AI-SCoRE (artificial intelligence-SARS CoV2 risk evaluation): a fast, objective and fully automated platform to predict the outcome in COVID-19 patients.

PURPOSE: To develop and validate an effective and user-friendly AI platform based on a few unbiased clinical variables integrated with advanced CT automatic analysis for COVID-19 patients' risk stratification. MATERIAL AND METHODS: In total, 1575 consecutive COVID-19 adults admitted to 16 hospitals during wave 1 (February 16-April 29, 2020), submitted to chest CT within 72 h from admission, were retrospectively enrolled. In total, 107 variables were initially collected; 64 extracted from CT. The outcome was survival. A rigorous AI model selection framework was adopted for models selection and automatic CT data extraction. Model performances were compared in terms of AUC. A web-mobile interface was developed using Microsoft PowerApps environment. The platform was externally validated on 213 COVID-19 adults prospectively enrolled during wave 2 (October 14-December 31, 2020). RESULTS: The final cohort included 1125 patients (292 non-survivors, 26%) and 24 variables. Logistic showed the best performance on the complete set of variables (AUC = 0.839 ± 0.009) as in models including a limited set of 13 and 5 variables (AUC = 0.840 ± 0.0093 and AUC = 0.834 ± 0.007). For non-inferior performance, the 5 variables model (age, sex, saturation, well-aerated lung parenchyma and cardiothoracic vascular calcium) was selected as the final model and the extraction of CT-derived parameters was fully automatized. The fully automatic model showed AUC = 0.842 (95% CI: 0.816-0.867) on wave 1 and was used to build a 0-100 scale risk score (AI-SCoRE). The predictive performance was confirmed on wave 2 (AUC 0.808; 95% CI: 0.7402-0.8766). CONCLUSIONS: AI-SCoRE is an effective and reliable platform for automatic risk stratification of COVID-19 patients based on a few unbiased clinical data and CT automatic analysis.

Hospitals with and without neurosurgery: a comparative study evaluating the outcome of patients with traumatic brain injury.

BACKGROUND: We leveraged the data of the international CREACTIVE consortium to investigate whether the outcome of traumatic brain injury (TBI) patients admitted to intensive care units (ICU) in hospitals without on-site neurosurgical capabilities (no-NSH) would differ had the same patients been admitted to ICUs in hospitals with neurosurgical capabilities (NSH). METHODS: The CREACTIVE observational study enrolled more than 8000 patients from 83 ICUs. Adult TBI patients admitted to no-NSH ICUs within 48 h of trauma were propensity-score matched 1:3 with patients admitted to NSH ICUs. The primary outcome was the 6-month extended Glasgow Outcome Scale (GOS-E), while secondary outcomes were ICU and hospital mortality. RESULTS: A total of 232 patients, less than 5% of the eligible cohort, were admitted to no-NSH ICUs. Each of them was matched to 3 NSH patients, leading to a study sample of 928 TBI patients where the no-NSH and NSH groups were well-balanced with respect to all of the variables included into the propensity score. Patients admitted to no-NSH ICUs experienced significantly higher ICU and in-hospital mortality. Compared to the matched NSH ICU admissions, their 6-month GOS-E scores showed a significantly higher prevalence of upper good recovery for cases with mild TBI and low expected mortality risk at admission, along with a progressively higher incidence of poor outcomes with increased TBI severity and mortality risk. CONCLUSIONS: In our study, centralization of TBI patients significantly impacted short- and long-term outcomes. For TBI patients admitted to no-NSH centers, our results suggest that the least critically ill can effectively be managed in centers without neurosurgical capabilities. Conversely, the most complex patients would benefit from being treated in high-volume, neuro-oriented ICUs.

Prognostic Value of a Combination of Circulating Biomarkers in Critically Ill Patients with Traumatic Brain Injury: Results from the European CREACTIVE Study.

