BACKGROUND Poor needle placement in prostate high-dose-rate brachytherapy (HDR-BT) results in sub-optimal dosimetry and mentally predicting these effects during HDR-BT is difficult, creating a barrier to widespread availability of high-quality prostate HDR-BT. PURPOSE To provide earlier feedback on needle implantation quality, we trained machine learning models to predict 2D dosimetry for prostate HDR-BT on axial TRUS images. METHODS AND MATERIALS Clinical treatment plans from 248 prostate HDR-BT patients were retrospectively collected and randomly split 80/20 for training/testing. Fifteen U-Net models were implemented to predict the 90%, 100%, 120%, 150%, and 200% isodose levels in the prostate base, midgland, and apex. Predicted isodose lines were compared to delivered dose using Dice similarity coefficient (DSC), precision, recall, average symmetric surface distance, area percent difference, and 95th percentile Hausdorff distance. To benchmark performance, 10 cases were retrospectively replanned and compared against the clinical plans using the same metrics. RESULTS Models predicting 90% and 100% isodose lines at midgland performed best, with median DSC of 0.97 and 0.96, respectively. Performance declined as isodose level increased, with median DSC of 0.90, 0.79, and 0.65 in the 120%, 150%, and 200% models. In the base, median DSC was 0.94 for 90% and decreased to 0.64 for 200%. In the apex, median DSC was 0.93 for 90% and decreased to 0.63 for 200%. Median prediction time was 25 ms. CONCLUSION U-Net models accurately predicted HDR-BT isodose lines on 2D TRUS images sufficiently quickly for real-time use. Incorporating auto-segmentation algorithms will allow intra-operative feedback on needle implantation quality.

Purpose High dose rate brachytherapy (HDR-BT) for treatment of prostate cancer requires careful placement of interstitial needles under transrectal ultrasound (TRUS) guidance. Poor needle placement can result in sub-optimal dosimetry, which may not be recognized until the radiation planning phase of the procedure. To provide earlier feedback on the quality of needle implantation, we have developed and validated a machine-learning based algorithm to predict 2D dosimetry based on information from a mid-gland, axial ultrasound image in real-time. Materials and Methods Clinical treatment plans and 3D TRUS images with visible needles from 248 prostate HDR-BT patients were retrospectively collected. For each plan, 5 mm axial slices were selected from the midgland and 2D binary masks were created for the prostate, urethra, catheters, and the selected isodose levels on these slices. 526 2D TRUS slices from 198 randomly selected patients were used to train five different U-Net models to predict the 90%, 100%, 120%, 150%, and 200% isodose levels with the prostate, urethra, and catheter masks as inputs. 135 slices from the remaining 50 patients were used to evaluate the performance of the models. On each image, we compared the area enclosed by the isodose line predicted by the model to the delivered dose using the Dice similarity coefficient (DSC), precision, and recall. We also calculated the area of the prostate receiving 90%, 100%, 120%, 150%, and 200% of the prescription dose and compared it with 2D versions of treatment planning goals. Results Results are given in Table 1. Models predicting the 90% and 100% isodose lines performed the best, with a median DSC, precision, and recall of 0.97, 0.97, and 0.97 respectively for the 90% isodose model, and 0.96, 0.98, and 0.95 for the 100% isodose model. Performance declined as the isodose level increased, with median DSC of 0.90, 0.79, and 0.65 in the 120%, 150%, and 200% models, respectively. Treatment planning goals were met by predictions from the 90% and 100% isodose models. The median time for the models to execute a prediction was 25 ms and the maximum time was 97 ms. Conclusion Our U-Net models were able to accurately predict specific HDR-BT isodose lines using information from a 2D TRUS image sufficiently quickly for real-time execution. Using this tool to help guide needle implantation should help improve procedure efficiency, resulting in faster procedures with potentially fewer needles. This tool may be especially useful in centres with limited HDR-BT experience, improving the consistency of oncologic outcomes.

Magnetic resonance imaging (MRI)-guided prostate focal laser ablation (FLA) therapy shows potential as a minimally invasive treatment method for localized prostate cancer, which minimizes overtreatment of surrounding structures, thereby improving quality of life. We previously developed an MRI-compatible mechatronic guidance system capable of needle positioning within an open-air and in-bore MRI environment. In comparison to open-air testing, an increased error was reported from in-bore experiments, suggesting the effects of image distortion, fiducial localization, and registration error may impact its accuracy. In this paper, we describe the design of an improved registration multi-fiducial for the robust registration of the mechatronic system to MRI, and comparison and validation of MRI-guided needle delivery to virtual targets (simulating localized focal zones) in tissue-mimicking prostate phantoms. The multi-fiducial structure is composed of thirty-six MR-spheres arranged across an extensive volume. Mechatronics-assisted MRI-guided needle delivery (N = 10) to virtual targets were evaluated with tissue-mimicking phantoms. 3T MRI images were acquired for registration, the mechatronic system was remotely actuated and needle insertion was performed, then verification images were acquired. The needle tip and needle trajectory error were quantified between the planned and actual trajectories. Our preliminary results show significant improvements in needle targeting with the improved registration fiducial with an FLA ablation region radius of 2.0 mm within 95% confidence. Improvements in robust registration show potential to enable accurate mechatronics-assisted MRI-guided needle delivery for FLA therapy.

