Ultrasonic Imaging最新文献

This work measures temporal signal-to-noise ratio (SNR) thresholds that indicate when random noise during ultrasound scanning becomes imperceptible to expert human observers. Visible noise compromises image quality and can potentially lead to non-diagnostic scans. Noise can arise from both stable acoustic sources (clutter) or randomly varying electronic sources (temporal noise). Extensive engineering effort has focused on decreasing noise in both of these categories. In this work, an observer study with five practicing sonographers was performed to assess sonographer sensitivity to temporal noise in ultrasound cine clips. Understanding the conditions where temporal noise is no longer visible during ultrasound imaging can inform engineering efforts seeking to minimize the impact this noise has on image quality. The sonographers were presented with paired temporal noise-free and noise-added simulated speckle cine clips and asked to select the noise-added clips. The degree of motion in the imaging target was found to have a significant effect on the SNR levels where noise was perceived, while changing imaging frequency had little impact. At realistic in vivo motion levels, temporal noise was not perceived in cine clips at and above 28 dB SNR. In a case study presented here, the potential of adaptive intensity adjustment based on this noise perception threshold is validated in a fetal imaging scenario. This study demonstrates how noise perception thresholds can be applied to help design or tune ultrasound systems for different imaging tasks and noise conditions.

Two-dimensional ultrasound transducers enable the acquisition of fully volumetric data that have been demonstrated to provide greater diagnostic information in the clinical setting and are a critical tool for emerging ultrasound methods, such as super-resolution and functional imaging. This technology, however, is not without its limitations. Due to increased fabrication complexity, some matrix probes with disjoint piezoelectric panels may require initial calibration. In this manuscript, two methods for calibrating the element positions of the Vermon 1024-channel 8 MHz matrix transducer are detailed. This calibration is a necessary step for acquiring high resolution B-mode images while minimizing transducer-based image degradation. This calibration is also necessary for eliminating vessel-doubling artifacts in super-resolution images and increasing the overall signal-to-noise ratio (SNR) of the image. Here, we show that the shape of the point spread function (PSF) can be significantly improved and PSF-doubling artifacts can be reduced by up to 10 dB via this simple calibration procedure.

To establish a predictive model incorporating conventional ultrasound, strain elastography and clinicopathological features for Ki-67 expression in small breast cancer (SBC) which defined as maximum diameter less than2 cm. In this retrospective study, 165 SBC patients from our hospital were allocated to a high Ki-67 group (n = 104) and a low Ki-67 group (n = 61). Multivariate regression analysis was performed to identify independent indicators for developing predictive models. The area under the receiver operating characteristic (AUC) curve was also determined to establish the diagnostic performance of different predictive models. The corresponding sensitivities and specificities of different models at the cutoff value were compared. Conventional ultrasound parameters (spiculated margin, absence of posterior shadowing and Adler grade 2-3), strain elastic scores and clinicopathological information (HER2 positive) were significantly correlated with high expression of Ki-67 in SBC (all p < .05). Model 2, which incorporated conventional ultrasound features and strain elastic scores, yielded good diagnostic performance (AUC = 0.774) with better sensitivity than model 1, which only incorporated ultrasound characteristics (78.85%vs. 55.77%, p = .000), with specificities of 77.05% and 62.30% (p = .035), respectively. Model 3, which incorporated conventional ultrasound, strain elastography and clinicopathological features, yielded better performance (AUC = 0.853) than model 1 (AUC = 0.694) and model 2 (AUC = 0.774), and the specificity was higher than model 1 (86.89% vs. 77.05%, p = .001). The predictive model combining conventional ultrasound, strain elastic scores and clinicopathological features could improve the predictive performance of Ki-67 expression in SBC.

