Evaluation of the algorithm for automatic identification of the common carotid artery in ARTSENS

Abstract

Arterial compliance (AC) is an indicator of the risk of cardiovascular diseases (CVDs) and it is generally estimated by B-mode ultrasound investigation. The number of sonologists in low- and middle-income countries is very disproportionate to the extent of CVD. To bridge this gap we are developing an image-free CVD risk screening tool-arterial stiffness evaluation for non-invasive screening (ARTSENS™) which can be operated with minimal training. ARTSENS uses a single element ultrasound transducer to investigate the wall dynamics of the common carotid artery (CCA) and subsequently measure the AC. Identification of the proximal and distal walls of the CCA, in the ultrasound frames, is an important step in the process of the measurement of AC. The image-free nature of ARTSENS creates some unique issues which necessitate the development of a new algorithm that can automatically identify the CCA from a sequence of A-mode radio-frequency (RF) frames. We have earlier presented the concept and preliminary results for an algorithm that employed clues from the relative positions and temporal motion of CCA walls, for identifying the CCA and finding the approximate wall positions. In this paper, we present the detailed algorithm and its extensive evaluation based on simulation and clinical studies. The algorithm identified the wall position correctly in more than 90% of all simulated datasets where the signal-to-noise ratio was greater than 3 dB. The algorithm was then tested extensively on RF data obtained from the CCA of 30 human volunteers, where it successfully located the arterial walls in more than 70% of all measurements. The algorithm could successfully reject frames where the CCA was not present thus assisting the operator to place the probe correctly in the image-free system, ARTSENS. It was demonstrated that the algorithm can be used in real-time with few trade-offs which do not affect the accuracy of CCA identification. A new method for depth range selection that leads to significant performance improvements has also been demonstrated.

Comparison of measurement of the augmentation index from ARTSENS and eTRACKING

“…ART-SENS uses just a single element ultrasound transducer which makes it very low-cost and portable compared to existing ultrasound-based technologies. In a series of earlier publications, we have demonstrated the capability of ARTSENS for the fully automated measurement of LAS and RAS [3][4][5][6][7][8][9][10]. It has been validated against the state-of-the-art Ep measurement device Hitachi-Aloka eTRACKING [9] and the cfPWV measurement device SphygmoCor [4] where we have demonstrated excellent agreement.…”

A Flexible Ultrasound Array for Local Pulse Wave Velocity Monitoring

“…In the low-frame-rate mode, the data of 2500 frames per second was extracted and reduced to 50 frames per second. The algorithm automatically identified the arterial wall locations according to the relative displacement relationship between the proximal wall and distal wall of the artery [ 32 ]. Once the arterial wall position was identified, the cross-correlation wall tracking algorithm was used to calculate the arterial distension waveform.…”

“…First, the original frames were filtered using a 4th order finite impulse response (FIR) band-pass filter with cut-off frequencies of 2 MHz and 8 MHz. The arterial wall auto-identification algorithm [ 32 ] was applied to locate the proximal and distal walls of the arteries. The positions at 1 mm in front of and behind the proximal and distal walls were selected as the regions of interest (ROIs) for tracing arterial distension.…”

Arterial compliance probe for cuffless evaluation of carotid pulse pressure

“…The acquired ultrasound echo frames and dual channel MPG signals were processed simultaneously, but independently in the digital domain. Construction of the arterial lumen diameter waveform from the ultrasound echo frames was performed using the fully automated algorithm of our clinically validated ARTSENS ® technology, demonstrated in a series of publications [ 27 – 29 , 33 – 35 ]. Briefly, in this technology locations of arterial near and far wall in the filtered ultrasound echoes were identified using wall detection algorithm [ 28 ].…”

“…Displacement of the identified wall locations was continuously tracked in successive frames using a correlation-based motion tracking technique [ 28 ], that enables capturing of the arterial diameter waveform, absolute ΔD and D D (in units of mm) in a beat-by-beat manner. Since the proposed approach is an image-free ultrasound technique [ 27 – 29 ], the quality of acquired ultrasound echoes was inspected continuously and displayed on the GUI by an application-specific signal quality parameterization algorithm [ 35 ].…”