MR imaging-guided interventions are well established in routine patient care in many parts of the world. There are many approaches, depending on magnet design and clinical need, based on MR imaging providing excellent inherent tissue contrast without ionizing radiation risk for patients. MR imaging-guided minimally invasive therapeutic procedures have advantages over conventional surgical procedures. In the genitourinary tract, MR imaging guidance has a role in tumor detection, localization, and staging and can provide accurate image guidance for minimally invasive procedures. The advent of molecular and metabolic imaging and use of higher strength magnets likely will improve diagnostic accuracy and allow targeted therapy to maximize disease control and minimize side effects.
RATIONALE AND OBJECTIVES: The aim of this study was to develop non-rigid image registration between preprocedure contrast-enhanced magnetic resonance (MR) images and intraprocedure unenhanced computed tomographic (CT) images, to enhance tumor visualization and localization during CT imaging-guided liver tumor cryoablation procedures. MATERIALS AND METHODS: A non-rigid registration technique was evaluated with different preprocessing steps and algorithm parameters and compared to a standard rigid registration approach. The Dice similarity coefficient, target registration error, 95th-percentile Hausdorff distance, and total registration time (minutes) were compared using a two-sided Student's t test. The entire registration method was then applied during five CT imaging-guided liver cryoablation cases with the intraprocedural CT data transmitted directly from the CT scanner, with both accuracy and registration time evaluated. RESULTS: Selected optimal parameters for registration were a section thickness of 5 mm, cropping the field of view to 66% of its original size, manual segmentation of the liver, B-spline control grid of 5 × 5 × 5, and spatial sampling of 50,000 pixels. A mean 95th-percentile Hausdorff distance of 3.3 mm (a 2.5 times improvement compared to rigid registration, P < .05), a mean Dice similarity coefficient of 0.97 (a 13% increase), and a mean target registration error of 4.1 mm (a 2.7 times reduction) were measured. During the cryoablation procedure, registration between the preprocedure MR and the planning intraprocedure CT imaging took a mean time of 10.6 minutes, MR to targeting CT image took 4 minutes, and MR to monitoring CT imaging took 4.3 minutes. Mean registration accuracy was <3.4 mm. CONCLUSIONS: Non-rigid registration allowed improved visualization of the tumor during interventional planning, targeting, and evaluation of tumor coverage by the ice ball. Future work is focused on reducing segmentation time to make the method more clinically acceptable.
We present a shape optimization approach to compute patient-specific models in customized prototyping applications. We design a coupled shape prior to model the transformation between a related pair of surfaces, using a nonparametric joint probability density estimation. The coupled shape prior forces with the help of application-specific data forces and smoothness forces drive a surface deformation towards a desired output surface. We demonstrate the usefulness of the method for generating customized shape models in applications of hearing aid design and pre-operative to intra-operative anatomic surface estimation.
