How should we measure left atrium size and function?

Echocardiographic assessment of left atrial size from M-mode or 2D echocardiography measurements has been used in clinical and research studies for years, but its accuracy is now questioned. New techniques, such as 3D and tissue Doppler imaging, assessing velocities, strain and strain rate, provide improved prognostic value in a wide range of diseases. 2D strain imaging using speckle tracking on B-mode images may yield even better, angle-independent, results than tissue Doppler imaging-derived strain echocardiography. Finally, velocity vector imaging is a novel image analysis technique that may be used to quantify left atrial volume.     

Registration of 3D fetal neurosonography and MRI

We propose a method for registration of 3D fetal brain ultrasound with a reconstructed magnetic resonance fetal brain volume. This method, for the first time, allows the alignment of models of the fetal brain built from magnetic resonance images with 3D fetal brain ultrasound, opening possibilities to develop new, prior information based image analysis methods for 3D fetal neurosonography. The reconstructed magnetic resonance volume is first segmented using a probabilistic atlas and a pseudo ultrasound image volume is simulated from the segmentation. This pseudo ultrasound image is then affinely aligned with clinical ultrasound fetal brain volumes using a robust block-matching approach that can deal with intensity artefacts and missing features in the ultrasound images. A qualitative and quantitative evaluation demonstrates good performance of the method for our application, in comparison with other tested approaches. The intensity average of 27 ultrasound images co-aligned with the pseudo ultrasound template shows good correlation with anatomy of the fetal brain as seen in the reconstructed magnetic resonance image.     

CT evaluation of left atrial pulmonary venous anatomy

Multidetector CT (MDCT) visualization of the left atrial pulmonary venous anatomy is becoming increasingly requested prior to radiofrequencey catheter ablation (RFCA) procedures for refractory cardiac arrhythmias. MDCT imaging can define left atrial anatomy including atrial size and venous attachments as well identify complications such as stenoses, dissections or perforations. Proper understanding enables the cardiac imager to be knowledgeable so as to obtain the specific information needed for the interventional cardiologist. This paper reviews the left atrial venous anatomy, the clinical aspects of refractory atrial fibrillation, MDCT imaging protocols, procedural aspects of the ablation, and complications should they arise.     

Integrating uncertainty in deep neural networks for MRI based stroke analysis

At present, the majority of the proposed Deep Learning (DL) methods provide point predictions without quantifying the model's uncertainty. However, a quantification of the reliability of automated image analysis is essential, in particular in medicine when physicians rely on the results for making critical treatment decisions. In this work, we provide an entire framework to diagnose ischemic stroke patients incorporating Bayesian uncertainty into the analysis procedure. We present a Bayesian Convolutional Neural Network (CNN) yielding a probability for a stroke lesion on 2D Magnetic Resonance (MR) images with corresponding uncertainty information about the reliability of the prediction. For patient-level diagnoses, different aggregation methods are proposed and evaluated, which combine the individual image-level predictions. Those methods take advantage of the uncertainty in the image predictions and report model uncertainty at the patient-level. In a cohort of 511 patients, our Bayesian CNN achieved an accuracy of 95.33% at the image-level representing a significant improvement of 2% over a non-Bayesian counterpart. The best patient aggregation method yielded 95.89% of accuracy. Integrating uncertainty information about image predictions in aggregation models resulted in higher uncertainty measures to false patient classifications, which enabled to filter critical patient diagnoses that are supposed to be closer examined by a medical doctor. We therefore recommend using Bayesian approaches not only for improved image-level prediction and uncertainty estimation but also for the detection of uncertain aggregations at the patient-level.     

