Multi-level digital-twin models of pulmonary mechanics: correlation analysis of 3D CT lung volume and 2D Chest motion

Creating multi-level digital-twin models for mechanical ventilation requires a detailed estimation of regional lung volume. An accurate generic map between 2D chest surface motion and 3D regional lung volume could provide improved regionalisation and clinically acceptable estimates localising lung damage. This work investigates the relationship between CT lung volumes and the forced vital capacity (FVC) a surrogate of tidal volume proven linked to 2D chest motion. In particular, a convolutional neural network (CNN) with U-Net architecture is employed to build a lung segmentation model using a benchmark CT scan dataset. An automated thresholding method is proposed for image morphology analysis to improve model performance. Finally, the trained model is applied to an independent CT dataset with FVC measurements for correlation analysis of CT lung volume projection to lung recruitment capacity. Model training results show a clear improvement of lung segmentation performance with the proposed automated thresholding method compared to a typically suggested fixed value selection, achieving accuracy greater than 95% for both training and independent validation sets. The correlation analysis for 160 patients shows a good correlation ofRsquared value of 0.73 between the proposed 2D volume projection and the FVC value, which indicates a larger and denser projection of lung volume relative to a greater FVC value and lung recruitable capacity. The overall results thus validate the potential of using non-contact, non-invasive 2D measures to enable regionalising lung mechanics models to equivalent 3D models with a generic map based on the good correlation. The clinical impact of improved lung mechanics digital twins due to regionalising the lung mechanics and volume to specific lung regions could be very high in managing mechanical ventilation and diagnosing or locating lung injury or dysfunction based on regular monitoring instead of intermittent and invasive lung imaging modalities.

High-resolution conductivity reconstruction by electrical impedance tomography using structure-aware hybrid-fusion learning

BACKGROUND

Electrical impedance tomography (EIT) has gained considerable attention in the medical field for the diagnosis of lung-related diseases, owing to its non-invasive and real-time characteristics. However, due to the ill-posedness and underdetermined nature of the inverse problem in EIT, suboptimal reconstruction performance and reduced robustness against the measurement noise and modeling errors are common issues.

OBJECTIVES

This study aims to mine the deep feature information from measurement voltages, acquired from the EIT sensor, to reconstruct the high-resolution conductivity distribution and enhance the robustness against the measurement noise and modeling errors using the deep learning method.

METHODS

A novel data-driven method named the structure-aware hybrid-fusion learning (SA-HFL) is proposed. SA-HFL is composed of three main components: a segmentation branch, a conductivity reconstruction branch, and a feature fusion module. These branches work in tandem to extract different feature information from the measurement voltage, which is then fused to reconstruct the conductivity distribution. The unique aspect of this network is its ability to utilize different features extracted from various branches to accomplish reconstruction objectives. To supervise the training of the network, we generated regular-shaped and lung-shaped EIT datasets through numerical calculations.

RESULTS

The simulations and three experiments demonstrate that the proposed SA-HFL exhibits superior performance in qualitative and quantitative analyses, compared with five cutting-edge deep learning networks and the optical image-guided group sparsity (IGGS) method. The evaluation metrics, relative error (RE), mean structural similarity index (MSSIM), and peak signal-to-noise ratio (PSNR), are improved by implementing the SA-HFL method. For the regular-shaped dataset, the values are 0.119 (RE), 0.9882 (MSSIM), and 31.03 (PSNR). For the lung-shaped dataset, the values are 0.257 (RE), 0.9151 (MSSIM), and 18.67 (PSNR). Furthermore, the proposed network can be executed with appropriate parameters and efficient floating-point operations per second (FLOPs), concerning network complexity and inference speed.

CONCLUSIONS

The reconstruction results indicate that fusing feature information from different branches enhances the accuracy of conductivity reconstruction in the EIT inverse problem. Moreover, the study shows that fusing different modalities of information to reconstruct the EIT conductivity distribution may be a future development direction.

