Functional Validation and Comparison Framework for EIT Lung Imaging

Introduction

Electrical impedance tomography (EIT) is an emerging clinical tool for monitoring ventilation distribution in mechanically ventilated patients, for which many image reconstruction algorithms have been suggested. We propose an experimental framework to assess such algorithms with respect to their ability to correctly represent well-defined physiological changes. We defined a set of clinically relevant ventilation conditions and induced them experimentally in 8 pigs by controlling three ventilator settings (tidal volume, positive end-expiratory pressure and the fraction of inspired oxygen). In this way, large and discrete shifts in global and regional lung air content were elicited.

Methods

We use the framework to compare twelve 2D EIT reconstruction algorithms, including backprojection (the original and still most frequently used algorithm), GREIT (a more recent consensus algorithm for lung imaging), truncated singular value decomposition (TSVD), several variants of the one-step Gauss-Newton approach and two iterative algorithms. We consider the effects of using a 3D finite element model, assuming non-uniform background conductivity, noise modeling, reconstructing for electrode movement, total variation (TV) reconstruction, robust error norms, smoothing priors, and using difference vs. normalized difference data.

Results and Conclusions

Our results indicate that, while variation in appearance of images reconstructed from the same data is not negligible, clinically relevant parameters do not vary considerably among the advanced algorithms. Among the analysed algorithms, several advanced algorithms perform well, while some others are significantly worse. Given its vintage and ad-hoc formulation backprojection works surprisingly well, supporting the validity of previous studies in lung EIT.     

Exploring Variability in CT Characterization of Tumors: A Preliminary Phantom Study

PURPOSE: To explore the effects of computed tomography (CT) slice thickness and reconstruction algorithm on quantification of image features to characterize tumors using a chest phantom. MATERIALS AND METHODS: Twenty-two phantom lesions of known sizes (10 and 20 mm), shapes (spherical, elliptical, lobulated, and spiculated), and densities [-630, -10, and +100 Hounsfield Unit (HU)] were inserted into an anthropomorphic thorax phantom and scanned three times with relocations. The raw data were reconstructed using six imaging settings, i.e., a combination of three slice thicknesses of 1.25, 2.5, and 5 mm and two reconstruction kernels of lung and standard. Lesions were segmented and 14 image features representing lesion size, shape, and texture were calculated. Differences in the measured image features due to slice thickness and reconstruction algorithm were compared using linear regression method by adjusting three confounding variables (size, density, and shape). RESULTS: All 14 features were significantly different between 1.25 and 5 mm slice images. The 1.25 and 2.5 mm slice thicknesses were better than 5 mm for volume, density mean, density SD gray-level co-occurrence matrix (GLCM) energy and homogeneity. As for the reconstruction algorithm, there was no significant difference in uni-dimension, volume, shape index 9, and compactness. Lung reconstruction was better for density mean, whereas standard reconstruction was better for density SD. CONCLUSIONS: CT slice thickness and reconstruction algorithm can significantly affect the quantification of image features. Thinner (1.25 and 2.5 mm) and thicker (5 mm) slice images should not be used interchangeably. Sharper and smoother reconstructions significantly affect the density-based features.     

基于动态聚焦的声聚焦光声内窥成像算法研究

目的 声聚焦光声内窥成像具有成像深度大的优点,是一种非常有前景的功能成像技术,该技术被广泛应用于直肠、食道等内窥成像中。声聚焦光声内窥成像通常采用基于单个聚焦超声传感器的侧向扫描方式,同时采用传统的B扫描方法进行重建,会大大降低图像质量。为了获得高质量的图像,本文提出了几种动态聚焦的声聚焦光声内窥成像算法。方法 本文使用几种动态聚焦算法进行了数值仿真,并搭建系统进行了仿体实验验证,从横向分辨率和信噪比等多方面比较了各算法在动态聚焦中的成像效果。结果 相比B扫描方法,动态聚焦后的图像在离焦区域的横向分辨率与信噪比方面都有提升,仿真模拟中最高可将离焦区域的成像目标分辨率提升约26倍,其信噪比经动态聚焦后最高可提高2.3倍左右,实验中的远距离点目标经动态聚焦重建后分辨率提升3～6倍。结论 整体而言,基于时空响应的算法和合成孔径聚焦重建算法是在实验条件下更为适用的算法。本工作对后续的声聚焦光声内窥成像的设计具有指导意义。     

