Prostate cancer detection at early stages is crucial for desirable treatment outcome. Among available imaging modalities, ultrasound (US) elastography is being developed as an effective clinical tool for prostate cancer diagnosis. Current clinical US elastography systems utilise strain imaging where tissue strain images are generated to approximate the tissue elastic modulus distribution. While strain images can be generated in real-time fashion, they lack the accuracy necessary for having desirable sensitivity and specificity. To improve strain imaging, full inversion based elastography techniques were proposed. Among these techniques, a constrained elastography technique was developed which showed promising results as long as the tumor and prostate geometry can be obtained accurately from the imaging modality used in conjunction with the elastography system. This requirement is not easy to fulfill, especially with US imaging. To address this issue, we present an unconstrained full inversion prostate elastography method in conjunction with US imaging where knowledge of tissue geometry is not necessary. One of the reasons that full inversion elastography techniques have not been routinely used in the clinic is lack of clinical validation studies. To our knowledge, no quasistatic full inversion based prostate US elastography technique has been applied in vivo before. In this work, the proposed method was applied to clinical prostate data and reconstructed elasticity images were compared to corresponding annotated histopathology images which is the first quasi-static full inversion based prostate US elastography technique applied successfully in vivo. Results demonstrated a good potential for clinical utility of the proposed method.
Prostate cancer detection at early stage is very critical for desirable treatment outcome. In fact prostate cancer can be cured, if it is detected at early stage. Among imaging modalities used for cancer assessment, ultrasound elastography is emerging as an effective clinical tool for prostate and breast cancer diagnosis. Current clinical ultrasound elastography systems utilize strain imaging where tissue strain images are generated to approximate the tissue elastic modulus distribution. While strain images can be generated in real-time fashion, they lack the accuracy necessary for having high sensitivity and specificity. To improve strain imaging, researchers have developed full inversion based elastography techniques. These techniques are not based on simplifying assumptions such as tissue stress uniformity leading to accurate elastic modulus reconstruction. The drawback of these techniques, however, is that they are computationally intensive, hence are not suitable for real-time imaging. Among these techniques, a constrained elastography technique was developed which showed promising results as long as the tumor geometry can be obtained accurately from the imaging modality used in conjunction with elastography. This requirement is not easy to fulfill, especially with ultrasound imaging. To address this issue, we present an unconstrained full inversion ultrasound elastography method for prostate cancer imaging where knowledge of tissue geometry is not necessary. Tissue elastic modulus reconstruction in the proposed elastography technique is iterative, where each iteration involves tissue stress computation using Finite Element Method (FEM) followed by Young’s modulus updating using Hooke’s law. The method was validated using in silico and tissue mimicking prostate phantom studies. Results obtained from these studies indicate that the technique is reasonably accurate and robust.
Prostate cancer is the second common cancer among men worldwide and remains the second leading cancer-related
cause of death in mature men. The disease can be cured if it is detected at early stage. This implies that prostate cancer
detection at early stage is very critical for desirable treatment outcome. Conventional techniques of prostate cancer
screening and detection, such as Digital Rectal Examination (DRE), Prostate-Specific Antigen (PSA) and Trans Rectal
Ultra-Sonography (TRUS), are known to have low sensitivity and specificity. Elastography is an imaging technique that
uses tissue stiffness as contrast mechanism. As the association between the degree of prostate tissue stiffness alteration
and its pathology is well established, elastography can potentially detect prostate cancer with a high degree of sensitivity
and specificity. In this paper, we present a novel elastography technique which, unlike other elastography techniques,
does not require displacement data acquisition system. This technique requires the prostate's pre-compression and postcompression
transrectal ultrasound images. The conceptual foundation of reconstructing the prostate's normal and
pathological tissues elastic moduli is to determine these moduli such that the similarity between calculated and observed
shape features of the post compression prostate image is maximized. Results indicate that this technique is highly
accurate and robust.
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