaluronic Acid Levels In Adult Transfusion Dependent Thalassemia Patients

Iron overload occurs as a result of multiple blood transfusions and increased iron absorption in thalassemia patients. Iron deposition in liver results in liver stiffness and fibrosis. Non invasive methods including imaging and serum biomarkers have been introduced for assessment of liver fibrosis. We aimed to study liver stiffness using transient elastography and serum hyaluronic acid levels and correlate them with serum ferritin levels in adult transfusion dependent beta thalassemia patients. MATERIAL: 70 transfusion dependent thalassemia patients of age ≥18 years, registered at Thalassemia Day Care Centre were subjected to investigations like CBC, Liver function tests, viral markers, serum ferritin, serum hyaluronic acid levels and transient elastography. Fibrosis indices like FIB-4, AAR and APRI were also calculated. 45 patients had T2*MRI reports with them;which were also included and analysed. Spearman coefficient r was used to test correlations between TE values and serum HA levels with other variables. OBSERVATION: 70 patients (41 male and 29 female) with mean age of 24.09±5.38 years and BMI 20.51 ±3.47 kg/m², were enrolled. Median values of hemoglobin, AST, ALT, TE, serum HA and serum ferritin were, 9.15 g/dl, 42 IU/L, 47.50 IU/L, 9.1 kPa, 284 ng/dl and 1841 ng/ml, respectively . TE values had significant positive correlation with serum ferritin (r=0.5, p < 0.001), ALT (r=0.59, p < 0.001), AST (r=0.58, p< 0.001), APRI (r=0.5, p<0.001) and FIB-4 (p=0.02), respectively and significant negative correlation with T2* MRI (ms) (r= -0.5, p<0.001). No significant correlation of HA was found with any variable. CONCLUSION: Transient elastography can be used as a non expensive, easily accessible and non invasive marker of liver iron overload. Further detailed studies are required to establish the role of serum Hyaluronic acid in thalassemia patients. © Journal of the Association of Physicians of India 2011.

Unlocking the benefits of the Baveno VI guidance when screening for varices: an audit of clinical practice across London.

Background: The Baveno VI consensus identifies patients with compensated advanced chronic liver disease (cACLD) who can safely avoid screening endoscopy. However, concordance in clinical practice with this guidance is unknown. We audited clinical practice and the provision of transient elastography (TE) aiming to identify potential cost savings and benefits. Methods: Retrospective data collection from 12 sites across London over 6 months by reviewing oesophagogastroduodenoscopy (OGD) reports, platelet count and TE results as well as information on site-specific provision of TE. Results: Three-hundred and fifty-one screening procedures were identified; 177 (50.43%) had a TE test performed within the preceding 12 months; 142 (80.23%) patients with a recent TE test did not meet criteria for screening OGD. TE provision varied widely between sites. Conclusion: Improving concordance with the Baveno criteria through improved provision of TE would have benefits for patients, healthcare systems and the environment and would help to address the challenges of moving on from the COVID-19 pandemic.

Contrast-Enhanced Ultrasound and Shear Wave Elastography: Novel Methods for the Evaluation of Urethral Stricture Disease.

PURPOSE: Urologists will benefit from an imaging modality which can assess intra and extraluminal characteristics of urethral strictures. We conducted a prospective pilot study evaluating the utility of contrast-enhanced ultrasound and shear wave elastography for the evaluation of bulbar urethral stricture disease. MATERIALS AND METHODS: Patients with a single, bulbar urethral stricture were prospectively recruited. Contrast-enhanced ultrasound and shear wave elastography were performed at the time of surgical repair and at 4 months' followup using an Aplio i800 scanner (Canon Medical Systems, Tustin, California) with an i8CX1 transducer. Sulfur hexafluoride lipid-type A microsphere ultrasound contrast (Lumason®, Bracco Imaging, Princeton, New Jersey) was injected retrograde through the urethra. Stiffness of the corpus spongiosum was measured at and adjacent to the stricture site. Stricture lengths based on retrograde urethrogram, grayscale ultrasound and contrast-enhanced ultrasound were correlated with measured intraoperative stricture length. RESULTS: Thirty men were enrolled. Contrast-enhanced ultrasound (R2=0.709) showed the best correlation with intraoperative measured stricture length compared to retrograde urethrogram (R2=0.016) or grayscale ultrasound (R2=0.471). Stiffness of the spongiosum was greater at the site of the stricture (32.6±5.4 vs 27.3±5.8 kPa, p=0.044) and in narrower caliber strictures (p=0.044) but did not differ by stricture length (p=0.182). At followup (4.3±1.1 months) contrast-enhanced ultrasound detected stricture recurrence with 80% sensitivity, 100% specificity, and 93% accuracy compared to cystoscopy. CONCLUSIONS: This pilot study demonstrates the ability of contrast-enhanced ultrasound and shear wave elastography to become safe, accurate, and potentially efficacious modalities for assessing bulbar urethral strictures and spongiofibrosis.

