Benjamin Castaneda

Tissue elasticity properties as biomarkers for prostate cancer

In this paper we evaluate tissue elasticity as a longstanding but qualitative biomarker for prostate cancer and sonoelastography as an emerging imaging tool for providing qualitative and quantitative measurements of prostate tissue stiffness. A Kelvin-Voigt Fractional Derivative (KVFD) viscoelastic model was used to characterize mechanical stress relaxation data measured from human prostate tissue samples. Mechanical testing results revealed that the viscosity parameter for cancerous prostate tissue is greater than that derived from normal tissue by a factor of approximately 2.4. It was also determined that a significant difference exists between normal and cancerous prostate tissue stiffness (p < 0.01) yielding an average elastic contrast that increases from 2.1 at 0.1 Hz to 2.5 at 150 Hz. Qualitative sonoelastographic results show promise for cancer detection in prostate and may prove to be an effective adjunct imaging technique for biopsy guidance. Elasticity images obtained with quantitative sonoelastography agree with mechanical testing and histological results. Overall, results indicate tissue elasticity is a promising biomarker for prostate cancer.

Quantitative characterization of viscoelastic properties of human prostate correlated with histology.

Quantification of mechanical properties of human prostate tissue is important for developing sonoelastography for prostate cancer detection. In this study, we characterized the frequency-dependent complex Youngs modulus of normal and cancerous prostate tissues in vitro by using stress relaxation testing and viscoelastic tissue modeling methods. After radical prostatectomy, small cylindrical tissue samples were acquired in the posterior region of each prostate. A total of 17 samples from eight human prostates were obtained and tested. Stress relaxation tests on prostate samples produced repeatable results that fit a viscoelastic Kelvin-Voigt fractional derivative (KVFD) model (r(2)>0.97). For normal (n = 8) and cancerous (n = 9) prostate samples, the average magnitudes of the complex Youngs moduli (|E*|) were 15.9 +/- 5.9 kPa and 40.4 +/- 15.7 kPa at 150 Hz, respectively, giving an elastic contrast of 2.6:1. Nine two-sample t-tests indicated that there are significant differences between stiffness of normal and cancerous prostate tissues in the same gland (p < 0.01). This study contributes to the current limited knowledge on the viscoelastic properties of the human prostate, and the inherent elastic contrast produced by cancer.

US Elastography of Breast and Prostate Lesions

Elastography is a technique that maps relative tissue stiffness. Ultrasonographic (US) elastography (sonoelastography) is a novel modality that is the subject of active research for clinical applications, primarily breast and prostate lesion imaging. Breast and prostate tumors generally have biomechanical properties different from those of normal tissues: Tumors are usually stiffer. This phenomenon is responsible for tissue contrast on elastograms. For the prostate gland and breast, the main image acquisition techniques are vibration sonoelastography and compression sonoelastography. The sonoelastographic appearances of several common breast lesions, including fibroadenomas, simple and complex cysts, ductal carcinomas, malignant lymph nodes, and hematomas, are reviewed. In addition, the US elastographic appearances of the normal prostate gland, prostate carcinomas, and benign prostate hyperplasia are illustrated. Potential pitfalls in the interpretation of elastograms, including false-positive and false-negative images, are illustrated. These imaging findings are derived from ongoing research because sonoelastography is not yet accepted for routine clinical use.

Quantitative sonoelastography for the in vivo assessment of skeletal muscle viscoelasticity

A novel quantitative sonoelastography technique for assessing the viscoelastic properties of skeletal muscle tissue was developed. Slowly propagating shear wave interference patterns (termed crawling waves) were generated using a two-source configuration vibrating normal to the surface. Theoretical models predict crawling wave displacement fields, which were validated through phantom studies. In experiments, a viscoelastic model was fit to dispersive shear wave speed sonoelastographic data using nonlinear least-squares techniques to determine frequency-independent shear modulus and viscosity estimates. Shear modulus estimates derived using the viscoelastic model were in agreement with that obtained by mechanical testing on phantom samples. Preliminary sonoelastographic data acquired in healthy human skeletal muscles confirm that high-quality quantitative elasticity data can be acquired in vivo. Studies on relaxed muscle indicate discernible differences in both shear modulus and viscosity estimates between different skeletal muscle groups. Investigations into the dynamic viscoelastic properties of (healthy) human skeletal muscles revealed that voluntarily contracted muscles exhibit considerable increases in both shear modulus and viscosity estimates as compared to the relaxed state. Overall, preliminary results are encouraging and quantitative sonoelastography may prove clinically feasible for in vivo characterization of the dynamic viscoelastic properties of human skeletal muscle.

Real-time sonoelastography of hepatic thermal lesions in a swine model

Sonoelastography has been developed as an ultrasound-based elasticity imaging technique. In this technique, external vibration is induced into the target tissue. In general, tissue stiffness is inversely proportional to the amplitude of tissue vibration. Imaging tissue vibration will provide the elasticity distribution in the target region. This study investigated the feasibility of using real-time sonoelastography to detect and estimate the volume of thermal lesions in porcine livers in vivo. A total of 32 thermal lesions with volumes ranging from 0.2to5.3cm3 were created using radiofrequency ablation (RFA) or high-intensity focused ultrasound (HIFU) technique. Lesions were imaged using sonoelastography and coregistered B-mode ultrasound. Volumes were reconstructed from a sequence of two-dimensional scans. The comparison of sonoelastographic measurements and pathology findings showed good correlation with respect to the area of the lesions (r2=0.8823 for RFA lesions, r2=0.9543 for HIFU lesions). In addition, good correspondence was found between three-dimensional sonoelastography and gross pathology (3.6% underestimate), demonstrating the feasibility of sonoelastography for volume estimation of thermal lesions. These results support that sonoelastography outperforms conventional B-mode ultrasound and could potentially be used for assessment of thermal therapies.

