Hierarchical clustering method to improve transrectal ultrasound-guided diffuse optical tomography for prostate cancer imaging

Abstract

The inclusion of anatomical prior information in reconstruction algorithms can improve the quality of reconstructed images in near-infrared diffuse optical tomography (DOT). Prior literature on possible locations of human prostate cancer from transrectal ultrasound (TRUS), however, is limited and has led to biased reconstructed DOT images. In this work, we propose a hierarchical clustering method (HCM) to improve the accuracy of image reconstruction with limited prior information. HCM reconstructs DOT images in three steps: 1) to reconstruct the human prostate, 2) to divide the prostate region into geometric clusters to search for anomalies in finer clusters, 3) to continue the geometric clustering within anomalies for improved reconstruction. We demonstrated this hierarchical clustering method using computer simulations and laboratory phantom experiments. Computer simulations were performed using combined TRUS/DOT probe geometry with a multilayered model; experimental demonstration was performed with a single-layer tissue simulating phantom. In computer simulations, two hidden absorbers without prior location information were reconstructed with a recovery rate of 100% in their locations and 95% in their optical properties. In experiments, a hidden absorber without prior location information was reconstructed with a recovery rate of 100% in its location and 83% in its optical property.

Keywords: DOT reconstruction; Hierarchical clustering method; detection of prostate cancer.

Fig. 1

Methodology showing steps through a flow chart showing HCM

Fig. 2

(a) Probe geometry used in this study; each optode is bifurcated to serve as a source and detector. (b) Mesh (elements not highlighted) has been rotated and sliced vertically into two halves to show the simulation geometry. (c) A slice from the mesh cut along the longitudinal direction, showing simulated rectum wall (green), surrounding tissue (blue), and prostate (sky blue). An anomaly has been created at 1-cm depth from the rectum wall. (d) Image reconstruction is in progress showing clusters within the prostate region.

Fig. 3

Reconstructed μ_a values in mm⁻¹ using different reconstruction steps for (a) an anomaly located within a simulated prostate. The dotted circles indicate the real locations of the anomaly. Reconstructed images (b) after Step 1 of HCM, (c) after Step 2 of HCM, (d) after Step 3 of HCM, (e) after Step 4 of HCM; (f) reconstructed image for the same case using a known hard prior anatomy/condition for the inclusion.

Fig. 4

Reconstructed μ_a values in mm⁻¹ of the anomaly created in increasing depths. Panels (a), (b) and 4(c) show the reconstructed images of an anomaly located at 1 cm, 2 cm, and 3 cm, respectively. Dotted circles show the actual location of the anomaly.

Fig. 5

This figure shows (a) the two anomalies separated by 2 cm and created at a depth of 2 cm, and (b) the two anomalies separated by 4 cm and located at depths of 1 cm and 2 cm. Dotted circles show the actual locations of the anomalies.

Fig. 6

Comparison of absorption coefficients between the recovered anomaly and the prostate background after Step 2.

Fig. 7

This figure shows (a) the reconstructed image with 1% noise added to the data and without any anomalies, while (b), (c), and (d) show the reconstructed images with 1%, 2%, and 3% noise levels, respectively.

Fig. 8

Instrumentation and probe setup utilized for laboratory phantom experiment. Eight sources and detectors were used for light delivery and detection. BS: beam splitter; PD: photodiode.

Fig. 9

Flow chart depicting various stages of detection electronics utilized in proposed instrumentation.

Fig. 10

(a) Experimental setup used in this study. The probe was placed on one side of the tank to avoid contact with the intralipid solution. An absorber was placed 1.5 cm from the probe side of the tank. (b) Photograph showing the experimental setup. (c) Photograph showing the photodiode array.

Fig. 11

Reconstructed μ_a values in mm⁻¹ using (a) regular DOT iterative reconstruction and HCM after (b) Step 2, (c) Step 3, and (d) Step 4. The dashed circles indicate the actual location of the 1-cm absorber with a depth of 1.5 cm below the measurement surface.