Jumpei Arata, Hiroaki Kozuka, Hyung Wook Kim, Naoyuki Takesue, B Vladimirov, Masamichi Sakaguchi, Junichi Tokuda, Nobuhiko Hata, Kiyoyuki Chinzei, and Hideo Fujimoto. 2010. “Open Core Control sSoftware for Surgical Robots.” Int J Comput Assist Radiol Surg, 5, 3, Pp. 211-20.Abstract
OBJECT: In these days, patients and doctors in operation room are surrounded by many medical devices as resulting from recent advancement of medical technology. However, these cutting-edge medical devices are working independently and not collaborating with each other, even though the collaborations between these devices such as navigation systems and medical imaging devices are becoming very important for accomplishing complex surgical tasks (such as a tumor removal procedure while checking the tumor location in neurosurgery). On the other hand, several surgical robots have been commercialized, and are becoming common. However, these surgical robots are not open for collaborations with external medical devices in these days. A cutting-edge "intelligent surgical robot" will be possible in collaborating with surgical robots, various kinds of sensors, navigation system and so on. On the other hand, most of the academic software developments for surgical robots are "home-made" in their research institutions and not open to the public. Therefore, open source control software for surgical robots can be beneficial in this field. From these perspectives, we developed Open Core Control software for surgical robots to overcome these challenges. MATERIALS AND METHODS: In general, control softwares have hardware dependencies based on actuators, sensors and various kinds of internal devices. Therefore, these control softwares cannot be used on different types of robots without modifications. However, the structure of the Open Core Control software can be reused for various types of robots by abstracting hardware dependent parts. In addition, network connectivity is crucial for collaboration between advanced medical devices. The OpenIGTLink is adopted in Interface class which plays a role to communicate with external medical devices. At the same time, it is essential to maintain the stable operation within the asynchronous data transactions through network. In the Open Core Control software, several techniques for this purpose were introduced. Virtual fixture is well known technique as a "force guide" for supporting operators to perform precise manipulation by using a master-slave robot. The virtual fixture for precise and safety surgery was implemented on the system to demonstrate an idea of high-level collaboration between a surgical robot and a navigation system. The extension of virtual fixture is not a part of the Open Core Control system, however, the function such as virtual fixture cannot be realized without a tight collaboration between cutting-edge medical devices. By using the virtual fixture, operators can pre-define an accessible area on the navigation system, and the area information can be transferred to the robot. In this manner, the surgical console generates the reflection force when the operator tries to get out from the pre-defined accessible area during surgery. RESULTS: The Open Core Control software was implemented on a surgical master-slave robot and stable operation was observed in a motion test. The tip of the surgical robot was displayed on a navigation system by connecting the surgical robot with a 3D position sensor through the OpenIGTLink. The accessible area was pre-defined before the operation, and the virtual fixture was displayed as a "force guide" on the surgical console. In addition, the system showed stable performance in a duration test with network disturbance. CONCLUSION: In this paper, a design of the Open Core Control software for surgical robots and the implementation of virtual fixture were described. The Open Core Control software was implemented on a surgical robot system and showed stable performance in high-level collaboration works. The Open Core Control software is developed to be a widely used platform of surgical robots. Safety issues are essential for control software of these complex medical devices. It is important to follow the global specifications such as a FDA requirement "General Principles of Software Validation" or IEC62304. For following these regulations, it is important to develop a self-test environment. Therefore, a test environment is now under development to test various interference in operation room such as a noise of electric knife by considering safety and test environment regulations such as ISO13849 and IEC60508. The Open Core Control software is currently being developed software in open-source manner and available on the Internet. A communization of software interface is becoming a major trend in this field. Based on this perspective, the Open Core Control software can be expected to bring contributions in this field.
Water diffusion in nerve fibers is strongly influenced by axon architecture. In this study, fractional diffusion anisotropy and transverse and longitudinal diffusion coefficients were measured in excised human cervical spinal cord with MR line-scan diffusion imaging, at 625 microm in-plane resolution and 3 mm slice thickness. A pixel-based comparison of fractional diffusion anisotropy, transverse diffusion coefficient, and longitudinal diffusion coefficient data with axon packing parameters derived from corresponding stained histological sections was performed for four slices. The axon packing parameters, axon density, axon area-fraction, and average axon size for entire specimen cross-sections were calculated by computerized segmentation of optical microscopy data obtained at 0.53 microm resolution. Salient features could be recognized on fractional diffusion anisotropy, transverse diffusion coefficient, axon density, axon area fraction, and average axon size maps. For white matter regions only, the average correlation coefficients for fractional diffusion anisotropy compared to histology-based parameters axon density and axon area fraction were 0.37 and 0.21, respectively. For transverse diffusion coefficient compared to axon density and axon area fraction, they were -0.40 and -0.36, and for longitudinal diffusion coefficient compared to axon density and axon area fraction, -0.14 and -0.30. All average correlation coefficients for average axon size were low. Correlation coefficients for collectively analyzed white and gray matter regions were significantly higher than correlation coefficients derived from analysis of white matter regions only.
