A Study of Needle Image Artifact Localization in Confirmation Imaging of MRI-guided Robotic Prostate Biopsy

Automatic needle tracking using Mask R-CNN for MRI-guided percutaneous interventions

PURPOSE

Accurate needle tracking provides essential information for MRI-guided percutaneous interventions. Passive needle tracking using MR images is challenged by variations of the needle-induced signal void feature in different situations. This work aimed to develop an automatic needle tracking algorithm for MRI-guided interventions based on the Mask Region Proposal-Based Convolutional Neural Network (R-CNN).

METHODS

Mask R-CNN was adapted and trained to segment the needle feature using 250 intra-procedural images from 85 MRI-guided prostate biopsy cases and 180 real-time images from MRI-guided needle insertion in ex vivo tissue. The segmentation masks were passed into the needle feature localization algorithm to extract the needle feature tip location and axis orientation. The proposed algorithm was tested using 208 intra-procedural images from 40 MRI-guided prostate biopsy cases, and 3 real-time MRI datasets in ex vivo tissue. The algorithm results were compared with human-annotated references.

RESULTS

In prostate datasets, the proposed algorithm achieved needle feature tip localization error with median Euclidean distance (dxy) of 0.71 mm and median difference in axis orientation angle (dθ) of 1.28°, respectively. In 3 real-time MRI datasets, the proposed algorithm achieved consistent dynamic needle feature tracking performance with processing time of 75 ms/image: (a) median dxy = 0.90 mm, median dθ = 1.53°; (b) median dxy = 1.31 mm, median dθ = 1.9°; (c) median dxy = 1.09 mm, median dθ = 0.91°.

CONCLUSIONS

The proposed algorithm using Mask R-CNN can accurately track the needle feature tip and axis on MR images from in vivo intra-procedural prostate biopsy cases and ex vivo real-time MRI experiments with a range of different conditions. The algorithm achieved pixel-level tracking accuracy in real time and has potential to assist MRI-guided percutaneous interventions.

Real-time probe tracking using EM-optical sensor for MRI-guided cryoablation

BACKGROUND

A method of real-time, accurate probe tracking at the entrance of the MRI bore is developed, which, fused with pre-procedural MR images, will enable clinicians to perform cryoablation efficiently in a large workspace with image guidance.

METHODS

Electromagnetic (EM) tracking coupled with optical tracking is used to track the probe. EM tracking is achieved with an MRI-safe EM sensor working under the scanner's magnetic field to compensate the line-of-sight issue of optical tracking. Unscented Kalman filter-based probe tracking is developed to smooth the EM sensor measurements when occlusion occurs and to improve the tracking accuracy by fusing the measurements of two sensors.

RESULTS

Experiments with a spine phantom show that the mean targeting errors using the EM sensor alone and using the proposed method are 2.21 mm and 1.80 mm, respectively.

CONCLUSION

The proposed method achieves more accurate probe tracking than using an EM sensor alone at the MRI scanner entrance.

Accuracy study of a robotic system for MRI-guided prostate needle placement

BACKGROUND

Accurate needle placement is the first concern in percutaneous MRI-guided prostate interventions. In this phantom study, different sources contributing to the overall needle placement error of a MRI-guided robot for prostate biopsy have been identified, quantified and minimized to the possible extent.

METHODS

The overall needle placement error of the system was evaluated in a prostate phantom. This error was broken into two parts: the error associated with the robotic system (called 'before-insertion error') and the error associated with needle-tissue interaction (called 'due-to-insertion error'). Before-insertion error was measured directly in a soft phantom and different sources contributing into this part were identified and quantified. A calibration methodology was developed to minimize the 4-DOF manipulator's error. The due-to-insertion error was indirectly approximated by comparing the overall error and the before-insertion error. The effect of sterilization on the manipulator's accuracy and repeatability was also studied.

RESULTS

The average overall system error in the phantom study was 2.5 mm (STD = 1.1 mm). The average robotic system error in the Super Soft plastic phantom was 1.3 mm (STD = 0.7 mm). Assuming orthogonal error components, the needle-tissue interaction error was found to be approximately 2.13 mm, thus making a larger contribution to the overall error. The average susceptibility artifact shift was 0.2 mm. The manipulator's targeting accuracy was 0.71 mm (STD = 0.21 mm) after robot calibration. The robot's repeatability was 0.13 mm. Sterilization had no noticeable influence on the robot's accuracy and repeatability.

CONCLUSIONS

The experimental methodology presented in this paper may help researchers to identify, quantify and minimize different sources contributing into the overall needle placement error of an MRI-guided robotic system for prostate needle placement. In the robotic system analysed here, the overall error of the studied system remained within the acceptable range.

Towards ultrasound probe positioning optimization during prostate needle biopsy using pressure feedback

PURPOSE

Accurate Transrectal Ultrasound (TRUS)-guided prostate needle biopsy requires registering preoperative 3D TRUS or MR image, in which tumors and other suspicious areas are visible, to intraoperative 2D TRUS images. Such image registration is time-consuming while its real-time implementation is yet to be developed. To bypass this registration step, robotic needle biopsy systems can be used to place the US probe at the same position relative to the prostate during the 3D and 2D image acquisition to ensure similar prostate deformation. To have such similar deformation, only visual feedback is not sufficient as such feedback can be used to only guarantee that the whole prostate is within the field of view irrespective of the probe's orientation. As such, contact pressure feedback can be utilized to ensure consistent minimum contact between the probe and prostate.

METHOD

A robotic system is proposed where a TRUS probe with pressure sensor array is used. The contact pressure can be measured during imaging and used to provide feedback in conjunction with an optimization algorithm for consistent probe positioning. The robotic system is driven by the feedback to position the probe such that pressure pattern of the sensors during 2D image acquisition is similar to the pressure pattern during 3D image acquisition. The proposed method takes into account the patient's body movement expected during image acquisition. In this study, an in silico phantom is used where the simulated contact pressure distribution required in the optimization algorithm is obtained using a prostate finite element model.

RESULT

Starting from an arbitrary position where the probe contacts the phantom, this position was varied systematically until a position corresponding to maximum pressure pattern similarity between contact pressure patterns corresponding to the 2D and 3D imaging was achieved successfully.

CONCLUSION

Results obtained from the in silico phantom study indicate that the proposed technique is capable of ensuring having only minimal relative prostate deformation between preoperative image acquisition and intraoperative imaging used for guiding needle biopsy, paving the way for faster and more accurate registration.

Biopsy needle artifact localization in MRI-guided robotic transrectal prostate intervention

Recently a number of robotic intervention systems for magnetic resonance image (MRI)-guided needle placement in the prostate have been reported. In MRI-guided needle interventions, after a needle is inserted, the needle position is often confirmed with a volumetric MRI scan. Commonly used titanium needles are not directly visible in an MRI, but they generate a susceptibility artifact in the immediate neighborhood of the needle. This paper reports the results of a quantitative study of the relationship between the true position of titanium biopsy needle and the corresponding needle artifact position in MRI, thereby providing a better understanding of the influence of needle artifact on targeting errors. The titanium needle tip artifact extended 9 mm beyond the actual needle tip location with tendency to bend toward the scanner's B (0) magnetic field direction, and axially displaced 0.38 and 0.32 mm (mean) in scanner's frequency and phase encoding direction, respectively.