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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 (J1–6) were evaluated in a clinically accessible workspace for bedside point‐of‐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 tissue‐mimicking 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 J1–6, respectively. Lookup table (LUT) corrections minimized the error in joints J1, J2, and J5. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: Image‐guided focal ablation procedures are first‐line therapy options in the treatment of liver cancer tumors that provide advantageous reductions in patient recovery times and complication rates relative to open surgery. However, extensive physician training is required and image guidance variabilities during freehand therapy applicator placement limit the sufficiency of ablation volumes and the overall potential of these procedures. We propose the use of three‐dimensional ultrasound (3D US) to provide guidance and localization of therapy applicators, augmenting current ablation therapies without the need for specialized procedure suites. We have developed a novel scanning mechanism for geometrically variable 3D US images, a mechanical tracking system, and a needle applicator insertion workflow using a custom needle applicator guide for targeted image‐guided procedures. Methods: A three‐motor scanner was designed to use any commercially available US probe to generate accurate, consistent, and geometrically variable 3D US images. The designed scanner was mounted on a counterbalanced stabilizing and mechanical tracking system for determining the US probe orientation, which was assessed using optical tracking. Further exploiting the utility of the motorized scanner, an image‐guidance workflow was developed that moved the probe to any identified target within an acquired 3D US image. The complete 3D US guidance system was used to perform mock targeted interventional procedures on a phantom by selecting a target in a 3D US image, navigating to the target, and performing needle insertion using a custom 3D‐printed needle applicator guide. Registered postinsertion 3D US images and cone‐beam computed tomography (CBCT) images were used to evaluate tip targeting errors when using the motors, tracking system, or mixed navigation approaches. Two 3D US image geometries were investigated to assess the accuracy of a small‐footprint tilt approach and a large field‐of‐view hybrid approach for a total of 48 targeted needle insertions. 3D US image quality was evaluated in a healthy volunteer and compared to a commercially available matrix array US probe. Results: A mean positioning error of 1.85 ± 1.33 mm was observed when performing compound joint manipulations with the mechanical tracking system. A combined approach for navigation that incorporated the motorized movement and the in‐plane tracking system corrections performed the best with a mean tip error of 3.77 ± 2.27 mm and 4.27 ± 2.47 mm based on 3D US and CBCT images, respectively. No significant differences were observed between hybrid and tilt image acquisition geometries with all mean registration errors ≤1.2 mm. 3D US volunteer images resulted in clear reconstruction of clinically relevant anatomy. Conclusions: A mechanically tracked system with geometrically variable 3D US provides a utility that enables enhanced applicator guidance, placement verification, and improved clinical workflow during focal liver tumor ablation procedures. Evaluations of the tracking accuracy, targeting capabilities, and clinical imaging feasibility of the proposed 3D US system, provided evidence for clinical translation. This system could provide a workflow for improving applicator placement and reducing local cancer recurrence during interventional procedures treating liver cancer and has the potential to be expanded to other abdominal interventions and procedures. [ABSTRACT FROM AUTHOR]

Purpose During image-guided prostate biopsy, needles are targeted at tissues that are suspicious of cancer to obtain specimen for histological examination. Unfortunately, patient motion causes targeting errors when using an MR-transrectal ultrasound ( TRUS) fusion approach to augment the conventional biopsy procedure. This study aims to develop an automatic motion correction algorithm approaching the frame rate of an ultrasound system to be used in fusion-based prostate biopsy systems. Two modes of operation have been investigated for the clinical implementation of the algorithm: motion compensation using a single user initiated correction performed prior to biopsy, and real-time continuous motion compensation performed automatically as a background process. Methods Retrospective 2D and 3D TRUS patient images acquired prior to biopsy gun firing were registered using an intensity-based algorithm utilizing normalized cross-correlation and Powell's method for optimization. 