PURPOSE: To demonstrate reduced field-of-view (RFOV) single-shot fast spin echo (SS-FSE) imaging based on the use of two-dimensional spatially selective radiofrequency (2DRF) pulses.
MATERIALS AND METHODS: The 2DRF pulses were incorporated into an SS-FSE sequence for RFOV imaging in both phantoms and the human brain on a 1.5 Tesla (T) whole-body MR system with the aim of demonstrating improvements in terms of shorter scan time, reduced blurring, and higher spatial resolution compared with full FOV imaging.
RESULTS: For phantom studies, scan time gains of up to 4.2-fold were achieved as compared to the full FOV imaging. For human studies, the spatial resolution was increased by a factor of 2.5 (from 1.7 mm/pixel to 0.69 mm/pixel) for RFOV imaging within a scan time (0.7 s) similar to full FOV imaging. A 2.2-fold shorter scan time along with a significant reduction of blurring was demonstrated in RFOV images compared with full FOV images for a target spatial resolution of 0.69 mm/pixel.
CONCLUSION: RFOV SS-FSE imaging using a 2DRF pulse shows advantages in scan time, blurring, and specific absorption rate reduction along with true spatial resolution increase compared with full FOV imaging. This approach is promising to benefit fast imaging applications such as image guided therapy.
Nyquist ghosts are an inherent artifact in echo planar imaging acquisitions. An approach to robustly eliminate Nyquist ghosts is presented that integrates two previous Nyquist ghost correction techniques: temporal domain encoding (phase labeling for additional coordinate encoding: PLACE and spatial domain encoding (phased array ghost elimination: PAGE). Temporal encoding modulates the echo planar imaging acquisition trajectory from frame to frame, enabling one to interleave data to remove inconsistencies that occur between sampling on positive and negative gradient readouts. With PLACE, one can coherently combine the interleaved data to cancel residual Nyquist ghosts. If the level of ghosting varies significantly from image to image, however, the signal cancellation that occurs with PLACE can adversely affect SNR-sensitive applications such as perfusion imaging with arterial spin labeling. This work proposes integrating PLACE into a PAGE-based reconstruction process to yield significantly better Nyquist ghost correction that is more robust than PLACE or PAGE alone. The robustness of this method is demonstrated in the presence of magnetic field drift with an in-vivo arterial spin labeling perfusion experiment.
BACKGROUND AND STUDY AIMS: Most natural orifice transluminal endoscopic surgery (NOTES) procedures have been performed in animal models through the anterior stomach wall, but this approach does not provide efficient access to all anatomic areas of interest. Moreover, injury of the adjacent structures has been reported when using a blind access. The aim of the current study was to assess the utility of a CT-based (CT: computed tomography) image registered navigation system in identifying safe gastrointestinal access sites for NOTES and identifying intraperitoneal structures. METHODS: A total of 30 access procedures were performed in 30 pigs: anterior gastric wall (n = 10), posterior gastric wall (n = 10), and anterior rectal wall (n = 10). Of these, 15 procedures used image registered guidance (IR-NOTES) and 15 procedures used a blind access (NOTES only). Timed abdominal exploration was performed with identification of 11 organs. The location of the endoscopic tip was tracked using an electromagnetic tracking system and was recorded for each case. Necropsy was performed immediately after the procedure. The primary outcome was the rate of complications; secondary outcome variables were number of organs identified and kinematic measurements. RESULTS: A total of 30 animals weighting a mean (± SD) of 30.2 ± 6.8 kg were included in the study. The incision point was correctly placed in 11 out of 15 animals in each group (73.3 %). The mean peritoneoscopy time and the number of properly identified organs were equivalent in the two groups. There were eight minor complications (26.7 %), two (13.3 %) in the IR-NOTES group and six (40.0 %) in the NOTES only group ( P = n. s.). Characteristics of the endoscope tip path showed a statistically significant improvement in trajectory smoothness of motion for all organs in the IR-NOTES group. CONCLUSION: The image registered system appears to be feasible in NOTES procedures and results from this study suggest that image registered guidance might be useful for supporting navigation with an increased smoothness of motion.
