Fully Automatic Three-Dimensional Ultrasound Imaging Based on Conventional B-Scan

Standalone ultrasound-based highly visualized volumetric spine imaging for surgical navigation

Current navigation systems employing intraoperative CT have been applied in spinal interventions for accurate and visualized guidance. The consequential issue of radiation doses and surgical workflow disruption spotlighted ultrasound (US) as an alternative imaging modality. However, the challenge of anatomy interpretation left US-based navigation inadequate in visualization, resulting in the necessity of registration of preoperative images. Here we report a standalone ultrasound image-guided system (SUIGS) leveraging a purpose-made network to automatically extract bone features and reconstruct them into highly visualized volumetric images for spinal navigation. We showed the SUIGS highly visualized the bone markers with an imaging accuracy of 1.19 ± 0.85 mm in scanning tests on human volunteers. Through extensive testing on data from hospitalized patients containing atypical cases (spinal deformity, obesity), we confirmed that SUIGS generalizes across different individuals with a 100% success rate in aligning with preoperative CT. Furthermore, SUIGS yielded comparable results to three-dimensional fluoroscopy guidance in intraoperative intraspinal tumor localization and reduced the procedure to 8 min. This study explored and broadened the clinical application of standalone US navigation by providing intraoperative high-visualized volumetric spinal imaging, which is expected to increase the likelihood of surgeons adopting it in practice to reduce the occurrence of wrong-site surgery.

Autonomous robotic ultrasound scanning system: a key to enhancing image analysis reproducibility and observer consistency in ultrasound imaging

Purpose

This study aims to develop an autonomous robotic ultrasound scanning system (auto-RUSS) pipeline, comparing its reproducibility and observer consistency in image analysis with physicians of varying levels of expertise.

Design/methodology/approach

An auto-RUSS was engineered using a 7-degree-of-freedom robotic arm, with real-time regulation based on force control and ultrasound visual servoing. Two phantoms were employed for the human-machine comparative experiment, involving three groups: auto-RUSS, non-expert (4 junior physicians), and expert (4 senior physicians). This setup enabled comprehensive assessment of reproducibility in contact force, image acquisition, image measurement and AI-assisted classification. Radiological feature variability was measured using the coefficient of variation (COV), while performance and reproducibility assessments utilized mean and standard deviation (SD).

Findings

The auto-RUSS had the potential to reduce operator-dependent variability in ultrasound examinations, offering enhanced repeatability and consistency across multiple dimensions including probe contact force, images acquisition, image measurement, and diagnostic model performance.

Originality/value

In this paper, an autonomous robotic ultrasound scanning system (auto-RUSS) pipeline was proposed. Through comprehensive human-machine comparison experiments, the auto-RUSS was shown to effectively improve the reproducibility of ultrasound images and minimize human-induced variability.

A review of robot-assisted ultrasound examination: Systems and technology

BACKGROUND

At present, the number and overall level of ultrasound (US) doctors cannot meet the medical needs, and the medical ultrasound robots will largely solve the shortage of medical resources.

METHODS

According to the degree of automation, the handheld, semi-automatic and automatic ultrasound examination robot systems are summarised. Ultrasound scanning path planning and robot control are the keys to ensure that the robot systems can obtain high-quality images. Therefore, the ultrasound scanning path planning and control methods are summarised. The research progress and future trends are discussed.

RESULTS

A variety of ultrasound robot systems have been applied to various medical works. With the continuous improvement of automation, the systems provide high-quality ultrasound images and image guidance for clinicians.

CONCLUSION

Although the development of medical ultrasound robot still faces challenges, with the continuous progress of robot technology and communication technology, medical ultrasound robot will have great development potential and broad application space.

