BACKGROUND: Macrophages contribute to the progression and acute complications of atherosclerosis. Macrophage imaging may serve as a biomarker to identify subclinical inflamed lesions, to predict future risk, and to aid in the assessment of novel therapies. METHODS AND RESULTS: To test the hypothesis that nanoparticle-enhanced, high-resolution magnetic resonance imaging (MRI) can measure plaque macrophage accumulation, we used 3-T MRI with a macrophage-targeted superparamagnetic nanoparticle preparation (monocrystalline iron oxide nanoparticles-47 [MION-47]) in cholesterol-fed New Zealand White rabbits 6 months after balloon injury. In vivo MRI visualized thickened abdominal aortas on both T1- and T2-weighted spin-echo images (T1 spin echo, 20 axial slices per animal; T2 spin echo, 28 slices per animal). Seventy-two hours after MION-47 injection, aortas exhibited lower T2 signal intensity compared with before contrast imaging (signal intensity ratio, aortic wall/muscle: before, 1.44 ± 0.26 versus after, 0.95 ± 0.22; 164 slices; P<0.01), whereas T1 spin echo images showed no significant change. MRI on ex vivo specimens provided similar results. Histological studies colocalized iron accumulation with immunoreactive macrophages in atheromata. The magnitude of signal intensity reduction on T2 spin echo in vivo images further correlated with macrophage areas in situ (150 slices; r=0.73). Treatment with rosuvastatin for 3 months yielded diminished macrophage content (P<0.05) and reversed T2 signal intensity changes (P<0.005). Signal changes in rosuvastatin-treated rabbits correlated with reduced macrophage burden (r=0.73). In vitro validation studies showed concentration-dependent MION-47 uptake by human primary macrophages. CONCLUSION: The magnitude of T2 signal intensity reduction in high-resolution MRI after administration of superparamagnetic phagocytosable nanoparticles can assess macrophage burden in atheromata, providing a clinically translatable tool to identify inflamed plaques and to monitor therapy-mediated changes in plaque inflammation.
OBJECTIVE: To quantify size and localization differences between tumors presenting with seizures vs nonseizure neurological symptoms. DESIGN: Retrospective imaging survey. We performed magnetic resonance imaging-based morphometric analysis and nonparametric mapping in patients with brain tumors. SETTING: University-affiliated teaching hospital. PATIENTS OR OTHER PARTICIPANTS: One hundred twenty-four patients with newly diagnosed supratentorial glial tumors. MAIN OUTCOME MEASURES: Volumetric and mapping methods were used to evaluate differences in size and location of the tumors in patients who presented with seizures as compared with patients who presented with other symptoms. RESULTS: In high-grade gliomas, tumors presenting with seizures were smaller than tumors presenting with other neurological symptoms, whereas in low-grade gliomas, tumors presenting with seizures were larger. Tumor location maps revealed that in high-grade gliomas, deep-seated tumors in the pericallosal regions were more likely to present with nonseizure neurological symptoms. In low-grade gliomas, tumors of the temporal lobe as well as the insular region were more likely to present with seizures. CONCLUSIONS: The influence of size and location of the tumors on their propensity to cause seizures varies with the grade of the tumor. In high-grade gliomas, rapidly growing tumors, particularly those situated in deeper structures, present with non-seizure-related symptoms. In low-grade gliomas, lesions in the temporal lobe or the insula grow large without other symptoms and eventually cause seizures. Quantitative image analysis allows for the mapping of regions in each group that are more or less susceptible to seizures.
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.
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.
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.
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.
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.
An inherent drawback of the traditional diffusion tensor model is its limited ability to provide detailed information about multidirectional fiber architecture within a voxel. This leads to erroneous fiber tractography results in locations where fiber bundles cross each other. This may lead to the inability to visualize clinically important tracts such as the lateral projections of the corticospinal tract. In this report, we present a deterministic two-tensor eXtended Streamline Tractography (XST) technique, which successfully traces through regions of crossing fibers. We evaluated the method on simulated and in vivo human brain data, comparing the results with the traditional single-tensor and with a probabilistic tractography technique. By tracing the corticospinal tract and correlating with fMRI-determined motor cortex in both healthy subjects and patients with brain tumors, we demonstrate that two-tensor deterministic streamline tractography can accurately identify fiber bundles consistent with anatomy and previously not detected by conventional single-tensor tractography. When compared to the dense connectivity maps generated by probabilistic tractography, the method is computationally efficient and generates discrete geometric pathways that are simple to visualize and clinically useful. Detection of crossing white matter pathways can improve neurosurgical visualization of functionally relevant white matter areas.
