real-time-monitoring-high-intensity-focused-ultrasound-hifu-ablation

Real-time Monitoring of High Intensity Focused Ultrasound (HIFU) Ablation of <em>In Vitro</em> Canine Livers Using Harmonic Motion Imaging for Focused Ultrasound (HMIFU)

Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a technique that can perform and monitor high-intensity focused ultrasound (HIFU) ablation. An ...

Columbia University

Columbia College

Ultrasound (US) scanners typically apply lossy, non-linear modifications to the US data for visualization purposes. The resulting images are then stored as compressed video data. Some system manufacturers provide dedicated software for quantification purposes to eliminate such processing distortions, at least partially. This is currently the recommended approach for quantitatively assessing changes in contrast-agent concentration from clinical data. However, the machine-specific access to US data and the limited set of analysis functionalities offered by each dedicated-software package make it difficult to perform comparable analyses with different US systems. The objective of this work was to establish if linearization of compressed video images obtained with an arbitrary US system can provide an alternative to dedicated-software analysis of machine-specific files for the estimation of echo-power. For this purpose, an Aplio 50 system (Toshiba Medical Systems, Tochigi, Japan), coupled with dedicated CHI-Q (Contrast Harmonic Imaging Quantification) software by Toshiba Medical Systems, was used. Results were compared with two approaches that apply algorithms to estimate relative echo-power from compressed video images: commercially available VueBox software by Bracco Suisse SA (Geneva, Switzerland) and in-laboratory software called PixPower. The echo-power estimated by CHI-Q analysis indicated a strong linear relationship versus agent concentration in vitro (R(2) ≥ 0.9996) for dynamic range (DR) settings of DR60 and DR80, with slopes between 9.22 and 9.57 dB/decade (p = 0.05). These values approach the theoretically predicted dependence of 10.0 dB/decade (equivalent to 3 dB for each concentration doubling). Echo-power estimations obtained from compressed video images with VueBox and PixPower also exhibited strong linear proportionality with concentration (R(2) ≥ 0.9996), with slopes between 9.30 and 9.68 dB/decade (p = 0.05). On an independent in vivo data set (N = 24), the difference in echo-power estimation between CHI-Q and each of the other two approaches was calculated after excluding regions that contain pixels affected by saturated or thresholded pixel values. The mean difference in estimates (expressed in decibels) was -0.25 dB between VueBox and CHI-Q (95% confidence interval: -0.75 to 0.26 dB) and -0.17 dB between PixPower and CHI-Q (95% confidence interval: -0.67 to 0.13 dB). To achieve linearization of data, one of the approaches (VueBox) requires calibration files provided by the software manufacturer for each machine type and setting. The other (PixPower) requires empirical correction of the imaging dynamic range based on ground truth data. These requirements could potentially be removed if US system manufacturers were willing to make relevant information on the applied processing publically available. Reliable echo-power estimation from linearized data would facilitate inclusion of different US systems in multicentric studies and more widespread implementation of emerging techniques for quantitative analysis of contrast ultrasound.

Echo-power estimation from log-compressed video data in dynamic contrast-enhanced ultrasound imaging.

Perfusion parameter estimation from dynamic contrast-enhanced ultrasound (DCE-US) data relies on fitting parametric models of flow to curves describing linear echo power as a function of time. The least squares criterion is generally used to fit these models to data. This criterion is optimal in the sense of maximum likelihood under the assumption of an additive white Gaussian noise. In the current work, it is demonstrated that this assumption is not held for DCEUS. A better-adapted maximum likelihood criterion based on a multiplicative model is proposed. It is tested on simulated bolus perfusion data and on 11 sequences acquired in vivo during bolus perfusion of contrast agent in the cortex of healthy murine kidney, an area where the perfusion is expected to be approximately homogeneous. Results on simulated data show a significant improvement (p < 0.05) of the precision and the accuracy for the estimations of perfusion parameters time to peak (TTP), wash-in rate (WiR), and mean transit time (MTT). On the 11 in vivo sequences, the new method leads to a significant reduction (p < 0.05) in the variation of parametric maps for 9 sequences for TTP and 10 sequences for WiR and MTT. The mean percent decreases of the coefficient of variation are 40%, 25%, and 59% for TTP, WiR, and MTT, respectively. This method should contribute to a more robust and accurate estimation of perfusion parameters and an improved resolution of parametric imaging.

A multiplicative model for improving microvascular flow estimation in dynamic contrast-enhanced ultrasound (DCE-US): theory and experimental validation.

