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Ultrasound-based relative elastic modulus imaging for visualizing thermal ablation zones in a porcine model.

ABSTRACT: The feasibility of using ultrasound-based elastic modulus imaging to visualize thermal ablation zones in an in vivo porcine model is reported. Elastic modulus images of soft tissues are estimated as an inverse optimization problem. Ultrasonically measured displacement data are utilized as inputs to determine an elastic modulus distribution that provides the best match to this displacement field. A total of 14 in vivo thermal ablation zones were investigated in this study. To determine the accuracy of delineation of each thermal ablation zone using elastic modulus imaging, the dimensions (lengths of long and short axes) and the area of each thermal ablation zone obtained from an elastic modulus image were compared to the corresponding gross pathology photograph of the same ablation zone. Comparison of elastic modulus imaging measurements and gross pathology measurements showed high correlation with respect to the area of thermal ablation zones (Pearson coefficient = 0.950 and p < 0.0001). The radiological-pathological correlation was slightly lower (correlation = 0.853, p < 0.0001) for strain imaging among these 14 in vivo ablation zones. We also found that, on average, elastic modulus imaging can more accurately depict thermal ablation zones, when compared to strain imaging (14.7% versus 22.3% absolute percent error in area measurements, respectively). Furthermore, elastic modulus imaging also provides higher (more than a factor of 2) contrast-to-noise ratios for evaluating these thermal ablation zones than those on corresponding strain images, thereby reducing inter-observer variability. Our preliminary results suggest that elastic modulus imaging might potentially enhance the ability to visualize thermal ablation zones, thereby improving assessment of ablative therapies.

SUBMITTER: Jiang J

PROVIDER: S-EPMC3068604 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature

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Ultrasound-based relative elastic modulus imaging for visualizing thermal ablation zones in a porcine model.

Jiang Jingfeng J Brace Chris C Andreano Anita A DeWall Ryan J RJ Rubert Nick N Fisher Ted G TG Varghese Tomy T Lee Fred F Hall Timothy J TJ

Physics in medicine and biology 20100330 8

The feasibility of using ultrasound-based elastic modulus imaging to visualize thermal ablation zones in an in vivo porcine model is reported. Elastic modulus images of soft tissues are estimated as an inverse optimization problem. Ultrasonically measured displacement data are utilized as inputs to determine an elastic modulus distribution that provides the best match to this displacement field. A total of 14 in vivo thermal ablation zones were investigated in this study. To determine the accura ...[more]

PMID: 20354279

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Project description:This work explored an elementwise approach to model transcranial MRI-guided focused ultrasound (TcMRgFUS) thermal ablation, a noninvasive approach to neurosurgery. Each element of the phased array transducer was simulated individually and could be simultaneously loaded into computer memory, allowing for rapid (~2.5 s) calculation of the pressure field for different phase offsets used for beam steering and aberration correction. We simulated the pressure distribution for 431 sonications in 32 patients, applied the phase and magnitude values used during treatment, and estimated the resulting temperature rise. We systematically varied the relationship between CT (computerized tomography)-derived skull density and the acoustic attenuation and sound speed to obtain the best agreement between the predictions and MR temperature imaging (MRTI). The optimization was validated with simulations of 396 sonications from 40 additional treatments. After optimization, the predicted and measured heating agreed well (R2: 0.74 patients 1-32; 0.71 patients 33-72). The dimensions and obliquity of the heating in the simulated temperature maps were correlated with the MRTI (R2: 0.62, 0.74, respectively), but the measured heating was more spatially diffuse. The energy needed to achieve ablation varied by an order of magnitude (3.3-36.1 kJ). While this elementwise approach required more computation time up front (the combined simulation matrices were approximately 4.6 times higher than a single large simulation), it could be performed in parallel on a computing cluster. It allows for rapid calculation of the three-dimensional heating at the focus for different phase and magnitude values on the array. We also show how this approach can be used to optimize the relationship between CT-derived skull density and acoustic properties. While the relationships found here need further validation in a larger patient population, these results demonstrate the promise of this approach to model TcMRgFUS.