Real-time functional MRI (rtfMRI) has been used as a basis for brain-computer interface (BCI) due to its ability to characterize region-specific brain activity in real-time. As an extension of BCI, we present an rtfMRI-based brain-machine interface (BMI) whereby 2-dimensional movement of a robotic arm was controlled by the regulation (and concurrent detection) of regional cortical activations in the primary motor areas. To do so, the subjects were engaged in the right- and/or left-hand motor imagery tasks. The blood oxygenation level dependent (BOLD) signal originating from the corresponding hand motor areas was then translated into horizontal or vertical robotic arm movement. The movement was broadcasted visually back to the subject as a feedback. We demonstrated that real-time control of the robotic arm only through the subjects' thought processes was possible using the rtfMRI-based BMI trials.
Quantitative, apparent T(2) values of suspected prostate cancer and healthy peripheral zone tissue in men with prostate cancer were measured using a Carr-Purcell-Meiboom-Gill (CPMG) imaging sequence in order to assess the cancer discrimination potential of tissue T(2) values. The CPMG imaging sequence was used to image the prostates of 18 men with biopsy-proven prostate cancer. Whole gland coverage with nominal voxel volumes of 0.54 x 1.1 x 4 mm(3) was obtained in 10.7 min, resulting in data sets suitable for generating high-quality images with variable T(2)-weighting and for evaluating quantitative T(2) values on a pixel-by-pixel basis. Region-of-interest analysis of suspected healthy peripheral zone tissue and suspected cancer, identified on the basis of both T(1)- and T(2)-weighted signal intensities and available histopathology reports, yielded significantly (P<.0001) longer apparent T(2) values in suspected healthy tissue (193+/-49 ms) vs. suspected cancer (100+/-26 ms), suggesting potential utility of this method as a tissue specific discrimination index for prostate cancer. We conclude that CPMG imaging of the prostate can be performed in reasonable scan times and can provide advantages over T(2)-weighted fast spin echo (FSE) imaging alone, including quantitative T(2) values for cancer discrimination as well as proton density maps without the point spread function degradation associated with short effective echo time FSE sequences.
Language functional magnetic resonance imaging (fMRI) is a promising non-invasive technique for pre-surgical planning in patients whose lesions are adjacent to or within critical language areas. Most language fMRI studies in patients use blocked experimental design. In this study, we compared a blocked design and a rapid event-related design with a jittered inter-stimulus-interval (ISI) (or stochastic design) for language fMRI in six healthy controls, and eight brain tumor patients, using a vocalized antonym generation task. Comparisons were based on visual inspection of fMRI activation maps and degree of language lateralization, both of which were assessed at a constant statistical threshold for each design. The results indicated a relatively high degree of discordance between the two task designs. In general, the event-related design provided maps with more robust activations in the putative language areas than the blocked design, especially for brain tumor patients. Our results suggest that the rapid event-related design has potential for providing comparable or even higher detection power over the blocked design for localizing language function in brain tumor patients, and therefore may be able to generate more sensitive language maps. More patient studies, and further investigation and optimization of language fMRI paradigms will be needed to determine the utility and validity of this approach for pre-surgical planning.
We introduce a framework for computing geometrical properties of white matter fibres directly from diffusion tensor fields. The key idea is to isolate the portion of the gradient of the tensor field corresponding to local variation in tensor orientation, and to project it onto a coordinate frame of tensor eigenvectors. The resulting eigenframe-centered representation makes it possible to define scalar geometrical measures that describe the underlying white matter fibres, directly from the diffusion tensor field and its gradient, without requiring prior tractography. We define two new scalar measures of (1) fibre dispersion and (2) fibre curving, and we demonstrate them on synthetic and in-vivo datasets. Finally, we illustrate their applicability in a group study on schizophrenia.