基于径向基函数神经网络的肺部加权频差电阻抗成像方法

目的 对肺通气过程进行床旁实时连续图像监控，是机械通气患者和临床医生的迫切需求。肺部电阻抗成像（EIT）可反映呼吸引起的胸腔电特性变化分布，在肺通气监测方面具有天然的优势。本文目的在于建立基于径向基函数神经网络（RBFNN）的肺部加权频差电阻抗成像（wfd-EIT）方法，实现对肺通气的高空间分辨率成像。方法 利用肺部wfd-EIT成像方法实时描绘胸腔电导率分布状况，再通过RBFNN将目标区域可视化并精准识别其边界信息。首先通过数值分析模拟，在各个激励频率利用COMSOL与MATLAB软件建立2 028个仿真样本，分为训练样本集和测试样本集，验证所提出成像方法的可行性和有效性。其次，为了验证仿真结果，建立肺部物理模型，选用具有低电导特性的生物组织模拟肺部通气区域，对其进行成像实验，并采用图像相关系数（ICC）和肺区域比（LRR）定量数据衡量成像方法的准确性。结果 wfd-EIT方法可以在任意时刻进行图像重建，并能够准确反映出目标区域的电特性分布；利用基于RBFNN的算法能够增强目标区域的成像精度，ICC可达0.94以上，更好地凸显其边界轮廓信息。结论 通过wfd-EIT成像方法，利用多频阻抗谱同步测量实现目标区域的快速可视化，并结合RBFNN网络逼近任意非线性函数的优点，实现对目标区域电特性变化的精准识别，为下一步进行临床肺通气的EIT图像监测奠定了理论和技术基础。     

Prospective image planning in radiation therapy for optimization of image quality and reduction of patient dose

IntroductionCT simulation data in image-guided radiation therapy (IGRT) provides patient-specific subject contrast. This information can be exploited to establish, a priori, a suitable imaging goal and to select patient-specific imaging acquisition parameters that optimize the similarity between reference and daily set-up images and reduce imaging dose. This study aims to describe and clinically validate a computerized algorithm designed to provide such optimization.Material and methodsAn image planning system (IPS) was developed to assist in planar kV imaging technique selection for radiation therapy. The system's patient-specific image quality and dose reduction capabilities were validated herein. Anthropomorphic phantom and clinical data were acquired. Mutual information (MI) was used to compare simulated and measured images in both phantom and clinical tests. Variations in contrast resolution resulting from imaging panel underexposure, saturation and a contrast plateau were investigated. For evaluation of patient-specific imaging dose reduction, the IPS was used to modify acquisition settings for six patients.ResultsPhantom data confirmed the IPS's predictive capability regarding image contrast. Measured and simulated images showed similar progressions from under-exposure, image quality peak, and loss of contrast due to detector saturation. Clinical data demonstrated that contrast resolution and imaging dose could be prospectively improved without loss of image contrast. The algorithm reduced imaging dose by an average of 47%, and a maximum of 80%.ConclusionsLoss of image contrast resulting from under-exposure or over-exposure, as well as a contrast plateau can be predicted by use of a prospective image planning algorithm. Image acquisition parameters can be predicted that reduce patient dose without loss of useful contrast.     

Evaluation of automatic image quality assessment in chest CT – A human cadaver study

PurposeThe evaluation of clinical image quality (IQ) is important to optimize CT protocols and to keep patient doses as low as reasonably achievable. Considering the significant amount of effort needed for human observer studies, automatic IQ tools are a promising alternative. The purpose of this study was to evaluate automatic IQ assessment in chest CT using Thiel embalmed cadavers.MethodsChest CT’s of Thiel embalmed cadavers were acquired at different exposures. Clinical IQ was determined by performing a visual grading analysis. Physical-technical IQ (noise, contrast-to-noise and contrast-detail) was assessed in a Catphan phantom. Soft and sharp reconstructions were made with filtered back projection and two strengths of iterative reconstruction. In addition to the classical IQ metrics, an automatic algorithm was used to calculate image quality scores (IQs). To be able to compare datasets reconstructed with different kernels, the IQs values were normalized.ResultsGood correlations were found between IQs and the measured physical-technical image quality: noise (ρ = −1.00), contrast-to-noise (ρ = 1.00) and contrast-detail (ρ = 0.96). The correlation coefficients between IQs and the observed clinical image quality of soft and sharp reconstructions were 0.88 and 0.93, respectively.ConclusionsThe automatic scoring algorithm is a promising tool for the evaluation of thoracic CT scans in daily clinical practice. It allows monitoring of the image quality of a chest protocol over time, without human intervention. Different reconstruction kernels can be compared after normalization of the IQs.     

