Use of intra-procedural fusion imaging combining contrast-enhanced ultrasound using a perflubutane-based contrast agent and auto sweep three-dimensional ultrasound for guiding radiofrequency ablation and evaluating its efficacy in patients with hepatocellular carcinoma.

Purpose: This study evaluated the usefulness of intraprocedural contrast-enhanced ultrasound (CEUS)/ultrasound (US) fusion imaging using a perflubutane-based contrast agent combined with preprocedural auto sweep three-dimensional US to obtain volume data for guidance and evaluation of the therapeutic efficacy of radiofrequency ablation (RFA).Methods: This uncontrolled clinical trial included 50 hepatocellular carcinomas (HCCs) with a mean diameter of 15.3 mm that had been treated by RFA. The efficacy of RFA was evaluated by CEUS/US fusion imaging during the procedure. If the ablation was deemed to be inadequate, further ablation was performed until adequate ablation was achieved. Contrast-enhanced computed tomography (CECT) or contrast-enhanced magnetic resonance imaging (CEMRI) was performed a month after RFA, and the images obtained using each modality were reviewed to evaluate the efficacy of RFA.Results: Thirty-three of the 50 lesions were evaluated by CEUS/US fusion imaging as having been adequately ablated after the first RFA procedure. The ablation was evaluated as inadequate in the remaining 17 lesions, for which additional ablation was performed. Ninety-eight (49/50) of all HCCs were evaluated as having been eventually adequately ablated on intraprocedural CEUS/US fusion imaging. The concordance rate for evaluations between intraprocedural CEUS/US fusion imaging and CECT/CEMRI performed 1 month after RFA was 88% (44/50). The kappa value for agreement between the two methods of evaluation was 0.792.Conclusion: Intraprocedural fusion imaging combining CEUS and auto sweep three-dimensional US appears to be a useful modality for RFA guidance and evaluation of therapeutic efficacy of RFA in patients with HCC.

Intraprocedurally EOB-MRI/US fusion imaging focusing on hepatobiliary phase findings can help to reduce the recurrence of hepatocellular carcinoma after radiofrequency ablation.

BACKGROUND & AIMS: To explore the ability of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid magnetic resonance imaging (EOB-MRI)/ultrasound (US) fusion imaging (FI) to improve the prognosis of radiofrequency ablation (RFA) by ablating the characteristic findings of hepatocellular carcinoma (HCC) in hepatobiliary phase (HBP) imaging. METHODS: We retrospectively recruited 115 solitary HCC lesions with size of (15.9 ± 4.6) mm. They were all treated by RFA and preoperative EOB-MRI. According to the modalities guiding RFA performance, the lesions were grouped into contrast enhanced US (CEUS)/US guidance group and EOB-MRI/US FI guidance group. For the latter group, the ablation scope was set to cover the HBP findings (peritumoral hypointensity and irregular protruding margin). The presence of HBP findings, the modalities guided RFA, the recurrence rate were observed. RESULTS: After an average follow-up of 377 days, local tumor progression (LTP) and intrahepatic distant recurrence (IDR) were 14.8% and 38.4%, respectively. The lesions having HBP findings exhibited a higher recurrence rate (73.7%) than the lesions without HBP findings (42.9%) (p = 0.002) and a low overall recurrence-free curve using the Kaplan-Meier method (p = 0.038). Using EOB-MRI/US FI as guidance, there was no difference in the recurrence rate between the groups with and without HBP findings (p = 0.799). In lesions with HBP findings, RFA guided by EOB-MRI/US FI (53.8%) produced a lower recurrence rate than CEUS/US (84.0%) (p = 0.045). CONCLUSIONS: The intraprocedurally application of EOB-MRI/US FI to determine ablation scope according to HBP findings is feasible and beneficial for prognosis of RFA.

Focused Ultrasound and Lithotripsy.