The impact of electrode area, contact impedance and boundary shape on EIT images

Electrical impedance tomography (EIT) measures the conductivity distribution within an object based on the current applied and voltage measured at surface electrodes. Thus, EIT images are sensitive to electrode properties (i.e. contact impedance, electrode area and boundary shape under the electrode). While some of these electrode properties have been investigated individually, this paper investigates these properties and their interaction using finite element method simulations and the complete electrode model (CEM). The effect of conformal deformations on image reconstruction when using the CEM was of specific interest. Observed artefacts were quantified using a measure that compared an ideal image to the reconstructed image, in this case a no-noise reconstruction that isolated the electrodes' effects. For electrode contact impedance and electrode area, uniform reductions to all electrodes resulted in ringing artefacts in the reconstructed images when the CEM was used, while parameter variations that were not correlated amongst electrodes resulted in artefacts distributed throughout the image. When the boundary shape changed under the electrode, as with non-symmetric conformal deformations, using the CEM resulted in structured distortions within the reconstructed image. Mean electrode contact impedance increases, independent of inter-electrode variation, did not result in artefacts in the reconstructed image.     

From macro-scale to micro-scale computational anatomy: a perspective on the next 20 years

This paper gives our perspective on the next two decades of computational anatomy, which has made great strides in the recognition and understanding of human anatomy from conventional clinical images. The results from this field are now used in a variety of medical applications, including quantitative analysis of organ shapes, interventional assistance, surgical navigation, and population analysis. Several anatomical models have also been used in computational anatomy, and these mainly target millimeter-scale shapes. For example, liver-shape models are almost completely modeled at the millimeter scale, and shape variations are described at such scales. Most clinical 3D scanning devices have had just under 1 or 0.5 mm per voxel resolution for over 25 years, and this resolution has not changed drastically in that time. Although Z-axis (head-to-tail direction) resolution has been drastically improved by the introduction of multi-detector CT scanning devices, in-plane resolutions have not changed very much either. When we look at human anatomy, we can see different anatomical structures at different scales. For example, pulmonary blood vessels and lung lobes can be observed in millimeter-scale images. If we take 10-µm-scale images of a lung specimen, the alveoli and bronchiole regions can be located in them. Most work in millimeter-scale computational anatomy has been done by the medical-image analysis community. In the next two decades, we encourage our community to focus on micro-scale computational anatomy. In this perspective paper, we briefly review the achievements of computational anatomy and its impacts on clinical applications; furthermore, we show several possibilities from the viewpoint of microscopic computational anatomy by discussing experimental results from our recent research activities.     

Susceptibility artefact correction using dynamic graph cuts: Application to neurosurgery

Echo Planar Imaging (EPI) is routinely used in diffusion and functional MR imaging due to its rapid acquisition time. However, the long readout period makes it prone to susceptibility artefacts which results in geometric and intensity distortions of the acquired image. The use of these distorted images for neuronavigation hampers the effectiveness of image-guided surgery systems as critical white matter tracts and functionally eloquent brain areas cannot be accurately localised. In this paper, we present a novel method for correction of distortions arising from susceptibility artefacts in EPI images. The proposed method combines fieldmap and image registration based correction techniques in a unified framework. A phase unwrapping algorithm is presented that can efficiently compute the B₀ magnetic field inhomogeneity map as well as the uncertainty associated with the estimated solution through the use of dynamic graph cuts. This information is fed to a subsequent image registration step to further refine the results in areas with high uncertainty. This work has been integrated into the surgical workflow at the National Hospital for Neurology and Neurosurgery and its effectiveness in correcting for geometric distortions due to susceptibility artefacts is demonstrated on EPI images acquired with an interventional MRI scanner during neurosurgery.     

Spatial normalization of lesioned HMPAO-SPECT images

We investigated the effect of nonlinear alignment on SPECT images with lesions. Linear alignment produces reliable results but the introduction of nonlinear methods can improve matching by accounting for global brain shape. We examined the hypothesis that nonlinear alignment can introduce unwanted image distortions when lesions are present. We set out to quantify possible distortions by constructing artificial lesions in order to obtain images with controllable characteristics. We examined the use of basis functions (in SPM96 and SPM99) and other nonlinear models (in AIR3.08) designed to achieve optimum alignment between image and template. We found that the use of models with high degrees of nonlinearity will result in unwanted deformations and that the safest way to align images with lesions is to use 12-point linear affine transformations. Masking was examined as a remedy to distortions caused by nonlinear methodologies and produced significantly improved results.     