RATIONALE AND OBJECTIVES: The authors present their initial experience using a 3-T whole-body scanner equipped with a 128-channel coil applied to lung motion assessment. Recent improvements in fast magnetic resonance imaging (MRI) technology have enabled several trials of free-breathing three-dimensional (3D) imaging of the lung. A large number of image frames necessarily increases the difficulty of image analysis and therefore warrants automatic image processing. However, the intensity homogeneities of images of prior dynamic 3D lung MRI studies have been insufficient to use such methods. In this study, initial data were obtained at 3 T with a 128-channel coil that demonstrate the feasibility of acquiring multiple sets of 3D pulmonary scans during free breathing and that have sufficient quality to be amenable to automatic segmentation.
MATERIALS AND METHODS: Dynamic 3D images of the lungs of two volunteers were acquired with acquisition times of 0.62 to 0.76 frames/s and an image matrix of 128 x 128, with 24 to 30 slice encodings. The volunteers were instructed to take shallow and deep breaths during the scans. The variation of lung volume was measured from the segmented images.
RESULTS: Dynamic 3D images were successfully acquired for both respiratory conditions for each subject. The images showed whole-lung motion, including lifting of the chest wall and the displacement of the diaphragm, with sufficient contrast to distinguish these structures from adjacent tissues. The average time to complete segmentation for one 3D image was 4.8 seconds. The tidal volume measured was consistent with known tidal volumes for healthy subjects performing deep-breathing maneuvers. The temporal resolution was insufficient to measure tidal volumes for shallow breathing.
CONCLUSION: This initial experience with a 3-T whole-body scanner and a 128-channel coil showed that the scanner and imaging protocol provided dynamic 3D images with spatial and temporal resolution sufficient to delineate the diaphragmatic domes and chest wall during active breathing. In addition, the intensity homogeneities and signal-to-noise ratio were adequate to perform automatic segmentation.
OBJECTIVE: The objective of this study was to investigate a method to generate positive contrast, selective to superparamagnetic iron oxide (SPIO) labeled cells, using the susceptibility-weighted echo-time encoding technique (SWEET).
MATERIALS AND METHODS: SPIO-labeled human epidermal carcinoma (KB) cells were placed in a gel phantom. Positive contrast from the labeled cells was created by subtraction between conventional spin-echo images and echo-time shifted susceptibility-weighted images. SPIO-labeled cells were injected into the left dorsal flank and hind limb of nude mice, and unlabeled cells were placed on the right side as controls. Tumor growth was monitored using the proposed method, and a histological analysis was used to confirm the presence of the labeled cells.
RESULTS: Based on in vitro testing, we could detect 5000 labeled cells at minimum and the number of pixels with positive contrast increased proportionally to the number of labeled cells. Animal experiments also revealed the presence of tumor growth from SPIO-loaded cells.
CONCLUSIONS: We demonstrated that the proposed method, based on the simple principle of echo-time shift, could be readily implemented in a clinical scanner to visualize the magnetic susceptibility effects of SPIO-loaded cells through a positive-contrast mechanism.
We describe a technique to simultaneously estimate a weighted, positive-definite multi-tensor fiber model and perform tractography. Existing techniques estimate the local fiber orientation at each voxel independently so there is no running knowledge of confidence in the estimated fiber model. We formulate fiber tracking as recursive estimation: at each step of tracing the fiber, the current estimate is guided by the previous. To do this we model the signal as a weighted mixture of Gaussian tensors and perform tractography within a filter framework. Starting from a seed point, each fiber is traced to its termination using an unscented Kalman filter to simultaneously fit the local model and propagate in the most consistent direction. Further, we modify the Kalman filter to enforce model constraints, i.e. positive eigenvalues and convex weights. Despite the presence of noise and uncertainty, this provides a causal estimate of the local structure at each point along the fiber. Synthetic experiments demonstrate that this approach significantly improves the angular resolution at crossings and branchings while consistently estimating the mixture weights. In vivo experiments confirm the ability to trace out fibers in areas known to contain such crossing and branching while providing inherent path regularization.
Automated interpretation and classification of functional MRI (fMRI) data is an emerging research field that enables the characterization of underlying cognitive processes with minimal human intervention. In this work, we present a method for the automated classification of human thoughts reflected on a trial-based paradigm using fMRI with a significantly shortened data acquisition time (less than one minute). Based on our preliminary experience with various cognitive imagery tasks, six characteristic thoughts were chosen as target tasks for the present work: right-hand motor imagery, left-hand motor imagery, right foot motor imagery, mental calculation, internal speech/word generation, and visual imagery. These six tasks were performed by five healthy volunteers and functional images were obtained using a T(*)(2)-weighted echo planar imaging (EPI) sequence. Feature vectors from activation maps, necessary for the classification of neural activity, were automatically extracted from the regions that were consistently and exclusively activated for a given task during the training process. Extracted feature vectors were classified using the support vector machine (SVM) algorithm. Parameter optimization, using a k-fold cross validation scheme, allowed the successful recognition of the six different categories of administered thought tasks with an accuracy of 74.5% (mean)+/-14.3% (standard deviation) across all five subjects. Our proposed study for the automated classification of fMRI data may be utilized in further investigations to monitor/identify human thought processes and their potential link to hardware/computer control.