Effect of a Patient-Specific Structural Prior Mask on Electrical Impedance Tomography Image Reconstructions

Electrical Impedance Tomography (EIT) is a low-cost imaging method which reconstructs two-dimensional cross-sectional images, visualising the impedance change within the thorax. However, the reconstruction of an EIT image is an ill-posed inverse problem. In addition, blurring, anatomical alignment, and reconstruction artefacts can hinder the interpretation of EIT images. In this contribution, we introduce a patient-specific structural prior mask into the EIT reconstruction process, with the aim of improving image interpretability. Such a prior mask ensures that only conductivity changes within the lung regions are reconstructed. To evaluate the influence of the introduced structural prior mask, we conducted numerical simulations with two scopes in terms of their different ventilation statuses and varying atelectasis scales. Quantitative analysis, including the reconstruction error and figures of merit, was applied in the evaluation procedure. The results show that the morphological structures of the lungs introduced by the mask are preserved in the EIT reconstructions and the reconstruction artefacts are decreased, reducing the reconstruction error by 25.9% and 17.7%, respectively, in the two EIT algorithms included in this contribution. The use of the structural prior mask conclusively improves the interpretability of the EIT images, which could facilitate better diagnosis and decision-making in clinical settings.

An efficient and fast multi-band focused bioimpedance solution with EIT-based reconstruction for pulmonary embolism assessment: a simulation study from massive to segmental blockage

OBJECTIVE

Pulmonary embolism (PE) is an acute condition that blocks the perfusion to the lungs and is a common complication of Covid-19. However, PE is often not diagnosed in time, especially in the pandemic time due to complicated diagnosis protocol. In this study, a non-invasive, fast and efficient bioimpedance method with the EIT-based reconstruction approach is proposed to assess the lung perfusion reliably.

APPROACH

Some proposals are presented to improve the sensitivity and accuracy for the bioimpedance method: (1) a new electrode configuration and focused pattern to help study deep changes caused by PE within each lung field separately, (2) a measurement strategy to compensate the effect of different boundary shapes and varied respiratory conditions on the perfusion signals and (3) an estimator to predict the lung perfusion capacity, from which the severity of PE can be assessed. The proposals were tested on the first-time simulation of PE events at different locations and degrees from segmental blockages to massive blockages. Different object boundary shapes and varied respiratory conditions were included in the simulation to represent for different populations in real measurements.

RESULTS

The correlation between the estimator and the perfusion was very promising (R = 0.91, errors < 6%). The measurement strategy with the proposed configuration and pattern has helped stabilize the estimator to non-perfusion factors such as the boundary shapes and varied respiration conditions (3-5% errors).

SIGNIFICANCE

This promising preliminary result has demonstrated the proposed bioimpedance method's capability and feasibility, and might start a new direction for this application.

Case report: Post-thoracoscopy pendelluft monitoring

Asynchronous alveolar ventilation is called pendelluft, which may induce lung injury in spontaneously breathing patients. We report a case that electrical impedance tomography (EIT) was used to assess the pendelluft in a post-thoracoscopy patient. The pendelluft amplitude was as high as 77.5% of the tidal variation. The average regional time shift was 0.5 s. The patient was instructed to adjust the breathing method, symptomatic treatment was performed, and the symptoms were improved. This is the first case reporting pendelluft in a post-thoracoscopy patient. Our case demonstrated that (1) pendelluft may occur in post-thoracoscopy patients and it effects lung function, and (2) early identification of affected patients and implementation of corresponding treatments could improve patient outcomes.

