Knut Moeller

Electrical impedance tomography: functional lung imaging on its way to clinical practice?

Electrical impedance tomography (EIT) has the potential to become a bedside tool for monitoring and guiding ventilator therapy as well as tracking the development of chronic lung diseases. This review article summarizes recent publications (from 2011) dealing with the applications of pulmonary EIT. Original papers on EIT lung imaging in clinical settings are analyzed and divided into several categories according to the lung pathology of the study subjects. Studies on children and infants are presented separately from studies on adult patients. Information on the study objectives and main results, the number of studied patients, the performed ventilatory maneuvers or interventions and the analyzed EIT information is given. Limitations that hinder EIT to become a routinely used tool in a clinical setting are also discussed.

Using multi-dimensional dynamic time warping for TUG test instrumentation with inertial sensors

The Timed Up and Go (TUG) is a clinical test used widely to measure balance and mobility, e.g. in Parkinsons disease (PD). The test includes a sequence of functional activities, namely: sit-to-stand, 3-meters walk, 180° turn, walk back, another turn and sit on the chair. Meanwhile the stopwatch is used to score the test by measuring the time which the patients with PD need to perform the test. Here, the work presents an instrumented TUG using a wearable inertial sensor unit attached on the lower back of the person. The approach is used to automate the process of assessment compared with the manual evaluation by using visual observation and a stopwatch. The developed algorithm is based on the Dynamic Time Warping (DTW) for multi-dimensional time series and has been applied with the augmented feature for detection and duration assessment of turn state transitions, while a 1-dimensional DTW is used to detect the sit-to-stand and stand-to-sit phases. The feature set is a 3-dimensional vector which consists of the angular velocity, derived angle and features from Linear Discriminant Analysis (LDA). The algorithm was tested on 10 healthy individuals and 20 patients with PD (10 patients with early and late disease phases respectively). The test demonstrates that the developed technique can successfully extract the time information of the sit-to-stand, both turns and stand-to-sit transitions in the TUG test.

Physiological relevance and performance of a minimal lung model – an experimental study in healthy and acute respiratory distress syndrome model piglets

BackgroundMechanical ventilation (MV) is the primary form of support for acute respiratory distress syndrome (ARDS) patients. However, intra- and inter- patient-variability reduce the efficacy of general protocols. Model-based approaches to guide MV can be patient-specific. A physiological relevant minimal model and its patient-specific performance are tested to see if it meets this objective above.MethodsHealthy anesthetized piglets weighing 24.0 kg [IQR: 21.0-29.6] underwent a step-wise PEEP increase manoeuvre from 5cmH2O to 20cmH2O. They were ventilated under volume control using Engström Care Station (Datex, General Electric, Finland), with pressure, flow and volume profiles recorded. ARDS was then induced using oleic acid. The data were analyzed with a Minimal Model that identifies patient-specific mean threshold opening and closing pressure (TOP and TCP), and standard deviation (SD) of these TOP and TCP distributions. The trial and use of data were approved by the Ethics Committee of the Medical Faculty of the University of Liege, Belgium.Results and discussions3 of the 9 healthy piglets developed ARDS, and these data sets were included in this study. Model fitting error during inflation and deflation, in healthy or ARDS state is less than 5.0% across all subjects, indicating that the model captures the fundamental lung mechanics during PEEP increase. Mean TOP was 42.4cmH2O [IQR: 38.2-44.6] at PEEP = 5cmH2O and decreased with PEEP to 25.0cmH2O [IQR: 21.5-27.1] at PEEP = 20cmH2O. In contrast, TCP sees a reverse trend, increasing from 10.2cmH2O [IQR: 9.0-10.4] to 19.5cmH2O [IQR: 19.0-19.7]. Mean TOP increased from average 21.2-37.4cmH2O to 30.4-55.2cmH2O between healthy and ARDS subjects, reflecting the higher pressure required to recruit collapsed alveoli. Mean TCP was effectively unchanged.ConclusionThe minimal model is capable of capturing physiologically relevant TOP, TCP and SD of both healthy and ARDS lungs. The model is able to track disease progression and the response to treatment.

Sampling of finite elements for sparse recovery in large scale 3D electrical impedance tomography

This study proposes a method to improve performance of sparse recovery inverse solvers in 3D electrical impedance tomography (3D EIT), especially when the volume under study contains small-sized inclusions, e.g. 3D imaging of breast tumours. Initially, a quadratic regularized inverse solver is applied in a fast manner with a stopping threshold much greater than the optimum. Based on assuming a fixed level of sparsity for the conductivity field, finite elements are then sampled via applying a compressive sensing (CS) algorithm to the rough blurred estimation previously made by the quadratic solver. Finally, a sparse inverse solver is applied solely to the sampled finite elements, with the solution to the CS as its initial guess. The results show the great potential of the proposed CS-based sparse recovery in improving accuracy of sparse solution to the large-size 3D EIT.

