Faculty Bibliography

The radio frequency ablation segmentation tool (RFAST) is a software application developed using the National Institutes of Health's medical image processing analysis and visualization (MIPAV) API for the specific purpose of assisting physicians in the planning of radio frequency ablation (RFA) procedures. The RFAST application sequentially leads the physician through the steps necessary to register, fuse, segment, visualize, and plan the RFA treatment. Three-dimensional volume visualization of the CT dataset with segmented three dimensional (3-D) surface models enables the physician to interactively position the ablation probe to simulate burns and to semimanually simulate sphere packing in an attempt to optimize probe placement. This paper describes software systems contained in RFAST to address the needs of clinicians in planning, evaluating, and simulating RFA treatments of malignant hepatic tissue.

This paper investigates the possibility of using the motion of a patient's anterior surface in combination with a motion model to compensate for internal respiratory motion during tracked biopsies. Position data from two electromagnetically tracked sensors, one placed on the patient's sternum, the other incorporated into a biopsy needle, were acquired during a liver biopsy. The data were used to evaluate the correlation between the position measurements of the two sensors and to derive an affine motion model to assess respiratory motion compensation for image-guided interventional procedures. The correlation reached up to 94% for ranges of steady respiration. The residual motion of the internal sensor after compensation is reduced by a factor of approximately four.

Purpose: To demonstrate clinical feasibility and measure accuracy of electromagnetic tracking for guidance of soft-tissue biopsy and radiofrequency ablation Methods: A prototype interventional guidance system based on electromagnetic tracking was used to evaluate retrospectively the accuracy of needle tracking in 20 patients. Target organs were liver (10), kidney (6), lung (3) and spine (1). Registration between tracking space and image space was obtained by touching 5 to 7 skin fiducials with the tracked needle during expiration breath holds. Tracking accuracy was determined by comparing the tracked needle sensor position, mapped onto the pre-acquired CT scan using the registration transformation, with the needle sensor position manually identified in the confirmation CT scans. Results: A total of 65 CT-confirmed needle positions were obtained. One patient was excluded from the analysis because of his inability to consistently follow breathing commands. The mean fiducials registration error was 1.9 +/- 0.6 mm; the mean tracking accuracy was 5.8 +/- 2.6 mm. Accuracy in liver (4.7 mm) was significantly (p = 0.05) better than in lung (8.7 mm). Conclusions: Electromagnetic needle tracking is safe and provides potential benefits to interventional procedures, including more accurate needle placement and reduced procedure time The demonstrated tracking accuracy is clinically relevant and warrants clinical evaluation of tracking for procedure guidance. This research was supported in part by the Intramural Research Program of the NIH, Clinical Center.

To demonstrate the feasibility of CT and B-mode Ultrasound (US) targeted HIFU, a prototype coaxial focused ultrasound transducer was registered and integrated to a CT scanner. CT and diagnostic ultrasound were used for HIFU targeting and monitoring, with the goals of both thermal ablation and non-thermal enhanced drug delivery. A 1 megahertz coaxial ultrasound transducer was custom fabricated and attached to a passive position-sensing arm and an active six degree-of-freedom. robotic arm via a CT stereotactic frame. The outer therapeutic transducer with a 10 cm fixed focal zone was coaxially mounted to an inner diagnostic US transducer (2-4 megahertz, Philips Medical Systems). This coaxial US transducer was connected to a modified commercial focused ultrasound generator (Focus Surgery, Indianapolis, IN) with a maximum total acoustic power of 100 watts. This pre-clinical paradigm was tested for ability to heat tissue in phantoms with monitoring and navigation from CT and live US. The feasibility of navigation via image fusion of CT with other modalities such as PET and MRI was demonstrated. Heated water phantoms were tested for correlation between CT numbers and temperature (for ablation monitoring). The prototype transducer and integrated CT/US imaging system enabled simultaneous multimodality imaging and therapy. Pre-clinical phantom models validated the treatment paradigm and demonstrated integrated multimodality guidance and treatment monitoring. Temperature changes during phantom cooling corresponded to CT number changes. Contrast enhanced or non-enhanced CT numbers may potentially be used to monitor thermal ablation with HIFU. Integrated CT, diagnostic US, and therapeutic focused ultrasound bridges a gap between diagnosis and therapy. Preliminary results show that the multimodality system may represent a relatively inexpensive, accessible, and simple method of both targeting and monitoring HIFU effects. Small animal pre-clinical models may be translated to large animals and humans for HIFU-induced ablation and drug delivery. Integrated CT-guided focused ultrasound holds promise for tissue ablation, enhancing local drug delivery, and CT thermometry for monitoring ablation in near real-time.