Planar projection methods have been shown to rapidly relate fields between two planes. Such an approach is particularly useful for characterizing transducers, since only a single plane needs to be measured in order to characterize an entire field. The present work considers the same approach in the presence of an arbitrary dispersion relation. Unlike traditional methods that use Fourier solutions of the time-domain wave equation, the approach starts from a frequency-domain Helmholtz equation for waves in a dispersive medium. It is shown that a transfer function similar to that derived from time domain equations can be utilized. Both the forward- and backward-projection behaviors are examined and it is demonstrated that the approach is invariant to propagation direction.
Conventional spatial-spectral radiofrequency pulses excite the water or the fat spins in a whole slice or slab. While such pulses prove useful in a number of applications, their applicability is severely limited in sequences with short pulse repetition time due to the relatively long duration of the pulses. In the present work, we demonstrate that, by manipulating the parameters of a two-dimensional spartially-selective (2DRF) pulse designed to excite a two-dimensional spatial profile, the chemical-shift sensitivity of the pulse can be exploited to obtain potentially useful spatially varying fat-water excitation patterns.
Low-frequency transcranial ultrasound (<1 MHz) is being investigated for a number of brain therapies, including stroke, tumor ablation, and localized opening of the blood-brain barrier. However, lower frequencies have been associated with the production of undesired standing waves and cavitation in the brain. Presently, we examine an approach to suppress standing waves during continuous-wave (CW) transcranial application. The investigation uses a small randomization in the frequency content of the signal for suppressing standing waves. The approach is studied in an ex-vivo human skull and a plastic-walled chamber, representing idealized conditions. The approach is compared to single-frequency CW operation as well as to a swept-frequency input. Acoustic field scans demonstrate that the swept-frequency method can suppress standing waves in the plastic chamber and skull by 3.4 and 1.6 times, respectively, compared to single-frequency CW excitation. With random modulation, standing waves were reduced by 5.6 and 2 times, respectively, in the plastic chamber and skull. It is expected that the process may play a critical role in providing a safer application of the ultrasound field in the brain and may have application in other areas where standing waves may be created.
Registration uncertainty may be important information to convey to a surgeon when surgical decisions are taken based on registered image data. However, conventional non-rigid registration methods only provide the most likely deformation. In this paper we show how to determine the registration uncertainty, as well as the most likely deformation, by using an elastic Bayesian registration framework that generates a dense posterior distribution on deformations. We model both the likelihood and the elastic prior on deformations with Boltzmann distributions and characterize the posterior with a Markov Chain Monte Carlo algorithm. We introduce methods that summarize the high-dimensional uncertainty information and show how these summaries can be visualized in a meaningful way. Based on a clinical neurosurgical dataset, we demonstrate the importance that uncertainty information could have on neurosurgical decision making.
This work provides a model for tubular structures, and devises an algorithm to automatically extract tubular anatomical structures from medical imagery. Our model fits many anatomical structures in medical imagery, in particular, various fiber bundles in the brain (imaged through diffusion-weighted magnetic resonance (DW-MRI)) such as the cingulum bundle, and blood vessel trees in computed tomography angiograms (CTAs). Extraction of the cingulum bundle is of interest because of possible ties to schizophrenia, and extracting blood vessels is helpful in the diagnosis of cardiovascular diseases. The tubular model we propose has advantages over many existing approaches in literature: fewer degrees-of-freedom over a general deformable surface hence energies defined on such tubes are less sensitive to undesirable local minima, and the tube (in 3-D) can be naturally represented by a 4-D curve (a radius function and centerline), which leads to computationally less costly algorithms and has the advantage that the centerline of the tube is obtained without additional effort. Our model also generalizes to tubular trees, and the extraction algorithm that we design automatically detects and evolves branches of the tree. We demonstrate the performance of our algorithm on 20 datasets of DW-MRI data and 32 datasets of CTA, and quantify the results of our algorithm when expert segmentations are available.