Ventilation distribution in rats: Part 2 -- A comparison of electrical impedance tomography and hyperpolarised helium magnetic resonance imaging

ABSTRACT: BACKGROUND: Hyperpolarised helium MRI (He3 MRI) is a new technique that enables imaging of the air distribution within the lungs. This allows accurate determination of the ventilation distribution in vivo. The technique has the disadvantages of requiring an expensive helium isotope, complex apparatus and moving the patient to a compatible MRI scanner. Electrical impedance tomography (EIT) a non-invasive bedside technique that allows constant monitoring of lung impedance, which is dependent on changes in air space capacity in the lung. We have used He3MRI measurements of ventilation distribution as the gold standard for assessment of EIT. METHODS: Seven rats were ventilated in supine, prone, left and right lateral position with 70% helium/30% oxygen for EIT measurements and pure helium for He3 MRI. The same ventilator and settings were used for both measurements. Image dimensions, geometric centre and global in homogeneity index were calculated. RESULTS: EIT images were smaller and of lower resolution and contained less anatomical detail than those from He3 MRI. However, both methods could measure positional induced changes in lung ventilation, as assessed by the geometric centre. The global in homogeneity index were comparable between the techniques. CONCLUSION: EIT is a suitable technique for monitoring ventilation distribution and inhomgeneity as assessed by comparison with He3 MRI.     

Streptococcus pneumoniae induced c-Jun-N-terminal kinase- and AP-1 -dependent IL-8 release by lung epithelial BEAS-2B cells

Background

Chronic lung diseases are a major issue in public health. A serial pulmonary assessment using imaging techniques free of ionizing radiation and which provides early information on local function impairment would therefore be a considerably important development. Magnetic resonance imaging (MRI) is a powerful tool for the static and dynamic imaging of many organs. Its application in lung imaging however, has been limited due to the low water content of the lung and the artefacts evident at air-tissue interfaces. Many attempts have been made to visualize local ventilation using the inhalation of hyperpolarized gases or gadolinium aerosol responding to MRI. None of these methods are applicable for broad clinical use as they require specific equipment.

Methods

We have shown previously that low-field MRI can be used for static imaging of the lung. Here we show that mathematical processing of data derived from serial MRI scans during the respiratory cycle produces good quality images of local ventilation without any contrast agent. A phantom study and investigations in 85 patients were performed.

Results

The phantom study proved our theoretical considerations. In 99 patient investigations good correlation (r = 0.8; p ≤ 0.001) was seen for pulmonary function tests and MR ventilation measurements. Small ventilation defects were visualized.

Conclusion

With this method, ventilation defects can be diagnosed long before any imaging or pulmonary function test will indicate disease. This surprisingly simple approach could easily be incorporated in clinical routine and may be a breakthrough for lung imaging and functional assessment.     

Electrical Impedance Tomography of Electrolysis

The primary goal of this study is to explore the hypothesis that changes in pH during electrolysis can be detected with Electrical Impedance Tomography (EIT). The study has relevance to real time control of minimally invasive surgery with electrolytic ablation. To investigate the hypothesis, we compare EIT reconstructed images to optical images acquired using pH-sensitive dyes embedded in a physiological saline agar gel phantom treated with electrolysis. We further demonstrate the biological relevance of our work using a bacterial E.Coli model, grown on the phantom. The results demonstrate the ability of EIT to image pH changes in a physiological saline phantom and show that these changes correlate with cell death in the E.coli model. The results are promising, and invite further experimental explorations.     

Efficient automatic noise reduction of electron tomographic reconstructions based on iterative median filtering

A simple, fast and efficient noise-reduction protocol for three-dimensional electron tomographic reconstructions of biological material is presented. The approach is based on iterative application of median filtering and shows promise for automatic noise reduction as a pre-processor for automated data analysis tools which aim at segmentation, feature extraction and pattern recognition. The application of this algorithm produces encouraging results for a wide variety of experimental and synthetic electron tomographic reconstructions.     