A three-dimensional,anatomically detailed foot model: a foundation for a finite element simulation and means of quantifying foot-bone position

We generated an anatomically detailed, three-dimensional (3-D) reconstruction of a human foot from 286 computerized topographic (CT) images. For each bone, 2-D cross-sectional data were obtained and aligned to form a stacked image model. We calculated the inertial matrix of each bone from the stacked image model and used it to determine the principal axes. Relative angles between the principal axes of the bones were employed to describe the shape of the foot, i.e., the relationships between the bones of the foot. A 3-D surface model was generated from the stacked image models and a detailed 3-D mesh for each bone was created. Additionally, the representative geometry of the plantar soft tissue was obtained from the CT scans, while the geometries of the cartilage between bones were obtained from the 3-D surface bone models. This model served dual purposes: it formed the anatomical foundation for a future finite element model of the human foot and we used it to objectively quantify foot shape using the relationships between the principal axes of the foot bones.     

Data compression of X-ray cardio-angiographic image series

Medical x-ray images are increasingly stored and transmitted in a digital format. To reduce the required storage space and transmission bandwidth, data compression can be applied. In this paper we describe a new method for data compression of cardio-angiographie x-ray image series. The method is based on so-called overlappedtransform coding. A comparison with the well-known block-based transform-coding methods JPEG and MPEG is presented. We found that overlapped-transform coding does not introduce any blocking artefacts, in contrast to block-based transform coding, which introduces clearly visible blocking artefacts at compression ratios above 8. Clinical evaluations of the new method have pointed out that the image quality obtained at a compression ratio of 12 is adequate for diagnostic applications.     

In vivo quantification of accumulating abdominal fluid using an electrical impedance tomography hemiarray

A new method to image and quantify intra-abdominal haemorrhage using electrical impedance tomography (EIT) was tested in vivo. Supine peritoneal dialysis patients were monitored using an 8-electrode hemiarray placed on the anterior abdomen. EIT measurements were recorded using the EPack II data acquisition system before, during, and after the administration of dialysate. The amount of dialysate infused was recorded synchronous with EIT measurements and used as a control. Tomographic images of impedance change were reconstructed using a weighted, sensitivity-based method and then post-processed to obtain a quantitative estimate of the total dialysate volume added and the rate of dialysate administration. Our preliminary study included two subjects, one male and one female, each of whom participated for two sessions spaced about 6 months apart. Data collected from these sessions indicated that with an in vivo SNR of about 35 dB the EPack II can detect accumulations larger than about 100 ml, with a quantification uncertainty of about 50 ml. The rate of accumulation was determined in less than 2 min. This method shows promise for automated detection of other pathologies, eg ascites, and is adaptable to detecting conductive accumulations in other anatomy.     

Statistical shape analysis of the left atrial appendage predicts stroke in atrial fibrillation

The shape of the left atrium (LA) and left atrial appendage (LAA) have been shown to predict stroke in patients with atrial fibrillation (AF). Prior studies rely on qualitative assessment of shape, which limits reproducibility and clinical utility. Statistical shape analysis (SSA) allows for quantitative assessment of shape. We use this method to assess the shape of the LA and LAA and predict stroke in patients with AF. From a database of AF patients who had previously undergone MRI of the LA, we identified 43 patients with AF who subsequently had an ischemic stroke. We also identified a cohort of 201 controls with AF who did not have a stroke after the MRI. We performed SSA of the LA and LAA shape to quantify the shape of these structures. We found three of the candidate LAA shape parameters to be predictive of stroke, while none of the LA shape parameters predicted stroke. When the three predictive LAA shape parameters were added to a logistic regression model that included the CHA₂DS₂-VASc score, the area under the ROC curve increased from 0.640 to 0.778 (p?=?.003). The shape of the LA and LAA can be assessed quantitatively using SSA. LAA shape predicts stroke in AF patients, while LA shape does not. Additionally, LAA shape predicts stroke independent of CHA₂DS₂-VASc score. SSA for assessment of LAA shape may improve stroke risk stratification and clinical decision making for AF patients.