2D and 3D images were downsampled and cropped to estimate the optimal amount of image information that would perform registrations quickly and accurately. The optimal search order during optimization was also analyzed to avoid local optima in the search space. Error in the algorithm was computed using target registration errors ( TREs) from manually identified homologous fiducials in a clinical patient dataset. The algorithm was evaluated for real-time performance using the two different modes of clinical implementations by way of user initiated and continuous motion compensation methods on a tissue mimicking prostate phantom. Results After implementation in a TRUS-guided system with an image downsampling factor of 4, the proposed approach resulted in a mean ± std TRE and computation time of 1.6 ± 0.6 mm and 57 ± 20 ms respectively. The user initiated mode performed registrations with in-plane, out-of-plane, and roll motions computation times of 108 ± 38 ms, 60 ± 23 ms, and 89 ± 27 ms, respectively, and corresponding registration errors of 0.4 ± 0.3 mm, 0.2 ± 0.4 mm, and 0.8 ± 0.5°. The continuous method performed registration significantly faster ( P < 0.05) than the user initiated method, with observed computation times of 35 ± 8 ms, 43 ± 16 ms, and 27 ± 5 ms for in-plane, out-of-plane, and roll motions, respectively, and corresponding registration errors of 0.2 ± 0.3 mm, 0.7 ± 0.4 mm, and 0.8 ± 1.0°. Conclusions The presented method encourages real-time implementation of motion compensation algorithms in prostate biopsy with clinically acceptable registration errors. Continuous motion compensation demonstrated registration accuracy with submillimeter and subdegree error, while performing < 50 ms computation times. Image registration technique approaching the frame rate of an ultrasound system offers a key advantage to be smoothly integrated to the clinical workflow. In addition, this technique could be used further for a variety of image-guided interventional procedures to treat and diagnose patients by improving targeting accuracy. [ABSTRACT FROM AUTHOR]

Purpose: In current clinical practice, there is no integrated 3D ultrasound (3DUS) guidance system clinically available for breast brachytherapy. In this study, the authors present a novel robot-assisted 3DUS system for real-time planning and guidance of breast interstitial high dose rate (HDR) brachytherapy treatment. Methods: For this work, a new computer controlled robotic 3DUS system was built to perform a hybrid motion scan, which is a combination of a 6 cm linear translation with a 30? rotation at both ends. The new 3DUS scanner was designed to fit on a modified Kuske assembly, keeping the current template grid configuration but modifying the frame to allow the mounting of the 3DUS system at several positions. A finer grid was also tested. A user interface was developed to perform image reconstruction, semiautomatic segmentation of the surgical bed as well as catheter reconstruction and tracking. A 3D string phantom was used to validate the geometric accuracy of the reconstruction. The volumetric accuracy of the system was validated with phantoms using magnetic resonance imaging (MRI) and computed tomography (CT) images. In order to accurately determine whether 3DUS can effectively replace CT for treatment planning, the authors have compared the 3DUS catheter reconstruction to the one obtained from CT images. In addition, in agarose-based phantoms, an end-to-end procedure was performed by executing six independent complete procedures with both 14 and 16 catheters, and for both standard and finer Kuske grids. Finally, in phantoms, five end-to-end procedures were performed with the final CT planning for the validation of 3DUS preplanning. Results: The 3DUS acquisition time is approximately 10 s. A paired Student t-test showed that there was no statistical significant difference between known and measured values of string separations in each direction. Both MRI and CT volume measurements were not statistically different from 3DUS volume (Student t-test: p > 0.05) and they were significantly correlated to 3DUS measurement (Pearson test: MRI p < 0.05 and CT p < 0.001). The mean angular separation distance between catheter trajectories segmented from 3DUS and CT images was 0.42 ±0.24, while the maximum and mean trajectory separations were 0.51±0.19 and 0.37 ±0.17 mm, respectively. Overall, the new finer grid has performed significantly better in terms of dosimetric indices. The planning target volume dosimetric indices were not found statistically different between 3DUS and CT planning (Student t-test, p > 0.05). Both the skin and the pectoral muscle dosimetric indices were within ABS guidelines. Conclusions: A novel robot-assisted 3DUS system was designed and validated. To their knowledge, this is the first system capable of performing real-time guidance and planning of breast multicatheter HDR brachytherapy treatments. Future investigation will test the feasibility of using the system in the clinic and for permanent breast brachytherapy. [ABSTRACT FROM AUTHOR]