Augmenting intraoperative ultrasound with preoperative magnetic resonance planning models for percutaneous renal access

ABSTRACT: BACKGROUND: Ultrasound (US) is a commonly-used intraoperative imaging modality for guiding percutaneous renal access (PRA). However, the anatomy identification and target localization abilities of the US imaging are limited. This paper evaluates the feasibility and efficiency of a proposed image-guided PRA by augmenting the intraoperative US with preoperative magnetic resonance (MR) planning models. METHODS: First, a preoperative surgical planning approach is presented to define an optimal needle trajectory using MR volume data. Then, a MR to US registration is proposed to transfer the preoperative planning into the intraoperative context. The proposed registration makes use of orthogonal US slices to avoid local minima while reduce processing time. During the registration, a respiratory gating method is used to minimize the impact of kidney deformation. By augmenting the intraoperative US with preoperative MR models and a virtual needle, a visual guidance is provided to guarantee the correct execution of the surgical planning. The accuracy, robustness and processing time of the proposed registration were evaluated by four urologists on human data from four volunteers. Furthermore, the PRA experiments were performed by the same four urologists on a kidney phantom. The puncture accuracy in terms of the needle-target distance was measured, while the perceptual quality in using the proposed image guidance was evaluated according to custom scoring method. RESULTS: The mean registration accuracy in terms of the root mean square (RMS) target registration error (TRE) is 3.53mm. The RMA distance from the registered feature points to their average is 0.81mm. The mean operating time of the registration is 6'4". In the phantom evaluation, the mean needle-target distance is 2.08mm for the left lesion and 1.85mm for the right one. The mean duration for all phantom PRA tests was 4'26". According to the custom scoring method, the mean scores of the Intervention Improvement, Workflow Impact, and Clinical Relevance were 4.0, 3.3 and 3.9 respectively. CONCLUSIONS: The presented image guidance is feasible and promising for PRA procedure. With careful setup it can be efficient for overcoming the limitation of current US-guided PRA.     

Virtual patient 3D dose reconstruction using in air EPID measurements and a back-projection algorithm for IMRT and VMAT treatments

PurposeAt our institute, a transit back-projection algorithm is used clinically to reconstruct in vivo patient and in phantom 3D dose distributions using EPID measurements behind a patient or a polystyrene slab phantom, respectively. In this study, an extension to this algorithm is presented whereby in air EPID measurements are used in combination with CT data to reconstruct ‘virtual’ 3D dose distributions. By combining virtual and in vivo patient verification data for the same treatment, patient-related errors can be separated from machine, planning and model errors.Methods and materialsThe virtual back-projection algorithm is described and verified against the transit algorithm with measurements made behind a slab phantom, against dose measurements made with an ionization chamber and with the OCTAVIUS 4D system, as well as against TPS patient data. Virtual and in vivo patient dose verification results are also compared.ResultsVirtual dose reconstructions agree within 1% with ionization chamber measurements. The average γ-pass rate values (3% global dose/3 mm) in the 3D dose comparison with the OCTAVIUS 4D system and the TPS patient data are 98.5 ± 1.9%(1SD) and 97.1 ± 2.9%(1SD), respectively. For virtual patient dose reconstructions, the differences with the TPS in median dose to the PTV remain within 4%.ConclusionsVirtual patient dose reconstruction makes pre-treatment verification based on deviations of DVH parameters feasible and eliminates the need for phantom positioning and re-planning. Virtual patient dose reconstructions have additional value in the inspection of in vivo deviations, particularly in situations where CBCT data is not available (or not conclusive).     

