OBJECTIVES: This study was conducted to validate the accuracy of image-based pre-operative segmentation using the gold standard endoscopic and microscopic findings for localization and pre-operative diagnosis of the offensive vessel. PATIENTS AND METHODS: Fourteen TN and 6 HS cases were randomly selected. All patients had 3T MRI, which included thin-sectioned 3D space T2, 3D Time of Flight and MPRAGE Sequences. Imaging sequences were loaded in BrainLab iPlanNet and fused. Individual segmentation of the affected cranial nerves and the compressing vascular structure was performed by a neurosurgeon, and the results were compared with the microscopic and endoscopic findings by two blinded neurosurgeons. For each case, at least three neurovascular landmarks were targeted. Each segmented neurovascular element was validated by manual placement of the navigation probe over each target, and errors of localization were measured in mm. RESULTS: All patients underwent retro-sigmoid craniotomy and MVD using both microscope and endoscope. Based on image segmentation, the compressing vessel was identified in all cases except one, which was also negative intraoperatively. Perfect correspondence was found between image-based segmentation and endoscopic and microscopic images and videos (Dice coefficient of 1). Measurement accuracy was 0.45±0.21mm (mean±SD). CONCLUSION: Image-based segmentation is a promising method for pre-operative identification and localization of offending blood vessels causing HFS and TN. Using this method may prevent some unnecessary explorations on especially atypical cases with no vascular contacts. However, negative pre-operative image segmentation may not preclude one from exploration in classic cases of TN or HFS. A multicenter study with larger number of cases is recommended.
To enhance neuro-navigation, high quality pre-operative images must be registered onto intra-operative configuration of the brain. Therefore evaluation of the degree to which structures may remain misaligned after registration is critically important. We consider two Hausdorff Distance (HD)-based evaluation approaches: the edge-based HD (EBHD) metric and the Robust HD (RHD) metric as well as various commonly used intensity-based similarity metrics such as Mutual Information (MI), Normalised Mutual Information (NMI), Entropy Correlation Coefficient (ECC), Kullback-Leibler Distance (KLD) and Correlation Ratio (CR). We conducted the evaluation by applying known deformations to simple sample images and real cases of brain shift. We conclude that the intensity-based similarity metrics such as MI, NMI, ECC, KLD and CR do not correlate well with actual alignment errors, and hence are not useful for assessing misalignment. On the contrary, the EBHD and the RHD metrics correlated well with actual alignment errors; however, they have been found to underestimate the actual misalignment. We also note that it is beneficial to present HD results as a percentile-HD curve rather than a single number such as the 95-percentile HD. Percentile-HD curves present the full range of alignment errors and also facilitate the comparison of results obtained using different approaches. Furthermore, the qualities that should be possessed by an ideal evaluation metric were highlighted. Future studies could focus on developing such an evaluation metric.
We present a proof of concept study designed to support the clinical development of mass spectrometry imaging (MSI) for the detection of pituitary tumors during surgery. We analyzed by matrix-assisted laser desorption/ionization (MALDI) MSI six nonpathological (NP) human pituitary glands and 45 hormone secreting and nonsecreting (NS) human pituitary adenomas. We show that the distribution of pituitary hormones such as prolactin (PRL), growth hormone (GH), adrenocorticotropic hormone (ACTH), and thyroid stimulating hormone (TSH) in both normal and tumor tissues can be assessed by using this approach. The presence of most of the pituitary hormones was confirmed by using MS/MS and pseudo-MS/MS methods, and subtyping of pituitary adenomas was performed by using principal component analysis (PCA) and support vector machine (SVM). Our proof of concept study demonstrates that MALDI MSI could be used to directly detect excessive hormonal production from functional pituitary adenomas and generally classify pituitary adenomas by using statistical and machine learning analyses. The tissue characterization can be completed in fewer than 30 min and could therefore be applied for the near-real-time detection and delineation of pituitary tumors for intraoperative surgical decision-making.
RATIONALE AND OBJECTIVES: Assess the impact of implementing a structured report template and a computer-aided diagnosis (CAD) tool on the quality of prostate multiparametric magnetic resonance imaging (mp-MRI) reports.
