Holmes, Philip M.

Applications, such as shear wave elastography and Doppler imaging, require high frame rates. Plane wave compounding (PWC) is widely used for these applications. Comb detection was proposed to combine the high frame rate of PWC and the high signal quality of focused beam scanning. Comb detection transmits multiple focused beams simultaneously to increase the frame rate. These comb beams are scanned laterally to cover the whole region-of-interest. The simultaneous multiple transmission of focused beams causes crosstalk between neighboring beams. Transmit crosstalk is related to the pressure field of transmit beams, and receive crosstalk is determined by the beam profile of receive beamforming. In this study, we varied f-number (F/N) and apodization window and measured their effects on crosstalk based on the pressure field and an arterial wall simulation using Field II. For transmit design, transmit apodization with a Hamming window significantly reduced crosstalk compared to a rectangular window and transmit F/N had little impact on the crosstalk. Regarding receive beamforming, a Hamming window led to lower crosstalk than the rectangular window and F/N from 1 to 5 suppressed crosstalk to below 30 dB. The effects of crosstalk in shear wave motion data from phantom experiments were also analyzed. Comb detection showed less motion artifact than PWC in phantom experiments.

Synthetic aperture (SA) acquisition allows for focusing at all points in ultrasound images during reconstruction. Both delay-and-sum (DAS) and delay-multiply-and-sum (DMAS) have been used to reconstruct SA images. An integral part of both algorithms is the aperture size used to define the beam shape with the f-number. Although f-number variation has been studied in DAS reconstruction, there has not been a systematic study on this topic for DMAS reconstruction in SA imaging. In this work, we evaluated the effects of f-number in DMAS reconstruction using an imaging phantom (CIRS 040GSE). We reconstructed DAS and DMAS images of hyperechoic, hypoechoic, and anechoic contrast targets, as well as point targets, while varying the transmit and receive f-numbers between 0 and 7 in 0.2 increments. Generalized contrast-to-noise ratio (gCNR) was measured for contrast targets. The full width at half maximum (FWHM) was evaluated using point targets. When imaging contrast targets, the DAS and DMAS algorithms responded very differently when varying the f-numbers. DMAS produced higher gCNR values with low transmit f-numbers and high receive f-numbers, while DAS produced higher gCNR values with high transmit and receive f-numbers. When evaluating FWHM, the optimal receive f-number was close to 1 for both algorithms.

Osteochondritis dissecans (OCD) is a focal joint defect that is prevalent among youth athletes. With the application of medical ultrasound, OCD of the humeral capitellum could be detected earlier and prevent surgery. In this work, we tested a modified Delay-Multiply-and-Sum (DMAS) reconstruction algorithm to evaluate how it affects medical ultrasound’s ability to detect OCD. Starting with the DMAS reconstruction algorithm described by Matrone et al. (2015), we modified the implementation of filtering and envelope detection steps. Delay-and-Sum (DAS), DMAS, and modified DMAS algorithms were tested on phantom and cadaveric models of capitellar OCD. The DMAS and modified DMAS images were histogram matched to the DAS image for quantitative comparison. By taking several profiles across the images of the artificial OCD lesions, we compared the lesion contrast and bone surface clarity produced by each algorithm. We found that the unmodified DMAS algorithm showed little improvement over the DAS algorithm, particularly after histogram matching. The modified DMAS algorithm showed a much greater improvement in the detection of OCD lesions compared to the DMAS algorithm. This modified DMAS algorithm could be used for other bone surface imaging applications. Future work includes evaluating these algorithms in vivo with patients diagnosed with OCD.

Osteochondritis dissecans (OCD) is a joint disease that is prevalent among youth athletes. Medical ultrasound is currently limited in its ability to detect and monitor OCD due to limitations of current Delay-and-Sum (DAS) reconstruction algorithms. In this work, we used a Delay-Multiply-and-Sum (DMAS) reconstruction algorithm to improve medical ultrasound’s ability to diagnose OCD. We artificially generated OCD lesions in unfixed cadaveric elbows and imaged them with a research ultrasound machine. We also imaged these cadaveric limbs with x-ray computed tomography (CT) with a high-resolution acquisition. These CT images were used as a gold standard for OCD geometry. We reconstructed the ultrasound images using both DAS and DMAS algorithms and compared them quantitatively by taking several profiles across the images of the artificial OCD lesions. The image metrics that we measured within these profiles were OCD lesion contrast, bone interface clarity, and lesion crack thickness accuracy. We found that the DMAS algorithm improved OCD lesion contrast by up to 26% when compared to DAS. We also found that the DMAS algorithm reduced the variability of bone interface clarity overall. Future work will involve an in vivo study, as well as optimization, of the DMAS algorithm for OCD lesion imaging.

Osteochondritis Dissecans (OCD) is a joint defect in which a crack in thesubchondral bone causes a separation of both subchondral bone and overlying cartilage from the bulk of the bone. Because there is an increased prevalence of OCD among youth athletes, an efficient, accurate, and non-ionizing screening method for this condition is being pursued. The aim of this project is to develop a clinical ultrasound image reconstruction algorithm that increases the detectability of bone surface defects, such as OCD. The proposed algorithm is a modified delay-multiply-and-sum (DMAS) algorithm that uses data acquired through synthetic aperture methods. The modifications made to the DMAS algorithm relevant to this work include transmit apodization and incoherent data summation. The modified DMAS algorithm was tested on data generated from k-Wave simulations and validated with experiments using bone mimicking material. Using both k-Wave and the bone mimicking material, we modeled fractures in the capitellum of the humerus with separations of 1, 2, and 3 mm. For experiments, we used synthetic aperture acquisitions using a Verasonics V1 system with a linear array (L7-4). The modified DMAS algorithm was found to enhance the clarity of bone surface defects when compared against DAS and DMAS algorithms.