Patient-specific Setting Research Articles

Structure Preserving Polytopal Discontinuous Galerkin Methods for the Numerical Modeling of Neurodegenerative Diseases

Many neurodegenerative diseases are connected to the spreading of misfolded prionic proteins. In this paper, we analyse the process of misfolding and spreading of both α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document}-synuclein and Amyloid-β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta $$\\end{document}, related to Parkinson’s and Alzheimer’s diseases, respectively. We introduce and analyze a positivity-preserving numerical method for the discretization of the Fisher-Kolmogorov equation, modelling accumulation and spreading of prionic proteins. The proposed approximation method is based on the discontinuous Galerkin method on polygonal and polyhedral grids for space discretization and on ϑ-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\vartheta -$$\\end{document}method time integration scheme. We prove the existence of the discrete solution and a convergence result where the Implicit Euler scheme is employed for time integration. We show that the proposed approach is structure-preserving, in the sense that it guarantees that the discrete solution is non-negative, a feature that is of paramount importance in practical application. The numerical verification of our numerical model is performed both using a manufactured solution and considering wavefront propagation in two-dimensional polygonal grids. Next, we present a simulation of α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document}-synuclein spreading in a two-dimensional brain slice in the sagittal plane. The polygonal mesh for this simulation is agglomerated maintaining the distinction of white and grey matter, taking advantage of the flexibility of PolyDG methods in the mesh construction. Finally, we simulate the spreading of Amyloid-β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta $$\\end{document} in a patient-specific setting by using a three-dimensional geometry reconstructed from magnetic resonance images and an initial condition reconstructed from positron emission tomography. Our numerical simulations confirm that the proposed method is able to capture the evolution of Parkinson’s and Alzheimer’s diseases.

Generation, validation, and benchmarking of a commercial independent Monte Carlo calculation beam model for multi-target SRS

BackgroundDosimetric validation of single isocenter multi-target radiosurgery plans is difficult due to conditions of electronic disequilibrium and the simultaneous irradiation of multiple off-axis lesions dispersed throughout the volume. Here we report the benchmarking of a customizable Monte Carlo secondary dose calculation algorithm specific for multi-target radiosurgery which future users may use to guide their commissioning and clinical implementation. PurposeTo report the generation, validation, and clinical benchmarking of a volumetric Monte Carlo (MC) dose calculation beam model for single isocenter radiosurgery of intracranial multi-focal disease. MethodsThe beam model was prepared within SciMoCa (ScientificRT, Munich Germany), a commercial independent dose calculation software, with the aim of broad availability via the commercial software for use with single isocenter radiosurgery. The process included (1) definition & acquisition of measurement data required for beam modeling, (2) tuning model parameters to match measurements, (3) validation of the beam model via independent measurements and end-to-end testing, and finally, (4) clinical benchmarking and validation of beam model utility in a patient specific QA setting. We utilized a 6X Flattening-Filter-Free photon beam from a TrueBeam STX linear accelerator (Siemens Healthineers, Munich Germany). ResultsIn addition to the measured data required for standard IMRT/VMAT (depth dose, central axis profiles & output factors, leaf gap), beam modeling and validation for single-isocenter SRS required central axis and off axis (5 cm & 9 cm) small field output factors and comparison between measurement and simulation of backscatter with aperture for jaw much greater than MLCs. Validation end-to-end measurements included SRS MapCHECK in StereoPHAN geometry (2%/1 mm Gamma = 99.2% ± 2.2%), and OSL & scintillator measurements in anthropomorphic STEEV phantom (6 targets, volume = 0.1–4.1cc, distance from isocenter = 1.2–7.9 cm) for which mean difference was −1.9% ± 2.2%. For 10 patient cases, MC for individual PTVs was −0.8% ± 1.5%, −1.3% ± 1.7%, and −0.5% ± 1.8% for mean dose, D95%, and D1%, respectively. This corresponded to custom passing rates action limits per AAPM TG-218 guidelines of ±5.2%, ±6.4%, and ±6.3%, respectively. ConclusionsThe beam modeling, validation, and clinical action criteria outlined here serves as a benchmark for future users of the customized beam model within SciMoCa for single isocenter radiosurgery of multi-focal disease.

