Pseudolipoma of the Inferior Vena Cava

Pseudolipoma of inferior vena cava refers to a normal variant of adipose collection that is seen in typical pericaval or juxtacaval location; however, it mimics an intracaval mass lesion, especially fat-containing lesions such as lipoma. Awareness of this entity is very important to avoid misdiagnosis and unnecessary diagnostic procedures.     

A novel way to reduce thrombus build‐up in vena cava filters

Objectives and background : The build‐up of thromboses in vena cava filters after deployment presents serious problem to the patients. We proposed a novel way to overcome this problem in a belief that intentionally induced swirling flow can optimize blood flow patterns in Vena cava filters, enhance the stirring motion of flow, in turn accelerate the dissolution of blood clots captured in the filter and facilitate blood to flow pass through the filters. Methods : In this study, we experimentally compared the work efficiency of a vena cava filter under swirling flow condition with that of the same filter under normal flow condition. Results : The results show that when compared to the normal flow, the swirling flow indeed has a significantly beneficial effect on a VCF which can decrease its flow‐out time nearly 40% and reduce clot build‐up in the filter more than 50%. Conclusions : We therefore believe that the design of an ideal VCF should take how to create swirling flow in the filter into the consideration. © 2011 Wiley Periodicals, Inc.     

Long-Term Outcomes of Endovascular Interventions in More than 500 patients with Budd–Chiari Syndrome

PurposeTo assess and compare the long-term outcomes of various endovascular interventions in patients with Budd-Chiari syndrome (BCS).Materials and MethodsIn this single-center retrospective study, 510 consecutive patients with BCS who had undergone a total of 618 endovascular procedures from January 2001 to December 2019 were included. Details of the type of endovascular intervention, technical success, clinical success, patency rate, complications, and survival outcomes were analyzed.ResultsThe overall technical success rate was 96% (593 of 618 procedures; 500 in treatment-naïve patients and 93 repeat interventions for recurrent disease). Endovascular procedures included recanalization procedures (angioplasty and stent placement) in 355 patients (71%) and transjugular intrahepatic portosystemic shunt (TIPS) creation in 145 (29%). Major postprocedure complications occurred in 14 patients (2.8%). Vascular/stent restenosis occurred in 95 patients (19%), and successful repeat intervention was performed in 82 of those 95 (86.3%). An additional 11 of these 82 (13.4%) underwent a third intervention for restenosis. In the recanalization and TIPS groups, the 1- and 5-y cumulative patency rates were 87% and 74% and 95% and 68%, respectively. The 1- and 5-y survival rates were 96% and 89% and 90% and 76%, respectively.ConclusionsEndovascular interventions for BCS are feasible and safe in the majority of patients, with excellent short- and long-term patency and survival rates.     

Sleep spindle detection using multivariate Gaussian mixture models

In this research study we have developed a clustering‐based automatic sleep spindle detection method that was evaluated on two different databases. The databases consisted of 20 all‐night polysomnograph recordings. Past detection methods have been based on subject‐independent and some subject‐dependent parameters, such as fixed or variable thresholds to identify spindles. Using a multivariate Gaussian mixture model clustering technique, our algorithm was developed to use only subject‐specific parameters to detect spindles. We have obtained an overall sensitivity range (65.1–74.1%) at a (59.55–119.7%) false positive proportion.     

Privacy-preserving matching of similar patients

The identification of similar entities represented by records in different databases has drawn considerable attention in many application areas, including in the health domain. One important type of entity matching application that is vital for quality healthcare analytics is the identification of similar patients, known as similar patient matching. A key component of identifying similar records is the calculation of similarity of the values in attributes (fields) between these records. Due to increasing privacy and confidentiality concerns, using the actual attribute values of patient records to identify similar records across different organizations is becoming non-trivial because the attributes in such records often contain highly sensitive information such as personal and medical details of patients. Therefore, the matching needs to be based on masked (encoded) values while being effective and efficient to allow matching of large databases.Bloom filter encoding has widely been used as an efficient masking technique for privacy-preserving matching of string and categorical values. However, no work on Bloom filter-based masking of numerical data, such as integer (e.g. age), floating point (e.g. body mass index), and modulus (numbers wrap around upon reaching a certain value, e.g. date and time), which are commonly required in the health domain, has been presented in the literature. We propose a framework with novel methods for masking numerical data using Bloom filters, thereby facilitating the calculation of similarities between records. We conduct an empirical study on publicly available real-world datasets which shows that our framework provides efficient masking and achieves similar matching accuracy compared to the matching of actual unencoded patient records.