A System for Reproducible 3D Ultrasound Measurements of Skeletal Muscles

In 3D freehand ultrasound imaging, operator dependent variations in applied forces and movements can lead to errors in the reconstructed images. In this paper, we introduce an automated 3D ultrasound system, which enables acquisitions with controlled movement trajectories by using motors, which electrically move the probe. Due to integrated encoders there is no need of position sensors. An included force control mechanism ensures a constant contact force to the skin. We conducted 8 trials with the automated 3D ultrasound system on 2 different phantoms with 3 force settings and 10 trials on a human tibialis anterior muscle with 2 force settings. For comparison, we also conducted 8 freehand 3D ultrasound scans from 2 operators (4 force settings) on one phantom and 10 with one operator on the tibialis anterior muscle. Both freehand and automated trials showed small errors in volume and length computations of the reconstructions, however the freehand trials showed larger standard deviations. We also computed the thickness of the phantom and the tibialis anterior muscle. We found significant differences in force settings for the operators and higher coefficients of variation for the freehand trials. Overall, the automated 3D ultrasound system shows a high accuracy in reconstruction. Due to the smaller coefficients of variation, the automated 3D ultrasound system enables more reproducible ultrasound examinations than the freehand scanning. Therefore, the automated 3D ultrasound system is a reliable tool for 3D investigations of skeletal muscle.

Review of robotic systems for thoracoabdominal puncture interventional surgery

Cancer, with high morbidity and high mortality, is one of the major burdens threatening human health globally. Intervention procedures via percutaneous puncture have been widely used by physicians due to its minimally invasive surgical approach. However, traditional manual puncture intervention depends on personal experience and faces challenges in terms of precisely puncture, learning-curve, safety and efficacy. The development of puncture interventional surgery robotic (PISR) systems could alleviate the aforementioned problems to a certain extent. This paper attempts to review the current status and prospective of PISR systems for thoracic and abdominal application. In this review, the key technologies related to the robotics, including spatial registration, positioning navigation, puncture guidance feedback, respiratory motion compensation, and motion control, are discussed in detail.

A fully autonomous robotic ultrasound system for thyroid scanning

The current thyroid ultrasound relies heavily on the experience and skills of the sonographer and the expertise of the radiologist, and the process is physically and cognitively exhausting. In this paper, we report a fully autonomous robotic ultrasound system, which is able to scan thyroid regions without human assistance and identify malignant nod- ules. In this system, human skeleton point recognition, reinforcement learning, and force feedback are used to deal with the difficulties in locating thyroid targets. The orientation of the ultrasound probe is adjusted dynamically via Bayesian optimization. Experimental results on human participants demonstrated that this system can perform high-quality ultrasound scans, close to manual scans obtained by clinicians. Additionally, it has the potential to detect thyroid nodules and provide data on nodule characteristics for American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) calculation.

Autonomous ultrasound scanning robotic system based on human posture recognition and image servo control: an application for cardiac imaging

In traditional cardiac ultrasound diagnostics, the process of planning scanning paths and adjusting the ultrasound window relies solely on the experience and intuition of the physician, a method that not only affects the efficiency and quality of cardiac imaging but also increases the workload for physicians. To overcome these challenges, this study introduces a robotic system designed for autonomous cardiac ultrasound scanning, with the goal of advancing both the degree of automation and the quality of imaging in cardiac ultrasound examinations. The system achieves autonomous functionality through two key stages: initially, in the autonomous path planning stage, it utilizes a camera posture adjustment method based on the human body's central region and its planar normal vectors to achieve automatic adjustment of the camera's positioning angle; precise segmentation of the human body point cloud is accomplished through efficient point cloud processing techniques, and precise localization of the region of interest (ROI) based on keypoints of the human body. Furthermore, by applying isometric path slicing and B-spline curve fitting techniques, it independently plans the scanning path and the initial position of the probe. Subsequently, in the autonomous scanning stage, an innovative servo control strategy based on cardiac image edge correction is introduced to optimize the quality of the cardiac ultrasound window, integrating position compensation through admittance control to enhance the stability of autonomous cardiac ultrasound imaging, thereby obtaining a detailed view of the heart's structure and function. A series of experimental validations on human and cardiac models have assessed the system's effectiveness and precision in the correction of camera pose, planning of scanning paths, and control of cardiac ultrasound imaging quality, demonstrating its significant potential for clinical ultrasound scanning applications.