Visualisation of Time-Variant Respiratory System Elastance in ARDS Models

Model-based mechanical ventilation (MV) can be used to characterise patient-specific condition and response to MV. This paper presents a novel method to visualise respiratory mechanics during MV of patients suffering from acute respiratory distress syndrome. The single compartment lung model is extended to monitor time-varying respiratory system elastance within each breathing cycle. Monitoring continuous in-breath me- chanics allows changes to be observed continuously, providing more insight into lung physiology. Thus, this new monitoring method may potentially aid clinicians to guide MV in a heterogeneous population.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications.

When the value of gold is zero

This manuscript presents the concerns around the increasingly common problem of not having readily available or useful “gold standard” measurements. This issue is particularly important in critical care where many measurements used in decision making are surrogates of what we would truly wish to use. However, the question is broad, important and applicable in many other areas.In particular, a gold standard measurement often exists, but is not clinically (or ethically in some cases) feasible. The question is how does one even begin to develop new measurements or surrogates if one has no gold standard to compare with?We raise this issue concisely with a specific example from mechanical ventilation, a core bread and butter therapy in critical care that is also a leading cause of length of stay and cost of care. Our proposed solution centers around a hierarchical validation approach that we believe would ameliorate ethics issues around radiation exposure that make current gold standard measures clinically infeasible, and thus provide a pathway to create a (new) gold standard.

Multi-layer ventilation inhomogeneity in cystic fibrosis

Differences in regional lung function between the 3rd and 5th intercostal space (ICS) were explored in 10 cystic fibrosis (CF) patients and compared to 10 lung-healthy controls by electrical impedance tomography (EIT). Regional ratios of impedance changes corresponding to the maximal volume of air exhaled within the first second of a forced expiration (ΔIFEV1) and the forced vital capacity (ΔIFVC) were determined. Regional airway obstruction and ventilation inhomogeneity were assessed by the frequency distribution of these ratios (ΔIFEV1/ΔIFVC) and an inhomogeneity index (GITI). The mean of the frequency distribution of ΔIFEV1/ΔIFVC and the GITI in both thorax planes were significantly different between CF patients and controls (p<0.001). CF patients exhibited a significantly lower mean of ΔIFEV1/ΔIFVC frequency distribution (p<0.05) and a significantly higher degree of ventilation inhomogeneity (p<0.01) in the 3rd ICS compared to the 5th ICS. Results indicated that EIT measurements at more cranial thorax planes may benefit the early diagnosis in CF.

Sparse regularization for EIT reconstruction incorporating structural information derived from medical imaging

Electrical impedance tomography (EIT) reconstructs the conductivity distribution of a domain using electrical data on its boundary. This is an ill-posed inverse problem usually solved on a finite element mesh. For this article, a special regularization method incorporating structural information of the targeted domain is proposed and evaluated. Structural information was obtained either from computed tomography images or from preliminary EIT reconstructions by a modified k-means clustering. The proposed regularization method integrates this structural information into the reconstruction as a soft constraint preferring sparsity in group level. A first evaluation with Monte Carlo simulations indicated that the proposed solver is more robust to noise and the resulting images show fewer artifacts. This finding is supported by real data analysis. The structure based regularization has the potential to balance structural a priori information with data driven reconstruction. It is robust to noise, reduces artifacts and produces images that reflect anatomy and are thus easier to interpret for physicians.

A fast time-difference inverse solver for 3D EIT with application to lung imaging

AbstractA class of sparse optimization techniques that require solely matrix–vector products, rather than an explicit access to the forward matrix and its transpose, has been paid much attention in the recent decade for dealing with large-scale inverse problems. This study tailors application of the so-called Gradient Projection for Sparse Reconstruction (GPSR) to large-scale time-difference three-dimensional electrical impedance tomography (3D EIT). 3D EIT typically suffers from the need for a large number of voxels to cover the whole domain, so its application to real-time imaging, for example monitoring of lung function, remains scarce since the large number of degrees of freedom of the problem extremely increases storage space and reconstruction time. This study shows the great potential of the GPSR for large-size time-difference 3D EIT. Further studies are needed to improve its accuracy for imaging small-size anomalies.