Biodegradable Cationic Nanoparticles as a Push Chemodrug Carrier and a Pull cfDNA Scavenger Against Breast Cancer Metastasis

The goal of this project is to develop a novel therapeutic approach for the prevention of breast cancer metastasis, by using nucleic acid binding nanoparticles (NABNPs) designed to deliver high payloads of cytotoxic drugs to tumor tissues, while simultaneously scavenging the pro-inflammatory cell-free DNA (cfDNA) that is released in the blood circulation as a result oftumor progression and/or destruction by chemotherapy. This is a collaborative research project conducted in partnership by two teams, supported by two distinct awards (BC180904, BC180904P1). Among the key aims of the research supported by this award (BC180904P1, partnering team) is the development of experimental models that enable the visualization and quantification of breast cancer dissemination in live animals, using non-invasive imaging techniques that can detect biox2;luminescent signals from live cancer cells, and compare them over time, in order to obtain longitudinal measurements of both the anatomical location and overall burden of metastatic tissue. During the first year of the award, we engineered multiple triple negative breast cancer (TNBC) cell lines with different lentivirus constructs, each encoding for both fluorescent (EGFP, ZsGreen) and bioluminescent reporters (different variants of Luciferase from the firefly Photinus pyralis). We then compared the performance of the various lentivirus constructs in terms of sensitivity and stability of expression over time, in both mouse and human TNBC cells, in vitro and in vivo. Our experiments led to the generation of 3 independent TNBC cell lines (1 murine, 2 human) expressing high levels of both ZsGreen and Luciferase (Photinus pyralis), and can be efficiently monitored in terms of longitudinal growth and spontaneous metastatic dissemination in live animals.

Impact of Interstitial Lung Diseases and COVID-19 on the body

Medical imaging techniques are often used in treatment and follow-ups for diagnosed diseases. Image scans provide quick acquisition of images and clear and precise information, along with a magnified view of a particular portion of the body. Chest images can demonstrate various lung disorders, such as, COVID-19, Interstitial Lung Diseases (ILD) and Chronic lung disease, Pneumonia, Bronchiectasis, Cystic Fibrosis, etc. However, subtle changes in the volume and character of lung abnormalities can be difficult to assess even by expert radiologists. This is where Artificial Intelligence (AI) comes in. AI can aid traditional medical imaging technology by offering computational prowess that process images with greater speed and precision. This work presents a solution that performs AI-empowered analysis of Chest image scans for diagnosis, tracking and prognosis of various lung diseases. © 2021 IEEE

Classification of COVID-19 from chest X-ray images using a deep convolutional neural network

The COVID-19 pandemic, also known as the coronavirus pandemic, is one of a major outbreak spreading across many countries around the world. It impacts severely on the health and life of many people all around the world. Medical imaging is a widely accepted technique for the early detection and diagnosis of disease that includes different techniques such as X-ray, computed tomography (CT) scan etc. For diagnosis COVID-19, chest X-ray is the imaging technique that plays an important role. In the recent years, deep neural networks have been successfully applied in many computer vision tasks including medical imaging. In this paper, we have experimented and evaluated DenseNet model for the classification of COVID-19 chest X-ray images. For that, a publicly available dataset contains 6432 chest X-ray images categorizes into 3 classes were used. Transfer learning and fine-tuning is applied for training the three variant of DenseNet model namely DenseNet121, DenseNet169 and DenseNet201. After evaluating the performance, it has been found that DenseNet201 achieved highest validation accuracy i.e. 0.9367 and lowest validation loss i.e. 0.1653 for classification of COVID-19 in chest X-ray images.