The Research Progress of Electrical Impedance Tomography for Lung Monitoring

Medical imaging can intuitively show people the internal structure, morphological information, and organ functions of the organism, which is one of the most important inspection methods in clinical medical diagnosis. Currently used medical imaging methods can only be applied to some diagnostic occasions after qualitative lesions have been generated, and the general imaging technology is usually accompanied by radiation and other conditions. However, electrical impedance tomography has the advantages of being noninvasive and non-radiative. EIT (Electrical Impedance Tomography) is also widely used in the early diagnosis and treatment of some diseases because of these advantages. At present, EIT is relatively mature and more and more image reconstruction algorithms are used to improve imaging resolution. Hardware technology is also developing rapidly, and the accuracy of data collection and processing is continuously improving. In terms of clinical application, EIT has also been used for pathological treatment of lungs, the brain, and the bladder. In the future, EIT has a good application prospect in the medical field, which can meet the needs of real-time, long-term monitoring and early diagnosis. Aiming at the application of EIT in the treatment of lung pathology, this article reviews the research progress of EIT, image reconstruction algorithms, hardware system design, and clinical applications used in the treatment of lung diseases. Through the research and introduction of several core components of EIT technology, it clarifies the characteristics of EIT system complexity and its solutions, provides research ideas for subsequent research, and once again verifies the broad development prospects of EIT technology in the future.

Lung ventilation distribution in patients after traditional full sternotomy and minimally invasive thoracotomy: An observational study

BACKGROUND

The aim of the study was to examine the post-operative ventilation distribution changes in cardiac surgical patients after traditional full sternotomy (FS) or minimally invasive thoracotomy (MIT).

METHODS

A total of 40 patients scheduled for FS with two-lung ventilation or MIT with one-lung ventilation were included. Ventilation distribution was measured with electrical impedance tomography (EIT) at T1, before surgery; T2, after surgery in ICU before weaning; T3, 24 hours after extubation. EIT-based parameters were calculated to assess the ventilation distribution, including the left-to-right lung ratio, ventral-to-dorsal ratio, and the global inhomogeneity index.

RESULTS

The global inhomogeneity index increased at T2 and T3 compared to T1 in all patients but only statistically significant in patients with MIT (FS, P = .06; MIT, P < .01). Notable decrease in the dorsal regions (FS) or in the non-ventilated side (MIT) was observed at T2. Ventilation distribution was partially improved at T3 but huge variations of recovery progresses were found in all patients regardless of the surgery types. Subgroup analysis indicated that operation duration was significantly lower in the MIT group (240 ± 40 in FS vs 205 ± 90 minutes in MIT, median ± interquartile range, P < .05) but the incidence of atrial fibrillation/flutter was significantly higher (5% in FS vs 50% in MIT, P < .01). Other exploratory outcomes showed no statistical differences.

CONCLUSIONS

Ventilation distribution was impaired after cardiac surgery. The recovery process of ventilation homogeneity was strongly depending on individuals so that MIT was not always superior in this aspect. EIT may help to identify the patients requiring further care after surgery.

Freezing resistance evaluation of rose stems during frost dehardening using electrical impedance tomography

BACKGROUND

Electrical impedance tomography (EIT) has rarely been applied in plant science, particularly to study plant resistance to abiotic and biotic stresses. In this study, we evaluated the freezing resistance of floribunda roses (Rosa Floribunda) during frost dehardening using the EIT technique to identify a new method for rapid and non-destructive measurement of plant freezing resistance.

RESULTS

The current was the excitation source, the boundary voltage value was measured, and then the boundary voltage reconstructed value was formed. Using an imaging algorithm, the two-dimensional (2D) distribution of impedance or impedance variation was reconstructed. The EIT reconstructed values decreased obviously with the decline in freezing temperatures. The EIT reconstructed values of stems had the best fit to the logistic equation, and subsequently, the semi-lethal temperatures were calculated. The freezing resistance results evaluated using EIT reconstructed values were linearly correlated with the results of the traditional electrolyte leakage (EL) method (r = 0.93, P < 0.01).

CONCLUSIONS

In conclusion, after freezing tests, the reconstructed values of EIT images could be used to quantitatively evaluate the freezing resistance of floribunda rose stems. The present study provides a reference for the further application of the EIT technique for non-destructive and rapid detection of plant freezing resistance.

