Experimental validation of acoustic and thermal modeling in heterogeneous phantoms using the hybrid angular spectrum method

Abstract

Purpose: The aim was to quantitatively validate the hybrid angular spectrum (HAS) algorithm, a rapid wave propagation technique for heterogeneous media, with both pressure and temperature measurements. Methods: Heterogeneous tissue-mimicking phantoms were used to evaluate the accuracy of the HAS acoustic modeling algorithm in predicting pressure and thermal patterns. Acoustic properties of the phantom components were measured by a through-transmission technique while thermal properties were measured with a commercial probe. Numerical models of each heterogeneous phantom were segmented from 3D MR images. Cylindrical phantoms 30-mm thick were placed in the pre-focal field of a focused ultrasound beam and 2D pressure measurements obtained with a scanning hydrophone. Peak pressure, full width at half maximum, and normalized root mean squared difference (RMSDn) between the measured and simulated patterns were compared. MR-guided sonications were performed on 150-mm phantoms to obtain MR temperature measurements. Using HAS-predicted power density patterns, temperature simulations were performed. Experimental and simulated temperature patterns were directly compared using peak and mean temperature plots, RMSDn metrics, and accuracy of heating localization. Results: The average difference between simulated and hydrophone-measured peak pressures was 9.0% with an RMSDn of 11.4%. Comparison of the experimental MRI-derived and simulated temperature patterns showed RMSDn values of 10.2% and 11.1% and distance differences between the centers of thermal mass of 2.0 and 2.2 mm. Conclusions: These results show that the computationally rapid hybrid angular spectrum method can predict pressure and temperature patterns in heterogeneous models, including uncertainties in property values and other parameters, to within approximately 10%.

The influence of bone model geometries on the determination of skull acoustic properties

“…We employed the hybrid angular spectrum (HAS) technique 19 to model ultrasound wave propagation. HAS extends the well‐known traditional angular spectrum method 20,21 to inhomogeneous models that more accurately represent complex tissue structures 19,22–24 . Vyas and Christensen found that HAS approximates the accuracy of the finite‐difference time‐domain technique with significantly shorter computation times 19 .…”

“…HAS extends the well-known traditional angular spectrum method 20,21 to inhomogeneous models that more accurately represent complex tissue structures. 19,[22][23][24] Vyas and Christensen found that HAS approximates the accuracy of the finitedifference time-domain technique with significantly shorter computation times. 19 Because HAS is more computationally efficient than most wave modeling strategies, it presents a promising alternative when performing iterative and computationally heavy optimization tasks.…”

Robust deep learning estimation of cortical bone porosity from MR T1-weighted images for individualized transcranial focused ultrasound planning

“…This is a significant problem and raises the concern that ongoing human studies using LOS may not be conclusive. Finitedifference time domain [13][14][15][16], hybrid angle spectrum [12,[17][18][19][20][21][22][23] or pseudo-spectral modeling [24][25][26] have been used for modeling of acoustic propagation through bone, however all those tools require individualized maps of the speed-of-sound and acoustic attenuation parameters as inputs. Those have traditionally been estimated using CT [27][28][29], but this can be difficult to justify as this increases radiation exposure and introduces cross-modality registration errors when using MRI for neuronavigation.…”