Follow-up CT of "reversed halo sign" in SARS-CoV-2 delta VOC pneumonia: A report of two cases.

In December 2019, a new type of virus, coronavirus disease 2019 broke out globally and caused great harm. The virus mutates rapidly, and more research reports are urgently needed to increase our understanding of the disease. We found the reversed halo sign (RHS) occurred in the imaging manifestations of severe acute respiratory syndrome coronavirus 2 delta variant of concern pneumonia. In the absence of pathology, the mechanism is unknown. Therefore, we reported two cases of RHS and tried to speculate the pathological mechanism through multiple computed tomography follow-up comparisons to judge the prognosis of the disease.

Impact of COVID-19 on the imaging diagnosis of cardiac disease in Europe.

OBJECTIVES: We aimed to explore the impact of the COVID-19 pandemic on cardiac diagnostic testing and practice and to assess its impact in different regions in Europe. METHODS: The online survey organised by the International Atomic Energy Agency Division of Human Health collected information on changes in cardiac imaging procedural volumes between March 2019 and March/April 2020. Data were collected from 909 centres in 108 countries. RESULTS: Centres in Northern and Southern Europe were more likely to cancel all outpatient activities compared with Western and Eastern Europe. There was a greater reduction in total procedure volumes in Europe compared with the rest of the world in March 2020 (45% vs 41%, p=0.003), with a more marked reduction in Southern Europe (58%), but by April 2020 this was similar in Europe and the rest of the world (69% vs 63%, p=0.261). Regional variations were apparent between imaging modalities, but the largest reductions were in Southern Europe for nearly all modalities. In March 2020, location in Southern Europe was the only independent predictor of the reduction in procedure volume. However, in April 2020, lower gross domestic product and higher COVID-19 deaths were the only independent predictors. CONCLUSION: The first wave of the COVID-19 pandemic had a significant impact on care of patients with cardiac disease, with substantial regional variations in Europe. This has potential long-term implications for patients and plans are required to enable the diagnosis of non-COVID-19 conditions during the ongoing pandemic.

SARS-CoV-2 diagnosis using medical imaging techniques and artificial intelligence: A review.

OBJECTIVE: SARS-CoV-2 is a worldwide health emergency with unrecognized clinical features. This paper aims to review the most recent medical imaging techniques used for the diagnosis of SARS-CoV-2 and their potential contributions to attenuate the pandemic. Recent researches, including artificial intelligence tools, will be described. METHODS: We review the main clinical features of SARS-CoV-2 revealed by different medical imaging techniques. First, we present the clinical findings of each technique. Then, we describe several artificial intelligence approaches introduced for the SARS-CoV-2 diagnosis. RESULTS: CT is the most accurate diagnostic modality of SARS-CoV-2. Additionally, ground-glass opacities and consolidation are the most common signs of SARS-CoV-2 in CT images. However, other findings such as reticular pattern, and crazy paving could be observed. We also found that pleural effusion and pneumothorax features are less common in SARS-CoV-2. According to the literature, the B lines artifacts and pleural line irregularities are the common signs of SARS-CoV-2 in ultrasound images. We have also stated the different studies, focusing on artificial intelligence tools, to evaluate the SARS-CoV-2 severity. We found that most of the reported works based on deep learning focused on the detection of SARS-CoV-2 from medical images while the challenge for the radiologists is how to differentiate between SARS-CoV-2 and other viral infections with the same clinical features. CONCLUSION: The identification of SARS-CoV-2 manifestations on medical images is a key step in radiological workflow for the diagnosis of the virus and could be useful for researchers working on computer-aided diagnosis of pulmonary infections.