Shock wave lithotripsy has generally been a first choice for kidney stone removal. The shock wave lithotripter uses an order of microsecond pulse durations and up to a 100 MPa pressure spike triggered at approximately 0.5-2 Hz to fragment kidney stones through mechanical mechanisms. One important mechanism is cavitation. We proposed an alternative type of lithotripsy method that maximizes cavitation activity to disintegrate kidney stones using high-intensity focused ultrasound (HIFU). Here we outline the method according to the previously published literature (Matsumoto et al., Dynamics of bubble cloud in focused ultrasound. Proceedings of the second international symposium on therapeutic ultrasound, pp 290-299, 2002; Ikeda et al., Ultrasound Med Biol 32:1383-1397, 2006; Yoshizawa et al., Med Biol Eng Comput 47:851-860, 2009; Koizumi et al., A control framework for the non-invasive ultrasound the ragnostic system. Proceedings of 2009 IEEE/RSJ International Conference on Intelligent Robotics and Systems (IROS), pp 4511-4516, 2009; Koizumi et al., IEEE Trans Robot 25:522-538, 2009). Cavitation activity is highly unpredictable; thus, a precise control system is needed. The proposed method comprises three steps of control in kidney stone treatment. The first step is control of localized high pressure fluctuation on the stone. The second step is monitoring of cavitation activity and giving feedback on the optimized ultrasound conditions. The third step is stone tracking and precise ultrasound focusing on the stone. For the high pressure control we designed a two-frequency wave (cavitation control (C-C) waveform); a high frequency ultrasound pulse (1-4 MHz) to create a cavitation cloud, and a low frequency trailing pulse (0.5 MHz) following the high frequency pulse to force the cloud into collapse. High speed photography showed cavitation collapse on a kidney stone and shock wave emission from the cloud. We also conducted in-vitro erosion tests of model and natural kidney stones. For the model stones, the erosion rate of the C-C waveform showed a distinct advantage with the combined high and low frequency waves over either wave alone. For optimization of the high frequency ultrasound intensity, we investigated the relationship between subharmonic emission from cavitation bubbles and stone erosion volume. For stone tracking we have also developed a non-invasive ultrasound theragnostic system (NIUTS) that compensates for kidney motion. Natural stones were eroded and most of the resulting fragments were less than 1 mm in diameter. The small fragments were small enough to pass through the urethra. The results demonstrate that, with the precise control of cavitation activity, focused ultrasound has the potential to be used to develop a less invasive and more controllable lithotripsy system.

Rib region detection for scanning path planning for fully automated robotic abdominal ultrasonography.

PURPOSE: Scanning path planning is an essential technology for fully automated ultrasound (US) robotics. During biliary scanning, the subcostal boundary is critical body surface landmarks for scanning path planning but are often invisible, depending on the individual. This study developed a method of estimating the rib region for scanning path planning toward fully automated robotic US systems. METHODS: We proposed a method for determining the rib region using RGB-D images and respiratory variation. We hypothesized that detecting the rib region would be possible based on changes in body surface position due to breathing. We generated a depth difference image by finding the difference between the depth image taken at the resting inspiratory position and the depth image taken at the maximum inspiratory position, which clearly shows the rib region. The boundary position of the subcostal was then determined by applying training using the YOLOv5 object detection model to this depth difference image. RESULTS: In the experiments with healthy subjects, the proposed method of rib detection using the depth difference image marked an intersection over union (IoU) of 0.951 and average confidence of 0.77. The average error between the ground truth and predicted positions was 16.5 mm in 3D space. The results were superior to rib detection using only the RGB image. CONCLUSION: The proposed depth difference imaging method, which measures respiratory variation, was able to accurately estimate the rib region without contact and physician intervention. It will be useful for planning the scan path during the biliary imaging.

Study on method of organ section retention and tracking through deep learning in automated diagnostic and therapeutic robotics.