A High-Resolution 3D Ultrasound Imaging System Oriented towards a Specific Application in Breast Cancer Detection Based on a 1 × 256 Ring Array

This paper presents the design and development of a high-resolution 3D ultrasound imaging system based on a 1 × 256 piezoelectric ring array, achieving an accuracy of 0.1 mm in both ascending and descending modes. The system achieves an imaging spatial resolution of approximately 0.78 mm. A 256 × 32 cylindrical sensor array and a digital phantom of breast tissue were constructed using the k-Wave toolbox. The signal is acquired layer by layer using 3D acoustic time-domain simulation, resulting in the collection of data from each of the 32 layers. The 1 × 256 ring array moves on a vertical trajectory from the chest wall to the nipple at a constant speed. A data set was collected at intervals of 1.5 mm, resulting in a total of 32 data sets. Surface rendering and volume rendering algorithms were used to reconstruct 3D ultrasound images from the volume data obtained via simulation so that the smallest simulated reconstructed lesion had a diameter of 0.3 mm. The reconstructed three-dimensional image derived from the experimental data exhibits the contour of the breast model along with its internal mass. Reconstructable dimensions can be achieved up to approximately 0.78 mm. The feasibility of applying the system to 3D breast ultrasound imaging has been demonstrated, demonstrating its attributes of resolution, precision, and exceptional efficiency.

Robotic ultrasound imaging: State-of-the-art and future perspectives

Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques. Additionally, we present the challenges that the scientific community needs to face in the coming years in order to achieve its ultimate goal of developing intelligent robotic sonographer colleagues. These colleagues are expected to be capable of collaborating with human sonographers in dynamic environments to enhance both diagnostic and intraoperative imaging.

Lightweight Force-Controlled Device for Freehand Ultrasound Acquisition

This study investigates a force-controlled auxiliary device for freehand ultrasound (US) examinations. The designed device allows sonographers to maintain a steady target pressure on the US probe, thereby improving the US image quality and reproducibility. The use of a screw motor to power the device and a Raspberry Pi as the system controller results in a lightweight and portable device, while a screen enhances user-interactivity. Using gravity compensation, error compensation, an adaptive proportional-integral-derivative algorithm, and low-pass signal filtering, the designed device provides highly accurate force control. Several experiments using the developed device, including clinical trials relating to the jugular and superficial femoral veins, validate its utility in ensuring the desired pressure in response to varying environments and prolonged US examinations, enabling low or high pressures to be maintained and lowering the threshold of clinical experience. Moreover, the experimental results show that the designed device effectively relieves the stress on the sonographer's hand joints during US examinations and enables rapid assessment of the tissue elasticity characteristics. With automatic pressure tracking between probe and patient, the proposed device offers potentially significant benefits for the reproducibility and stability of US images and the health of sonographers.

Portable Device to Assist With Force Control in Ultrasound Acquisition

This study presents a portable device that ensures precise contact force between a subject and a probe to improve the stability and reproducibility of ultrasound (US) acquisition. The mechanical portion of the device includes a servo motor, gears, and a ball screw linear actuator; two photoelectric switches are used to limit the stroke. A combined force and position control system is developed, and a pressure threshold is introduced to reduce the chattering of the system so that it can be applied to US examinations of tissues of different stiffness levels. Force control experiments were conducted on the device, and the results showed that the device can overcome the chattering of a physician's hand and movement caused by a subject's respiration. Additionally, the stability of the US acquisition was substantially improved. Based on clinical trials on humans, this device was observed to improve the consistency of ultrasonic results and the repeatability of images, and it assisted sonographers with maintaining suitable contact force and improving imaging quality. The device can either be handheld by a physician or easily integrated with a manipulator as an autonomous robotic US acquisition device, thereby validating its potential for US applications.