Individualized patient care is essential to reduce the global burden of traumatic brain injury (TBI). This pilot study focused on TBI patients admitted to intensive care units (ICUs) and aimed at identifying patterns of circulating biomarkers associated with the disability level at 6 months from injury, measured by the extended Glasgow Outcome Scale (GOS-E). The concentration of 107 biomarkers, including proteins related to inflammation, innate immunity, TBI, and central nervous system, were quantified in blood samples collected on ICU admission from 80 patients. Patients were randomly selected among those prospectively enrolled in the Collaborative Research on Acute Traumatic Brain Injury in Intensive Care Medicine in Europe (CREACTIVE) observational study. Six biomarkers were selected to be associated with indicators of primary or secondary brain injury: three glial proteins (glial cell-derived neurotrophic factor, glial fibrillary acidic protein, and S100 calcium-binding protein B) and three cytokines (stem cell factor, fibroblast growth factor [FGF] 23 and FGF19). The subjects were grouped into three clusters according to the expression of these proteins. The distribution of the 6-month GOS-E was significantly different across clusters (p < 0.001). In two clusters, the number of 6-month deaths or vegetative states was significantly lower than expected, as calculated according to a customization of the corticosteroid randomization after significant head injury (CRASH) scores (observed/expected [O/E] events = 0.00, 95% confidence interval [CI]: 0.00-0.90 and 0.00, 95% CI: 0.00-0.94). In one cluster, less-than-expected unfavorable outcomes (O/E = 0.50, 95% CI: 0.05-0.95) and more-than-expected good recoveries (O/E = 1.55, 95% CI: 1.05-2.06) were observed. The improved prognostic accuracy of the pattern of these six circulating biomarkers at ICU admission upon established clinical parameters and computed tomography results needs validation in larger, independent cohorts. Nonetheless, the results of this pilot study are promising and will prompt further research in personalized medicine for TBI patients.

Biomarkers for Traumatic Brain Injury: Data Standards and Statistical Considerations.

Recent biomarker innovations hold potential for transforming diagnosis, prognostic modeling, and precision therapeutic targeting of traumatic brain injury (TBI). However, many biomarkers, including brain imaging, genomics, and proteomics, involve vast quantities of high-throughput and high-content data. Management, curation, analysis, and evidence synthesis of these data are not trivial tasks. In this review, we discuss data management concepts and statistical and data sharing strategies when dealing with biomarker data in the context of TBI research. We propose that application of biomarkers involves three distinct steps-discovery, evaluation, and evidence synthesis. First, complex/big data has to be reduced to useful data elements at the stage of biomarker discovery. Second, inferential statistical approaches must be applied to these biomarker data elements for assessment of biomarker clinical utility and validity. Last, synthesis of relevant research is required to support practice guidelines and enable health decisions informed by the highest quality, up-to-date evidence available. We focus our discussion around recent experiences from the International Traumatic Brain Injury Research (InTBIR) initiative, with a specific focus on four major clinical projects (Transforming Research and Clinical Knowledge in TBI, Collaborative European NeuroTrauma Effectiveness Research in TBI, Collaborative Research on Acute Traumatic Brain Injury in Intensive Care Medicine in Europe, and Approaches and Decisions in Acute Pediatric TBI Trial), which are currently enrolling subjects in North America and Europe. We discuss common data elements, data collection efforts, data-sharing opportunities, and challenges, as well as examine the statistical techniques required to realize successful adoption and use of biomarkers in the clinic as a foundation for precision medicine in TBI.

PROSAFE: a European endeavor to improve quality of critical care medicine in seven countries.

BACKGROUND: Long-lasting shared research databases are an important source of epidemiological information and can promote comparison between different healthcare services. Here we present PROSAFE, an advanced international research network in intensive care medicine, with the focus on assessing and improving the quality of care. The project involved 343 ICUs in seven countries. All patients admitted to the ICU were eligible for data collection. METHODS: The PROSAFE network collected data using the same electronic case report form translated into the corresponding languages. A complex, multidimensional validation system was implemented to ensure maximum data quality. Individual and aggregate reports by country, region, and ICU type were prepared annually. A web-based data-sharing system allowed participants to autonomously perform different analyses on both own data and the entire database. RESULTS: The final analysis was restricted to 262 general ICUs and 432,223 adult patients, mostly admitted to Italian units, where a research network had been active since 1991. Organization of critical care medicine in the seven countries was relatively similar, in terms of staffing, case mix and procedures, suggesting a common understanding of the role of critical care medicine. Conversely, ICU equipment differed, and patient outcomes showed wide variations among countries. CONCLUSIONS: PROSAFE is a permanent, stable, open access, multilingual database for clinical benchmarking, ICU self-evaluation and research within and across countries, which offers a unique opportunity to improve the quality of critical care. Its entry into routine clinical practice on a voluntary basis is testimony to the success and viability of the endeavor.