Anomaly Detection Using Electric Impedance Tomography Based on Real and Imaginary Images

This research offers a method for separating the components of tissue impedance, namely resistance and capacitive reactance. Two objects that have similar impedance or low contrast can be improved through separating the real and imaginary images. This method requires an Electrical Impedance Tomography (EIT) device. EIT can obtain potential data and the phase angle between the current and the potential measured. In the future, the device is very suitable for imaging organs in the thorax and abdomen that have the same impedance but different resistance and capacitive reactance. This device consists of programmable generators, Voltage Controlled Current Source (VCCS), mulptiplexer-demultiplexer potential meters, and phase meters. Data collecting was done by employing neighboring, while reconstruction was used the linear back-projection method from two different data frequencies, namely 10 kHz and 100 kHz. Phantom used in this experiment consists of distillated water and a carrot as an anomaly. Potential and phase data from the device is reconstructed to produce impedance, real, and imaginary images. Image analysis is performed by comparing the three images to the phantom. The experimental results show that the device is reliable.

The dawn of physiological closed-loop ventilation-a review

The level of automation in mechanical ventilation has been steadily increasing over the last few decades. There has recently been renewed interest in physiological closed-loop control of ventilation. The development of these systems has followed a similar path to that of manual clinical ventilation, starting with ensuring optimal gas exchange and shifting to the prevention of ventilator-induced lung injury. Systems currently aim to encompass both aspects, and early commercial systems are appearing. These developments remain unknown to many clinicians and, hence, limit their adoption into the clinical environment. This review shows the evolution of the physiological closed-loop control of mechanical ventilation.

Optimal mean airway pressure during high-frequency oscillatory ventilation in an experimental model of acute respiratory distress syndrome: EIT-based method

Background

High-frequency oscillatory ventilation (HFOV) may theoretically provide lung protective ventilation. The negative clinical results may be due to inadequate mean airway pressure (mPaw) settings in HFOV. Our objective was to evaluate the air distribution, ventilatory and hemodynamic effects of individual mPaw titration during HFOV in ARDS animal based on oxygenation and electrical impedance tomography (EIT).

Methods

ARDS was introduced with repeated bronchoalveolar lavage followed by injurious mechanical ventilation in ten healthy male pigs (51.2 ± 1.9 kg). Settings of HFOV were 9 Hz (respiratory frequency), 33% (inspiratory time) and 70 cmH₂O (∆pressure). After lung recruitment, the mPaw was reduced in steps of 3 cmH₂O every 6 min. Hemodynamics and blood gases were obtained in each step. Regional ventilation distribution was determined with EIT.

Results

PaO₂/FiO₂ decreased significantly during the mPaw decremental phase (p < 0.001). Lung overdistended regions decreased, while recruitable regions increased as mPaw decreased. The optimal mPaw with respect to PaO₂/FiO₂ was 21 (18.0–21.0) cmH₂O, that is comparable to EIT-based center of ventilation (EIT-CoV) and EIT-collapse/over, 19.5 (15.0–21.0) and 19.5 (18.0–21.8), respectively (p = 0.07). EIT-CoV decreasing along with mPaw decrease revealed redistribution toward non-dependent regions. The individual mPaw titrated by EIT-based indices improved regional ventilation distribution with respect to overdistension and collapse (p = 0.035).

Conclusion

Our data suggested personalized optimal mPaw titration by EIT-based indices improves regional ventilation distribution and lung homogeneity during high-frequency oscillatory ventilation.

Applications of near infrared and surface enhanced Raman scattering techniques in tumor imaging: A short review

Imaging technologies play a vital role in clinical oncology and have undergone massive growth over the past few decades. Research in the field of tumor imaging and biomedical diagnostics requires early detection of physiological alterations so as to provide curative treatment in real time. The objective of this review is to provide an insight about near infrared fluorescence (NIRF) and surface enhanced Raman scattering (SERS) imaging techniques that can be used to expand their capabilities for the early detection and diagnosis of cancer cells. Basic setup, principle and working of the instruments has been provided and common NIRF imaging agents as well as SERS tags are also discussed besides the analytical advantages/disadvantages of these techniques. This review can help researchers working in the field of molecular imaging to design cost effective fluorophores and SERS tags to overcome the limitations of both NIRF as well as SERS imaging technologies.