Purpose: Two-dimensional ultrasound (2D US) imaging is commonly used for diagnostic and intraoperative guidance of interventional liver procedures; however, 2D US lacks volumetric information that may benefit interventional procedures. Over the past decade, three-dimensional ultrasound (3D US) has been developed to provide the missing spatial information. 3D US image acquisition is mainly based on mechanical, electromagnetic, and freehand tracking of conventional 2D US transducers, or 2D array transducers available on high-end machines. These approaches share many problems during clinical use for interventional liver imaging due to lack of flexibility and compatibility with interventional equipment, limited field-of-view (FOV), and significant capital cost compared to the benefits they introduce. In this paper, a novel system for mechanical 3D US scanning is introduced to address these issues. Methods: The authors have developed a handheld mechanical 3D US system that incorporates mechanical translation and tilt sector sweeping of any standard 2D US transducer to acquire 3D images. Each mechanical scanning function can be operated independently or may be combined to allow for a hybrid wide FOV acquisition. The hybrid motion mode facilitates registration of other modalities (e.g., CT or MRI) to the intraoperative 3D US images by providing a larger FOV in which to acquire anatomical information. The tilting mechanism of the developed mover allows image acquisition in the intercostal rib space to avoid acoustic shadowing from bone. The geometric and volumetric scanning validity of the 3D US system was evaluated on tissue mimicking US phantoms for different modes of operation. Identical experiments were performed on a commercially available 3D US system for direct comparison. To replicate a clinical scenario, the authors evaluated their 3D US system by comparing it to CT for measurement of angle and distance between interventional needles in different configurations, similar to those used for percutaneous ablation of liver tumors. Results: The mean geometrical hybrid 3D reconstruction error measured from scanning of a known string phantom was less than 1 mm in two directions and 2.5 mm in the scanning direction, which was comparable or better than the same measurements obtained from a commercially available 3D US system. The error in volume measurements of spherical phantom models depended on depth of the object. For a 20 cm3 model at a depth of 15 cm, a standard depth for liver imaging, the mean error was 3.6% ± 4.5% comparable to the 2.3% ± 1.8% error for the 3D US commercial system. The error in 3D US measurement of the tip distance and angle between two microwave ablation antennas inserted into the phantom was 0.9 ± 0.5 mm and 1.1° ± 0.7°, respectively. Conclusions: A 3D US system with hybrid scanning motions for large field-of-view 3D abdominal imaging has been developed and validated. The superior spatial information provided by 3D US might enhance image-guidance for percutaneous interventional treatment of liver malignancies. The system has potential to be integrated with other liver procedures and has application in other abdominal organs such as kidneys, spleen, or adrenals. [ABSTRACT FROM AUTHOR]

Purpose: Ultrasound imaging has improved the treatment of prostate cancer by producing increasingly higher quality images and influencing sophisticated targeting procedures for the insertion of radioactive seeds during brachytherapy. However, it is critical that the needles be placed accurately within the prostate to deliver the therapy to the planned location and avoid complications of damaging surrounding tissues. Methods: The authors have developed a compact mechatronic system, as well as an effective method for guiding and controlling the insertion of transperineal needles into the prostate. This system has been designed to allow guidance of a needle obliquely in 3D space into the prostate, thereby reducing pubic arch interference. The choice of needle trajectory and location in the prostate can be adjusted manually or with computer control. Results: To validate the system, a series of experiments were performed on phantoms. The 3D scan of the string phantom produced minimal geometric error, which was less than 0.4 mm. Needle guidance accuracy tests in agar prostate phantoms showed that the mean error of bead placement was less then 1.6 mm along parallel needle paths that were within 1.2 mm of the intended target and 1° from the preplanned trajectory. At oblique angles of up to 15° relative to the probe axis, beads were placed to within 3.0 mm along a trajectory that were within 2.0 mm of the target with an angular error less than 2°. Conclusions: By combining 3D TRUS imaging system to a needle tracking linkage, this system should improve the physician's ability to target and accurately guide a needle to selected targets without the need for the computer to directly manipulate and insert the needle. This would be beneficial as the physician has complete control of the system and can safely maneuver the needle guide around obstacles such as previously placed needles. [ABSTRACT FROM AUTHOR]