Convolutional Neural Networks Promising in Lung Cancer T-Parameter Assessment on Baseline FDG-PET/CT.

Aim: To develop an algorithm, based on convolutional neural network (CNN), for the classification of lung cancer lesions as T1-T2 or T3-T4 on staging fluorodeoxyglucose positron emission tomography (FDG-PET)/CT images. Methods: We retrospectively selected a cohort of 472 patients (divided in the training, validation, and test sets) submitted to staging FDG-PET/CT within 60 days before biopsy or surgery. TNM system seventh edition was used as reference. Postprocessing was performed to generate an adequate dataset. The input of CNNs was a bounding box on both PET and CT images, cropped around the lesion centre. The results were classified as Correct (concordance between reference and prediction) and Incorrect (discordance between reference and prediction). Accuracy (Correct/[Correct + Incorrect]), recall (Correctly predicted T3-T4/[all T3-T4]), and specificity (Correctly predicted T1-T2/[all T1-T2]), as commonly defined in deep learning models, were used to evaluate CNN performance. The area under the curve (AUC) was calculated for the final model. Results: The algorithm, composed of two networks (a "feature extractor" and a "classifier"), developed and tested achieved an accuracy, recall, specificity, and AUC of 87%, 69%, 69%, and 0.83; 86%, 77%, 70%, and 0.73; and 90%, 47%, 67%, and 0.68 in the training, validation, and test sets, respectively. Conclusion: We obtained proof of concept that CNNs can be used as a tool to assist in the staging of patients affected by lung cancer.

Modeling hemodynamics in intracranial aneurysms: Comparing accuracy of CFD solvers based on finite element and finite volume schemes.

Image-based computational fluid dynamics (CFD) has shown potential to aid in the clinical management of intracranial aneurysms, but its adoption in the clinical practice has been missing, partially because of lack of accuracy assessment and sensitivity analysis. To numerically solve the flow-governing equations, CFD solvers generally rely on 2 spatial discretization schemes: finite volume (FV) and finite element (FE). Since increasingly accurate numerical solutions are obtained by different means, accuracies and computational costs of FV and FE formulations cannot be compared directly. To this end, in this study, we benchmark 2 representative CFD solvers in simulating flow in a patient-specific intracranial aneurysm model: (1) ANSYS Fluent, a commercial FV-based solver, and (2) VMTKLab multidGetto, a discontinuous Galerkin (dG) FE-based solver. The FV solver's accuracy is improved by increasing the spatial mesh resolution (134k, 1.1m, 8.6m, and 68.5m tetrahedral element meshes). The dGFE solver accuracy is increased by increasing the degree of polynomials (first, second, third, and fourth degree) on the base 134k tetrahedral element mesh. Solutions from best FV and dGFE approximations are used as baseline for error quantification. On average, velocity errors for second-best approximations are approximately 1 cm/s for a [0,125] cm/s velocity magnitude field. Results show that high-order dGFE provides better accuracy per degree of freedom but worse accuracy per Jacobian nonzero entry as compared with FV. Cross-comparison of velocity errors demonstrates asymptotic convergence of both solvers to the same numerical solution. Nevertheless, the discrepancy between underresolved velocity fields suggests that mesh independence is reached following different paths.

A fluid-dynamic based approach to reconnect the retinal vessels in fundus photography.

