We conducted a canine study to investigate the in vivo feasibility of photoacoustic imaging for intraoperative updates to brachytherapy treatment plans. A fiber coupled to a 1064-nm Nd:YAG laser was inserted into high-dose-rate brachytherapy needles, which diffused light spherically. These needles were inserted through the perineum into the prostate for interstitial light delivery and the resulting acoustic waves were detected with a transrectal ultrasound probe. Postoperative computed tomography images and ex vivo photoacoustic images confirmed seed locations. Limitations with insufficient light delivery were mitigated with short-lag spatial coherence (SLSC) beamforming, providing a 10-20 dB contrast improvement over delay-and-sum (DAS) beamforming for pulse energies ranging from 6.8 to 10.5 mJ with a fiber-seed distance as large as 9.5 mm. For the same distance and the same range of energy densities, signal-to-noise ratios (SNRs) were similar while the contrast-to-noise ratio (CNR) was higher in SLSC compared to DAS images. Challenges included visualization of signals associated with the interstitial fiber tip and acoustic reverberations between seeds separated by ≤ 2 mm. Results provide insights into the potential for clinical translation to humans.

Abstract:Prostate brachytherapy, administered by implanting tiny radioactive seeds to treat prostate cancer, currently relies on transrectal ultrasound imaging for intraoperative visualization of the metallic seeds. Photoacoustic (PA) imaging has been suggested as a feasible alternative to ultrasound imaging due to its superior sensitivity to metal surrounded by tissue. However, PA images suffer from poor contrast when seeds are distant from the light source. We propose a transperineal light delivery method and investigate the application of a short-lag spatial coherence (SLSC) beamformer to enhance low-contrast photoacoustic signals that are distant from this type of light source. Performance is compared to a conventional delay-and-sum beamformer. A pure gelatin phantom was implanted with black ink-coated brachytherapy seeds and the mean contrast was improved by 3-25 dB with the SLSC beamformer for fiber-seed distances ranging 0.6-6.3 cm, when approximately 10% of the receive aperture elements were included in the short-lag sum. For fiber-seed distances greater than 3-4 cm, the mean contrast-to-noise ratio (CNR) was approximately doubled with the SLSC beamformer, while mean signal-to-noise ratios (SNR) were mostly similar with both beamformers. Lateral resolution was decreased by 2 mm, but improved with larger short-lag values at the expense of poorer CNR and SNR. Similar contrast and CNR improvements were achieved with an uncoated brachytherapy seed implanted in ex vivo tissue. Results indicate that the SLSC beamformer has potential to enhance the visualization of prostate brachytherapy seeds that are distant from the light source.

A magnetic resonance imaging (MRI) pulse sequence and a corresponding image processing algorithm to localize prostate brachytherapy seeds during or after therapy are presented. InversionRecovery with ON-resonant water suppression (IRON) is an MRI methodology that generates positive contrast in regions of magnetic field susceptibility, as created by prostate brachytherapy seeds. Phantoms comprising of several materials found in brachytherapy seeds were created to assess the usability of the IRON pulse sequence for imaging seeds. Resulting images show that seed materials are clearly visible with high contrast using IRON, agreeing with theoretical predictions. A seed localization algorithm to process IRON images demonstrates the potential of this imaging technique for seed localization and dosimetry.

The success of prostate brachytherapy critically depends on delivering adequate dose to the prostate gland, and the capability of intraoperatively localizing implanted seeds provides potential for dose evaluation and optimization during therapy. REDMAPS is a recently reported algorithm that carries out seed localization by detecting, matching, and reconstructing seeds in only a few seconds from three acquired x-ray images. In this paper, we present an automatic pose correction (APC) process that is combined with REDMAPS to allow for both more accurate seed reconstruction and the use of images with relatively large pose errors. APC uses a set of reconstructed seeds as a fiducial and corrects the image pose by minimizing the overall projection error. The seed matching and APC are iteratively computed until a stopping condition is met. Simulations and clinical studies show that APC significantly improves the reconstructions with an overall average matching rate of ≥ 99.4%, reconstruction error of ≤ 0.5 mm, and the matching solution optimality of ≥ 99.8%.