Lori Gardi

Mechanically assisted 3D ultrasound guided prostate biopsy system

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 physicians 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.

Brachytherapy needle deflection evaluation and correction.

In prostate brachytherapy, an 18-gauge needle is used to implant radioactive seeds. This thin needle can be deflected from the preplanned trajectory in the prostate, potentially resulting in a suboptimum dose pattern and at times requiring repeated needle insertion to achieve optimal dosimetry. In this paper, we report on the evaluation of brachytherapy needle deflection and bending in test phantoms and two approaches to overcome the problem. First we tested the relationship between needle deflection and insertion depth as well as whether needle bending occurred. Targeting accuracy was tested by inserting a brachytherapy needle to target 16 points in chicken tissue phantoms. By implanting dummy seeds into chicken tissue phantoms under 3D ultrasound guidance, the overall accuracy of seed implantation was determined. We evaluated methods to overcome brachytherapy needle deflection with three different insertion methods: constant orientation, constant rotation, and orientation reversal at half of the insertion depth. Our results showed that needle deflection is linear with needle insertion depth, and that no noticeable bending occurs with needle insertion into the tissue and agar phantoms. A 3D principal component analysis was performed to obtain the population distribution of needle tip and seed position relative to the target positions. Our results showed that with the constant orientation insertion method, the mean needle targeting error was 2.8 mm and the mean seed implantation error was 2.9 mm. Using the constant rotation and orientation reversal at half insertion depth methods, the deflection error was reduced. The mean needle targeting errors were 0.8 and 1.2 mm for the constant rotation and orientation reversal methods, respectively, and the seed implantation errors were 0.9 and 1.5 mm for constant rotation insertion and orientation reversal methods, respectively.

Assessment of image registration accuracy in three-dimensional transrectal ultrasound guided prostate biopsy

PURPOSE Prostate biopsy, performed using two-dimensional (2D) transrectal ultrasound (TRUS) guidance, is the clinical standard for a definitive diagnosis of prostate cancer. Histological analysis of the biopsies can reveal cancerous, noncancerous, or suspicious, possibly precancerous, tissue. During subsequent biopsy sessions, noncancerous regions should be avoided, and suspicious regions should be precisely rebiopsied, requiring accurate needle guidance. It is challenging to precisely guide a needle using 2D TRUS due to the limited anatomic information provided, and a three-dimensional (3D) record of biopsy locations for use in subsequent biopsy procedures cannot be collected. Our tracked, 3D TRUS-guided prostate biopsy system provides additional anatomic context and permits a 3D record of biopsies. However, targets determined based on a previous biopsy procedure must be transformed during the procedure to compensate for intraprocedure prostate shifting due to patient motion and prostate deformation due to transducer probe pressure. Thus, registration is a critically important step required to determine these transformations so that correspondence is maintained between the prebiopsied image and the real-time image. Registration must not only be performed accurately, but also quickly, since correction for prostate motion and deformation must be carried out during the biopsy procedure. The authors evaluated the accuracy, variability, and speed of several surface-based and image-based intrasession 3D-to-3D TRUS image registration techniques, for both rigid and nonrigid cases, to find the required transformations. METHODS Our surface-based rigid and nonrigid registrations of the prostate were performed using the iterative-closest-point algorithm and a thin-plate spline algorithm, respectively. For image-based rigid registration, the authors used a block matching approach, and for nonrigid registration, the authors define the moving image deformation using a regular, 3D grid of B-spline control points. The authors measured the target registration error (TRE) as the postregistration misalignment of 60 manually marked, corresponding intrinsic fiducials. The authors also measured the fiducial localization error (FLE), the effect of segmentation variability, and the effect of fiducial distance from the transducer probe tip. Lastly, the authors performed 3D principal component analysis (PCA) on the x, y, and z components of the TREs to examine the 95% confidence ellipsoids describing the errors for each registration method. RESULTS Using surface-based registration, the authors found mean TREs of 2.13 +/- 0.80 and 2.09 +/- 0.77 mm for rigid and nonrigid techniques, respectively. Using image-based rigid and non-rigid registration, the authors found mean TREs of 1.74 +/- 0.84 and 1.50 +/- 0.83 mm, respectively. Our FLE was 0.21 mm and did not dominate the overall TRE. However, segmentation variability contributed substantially approximately50%) to the TRE of the surface-based techniques. PCA showed that the 95% confidence ellipsoid encompassing fiducial distances between the source and target registra- tion images was reduced from 3.05 to 0.14 cm3, and 0.05 cm3 for the surface-based and image-based techniques, respectively. The run times for both registration methods were comparable at less than 60 s. CONCLUSIONS Our results compare favorably with a clinical need for a TRE of less than 2.5 mm, and suggest that image-based registration is superior to surface-based registration for 3D TRUS-guided prostate biopsies, since it does not require segmentation.

