Immersed boundary-finite element model of fluid-structure interaction in the aortic root

It has long been recognized that aortic root elasticity helps to ensure efficient aortic valve closure, but our understanding of the functional importance of the elasticity and geometry of the aortic root continues to evolve as increasingly detailed in vivo imaging data become available. Herein, we describe fluid-structure interaction models of the aortic root, including the aortic valve leaflets, the sinuses of Valsalva, the aortic annulus, and the sinotubular junction, that employ a version of Peskin's immersed boundary (IB) method with a finite element (FE) description of the structural elasticity. We develop both an idealized model of the root with three-fold symmetry of the aortic sinuses and valve leaflets, and a more realistic model that accounts for the differences in the sizes of the left, right, and noncoronary sinuses and corresponding valve cusps. As in earlier work, we use fiber-based models of the valve leaflets, but this study extends earlier IB models of the aortic root by employing incompressible hyperelastic models of the mechanics of the sinuses and ascending aorta using a constitutive law fit to experimental data from human aortic root tissue. In vivo pressure loading is accounted for by a backwards displacement method that determines the unloaded configurations of the root models. Our models yield realistic cardiac output at physiological pressures, with low transvalvular pressure differences during forward flow, minimal regurgitation during valve closure, and realistic pressure loads when the valve is closed during diastole. Further, results from high-resolution computations demonstrate that IB models of the aortic valve are able to produce essentially grid-converged dynamics at practical grid spacings for the high-Reynolds number flows of the aortic root

A multi-center study of neurofilament assay reliability and inter-laboratory variability

Objectives: Significantly elevated levels of neurofilament light chain (NfL) and phosphorylated neurofilament heavy chain (pNfH) have been described in the blood and cerebrospinal fluid (CSF) of amyotrophic lateral sclerosis (ALS) patients. The aim of this study was to evaluate the analytical performance of different neurofilament assays in a round robin with 10 centers across Europe/U.S. Methods: Serum, plasma and CSF samples from a group of five ALS and five neurological control patients were distributed across 10 international specialist neurochemical laboratories for analysis by a range of commercial and in-house neurofilament assays. The performance of all assays was evaluated for their ability to differentiate between the groups. The inter-assay coefficient of variation was calculated where appropriate from sample measurements performed across multiple laboratories using the same assay. Results: All assays could differentiate ALS patients from controls in CSF. Inter-assay coefficient of variation of analytical platforms performed across multiple laboratories varied between 6.5% and 41.9%. Conclusions: This study is encouraging for the growing momentum toward integration of neurofilament measurement into the specialized ALS clinic. It demonstrates the importance of ‘round robin’ studies necessary to ensure the analytical quality required for translation to the routine clinical setting. A standardized neurofilament probe is needed which can be used as international benchmark for analytical performance in ALS

A multi-center study of neurofilament assay reliability and inter-laboratory variability

© 2020 World Federation of Neurology on behalf of the Research Group on Motor Neuron Diseases. Objectives: Significantly elevated levels of neurofilament light chain (NfL) and phosphorylated neurofilament heavy chain (pNfH) have been described in the blood and cerebrospinal fluid (CSF) of amyotrophic lateral sclerosis (ALS) patients. The aim of this study was to evaluate the analytical performance of different neurofilament assays in a round robin with 10 centers across Europe/U.S. Methods: Serum, plasma and CSF samples from a group of five ALS and five neurological control patients were distributed across 10 international specialist neurochemical laboratories for analysis by a range of commercial and in-house neurofilament assays. The performance of all assays was evaluated for their ability to differentiate between the groups. The inter-assay coefficient of variation was calculated where appropriate from sample measurements performed across multiple laboratories using the same assay. Results: All assays could differentiate ALS patients from controls in CSF. Inter-assay coefficient of variation of analytical platforms performed across multiple laboratories varied between 6.5% and 41.9%. Conclusions: This study is encouraging for the growing momentum toward integration of neurofilament measurement into the specialized ALS clinic. It demonstrates the importance of ‘round robin’ studies necessary to ensure the analytical quality required for translation to the routine clinical setting. A standardized neurofilament probe is needed which can be used as international benchmark for analytical performance in ALS

A classification prognostic score to predict OS in stage IV well-differentiated neuroendocrine tumors

No validated prognostic tool is available for predicting overall survival (OS) of patients with well-differentiated neuroendocrine tumors (WDNETs). This study, conducted in three independent cohorts of patients from five different European countries, aimed to develop and validate a classification prognostic score for OS in patients with stage IV WDNETs. We retrospectively collected data on 1387 patients: (i) patients treated at the Istituto Nazionale Tumori (Milan, Italy; n = 515); (ii) European cohort of rare NET patients included in the European RARECAREnet database (n = 457); (iii) Italian multicentric cohort of pancreatic NET (pNETs) patients treated at 24 Italian institutions (n = 415). The score was developed using data from patients included in cohort (i) (training set); external validation was performed by applying the score to the data of the two independent cohorts (ii) and (iii) evaluating both calibration and discriminative ability (Harrell C statistic). We used data on age, primary tumor site, metastasis (synchronous vs metachronous), Ki-67, functional status and primary surgery to build the score, which was developed for classifying patients into three groups with differential 10-year OS: (I) favorable risk group: 10-year OS 6570%; (II) intermediate risk group: 30% 64 10-year OS < 70%; (III) poor risk group: 10-year OS <30%. The Harrell C statistic was 0.661 in the training set, and 0.626 and 0.601 in the RARECAREnet and Italian multicentric validation sets, respectively. In conclusion, based on the analysis of three 'field-practice' cohorts collected in different settings, we defined and validated a prognostic score to classify patients into three groups with different long-term prognoses