BACKGROUND: A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning.
RESULTS: We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications.
CONCLUSION: Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.
The diffusion coefficient of lipids, D(l), within bone marrow, fat deposits and metabolically active intracellular lipids in vivo will depend on several factors including the precise chemical composition of the lipid distribution (chain lengths, degree of unsaturation, etc.) as well as the temperature. As such, D(l) may ultimately prove of value in assessing abnormal fatty acid distributions linked to diseases such as cystic fibrosis, diabetes and coronary heart disease. A sensitive temperature dependence of D(l) may also prove of value for MR-guided thermal therapies for bone tumors or disease within other fatty tissues like the breast. Measuring diffusion coefficients of high molecular weight lipids in vivo is, however, technically difficult for a number of reasons. For instance, due to the much lower diffusion coefficients compared to water, much higher b factors than those used for central nervous system applications are needed. In addition, the pulse sequence design must incorporate, as much as possible, immunity to motion, susceptibility and chemical shift effects present whenever body imaging is performed. In this work, high b-factor line scan diffusion imaging sequences were designed, implemented and tested for D(l) measurement using a 4.7-T horizontal bore animal scanner. The gradient set available allowed for b factors as high as 0.03 micros/nm(2) (30,000 s/mm(2)) at echo times as short as 42 ms. The methods were used to measure lipid diffusion coefficients within the marrow of rat paws in vivo, yielding lipid diffusion coefficients approximately two orders of magnitude smaller than typical tissue water diffusion coefficients. Phantom experiments that demonstrate the sensitivity of lipid diffusion coefficients to chain length and temperature were also performed.
MR diffusion tensor imaging (DTI) can measure and visualize organization of white matter fibre tracts in vivo. DTI is a relatively new imaging technique, and new tools developed for quantifying fibre tracts require evaluation. The purpose of this study was to compare the reliability of a novel clustering approach with a multiple region of interest (MROI) approach in both healthy and disease (schizophrenia) populations. DTI images were acquired in 20 participants (n=10 patients with schizophrenia: 56+/-15 years; n=10 controls: 51+/-20 years) (1.5 T GE system) with diffusion gradients applied in 23 non-collinear directions, repeated three times. Whole brain seeding and creation of fibre tracts were then performed. Interrater reliability of the clustering approach, and the MROI approach, were each evaluated and the methods compared. There was high spatial (voxel-based) agreement within and between the clustering and MROI methods. Fractional anisotropy, trace, and radial and axial diffusivity values showed high intraclass correlation (p<0.001 for all tracts) for each approach. Differences in scalar indices of diffusion between the clustering and MROI approach were minimal. The excellent interrater reliability of the clustering method and high agreement with the MROI method, quantitatively and spatially, indicates that the clustering method can be used with confidence. The clustering method avoids biases of ROI drawing and placement, and, not limited by a priori predictions, may be a more robust and efficient way to identify and measure white matter tracts of interest.
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.
OBJECTIVE: We report nine consecutive percutaneous image-guided cryoablation procedures of head and neck tumors in seven patients (four men and three women; mean age, 68 years; age range, 50-78 years). Ablation of the entire tumor for local control or ablation of a region of tumor for pain relief or preservation of function was achieved in eight of nine procedures. One patient experienced intraprocedural bradycardia, and another developed a neopharyngeal abscess. There were no deaths, permanent neurologic or functional deficits, vascular complications, or adverse cosmetic sequelae due to the procedures. CONCLUSION: Percutaneous image-guided cryoablation offers a potentially less morbid minimally invasive treatment option than salvage head and neck surgery. The complications that we encountered may be avoidable with increased experience. Further work is needed to continue improving the safety and efficacy of cryoablation of head and neck tumors and to continue expanding the use of cryoablation in patients with head and neck tumors that cannot be treated surgically.