This paper introduces the use of fluid-dynamic modeling to determine the connectivity of overlapping venous and arterial vessels in fundus images. Analysis of the retinal vascular network may provide information related to systemic and local disorders. However, the automated identification of the vascular trees in retinal images is a challenging task due to the low signal-to-noise ratio, nonuniform illumination and the fact that fundus photography is a projection on to the imaging plane of three-dimensional retinal tissue. A zero-dimensional model was created to estimate the hemodynamic status of candidate tree configurations. Simulated annealing was used to search for an optimal configuration. Experimental results indicate that simulated annealing was very efficient on test cases that range from small to medium size networks, while ineffective on large networks. Although for large networks the nonconvexity of the cost function and the large solution space made searching for the optimal solution difficult, the accuracy (average success rate = 98.35%), and simplicity of our novel approach demonstrate its potential effectiveness in segmenting retinal vascular trees.

Effect of Sirolimus on Disease Progression in Patients with Autosomal Dominant Polycystic Kidney Disease and CKD Stages 3b-4.

BACKGROUND AND OBJECTIVES: The effect of mammalian target of rapamycin (mTOR) inhibitors has never been tested in patients with autosomal dominant polycystic kidney disease (ADPKD) and severe renal insufficiency. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: In this academic, prospective, randomized, open label, blinded end point, parallel group trial (ClinicalTrials.gov no. NCT01223755), 41 adults with ADPKD, CKD stage 3b or 4, and proteinuria ≤0.5 g/24 h were randomized between September of 2010 and March of 2012 to sirolimus (3 mg/d; serum target levels of 5-10 ng/ml) added on to conventional therapy (n=21) or conventional treatment alone (n=20). Primary outcome was GFR (iohexol plasma clearance) change at 1 and 3 years versus baseline. RESULTS: At the 1-year preplanned interim analysis, GFR fell from 26.7±5.8 to 21.3±6.3 ml/min per 1.73 m(2) (P<0.001) and from 29.6±5.6 to 24.9±6.2 ml/min per 1.73 m(2) (P<0.001) in the sirolimus and conventional treatment groups, respectively. Albuminuria (73.8±81.8 versus 154.9±152.9 µg/min; P=0.02) and proteinuria (0.3±0.2 versus 06±0.4 g/24 h; P<0.01) increased with sirolimus. Seven patients on sirolimus versus one control had de novo proteinuria (P=0.04), ten versus three patients doubled proteinuria (P=0.02), 18 versus 11 patients had peripheral edema (P=0.04), and 14 versus six patients had upper respiratory tract infections (P=0.03). Three patients on sirolimus had angioedema, 14 patients had aphthous stomatitis, and seven patients had acne (P<0.01 for both versus controls). Two patients progressed to ESRD, and two patients withdrew because of worsening of proteinuria. These events were not observed in controls. Thus, the independent data and safety monitoring board recommend early trial termination for safety reasons. At 1 year, total kidney volume (assessed by contrast-enhanced computed tomography imaging) increased by 9.0% from 2857.7±1447.3 to 3094.6±1519.5 ml on sirolimus and 4.3% from 3123.4±1695.3 to 3222.6±1651.4 ml on conventional therapy (P=0.12). On follow-up, 37% and 7% of serum sirolimus levels fell below or exceeded the therapeutic range, respectively. CONCLUSIONS: Finding that sirolimus was unsafe and ineffective in patients with ADPKD and renal insufficiency suggests that mTOR inhibitor therapy may be contraindicated in this context.

AView: An Image-based Clinical Computational Tool for Intracranial Aneurysm Flow Visualization and Clinical Management.

Intracranial aneurysms (IAs) occur in around 3% of the entire population. IA rupture is responsible for the most devastating type of hemorrhagic strokes, with high fatality and disability rates as well as healthcare costs. With increasing detection of unruptured aneurysms, clinicians are routinely faced with the dilemma whether to treat IA patients and how to best treat them. Hemodynamic and morphological characteristics are increasingly considered in aneurysm rupture risk assessment and treatment planning, but currently no computational tools allow routine integration of flow visualization and quantitation of these parameters in clinical workflow. In this paper, we introduce AView, a prototype of a clinician-oriented, integrated computation tool for aneurysm hemodynamics, morphology, and risk and data management to aid in treatment decisions and treatment planning in or near the procedure room. Specifically, we describe how we have designed the AView structure from the end-user's point of view, performed a pilot study and gathered clinical feedback. The positive results demonstrate AView's potential clinical value on enhancing aneurysm treatment decision and treatment planning.

pyNS: an open-source framework for 0D haemodynamic modelling.