Combination of dual-energy computed tomography and iterative metal artefact reduction to increase general quality of imaging for radiotherapy patients with high dense materials. Phantom study

PurposeTo evaluate the use of pseudo-monoenergetic reconstructions (PMR) from dual-energy computed tomography, combined with the iterative metal artefact reduction (iMAR) method.MethodsPseudo-monoenergetic CT images were obtained using the dual-energy mode on the Siemens Somatom Definition AS scanner. A range of PMR combinations (70–130 keV) were used with and without iMAR. A Virtual Water™ phantom was used for quantitative assessment of error in the presence of high density materials: titanium, alloys 330 and 600. The absolute values of CT number differences (AD) and normalised standard deviations (NSD) were calculated for different phantom positions. Image quality was assessed using an anthropomorphic pelvic phantom with an embedded hip prosthesis. Image quality was scored blindly by five observers.ResultsAD and NSD values revealed differences in CT number errors between tested sets. AD and NSD were reduced in the vicinity of metal for images with iMAR (p < 0.001 for AD/NSD). For ROIs away from metal, with and without iMAR, 70 keV PMR and pCT AD values were lower than for the other reconstructions (p = 0.039). Similarly, iMAR NSD values measured away from metal were lower for 130 keV and 70 keV PMR (p = 0.002). Image quality scores were higher for 70 keV and 130 keV PMR with iMAR (p = 0.034).ConclusionThe use of 70 keV PMR with iMAR allows for significant metal artefact reduction and low CT number errors observed in the vicinity of dense materials. It is therefore an attractive alternative to high keV imaging when imaging patients with metallic implants, especially in the context of radiotherapy planning.     

Mechanical strain promotes osteoblast ECM formation and improves its osteoinductive potential

Background

Hyperpolarised helium MRI (He3 MRI) is a new technique that enables imaging of the air distribution within the lungs. This allows accurate determination of the ventilation distribution in vivo. The technique has the disadvantages of requiring an expensive helium isotope, complex apparatus and moving the patient to a compatible MRI scanner. Electrical impedance tomography (EIT) a non-invasive bedside technique that allows constant monitoring of lung impedance, which is dependent on changes in air space capacity in the lung. We have used He3MRI measurements of ventilation distribution as the gold standard for assessment of EIT.

Methods

Seven rats were ventilated in supine, prone, left and right lateral position with 70% helium/30% oxygen for EIT measurements and pure helium for He3 MRI. The same ventilator and settings were used for both measurements. Image dimensions, geometric centre and global in homogeneity index were calculated.

Results

EIT images were smaller and of lower resolution and contained less anatomical detail than those from He3 MRI. However, both methods could measure positional induced changes in lung ventilation, as assessed by the geometric centre. The global in homogeneity index were comparable between the techniques.

Conclusion

EIT is a suitable technique for monitoring ventilation distribution and inhomgeneity as assessed by comparison with He3 MRI.     

Model-based particle picking for cryo-electron microscopy

We describe an algorithm for finding particle images in cryo-EM micrographs. The algorithm starts from a crude 3D map of the target particle, computed from a relatively small number of manually picked images, and then projects the map in many different directions to give synthetic 2D templates. The templates are clustered and averaged and then cross-correlated with the micrographs. A probabilistic model of the imaging process then scores cross-correlation peaks to produce the final picks. We give quantitative results on two quite different target particles: keyhole limpet hemocyanin and p97 AAA ATPase. On these particles our automatic particle picker shows human performance level, as measured by the Fourier shell correlations of 3D reconstructions.     

An accurate and effective FMM-based approach for freehand 3D ultrasound reconstruction

Freehand three-dimensional ultrasound imaging is a highly attractive research area because it is capable of volumetric visualization and analysis of tissues and organs. The reconstruction algorithm plays a key role to the construction of three-dimensional ultrasound volume data with higher image quality and faster reconstruction speed. However, a systematic approach to such problem is still missing. A new fast marching method (FMM) for three-dimensional ultrasound volume reconstruction using the tracked and hand-held probe is proposed in this paper. Our reconstruction approach consists of two stages: bin-filling stage and hole-filling stage. Each pixel in the B-scan images is traversed and its intensity value is assigned to its nearest voxel in the bin-filling stage. For the efficient and accurate reconstruction, we present a new hole-filling algorithm based on the fast marching method. Our algorithm advances the interpolation boundary along its normal direction and fills the area closest to known voxel points in first, which ensure that the structural details of image can be preserved. Experimental results on both ultrasonic abdominal phantom and in vivo urinary bladder of human subject and comparisons with some popular algorithms are used to demonstrate its improvement in both reconstruction accuracy and efficiency.     

