Magnetic Resonance Visibility, Artifacts, and Overall Safety of the Self-Locating Peritoneal Dialysis Catheter with a Tungsten Tip.

Background: The self-locating peritoneal dialysis (PD) catheter, contains a tungsten tip. The effects of magnetic resonance (MR) on the catheter were evaluated, emphasizing its MR signal, artifacts, ferromagnetism, and possible heating production during the MR sequences. Methods: The catheter was studied in an ex vivo model using a 1.5T MR system and placed into a plastic box containing saline solution. Acquisitions on coronal and axial planes were obtained on fast gradient-echo T1-weighted and fast spin-echo T2-weighted. In vivo abdominal MR exams were also carried out. Results: Overall, the catheter had good visibility. In all sequences, an extensive paramagnetic blooming artifact was detected at the level of the tip tungsten ballast, with a circular artifact of 5 cm in diameter. The catheter showed no magnetic deflection, rotation, or movements during all MR sequences. After imaging, the temperature of the saline solution did not change compared to the basal measurement. Patients safely underwent abdominal MR. Conclusions: The results point to the possibility of safely performing MR in PD patients carrying the self-locating catheter. The self-locating PD catheter is stable when subjected to a 1.5T MR system. However, it creates some visual interference, preventing an accurate study of the tissues surrounding the tungsten tip.

Aortoiliac Occlusion Disease.

Leriche syndrome is characterized by abdominal aorta and/or bilateral iliac occlusive disease, with a triad of clinical symptoms and signs such as claudication, erectile dysfunction, and decreased distal pulses. Diagnostic imaging is one of the key factors for diagnosis of the anatomic origin of the Leriche symptoms. We report the case of a 56-year-old man with diagnosis of abdominal aorta and bilateral iliac occlusive disease with a wide collateral vascular network.

Abdominal Aorta Anastomotic False Aneurysm Leading to Double Focal Vertebral Body Erosion.

Anastomotic aortic false aneurysm with consequent erosion of vertebral bodies is a very rare event that needs prompt treatment. We report the case of a 71-year-old man with an aortobifemoral graft that was complicated by an uninfected proximal anastomotic pseudoaneurysm with double focal vertebral body erosion.

Ruptured Popliteal Artery Aneurysm.

Rupture of a popliteal artery aneurysm is an uncommon event in an uncommon disease. We present the case of an 88-year-old female with a ruptured popliteal artery aneurysm that was diagnosed by multidetector computed tomography and treated by an endovascular approach.

Congenital Anatomical Variant with Cranial Origin of Internal Iliac Arteries.

We report the case of a 73-year-old male who underwent abdominal multidetector computed tomography with vascular reconstruction that highlighted a congenital variant of iliac arteries. Iliac artery anatomical variants are exceedingly rare and only a few cases have been reported in the literature.

AIforCOVID: Predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre study.

Recent epidemiological data report that worldwide more than 53 million people have been infected by SARS-CoV-2, resulting in 1.3 million deaths. The disease has been spreading very rapidly and few months after the identification of the first infected, shortage of hospital resources quickly became a problem. In this work we investigate whether artificial intelligence working with chest X-ray (CXR) scans and clinical data can be used as a possible tool for the early identification of patients at risk of severe outcome, like intensive care or death. Indeed, further to induce lower radiation dose than computed tomography (CT), CXR is a simpler and faster radiological technique, being also more widespread. In this respect, we present three approaches that use features extracted from CXR images, either handcrafted or automatically learnt by convolutional neuronal networks, which are then integrated with the clinical data. As a further contribution, this work introduces a repository that collects data from 820 patients enrolled in six Italian hospitals in spring 2020 during the first COVID-19 emergency. The dataset includes CXR images, several clinical attributes and clinical outcomes. Exhaustive evaluation shows promising performance both in 10-fold and leave-one-centre-out cross-validation, suggesting that clinical data and images have the potential to provide useful information for the management of patients and hospital resources.

Multiple Myeloma: Lytic Bone Lesions of the Skull.