Electric Bioimpedance Sensing for the Detection of Head and Neck Squamous Cell Carcinoma.

The early detection of head and neck squamous cell carcinoma (HNSCC) is essential to improve patient prognosis and enable organ and function preservation treatments. The objective of this study is to assess the feasibility of using electrical bioimpedance (EBI) sensing technology to detect HNSCC tissue. A prospective study was carried out analyzing tissue from 46 patients undergoing surgery for HNSCC. The goal was the correct identification of pathologic tissue using a novel needle-based EBI sensing device and AI-based classifiers. Considering the data from the overall patient cohort, the system achieved accuracies between 0.67 and 0.93 when tested on tissues from the mucosa, skin, muscle, lymph node, and cartilage. Furthermore, when considering a patient-specific setting, the accuracy range increased to values between 0.82 and 0.95. This indicates that more reliable results may be achieved when considering a tissue-specific and patient-specific tissue assessment approach. Overall, this study shows that EBI sensing may be a reliable technology to distinguish pathologic from healthy tissue in the head and neck region. This observation supports the continuation of this research on the clinical use of EBI-based devices for early detection and margin assessment of HNSCC.

Aortic haemodynamics and wall stress analysis following arch aneurysm repair using a single-branched endograft.

Thoracic endovascular aortic repair (TEVAR) of the arch is challenging given its complex geometry and the involvement of supra-aortic arteries. Different branched endografts have been designed for use in this region, but their haemodynamic performance and the risk for post-intervention complications are not yet clear. This study aims to examine aortic haemodynamics and biomechanical conditions following TVAR treatment of an aortic arch aneurysm with a two-component single-branched endograft. Computational fluid dynamics and finite element analysis were applied to a patient-specific case at different stages: pre-intervention, post-intervention and follow-up. Physiologically accurate boundary conditions were used based on available clinical information. Computational results obtained from the post-intervention model confirmed technical success of the procedure in restoring normal flow to the arch. Simulations of the follow-up model, where boundary conditions were modified to reflect change in supra-aortic vessel perfusion observed on the follow-up scan, predicted normal flow patterns but high levels of wall stress (up to 1.3M MPa) and increased displacement forces in regions at risk of compromising device stability. This might have contributed to the suspected endoleaks or device migration identified at the final follow up. Our study demonstrated that detailed haemodynamic and biomechanical analysis can help identify possible causes for post-TEVAR complications in a patient-specific setting. Further refinement and validation of the computational workflow will allow personalised assessment to aid in surgical planning and clinical decision making.

Delivery of a quality improvement program in team-based rehabilitation for patients with rheumatic and musculoskeletal diseases: a mixed methods study

Purpose To investigate how a quality improvement program (BRIDGE), designed to promote coordination and continuity in rehabilitation services, was delivered and perceived by providers in routine practice for patients with rheumatic and musculoskeletal diseases. Methods A convergent mixed methods approach was nested within a stepped-wedge, randomized controlled trial. The intervention program was developed to bridge gaps between secondary and primary healthcare, comprising the following elements: motivational interviewing; patient-specific goal setting; written rehabilitation-plans; personalized feedback on progress; and tailored follow-up. Data from health professionals who delivered the program were collected and analyzed separately, using two questionnaires and three focus groups. Results were integrated during the overall interpretation and discussion. Results The program delivery depended on the providers’ skills and competence, as well as on contextual factors in their teams and institutions. Suggested possibilities for improvements included follow-up with sufficient support from next of kin and external services, and the practicing of action and coping plans, standardized outcome measures, and feedback on progress. Conclusions Leaders and clinicians should discuss efforts to ensure confident and qualified rehabilitation delivery at the levels of individual providers, teams, and institutions, and pay equal attention to each component in the process from admission to follow-up.