MATERIALS AND METHODS: Institutional Review Board approval was obtained for this Health Insurance Portability and Accountability Act-compliant study performed at an academic medical center. The study cohort included all prostate mp-MRI reports (n = 385) finalized 6 months before and after implementation of a structured report template and a CAD tool (collectively the information technology [IT] tools) integrated into the picture archiving and communication system workstation. Primary outcome measure was quality of prostate mp-MRI reports. An expert panel of our institution's subspecialty-trained abdominal radiologists defined prostate mp-MRI report quality as optimal, satisfactory, or unsatisfactory based on documentation of nine variables. Reports were reviewed to extract the predefined quality variables and determine whether the IT tools were used to create each report. Chi-square and Student's t tests were used to compare report quality before and after implementation of IT tools.
RESULTS: The overall proportion of optimal or satisfactory reports increased from 29.8% (47/158) to 53.3% (121/227) (P < .001) after implementing the IT tools. Although the proportion of optimal or satisfactory reports increased among reports generated using at least one of the IT tools (47/158 = [29.8%] vs. 105/161 = [65.2%]; P < .001), there was no change in quality among reports generated without use of the IT tools (47/158 = [29.8%] vs. 16/66 = [24.2%]; P = .404).
CONCLUSIONS: The use of a structured template and CAD tool improved the quality of prostate mp-MRI reports compared to free-text report format and subjective measurement of contrast enhancement kinetic curve.
BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) tractography reconstruction of white matter pathways can help guide brain tumor resection. However, DTI tracts are complex mathematical objects and the validity of tractography-derived information in clinical settings has yet to be fully established. To address this issue, we initiated the DTI Challenge, an international working group of clinicians and scientists whose goal was to provide standardized evaluation of tractography methods for neurosurgery. The purpose of this empirical study was to evaluate different tractography techniques in the first DTI Challenge workshop. METHODS: Eight international teams from leading institutions reconstructed the pyramidal tract in four neurosurgical cases presenting with a glioma near the motor cortex. Tractography methods included deterministic, probabilistic, filtered, and global approaches. Standardized evaluation of the tracts consisted in the qualitative review of the pyramidal pathways by a panel of neurosurgeons and DTI experts and the quantitative evaluation of the degree of agreement among methods. RESULTS: The evaluation of tractography reconstructions showed a great interalgorithm variability. Although most methods found projections of the pyramidal tract from the medial portion of the motor strip, only a few algorithms could trace the lateral projections from the hand, face, and tongue area. In addition, the structure of disagreement among methods was similar across hemispheres despite the anatomical distortions caused by pathological tissues. CONCLUSIONS: The DTI Challenge provides a benchmark for the standardized evaluation of tractography methods on neurosurgical data. This study suggests that there are still limitations to the clinical use of tractography for neurosurgical decision making.
This paper proposes an inference method well-suited to large sets of medical images. The method is based upon a framework where distinctive 3D scale-invariant features are indexed efficiently to identify approximate nearest-neighbor (NN) feature matches-in O (log N) computational complexity in the number of images N. It thus scales well to large data sets, in contrast to methods based on pair-wise image registration or feature matching requiring O(N) complexity. Our theoretical contribution is a density estimator based on a generative model that generalizes kernel density estimation and K-nearest neighbor (KNN) methods.. The estimator can be used for on-the-fly queries, without requiring explicit parametric models or an off-line training phase. The method is validated on a large multi-site data set of 95,000,000 features extracted from 19,000 lung CT scans. Subject-level classification identifies all images of the same subjects across the entire data set despite deformation due to breathing state, including unintentional duplicate scans. State-of-the-art performance is achieved in predicting chronic pulmonary obstructive disorder (COPD) severity across the 5-category GOLD clinical rating, with an accuracy of 89% if both exact and one-off predictions are considered correct.
We present an image segmentation method that transfers label maps of entire organs from the training images to the novel image to be segmented. The transfer is based on sparse correspondences between keypoints that represent automatically identified distinctive image locations. Our segmentation algorithm consists of three steps: (i) keypoint matching, (ii) voting-based keypoint labeling, and (iii) keypoint-based probabilistic transfer of organ label maps. We introduce generative models for the inference of keypoint labels and for image segmentation, where keypoint matches are treated as a latent random variable and are marginalized out as part of the algorithm. We report segmentation results for abdominal organs in whole-body CT and in contrast-enhanced CT images. The accuracy of our method compares favorably to common multi-atlas segmentation while offering a speed-up of about three orders of magnitude. Furthermore, keypoint transfer requires no training phase or registration to an atlas. The algorithm's robustness enables the segmentation of scans with highly variable field-of-view.