PURPOSE: In high-intensity focused ultrasound (HIFU) treatment of the kidney and liver, tracking the organs is essential because respiratory motions make continuous cauterization of the affected area difficult and may cause damage to other parts of the body. In this study, we propose a tracking system for rotational scanning, and propose and evaluate a method for estimating the angles of organs in ultrasound images. METHODS: We proposed AEMA, AEMAD, and AEMAD++ as methods for estimating the angles of organs in ultrasound images, using RUDS and a phantom to acquire 90-degree images of a kidney from the long-axis image to the short-axis image as a data set. Six datasets were used, with five for preliminary preparation and one for testing, while the initial position was shifted by 2 mm in the contralateral axis direction. The test data set was evaluated by estimating the angle using each method. RESULTS: The accuracy and processing speed of angle estimation for AEMA, AEMAD, and AEMAD++ were 23.8% and 0.33 FPS for AEMAD, 32.0% and 0.56 FPS for AEMAD, and 29.5% and 3.20 FPS for AEMAD++, with tolerance of ± 2.5 degrees. AEMAD++ offered the best speed and accuracy. CONCLUSION: In the phantom experiment, AEMAD++ showed the effectiveness of tracking the long-axis image of the kidney in rotational scanning. In the future, we will add either the area of surrounding organs or the internal structure of the kidney as a new feature to validate the results.

Current status and future outlook of ultrasound treatment for prostate cancer.

Radical prostatectomy and radiation therapy are the standard treatment options for localized prostate cancer (PC). However, radical prostatectomy may cause the deterioration of urinary and sexual function, and radiation-induced hemorrhagic cystitis and severe rectal bleeding are risk factors for fatal conditions in patients after radiation therapy. With the recent development of magnetic resonance imaging (MRI) for the localization of clinically significant PC (csPC) and treatment modalities, "focal therapy", which cures csPC while preserving anatomical structures related to urinary and sexual functions, has become a minimally invasive treatment for localized PC. Based on the clinical results of transrectal high-intensity focused ultrasound (HIFU) for localized PC in the whole gland and focal therapy, HIFU is considered an attractive treatment option for focal therapy. Recently, the short-term clinical results of transurethral high-intensity directional ultrasound (HIDU) have been reported. With the resolution of some issues, HIDU may be commonly used for PC treatment similar to HIFU. Because HIFU and HIDU have limitations regarding the treatment of patients with large prostate calcifications and large prostate volumes, the proper use of these modalities will enable the treatment of any target area in the prostate. To establish a standard treatment strategy for localized PC, pair-matched and historically controlled studies are required to verify the oncological and functional outcomes of ultrasound treatment for patients with localized PC.

A VS ultrasound diagnostic system with kidney image evaluation functions.

PURPOSE: An inevitable feature of ultrasound-based diagnoses is that the quality of the ultrasound images produced depends directly on the skill of the physician operating the probe. This is because physicians have to constantly adjust the probe position to obtain a cross section of the target organ, which is constantly shifting due to patient respiratory motions. Therefore, we developed an ultrasound diagnostic robot that works in cooperation with a visual servo system based on deep learning that will help alleviate the burdens imposed on physicians. METHODS: Our newly developed robotic ultrasound diagnostic system consists of three robots: an organ tracking robot (OTR), a robotic bed, and a robotic supporting arm. Additionally, we used different image processing methods (YOLOv5s and BiSeNet V2) to detect the target kidney location, as well as to evaluate the appropriateness of the obtained ultrasound images (ResNet 50). Ultimately, the image processing results are transmitted to the OTR for use as motion commands. RESULTS: In our experiments, the highest effective tracking rate (0.749) was obtained by YOLOv5s with Kalman filtering, while the effective tracking rate was improved by about 37% in comparison with cases without such filtering. Additionally, the appropriateness probability of the ultrasound images obtained during the tracking process was also the highest and most stable. The second highest tracking efficiency value (0.694) was obtained by BiSeNet V2 with Kalman filtering and was a 75% improvement over the case without such filtering. CONCLUSION: While the most efficient tracking achieved is based on the combination of YOLOv5s and Kalman filtering, the combination of BiSeNet V2 and Kalman filtering was capable of detecting the kidney center of gravity closer to the kidney's actual motion state. Furthermore, this model could also measure the cross-sectional area, maximum diameter, and other detailed information of the target kidney, which meant it is more practical for use in actual diagnoses.

