Method for enhancing the accuracy of in vivo sound velocity estimation

1989 ◽  
Vol 85 (6) ◽  
pp. 2699-2699
Author(s):  
Jonathan Ophir
Keyword(s):  
Sound Velocity ◽  
Velocity Estimation

scholarly journals Ultrasonic Heating Detects Lipiodol Deposition within Liver Tumors after Transarterial Embolization: An In Vivo Approach

Biology ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 901
Author(s):  
Natsuhiko Saito ◽  
Toshihiro Tanaka ◽  
Kiyoyuki Minamiguchi ◽  
Ryosuke Taiji ◽  
Hideyuki Nishiofuku ◽  
...  
Keyword(s):  
Sound Velocity ◽  
Temperature Coefficient ◽  
Rat Liver ◽  
Liver Tumors ◽  
Transarterial Embolization ◽  
Rate Of Change ◽  
Accumulation Ratio ◽  
Ct Value ◽  
The Mean

Computed tomography (CT) is the standard method to evaluate Lipiodol deposition after transarterial embolization (TAE) for a long period. However, iodine but not Lipiodol can be observed on CT. A minimally invasive other method to detect Lipiodol has been needed to evaluate accurate evaluation after procedure. The purpose of this study was to evaluate the efficacy of using the rate of change in sound velocity caused by ultrasonic heating to reflect Lipiodol accumulation after TAE in a rat liver tumor model. We analyzed the association of this developed technique with CT images and histological findings. Eight rats bearing N1S1 cells were prepared. After confirmation of tumor development in a rat liver, Lipiodol was injected via the hepatic artery. Seven days after TAE, CT scan and sound velocity changes caused by ultrasonic heating were measured, and then the rats were sacrificed. An ultrasonic pulse-echo method was used to measure the sound velocity. The temperature coefficient of the sound velocity in each treated tumor was evaluated and compared with the mean CT value and the histological Lipiodol accumulation ratio. Pearson’s correlation coefficients were calculated to assess the correlation between the measured values. The correlation coefficient (r) of the mean CT value and histological Lipiodol accumulation ratio was 0.835 (p = 0.010), which was considered statistically significant. Also, those of the temperature coefficient of the sound velocity and the histological Lipiodol accumulation ratio were statistically significant (r = 0.804; p = 0.016). To our knowledge, this is the first study that reported the efficacy of ultrasonic heating to detect Lipiodol accumulation in rat liver tumors after TAE. Our results suggest that the rate of change in sound velocity caused by ultrasonic heating can be used to evaluate Lipiodol accumulation in liver tumors after TAE, and thus could represent an alternative to CT in this application. This new innovative technique is easy to treat and less invasive in terms of avoiding radiation compared with CT.

scholarly journals FPGA Implementation of a Single Step MFCV Estimator Based on EMG in Diabetic Neuropathy

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Daniela De Venuto ◽  
Giovanni Mezzina
Keyword(s):  
Diabetic Neuropathy ◽  
Real Time ◽  
Muscle Fibre ◽  
Diagnostic System ◽  
Correlation Method ◽  
Single Step ◽  
Velocity Estimation ◽  
In Vivo Test ◽  
Starting Point

This paper details the design and the hardware implementation of a real-time diagnostic system based on FPGA for the muscle fibre conduction velocity estimation (MFCV). The MFCV is considered as a principal monitoring index for diabetic neuropathy (DPN), as well as in muscle fatigue assessment, to evaluate the muscle fibre status. The FPGA platform evaluates the MFCV during dynamic contractions (e.g., gait), by exploiting a multichannel sensing system composed of 4 wireless surface EMG electrodes, placed in pair on each leg. Raw data are digitized and made binary to create two bitstreams for each monitored limb. Then, a comparison between the two-bit streamed EMGs extracted from the same leg is carried out. The comparison, which allows extracting the MFCV, exploits a computationally light version of the cross-correlation method. The overall architecture implemented and validated on an Altera Cyclone V FPGA is HPS-free and exploits 22.5% ALMs, 10,874 ALUTs, 9.81% registers, 3.36% block memory, and <2.7% of the total wires available on the platform. The choice of FPGA as computing system lies in the possibility to determine resource utilization, related timing constraints for a future real-time ASIC implementation in wearable applications. From the actual muscle contraction during gait (cyclical starting point of the computing), the system spends about 316 ms to acquire useful data and 47.5 ms (on average) to process the signal and provide the output, dynamically dissipating 28.6 mW. The accuracy of the tool evaluation has been evaluated proving the repeatability of the measurements by in vivo test. In this context, 1250 contractions from each subject involved in a protocolled 10-meter walk have been acquired (n=10 subjects evaluated). On average, the same MFCV estimation has been extracted on 1184/1250 contractions (standard deviation of 11 contractions), reaching an accuracy of 94.7%. These estimations fully match the physiological value range reported in literature.

Feasibility of pulse wave velocity estimation from low frame rate US sequences in vivo

2017 ◽  
Author(s):  
Maria Zontak ◽  
Matthew Bruce ◽  
Michelle Hippke ◽  
Alan Schwartz ◽  
Matthew O'Donnell
Keyword(s):  
Pulse Wave Velocity ◽  
Wave Velocity ◽  
Pulse Wave ◽  
Velocity Estimation ◽  
Frame Rate ◽  
Low Frame Rate
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