It has been observed that many pathological process increase the elastic modulus of soft tissue compared to normal. In order to image tissue stiffness using ultrasound, a mechanical compression is applied to tissues of interest and local tissue deformation is measured. Based on the mechanical excitation, ultrasound stiffness imaging methods are classified as compression or strain imaging which is based on external compression and Acoustic Radiation Force Impulse (ARFI) imaging which is based on force generated by focused ultrasound. When ultrasound is focused on tissue, shear wave is generated in lateral direction and shear wave velocity is proportional to stiffness of tissues. The work presented in this paper investigates strain elastography and ARFI imaging in clinical cancer diagnostics using real time patient data. Ultrasound B-mode imaging, strain imaging, ARFI displacement and ARFI shear wave velocity imaging were conducted on 50 patients (31 Benign and 23 malignant categories) using Siemens S2000 machine. True modulus contrast values were calculated from the measured shear wave velocities. For ultrasound B-mode, ARFI displacement imaging and strain imaging, observed image contrast and Contrast to Noise Ratio were calculated for benign and malignant cancers. Observed contrast values were compared based on the true modulus contrast values calculated from shear wave velocity imaging. In addition to that, student unpaired t-test was conducted for all the four techniques and box plots are presented. Results show that, strain imaging is better for malignant cancers whereas ARFI imaging is superior than strain imaging and B-mode for benign lesions representations.
The elastic properties of tissue are related to tissue composition and pathological changes. It has been observed that many pathological processes increase the elastic modulus of soft tissue compared to normal. Ultrasound compression elastography is a method of characterization of elastic properties that has been the focus of many research efforts in the last two decades. In medical radiology, compression elastography is provided as an additional tool with ultrasound B-mode in the existing scanners, and the combined features of elastography and echography act as a promising diagnostic method in breast cancer detection. However, the full capability of the ultrasound elastography technique together with B-mode has not been utilized by novice radiologists due to the nonavailability of suitable, appropriately designed tissue-mimicking phantoms. Since different commercially available ultrasound elastographic scanners follow their own unique protocols, training novice radiologists is becoming cumbersome. The main focus of this work is to develop a tissue-like agar-based phantom, which mimics breast tissue with common abnormal lesions like fibroadenoma and invasive ductal carcinoma in a clinically perceived way and compares the sonographic and elastographic appearances using different commercially available systems. In addition, the developed phantoms are simulated using the finite-element method, and ideal strain images are generated. Strain images from experiment and simulation are compared based on image contrast parameters, namely contrast transfer efficiency (CTE) and observed strain, and they are in good agreement. The strain image contrast of malignant inclusions is significantly improved compared to benign inclusions, and the trend of CTE is similar for all elastographic scanners under investigation.
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