Background: Mammographic screening has reduced mortality in women through the early detection of breast cancer. However, the sensitivity for breast cancer detection is significantly reduced in women with dense breasts, in addition to being an independent risk factor. Ultrasound (US) has been proven effective in detecting small, early-stage, and invasive cancers in women with dense breasts. Purpose: To develop an alternative, versatile, and cost-effective spatially tracked three-dimensional (3D) US system for whole-breast imaging. This paper describes the design, development, and validation of the spatially tracked 3DUS system, including its components for spatial tracking, multi-image registration and fusion, feasibility for whole-breast 3DUS imaging and multi-planar visualization in tissue-mimicking phantoms, and a proof-of-concept healthy volunteer study. Methods: The spatially tracked 3DUS system contains (a) a six-axis manipulator and counterbalanced stabilizer, (b) an in-house quick-release 3DUS scanner, adaptable to any commercially available US system, and removable, allowing for handheld 3DUS acquisition and two-dimensional US imaging, and (c) custom software for 3D tracking, 3DUS reconstruction, visualization, and spatial-based multi-image registration and fusion of 3DUS images for whole-breast imaging. Spatial tracking of the 3D position and orientation of the system and its joints (J(1-6)) were evaluated in a clinically accessible workspace for bedside pointof-care (POC) imaging. Multi-image registration and fusion of acquired 3DUS images were assessed with a quadrants-based protocol in tissue-mimicking phantoms and the target registration error (TRE) was quantified. Whole-breast 3DUS imaging and multi-planar visualization were evaluated with a tissuemimicking breast phantom. Feasibility for spatially tracked whole-breast 3DUS imaging was assessed in a proof-of-concept healthy male and female volunteer study. Results: Mean tracking errors were 0.87 +/- 0.52, 0.70 +/- 0.46, 0.53 +/- 0.48, 0.34 +/- 0.32, 0.43 +/- 0.28, and 0.78 +/- 0.54 mm for joints J(1-6), respectively. Lookup table (LUT) corrections minimized the error in joints J(1) , J(2), and J(5). Compound motions exercising all joints simultaneously resulted in a mean tracking error of 1.08 +/- 0.88 mm (N = 20) within the overall workspace for bedside 3DUS imaging. Multi-image registration and fusion of two acquired 3DUS images resulted in a mean TRE of 1.28 +/- 0.10 mm. Whole-breast 3DUS imaging and multi-planar visualization in axial, sagittal, and coronal views were demonstrated with the tissue-mimicking breast phantom. The feasibility of the whole-breast 3DUS approach was demonstrated in healthy male and female volunteers. In the male volunteer, the high-resolution whole-breast 3DUS acquisition protocol was optimized without the added complexities of curvature and tissue deformations. With small post-acquisition corrections for motion, whole-breast 3DUS imaging was performed on the healthy female volunteer showing relevant anatomical structures and details. Conclusions: Our spatially tracked 3DUS system shows potential utility as an alternative, accurate, and feasible whole-breast approach with the capability for bedside POC imaging. Future work is focused on reducing misregistration errors due to motion and tissue deformations, to develop a robust spatially tracked whole-breast 3DUS acquisition protocol, then exploring its clinical utility for screening high-risk women with dense breasts.