Prostate Cancer Detection Using Crawling Wave Sonoelastography

Crawling wave (CrW) sonoelastography is an elasticity imaging technique capable of estimating the localized shear wave speed in tissue and, therefore, can provide a quantitative estimation of the Youngs modulus for a given vibration frequency. In this paper, this technique is used to detect cancer in excised human prostates and to provide quantitative estimations of the viscoelastic properties of cancerous and normal tissues. Image processing techniques are introduced to compensate for attenuation and reflection artifacts of the CrW images. Preliminary results were obtained with fifteen prostate glands after radical prostatectomy. The glands were vibrated at 100, 120 and 140Hz. At each frequency, three cross-sections of the gland (apex, mid-gland and base) were imaged using CrW Sonoelastography and compared to corresponding histological slices. Results showed good spatial correspondence with histology and an 80% accuracy in cancer detection. In addition, shear velocities for cancerous and normal tissues were estimated as 4.75±0.97 m/s and 3.26±0.87 m/s, respectively.

5C-6 Muscle Tissue Characterization Using Quantitative Sonoelastography: Preliminary Results

A quantitative sonoelastographic technique for skeletal muscle tissue characterization is introduced. Experimental data was collected in both ex vivo bovine and in vivo human skeletal muscle tissue. Crawling wave sonoelastographic data was processed using a quantitative technique for estimating local shear wave speed distributions. Results on ex vivo skeletal muscle samples demonstrate shear wave anisotropy and existence of fast and slow shear waves corresponding to propagation parallel and perpendicular to muscle fibers. Comparison of relative frequency-dependent changes between shear wave speed estimates for both shear wave propagation parallel and perpendicular to muscle fibers suggests increased viscoelastic effects for the former. Preliminary sonoelastographic data from two healthy human subjects was acquired in the relaxed rectus femoris muscles. Results demonstrate that quantitative elasticity data can be reproducibly acquired in vivo. Overall, preliminary results are encouraging and quantitative sonoelastography may prove clinically feasible for the in vivo characterization of skeletal muscle in health and disease.

Semi-automated segmentation of the prostate gland boundary in ultrasound images using a machine learning approach

This paper presents a semi-automated algorithm for prostate boundary segmentation from three-dimensional (3D) ultrasound (US) images. The US volume is sampled into 72 slices which go through the center of the prostate gland and are separated at a uniform angular spacing of 2.5 degrees. The approach requires the user to select four points from slices (at 0, 45, 90 and 135 degrees) which are used to initialize a discrete dynamic contour (DDC) algorithm. 4 Support Vector Machines (SVMs) are trained over the output of the DDC and classify the rest of the slices. The output of the SVMs is refined using binary morphological operations and DDC to produce the final result. The algorithm was tested on seven ex vivo 3D US images of prostate glands embedded in an agar mold. Results show good agreement with manual segmentation.

A 3D assessment tool for accurate volume measurement for monitoring the evolution of cutaneous Leishmaniasis wounds

Clinical assessment and outcome metrics are serious weaknesses identified on the systematic reviews of cutaneous Leishmaniasis wounds. Methods with high accuracy and low-variability are required to standarize study outcomes in clinical trials. This work presents a precise, complete and noncontact 3D assessment tool for monitoring the evolution of cutaneous Leishmaniasis (CL) wounds based on a 3D laser scanner and computer vision algorithms. A 3D mesh of the wound is obtained by a commercial 3D laser scanner. Then, a semi-automatic segmentation using active contours is performed to separate the ulcer from the healthy skin. Finally, metrics of volume, area, perimeter and depth are obtained from the mesh. Traditional manual 3D and 3D measurements are obtained as a gold standard. Experiments applied to phantoms and real CL wounds suggest that the proposed 3D assessment tool provides higher accuracy (error <;2%) and precision rates (error <;4%) than conventional manual methods (precision error <; 35%). This 3D assessment tool provides high accuracy metrics which deserve more formal prospective study.

P1C-9 Prostate Cancer Detection Based on Three Dimensional Sonoelastography

In this paper, we evaluate the performance of sonoelastography for prostate cancer detection. Ultrasound (US) B-mode and sonoelastographic volumes were acquired from five prostate glands ex vivo. Additionally, one more gland was imaged in vivo using a transrectal US probe. Semi-automatic algorithms were used to segment the surface of the gland from the B-mode volume and the tumors from sonoelastographic data. To assess the detection performance, three dimensional (3D) sonoelastographic findings were compared in size and position to 3D histological data. Sonoelastography detected seven out of nine cancers in the ex vivo prostate glands and two out of three malignant masses in the in vivo experiment. Overall, 3D sonoelastography has shown potential for prostate cancer detection albeit based on limited data.