Development and future prospective of treatment for localized prostate cancer with high-intensity focused ultrasound.

High-intensity focused ultrasound (HIFU) was experimentally used for focal therapy for anti-cancer effects in prostate cancer (PC). Focal therapy is a diagnosis-based investigational treatment option for localized PC that cures clinically significant PC (csPC) while preserving the anatomical structures related to urinary and sexual function based on its spread observed using multi-parametric magnetic resonance imaging (mpMRI). The European Association of Urology indicated that the current status of focal therapy for localized PC was an investigational modality and encouraged prospective recording of outcomes and recruitment of suitable patients in 2018. During the last few years, large-population multi- and single-center prospective studies have investigated focal therapy as a treatment strategy for localized PC. In a multicenter prospective study with 5-year follow-up, failure-free survival, which was defined as avoidance of local salvage therapy (surgery or radiotherapy), systemic therapy, metastases, and prostate cancer-specific death, was 88%. In the previous studies, there was no significant influence on urinary function before and at 3 months after the treatment, although transient impairment was reported 1 month after the treatment. Pad- and leak-free continence was preserved in 80-100% of the patients after treatment. Erectile function was significantly impaired in the initial 3 months after treatment compared to the pretreatment values, but it improved 6 months after the focal therapy in the previous reports. Paired comparison studies and cohort studies with long-term follow-up will contribute to verifying this treatment's clinical outcomes for patients with localized PC.

A novel complementation method of an acoustic shadow region utilizing a convolutional neural network for ultrasound-guided therapy.

PURPOSE: Noise-free ultrasound images are essential for organ monitoring during regional ultrasound-guided therapy. When the affected area is located under the ribs, however, acoustic shadow is caused by the reflection of sound from hard tissues such as bone, and the image is output with missing information in this region. Therefore, in the present study, we attempt to complement the image in the missing area. METHODS: The overall flow of the complementation method to generate a shadow-free composite image is as follows. First, we constructed a binary classification method for the presence or absence of acoustic shadow on a phantom kidney based on a convolutional neural network. Second, we created a composite shadow-free image by searching for a suitable image from a time-series database and superimposing the corresponding area without shadow onto the missing area of the target image. In addition, we constructed and verified an automatic kidney mask generation method utilizing U-Net. RESULTS: The complementation accuracy for kidney tracking could be enhanced by template matching. Zero-mean normalized cross-correlation (ZNCC) values after complementation were higher than that of before complementation under four different data generation conditions: (i) changing the position of the bed of the robotic ultrasound diagnostic system in the translational direction, (ii) changing the probe angle in the translational direction, (iii) with the addition of rotational motion of the probe to condition (ii). Although there was large variation in the shape of the kidney contour in condition (iii), the proposed method improved the ZNCC value from 0.5437 to 0.5807. CONCLUSIONS: The effectiveness of the proposed method was demonstrated in phantom experiments. Verification of its effectiveness in real organs is necessary in future study.

Evaluation of ultrasonic fibrosis diagnostic system using convolutional network for ordinal regression.

PURPOSE: Diagnosis of liver fibrosis is important for establishing treatment and assessing the risk of carcinogenesis. Ultrasound imaging is an excellent diagnostic method as a screening test in terms of non-invasiveness and simplicity. The purpose of this study was to automatically diagnose liver fibrosis using ultrasound images to reduce the burden on physicians. METHODS: We proposed and implemented a system for extracting regions of liver parenchyma utilizing U-Net. Using regions of interest, the stage of fibrosis was classified as F0, F1, F2, F3, or F4 utilizing CORALNet, an ordinal regression model based on ResNet18. The effectiveness of the proposed system was verified. RESULTS: The system implemented using U-Net had a maximum mean Dice coefficient of 0.929. The results of classification of liver fibrosis utilizing CORALNet had a mean absolute error (MAE) of 1.22 and root mean square error (RMSE) of 1.60. The per-case results had a MAE of 1.55 and RMSE of 1.34. CONCLUSION: U-Net extracted regions of liver parenchyma from the images with high accuracy, and CORALNet showed effectiveness using ordinal information to classify fibrosis in the images. As a future task, we will study a model that is less dependent on teaching data.