A number of computational approaches have been proposed for the simulation of haemodynamics and vascular wall dynamics in complex vascular networks. Among them, 0D pulse wave propagation methods allow to efficiently model flow and pressure distributions and wall displacements throughout vascular networks at low computational costs. Although several techniques are documented in literature, the availability of open-source computational tools is still limited. We here present python Network Solver, a modular solver framework for 0D problems released under a BSD license as part of the archToolkit ( http://archtk.github.com ). As an application, we describe patient-specific models of the systemic circulation and detailed upper extremity for use in the prediction of maturation after surgical creation of vascular access for haemodialysis.

Computational model for simulation of vascular adaptation following vascular access surgery in haemodialysis patients.

An important number of surgical procedures for creation of vascular access (VA) in haemodialysis patients still results in non-adequate increase in blood flow (non-maturation). The rise in blood flow in arteriovenous shunts depends on vascular remodelling. Computational tools to predict the outcome of VA surgery would be important in this clinical context. The aim of our investigation was then to develop a 0D/1D computational model of arm vasculature able to simulate vessel wall remodelling and related changes in blood flow. We assumed that blood vessel remodelling is driven by peak wall shear stress. The model was calibrated with previously reported values of radial artery diameter and blood flow after end-to-end distal fistula creation. Good agreement was obtained between predicted changes in VA flow and in arterial diameter after surgery and corresponding measured values. The use of this computational model may allow accurate vascular surgery planning and ameliorate VA surgery outcomes.

Effect of longacting somatostatin analogue on kidney and cyst growth in autosomal dominant polycystic kidney disease (ALADIN): a randomised, placebo-controlled, multicentre trial.

BACKGROUND: Autosomal dominant polycystic kidney disease slowly progresses to end-stage renal disease and has no effective therapy. A pilot study suggested that the somatostatin analogue octreotide longacting release (LAR) could be nephroprotective in this context. We aimed to assess the effect of 3 years of octreotide-LAR treatment on kidney and cyst growth and renal function decline in participants with this disorder. METHODS: We did an academic, multicentre, randomised, single-blind, placebo-controlled, parallel-group trial in five hospitals in Italy. Adult (>18 years) patients with estimated glomerular filtration rate (GFR) of 40 mL/min per 1·73 m(2) or higher were randomly assigned (central allocation by phone with a computerised list, 1:1 ratio, stratified by centre, block size four and eight) to 3 year treatment with two 20 mg intramuscular injections of octreotide-LAR (n=40) or 0·9% sodium chloride solution (n=39) every 28 days. Study physicians and nurses were aware of the allocated group; participants and outcome assessors were masked to allocation. The primary endpoint was change in total kidney volume (TKV), measured by MRI, at 1 year and 3 year follow-up. Analyses were by modified intention to treat. This study is registered with ClinicalTrials.gov, NCT00309283. FINDINGS: Recruitment was between April 27, 2006, and May 12, 2008. 38 patients in the octreotide-LAR group and 37 patients in the placebo group had evaluable MRI scans at 1 year follow-up, at this timepoint, mean TKV increased significantly less in the octreotide-LAR group (46·2 mL, SE 18·2) compared with the placebo group (143·7 mL, 26·0; p=0·032). 35 patients in each group had evaluable MRI scans at 3 year follow-up, at this timepoint, mean TKV increase in the octreotide-LAR group (220·1 mL, 49·1) was numerically smaller than in the placebo group (454·3 mL, 80·8), but the difference was not significant (p=0·25). 37 (92·5%) participants in the octreotide-LAR group and 32 (82·1%) in the placebo group had at least one adverse event (p=0·16). Participants with serious adverse events were similarly distributed in the two treatment groups. However, four cases of cholelithiasis or acute cholecystitis occurred in the octreotide-LAR group and were probably treatment-related. INTERPRETATION: These findings provide the background for large randomised controlled trials to test the protective effect of somatostatin analogues against renal function loss and progression to end-stage kidney disease. FUNDING: Polycystic Kidney Disease Foundation.