     

Generating accurate finite element meshes for the forward model of the human head in EIT

The use of realistic anatomy in the model used for image reconstruction in EIT of brain function appears to confer significant improvements compared to geometric shapes such as a sphere. Accurate model geometry may be achieved by numerical models based on magnetic resonance images (MRIs) of the head, and this group has elected to use finite element meshing (FEM) as it enables detailed internal anatomy to be modelled and has the capability to incorporate information about tissue anisotropy. In this paper a method for generating accurate FEMs of the human head is presented where MRI images are manually segmented using custom adaptation of industry standard commercial design software packages. This is illustrated with example surface models and meshes from adult epilepsy patients, a neonatal baby and a phantom latex tank incorporating a real skull. Mesh quality is assessed in terms of element stretch and hence distortion.     

A three-dimensional finite element model of human atrial anatomy: New methods for cubic Hermite meshes with extraordinary vertices

High-order cubic Hermite finite elements have been valuable in modeling cardiac geometry, fiber orientations, biomechanics, and electrophysiology, but their use in solving three-dimensional problems has been limited to ventricular models with simple topologies. Here, we utilized a subdivision surface scheme and derived a generalization of the “local-to-global” derivative mapping scheme of cubic Hermite finite elements to construct bicubic and tricubic Hermite models of the human atria with extraordinary vertices from computed tomography images of a patient with atrial fibrillation. To an accuracy of 0.6 mm, we were able to capture the left atrial geometry with only 142 bicubic Hermite finite elements, and the right atrial geometry with only 90. The left and right atrial bicubic Hermite meshes were G1 continuous everywhere except in the one-neighborhood of extraordinary vertices, where the mean dot products of normals at adjacent elements were 0.928 and 0.925. We also constructed two biatrial tricubic Hermite models and defined fiber orientation fields in agreement with diagrammatic data from the literature using only 42 angle parameters. The meshes all have good quality metrics, uniform element sizes, and elements with aspect ratios near unity, and are shared with the public. These new methods will allow for more compact and efficient patient-specific models of human atrial and whole heart physiology.     

MR susceptibility artefact associated with the use of Barricade coils for treatment of intracranial aneurysms

Magnetic resonance angiography (MRA) is commonly used to follow up patients after endovascular treatment for intracranial aneurysms. Magnetic resonance artefacts from coil constructs may impair image quality and jeopardise the evaluation of the effectiveness of treatment and review of adjacent vasculature. We present here a technical note on the usage of Barricade coils recently introduced at our institution. The MRA artefacts associated with these coils may make it impossible to ascertain aneurysm closure and anatomy. Hence these patients would need to be recalled for digital subtraction angiograms for a complete neuroradiological follow-up.     

Generalized image models and their application as statistical models of images

A generalized image model (GIM) is presented. Images are represented as sets of four-dimensional (4D) sites combining position and intensity information, as well as their associated uncertainty and joint variation. This model seamlessly allows for the representation of both images and statistical models (such as those used for classification of normal/abnormal anatomy and for inter-patient registration), as well as other representations such as landmarks or meshes. A GIM-based registration method aimed at the construction and application of statistical models of images is proposed. A procedure based on the iterative closest point (ICP) algorithm is modified to deal with features other than position and to integrate statistical information. Furthermore, we modify the ICP framework by using a Kalman filter to efficiently compute the transformation. The initialization and update of the statistical model are also described. Preliminary results show the feasibility of the approach and its potentialities.     

Detecting abnormality in optic nerve head images using a feature extraction analysis

Imaging and evaluation of the optic nerve head (ONH) plays an essential part in the detection and clinical management of glaucoma. The morphological characteristics of ONHs vary greatly from person to person and this variability means it is difficult to quantify them in a standardized way. We developed and evaluated a feature extraction approach using shift-invariant wavelet packet and kernel principal component analysis to quantify the shape features in ONH images acquired by scanning laser ophthalmoscopy (Heidelberg Retina Tomograph [HRT]). The methods were developed and tested on 1996 eyes from three different clinical centers. A shape abnormality score (SAS) was developed from extracted features using a Gaussian process to identify glaucomatous abnormality. SAS can be used as a diagnostic index to quantify the overall likelihood of ONH abnormality. Maps showing areas of likely abnormality within the ONH were also derived. Diagnostic performance of the technique, as estimated by ROC analysis, was significantly better than the classification tools currently used in the HRT software – the technique offers the additional advantage of working with all images and is fully automated.OCIS codes: (100.2960) Image analysis, (100.4993) Pattern recognition, Baysian processors, (100.7410) Wavelets, (150.1835) Defect understanding, (170.4470) Ophthalmology, (170.5755) Retina scanning, (170.4580) Optical diagnostics for medicine     