A 77-year-old woman with a 1 years history of Multiple Myeloma (MM) presented with headache, fatigue, and bone pain. She underwent whole body multi-detector computed tomographic (MD-CT) to evaluate possible lytic bone lesions. MD-CT showed small, multiple osteolytic lesions, particularly at the skull level (Figure 1, 2). MM is a plasma cell disorder. It is characterized by the monoclonal proliferation of malignant plasma cells (1,2). These cells, among their various characteristics, determine an infiltrate haemopoietic locations (1). Pathogenesis of MM related bone disease is the uncoupling of the bone remodelling process. There is an increased activity of osteoclastogenesis with the suppressed osteoblastic one, resulting in bone loss (1- 3). This process creates lytic lesions without reactive bone formation (2). Bone disease could be from single lytic lesion to multiple lytic lesions affecting any part of skeleton, preferably skull, spine and long bones (3). MD-CT, with dedicated low-dose protocols, is able to provide whole body skeletal volume information with a greater sensitivity than conventional X-ray studies in MM patients (3). Whole body CT with lowdose protocols can detect lesions with less than 5% trabecular bone destruction, and it is the first-line diagnostic imaging procedure for the diagnosis of lytic bone disease in patients affected by MM (4). When skull is involved, its most common MD-CT presentation is by numerous, well-circumscribed and punched-out lytic bone lesions, without reactive bone formation and diffuse osteopenia (1-5), as in the case presented.

Machine Learning to Predict In-Hospital Mortality in COVID-19 Patients Using Computed Tomography-Derived Pulmonary and Vascular Features.

Pulmonary parenchymal and vascular damage are frequently reported in COVID-19 patients and can be assessed with unenhanced chest computed tomography (CT), widely used as a triaging exam. Integrating clinical data, chest CT features, and CT-derived vascular metrics, we aimed to build a predictive model of in-hospital mortality using univariate analysis (Mann-Whitney U test) and machine learning models (support vectors machines (SVM) and multilayer perceptrons (MLP)). Patients with RT-PCR-confirmed SARS-CoV-2 infection and unenhanced chest CT performed on emergency department admission were included after retrieving their outcome (discharge or death), with an 85/15% training/test dataset split. Out of 897 patients, the 229 (26%) patients who died during hospitalization had higher median pulmonary artery diameter (29.0 mm) than patients who survived (27.0 mm, p < 0.001) and higher median ascending aortic diameter (36.6 mm versus 34.0 mm, p < 0.001). SVM and MLP best models considered the same ten input features, yielding a 0.747 (precision 0.522, recall 0.800) and 0.844 (precision 0.680, recall 0.567) area under the curve, respectively. In this model integrating clinical and radiological data, pulmonary artery diameter was the third most important predictor after age and parenchymal involvement extent, contributing to reliable in-hospital mortality prediction, highlighting the value of vascular metrics in improving patient stratification.

Epicardial fat inflammation response to COVID-19 therapies.

OBJECTIVE: Adipose tissue plays a role in the novel coronavirus disease 2019 (COVID-19). Epicardial adipose tissue (EAT), a unique visceral fat, presents with a high degree of inflammation in severe COVID-19. Whether and how adipose tissue may respond to the COVID-19 therapies is unknown. METHODS: The difference in computed tomography-measured EAT and subcutaneous (SAT) attenuation, defined as mean attenuation expressed in Hounsfield units (HU), was retrospectively analyzed in 72 patients (mean [SD] age was 59.6 [12.4] years, 50 patients [69%] were men) at the hospital admission for COVID-19 and 99 days (interquartile range = 71-129) after discharge. RESULTS: At the admission, EAT-HU was significantly correlated with blood glucose levels, interleukin 6, troponin T levels, and waist circumference. EAT-HU decreased from -87.21 (16.18) to -100.0 (11) (p < 0.001), whereas SAT-HU did not change (-110.21 [12.1] to -111.11 [27.82]; p = 0.78) after therapy. Changes in EAT-HU (expressed as ∆) significantly correlated with dexamethasone therapy (r = -0.46, p = 0.006) and when dexamethasone was combined with tocilizumab (r = -0.24, p = 0.04). CONCLUSIONS: Dexamethasone therapy was associated with significant reduction of EAT inflammation in COVID-19 patients, whereas SAT showed no changes. Anti-inflammatory therapies targeting visceral fat may be helpful in COVID-19.

Generalized chest CT and lab curves throughout the course of COVID-19.