The incidence and interpretation of large differences in EIT-based measures for PEEP titration in ARDS patients

Positive end-expiratory pressure (PEEP) can be titrated by electrical impedance tomography (EIT). The aim of the present study was to examine the performance of different EIT measures during PEEP trials with the aim of identifying "optimum" PEEP and to provide possible interpretations of largely diverging results. After recruitment (maximum plateau pressure 35 cmH₂O), decremental PEEP trial with steps of 2 cmH₂O and duration of 2 min per step was performed. Ventilation gain and loss, the global inhomogeneity (GI) index, trend of end-expiratory lung impedance (EELI) and regional compliance (C_reg) for estimation of overdistension and collapse were calculated. Largely diverging results of PEEP selection among the measures were defined as differences ≥ 4 PEEP steps (i.e. ≥ 8 cmH₂O). In 30 ARDS patients we examined so far, 3 patients showed significant differences in PEEP selections. Overdistension and collapse estimation based on C_reg tended to select lower PEEP while the GI index and EELI trend suggested higher PEEP settings. Regional inspiration times were heterogeneous indicating that the assumption of a uniform driving pressure in the calculation of C_reg may not be valid. Judging by the predominant ventilation distribution in the most dependent regions, these patients were non-recruitable with the applied recruitment method or pressure levels. The existence of differences in the recommended PEEP among the analyzed EIT measures might be an indicator of non-recruitable lungs and heterogeneous airway resistances. In these extreme cases, the largely diverging results may prompt the attending clinician to develop individual ventilation strategies.Clinical Trial Registration Registration number NCT03112512, https://clinicaltrials.gov/ Registered 13 April 2017.

A Review of Electrical Impedance Tomography in Lung Applications: Theory and Algorithms for Absolute Images

Electrical Impedance Tomography (EIT) is under fast development, the present paper is a review of some procedures that are contributing to improve spatial resolution and material properties accuracy, admitivitty or impeditivity accuracy. A review of EIT medical applications is presented and they were classified into three broad categories: ARDS patients, obstructive lung diseases and perioperative patients. The use of absolute EIT image may enable the assessment of absolute lung volume, which may significantly improve the clinical acceptance of EIT. The Control Theory, the State Observers more specifically, have a developed theory that can be used for the design and operation of EIT devices. Electrode placement, current injection strategy and electrode electric potential measurements strategy should maximize the number of observable and controllable directions of the state vector space. A non-linear stochastic state observer, the Unscented Kalman Filter, is used directly for the reconstruction of absolute EIT images. Historically, difference images were explored first since they are more stable in the presence of modelling errors. Absolute images require more detailed models of contact impedance, stray capacitance and properly refined finite element mesh where the electric potential gradient is high. Parallelization of the forward program computation is necessary since the solution of the inverse problem often requires frequent solutions of the forward problem. Several reconstruction algorithms benefit by the Bayesian inverse problem approach and the concept of prior information. Anatomic and physiologic information are used to form the prior information. An already tested methodology is presented to build the prior probability density function using an ensemble of CT scans and in vivo impedance measurements. Eight absolute EIT image algorithms are presented.

Optimising mechanical ventilation through model-based methods and automation

Mechanical ventilation (MV) is a core life-support therapy for patients suffering from respiratory failure or acute respiratory distress syndrome (ARDS). Respiratory failure is a secondary outcome of a range of injuries and diseases, and results in almost half of all intensive care unit (ICU) patients receiving some form of MV. Funding the increasing demand for ICU is a major issue and MV, in particular, can double the cost per day due to significant patient variability, over-sedation, and the large amount of clinician time required for patient management. Reducing cost in this area requires both a decrease in the average duration of MV by improving care, and a reduction in clinical workload. Both could be achieved by safely automating all or part of MV care via model-based dynamic systems modelling and control methods are ideally suited to address these problems. This paper presents common lung models, and provides a vision for a more automated future and explores predictive capacity of some current models. This vision includes the use of model-based methods to gain real-time insight to patient condition, improve safety through the forward prediction of outcomes to changes in MV, and develop virtual patients for in-silico design and testing of clinical protocols. Finally, the use of dynamic systems models and system identification to guide therapy for improved personalised control of oxygenation and MV therapy in the ICU will be considered. Such methods are a major part of the future of medicine, which includes greater personalisation and predictive capacity to both optimise care and reduce costs. This review thus presents the state of the art in how dynamic systems and control methods can be applied to transform this core area of ICU medicine.