Deep Learning for Cross-Diagnostic Prediction of Mental Disorder Diagnosis and Prognosis Using Danish Nationwide Register and Genetic Data

Diagnoses and treatment of mental disorders are hampered by the current lack of objective markers needed to provide a more precise diagnosis and treatment strategy. To develop deep learning models to predict mental disorder diagnosis and severity spanning multiple diagnoses using nationwide register data, family and patient-specific diagnostic history, birth-related measurement, and genetics. This study was conducted from May 1, 1981, to December 31, 2016. For the analysis, which used a Danish population-based case-cohort sample of individuals born between 1981 and 2005, genotype data and matched longitudinal health register data were taken from the longitudinal Danish population-based Integrative Psychiatric Research Consortium 2012 case-cohort study. Included were individuals with mental disorders (attention-deficit/hyperactivity disorder [ADHD]), autism spectrum disorder (ASD), major depressive disorder (MDD), bipolar disorder (BD), schizophrenia spectrum disorders (SCZ), and population controls. Data were analyzed from February 1, 2021, to January 24, 2022. At least 1 hospital contact with diagnosis of ADHD, ASD, MDD, BD, or SCZ. The predictability of (1) mental disorder diagnosis and (2) severity trajectories (measured by future outpatient hospital contacts, admissions, and suicide attempts) were investigated using both a cross-diagnostic and single-disorder setup. Predictive power was measured by AUC, accuracy, and Matthews correlation coefficient (MCC), including an estimate of feature importance. A total of 63 535 individuals (mean [SD] age, 23 [7] years; 34 944 male [55%]; 28 591 female [45%]) were included in the model. Based on data prior to diagnosis, the specific diagnosis was predicted in a multidiagnostic prediction model including the background population with an overall area under the curve (AUC) of 0.81 and MCC of 0.28, whereas the single-disorder models gave AUCs/MCCs of 0.84/0.54 for SCZ, 0.79/0.41 for BD, 0.77/0.39 for ASD, 0.74/0.38, for ADHD, and 0.74/0.38 for MDD. The most important data sets for multidiagnostic prediction were previous mental disorders and age (11%-23% reduction in prediction accuracy when removed) followed by family diagnoses, birth-related measurements, and genetic data (3%-5% reduction in prediction accuracy when removed). Furthermore, when predicting subsequent disease trajectories of the disorder, the most severe cases were the most easily predictable, with an AUC of 0.72. Results of this diagnostic study suggest the possibility of combining genetics and registry data to predict both mental disorder diagnosis and disorder progression in a clinically relevant, cross-diagnostic setting prior to clinical assessment.

Validation of the Reduced Unified Continuum Formulation Against In Vitro 4D-Flow MRI.

We previously introduced and verified the reduced unified continuum formulation for vascular fluid-structure interaction (FSI) against Womersley's deformable wall theory. Our present work seeks to investigate its performance in a patient-specific aortic setting in which assumptions of idealized geometries and velocity profiles are invalid. Specifically, we leveraged 2D magnetic resonance imaging (MRI) and 4D-flow MRI to extract high-resolution anatomical and hemodynamic information from an in vitro flow circuit embedding a compliant 3D-printed aortic phantom. To accurately reflect experimental conditions, we numerically implemented viscoelastic external tissue support, vascular tissue prestressing, and skew boundary conditions enabling in-plane vascular motion at each inlet and outlet. Validation of our formulation is achieved through close quantitative agreement in pressures, lumen area changes, pulse wave velocity, and early systolic velocities, as well as qualitative agreement in late systolic flow structures. Our validated suite of FSI techniques offers a computationally efficient approach for numerical simulation of vascular hemodynamics. This study is among the first to validate a cardiovascular FSI formulation against an in vitro flow circuit involving a compliant vascular phantom of complex patient-specific anatomy.

Pelvic radiation therapy with volumetric modulated arc therapy and intensity-modulated radiotherapy after renal transplant: A report of 3 cases.