Kidney failure: aims for the next 10 years and barriers to success.

Although in some parts of the world acute and chronic kidney diseases are preventable or treatable disorders, in many other regions these diseases are left without any care. The nephrology community needs to commit itself to reduction of this divide between high-income and low-income regions. Moreover, new and exciting developments in fields such as pharmacology, genetic, or bioengineering, can give a boost, in the next decade, to a new era of diagnosis and treatment of kidney diseases, which should be made available to more patients.

Validation of a patient-specific hemodynamic computational model for surgical planning of vascular access in hemodialysis patients.

Vascular access dysfunction is one of the main causes of morbidity and hospitalization in hemodialysis patients. This major clinical problem points out the need for prediction of hemodynamic changes induced by vascular access surgery. Here we reviewed the potential of a patient-specific computational vascular network model that includes vessel wall remodeling to predict blood flow change within 6 weeks after surgery for different arteriovenous fistula configurations. For model validation, we performed a multicenter, prospective clinical study to collect longitudinal data on arm vasculature before and after surgery. Sixty-three patients with newly created arteriovenous fistula were included in the validation data set and divided into four groups based on fistula configuration. Predicted brachial artery blood flow volumes 40 days after surgery had a significantly high correlation with measured values. Deviation of predicted from measured brachial artery blood flow averaged 3% with a root mean squared error of 19.5%, showing that the computational tool reliably predicted patient-specific blood flow increase resulting from vascular access surgery and subsequent vascular adaptation. This innovative approach may help the surgeon to plan the most appropriate fistula configuration to optimize access blood flow for hemodialysis, potentially reducing the incidence of vascular access dysfunctions and the need of patient hospitalization.

Impact of hemodynamics on lumen boundary displacements in abdominal aortic aneurysms by means of dynamic computed tomography and computational fluid dynamics.

The aim of the present work is to quantitatively assess the three-dimensional distributions of the displacements experienced during the cardiac cycle by the luminal boundary of abdominal aortic aneurysm (AAA) and to correlate them with the local bulk hemodynamics. Ten patients were acquired by means of time resolved computed tomography, and each patient-specific vascular morphology was reconstructed for all available time frames. The AAA lumen boundary motion was tracked, and the lumen boundary displacements (LBD) computed for each time frame. The intra-aneurysm hemodynamic quantities, specifically wall shear stress (WSS), were evaluated with computational fluid dynamics simulations. Co-localization of LBD and WSS distributions was evaluated by means of Pearson correlation coefficient. A clear anisotropic distribution of LBD was evidenced in both space and time; a combination of AAA lumen boundary inward- and outward-directed motions was assessed. A co-localization between largest outward LBD and high WSS was demonstrated supporting the hypothesis of a mechanistic relationship between anisotropic displacement and hemodynamic forces related to the impingement of the blood on the lumen boundary. The presence of anisotropic displacement of the AAA lumen boundary and their link to hemodynamic forces have been assessed, highlighting a new possible role for hemodynamics in the study of AAA progression.

Patient-specific model of arterial circulation for surgical planning of vascular access.

PURPOSE: To report the technical aspects of a novel method to generate patient-specific vascular network models of arterial vasculature for the surgical planning of vascular access (VA) for hemodialysis. METHODS: On the basis of literature data, we defined a set of rules for estimation of diameter, length and compliance of arterial network segments, at patient-specific level, as a function of general descriptors (i.e. sex, age, body size and pathology). Using this method we generated vascular network models of height hypothetical patients with different age, sex and body surface area and we computed pressures and blood flows along the arterial arm vasculature using a wave propagation model. RESULTS: Simulation results show that vascular geometry is influenced by sex, age and body size leading to important differences in hemodynamic function. Calculated wall shear stress is higher in women females as compared to men, regardless of body size and age. CONCLUSIONS: Our method facilitates estimating vascular network model parameters useful for patient-specific pre-operative assessment of blood flow distribution in the arterial arm circulation.