Three-dimensional ultrasound image reconstruction based on 3D-ResNet in the musculoskeletal system using a 1D probe:ex vivoandin vivofeasibility studies

Objective. Three-dimensional (3D) ultrasound (US) is needed to provide sonographers with a more intuitive panoramic view of the complex anatomical structure, especially the musculoskeletal system. In actual scanning, sonographers may perform fast scanning using a one-dimensional (1D) array probe .at random angles to gain rapid feedback, which leads to a large US image interval and missing regions in the reconstructed volume.Approach.In this study, a 3D residual network (3D-ResNet) modified by a 3D global residual branch (3D-GRB) and two 3D local residual branches (3D-LRBs) was proposed to retain detail and reconstruct high-quality 3D US volumes with high efficiency using only sparse two-dimensional (2D) US images. The feasibility and performance of the proposed algorithm were evaluated onex vivoandin vivosets.Main results. High-quality 3D US volumes in the fingers, radial and ulnar bones, and metacarpophalangeal joints were obtained by the 3D-ResNet, respectively. Their axial, coronal, and sagittal slices exhibited rich texture and speckle details. Compared with kernel regression, voxel nearest-neighborhood, squared distance weighted methods, and a 3D convolution neural network in the ablation study, the mean peak-signal-to-noise ratio and mean structure similarity of the 3D-ResNet were up to 28.53 ± 1.29 dB and 0.98 ± 0.01, respectively, and the corresponding mean absolute error dropped to 0.023 ± 0.003 with a better resolution gain of 1.22 ± 0.19 and shorter reconstruction time.Significance.These results illustrate that the proposed algorithm can rapidly reconstruct high-quality 3D US volumes in the musculoskeletal system in cases of a large amount of data loss. This suggests that the proposed algorithm has the potential to provide rapid feedback and precise analysis of stereoscopic details in complex and meticulous musculoskeletal system scanning with a less limited scanning speed and pose variations for the 1D array probe.

Automatic 3-D spine curve measurement in freehand ultrasound via structure-aware reinforcement learning spinous process localization

Freehand 3-D ultrasound systems have been advanced in scoliosis assessment to avoid radiation hazards, especially for teenagers. This novel 3-D imaging method also makes it possible to evaluate the spine curvature automatically from the corresponding 3-D projection images. However, most approaches neglect the three-dimensional spine deformity by only using the rendering images, thus limiting their usage in clinical applications. In this study, we proposed a structure-aware localization model to directly identify the spinous processes for automatic 3-D spine curve measurement using the images acquired with freehand 3-D ultrasound imaging. The pivot is to leverage a novel reinforcement learning (RL) framework to localize the landmarks, which adopts a multi-scale agent to boost structure representation with positional information. We also introduced a structure similarity prediction mechanism to perceive the targets with apparent spinous process structures. Finally, a two-fold filtering strategy was proposed to screen the detected spinous processes landmarks iteratively, followed by a three-dimensional spine curve fitting for the spine curvature assessments. We evaluated the proposed model on 3-D ultrasound images among subjects with different scoliotic angles. The results showed that the mean localization accuracy of the proposed landmark localization algorithm was 5.95 pixels. Also, the curvature angles on the coronal plane obtained by the new method had a high linear correlation with those by manual measurement (R = 0.86, p < 0.001). These results demonstrated the potential of our proposed method for facilitating the 3-D assessment of scoliosis, especially for 3-D spine deformity assessment.

A Study on a Parameter Estimator for the Homodyned K Distribution Based on Table Search for Ultrasound Tissue Characterization

OBJECTIVE

The homodyned K (HK) distribution is considered to be the most suitable distribution in the context of tissue characterization; therefore, the search for a rapid and reliable parameter estimator for HK distribution is important.

METHODS

We propose a novel parameter estimator based on a table search (TS) for HK parameter estimates. The TS estimator can inherit the strength of conventional estimators by integrating various features and taking advantage of the TS method in a rapid and easy operation. Performance of the proposed TS estimator was evaluated and compared with that of XU (the estimation method based on X and U statistics) and artificial neural network (ANN) estimators.

DISCUSSION

The simulation results revealed that the TS estimator is superior to the XU and ANN estimators in terms of normalized standard deviations and relative root mean squared errors of parameter estimation, and is faster. Clinical experiments found that the area under the receiver operating curve for breast lesion classification using the parameters estimated by the TS estimator could reach 0.871.

CONCLUSION

The proposed TS estimator is more accurate, reliable and faster than the state-of-the-art XU and ANN estimators and has great potential for ultrasound tissue characterization based on the HK distribution.