Purpose Image-guided needle biopsy of small, detectable lesions is crucial for early-stage diagnosis, treatment planning, and management of breast cancer. High-resolution positron emission mammography (PEM) is a dedicated functional imaging modality that can detect breast cancer independent of breast tissue density, but anatomical context and real-time needle visualization are not yet available to guide biopsy. We propose a mechatronic guidance system integrating an ultrasound (US)-guided core-needle biopsy (CNB) with high-resolution PEM localization to improve the spatial sampling of breast lesions. This paper presents the benchtop testing and phantom studies to evaluate the accuracy of the system and its constituent components for targeted PEM-US-guided biopsy under simulated high-resolution PEM localization. Methods A mechatronic guidance system was developed to operate with the Radialis PEM system and a conventional US system. The system includes a user-operated guidance arm and end-effector biopsy device, integrating a US transducer and CNB gun, with its needle focused on a remote center of motion (RCM). Custom software modules were developed to track, display, and guide the end-effector biopsy device. Registration of the mechatronic guidance system to a simulated PEM detector plate was performed using a landmark-based method. Testing was performed with fiducials positioned in the peripheral and central regions of the simulated detector plate and registration error was quantified. Breast phantom experiments were performed under ideal detection and localization to evaluate for bias in the end-effector biopsy device. The accuracy of the complete mechatronic guidance system to perform targeted breast biopsy was assessed using breast phantoms with simulated lesions. Three-dimensional positioning error was quantified, and principal component analysis assessed for directional trends in 3D space within 95% prediction intervals. Targeted breast biopsies with test phantoms were performed and an overall in-plane needle targeting error was quantified. Results The mean registration errors were 0.63 mm (N = 44) and 0.73 mm (N = 72) in the peripheral and central regions of the simulated PEM detector plate, respectively. A 3D 95% prediction ellipsoid shows an error volume <2.0 mm in diameter, centered on the mean registration error. Under ideal detection and localization, targets <1.0 mm in diameter can be sampled with 95% confidence. The complete mechatronic guidance system was able to successfully spatially sample simulated breast lesions, 4 mm and 6 mm in diameter and height (N = 20) in known 3D positions in the PEM image coordinate space. The 3D positioning error was 0.85 mm (N = 20) with 0.64 mm in-plane and 0.44 mm cross-plane component errors. Targeted breast biopsies resulted in a mean in-plane needle targeting error of 1.08 mm (N = 15) allowing for targets 1.32 mm in radius to be sampled with 95% confidence. Conclusions We demonstrated the utility of our mechatronic guidance system for targeted breast biopsy under high-resolution PEM localization. Breast phantom studies showed the ability to accurately guide, position, and target breast lesions with the accuracy to spatially sample targets <3.0 mm in diameter with 95% confidence. Future work will integrate the developed system with the Radialis PEM system toward combined PEM-US-guided breast biopsy.

Prostate cancer is the most frequently diagnosed non-cutaneous cancer and the second leading cause of cancer-related deaths in men. Whole gland surgical and radiation treatments for prostate cancer are highly effective for long-term cancer control. However, these are often associated with overtreatment, resulting in urinary complications and sexual dysfunction, adversely impacting the quality of life. Focal laser ablation (FLA) under magnetic resonance imaging (MRI)-guidance is an alternative minimally invasive treatment method for localized prostate tumors while preserving surrounding structures and healthy tissues. Accurate needle positioning and delivery are critical for the therapeutic success of MRI-guided FLA. We propose an MRI-compatible mechatronic system for in-bore transperineal FLA needle guidance to localized prostate lesions. This paper presents the mechatronic system design, including a remotely actuated, four degree-of-freedom transperineal positioning and needle guidance mechanism, and adaptable needle guide. We demonstrate its MR compatibility and evaluated its mechanical bias in free-space testing using an external optical tracking system with several measurement points (N=40) over its range-of-motion. Free-space testing resulted in a root-mean-square error of 0.71 ± 0.30 mm. Within an MR environment, in-bore testing to virtual targets (N=10) with projected needle trajectories resulted in a mean needle tip error of 1.81 ± 0.56 mm and needle trajectory error of 0.78 ± 0.75°. This suggests that localized ablation regions can be accurately targeted within 2.16 mm within 95% confidence. An extensive in-bore analysis and correction for systematic bias across the range-of-motion may improve this accuracy. This study shows that our proposed mechatronic needle guidance system may be a feasible alternative for accurate MR-guided FLA for localized prostate therapy.