Development of an RSA calibration system with improved accuracy and precision

In this study, a new radiostereometric analysis (RSA) calibration cage was developed with the aim of improving the accuracy and precision of RSA. This development consisted of three steps: a numerical simulation technique was first used to design the new cage; a synthetic imaging method was then implemented to predict the performance of the designed cage before it was actually fabricated; and an experimental phantom test was finally conducted to verify the actual performance of the new cage and compare with two currently widely used cages. Accuracy was calculated as the 95% prediction intervals from regression analyses between the measured and actual displacements, and precision was defined as the standard deviation of repeated measurements. The final experimental phantom tests showed that the accuracy and precision of the new calibration cage were improved by about 40% over an existing biplanar cage and by about 70% compared to a uniplanar cage design. This new cage can be used with any skeletal joints, in either static or kinematic examination, which is helpful for the standardization of the RSA application.     

A Novel Weighted Total Difference Based Image Reconstruction Algorithm for Few-View Computed Tomography

In practical applications of computed tomography (CT) imaging, due to the risk of high radiation dose imposed on the patients, it is desired that high quality CT images can be accurately reconstructed from limited projection data. While with limited projections, the images reconstructed often suffer severe artifacts and the edges of the objects are blurred. In recent years, the compressed sensing based reconstruction algorithm has attracted major attention for CT reconstruction from a limited number of projections. In this paper, to eliminate the streak artifacts and preserve the edge structure information of the object, we present a novel iterative reconstruction algorithm based on weighted total difference (WTD) minimization, and demonstrate the superior performance of this algorithm. The WTD measure enforces both the sparsity and the directional continuity in the gradient domain, while the conventional total difference (TD) measure simply enforces the gradient sparsity horizontally and vertically. To solve our WTD-based few-view CT reconstruction model, we use the soft-threshold filtering approach. Numerical experiments are performed to validate the efficiency and the feasibility of our algorithm. For a typical slice of FORBILD head phantom, using 40 projections in the experiments, our algorithm outperforms the TD-based algorithm with more than 60% gains in terms of the root-mean-square error (RMSE), normalized root mean square distance (NRMSD) and normalized mean absolute distance (NMAD) measures and with more than 10% gains in terms of the peak signal-to-noise ratio (PSNR) measure. While for the experiments of noisy projections, our algorithm outperforms the TD-based algorithm with more than 15% gains in terms of the RMSE, NRMSD and NMAD measures and with more than 4% gains in terms of the PSNR measure. The experimental results indicate that our algorithm achieves better performance in terms of suppressing streak artifacts and preserving the edge structure information of the object.     

A fast bilateral filter with application to artefact reduction

Elastography in medical ultrasound is an imaging technique that displays information about tissue stiffness. However, elastography suffers from artefact noise that may come from two dominant sources: decorrelation error and amplitude modulation error. In order to reduce artefact and improve the quality of ultrasonic elastography, a fast bilateral filter is proposed in this study based on local histogram. The presented filter is derived from a conventional bilateral filter, and a local histogram is introduced to speed up the filter. The proposed algorithm can reduce artefact noise and, at the same time, maintain the tissue structure. Both simulation and phantom testing show that the proposed method can improve the quality of ultrasonic elastography in terms of tissue elastographic signal-to-noise ratio and elastographic contrast-to-noise ratio values.     

Evaluation of Non-Local Means Based Denoising Filters for Diffusion Kurtosis Imaging Using a New Phantom

Image denoising has a profound impact on the precision of estimated parameters in diffusion kurtosis imaging (DKI). This work first proposes an approach to constructing a DKI phantom that can be used to evaluate the performance of denoising algorithms in regard to their abilities of improving the reliability of DKI parameter estimation. The phantom was constructed from a real DKI dataset of a human brain, and the pipeline used to construct the phantom consists of diffusion-weighted (DW) image filtering, diffusion and kurtosis tensor regularization, and DW image reconstruction. The phantom preserves the image structure while minimizing image noise, and thus can be used as ground truth in the evaluation. Second, we used the phantom to evaluate three representative algorithms of non-local means (NLM). Results showed that one scheme of vector-based NLM, which uses DWI data with redundant information acquired at different b-values, produced the most reliable estimation of DKI parameters in terms of Mean Square Error (MSE), Bias and standard deviation (Std). The result of the comparison based on the phantom was consistent with those based on real datasets.