Vascular diseases may occur in the upper extremities, and the lesions can span the entire length of the blood vessel. One of the most popular methods to identify vascular disorders is ultrasound Doppler imaging. However, traditional two-dimensional (2D) ultrasound Doppler imaging cannot capture the entire length of a long vessel in one image. Medical professionals often have to painstakingly reconstruct three-dimensional (3D) data using 2D ultrasound images to locate the lesions, especially for large blood vessels. 3D ultrasound Doppler imaging can display the morphological structure of blood vessels and the distribution of lesions more directly, providing a more comprehensive view compared to 2D imaging. In this work, we propose a wide-range 3D volumetric ultrasound Doppler imaging system with dual modality, in which a high-definition camera is adopted to automatically track the movement of the ultrasound transducer, simultaneously capturing a corresponding sequence of 2D ultrasound Doppler images. We conducted experiments on human arms using our proposed system and separately with X-ray computerized tomography (X-CT). The comparison results prove the potential value of our proposed system in the diagnosis of arm vascular diseases.

Subharmonic aided pressure estimation (SHAPE) is a technique that utilizes subharmonic signals from microbubble contrast agents for pressure estimation. Validation of the SHAPE technique relies on synchronous measurements of in vivo pressures using contrast microbubbles and a pressure catheter (reference standard). For the guidance and placement of pressure catheter in vivo, iodinated contrast is used with fluoroscopy. Therefore, during data acquisition for validation studies of the SHAPE technique, both contrast microbubbles and iodinated contrast are present simultaneously within the vasculature. This study aims to elucidate the effects of iodinated contrast (Visipaque, GE HealthCare) on subharmonic signal amplitude from contrast microbubbles (Definity, Lantheus Medical Imaging, Inc.). In an acrylic water tank, 0.06 mL of Definity and varied amounts of Visipaque (0.14, 0.43, 0.85, and 1.70 mL) were added to 425 mL of deionized water. Ultrasound scanning was performed with a SonixTablet scanner (BK Medical Systems) using optimized parameters for SHAPE with Definity (f_{transmit/receive} = 3.0/1.5 MHz; chirp down pulse). Subharmonic data was acquired and analyzed at 9 different incident acoustic outputs (n = 3). Results showed an increase in subharmonic signal amplitude from Definity microbubbles in the presence of 0.14 mL Visipaque by 2.8 ± 1.3 dB (p < .001), no change with 0.85 mL Visipaque (0.7 ± 1.2 dB; p = .09) and a decrease in subharmonic amplitude in the presence of 1.70 mL Visipaque by 1.9 ± 0.7 dB (p < .001). While statistically significant effect on subharmonic signal amplitude of Definity microbubbles was noted due to the mixture, the magnitude of the effect was minimal (~2.8 dB) and unlikely to impact in vivo SHAPE measurements.

Henoch-Schönlein purpura nephritis (HSPN) is one of the most common kidney diseases in children. The current diagnosis and classification of HSPN depend on pathological biopsy, which is seriously limited by its invasive and high-risk nature. The aim of the study was to explore the potential of radiomics model for evaluating the histopathological classification of HSPN based on the ultrasound (US) images. A total of 440 patients with Henoch-Schönlein purpura nephritis proved by biopsy were analyzed retrospectively. They were grouped according to two histopathological categories: those without glomerular crescent formation (ISKDC grades I-II) and those with glomerular crescent formation (ISKDC grades III-V). The patients were randomly assigned to either a training cohort (n = 308) or a validation cohort (n = 132) with a ratio of 7:3. The sonologist manually drew the regions of interest (ROI) on the ultrasound images of the right kidney including the cortex and medulla. Then, the ultrasound radiomics features were extracted using the Pyradiomics package. The dimensions of radiomics features were reduced by Spearman correlation coefficients and least absolute shrinkage and selection operator (LASSO) method. Finally, three radiomics models using k-nearest neighbor (KNN), logistic regression (LR), and support vector machine (SVM) were established, respectively. The predictive performance of such classifiers was assessed with receiver operating characteristic (ROC) curve. 105 radiomics features were extracted from derived US images of each patient and 14 features were ultimately selected for the machine learning analysis. Three machine learning models including k-nearest neighbor (KNN), logistic regression (LR), and support vector machine (SVM) were established for HSPN classification. Of the three classifiers, the SVM classifier performed the best in the validation cohort [area under the curve (AUC) =0.870 (95% CI, 0.795-0.944), sensitivity = 0.706, specificity = 0.950]. The US-based radiomics had good predictive value for HSPN classification, which can be served as a noninvasive tool to evaluate the severity of renal pathology and crescentic formation in children with HSPN.