PURPOSE Prostate cancer is the most common non-cutaneous cancer among men in the USA and is the second leading cause of cancer death in American men [1]. Focal laser ablation (FLA) has the potential to control small tumours while preserving urinary and erectile function by leaving the neurovascular bundles and urethral sphincters intact. Accurate needle guidance is critical to the success of FLA. Multi-parametric magnetic resonance images (mpMRI) can be used to identify targets, guide needles, and assess treatment outcomes. The purpose of this work was to design and evaluate the accuracy of an MR-compatible mechatronic system for in-bore transperineal guidance of FLA ablation needles to localized lesions in the prostate. METHODS The mechatronic system was constructed entirely of non-ferromagnetic materials, with actuation controlled by piezoelectric motors and optical encoders. The needle guide hangs between independent front and rear two-link arms, which allows for horizontal and vertical translation as well as pitch and yaw rotation of the guide with a 6.0 cm range of motion in each direction. Needles are inserted manually through a chosen hole in the guide, which has been aligned with the target in the prostate. Open-air positioning error was evaluated using an optical tracking system (0.25 mm RMS accuracy) to measure 125 trajectories in free space. Correction of systematic bias in the system was performed using 85 of the trajectories, and the remaining 40 were used to estimate the residual error. The error was calculated as the horizontal and vertical displacement between the axis of the desired and measured trajectories at a typical needle insertion depth of 10 cm. MR-compatibility was evaluated using a grid phantom to assess image degradation due to the presence of the system, and induced force, heating, and electrical interference in the system were assessed qualitatively. In-bore positioning error was evaluated on 25 trajectories. RESULTS Open-air mean positioning error at the needle tip was 0.80±0.36mm with a one-sided 95% confidence interval of 1.40mm. The mean deviation of needle trajectories from the planned direction was 0.14 ± 0.06°. In the MR bore, the mean positioning error at the needle tip was 2.11 ± 1.05mm with a one-sided 95% prediction interval of 3.84mm. The mean angular error was 0.49±0.26°. The system was found to be compatible with the MR environment under the specified gradient-echo sequence parameters used in this study. CONCLUSION A complete system for delivering needles to localized prostate tumours was developed and described in this work, and its compatibility with the MR environment was demonstrated. In-bore MRI positioning error was sufficiently small for targeting small localized prostate tumours.

PurposeProstate cancer is the most common noncutaneous cancer among men in the USA. Focal laser thermal ablation (FLA) has the potential to control small tumors while preserving urinary and erectile function by leaving the neurovascular bundles and urethral sphincters intact. Accurate needle guidance is critical to the success of FLA. Multiparametric magnetic resonance images (mpMRI) can be used to identify targets, guide needles, and assess treatment outcomes. In this study, we evaluated the location of ablation zones relative to targeted lesions in 23 patients who underwent FLA therapy in a phase II trial. The ablation zone margins and unablated tumor volume were measured to determine whether complete coverage of each tumor was achieved, which would be considered a clinically successful ablation.MethodsPreoperative mpMRI was acquired for each patient 2–3 months preceding the procedure and the prostate and lesion(s) were manually contoured on 3 T T2‐weighted axial images. The prostate and ablation zone(s) were also manually contoured on postablation 1.5 T T1‐weighted contrast‐enhanced axial images acquired immediately after the procedure intraoperatively. The lesion surface was nonrigidly registered to the postablation image using an initial affine registration followed by nonrigid thin‐plate spline registration of the prostate surfaces. The margins between the registered lesion and ablation zone were calculated using a uniform spherical distribution of rays, and the volume of intersection was also calculated. Each prostate was contoured five times to determine the segmentation variability and its effect on intersection of the lesion and ablation zone.ResultsOur study showed that the boundaries of the segmented tumor and ablation zone were close. Of the 23 lesions that were analyzed, 11 were completely covered by the ablation zone and 12 were partially covered. A shift of 1.0, 2.0, and 2.6 mm would result in 19, 21, and all tumors completely covered by the ablation zone, respectively. The median unablated tumor volume across all tumors was 0.1 with an IQR of 3.7 , which was 0.2% of the median tumor volume (46.5 with an IQR of 46.3 ). The median extension of the tumors beyond the ablation zone, in cases which were partially ablated, was 0.9 mm (IQR of 1.3 mm), with the furthest tumor extending 2.6 mm.ConclusionIn all cases, the boundary of the tumor was close to the boundary of the ablation zone, and in some cases, the boundary of the ablation zone did not completely enclose the tumor. Our results suggest that some of the ablations were not clinically successful and that there is a need for more accurate needle tracking and guidance methods. Limitations of the study include errors in the registration and segmentation methods used as well as different voxel sizes and contrast between the registered T2 and T1 MRI sequences and asymmetric swelling of the prostate postprocedurally.

MRI-guided focal laser ablation (FLA) is a promising minimally-invasive therapy method for men with localized prostate cancer. We previously developed an MR-compatible mechatronic system capable of transperineal needle delivery within an in-bore 3T MRI environment. This work presents an improved multi-fiducial structure for robust registration of the mechatronic system for MRI-guided FLA needle delivery. Real-time MRI-guided needle delivery was performed in a tissue-mimicking prostate phantom to virtual targets simulating focal ablation zones. With the implementation of the improved multi-fiducial structure, mechatronics-assisted MRI-guided needle delivery enables a 1.44 mm ablation radius, showing potential utility for accurate FLA to small prostate lesions.