Calibration method for a breast intervention robot based on four-dimensional ultrasound image guidance

In breast interventional ultrasound therapy, it is difficult to directly diagnose the location of a tumor in 2-D ultrasound images. To assist surgeons in treatment more intuitively, a four-dimensional ultrasound image-guided breast intervention robot is proposed. The calibration approach of the ultrasonic image for the robot is one of the main contents of the research. This method is based on the establishment of a complete coordinate system conversion model, and it uses the ORB (oriented FAST and rotated BRIEF) feature extraction method to obtain and record the real-time image marker pixel positions, calculate the unknown parameters of the coordinate system conversion matrix, and establish a complete calibration system. This article demonstrates the feasibility of the calibration approach through experiments in our developed US-guided robotic system. Additional experimental and parametrical comparisons of the proposed method with state-of-the-art methods were conducted to thoroughly evaluate the outperformance of the proposed method.

Force-guided autonomous robotic ultrasound scanning control method for soft uncertain environment

PURPOSE

Autonomous ultrasound imaging by robotic ultrasound scanning systems in complex soft uncertain clinical environments is important and challenging to assist in therapy. To cope with the complex environment faced by the ultrasound probe during the scanning process, we propose an autonomous robotic ultrasound (US) control method based on reinforcement learning (RL) model to build the relationship between the environment and the system. The proposed method requires only contact force as input information to achieve robot control of the posture and contact force of the probe without any a priori information about the target and the environment.

METHODS

First, an RL agent is proposed and trained by a policy gradient theorem-based RL model with the 6-degree-of-freedom (DOF) contact force of the US probe to learn the relationship between contact force and output force directly. Then, a force control strategy based on the admittance controller is proposed for synchronous force, orientation and position control by defining the desired contact force as the action space.

RESULTS

The proposed method was evaluated via collected US images, contact force and scan trajectories by scanning an unknown soft phantom. The experimental results indicated that the proposed method differs from the free-hand scanned approach in the US images within 3 ± 0.4%. The analysis results of contact forces and trajectories indicated that our method could make stable scanning processes on a soft uncertain skin surface and obtained US images.

CONCLUSION

We propose a concise and efficient force-guided US robot scanning control method for soft uncertain environment based on reinforcement learning. Experimental results validated our method's feasibility and validity for complex skin surface scanning, and the volunteer experiments indicated the potential application value in the complex clinical environment of robotic US imaging system especially with limited visual information.

A two-steps implementation of 3D ultrasound imaging in frequency domain with 1D array transducer

Compared with B-mode imaging, three-dimensional (3D) ultrasound imaging is more helpful in research and clinical application. At present, the 3D ultrasound images can be acquired directly with two-dimensional (2D) array transducer or reconstructed from a series of B-mode images obtained with one-dimensional (1D) array transducer. Imaging with 2D array transducer can achieve a high frame rate, but suffering from the complexity of the imaging system, such as the large amount of channels, and high computational complexity. Reconstructing 3D images from a series of B-mode images can be implemented by recording the position and orientation of the slice images. This is a low-cost and flexible imaging method, but usually suffering from the low imaging quality and low frame rate. In our previous work, a novel 3D ultrasound imaging method in frequency domain with a moved 1D array transducer is presented. This method can reduce the computational complexity with FFT, and get improved imaging quality and frame rate to some extent. Besides, this method can be adopted to construct images with a row-column-addressed 2D array, which can reduce the amount of channels effectively. In this paper, a two-steps implementation of this imaging method is proposed, in which the combined implementation of the 3D imaging is decomposed to two steps of 2D imaging processes in Frequency domain. In the first step, the received echoes of the 1D array transducer at each position are processed with a 2D imaging processes in the lateral- axial planes. In the second step, a 2D imaging processes is preformed in the planes of orthogonal to the transducer. Simulation results show that the two-steps implementation can achieve almost the same imaging quality to the previous work. Compared with the implementation of 3D imaging in our previous work, the proposed two-steps implementation can be carried out with parallel process to improve the computational efficiency, or carried out with loop to reduce the hardware cost. Besides, the first step can be performed with a conventional DAS imaging method when a cylindrical wave is adopted for imaging. The influence of the spread angle of the field is also discussed.