In this paper, we present a tendon-driven continuum robot for endoscopic surgery. The robot has two sections for articulation actuated by tendon wires. By actuating the two sections independently, the robot can generate a variety of tip positions while maintaining the tip direction. This feature offers more flexibility in positioning the tip for large viewing angles of up to 180 degrees than does a conventional endoscope. To accurately estimate the tip position at large viewing angles, we employed kinematic mapping with a tension propagation model including friction between the tendon wires and the robot body. In a simulation study using this kinematic-mapping, the two-section robot at a target scale (outer diameter 1.7 mm and length 60 mm) produced a variety of tip positions within 50-mm ranges at the 180°-angle view. In the experimental validation, a 10:1 scale prototype performed three salient postures with different tip positions at the 180°-angle view. The proposed forward kinematic mapping (FKM) predicted the tip position within a tip-to-tip error of 6 mm over the 208-mm articulating length. The tip-to-tip error by FKM was significantly less than the one by conventional piecewise-constant-curvature approximation (PCCA) (FKM: 5.9 ± 2.9 mm vs. PCCA: 23.7 ± 3.6 mm, n=15, P < 0.01).
BACKGROUND: There is accumulating evidence that extent of resection (EOR) in intrinsic brain tumor surgery prolongs overall survival (OS) and progression-free survival (PFS). One of the strategies to increase EOR is the use of intraoperative MRI (ioMRI); however, considerable infrastructure investment is needed to establish and maintain a sophisticated ioMRI. We report the preliminary results of an extraoperative (eoMRI) protocol, with a focus on safety, feasibility, and EOR in intrinsic brain tumor surgery.
METHODS: Ten patients underwent an eoMRI protocol consisting of surgical resection in a conventional operating room followed by an immediate MRI in a clinical MRI scanner while the patient was still under anesthesia. If findings of the MRI suggested residual safely resectable tumor, the patient was returned to the operating room. A retrospective volumetric analysis was undertaken to investigate the percentage of tumor resected after first resection and if applicable, after further resection.
RESULTS: Six of 10 (60%) patients were thought to require no further resection after eoMRI. The EOR in these patients was 97.8% ± 1.8%. In the 4 patients who underwent further resection, the EOR during the original surgery was 88.5% ± 9.5% (P = 0.04). There was an average of 10.1% more tumor removed between the first and second surgery. In 3 of 4 (75%) of patients who returned for further resection, gross total resection of tumor was achieved.
CONCLUSION: An eoMRI protocol appears to be a safe and practical method to ensure maximum safe resections in patients with brain tumors and can be performed readily in all centers with MRI capabilities.
RATIONALE AND OBJECTIVES: Accuracy and speed are essential for the intraprocedural nonrigid magnetic resonance (MR) to computed tomography (CT) image registration in the assessment of tumor margins during CT-guided liver tumor ablations. Although both accuracy and speed can be improved by limiting the registration to a region of interest (ROI), manual contouring of the ROI prolongs the registration process substantially. To achieve accurate and fast registration without the use of an ROI, we combined a nonrigid registration technique on the basis of volume subdivision with hardware acceleration using a graphics processing unit (GPU). We compared the registration accuracy and processing time of GPU-accelerated volume subdivision-based nonrigid registration technique to the conventional nonrigid B-spline registration technique.
MATERIALS AND METHODS: Fourteen image data sets of preprocedural MR and intraprocedural CT images for percutaneous CT-guided liver tumor ablations were obtained. Each set of images was registered using the GPU-accelerated volume subdivision technique and the B-spline technique. Manual contouring of ROI was used only for the B-spline technique. Registration accuracies (Dice similarity coefficient [DSC] and 95% Hausdorff distance [HD]) and total processing time including contouring of ROIs and computation were compared using a paired Student t test.