The value of hepatobiliary phase in EOB-MRI in predicting hypervascularization outcome of non-hypervascular hypointense lesions in high-risk patients for hepatocellular carcinoma.

PURPOSE: To estimate the role of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid-enhanced MRI (EOB-MRI) in predicting hypervascularization outcome of non-hypervascular hypointense hepatic lesions in high-risk patients for hepatocellular carcinoma (HCC). METHODS: Under the premise of non-hyperenhance in arterial phase (AP) and hypointensity in hepatobiliary phase (HBP) of EOB-MRI, 29 fresh lesions from 22 patients with chronic viral hepatitis (median (range) age: 69(57-82) years) were prospectively enrolled. During continuously followed-up by EOB-MRI, lesional vascularity in AP, the signal intensity (SI) ratios of lesions-to-parenchyma in HBP images (post-contrast ratio) and adjusted enhancement with reference of unenhanced images (EOB enhancement ratio) were examined. RESULTS: After 644 (220-2912) days of follow-up, 20 lesions changed into hyperenhancement in AP of EOB-MRI (hypervascularized group), while nine remained non-hyperenhanced (maintained non-hypervascular group). There is no statistical difference of post-contrast ratio at the initial detection. The post-contrast ratios in hypervascularized group were different between each follow-up time point when followed-up ≥ three (P < 0.01) and four (P < 0.05) times, and exposed a linear downward trend with time. Between the hypervascularized and maintained non-hypervascular groups, there were significant differences in the post-contrast ratio at endpoint for three-times' follow-up (P < 0.001); and at the second (P = 0.037), third follow-up time points (P = 0.005), endpoint (P = 0.005) for four-times' follow-up. EOB enhancement ratio showed inter-group difference only at endpoint for three-times' follow-up (P = 0.008). CONCLUSION: For non-hypervascular, HBP hypointense hepatic lesions, decreasing trend of SI in HBP may early predict unfavorable hypervascularized outcome.

Estimating 3-dimensional liver motion using deep learning and 2-dimensional ultrasound images.

PURPOSE: The main purpose of this study is to construct a system to track the tumor position during radiofrequency ablation (RFA) treatment. Existing tumor tracking systems are designed to track a tumor in a two-dimensional (2D) ultrasound (US) image. As a result, the three-dimensional (3D) motion of the organs cannot be accommodated and the ablation area may be lost. In this study, we propose a method for estimating the 3D movement of the liver as a preliminary system for tumor tracking. Additionally, in current 3D movement estimation systems, the motion of different structures during RFA could reduce the tumor visibility in US images. Therefore, we also aim to improve the estimation of the 3D movement of the liver by improving the liver segmentation. We propose a novel approach to estimate the relative 6-axial movement (x, y, z, roll, pitch, and yaw) between the liver and the US probe in order to estimate the overall movement of the liver. METHOD: We used a convolutional neural network (CNN) to estimate the 3D displacement from two-dimensional US images. In addition, to improve the accuracy of the estimation, we introduced a segmentation map of the liver region as the input for the regression network. Specifically, we improved the extraction accuracy of the liver region by using a bi-directional convolutional LSTM U-Net with densely connected convolutions (BCDU-Net). RESULTS: By using BCDU-Net, the accuracy of the segmentation was dramatically improved, and as a result, the accuracy of the movement estimation was also improved. The mean absolute error for the out-of-plane direction was 0.0645 mm/frame. CONCLUSION: The experimental results show the effectiveness of our novel method to identify the movement of the liver by BCDU-Net and CNN. Precise segmentation of the liver by BCDU-Net also contributes to enhancing the performance of the liver movement estimation.

PRECEDE-PROCEED model based questionnaire and saliva tests for oral health checkup in adult.