2D-3D rigid registration to compensate for prostate motion during 3D TRUS-guided biopsy.

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 Powells 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.

A compact mechatronic system for 3D ultrasound guided prostate interventions.

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 degree from the preplanned trajectory. At oblique angles of up to 15 degrees 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 degrees. CONCLUSIONS By combining 3D TRUS imaging system to a needle tracking linkage, this system should improve the physicians 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.

A 3D ultrasound scanning system for image guided liver interventions

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 cm(3) 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.

Robotic-aided 3D TRUS guided intraoperative prostate brachytherapy

We have developed a robotic aided 3D transrectal ultrasound (TRUS) guided, intraoperative prostate brachytherapy. This system allows brachytherapy needles to be inserted into the prostate along various trajectories including oblique to avoid pubic arch interference. We unified the robotic coordinate system with the 3D TRUS image coordinate system. In addition, we also hdeveloped the method to automatically detect the needle in TRUS images for oblique insertion. We have evaluated our prototype system using prostate phantoms in terms of different needle insertion depths and the distances of the needle from the TRUS transducer. We have shown that our robotic aided 3D TRUS guided system was capable of placing the needle tip with approximately 0.74 mm ± 0.24 mm accuracy at a target identified in the 3D TRUS image. Brachytherapy accuracy was tested by dropping 0.8 mm beads into prostate phantoms via various angles up to ± 20°. Our results showed that the bead-dropping accuracy was 2.59 mm ± 0.76 mm with the error due to the needle deflection caused by the needles bevel.

Oblique needle segmentation for 3D TRUS-guided robot-aided transperineal prostate brachytherapy

3D TRUS-guided robot-aided prostate brachytherapy provides tools for dynamic re-optimization of a dose plan by freeing needle insertions from parallel trajectory constraints, i.e., needle trajectories can be positioned with considerable flexibility including oblique. However, oblique insertion results in the needle intersecting the 2D TRUS image and appearing as a dot, leading to blind guidance. Here, we propose a method for oblique needle segmentation and tracking to be used in a 3D TRUS guided and robot aided prostate brachytherapy system. This algorithm applies a grey-level change detection technique to find the location and orientation of needles from 3D images. Three 2D images containing the needle (oblique sagittal, coronal and transverse planes) are extracted and displayed in near real-time. Testing showed that our algorithm can find 3D needle orientation within 0.54/spl deg/ for a chicken tissue phantom, and 0.58/spl deg/ for agar phantoms, over a /spl plusmn/15/spl deg/ insertion orientation. The execution time averaged 0.13s on a 1.2 GHz computer.

Registered 3-D Ultrasound and Digital Stereotactic Mammography for Breast Biopsy Guidance

Large core needle biopsy is a common procedure used to obtain histological samples when cancer is suspected in diagnostic breast images. The procedure is typically performed under image guidance, with freehand ultrasound and stereotactic mammography (SM) being the most common modalities used. To utilize the advantages of both modalities, a biopsy device combining three-dimensional ultrasound (3DUS) and digital SM imaging with computer-aided needle guidance was developed. An implementation of a stereo camera method was applied to SM calibration, providing a target localization error of 0.35 mm. The 3D transformation between the two imaging modalities was then derived, with a target registration error of 0.52 mm. Finally, the needle guidance error of the device was evaluated using tissue-mimicking phantoms, showing a sample mean and standard deviation of and 0.49 plusmn 0.27 mm for targets planned from 3DUS and SM images, respectively. These results suggest that a biopsy procedure guided using this device would successfully sample breast lesions at a size greater than or equal to the smallest typically detected in mammographic screening (~2mm).

Fusion of MRI to 3D TRUS for mechanically-assisted targeted prostate biopsy: system design and initial clinical experience

This paper presents a mechanically-assisted 3D transrectal ultrasound (TRUS) biopsy system with MRI-3D TRUS fusion. The 3D TRUS system employs a 4 degree-of-freedom linkage for real-time TRUS probe tracking. MRI-TRUS fusion is achieved using a surface-based nonlinear registration incorporating thin-plate splines to provide real-time overlays of suspicious MRI lesions on 3D TRUS for intrabiopsy targeted needle guidance. Clinical use of the system is demonstrated on a prospective cohort study of 25 patients with clinical findings concerning for prostate adenocarcinoma (PCa). The MRI-3D TRUS registration accuracy is quantified and compared with alternative algorithms for optimal performance. Results of the clinical study demonstrated a significantly higher rate of positive biopsy cores and a higher Gleason score cancer grading for targeted biopsies using the MRI-3D TRUS fusion as compared to the standard 12-core sextant biopsy distribution. Lesion targeted biopsy cores that were positive for PCa contained a significantly higher percentage of tumor within each biopsy sample compared to the sextant cores and in some patients resulted in identifying higher risk disease.