RESULTS: Accuracies of the GPU-accelerated registrations and B-spline registrations, respectively, were 88.3 ± 3.7% versus 89.3 ± 4.9% (P = .41) for DSC and 13.1 ± 5.2 versus 11.4 ± 6.3 mm (P = .15) for HD. Total processing time of the GPU-accelerated registration and B-spline registration techniques was 88 ± 14 versus 557 ± 116 seconds (P < .000000002), respectively; there was no significant difference in computation time despite the difference in the complexity of the algorithms (P = .71).
CONCLUSIONS: The GPU-accelerated volume subdivision technique was as accurate as the B-spline technique and required significantly less processing time. The GPU-accelerated volume subdivision technique may enable the implementation of nonrigid registration into routine clinical practice.
PURPOSE: To demonstrate the utility of a robotic needle-guidance template device as compared to a manual template for in-bore 3T transperineal magnetic resonance imaging (MRI)-guided prostate biopsy. MATERIALS AND METHODS: This two-arm mixed retrospective-prospective study included 99 cases of targeted transperineal prostate biopsies. The biopsy needles were aimed at suspicious foci noted on multiparametric 3T MRI using manual template (historical control) as compared with a robotic template. The following data were obtained: the accuracy of average and closest needle placement to the focus, histologic yield, percentage of cancer volume in positive core samples, complication rate, and time to complete the procedure. RESULTS: In all, 56 cases were performed using the manual template and 43 cases were performed using the robotic template. The mean accuracy of the best needle placement attempt was higher in the robotic group (2.39 mm) than the manual group (3.71 mm, P < 0.027). The mean core procedure time was shorter in the robotic (90.82 min) than the manual group (100.63 min, P < 0.030). Percentage of cancer volume in positive core samples was higher in the robotic group (P < 0.001). Cancer yields and complication rates were not statistically different between the two subgroups (P = 0.557 and P = 0.172, respectively). CONCLUSION: The robotic needle-guidance template helps accurate placement of biopsy needles in MRI-guided core biopsy of prostate cancer.
PURPOSE: To describe how B0 inhomogeneities can cause errors in proton resonance frequency (PRF) shift thermometry, and to correct for these errors. METHODS: With PRF thermometry, measured phase shifts are converted into temperature measurements through the use of a scaling factor proportional to the echo time, TE. However, B0 inhomogeneities can deform, spread, and translate MR echoes, potentially making the "true" echo time vary spatially within the imaged object and take on values that differ from the prescribed TE value. Acquisition and reconstruction methods able to avoid or correct for such errors are presented. RESULTS: Tests were performed in a gel phantom during sonication, and temperature measurements were made with proper shimming as well as with intentionally introduced B0 inhomogeneities. Errors caused by B0 inhomogeneities were observed, described, and corrected by the proposed methods. No statistical difference was found between the corrected results and the reference results obtained with proper shimming, while errors by more than 10% in temperature elevation were corrected for. The approach was also applied to an abdominal in vivo dataset. CONCLUSION: Field variations induce errors in measured field values, which can be detected and corrected. The approach was validated for a PRF thermometry application.
PURPOSE: To develop and evaluate an automatic segmentation method that extracts the 3D configuration of the ablation zone, the iceball, from images acquired during the freezing phase of MRI-guided cryoablation. MATERIALS AND METHODS: Intraprocedural images at 63 timepoints from 13 kidney tumor cryoablation procedures were examined retrospectively. The images were obtained using a 3 Tesla wide-bore MRI scanner and axial HASTE sequence. Initialized with semiautomatically localized cryoprobes, the iceball was segmented automatically at each timepoint using the graph cut (GC) technique with adapted shape priors. RESULTS: The average Dice Similarity Coefficients (DSC), compared with manual segmentations, were 0.88, 0.92, 0.92, 0.93, and 0.93 at 3, 6, 9, 12, and 15 min timepoints, respectively, and the average DSC of the total 63 segmentations was 0.92 ± 0.03. The proposed method improved the accuracy significantly compared with the approach without shape prior adaptation (P = 0.026). The number of probes involved in the procedure had no apparent influence on the segmentation results using our technique. The average computation time was 20 s, which was compatible with an intraprocedural setting. CONCLUSION: Our automatic iceball segmentation method demonstrated high accuracy and robustness for practical use in monitoring the progress of MRI-guided cryoablation.