The Effect of Gold Nanoparticles on Electrical Impedance of Tissue on Low Frequency Ranges

INTRODUCTION

Electrical impedance of tissues on low frequencies includes useful information about functional and structural changes in tissues. This property is used in Electrical Impedance Tomography (EIT) imaging modality for the detection of lesions in tissues.

OBJECTIVE

The goal of this article is to study changes in electrical impedance of tissues in the presence of gold nanoparticles.

MATERIALS AND METHODS

Spherical gold nanoparticles with size of 20-25 nm were synthesized with Turkevich method. Size distribution and shape of nanoparticles were characterized by transmission electron microscopy (TEM). Electrical impedance of two types of phantoms (chicken fat and muscle paste tissues) was measured by 4-electrode method with and without gold nanoparticles.

RESULTS

Results demonstrate a reduction in electrical impedance of tissues in the presence of gold nanoparticles. However, this reduction is not the same for fat and muscle tissues. Reductions in resistive impedance are 40.24Ω and 1.93 Ω for fat and muscle tissues on the frequency of 1 KHz, respectively. A reduction in electrical impedance is accompanied by a rise in electrical conductance leading to increase in EIT signal.

CONCLUSION

As signal enhancement is different for fat and muscle tissues; presence of gold nanoparticles could be used to improve EIT image contrast.

Ventilation inhomogeneity in obstructive lung diseases measured by electrical impedance tomography: a simulation study

Electrical impedance tomography (EIT) has mostly been used in the Intensive Care Unit (ICU) to monitor ventilation distribution but is also promising for the diagnosis in spontaneously breathing patients with obstructive lung diseases. Beside tomographic images, several numerical measures have been proposed to quantitatively assess the lung state. In this study two common measures, the 'Global Inhomogeneity Index' and the 'Coefficient of Variation' were compared regarding their capability to reflect the severity of lung obstruction. A three-dimensional simulation model was used to simulate obstructed lungs, whereby images were reconstructed on a two-dimensional domain. Simulations revealed that minor obstructions are not adequately recognized in the reconstructed images and that obstruction above and below the electrode plane may result in misleading values of inhomogeneity measures. EIT measurements on several electrode planes are necessary to apply these measures in patients with obstructive lung diseases in a promising manner.

EIT based pulsatile impedance monitoring during spontaneous breathing in cystic fibrosis

OBJECTIVE

Evaluating the lung function in patients with obstructive lung disease by electrical impedance tomography (EIT) usually requires breathing maneuvers containing deep inspirations and forced expirations. Since these maneuvers strongly depend on the patient's co-operation and health status, normal tidal breathing was investigated in an attempt to develop continuous maneuver-free measurements.

APPROACH

Ventilation related and pulsatile impedance changes were systematically analyzed during normal tidal breathing in 12 cystic fibrosis (CF) patients and 12 lung-healthy controls (HL). Tidal breaths were subdivided into three inspiratory (In1, In2, In3) and three expiratory (Ex1, Ex2, Ex3) sections of the same amplitude of global impedance change. Maximal changes of the ventilation and the pulsatile impedance signal occurring during these sections were determined (▵I _V and ▵I _P). Differences in ▵I _V and ▵I _P among sections were ascertained in relation to the first inspiratory section. In addition, ▵I _V/▵I _P was calculated for each section.

