Systemic Sclerosis (SSc) is an autoimmune disease characterized by a triad of inflammation, vasculopathy, and fibrosis of the skin and internal organs such as gastrointestinal tract, heart, lungs, and kidneys. SSc can lead to premature death especially when there is cardiopulmonary involvement. At early stages, SSc is characterized by an alteration of blood vessel network and hypoxia in the fingertip. Imaging these parameters could lead to early diagnosis of SSc patients. In this study, we investigated the feasibility to detect and diagnose SSc by imaging the oxygen saturation in the nail-bed using photoacoustics (PA) and estimating skin thickening using high-frequency ultrasound (HFUS). Thirty-one subjects (adult man and women) participated in this study: 12 patients with systemic sclerosis, 5 patients with early systemic sclerosis, 5 subjects with primary Raynaud’s phenomenon, and 9 healthy volunteers. The measurements showed that both the nail bed oxygen saturation (77.9% ±10.5 vs. 94.8% ±2.8, p < 0.0001) and the skin thickness (0.51 ±0.17 mm vs. 0.31 ±0.06 mm, p<0.005) of patients with SSc was significantly different compared to healthy volunteers. Most importantly the measurements showed a significant difference between early SSc and primary Raynaud’s phenomenon for both oxygen saturation (80.8 ± 8.1% vs. 93.9 ± 1.1%) and skin thickness (0.48 ± 0.06 mm vs. 0.27 ± 0.01 mm). The PA and HFUS data was supported by conventional capillaroscopy imaging performed on all participants. This pilot study demonstrates the possibility to use photoacoustics and high-frequency ultrasound as a diagnostic tool for early detection of systemic sclerosis.
Fusion-based ultrasound (US)-guided biopsy in a breast is challenging due to the high deformability of the tissue combined with the fact that the breast is usually differently deformed in CT, MR, and US acquisition which makes registration difficult. With this phantom study, we demonstrate the feasibility of a fusion-based ultrasound-guided method for breast biopsy. 3D US and 3D CT data were acquired using dedicated imaging setups of a breast phantom freely hanging in prone position with lesions. The 3D breast CT set up was provided by Koning (Koning Corp., West Henrietta, NY). For US imaging, a dedicated breast scanning set up was developed consisting of a cone-shaped revolving water tank with a 152- mm-sized US transducer mounted in its wall and an aperture for needle insertion. With this setup, volumetric breast US data (0.5×0.5×0.5 mm3 voxel size) can be collected and reconstructed within 3 minutes. The position of the lesion as detected with breast CT was localized in the US data by rigid registration. After lesion localization, the tank rotates the transducer until the lesion is in the US plane. Since the lesion was visible on ultrasound, the performance of the registration was validated. To facilitate guided biopsy, the lesion motion, induced by needle insertion, is estimated using cross-correlation-based speckle tracking and the tracked lesion visualized in the US image at an update frequency of 10 Hz. Thus, in conclusion a fusion-based ultrasound-guided method was introduced which enables ultrasound-guided biopsy in breast that is applicable also for ultrasound occult lesions.
KEYWORDS: Transducers, Image quality, Ultrasonography, Data acquisition, 3D image reconstruction, 3D acquisition, Signal to noise ratio, Visualization, 3D image processing, Breast
Collecting high quality volumetric ultrasound (US) data using freehand scanning is challenging. The quality of the final 3DUS image is highly related to the applied scanning protocol and the subsequently used reconstruction method. The protocol should ensure the sonographer collects sufficient data of satisfactory quality for an accurate reconstruction.
In this study we developed a real-time reconstruction method that provides visual feedback during scanning. The feedback indicates the areas, of which the sonographer should collect more data. The method was tested by acquiring US data of a breast phantom in a setup mimicking freehand scanning which consisted of a linear transducer mounted in a translation stage that also allowed rotation.
To reconstruct the volume in real-time on a target grid of 0.5x0.5x0.5mm, we applied a simplified Voxel Nearest Neighbor (VNN) method, i.e., only the closest to B-mode plane voxels were updated. Furthermore, voxels were updated only when their projection on the B-mode plane was closer to the transducer surface than in the previous scan planes. Interpolation was performed within the acquired volume to fill in the holes where sufficient data were available. Sub-volumes with insufficient data were visualized in the reconstructed volume (update rate 50 Hz). This visual feedback can guide the sonographer during freehand scanning to improve the quality of the reconstructed 3DUS images. Cross-sections of the reconstructed data were compared to the independently acquired B-mode images and confirmed that our real-time method of low computational complexity provided accurate volumetric ultrasound images.