OBJECTIVE: To compare the diagnostic yield and safety profiles of intraoperative magnetic resonance imaging (MRI)-guided needle brain biopsy with 2 traditional brain biopsy methods: frame-based and frameless stereotactic brain biopsy. METHODS: A retrospective analysis was performed of 288 consecutive needle brain biopsies in 277 patients undergoing stereotactic brain biopsy with any of the 3 biopsy methods at Brigham and Women's Hospital from 2000-2008. Variables including age, sex, history of radiation and previous surgery, pathology results, complications, and postoperative length of hospital stay were analyzed. RESULTS: Over the course of 8 years, 288 brain biopsies were performed. Of these, 253 (87.8%) biopsies yielded positive diagnostic tissue. Young age (<40 years old) and history of brain radiation or surgery were significant negative predictors for a positive biopsy diagnostic yield. Excluding patients with prior radiation or surgeries, no significant difference in diagnostic yield was detected among the 3 groups, with frame-based biopsies yielding 96.9%, frameless biopsies yielding 91.8%, and intraoperative MRI-guided needle biopsies yielding 89.9% positive diagnostic yield. Serious adverse events occurred 19 biopsies (6.6%). Intraoperative MRI-guided brain biopsies were associated with less serious adverse events and the shortest postoperative hospital stay. CONCLUSIONS: Frame-based, frameless stereotactic, and intraoperative MRI-guided brain needle biopsy techniques have comparable diagnostic yield for patients with no prior treatments (either radiation or surgery). Intraoperative MRI-guided brain biopsy is associated with fewer serious adverse events and shorter hospital stay.
OBJECTIVES: To compare five different seeding methods to delineate hand, foot, and lip components of the corticospinal tract (CST) using single tensor tractography. METHODS: We studied five healthy subjects and 10 brain tumor patients. For each subject, we used five different seeding methods, from (1) cerebral peduncle (CP), (2) posterior limb of the internal capsule (PLIC), (3) white matter subjacent to functional MRI activations (fMRI), (4) whole brain and then selecting the fibers that pass through both fMRI and CP (WBF-CP), and (5) whole brain and then selecting the fibers that pass through both fMRI and PLIC (WBF-PLIC). Two blinded neuroradiologists rated delineations as anatomically successful or unsuccessful tractography. The proportions of successful trials from different methods were compared by Fisher's exact test. RESULTS: To delineate hand motor tract, seeding through fMRI activation areas was more effective than through CP (p<0.01), but not significantly different from PLIC (p>0.1). WBF-CP delineated hand motor tracts in a larger proportion of trials than CP alone (p<0.05). Similarly, WBF-PLIC depicted hand motor tracts in a larger proportion of trials than PLIC alone (p<0.01). Foot motor tracts were delineated in all trials by either PLIC or whole brain seeding (WBF-CP and WBF-PLIC). Seeding from CP or fMRI activation resulted in foot motor tract visualization in 87% of the trials (95% confidence interval: 60-98%). The lip motor tracts were delineated only by WBF-PLIC and in 36% of trials (95% confidence interval: 11-69%). CONCLUSIONS: Whole brain seeding and then selecting the tracts that pass through two anatomically relevant ROIs can delineate more plausible hand and lip motor tracts than seeding from a single ROI. Foot motor tracts can be successfully delineated regardless of the seeding method used.
The electrocardiogram (ECG) is often acquired during magnetic resonance imaging (MRI), but its analysis is restricted by the presence of a strong artefact, called magnetohydrodynamic (MHD) effect. MHD effect is induced by the flow of electrically charged particles in the blood perpendicular to the static magnetic field, which creates a potential of the order of magnitude of the ECG and temporally coincident with the repolarisation period. In this study, a new MHD model is proposed by using MRI-based 4D blood flow measurements made across the aortic arch. The model is extended to several cardiac cycles to allow the simulation of a realistic ECG acquisition during MRI examination and the quality assessment of MHD suppression techniques. A comparison of two existing models, based, respectively, on an analytical solution and on a numerical method-based solution of the fluids dynamics problem, is made with the proposed model and with an estimate of the MHD voltage observed during a real MRI scan. Results indicate a moderate agreement between the proposed model and the estimated MHD model for most leads, with an average correlation factor of 0.47. However, the results demonstrate that the proposed model provides a closer approximation to the observed MHD effects and a better depiction of the complexity of the MHD effect compared with the previously published models, with an improved correlation (+5%), coefficient of determination (+22%) and fraction of energy (+1%) compared with the best previous model. The source code will be made freely available under an open source licence to facilitate collaboration and allow more rapid development of more accurate models of the MHD effect.