Describe characteristics and outcomes of three patients treated with pelvic radiation therapy after kidney transplant. The incidence of pelvic cancers in kidney transplant (KT) recipients is rising. Currently it is the leading cause of death. Moreover, treatment is challenging because anatomical variants, comorbidities, and associated treatments, which raises the concern of using radiotherapy (RT). RT has been discouraged due to the increased risk of urethral/ureteral stricture and KT dysfunction. We reviewed the electronic health records and digital planning system of patients treated with pelvic RT between December 2013 and December 2018 to identify patients with previous KT. We describe three successful cases of KT patients in which modern techniques allowed full standard RT for pelvic malignances (2 prostate and 1 vaginal cancer) with or without elective pelvic nodal RT, without allograft toxicity at short and long follow-up (up to 60 months). When needed, RT modern techniques remain a valid option with excellent oncologic results and acceptable toxicity. Physicians should give special considerations to accomplish all OAR dose constraints in the patient's specific setting. Recent publications recommend KT mean dose <4 Gy, but graft proximity to CTV makes this unfeasible. We present 2 cases where dose constraint was not achieved, and to a short follow-up of 20 months renal toxicity has not been documented. We recommend the lowest possible mean dose to the KT, but never compromising the CTV coverage, since morbimortality from recurrent or progressive cancer disease outweighs the risk of graft injury.

PGANs: Personalized Generative Adversarial Networks for ECG Synthesis to Improve Patient-Specific Deep ECG Classification

The Electrocardiogram (ECG) is performed routinely by medical personnel to identify structural, functional and electrical cardiac events. Many attempts were made to automate this task using machine learning algorithms including classic supervised learning algorithms and deep neural networks, reaching state-of-the-art performance. The ECG signal conveys the specific electrical cardiac activity of each subject thus extreme variations are observed between patients. These variations are challenging for deep learning algorithms, and impede generalization. In this work, we propose a semisupervised approach for patient-specific ECG classification. We propose a generative model that learns to synthesize patient-specific ECG signals, which can then be used as additional training data to improve a patient-specific classifier performance. Empirical results prove that the generated signals significantly improve ECG classification in a patient-specific setting.

Tumor localization accuracy for high-precision radiotherapy during active breath-hold

BackgroundConventionally fractionated and stereotactic body radiation therapy (SBRT) for thoracoabdominal tumors may utilize breath-hold techniques. However, there are concerns that differential amounts of inspired airflow may result in unplanned tumor dislocation and underdosing. Thus, we investigated tumor localization accuracy associated with lung volume variations during breath-hold treatment via an automated-gating interface. MethodsTwelve patients received breath-hold treatment with the active breathing coordinator (ABC) through an automated-gating interface. All breath-hold volumes were recorded at CT simulation, setup imaging, and during treatment, and analyzed as a function of airflow rate into the ABC. The variation of breath-hold volumes was calculated for each fraction over entire course. Intrafraction target motion related to the breathing variation was investigated based on daily imaging acquired before the breath-hold treatment. Correlation between target location and breath-hold variation was statistically analyzed. ResultsThe air volume held by the ABC increased as the airflow rate increased on inhalation and decreased on exhalation. The mean range of airflow rate was 0.77 L/s and 0.29 L/s in the conventionally fractionated and SBRT patients, respectively. The maximum air volume difference with respect to the reference volume at the CT simulation was 1.0 L for conventional fractionation and 0.16 L for SBRT. The target dislocation caused by 0.25 L of air volume difference was 6 mm for SBRT. Three patients showed significant correlation between the target location and breath-hold variations. ConclusionsThis investigation shows that because variations in the breath-hold volume may cause target dislocation, patient-specific breath-hold setting is required to improve tumor localization accuracy.

Quantifying the Dynamics of Field Cancerization in Tobacco-Related Head and Neck Cancer: A Multiscale Modeling Approach.