Project description:PurposeThe goal of this study was to develop and evaluate a volumetric three-dimensional (3D) approach to improve the accuracy of ablation margin assessment following thermal ablation of hepatic tumors.MethodsThe 3D margin assessment technique was developed to generate the new 3D assessment metrics: volumes of insufficient coverage (VICs) measuring volume of tissue at risk post-ablation. VICs were computed for the tumor and tumor plus theoretical 5- and 10-mm margins. The diagnostic accuracy of the 3D assessment to predict 2-year local tumor progression (LTP) was compared to that of manual 2D assessment using retrospective analysis of a patient cohort that has previously been reported as a part of an outcome-centered study. Eighty-six consecutive patients with 108 colorectal cancer liver metastases treated with radiofrequency ablation (2002-2012) were used for evaluation. The 2-year LTP discrimination power was assessed using receiver operating characteristic area under the curve (AUC) analysis.ResultsA 3D assessment of margins was successfully completed for 93 out of 108 tumors. The minimum margin size measured using the 3D method had higher discrimination power compared with the 2D method, with an AUC value of 0.893 vs. 0.790 (p = 0.01). The new 5-mm VIC metric had the highest 2-year LTP discrimination power with an AUC value of 0.923 (p = 0.004).ConclusionsVolumetric semi-automated 3D assessment of the ablation zone in the liver is feasible and can improve accuracy of 2-year LTP prediction following thermal ablation of hepatic tumors.Key points• More accurate prediction of local tumor progression risk using volumetric 3D ablation zone assessment can help improve the efficacy of image-guided percutaneous thermal ablation of hepatic tumors. • The accuracy of evaluation of ablation zone margins after thermal ablation of colorectal liver metastases can be improved using a volumetric 3D semi-automated assessment approach and the volume of insufficient coverage assessment metric. • The new 5-mm volume-of-insufficient-coverage metric, indicating the volume of tumor plus 5-mm margin that remained untreated, had the highest 2-year local tumor progression discrimination power.

Project description:In living tissues, mechanical stiffness and biological function are intrinsically linked. Alterations in the stiffness of tissues can induce pathological interactions that affect cellular activity and tissue function. Underlying connections between tissue stiffness and disease highlights the importance of accurate quantitative characterizations of soft tissue mechanics, which can improve our understanding of disease and inform therapeutic development. In particular, accurate measurement of lung mechanical properties has been especially challenging due to the anatomical and mechanobiological complexities of the lung. Discrepancies between measured mechanical properties of dissected lung tissue samples and intact lung tissues in vivo has limited the ability to accurately characterize integral lung mechanics. Here, we report a non-destructive vacuum-assisted method to evaluate mechanical properties of soft biomaterials, including intact tissues and hydrogels. Using this approach, we measured elastic moduli of rat lung tissue that varied depending on stress-strain distribution throughout the lung. We also observed that the elastic moduli of enzymatically disrupted lung parenchyma increased by at least 64%. The reported methodology enables assessment of the nonlinear viscoelastic characteristics of intact lungs under normal and abnormal (i.e., injured, diseased) conditions and allows measurement of mechanical properties of tissue-mimetic biomaterials for use in therapeutics or in vitro models. STATEMENT OF SIGNIFICANCE: Accurate quantification of tissue stiffness is critical for understanding mechanisms of disease and developing effective therapeutics. Current modalities to measure tissue stiffness are destructive and preclude accurate assessment of lung mechanical properties, as lung mechanics are determined by complex features of the intact lung. To address the need for alternative methods to assess lung mechanics, we report a non-destructive vacuum-based approach to quantify tissue stiffness. We applied this method to correlate lung tissue mechanics with tissue disruption, and to assess the stiffness of biomaterials. This method can be used to inform the development of tissue-mimetic materials for use in therapeutics and disease models, and could potentially be applied for in-situ evaluation of tissue stiffness as a diagnostic or prognostic tool.

Dataset Information

Ultrasound-based relative elastic modulus imaging for visualizing thermal ablation zones in a porcine model.

Publications

Ultrasound-based relative elastic modulus imaging for visualizing thermal ablation zones in a porcine model.

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