Purpose: Automatic identification of the biopsy-core tissue location during a prostate biopsy procedure would provide verification that targets were adequately sampled and would allow for appropriate intraprocedure biopsy target modification. Localization of the biopsy core requires accurate segmentation of the biopsy needle and needle tip from transrectal ultrasound (TRUS) biopsy images. A temporal-based TRUS needle segmentation algorithm was developed specifically for the prostate biopsy procedure to automatically identify the TRUS image containing the biopsy needle from a collection of 2D TRUS images and to segment the biopsy-core location from the 2D TRUS image. Methods: The temporal-based segmentation algorithm performs a temporal analysis on a series of biopsy TRUS images collected throughout needle insertion and withdrawal. Following the identification of points of needle insertion and retraction, the needle axis is segmented using a Hough transform-based algorithm, which is followed by a temporospectral TRUS analysis to identify the biopsy-needle tip. Validation of the temporal-based algorithm is performed on 108 TRUS biopsy sequences collected from the procedures of ten patients. The success of the temporal search to identify the proper images was manually assessed, while the accuracies of the needle-axis and needle-tip segmentations were quantitatively compared to implementations of two other needle segmentation algorithms within the literature. Results: The needle segmentation algorithm demonstrated a >99% accuracy in identifying the TRUS image at the moment of needle insertion from the collection of real-time TRUS images throughout the insertion and withdrawal of the biopsy needle. The segmented biopsy-needle axes were accurate to within 2.3±2.0° and 0.48±0.42 mm of the gold standard. Identification of the needle tip to within half of the biopsy-core length (<10 mm) was 95% successful with a mean error of 2.4±4.0 mm. Needle-tip detection using the temporal-based algorithm was significantly more accurate (p<0.001) than the other two algorithms tested, while the segmentation of the needle axis was not significantly different between the three algorithms. Conclusions: The temporal-based needle segmentation algorithm accurately segments the location of the biopsy core from 2D TRUS images of clinical prostate biopsy procedures. The results for needle-tip localization demonstrated that the temporal-based algorithm is significantly more accurate than implementations of some existing needle segmentation algorithms within the literature. [ABSTRACT FROM AUTHOR]

Quantitative measurements of carotid atherosclerosis can be determined using three-dimensional ultrasound (3DUS). This pilot study involved the development of prospective cardiac gating of 3DUS carotid images to reduce cardiac cycle-derived arterial pulsatility. The method developed uses electrocardiograph signal detection of the cardiac cycle R wave with imaging acquisition delayed in time (Δt) after the R wave is detected. Pulsatility of the common carotid artery was measured by calculating the mean percentage change in arterial cross-sectional area (%ΔA) in moderate atherosclerosis (MA) patients (12%±1%) and healthy volunteers (HVs) (16%±3%) and found that %ΔA was significantly higher for HV than for MA (p=0.016) when no cardiac gating was used. The cardiac gating method was tested with Δt=250 ms and Δt=400 ms in young healthy volunteers and rheumatoid arthritis (RA) patients. For all 3DUS measurements acquired without gating, there was a significant association between %ΔA and age (r2=0.20, p=0.035), and mean %ΔA (in HV and RA) was 13%±5% [95% confidence interval (CI)=10%–17%]. For Δt=250 ms mean %ΔA was significantly different and decreased to 7%±3% (95% CI=5%–10%) and for Δt=400 ms it was significantly different and decreased to 6%±1% (95% CI=6%–7%) (p=0.001 for both comparisons). There was no significant difference in mean %ΔA between gating conditions (p=0.8); however, the 95% CI for %ΔA was decreased for Δt=400 ms as compared to Δt=250 ms. Both gating methods also significantly decreased %ΔA to below the reference standard of 12%±1% for MA (p<0.01 for both comparisons), suggesting that prospective cardiac gating of carotid 3DUS reduces pulsatility effects in HV and RA to levels lower than observed for much older MA patients. [ABSTRACT FROM AUTHOR]