Automation of data analysis in molecular cancer imaging and its potential impact on future clinical practice

Digitalization, especially the use of machine learning and computational intelligence, is considered to dramatically shape medical procedures in the near future. In the field of cancer diagnostics, radiomics, the extraction of multiple quantitative image features and their clustered analysis, is gaining increasing attention to obtain more detailed, reproducible, and meaningful information about the disease entity, its prognosis and the ideal therapeutic option. In this context, automation of diagnostic procedures can improve the entire pipeline, which comprises patient registration, planning and performing an imaging examination at the scanner, image reconstruction, image analysis, and feeding the diagnostic information from various sources into decision support systems. With a focus on cancer diagnostics, this review article reports and discusses how computer-assistance can be integrated into diagnostic procedures and which benefits and challenges arise from it. Besides a strong view on classical imaging modalities like x-ray, CT, MRI, ultrasound, PET, SPECT and hybrid imaging devices thereof, it is outlined how imaging data can be combined with data deriving from patient anamnesis, clinical chemistry, pathology, and different omics. In this context, the article also discusses IT infrastructures that are required to realize this integration in the clinical routine. Although there are still many challenges to comprehensively implement automated and integrated data analysis in molecular cancer imaging, the authors conclude that we are entering a new era of medical diagnostics and precision medicine.

Probe Sector Matching for Freehand 3D Ultrasound Reconstruction

A 3D ultrasound image reconstruction technique, named probe sector matching (PSM), is proposed in this paper for a freehand linear array ultrasound probe equipped with multiple sensors, providing the position and attitude of the transducer and the pressure between the transducer and the target surface. The proposed PSM method includes three main steps. First, the imaging target and the working range of the probe are set to be the center and the radius of the imaging field of view, respectively. To reconstruct a 3D volume, the positions of all necessary probe sectors are pre-calculated inversely to form a sector database. Second, 2D cross-section probe sectors with the corresponding optical positioning, attitude and pressure information are collected when the ultrasound probe is moving around the imaging target. Last, an improved 3D Hough transform is used to match the plane of the current probe sector to the existing sector images in the sector database. After all pre-calculated probe sectors are acquired and matched into the 3D space defined by the sector database, a 3D ultrasound reconstruction is completed. The PSM is validated through two experiments: a virtual simulation using a numerical model and a lab experiment using a real physical model. The experimental results show that the PSM effectively reduces the errors caused by changes in the target position due to the uneven surface pressure or the inhomogeneity of the transmission media. We conclude that the PSM proposed in this study may help to design a lightweight, inexpensive and flexible ultrasound device with accurate 3D imaging capacity.

Measurement of Quasi-Static 3-D Knee Joint Movement Based on the Registration From CT to US

The measurement of quasi-static 3-D knee joint movement is an important basis for studying the mechanism of knee joint injury. Most of the existing measurement methods make use of computed tomography (CT) and nuclear magnetic resonance (MR) imaging technology and hence have the disadvantages of invasiveness, ionizing radiation, low accuracy, and high cost. To overcome those drawbacks, this article innovatively proposes a 3-D motion measurement system for the knee joint based on the registration of CT images to ultrasound (US) images. More specifically, the lower limbs of a subject were first scanned once to acquire the CT images. A portable handheld device was designed to control a US probe for mechanically scanning the subject's lower limbs in a linear trajectory. During the movement of the subject's lower limbs, the US scanning was performed quasi-statically. The acquired US images were then registered to the CT images, and the 3-D motions of the lower limb bones could be recreated with the bones scanned in CT images. To guarantee the registration accuracy and efficiency, we used the H-shaped multiview slice assembly as the structural image content for the registration process. The experimental results show that our approach can accurately measure the 3-D motion of the knee joint and meet the needs of 3-D motion analysis of knee joint in practice.

