Ultrasound Elastography of the Prostate Using an Unconstrained Modulus Reconstruction Technique: A Pilot Clinical Study

Abstract

A novel full-inversion-based technique for quantitative ultrasound elastography was investigated in a pilot clinical study on five patients for non-invasive detection and localization of prostate cancer and quantification of its extent. Conventional-frequency ultrasound images and radiofrequency (RF) data (~5 MHz) were collected during mechanical stimulation of the prostate using a transrectal ultrasound probe. Pre and post-compression RF data were used to construct the strain images. The Young's modulus (YM) images were subsequently reconstructed using the derived strain images and the stress distribution estimated iteratively using finite element (FE) analysis. Tumor regions determined based on the reconstructed YM images were compared to whole-mount histopathology images of radical prostatectomy specimens. Results indicated that tumors were significantly stiffer than the surrounding tissue, demonstrating a relative YM of 2.5±0.8 compared to normal prostate tissue. The YM images had a good agreement with the histopathology images in terms of tumor location within the prostate. On average, 76%±28% of tumor regions detected based on the proposed method were inside respective tumor areas identified in the histopathology images. Results of a linear regression analysis demonstrated a good correlation between the disease extents estimated using the reconstructed YM images and those determined from whole-mount histopathology images (r²=0.71). This pilot study demonstrates that the proposed method has a good potential for detection, localization and quantification of prostate cancer. The method can potentially be used for prostate needle biopsy guidance with the aim of decreasing the number of needle biopsies. The proposed technique utilizes conventional ultrasound imaging system only while no additional hardware attachment is required for mechanical stimulation or data acquisition. Therefore, the technique may be regarded as a non-invasive, low cost and potentially widely-available clinical tool for prostate cancer diagnosis.

Figure 1

Flowchart illustrating the iterative procedure for YM reconstruction.

Figure 2

Imaging and histopathology data acquired from the 5 patients: (a) Ultrasound B-mode images (scale bar represents ~1 cm), (b) corresponding clinical strain images, (c) calculated strain images, (d) calculated YM images, (e) tumor regions based on YM images overlaid on the B-mode images, and (f) macroscopic images of whole-mount histopathology sections of the prostatectomy specimen (tumor region identified by pathologists are delineated with solid white contours; scale bar represents ~1 cm).

Figure 3

Registration of the tumor regions determined based on the YM images (outlined in solid black) to their corresponding histopathology images (with tumor regions outlined in solid white) for the 5 patients. Yellow outline in each case shows the biggest circle within respective overlap regions of black and white contours that is centered at the centroid of area contoured in black. The circle diameter is given for each case.

Figure 4

Extent of disease estimated/identified for each patient. The plot demonstrates relative areas of disease estimated noninvasively using the reconstructed YM images versus those identified from whole-mount histopathology. Each case has been labeled with the patient number. The lines were fitted to data via linear regression analyses and presented within the 95% confidence intervals.

Figure 5

A three-dimensional scatter plot demonstrating relative YM of tumor to surrounding tissue versus Gleason score and PSA level for each patient. The numbers above each case present the corresponding Gleason score, PSA level, and YM ratio, respectively.