Worldwide, 99% of all maternal deaths occur in low-resource countries. Ultrasound imaging can be used to detect maternal risk factors, but requires a well-trained sonographer to obtain the biometric parameters of the fetus. One of the most important biometric parameters is the fetal Head Circumference (HC). The HC can be used to estimate the Gestational Age (GA) and assess the growth of the fetus. In this paper we propose a method to estimate the fetal HC with the use of the Obstetric Sweep Protocol (OSP). With the OSP the abdomen of pregnant women is imaged with the use of sweeps. These sweeps can be taught to somebody without any prior knowledge of ultrasound within a day. Both the OSP and the standard two-dimensional ultrasound image for HC assessment were acquired by an experienced gynecologist from fifty pregnant women in St. Luke’s Hospital in Wolisso, Ethiopia. The reference HC from the standard two-dimensional ultrasound image was compared to both the manually measured HC and the automatically measured HC from the OSP data. The median difference between the estimated GA from the manual measured HC using the OSP and the reference standard was -1.1 days (Median Absolute Deviation (MAD) 7.7 days). The median difference between the estimated GA from the automatically measured HC using the OSP and the reference standard was -6.2 days (MAD 8.6 days). Therefore, it can be concluded that it is possible to estimate the fetal GA with simple obstetric sweeps with a deviation of only one week.
Automated segmentation of 3D echocardiographic images in patients with congenital heart disease is challenging, because the boundary between blood and cardiac tissue is poorly defined in some regions. Cardiologists mentally incorporate movement of the heart, using temporal coherence of structures to resolve ambiguities. Therefore, we investigated the merit of temporal cross-correlation for automated segmentation over the entire cardiac cycle. Optimal settings for maximum cross-correlation (MCC) calculation, based on a 3D cross-correlation based displacement estimation algorithm, were determined to obtain the best contrast between blood and myocardial tissue over the entire cardiac cycle. Resulting envelope-based as well as RF-based MCC values were used as additional external force in a deformable model approach, to segment the left-ventricular cavity in entire systolic phase. MCC values were tested against, and combined with, adaptive filtered, demodulated RF-data. Segmentation results were compared with manually segmented volumes using a 3D Dice Similarity Index (3DSI). Results in 3D pediatric echocardiographic images sequences (n = 4) demonstrate that incorporation of temporal information improves segmentation. The use of MCC values, either alone or in combination with adaptive filtered, demodulated RF-data, resulted in an increase of the 3DSI in 75% of the cases (average 3DSI increase: 0.71 to 0.82). Results might be further improved by optimizing MCC-contrast locally, in regions with low blood-tissue contrast. Reducing underestimation of the endocardial volume due to MCC processing scheme (choice of window size) and consequential border-misalignment, could also lead to more accurate segmentations. Furthermore, increasing the frame rate will also increase MCC-contrast and thus improve segmentation.
With ultrasound imaging, the motion and deformation of tissue can be measured. Tissue can be deformed by applying a
force on it and the resulting deformation is a function of its mechanical properties. Quantification of this resulting tissue
deformation to assess the mechanical properties of tissue is called elastography. If the tissue under interrogation is
actively deforming, the deformation is directly related to its function and quantification of this deformation is normally
referred as ‘strain imaging’. Elastography can be used for atherosclerotic plaques characterization, while the contractility
of the heart or skeletal muscles can be assessed with strain imaging.
We developed radio frequency (RF) based ultrasound methods to assess the deformation at higher resolution and with
higher accuracy than commercial methods using conventional image data (Tissue Doppler Imaging and 2D speckle
tracking methods). However, the improvement in accuracy is mainly achieved when measuring strain along the
ultrasound beam direction, so 1D. We further extended this method to multiple directions and further improved precision
by using compounding of data acquired at multiple beam steered angles.
In arteries, the presence of vulnerable plaques may lead to acute events like stroke and myocardial infarction.
Consequently, timely detection of these plaques is of great diagnostic value. Non-invasive ultrasound strain
compounding is currently being evaluated as a diagnostic tool to identify the vulnerability of plaques. In the heart, we
determined the strain locally and at high resolution resulting in a local assessment in contrary to conventional global
functional parameters like cardiac output or shortening fraction.