There are currently limitations associated with the prostate biopsy procedure, which is the most commonly used method for a definitive diagnosis of prostate cancer. With the use of two-dimensional (2D) transrectal ultrasound (TRUS) for needle-guidance in this procedure, the physician has restricted anatomical reference points for guiding the needle to target sites. Further, any motion of the physician’s hand during the procedure may cause the prostate to move or deform to a prohibitive extent. These variations make it difficult to establish a consistent reference frame for guiding a needle. We have developed a 3D navigation system for prostate biopsy, which addresses these shortcomings. This system is composed of a 3D US imaging subsystem and a passive mechanical arm to minimize prostate motion. To validate our prototype, a series of experiments were performed on prostate phantoms. The 3D scan of the string phantom produced minimal geometric distortions, and the geometric error of the 3D imaging subsystem was 0.37 mm. The accuracy of 3D prostate segmentation was determined by comparing the known volume in a certified phantom to a reconstructed volume generated by our system and was shown to estimate the volume with less then 5% error. Biopsy needle guidance accuracy tests in agar prostate phantoms showed that the mean error was 2.1 mm and the 3D location of the biopsy core was recorded with a mean error of 1.8 mm. In this paper, we describe the mechanical design and validation of the prototype system using an in vitro prostate phantom. Preliminary results from an ongoing clinical trial show that prostate motion is small with an in-plane displacement of less than 1 mm during the biopsy procedure. [ABSTRACT FROM AUTHOR]

Purpose: Three-dimensional (3D) transrectal ultrasound (TRUS)-guided systems have been developed to improve targeting accuracy during prostate biopsy. However, prostate motion during the procedure is a potential source of error that can cause target misalignments. The authors present an image-based registration technique to compensate for prostate motion by registering the live two-dimensional (2D) TRUS images acquired during the biopsy procedure to a preacquired 3D TRUS image. The registration must be performed both accurately and quickly in order to be useful during the clinical procedure. Methods: The authors implemented an intensity-based 2D-3D rigid registration algorithm optimizing the normalized cross-correlation (NCC) metric using Powell's method. The 2D TRUS images acquired during the procedure prior to biopsy gun firing were registered to the baseline 3D TRUS image acquired at the beginning of the procedure. The accuracy was measured by calculating the target registration error (TRE) using manually identified fiducials within the prostate; these fiducials were used for validation only and were not provided as inputs to the registration algorithm. They also evaluated the accuracy when the registrations were performed continuously throughout the biopsy by acquiring and registering live 2D TRUS images every second. This measured the improvement in accuracy resulting from performing the registration, continuously compensating for motion during the procedure. To further validate the method using a more challenging data set, registrations were performed using 3D TRUS images acquired by intentionally exerting different levels of ultrasound probe pressures in order to measure the performance of our algorithm when the prostate tissue was intentionally deformed. In this data set, biopsy scenarios were simulated by extracting 2D frames from the 3D TRUS images and registering them to the baseline 3D image. A graphics processing unit (GPU)-based implementation was used to improve the registration speed. They also studied the correlation between NCC and TREs. Results: The root-mean-square (RMS) TRE of registrations performed prior to biopsy gun firing was found to be 1.87 ± 0.81 mm. This was an improvement over 4.75 ± 2.62 mm before registration. When the registrations were performed every second during the biopsy, the RMS TRE was reduced to 1.63 ± 0.51 mm. For 3D data sets acquired under different probe pressures, the RMS TRE was found to be 3.18 ± 1.6 mm. This was an improvement from 6.89 ± 4.1 mm before registration. With the GPU based implementation, the registrations were performed with a mean time of 1.1 s. The TRE showed a weak correlation with the similarity metric. However, the authors measured a generally convex shape of the metric around the ground truth, which may explain the rapid convergence of their algorithm to accurate results. Conclusions: Registration to compensate for prostate motion during 3D TRUS-guided biopsy can be performed with a measured accuracy of less than 2 mm and a speed of 1.1 s, which is an important step toward improving the targeting accuracy of a 3D TRUS-guided biopsy system. [ABSTRACT FROM AUTHOR]