MAIN RESULTS

Medians of changes in ▵I _V were  <0.05% in all sections for both subject groups. Both groups showed a similar pattern of ▵I _P changes during tidal breathing. Changes in ▵I _P first decreased during inspiration (In2), then increased towards the end of inspiration (In3) and reached a maximum at the beginning of expiration (Ex1). During the last two sections of expiration (Ex2, Ex3) ▵I _P changes decreased. The CF patients showed higher variations in ▵I _P changes compared to the controls (CF:  -426.5%, HL:  -158.1%, coefficient of variation). Furthermore, ▵I _V/▵I _P significantly differed between expiratory sections for the CF patients (Ex1-Ex2, p  <  0.01; Ex1-Ex3, p  <  0.001; Ex2-Ex3, p  <  0.05), but not for the controls. No significant differences in ▵I _V/▵I _P between inspiratory sections were determined for both groups.

SIGNIFICANCE

Differences in ▵I _P changes and in ▵I _V/▵I _P between both subject groups were speculated to be caused by higher breathing efforts of the CF patients due to airway obstruction leading to higher intrathoracic pressures, and thus to greater changes in lung perfusion.

Electrical impedance tomography

Continuous assessment of respiratory status is one of the cornerstones of modern intensive care unit (ICU) monitoring systems. Electrical impedance tomography (EIT), although with some constraints, may play the lead as a new diagnostic and guiding tool for an adequate optimization of mechanical ventilation in critically ill patients. EIT may assist in defining mechanical ventilation settings, assess distribution of tidal volume and of end-expiratory lung volume (EELV) and contribute to titrate positive end-expiratory pressure (PEEP)/tidal volume combinations. It may also quantify gains (recruitment) and losses (overdistention or derecruitment), granting a more realistic evaluation of different ventilator modes or recruitment maneuvers, and helping in the identification of responders and non-responders to such maneuvers. Moreover, EIT also contributes to the management of life-threatening lung diseases such as pneumothorax, and aids in guiding fluid management in the critical care setting. Lastly, assessment of cardiac function and lung perfusion through electrical impedance is on the way.

Spontaneous breathing trials after prolonged mechanical ventilation monitored by electrical impedance tomography: an observational study

BACKGROUND

The study objective was to examine the correlation between regional ventilation distribution measured with electrical impedance tomography (EIT) and weaning outcomes during spontaneous breathing trial (SBT).

METHODS

Fifteen patients received 100% automatic tube compensation (ATC) during the first and 70% during the second hour. Another 15 patients received external continuous positive airway pressure (CPAP) of 5 and 7.5 cmH₂ O during the first and second hours, respectively. Regional ventilation distributions were monitored with EIT.

RESULTS

Tidal volume and tidal variation of impedance correlated significantly during assist-control ventilation and ATC in all patients (r² = 0.80 ± 0.18, P < 0.001). Higher support levels resulted in similar ventilation distribution and tidal volume, but higher end-expiratory lung impedance (EELI) (P < 0.05). Analysis of regional intratidal gas distribution revealed a redistribution of ventilation towards dorsal regions with lower support level in 13 of 30 patients. These patients had a higher weaning success rate (only 1 of 13 patients failed). Eight of 17 other patient failed (P < 0.05). The number of SBT days needed for weaning was significantly lower in the former group of 13 patients (13.1 ± 4.0 vs. 20.9 ± 11.2 days, P < 0.05).

CONCLUSIONS

Regional ventilation distribution patterns during inspiration were associated with weaning outcomes, and they may be used to predict the success of extubation.

Assessing Respiratory System Mechanical Function

The main goals of assessing respiratory system mechanical function are to evaluate the lung function through a variety of methods and to detect early signs of abnormalities that could affect the patient's outcomes. In ventilated patients, it has become increasingly important to recognize whether respiratory function has improved or deteriorated, whether the ventilator settings match the patient's demand, and whether the selection of ventilator parameters follows a lung-protective strategy. Ventilator graphics, esophageal pressure, intra-abdominal pressure, and electric impedance tomography are some of the best-known monitoring tools to obtain measurements and adequately evaluate the respiratory system mechanical function.

Trends in mechanical ventilation: are we ventilating our patients in the best possible way?