Generation of 3D shape,density, cortical thickness and finite element mesh of proximal femur from a DXA image

Areal bone mineral density (aBMD), as measured by dual-energy X-ray absorptiometry (DXA), predicts hip fracture risk only moderately. Simulation of bone mechanics based on DXA imaging of the proximal femur, may help to improve the prediction accuracy. Therefore, we collected three (1−3) image sets, including CT images and DXA images of 34 proximal cadaver femurs (set 1, including 30 males, 4 females), 35 clinical patient CT images of the hip (set 2, including 27 males, 8 females) and both CT and DXA images of clinical patients (set 3, including 12 female patients). All CT images were segmented manually and landmarks were placed on both femurs and pelvises. Two separate statistical appearance models (SAMs) were built using the CT images of the femurs and pelvises in sets 1 and 2, respectively. The 3D shape of the femur was reconstructed from the DXA image by matching the SAMs with the DXA images. The orientation and modes of variation of the SAMs were adjusted to minimize the sum of the absolute differences between the projection of the SAMs and a DXA image. The mesh quality and the location of the SAMs with respect to the manually placed control points on the DXA image were used as additional constraints. Then, finite element (FE) models were built from the reconstructed shapes. Mean point-to-surface distance between the reconstructed shape and CT image was 1.0 mm for cadaver femurs in set 1 (leave-one-out test) and 1.4 mm for clinical subjects in set 3. The reconstructed volumetric BMD showed a mean absolute difference of 140 and 185 mg/cm³ for set 1 and set 3 respectively. The generation of the SAM and the limitation of using only one 2D image were found to be the most significant sources of errors in the shape reconstruction. The noise in the DXA images had only small effect on the accuracy of the shape reconstruction. DXA-based FE simulation was able to explain 85% of the CT-predicted strength of the femur in stance loading. The present method can be used to accurately reconstruct the 3D shape and internal density of the femur from 2D DXA images. This may help to derive new information from clinical DXA images by producing patient-specific FE models for mechanical simulation of femoral bone mechanics.     

Electroanatomic mapping of the right atrium with a right atrial basket catheter and three-dimensional intracardiac echocardiography

The ablation of arrhythmias progresses towards an approach based upon application of linear lesions between nonconducting anatomic/electrical areas. Hence the identification of detailed anatomy together with electrical behavior becomes increasingly important. This study aims to achieve true electroanatomic mapping by the use of three-dimensional intracardiac imaging of the right atrium combined with use of a right atrial basket to obtain detailed electrical information. We studied nine patients, seven requiring atrial flutter ablation. A 9 Fr, 9 MHZ intracardiac echo catheter was pulled back from SVC to IVC using respiratory and ECG gating. The images, recorded on a Clearview ultrasound machine, were reconstructed using commercially available software. The intracardiac basket was placed into the atrium using the markers and fluoroscopy to allow orientation. Isochronal maps were obtained from the basket in sinus rhythm, pacing from different sites within the atrium and in atrial flutter. Isochronal maps were constructed and superimposed on the ICE image. The maps with pacing were consistent with that which was expected, confirming the validity of this approach. We were able to visualize changes in activation sequence following the placement of bidirectional isthmus block. True electroanatomic mapping is possible by the use of three-dimensional ICE reconstruction of the right atrium with electrical activation obtained from an intracardiac basket. This has significance for anatomically based arrhythmia ablations such as the ablation of atrial flutter, atrial fibrillation, with transcatheter MAZE procedures and pulmonary vein isolation. Further developments in software will allow such maps to be produced simultaneously with greater rapidity.