High rates of local recurrence in tobacco-related head and neck squamous cell carcinoma (HNSCC) are commonly attributed to unresected fields of precancerous tissue. Because they are not easily detectable at the time of surgery without additional biopsies, there is a need for noninvasive methods to predict the extent and dynamics of these fields. Here, we developed a spatial stochastic model of tobacco-related HNSCC at the tissue level and calibrated the model using a Bayesian framework and population-level incidence data from the Surveillance, Epidemiology, and End Results (SEER) registry. Probabilistic model analyses were performed to predict the field geometry at time of diagnosis, and model predictions of age-specific recurrence risks were tested against outcome data from SEER. The calibrated models predicted a strong dependence of the local field size on age at diagnosis, with a doubling of the expected field diameter between ages at diagnosis of 50 and 90 years, respectively. Similarly, the probability of harboring multiple, clonally unrelated fields at the time of diagnosis was found to increase substantially with patient age. On the basis of these findings, we hypothesized a higher recurrence risk in older than in younger patients when treated by surgery alone; we successfully tested this hypothesis using age-stratified outcome data. Further clinical studies are needed to validate the model predictions in a patient-specific setting. This work highlights the importance of spatial structure in models of epithelial carcinogenesis and suggests that patient age at diagnosis may be a critical predictor of the size and multiplicity of precancerous lesions. Cancer Res; 76(24); 7078-88. ©2016 AACR.

Abstract 2829: Preclinical analysis and characterization of abemaciclib using three-dimensional patient-derived colorectal cancer organoid cultures

Abstract Proper patient-tailoring strategy and the validation of novel therapeutic targets remain enormous challenges during drug discovery processes. Patient-derived three-dimensional organoid cell culture models possess great potential to associate compound sensitivity and disease complexity in order to provide a key missing link between compound screening and clinical trials. Abemaciclib is a reversible, ATP competitive, selective inhibitor of the kinase activity of both CDK4 and CDK6 and is currently undergoing advanced clinical testing. In this study, we established and characterized three-dimensional organoid cultures from primary colorectal cancer patients and validated their use as drug sensitivity models. We aimed to explore the antitumor activity of abemaciclib in colon cancer organoid cultures by assessing markers for cell viability, proliferation, cell cycle, senescence and apoptosis. Single cell suspension of patient-derived samples were precultured for four days to allow for complete morphogenesis of three-dimensional organoid structures. Subsequently, the cultures were treated for at least two population doubling times and analyzed by luminescent cell viability, immunohistochemistry and flow cytometry assays. Our data suggest that abemaciclib treatment decreased the cell viability of patient-derived colorectal cancer organoid cultures characterized by G1 cell cycle arrest and reduced Ki-67-positive cells. Furthermore, treated cultures showed elevated levels of reactive oxygen species and increased markers for early and late apoptosis. In summary, complex organoid models have the potential to further evaluate the antitumor activity of abemaciclib in various tumor types by enabling mechanistic studies in a patient-specific preclinical setting. Citation Format: Karsten Boehnke, Bruna Calsina, Joaquín Amat, Ana Hermoso, Raquel Torres, Christoph Reinhard, Juan A. Velasco, Philip W. Iversen, Alfonso De Dios, Sean Buchanan, Richard P. Beckmann, Dirk Schumacher, Christian RA Regenbrecht, Marie-Laure Yaspo, Hans Lehrach, María José Lallena. Preclinical analysis and characterization of abemaciclib using three-dimensional patient-derived colorectal cancer organoid cultures. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2829.

Factors Regulating Stem Cell Biology in Development and Disease.

Stem cells in general are characterized by their ability to self-renew and to differentiate towards various progeny. Great efforts started to give hope since the first discovery of mammalian pluripotency by Stevens and Little, 1954; the field of stem cell research using pluripotent stem cells (PSC) has reached a state of general interest in both science and medicine. Following an overall fast development of in vivo and in vitro research, stem cells are nowadays regularly implied in developmental and pathomechanistical studies. Their unique ability to generate all cell types of the respective organism allows for the directed differentiation of in vitro cultured PSCs into the desired direction. Subsequently, development and function of this differentiated progeny may be investigated in detail. This specifically accounts for the human system where primary materials as well as in vivo studies are strongly limited. In addition, the groundbreaking study describing the generation of PSCs from somatic cells by Takahashi and Yamanaka, served as a lift for unlimited use of individual and patient specific stem cell based investigations. Today, these induced pluripotent stem cells (iPSCs) are amongst others utilized to explicitly study human pathomechanisms in a patient specific setting. Moreover, tissue specific stem cell, for example, serving as a cellular reserve and substitute for decayed cells and degenerated tissue, is discussed as a useful source of human tissue and tissue specific cells. Clearly, these adult stem cells have already been successfully used in therapeutic approaches for decades, such as hematopoietic stem cells in bone marrow transplantations.