Helical flows and asymmetry of blood jet in dilated ascending aorta with normally functioning bicuspid valve.

Bicuspid aortic valve (BAV) is associated with aortic dilatation and aneurysm. Several studies evidenced an eccentric systolic flow in ascending aorta associated with increased wall shear stresses (WSS) and the occurrence of an helical systolic flow. This study seeks to elucidate the connections between jet asymmetry and helical flow in patients with normally functioning BAV and dilated ascending aorta. We performed a computational parametric study by varying, for a patient-specific geometry, the valve area and the flow rate entering the aorta and drawing also a tricuspid valve (TAV). We considered also phase-contrast magnetic resonance imaging of four BAV and TAV patients. Measurement of normalized flow asymmetry index, systolic WSS and of a new index (positive helix fraction, PHF) quantifying the presence of a single a single helical flow were performed. In our computation, BAV cases featured higher values of all indices with respect to TAV in both numerical and imaged-based results. Moreover, all indices increased with decreasing valve area and/or with increasing flow rate. This allowed to separate the BAV and TAV cases with respect to the jet asymmetry, WSS localization and helical flow. Interestingly, these results were obtained without modeling the leaflets.

The accuracy of ultrasound volume flow measurements in the complex flow setting of a forearm vascular access.

PURPOSE: Maturation of an arterio-venous fistula (AVF) frequently fails, with low post-operative fistula flow as a prognostic marker for this event. As pulsed wave Doppler (PWD) is commonly used to assess volume flow, we studied the accuracy of this measurement in the setting of a radio-cephalic AVF. METHODS: As in-vivo validation of fistula flow measurements is cumbersome, we performed simulations, integrating computational fluid dynamics with an ultrasound (US) simulator. Flow in the arm was calculated, based on a patient-specific model of the arm vasculature pre and post AVF creation. Raw ultrasound signals were subsequently simulated, from which Doppler spectra were calculated in both a proximal and a distal location. RESULTS: The velocity component in the direction of the PWD-US beam (vPWD), in a centered, small, sample volume, can be captured accurately using PWD spectrum mean-tracking (maximum bias [mB] 8.1%). However, when deriving flow rate from these measurements, a high degree of inaccuracy occurs. First, the angle-correction of vPWD towards the velocity along the axis of the vessel is largely influenced by the radial velocity components in the complex flow field (mB=16.3%). Second, the largest error is introduced when transferring the centerline velocity to the cross-sectional mean velocity without any knowledge of the flow profile (mB=97.7%). CONCLUSIONS: In the setting of a forearm AVF, flow estimates based on PWD are hampered by the complex flow patterns. Overall, flow estimation based on centerline measurement, analyzed by mean-tracking of the RF-spectral estimates, under the assumption of a parabolic flow profile, appeared to provide the most reasonable values.

Automatic trajectory planner for StereoElectroEncephaloGraphy procedures: a retrospective study.

In StereoElectroEncephaloGraphy (SEEG) procedures, intracerebral electrodes are implanted in order to identify the epileptogenic zone in drug-resistant epileptic patients. This paper presents an automatic multitrajectory planner that computes the best trajectory in terms of distance from vessels and guiding screws angle, once the candidate entry and target regions are quickly and roughly defined. The planning process is designed also to spare some brain structures, such as cella media and trigone of the lateral ventricles and brain stem. The planner was retrospectively evaluated on 15 patients who had previously undergone SEEG investigation. Quantitative comparison was performed computing for each patient and for each electrode trajectory 1) the Euclidean distance from the closest vessel; 2) the trajectory incidence angle (guiding screws angle); and 3) the sulcality value. The automatic planner proved to satisfy the clinical requirements, planning safe trajectories in a clinical-compatible timeframe. Qualitative evaluation performed by three neurosurgeons showed that the automatically computed trajectories would have been accepted by them.