Successful and accurate imaging of prostate cancer is integral to its clinical management from detection and staging to subsequent monitoring. Various modalities are used including ultrasound, computed tomography, and magnetic resonance imaging, with the greatest advances seen in the field of magnetic resonance.
OBJECTIVE: Accurate biopsy sampling of the suspected lesions is critical for the diagnosis and clinical management of prostate cancer. Transperineal in-bore MRI-guided prostate biopsy (tpMRgBx) is a targeted biopsy technique that was shown to be safe, efficient, and accurate. Our goal was to develop an open source software platform to support evaluation, refinement, and translation of this biopsy approach. METHODS: We developed SliceTracker, a 3D Slicer extension to support tpMRgBx. We followed modular design of the implementation to enable customization of the interface and interchange of image segmentation and registration components to assess their effect on the processing time, precision, and accuracy of the biopsy needle placement. The platform and supporting documentation were developed to enable the use of software by an operator with minimal technical training to facilitate translation. Retrospective evaluation studied registration accuracy, effect of the prostate segmentation approach, and re-identification time of biopsy targets. Prospective evaluation focused on the total procedure time and biopsy targeting error (BTE). RESULTS: Evaluation utilized data from 73 retrospective and ten prospective tpMRgBx cases. Mean landmark registration error for retrospective evaluation was 1.88 ± 2.63 mm, and was not sensitive to the approach used for prostate gland segmentation. Prospectively, we observed target re-identification time of 4.60 ± 2.40 min and BTE of 2.40 ± 0.98 mm. CONCLUSION: SliceTracker is modular and extensible open source platform for supporting image processing aspects of the tpMRgBx procedure. It has been successfully utilized to support clinical research procedures at our site.
Patient-mounted needle guide devices for percutaneous ablation are vulnerable to patient motion. The objective of this study is to develop and evaluate a software system for an MRI-compatible patient-mounted needle guide device that can adaptively compensate for displacement of the device due to patient motion using a novel image-based automatic device-to-image registration technique. We have developed a software system for an MRI-compatible patient-mounted needle guide device for percutaneous ablation. It features fully-automated image-based device-to-image registration to track the device position, and a device controller to adjust the needle trajectory to compensate for the displacement of the device. We performed: (a) a phantom study using a clinical MR scanner to evaluate registration performance; (b) simulations using intraoperative time-series MR data acquired in 20 clinical cases of MRI-guided renal cryoablations to assess its impact on motion compensation; and (c) a pilot clinical study in three patients to test its feasibility during the clinical procedure. FRE, TRE, and success rate of device-to-image registration were [Formula: see text] mm, [Formula: see text] mm, and 98.3% for the phantom images. The simulation study showed that the motion compensation reduced the targeting error for needle placement from 8.2 mm to 5.4 mm (p < 0.0005) in patients under general anesthesia (GA), and from 14.4 mm to 10.0 mm ([Formula: see text]) in patients under monitored anesthesia care (MAC). The pilot study showed that the software registered the device successfully in a clinical setting. Our simulation study demonstrated that the software system could significantly improve targeting accuracy in patients treated under both MAC and GA. Intraprocedural image-based device-to-image registration was feasible.