One key pitfall in diffusion magnetic resonance imaging (dMRI) clinical neuroimaging research is the challenge of understanding and interpreting the results of a complex analysis pipeline. The sophisticated algorithms employed by the analysis software, combined with the relatively non-specific nature of many diffusion measurements, lead to challenges in interpretation of the results. This paper is aimed at an intended audience of clinical researchers who are learning about dMRI or trying to interpret dMRI results, and who may be wondering "Does dMRI tell us anything about the white matter?" We present a critical review of dMRI methods and measures used in clinical neuroimaging research, focusing on the most commonly used analysis methods and the most commonly reported measures. We describe important pitfalls in every section, and provide extensive references for the reader interested in more detail.
Effective drug delivery to brain tumors is often challenging because of the heterogeneous permeability of the 'blood tumor barrier' (BTB) along with other factors such as increased interstitial pressure and drug efflux pumps. Focused ultrasound (FUS) combined with microbubbles can enhance the permeability of the BTB in brain tumors, as well as the blood-brain barrier in the surrounding tissue. In this study, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was used to characterize the FUS-induced permeability changes of the BTB in a rat glioma model at different times after implantation. 9L gliosarcoma cells were implanted in both hemispheres in male rats. At day 9, 14, or 17 days after implantation, FUS-induced BTB disruption using 690 kHz ultrasound and definity microbubbles was performed in one tumor in each animal. Before FUS, liposomal doxorubicin was administered at a dose of 5.67 mg kg(-1). This chemotherapy agent was previously shown to improve survival in animal glioma models. The transfer coefficient Ktrans describing extravasation of the MRI contrast agent Gd-DTPA was measured via DCE-MRI before and after sonication. We found that tumor doxorubicin concentrations increased monotonically (823 ± 600, 1817 ± 732 and 2432 ± 448 ng g(-1)) in the control tumors at 9, 14 and 17 d. With FUS-induced BTB disruption, the doxorubicin concentrations were enhanced significantly (P < 0.05, P < 0.01, and P < 0.0001 at days 9, 14, and 17, respectively) and were greater than the control tumors by a factor of two or more (2222 ± 784, 3687 ± 796 and 5658 ± 821 ng g(-1)) regardless of the stage of tumor growth. The transfer coefficient Ktrans was significantly (P < 0.05) enhanced compared to control tumors only at day 9 but not at day 14 or 17. These results suggest that FUS-induced enhancements in tumor drug delivery are relatively consistent over time, at least in this tumor model. These results are encouraging for the use of large drug carriers, as they suggest that even large/late-stage tumors can benefit from FUS-induced drug enhancement. Corresponding enhancements in Ktrans were found to be variable in large/late-stage tumors and not significantly different than controls, perhaps reflecting the size mismatch between the liposomal drug (~100 nm) and Gd-DTPA (molecular weight: 938 Da; hydrodynamic diameter: ≃2 nm). It may be necessary to use a larger MRI contrast agent to effectively evaluate the sonication-induced enhanced permeabilization in large/late-stage tumors when a large drug carrier such as a liposome is used.
In a previous study we have demonstrated, using a novel diffusion MRI analysis called free-water imaging, that the early stages of schizophrenia are more likely associated with a neuroinflammatory response and less so with a white matter deterioration or a demyelination process. What is not known is how neuroinflammation and white matter deterioration change along the progression of the disorder. In this study we apply the free-water measures on a population of 29 chronic schizophrenia subjects and compare them with 25 matching controls. Our aim was to compare the extent of free-water imaging abnormalities in chronic subjects with the ones previously obtained for subjects at their first psychotic episode. We find that chronic subjects showed a limited extent of abnormal increase in the volume of the extracellular space, suggesting a less extensive neuroinflammatory response relative to patients at the onset of schizophrenia. At the same time, the chronic schizophrenia subjects had greater extent of reduced fractional anisotropy compared to the previous study, suggesting increased white matter deterioration along the progression of the disease. Our findings substantiate the role of neuroinflammation in the earlier stages of the disorder, and the effect of neurodegeneration that is worsening in the chronic phase.
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.