The aim of this study was to evaluate the capacity of BR55, an ultrasound contrast agent specifically targeting vascular endothelial growth factor receptor 2 (VEGFR2), to distinguish the specific anti-VEGFR2 therapy effect of sunitinib from other anti-angiogenic effects of a therapy (imatinib) that does not directly inhibit VEGFR2. Sunitinib, imatinib and placebo were administered daily for 11 d (264 h) to 45 BalbC mice bearing ectopic CT26 murine colorectal carcinomas. During the course of therapy, B-mode ultrasound, contrast-enhanced ultrasound and VEGFR2-targeted contrast-enhanced ultrasound were performed to assess tumor morphology, vascularization and VEGFR2 expression, respectively. The angiogenic effects on these three aspects were characterized using tumor volume, contrast-enhanced area and differential targeted enhancement. Necrosis, microvasculature and expression of VEGFR2 were also determined by histology and immunostaining. B-Mode imaging revealed that tumor growth was significantly decreased in sunitinib-treated mice at day 11 (p < 0.05), whereas imatinib did not affect growth. Functional evaluation revealed that the contrast-enhanced area decreased significantly (p < 0.02) and by similar amounts under both anti-angiogenic treatments by day 8 (192 h): -23% for imatinib and -21% for sunitinib. No significant decrease was observed in the placebo group. Targeted contrast-enhanced imaging revealed lower differential targeted enhancement, that is, lower levels of VEGFR2 expression, in sunitinib-treated mice relative to placebo-treated mice from 24 h (p < 0.05) and relative to both placebo- and imatinib-treated mice from 48 h (p < 0.05). Histologic assessment of tumors after the final imaging indicated that necrotic area was significantly higher for the sunitinib group (21%) than for the placebo (8%, p < 0.001) and imatinib (11%, p < 0.05) groups. VEGFR2-targeted ultrasound was able to sensitively differentiate the anti-VEGFR2 effect from the reduced area of tumor with functional flow produced by both anti-angiogenic agents. BR55 molecular imaging was, thus, able both to detect early therapeutic response to sunitinib in CT26 tumors as soon as 24 h after the beginning of the treatment and to provide early discrimination (48 h) between tumor response during anti-angiogenic therapy targeting VEGFR2 expression and response during anti-angiogenic therapy not directly acting on this receptor.

VEGFR2-Targeted Contrast-Enhanced Ultrasound to Distinguish between Two Anti-Angiogenic Treatments.

Harmonic motion imaging (HMI) is a radiationforce- based elasticity imaging technique that tracks oscillatory tissue displacements induced by sinusoidal ultrasonic radiation force to assess the resulting oscillatory displacement denoting the underlying tissue stiffness. The objective of this study was to evaluate the feasibility of HMI in pancreatic tumor detection and high-intensity focused ultrasound (HIFU) treatment monitoring. The HMI system consisted of a focused ultrasound transducer, which generated sinusoidal radiation force to induce oscillatory tissue motion at 50 Hz, and a diagnostic ultrasound transducer, which detected the axial tissue displacements based on acquired radio-frequency signals using a 1-D cross-correlation algorithm. For pancreatic tumor detection, HMI images were generated for pancreatic tumors in transgenic mice and normal pancreases in wild-type mice. The obtained HMI images showed a high contrast between normal and malignant pancreases with an average peak-to-peak HMI displacement ratio of 3.2. Histological analysis showed that no tissue damage was associated with HMI when it was used for the sole purpose of elasticity imaging. For pancreatic tumor ablation monitoring, the focused ultrasound transducer was operated at a higher acoustic power and longer pulse length than that used in tumor detection to simultaneously induce HIFU thermal ablation and oscillatory tissue displacements, allowing HMI monitoring without interrupting tumor ablation. HMI monitoring of HIFU ablation found significant decreases in the peak-to-peak HMI displacements before and after HIFU ablation with a reduction rate ranging from 15.8% to 57.0%. The formation of thermal lesions after HIFU exposure was confirmed by histological analysis. This study demonstrated the feasibility of HMI in abdominal tumor detection and HIFU ablation monitoring.

Harmonic motion imaging for abdominal tumor detection and high-intensity focused ultrasound ablation monitoring: an in vivo feasibility study in a transgenic mouse model of pancreatic cancer.

Thomas Payen

Department of Biomedical Engineering

Columbia University

Real-time Monitoring of High Intensity Focused Ultrasound (HIFU) Ablation of In Vitro Canine Livers Using Harmonic Motion Imaging for Focused Ultrasound (HMIFU)

Thomas Payen

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Biomedical Engineering

Columbia University

Real-time Monitoring of High Intensity Focused Ultrasound (HIFU) Ablation of In Vitro Canine Livers Using Harmonic Motion Imaging for Focused Ultrasound (HMIFU)

Department of Biomedical Engineering