PURPOSE: To develop and evaluate an approach to estimate the respiratory-induced motion of lesions in the chest and abdomen. MATERIALS AND METHODS: The proposed approach uses the motion of an initial reference needle inserted into a moving organ to estimate the lesion (target) displacement that is caused by respiration. The needles position is measured using an inertial measurement unit (IMU) sensor externally attached to the hub of an initially placed reference needle. Data obtained from the IMU sensor and the target motion are used to train a learning-based approach to estimate the position of the moving target. An experimental platform was designed to mimic respiratory motion of the liver. Liver motion profiles of human subjects provided inputs to the experimental platform. Variables including the insertion angle, target depth, target motion velocity and target proximity to the reference needle were evaluated by measuring the error of the estimated target position and processing time. RESULTS: The mean error of estimation of the target position ranged between 0.86 and 1.29 mm. The processing maximum training and testing time was 5 ms which is suitable for real-time target motion estimation using the needle position sensor. CONCLUSION: The external motion of an initially placed reference needle inserted into a moving organ can be used as a surrogate, measurable and accessible signal to estimate in real-time the position of a moving target caused by respiration; this technique could then be used to guide the placement of subsequently inserted needles directly into the target.
Brain shift during tumor resection compromises the spatial validity of registered preoperative imaging data that is critical to image-guided procedures. One current clinical solution to mitigate the effects is to reimage using intraoperative magnetic resonance (iMR) imaging. Although iMR has demonstrated benefits in accounting for preoperative-to-intraoperative tissue changes, its cost and encumbrance have limited its widespread adoption. While iMR will likely continue to be employed for challenging cases, a cost-effective model-based brain shift compensation strategy is desirable as a complementary technology for standard resections. We performed a retrospective study of [Formula: see text] tumor resection cases, comparing iMR measurements with intraoperative brain shift compensation predicted by our model-based strategy, driven by sparse intraoperative cortical surface data. For quantitative assessment, homologous subsurface targets near the tumors were selected on preoperative MR and iMR images. Once rigidly registered, intraoperative shift measurements were determined and subsequently compared to model-predicted counterparts as estimated by the brain shift correction framework. When considering moderate and high shift ([Formula: see text], [Formula: see text] measurements per case), the alignment error due to brain shift reduced from [Formula: see text] to [Formula: see text], representing [Formula: see text] correction. These first steps toward validation are promising for model-based strategies.
OBJECTIVE: The purpose of this article is to report our intermediate to long-term outcomes with image-guided percutaneous hepatic tumor cryoablation and to evaluate its technical success, technique efficacy, local tumor progression, and adverse event rate. MATERIALS AND METHODS: Between 1998 and 2014, 299 hepatic tumors (243 metastases and 56 primary tumors; mean diameter, 2.5 cm; median diameter, 2.2 cm; range, 0.3-7.8 cm) in 186 patients (95 women; mean age, 60.9 years; range, 29-88 years) underwent cryoablation during 236 procedures using CT (n = 126), MRI (n = 100), or PET/CT (n = 10) guidance. Technical success, technique efficacy at 3 months, local tumor progression (mean follow-up, 2.5 years; range, 2 months to 14.6 years), and adverse event rates were calculated. RESULTS: The technical success rate was 94.6% (279/295). The technique efficacy rate was 89.5% (231/258) and was greater for tumors smaller than 4 cm (93.4%; 213/228) than for larger tumors (60.0%; 18/30) (p < 0.0001). Local tumor progression occurred in 23.3% (60/258) of tumors and was significantly more common after the treatment of tumors 4 cm or larger (63.3%; 19/30) compared with smaller tumors (18.0%; 41/228) (p < 0.0001). Adverse events followed 33.8% (80/236) of procedures and were grade 3-5 in 10.6% (25/236) of cases. Grade 3 or greater adverse events more commonly followed the treatment of larger tumors (19.5%; 8/41) compared with smaller tumors (8.7%; 17/195) (p = 0.04). CONCLUSION: Image-guided percutaneous cryoablation of hepatic tumors is efficacious; however, tumors smaller than 4 cm are more likely to be treated successfully and without an adverse event.