Sonoelastography is an ultrasound imaging technique where low amplitude, low-frequency shear waves (less than 0.1 mm displacement and less than 1 kHz frequency) are propagated through internal organs, while real-time Doppler techniques are used to image the resulting vibration pattern. When a discrete hard inhomogeneity, such as a tumour, is present within a region of soft tissue, a decrease in the vibration amplitude will occur at its location. This forms the basis for tumour detection using sonoelastography. For three-dimensional (3D) imaging the acquisition of sequential tomographic slices using this technique, combined with image segmentation, enables the reconstruction, quantification and visualization of tumour volumes. Sonoelastography and magnetic resonance images (MRI) of a tissue phantom containing a hard isoechoic inclusion are compared to evaluate the accuracy of this method. The tumour delineation from sonoelastography was found to have good agreement with the tumour from MRI except for a bleeding at one of its ends. Although sonoelastography is still in an experimental phase, the principles behind this imaging modality are explained and some practical aspects of acquiring sonoelastography images are described. Results from a 3D sonoelastography reconstruction of a tissue mimicking phantom and an ex vivo whole prostate specimen are presented.

This paper describes fusion of three-dimensional (3-D) ultrasound (US) and magnetic resonance imaging (MRI) data sets, without the assistance of external fiducial markers or external position sensors. Fusion of these two modalities combines real-time 3-D ultrasound scans of soft tissue with the larger anatomical framework from MRI. The complementary information available from multiple imaging modalities warrants the development of robust fusion capabilities. We describe the data acquisition, specialized algorithms, and results for 3-D fused data from phantom studies and in vivo studies of the normal human vasculature and musculoskeletal systems.

PURPOSE: To prospectively evaluate the accuracy of 3D sonoelastography for detection of prostate cancer relative to gray scale sonography in vitro.METHODS: Using an Institutional Review Board-approved, HIPAA compliant protocol with informal consent, 19 prostatectomy specimens from patients 46 to 70 years of age with biopsy proven prostate cancer were scanned in 3D using conventional B-scan and sonoelastography using vibrations above 100Hz.Step-sectioned whole-mount histology was utilized to create a 3D volume of the prostate and tumors within it. B-scan ultrasound images and regions of low vibration in the sonoelastography images (hard regions) were formatted in 3D. The lesions in the nineteen cases were analyzed as two groups: G1) pathology-confirmed tumors of 1.0 cc or greater; and G2) pathology-confirmed tumor size less than 1.0 cc. G1 cases were evaluated for B-scan ultrasound and sonoelastography vs. histology as a reference standard and were scored as either a True Positive, a False Positive, a True Negative, or a False Negative. G2 cases were evaluated for sonoelastography only. True positives required 3D lesion correlation between pathology and imaging data. Conventional definitions of accuracy and sensitivity were employed to calculate these statistics. RESULTS: G1 (7 lesions with tumor volume 1.0 cc or greater): Sonoelastography: accuracy of 55%, sensitivity of 71%. B-scan: accuracy of 17%, sensitivity of 29%. Mean tumor size is 3.1cc +/-2.1cc. G2 (22 lesions with tumor volume less than 1.0 cc). Mean tumor size is 0.32 cc +/-0.21 cc. Sonoelastography: accuracy of 34%, sensitivity of 41%, false positives: 6.CONCLUSIONS: Sonoelastography performed considerably better than gray scale sonography in the detection of prostate cancer tumors over 1 cc.

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