A better understanding of temporal relationships between chest CT and labs may provide a reference for disease severity over the disease course. Generalized curves of lung opacity volume and density over time can be used as standardized references from well before symptoms develop to over a month after recovery, when residual lung opacities remain. 739 patients with COVID-19 underwent CT and RT-PCR in an outbreak setting between January 21st and April 12th, 2020. 29 of 739 patients had serial exams (121 CTs and 279 laboratory measurements) over 50 ± 16 days, with an average of 4.2 sequential CTs each. Sequential volumes of total lung, overall opacity and opacity subtypes (ground glass opacity [GGO] and consolidation) were extracted using deep learning and manual segmentation. Generalized temporal curves of CT and laboratory measurements were correlated. Lung opacities appeared 3.4 ± 2.2 days prior to symptom onset. Opacity peaked 1 day after symptom onset. GGO onset was earlier and resolved later than consolidation. Lactate dehydrogenase, and C-reactive protein peaked earlier than procalcitonin and leukopenia. The temporal relationships of quantitative CT features and clinical labs have distinctive patterns and peaks in relation to symptom onset, which may inform early clinical course in patients with mild COVID-19 pneumonia, or may shed light upon chronic lung effects or mechanisms of medical countermeasures in clinical trials.

Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan.

The recent outbreak of Coronavirus Disease 2019 (COVID-19) has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. The current guideline is using RT-PCR for testing. As a complimentary tool with diagnostic imaging, chest Computed Tomography (CT) has been shown to be able to reveal visual patterns characteristic for COVID-19, which has definite value at several stages during the disease course. To facilitate CT analysis, recent efforts have focused on computer-aided characterization and diagnosis with chest CT scan, which has shown promising results. However, domain shift of data across clinical data centers poses a serious challenge when deploying learning-based models. A common way to alleviate this issue is to fine-tune the model locally with the target domains local data and annotations. Unfortunately, the availability and quality of local annotations usually varies due to heterogeneity in equipment and distribution of medical resources across the globe. This impact may be pronounced in the detection of COVID-19, since the relevant patterns vary in size, shape, and texture. In this work, we attempt to find a solution for this challenge via federated and semi-supervised learning. A multi-national database consisting of 1704 scans from three countries is adopted to study the performance gap, when training a model with one dataset and applying it to another. Expert radiologists manually delineated 945 scans for COVID-19 findings. In handling the variability in both the data and annotations, a novel federated semi-supervised learning technique is proposed to fully utilize all available data (with or without annotations). Federated learning avoids the need for sensitive data-sharing, which makes it favorable for institutions and nations with strict regulatory policy on data privacy. Moreover, semi-supervision potentially reduces the annotation burden under a distributed setting. The proposed framework is shown to be effective compared to fully supervised scenarios with conventional data sharing instead of model weight sharing.

The role of lung ultrasound as a frontline diagnostic tool in the era of COVID-19 outbreak.

The diffusion of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) worldwide prompted the World Health Organization to declare the status of pandemic. The molecular diagnosis of SARS-CoV-2 infection is based on the detection of viral RNA on different biological specimens. Unfortunately, the test may require several hours to be performed. In the present study, we evaluated the diagnostic accuracy of lung point-of-care ultrasound (POCUS) for SARS-CoV-2 pneumonia in a cohort of symptomatic patients admitted to one emergency department (ED) in a high-prevalence setting. This retrospective study enrolled all patients who visited one ED with suspected respiratory infection in March 2020. All the patients were tested (usually twice if the first was negative) for SARS-CoV-2 on ED admission. The reference standard was considered positive if at least one specimen was positive. If all the specimens tested negative, the reference was considered negative. Diagnostic accuracy was evaluated using sensitivity, specificity, and positive and negative predictive value. Of the 444 symptomatic patients who were admitted to the ED in the study period, the result of the lung POCUS test was available for 384 (86.5%). The sensitivity of the test was 92.0% (95% CI 88.2-94.9%), and the specificity was 64.9% (95% CI 54.6-74.4%). We observed a prevalence of SARS-CoV-2 infection of 74.7%. In this setting, the positive and negative predicted values were 88.6% (95% CI 84.4-92.0) and 73.3% (95% CI 62.6-82.2%), respectively. Lung POCUS is a sensitive first-line screening tool for ED patients presenting with symptoms suggestive of SARS-CoV-2 infection.

Isolated olfactory cleft involvement in SARS-CoV-2 infection: prevalence and clinical correlates.