Development and Analysis of Patient-Based Complete Conducting Airways Models.

The analysis of high-resolution computed tomography (CT) images of the lung is dependent on inter-subject differences in airway geometry. The application of computational models in understanding the significance of these differences has previously been shown to be a useful tool in biomedical research. Studies using image-based geometries alone are limited to the analysis of the central airways, down to generation 6–10, as other airways are not visible on high-resolution CT. However, airways distal to this, often termed the small airways, are known to play a crucial role in common airway diseases such as asthma and chronic obstructive pulmonary disease (COPD). Other studies have incorporated an algorithmic approach to extrapolate CT segmented airways in order to obtain a complete conducting airway tree down to the level of the acinus. These models have typically been used for mechanistic studies, but also have the potential to be used in a patient-specific setting. In the current study, an image analysis and modelling pipeline was developed and applied to a number of healthy (n = 11) and asthmatic (n = 24) CT patient scans to produce complete patient-based airway models to the acinar level (mean terminal generation 15.8 ± 0.47). The resulting models are analysed in terms of morphometric properties and seen to be consistent with previous work. A number of global clinical lung function measures are compared to resistance predictions in the models to assess their suitability for use in a patient-specific setting. We show a significant difference (p < 0.01) in airways resistance at all tested flow rates in complete airway trees built using CT data from severe asthmatics (GINA 3–5) versus healthy subjects. Further, model predictions of airways resistance at all flow rates are shown to correlate with patient forced expiratory volume in one second (FEV1) (Spearman ρ = −0.65, p < 0.001) and, at low flow rates (0.00017 L/s), FEV1 over forced vital capacity (FEV1/FVC) (ρ = −0.58, p < 0.001). We conclude that the pipeline and anatomical models can be used directly in mechanistic modelling studies and can form the basis for future patient-based modelling studies.

Feasibility of titrating PEEP to minimum elastance for mechanically ventilated patients.

BackgroundSelecting positive end-expiratory pressure (PEEP) during mechanical ventilation is important, as it can influence disease progression and outcome of acute respiratory distress syndrome (ARDS) patients. However, there are no well-established methods for optimizing PEEP selection due to the heterogeneity of ARDS. This research investigates the viability of titrating PEEP to minimum elastance for mechanically ventilated ARDS patients.MethodsTen mechanically ventilated ARDS patients from the Christchurch Hospital Intensive Care Unit were included in this study. Each patient underwent a stepwise PEEP recruitment manoeuvre. Airway pressure and flow data were recorded using a pneumotachometer. Patient-specific respiratory elastance (Ers) and dynamic functional residual capacity (dFRC) at each PEEP level were calculated and compared. Optimal PEEP for each patient was identified by finding the minima of the PEEP-Ers profile.ResultsMedian Ers and dFRC over all patients and PEEP values were 32.2 cmH2O/l [interquartile range (IQR) 25.0–45.9] and 0.42 l [IQR 0.11–0.87]. These wide ranges reflect patient heterogeneity and variable response to PEEP. The level of PEEP associated with minimum Ers corresponds to a high change of functional residual capacity, representing the balance between recruitment and minimizing the risk of overdistension.ConclusionsMonitoring patient-specific Ers can provide clinical insight to patient-specific condition and response to PEEP settings. The level of PEEP associated with minimum-Ers can be identified for each patient using a stepwise PEEP recruitment manoeuvre. This ‘minimum elastance PEEP’ may represent a patient-specific optimal setting during mechanical ventilation.Trial registrationAustralian New Zealand Clinical Trials Registry: ACTRN12611001179921.Electronic supplementary materialThe online version of this article (doi:10.1186/s40814-015-0006-2) contains supplementary material, which is available to authorized users.