Hepatic steatosis assessment using ultrasound homodyned-K parametric imaging: the effects of estimators

BACKGROUND

The homodyned-K (HK) distribution is an important statistical model for describing ultrasound backscatter envelope statistics. HK parametric imaging has shown potential for characterizing hepatic steatosis. However, the feasibility of HK parametric imaging in assessing human hepatic steatosis in vivo remains unclear.

METHODS

In this paper, ultrasound HK μ parametric imaging was proposed for assessing human hepatic steatosis in vivo. Two recent estimators for the HK model, RSK (the level-curve method that uses the signal-to-noise ratio (SNR), skewness, and kurtosis based on the fractional moments of the envelope) and XU (the estimation method based on the first moment of the intensity and two log-moments, namely X- and U-statistics), were investigated. Liver donors (n=72) and patients (n=204) were recruited to evaluate hepatic fat fractions (HFFs) using magnetic resonance spectroscopy and to evaluate the stages of fatty liver disease (normal, mild, moderate, and severe) using liver biopsy with histopathology. Livers were scanned using a 3-MHz ultrasound to construct μ RSK and μ XU images to correlate with HFF analyses and fatty liver stages. The μ RSK and μ XU parametric images were constructed using the sliding window technique with the window side length (WSL) =1-9 pulse lengths (PLs). The diagnostic values of the μ RSK and μ XU parametric imaging methods were evaluated using receiver operating characteristic (ROC) curves.

RESULTS

For the 72 participants in Group A, the μ RSK parametric imaging with WSL =2-9 PLs exhibited similar correlation with log10(HFF), and the μ RSK parametric imaging with WSL = 3 PLs had the highest correlation with log10(HFF) (r=0.592); the μ XU parametric imaging with WSL =1-9 PLs exhibited similar correlation with log10(HFF), and the μ XU parametric imaging with WSL =1 PL had the highest correlation with log10(HFF) (r=0.628). For the 204 patients in Group B, the areas under the ROC (AUROCs) obtained using μ RSK for fatty stages ≥ mild (AUROC1), ≥ moderate (AUROC2), and ≥ severe (AUROC3) were (AUROC1, AUROC2, AUROC3) = (0.56, 0.57, 0.53), (0.68, 0.72, 0.75), (0.73, 0.78, 0.80), (0.74, 0.77, 0.79), (0.74, 0.78, 0.79), (0.75, 0.80, 0.82), (0.74, 0.77, 0.83), (0.74, 0.78, 0.84) and (0.73, 0.76, 0.83) for WSL =1, 2, 3, 4, 5, 6, 7, 8 and 9 PLs, respectively. The AUROCs obtained using μ XU for fatty stages ≥ mild, ≥ moderate, and ≥ severe were (AUROC1, AUROC2, AUROC3) = (0.75, 0.83, 0.81), (0.74, 0.80, 0.80), (0.76, 0.82, 0.82), (0.74, 0.80, 0.84), (0.76, 0.80, 0.83), (0.75, 0.80, 0.84), (0.75, 0.79, 0.85), (0.75, 0.80, 0.85) and (0.73, 0.77, 0.83) for WSL = 1, 2, 3, 4, 5, 6, 7, 8 and 9 PLs, respectively.

CONCLUSIONS

Both the μ RSK and μ XU parametric images are feasible for evaluating human hepatic steatosis. The WSL exhibits little impact on the diagnosing performance of the μ RSK and μ XU parametric imaging. The μ XU parametric imaging provided improved performance compared to the μ RSK parametric imaging in characterizing human hepatic steatosis in vivo.

Scoliotic Imaging With a Novel Double-Sweep 2.5-Dimensional Extended Field-of-View Ultrasound

Extended field-of-view ultrasound (US EFOV) imaging is a technique used extensively in the clinical field to attain interpretable panorama of anatomy; 2.5-D US EFOV has recently been proposed for spine imaging. In the original 2.5-D US EFOV, it makes use of a six degrees-of-freedom positional sensor attached to the US probe to record the corresponding position of each B-scan. By combining the positional information and the B-scan images, the 2.5-D EFOV can reconstruct a panorama on a curved image plane when the scanning trajectory of the US probe is curved. In this paper, an improved method based on the Bezier interpolation is proposed to better reconstruct 2.5-D US EFOV imaging, producing the panoramas with smoother texture and higher quality. To make it more applicable for scoliosis patients, we designed a novel method called double-sweep 2.5-D EFOV to better image the spinal tissues and easily compute the Cobb angle. In vitro and in vivo experiments demonstrated that the 2.5-D EFOV images obtained by the proposed method can present anatomical structures of the scanning region accurately.

