A variety of advanced image analysis methods have been under development for ultrasound-guided interventions. Unfortunately, the transition from an image analysis algorithm to clinical feasibility trials as part of an intervention system requires integration of many components, such as imaging and tracking devices, data processing algorithms, and visualization software. The objective of our work is to provide a freely available open-source software platform – PLUS: Public software Library for Ultrasound – to facilitate rapid prototyping of ultrasound-guided intervention systems for translational clinical research. PLUS provides a variety of methods for interventional tool pose and ultrasound image acquisition from a wide range of tracking and imaging devices, spatial and temporal calibration, volume reconstruction, simulated image generation, and recording and live streaming of the acquired data. This paper introduces PLUS, explains its functionality and architecture, and presents typical uses and performance in ultrasound-guided intervention systems. PLUS fulfills the essential requirements for the development of ultrasound-guided intervention systems and it aspires to become a widely used translational research prototyping platform. PLUS is freely available as open source under BSD license, the code and documentation are available at http://www.plustoolkit.org.
This paper presents the development, preclinical evaluation, and preliminary clinical study of a robotic system for targeted transperineal prostate biopsy under direct interventional magnetic resonance imaging (MRI) guidance. The clinically integrated robotic system is developed based on a modular design approach, comprised of surgical navigation application, robot control software, MRI robot controller hardware, and robotic needle placement manipulator. The system provides enabling technologies for MRI-guided procedures. It can be easily transported and setup for supporting the clinical workflow of interventional procedures, and the system is readily extensible and reconfigurable to other clinical applications. Preclinical evaluation of the system is performed with phantom studies in a 3 Tesla MRI scanner, rehearsing the proposed clinical workflow, and demonstrating an in-plane targeting error of 1.5mm. The robotic system has been approved by the institutional review board (IRB) for clinical trials. A preliminary clinical study is conducted with the patient consent, demonstrating the targeting errors at two biopsy target sites to be 4.0mm and 3.7mm, which is sufficient to target a clinically significant tumor foci. First-in-human trials to evaluate the system’s effectiveness and accuracy for MR image-guide prostate biopsy are underway.
The authors found properly adjusting the TRUS imaging settings to lower the ultrasound gain and power effectively minimized the appearance of elevation beamwidth artifacts and in turn reduced the localization errors of the needle tip.
This paper presents the results of a feasibility study to demonstrate the application of ultrasound RF time series imaging to accurately differentiate ablated and nonablated tissue. For 12 ex vivo and two in situ tissue samples, RF ultrasound signals are acquired prior to, and following, high-intensity ultrasound ablation. Spatial and temporal features of these signals are used to characterize ablated and nonablated tissue in a supervised-learning framework. In cross-validation evaluation, a subset of four features extracted from RF time series produce a classification accuracy of 84.5%, an area under ROC curve of 0.91 for ex vivo data, and an accuracy of 85% for in situ data. Ultrasound RF time series is a promising approach for characterizing ablated tissue.
We successfully performed MRgRA iFUS ablation in swine and found intraoperative and postoperative imaging to correlate with histological examination. These data are useful to validate our system and to guide imaging follow-up for thermal ablation lesions in brain tissue from our therapy, tcMRgFUS, and LITT.
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