Screening is a fundamental strategy for early detection, treatment, and prevention of progression of oral disease and those at high risk for oral disease. While numerous screening tools exist, questionnaires, and saliva tests are often suitable for screening. The questionnaire based on the PRECEDE-PROCEED model was developed, validated, and elucidated on the structural interrelationship between these two methods. In the current investigation, 311 adults had this questionnaire and saliva testing administered simultaneously during an occupational health checkup. The questionnaire was validated by classical test theory, item response theory, and path analysis. Through structural equation modeling, it was found that self-care guidance may be an important role of the family dentist. In addition, self-awareness of oral symptoms was significantly related to saliva test results. However, self-administered questionnaires and saliva tests together may provide more information than either of them alone for the detection, treatment, and prevention of progression of oral disease. Thus, simultaneous application of self-administered questionnaires and saliva tests is recommended during oral health checkups for adults.

A new device for fiducial registration of image-guided navigation system for liver RFA.

PURPOSE: Radiofrequency ablation for liver tumors (liver RFA) is widely performed under ultrasound guidance. However, discriminating between the tumor and the needle is often difficult because of cavitation caused by RFA-induced coagulation. An unclear ultrasound image can lead to complications and tumor residue. Therefore, image-guided navigation systems based on fiducial registration have been developed. Fiducial points are usually set on a patient's skin. But the use of internal fiducial points can improve the accuracy of navigation. In this study, a new device is introduced to use internal fiducial points using 2D US. METHODS: 3D Slicer as the navigation software, Polaris Vicra as the position sensor, and two target tumors in a 3D abdominal phantom as puncture targets were used. Also, a new device that makes it possible to obtain tracking coordinates in the body was invented. First, two-dimensional reslice images from the CT images using 3D Slicer were built. A virtual needle was displayed on the two-dimensional reslice image, reflecting the movement of the actual needle after fiducial registration. A phantom experiment using three sets of fiducial point configurations: one conventional case using only surface points, and two cases in which the center of the target tumor was selected as a fiducial point was performed. For each configuration, one surgeon punctured each target tumor ten times under guidance from the 3D Slicer display. Finally, a statistical analysis examining the puncture error was performed. RESULTS: The puncture error for each target tumor decreased significantly when the center of the target tumor was included as one of the fiducial points, compared with when only surface points were used. CONCLUSION: This study introduces a new device to use internal fiducial points and suggests that the accuracy of image-guided navigation systems for liver RFA can be improved by using the new device.

Ultrasound image based visual servoing for moving target ablation by high intensity focused ultrasound.

BACKGROUND: Although high intensity focused ultrasound (HIFU) is a promising technology for tumor treatment, a moving abdominal target is still a challenge in current HIFU systems. In particular, respiratory-induced organ motion can reduce the treatment efficiency and negatively influence the treatment result. In this research, we present: (1) a methodology for integration of ultrasound (US) image based visual servoing in a HIFU system; and (2) the experimental results obtained using the developed system. MATERIALS AND METHODS: In the visual servoing system, target motion is monitored by biplane US imaging and tracked in real time (40 Hz) by registration with a preoperative 3D model. The distance between the target and the current HIFU focal position is calculated in every US frame and a three-axis robot physically compensates for differences. Because simultaneous HIFU irradiation disturbs US target imaging, a sophisticated interlacing strategy was constructed. RESULTS: In the experiments, respiratory-induced organ motion was simulated in a water tank with a linear actuator and kidney-shaped phantom model. Motion compensation with HIFU irradiation was applied to the moving phantom model. Based on the experimental results, visual servoing exhibited a motion compensation accuracy of 1.7 mm (RMS) on average. Moreover, the integrated system could make a spherical HIFU-ablated lesion in the desired position of the respiratory-moving phantom model. CONCLUSIONS: We have demonstrated the feasibility of our US image based visual servoing technique in a HIFU system for moving target treatment.

Novel and Simple Ultrasonographic Methods for Estimating the Abdominal Visceral Fat Area.