In Vivo Measurement of the Human Lumbar Spine Using Magnetic Resonance Imaging to Ultrasound Registration

OBJECTIVE

This study aimed to refine a magnetic resonance imaging (MRI)-ultrasound registration (ie, alignment) technique to make noninvasive, nonionizing, 3-dimensional measurement of the lumbar segmental motion in vivo.

METHODS

Five healthy participants participated in this validation study. We scanned the lumbar region of each participant 5 times using an ultrasound probe while he or she kept a prone lying posture on a plinth. Participant-specific models of L1-L5 were constructed from magnetic resonance (MR) images and aligned with the 3-dimensional ultrasound dataset of each scan using 4 variants of MRI-ultrasound registration approach (simplified intensity-based registration [1] with and [2] without including the transverse processes and their surrounding soft tissues [denoted as TP complex]; and hierarchical intensity-based registration [3] with and [4] without including the TP complex). The robustness and precision of these registration approaches were compared.

RESULTS

Although all registration approaches converged to a similar solution, excluding the TP complex improved the percentage of successful registration from 92% to 100%. There was no significant difference in the precision among the 4 MRI-ultrasound registration variants. For the simplified intensity-based registration without including the TP complex, average precision at each degree of freedom was 1.33° (flexion-extension), 2.48° (lateral bending), 1.32° (axial rotation), 2.15 mm (left/right), 1.08 mm (anterior-posterior), and 1.16 (superior-inferior), respectively.

CONCLUSION

Given that using simplified intensity-based MRI-ultrasound registration can substantially streamline the registration process and excluding the TP complex would improve the robustness of the registration, we conclude that this combination is the method of choice for in vivo human applications.

An Accurate Recognition of Infrared Retro-Reflective Markers in Surgical Navigation

Marker-based optical tracking systems (OTS) are widely used in clinical image-guided therapy. However, the emergence of ghost markers, which is caused by the mistaken recognition of markers and the incorrect correspondences between marker projections, may lead to tracking failures for these systems. Therefore, this paper proposes a strategy to prevent the emergence of ghost markers by identifying markers based on the features of their projections, finding the correspondences between marker projections based on the geometric information provided by markers, and fast-tracking markers in a 2D image between frames based on the sizes of their projections. Apart from validating its high robustness, the experimental results show that the proposed strategy can accurately recognize markers, correctly identify their correspondences, and meet the requirements of real-time tracking.

Hepatic Steatosis Assessment Using Quantitative Ultrasound Parametric Imaging Based on Backscatter Envelope Statistics

Hepatic steatosis is a key manifestation of non-alcoholic fatty liver disease (NAFLD). Early detection of hepatic steatosis is of critical importance. Currently, liver biopsy is the clinical golden standard for hepatic steatosis assessment. However, liver biopsy is invasive and associated with sampling errors. Ultrasound has been recommended as a first-line diagnostic test for the management of NAFLD. However, B-mode ultrasound is qualitative and can be affected by factors including image post-processing parameters. Quantitative ultrasound (QUS) aims to extract quantified acoustic parameters from the ultrasound backscattered signals for ultrasound tissue characterization and can be a complement to conventional B-mode ultrasound. QUS envelope statistics techniques, both statistical model-based and non-model-based, have shown potential for hepatic steatosis characterization. However, a state-of-the-art review of hepatic steatosis assessment using envelope statistics techniques is still lacking. In this paper, envelope statistics-based QUS parametric imaging techniques for characterizing hepatic steatosis are reviewed and discussed. The reviewed ultrasound envelope statistics parametric imaging techniques include acoustic structure quantification imaging, ultrasound Nakagami imaging, homodyned-K imaging, kurtosis imaging, and entropy imaging. Future developments are suggested.