PURPOSE: Smell alterations are a symptom of COVID-19 and have been associated with olfactory cleft mucosal thickening (OCMT). Although their pathogenesis is unclear, evidences link them to viral neuroinvasive potential. This study aims at estimating the prevalence of OCMT in CT scans of COVID-19 patients and investigating its clinical correlates. METHODS: In a single-institution retrospective cross-sectional study, we included all patients hospitalized for COVID-19 undergoing head CT scan for any reason. Exclusion criteria were history of recent head trauma or chronic rhinosinusitis; opacification > 2 mm in any sinonasal space other than the olfactory cleft; CT performed during/after invasive ventilation or feeding via nasogastric tube. We recorded the prevalence of OCMT and related it to age, sex, need for invasive ventilation during hospital stay, outcome, length of hospital stay, diffusion of lung SARS-CoV-19 lesions and outcome. RESULTS: 63 eligible patients were identified (39 male, 24 female; median age 77.82 ± 17.77 years). OCMT was identified in 16 patients (25.4%; 95% CI 15.3-37.9%). Patients with OCMT had longer hospital stays (median 16 ± 4 vs. 9 ± 14.5 days, p = .009, Mann-Whitney U test) and required invasive ventilation more frequently than patients without mucosal thickening (OR 4.89, 95% CI 0.96-24.89, p = .063, Fisher's test). No other difference was observed. CONCLUSION: OCMT affects nearly one in four patients hospitalized for COVID-19. It is associated with a worse disease course irrespective of age, sex and diffusion of lung lesions, although with no direct effect on survival.

Endovascular management of the deep venous thrombosis: A new challenging role for the endovascular specialist in 2020.

Over the last years, the endovascular approach to the management of the acute and chronic deep vein thrombosis (DVT) has gained more and more attention from the scientific community. DVT is the third most common cardiovascular disease after coronary heart disease and stroke, with classic treatment based on anticoagulation. Recent evidences have highlighted the risk of postthrombotic syndrome as high as 30%-50% in proximal ilio-femoral lesions, with irreversible clinical symptoms and impact on the quality of life of the population. Since 2000s, the new concept of thrombus removal in the acute phase has been supported by the introduction of different techniques based on the endovascular ablation of the clot by in-situ fibrinolysis and, more recently, fragmentation and aspiration. In the chronic phase, recanalization of the thrombosed segment is recommended by stent placement to remove the obstruction and eventually reduce the congestion. Immediate technical success of these procedures is widely satisfying, whereas the long-term clinical benefits are still debated. This paper presents an overview of the modern management of the DVT by endovascular approach with regard to the clinical contexts, interventional strategies and clinical outcomes. Endovascular specialist needs to be aware of this incoming challenge, as local expertise is demanded for the modern management of these patients in multidisciplinary theaters.

Multicenter Experience with the Surfacer Inside-Out Access Catheter System in Patients with Thoracic Venous Obstruction: Results from the SAVE Registry.

PURPOSE: To report the device performance and safety for the Surfacer Inside-Out access catheter system in patients with thoracic central venous obstruction (TCVO) requiring central venous access (CVA). MATERIALS AND METHODS: Five sites prospectively enrolled 30 patients requiring a tunneled dialysis catheter between February 2017 and September 2018 in the SAVE (Surfacer System to Facilitate Access in Venous Obstructions) registry. Patient demographics, medical history, and type of TCVO were documented at enrollment. Device performance and adverse events were collected during the procedure and upon hospital discharge. Twenty-nine of the 30 patients enrolled required CVA for hemodialysis. Retrospective classification of TCVOs according to SIR reporting standards showed 9 patients (30%) had Type 4 obstructions, 8 (26.7%) had Type 3, 5 (16.7%) had Type 2, and 8 (26.7%) had Type 1 obstruction. RESULTS: Central venous catheters (CVCs) were successfully placed in 29 of 30 patients (96.7%). The procedure was discontinued in 1 patient due to vascular anatomical tortuosity. All 29 patients with successful CVC placement achieved adequate catheter patency and tip positioning. There were no device-related adverse events, catheter malposition, or intra- or postprocedural complications. Mean time from device insertion to removal for the 29 patients who successfully completed the procedure was 24 ± 14.9 (range, 6-70) minutes. Mean fluoroscopy time was 6.8 ± 4.5 (range, 2.2-25.5) minutes. CONCLUSIONS: The Surfacer Inside-Out procedure provided an alternative option to restore right-sided CVA in patients with TCVO.