OBJECTIVES: To evaluate the abdominal visceral fat area (VFA), we developed novel ultrasonographic (US) methods for estimating. METHODS: 100 male volunteers were recruited, and their VFA was calculated by two novel US methods, the triangle method and the ellipse method. The VFA calculated by these methods was compared with the VFA calculated by CT. RESULTS: Both the VFA calculated by the triangle method (r = 0.766, p < 0.001) and the ellipse method (r = 0.781, p < 0.001) showed a high correlation coefficient with the VFA calculated by CT. Also, the VFA calculated by our novel methods were significantly increased in subjects with one or more metabolic risk factors than in those without any risk factors. Furthermore, the correlation coefficients obtained using the two methods were enhanced by the addition of multiple regression analysis (with the triangle method, r = 0.8586, p < 0.001; with the ellipse method, r = 0.8642, p < 0.001). CONCLUSIONS: The VFA calculated by the triangle or ellipse method showed a high correlation coefficient with the VFA calculated by CT. These US methods are easy to use, they involve no radiation exposure, and the measurements can be conducted frequently. We hope that our simple methods would be widely adopted for the evaluation of VFA.

Automatic distance measurement of abdominal aorta for ultrasonography-based visceral fat estimation.

Ultrasonography-based visceral fat estimation is a promising method to assess central obesity, which is associated with metabolic syndrome. The key to this method is to measure three types of distance in the ultrasound image. The most important one is the distance from the skin surface to the posterior wall of the abdominal aorta. We present a novel automatic measurement method to calculate this distance using 1D ultrasound signal processing. It is different from the conventional 2D image processing based methods which have high failure rate when the target is blurred or partially imaged. The proposed method identifies the waveforms of the aorta along a group of ultrasound scan lines and a rating mechanism is introduced to choose the best waveform for distance calculation. The robustness and accuracy of the method were evaluated by experiments based on clinical data.

Visual servoing for a US-guided therapeutic HIFU system by coagulated lesion tracking: a phantom study.

BACKGROUND: Applying ultrasound (US)-guided high-intensity focused ultrasound (HIFU) therapy for kidney tumours is currently very difficult, due to the unclearly observed tumour area and renal motion induced by human respiration. In this research, we propose new methods by which to track the indistinct tumour area and to compensate the respiratory tumour motion for US-guided HIFU treatment. METHODS: For tracking indistinct tumour areas, we detect the US speckle change created by HIFU irradiation. In other words, HIFU thermal ablation can coagulate tissue in the tumour area and an intraoperatively created coagulated lesion (CL) is used as a spatial landmark for US visual tracking. Specifically, the condensation algorithm was applied to robust and real-time CL speckle pattern tracking in the sequence of US images. Moreover, biplanar US imaging was used to locate the three-dimensional position of the CL, and a three-actuator system drives the end-effector to compensate for the motion. Finally, we tested the proposed method by using a newly devised phantom model that enables both visual tracking and a thermal response by HIFU irradiation. RESULTS: In the experiment, after generation of the CL in the phantom kidney, the end-effector successfully synchronized with the phantom motion, which was modelled by the captured motion data for the human kidney. The accuracy of the motion compensation was evaluated by the error between the end-effector and the respiratory motion, the RMS error of which was approximately 2 mm. CONCLUSION: This research shows that a HIFU-induced CL provides a very good landmark for target motion tracking. By using the CL tracking method, target motion compensation can be realized in the US-guided robotic HIFU system.

Fast and accurate ultrasonography for visceral fat measurement.

Visceral fat area (VFA) has close relationship with hypertension, diabetes and cardiovascular disease, and therefore serve as a reliable indicator of these diseases. Abdominal computed tomography (CT) enables precise quantification of the VFA and has been considered as the gold standard for VFA assessment. In this paper, we develope a novel method to quickly and accurately measure the VFA with ultrasonography (US). We evaluated the novel method on five volunteers and the diagnosis procedures lasted less than 30 seconds averagely. The simulation results by our method were compared with VFA estimated by abdominal CT. The correlation coefficient between them was 0.913 for men and 0.858 for women. And the mean deviation of between VFA by CT and by our method was 19.8 cm2 for men and 13.3 cm2 for women.