PURPOSE: To assess the feasibility of the use of preprocedural imaging for guide wire, catheter, and needle navigation with electromagnetic tracking in phantom and animal models. MATERIALS AND METHODS: An image-guided intervention software system was developed based on open-source software components. Catheters, needles, and guide wires were constructed with small position and orientation sensors in the tips. A tetrahedral-shaped weak electromagnetic field generator was placed in proximity to an abdominal vascular phantom or three pigs on the angiography table. Preprocedural computed tomographic (CT) images of the phantom or pig were loaded into custom-developed tracking, registration, navigation, and rendering software. Devices were manipulated within the phantom or pig with guidance from the previously acquired CT scan and simultaneous real-time angiography. Navigation within positron emission tomography (PET) and magnetic resonance (MR) volumetric datasets was also performed. External and endovascular fiducials were used for registration in the phantom, and registration error and tracking error were estimated. RESULTS: The CT scan position of the devices within phantoms and pigs was accurately determined during angiography and biopsy procedures, with manageable error for some applications. Preprocedural CT depicted the anatomy in the region of the devices with real-time position updating and minimal registration error and tracking error (<5 mm). PET can also be used with this system to guide percutaneous biopsies to the most metabolically active region of a tumor. CONCLUSIONS: Previously acquired CT, MR, or PET data can be accurately codisplayed during procedures with reconstructed imaging based on the position and orientation of catheters, guide wires, or needles. Multimodality interventions are feasible by allowing the real-time updated display of previously acquired functional or morphologic imaging during angiography, biopsy, and ablation.

An experimental workstation and surgical tools are presented utilizing electro-magnetic tracking to register real-time laparoscopic ultrasound (LUS) images with static, pre-acquired CT volumes. The registration and image fusion were used to guide tracked needles to target locations in an abdominal phantom. A custom-made sleeve equipped with magnetic sensor coils and attached to the steerable tip of a commercial LUS probe allowed precise localization of the imaging array without line-of-sight restrictions. For registration with CT image space, landmarks in physical space were identified using three different methods: (1) by pointing with a separate, electro-magnetically tracked pointer, (2) by pointing with the tip of the laparoscope, or (3) by imaging and subsequent manual identification of the landmark with LUS. The root-mean square (RMS) registration error using the three methods was 1.5 mm, 1.4 mm, and 1.1 mm, respectively. Overlays of real-time LUS with pre-acquired CT demonstrated the registration quality. Based on these registrations, tracked needles were guided into user-defined target locations. The RMS placement accuracy was 1.8 mm, 1.3 mm, and 1.9 mm, respectively. Accuracy is sufficient for planned clinical trials. (c) 2005 CARS &amp; Elsevier B.V. All rights reserved.

The Radio Frequency Ablation Segmentation Tool (RFAST) is a software application developed using NIH's Medical Image Processing Analysis and Visualization (MIPAV) API for the specific purpose of assisting physicians in the planning of radio frequency ablation (RFA) procedures. The RFAST application sequentially leads the physician through the steps necessary to register, fuse, segment, visualize and plan the RFA treatment. Three-dimensional volume visualization of the CT dataset with segmented 3D surface models enables the physician to interactively position the ablation probe to simulate burns and to semi-manually simulate sphere packing in an attempt to optimize probe placement.

Ultrasound has become popular in clinical/surgical applications, both as the primary image guidance modality and also in conjunction with other modalities like CT or MRI. Three dimensional ultrasound (3DUS) systems have also demonstrated usefulness in image-guided therapy (IGT). At the same time, however, current lack of open-source and open-architecture multi-modal medical visualization systems prevents 3DUS, from fulfilling its potential. Several standalone 3DUS systems, like Stradx or In-Vivo exist today. Although these systems have been found to be useful in real clinical setting it is difficult to augment their functionality and integrate them in versatile IGT systems. To address these limitations, a robotic/freehand 3DUS open environment (CISUS) is being integrated into the 3D Slicer, an open-source research tool developed for medical image analysis and surgical planning. In addition, the system capitalizes on generic application programming interfaces (APIs) for tracking devices and robotic control. The resulting platform-independent open-source system may serve as a valuable tool to the image guided surgery community. Other researchers could straightforwardly integrate the generic CISUS system along with other functionalities (i.e. dual view visualization, registration, real-time tracking, segmentation, etc. .) to rapidly create their medical/surgical applications. Our current driving clinical application is robotically assisted and freehand 3DUS-guided liver ablation, which is fully being integrated under the CISUS-3D Slicer. Initial functionality and pre-clinical feasibility are demonstrated on phantom and ex-vivo animal models.