The feasibility of echographic imaging of the tissues in healthy lip and in reconstructed cleft lip and estimating the dimensions and the normalized echo level of these tissues is investigated. Echographic images of the upper lip were made with commercial medical ultrasound equipment, using a linear array transducer (7-11 MHz bandwidth) and a non-contact gel coupling. Tissue dimensions were measured by means of software calipers. Echo levels were calibrated and corrected for beam characteristics, gel path and tissue attenuation by using a tissue-mimicking phantom. At central position of philtrum, mean thickness (and standard deviation) of lip loose connective tissue layer, orbicularis oris muscle and dense connective layer was 4.0 (sd 0.1) mm, 2.3 (sd 0.7) mm, 2.2 (sd 0.7) mm, respectively, in healthy lip at rest. Mean (sd) echo level of muscle and dense connective tissue layer with respect to echo level of lip loose connective tissue layer was in relaxed condition: - 19.3 (sd 0.6) dB and - 10.7 (sd 4.0) dB, respectively. Echo level of loose connective tissue layer was +25.6 (sd 4.2) dB relative to phantom echo level obtained in the focus of the transducer. Color mode echo images were calculated, after adaptive filtering of the images, which show the tissues in separate colors and highlight the details of healthy lip and reconstructed cleft lip. Quantitative assessment of thickness and echo level of various lip tissues is feasible after proper calibration of the echographic equipment. Diagnostic potentials of the developed quantitative echographic techniques for non-invasive evaluation of the outcome of cleft lip reconstruction are promising.
Segmentation of the heart muscle in 3D echocardiographic images provides a tool for visualization of cardiac anatomy and assessment of heart function, and serves as an important pre-processing step for cardiac strain imaging. By incorporating spatial and temporal information of 3D ultrasound image sequences (4D), a fully automated method using image statistics was developed to perform 3D segmentation of the heart muscle. 3D rf-data were acquired with a Philips SONOS 7500 live 3D ultrasound system, and an X4 matrix array transducer (2-4 MHz). Left ventricular images of five healthy children were taken in transthoracial short/long axis view. As a first step, image statistics of blood and heart muscle were investigated. Next, based on these statistics, an adaptive mean squares filter was selected and applied to the images. Window size was related to speckle size (5x2 speckles). The degree of adaptive filtering was automatically steered by the local homogeneity of tissue. As a result, discrimination of heart muscle and blood was optimized, while sharpness of edges was preserved. After this pre-processing stage, homomorphic filtering and automatic thresholding were performed to obtain the inner borders of the heart muscle. Finally, a deformable contour algorithm was used to yield a closed contour of the left ventricular cavity in each elevational plane. Each contour was optimized using contours of the surrounding planes (spatial and temporal) as limiting condition to ensure spatial and temporal continuity.
Better segmentation of the ventricle was obtained using 4D information than using information of each plane separately.
Segmentation of deformable structures remains a challenging task in ultrasound imaging especially in low signal-to-noise ratio applications. In this paper a fully automatic method, dedicated to the luminal contour segmentation in intracoronary ultrasound imaging is introduced. The method is based on an active contour with a priori properties that evolves according to the statistics of the ultrasound texture brightness, determined as being mainly Rayleigh distributed. However, contrary to classical snake-based algorithms, the presented technique neither requires from the user the pre-selection of a region of interest tight around the boundary, nor parameter tuning. This fully automatic character is achieved by an initial contour that is not set, but estimated and thus adapted to each image. Its estimation combines two statistical criteria extracted from the a posteriori probability, function of the contour position. These criteria are the location of the function maximum (or maximum a posteriori estimator) and the first zero-crossing of the function derivative. Then starting form the initial contour, a region of interest is automatically selected and the process iterated until the contour evolution can be ignored. In vivo coronary images from 15 patients, acquired with a 20 MHz central frequency Jomed Invision ultrasound scanner were segmented with the developed method. Automatic contours were compared to those manually drawn by two physician in terms of mean absolute difference. Results demonstrate that the error between automatic contours and the average of manual ones (0.099±0.032mm) and the inter-expert error (0.097±0.027mm) are similar and of small amplitude.
KEYWORDS: Raman spectroscopy, Intravascular ultrasound, Near infrared, Elastography, Tissues, In vitro testing, Ultrasonography, Arteries, In vivo imaging, Spectroscopy
The composition and morphology of the atherosclerotic lesion are considered to be important determinants of acute coronary ischemic syndromes. We investigated the potentials of a combination of intravascular ultrasound (IVUS) elastography and intravascular Near Infrared Raman (NIR) spectroscopy, to assess the physical and chemical composition of the vessel wall and plaque. Intact human coronary arteries were mounted in an in vitro pressurized perfusion setup and investigated with a 20 MHz VisionsR IVUS catheter. At selected cross- sections, two echo-frames were acquired at intraluminal pressures of 80 and 100 mmHg to strain the tissue in order to obtain elastograms. Next, Raman spectra were obtained during 30 seconds at 4 angles (0, 90, 180 and 270 degrees) using a sideways viewing probe. Spectra were modeled to obtain quantitative chemical information, while leaving the specimens intact. Calcified areas were identifiable on the echograms, elastograms and Raman spectra. A combination of geometric information provided by the echogram, chemical information as obtained with Raman spectroscopy, and high stress regions determined by the elastogram, may prove to be a valuable tool to identify plaque vulnerability.
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