This review addresses how the combination of physiology, medicine and engineering principles contributed to the development and advancement of mechanical ventilation, emphasising the most urgent needs for improvement and the most promising directions of future development. Several aspects of mechanical ventilation are introduced, highlighting on one side the importance of interdisciplinary research for further development and, on the other, the importance of training physicians sufficiently on the technological aspects of modern devices to exploit properly the great complexity and potentials of this treatment.

EDUCATIONAL AIMS

To learn how mechanical ventilation developed in recent decades and to provide a better understanding of the actual technology and practice.To learn how and why interdisciplinary research and competences are necessary for providing the best ventilation treatment to patients.To understand which are the most relevant technical limitations in modern mechanical ventilators that can affect their performance in delivery of the treatment.To better understand and classify ventilation modes.To learn the classification, benefits, drawbacks and future perspectives of automatic ventilation tailoring algorithms.

Lobe based image reconstruction in Electrical Impedance Tomography

PURPOSE

Electrical Impedance Tomography (EIT) is an imaging modality used to generate two-dimensional cross-sectional images representing impedance change in the thorax. The impedance of lung tissue changes with change in air content of the lungs; hence, EIT can be used to examine regional lung ventilation in patients with abnormal lungs. In lung EIT, electrodes are attached around the circumference of the thorax to inject small alternating currents and measure resulting voltages. In contrast to X-ray computed tomography (CT), EIT images do not depict a thorax slice of well defined thickness, but instead visualize a lens-shaped region around the electrode plane, which results from diffuse current propagation in the thorax. Usually, this is considered a drawback, since image interpretation is impeded if 'off-plane' conductivity changes are projected onto the reconstructed two-dimensional image. In this paper we describe an approach that takes advantage of current propagation below and above the electrode plane. The approach enables estimation of the individual conductivity change in each lung lobe from boundary voltage measurements. This could be used to monitor disease progression in patients with obstructive lung diseases, such as chronic obstructive pulmonary disease (COPD) or cystic fibrosis (CF) and to obtain a more comprehensive insight into the pathophysiology of the lung.

METHODS

Electrode voltages resulting from different conductivities in each lung lobe were simulated utilizing a realistic 3D finite element model (FEM) of the human thorax and the lungs. Overall 200 different patterns of conductivity change were simulated. A 'lobe reconstruction' algorithm was developed, applying patient-specific anatomical information in the reconstruction process. A standard EIT image reconstruction algorithm and the proposed 'lobe reconstruction' algorithm were used to estimate conductivity change in the lobes. The agreement between simulated and reconstructed conductivity change in particular lobes were compared using Bland-Altman plots, correlation plots and linear regression. To test the applicability of the approach in a realistic scenario, EIT measurements of a patient suffering from cystic fibrosis (CF) were carried out.

RESULTS

Conductivity changes in each lobe generate specific patterns of voltage change. These can be used to estimate the conductivity change in lobes from measured boundary voltage. The correlation coefficient between simulated and reconstructed conductivity change in particular lobes is r > 0.89 for all lobes. Unknown position of the electrode plane leads to over- or underestimation of reconstructed conductivity change. Slight mismatches (± 5% of the forward model height) between the actual position of the electrode plane and the position used in the reconstruction model lead to regression coefficients of 0.7 to 1.3 between simulated and reconstructed conductivity change in the lobes.

CONCLUSION

The presented approach enhances common reconstruction methods by providing information about anatomically assignable units and thus facilitates image interpretation, since impedance change and thus ventilation of each lobe is directly determined in the reconstructions.

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 (ΔI_FEV1) and the forced vital capacity (ΔI_FVC) were determined. Regional airway obstruction and ventilation inhomogeneity were assessed by the frequency distribution of these ratios (ΔI_FEV1/ΔI_FVC) and an inhomogeneity index (GI_TI). The mean of the frequency distribution of ΔI_FEV1/ΔI_FVC and the GI_TI in both thorax planes were significantly different between CF patients and controls (p<0.001). CF patients exhibited a significantly lower mean of ΔI_FEV1/ΔI_FVC 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.