Concise Review: Modeling Multiple Sclerosis With Stem Cell Biological Platforms: Toward Functional Validation of Cellular and Molecular Phenotypes in Inflammation-Induced Neurodegeneration

In recent years, tremendous progress has been made in identifying novel mechanisms and new medications that regulate immune cell function in multiple sclerosis (MS). However, a significant unmet need is the identification of the mechanisms underlying neurodegeneration, because patients continue to manifest brain atrophy and disability despite current therapies. Neural and mesenchymal stem cells have received considerable attention as therapeutic candidates to ameliorate the disease in preclinical and phase I clinical trials. More recently, progress in somatic cell reprogramming and induced pluripotent stem cell technology has allowed the generation of human "diseased" neurons in a patient-specific setting and has provided a unique biological tool that can be used to understand the cellular and molecular mechanisms of neurodegeneration. In the present review, we discuss the application and challenges of these technologies, including the generation of neurons, oligodendrocytes, and oligodendrocyte progenitor cells (OPCs) from patients and novel stem cell and OPC cellular arrays, in the discovery of new mechanistic insights and the future development of MS reparative therapies.

Toward Patient-Specific Targeting and Parameter Setting of Deep Brain Stimulation for Relief of Depression

Toward Patient-Specific Targeting and Parameter Setting of Deep Brain Stimulation for Relief of Depression

Three-dimensional finite element analysis of shaping curved root canals with the ProTaper and HeroShaper systems

In this study, we simulated the shaping of a curved root canal with the ProTaper and HeroShaper file systems using three-dimensional finite element modeling. A total of seven of the Ni–Ti rotary instruments were employed to investigate the influence of cutting geometry. A workflow was developed using the mechanical design and analysis software I-DEAS 11 and the LS-DYNA finite element package. The three-dimensional tooth model was constructed from a micro-computed tomography dental scan and a simulated canal. It was found that stresses concentrated towards the outer aspect of curvature in the apical portion of the canal when the ProTaper file system was employed. For the HeroShaper files, the stresses concentrated in the middle portion of the tooth model. Our simulated root canal procedure enables the efficacy of rotary Ni–Ti instruments to be evaluated in a patient-specific setting. This may aid the dentist in choosing the optimal tool set and provides data for improving tool design.

Rumpel-Leede Phenomenon After Tourniquet Use in Limb Surgery: A Case Report.

Pneumatic tourniquets are widely used for limb surgery to provide a bloodless field and facilitate dissection. In the United States, more than 15,000 surgical procedures are performed daily with the application of a pneumatic tourniquet1. Modern automatic pneumatic tourniquets, designed to minimize the incidence of potential complications1, include a microprocessor to maintain cuff pressure to within 1% of the set pressure as well as an automatic timer to record the inflation time of the tourniquet. They can also perform an automated estimation of the limb occlusion pressure, allowing for a patient-specific setting of safer tourniquet pressures. Although patient safety has been improved, modern tourniquets can be associated with potential morbidity, leading to prolonged hospitalization and delayed return to work2. There are two types of complications: systemic effects caused by the ischemia-reperfusion mechanism and local effects caused by direct compression of tissues. Complications can range from minor and self-limiting events to severe3-7 or fatal8,9 events. We report a non-life-threatening complication related to trauma induced by a tourniquet, resulting in a prolonged severe rash and petechiae distal to the tourniquet cuff. The patient was informed that data concerning this case would be submitted for publication, and she provided consent. A sixty-eight-year-old woman was scheduled for excision of a giant-cell tumor of the tendon sheath arising from the volar aspect …

Challenges for Engineers in Biomedical and Clinical Sciences

Challenges for Engineers in Biomedical and Clinical Sciences