BACKGROUND: To evaluate the information gain by the application of both non-contrast and contrast enhanced computed tomography (CT) with extended mediastinal display window settings in the evaluation of pure ground glass nodules (pGGNs) and or mixed ground glass nodules (mGGNs) in the context of pre-invasive or early stage lung adenocarcinoma. METHODS: One hundred and fifty patients with ground glass nodules (GGNs) and mGGNs, with contrast enhanced CT scans within 2 weeks of thoracic surgery were included in the study. Quantitative evaluation of all nodules was performed in a conventional mediastinal window (CMW) and an extended mediastinal window (EMW) both on non-contrast images and contrast-enhanced images. RESULTS: Contrast-enhanced images with CMW demonstrated amplification of solid portion in 23 (43%), 41 (77%) with EMW out of 53 minimally invasive adenocarcinoma (MIA) nodules, and in 34 of 37 (91%) of invasive adenocarcinoma (IAC) nodules. Using the increase in size of solid portion of the nodule measured on the enhanced CT images with EMW, area under the receiver operating characteristic (ROC) curve of 0.872 and 0.899 was utilized for differentiating between the pre-invasive nodules and MIA and between MIA and IAC nodules, respectively. Statistically significant differences existed between the pre-invasive and the MIA groups, and MIA and the IAC groups in smaller nodules (P<0.01). CONCLUSIONS: Comparative quantitative analysis of the pre and post contrast images can help differentiate between atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), MIAs, and IACs. Extension of the CT mediastinal window setting improves the evaluation of small GGNs, and can augment the diagnostic accuracy when evaluating small pGGNs and mGGNs.
BACKGROUND: Skull base tumors frequently encase or invade adjacent normal neurovascular structures. For this reason, optimal tumor resection with incomplete knowledge of patient anatomy remains a challenge. METHODS: To determine the accuracy and utility of image-based preoperative segmentation in skull base tumor resections, we performed a prospective study. Ten patients with skull base tumors underwent preoperative 3T magnetic resonance imaging, which included thin section three-dimensional (3D) space T2, 3D time of flight, and magnetization-prepared rapid acquisition gradient echo sequences. Imaging sequences were loaded in the neuronavigation system for segmentation and preoperative planning. Five different neurovascular landmarks were identified in each case and measured for accuracy using the neuronavigation system. Each segmented neurovascular element was validated by manual placement of the navigation probe, and errors of localization were measured. RESULTS: Strong correspondence between image-based segmentation and microscopic view was found at the surface of the tumor and tumor-normal brain interfaces in all cases. The accuracy of the measurements was 0.45 ± 0.21 mm (mean ± standard deviation). This information reassured the surgeon and prevented vascular injury intraoperatively. Preoperative segmentation of the related cranial nerves was possible in 80% of cases and helped the surgeon localize involved cranial nerves in all cases. CONCLUSION: Image-based preoperative vascular and neural element segmentation with 3D reconstruction is highly informative preoperatively and could increase the vigilance of neurosurgeons for preventing neurovascular injury during skull base surgeries. Additionally, the accuracy found in this study is superior to previously reported measurements. This novel preliminary study is encouraging for future validation with larger numbers of patients.
BACKGROUND: To develop a technique to noninvasively estimate stroke volume in real time during magnetic resonance imaging (MRI)-guided procedures, based on induced magnetohydrodynamic voltages (VMHD) that occur in ECG recordings during MRI exams, leaving the MRI scanner free to perform other imaging tasks. Because of the relationship between blood flow (BF) and VMHD, we hypothesized that a method to obtain stroke volume could be derived from extracted VMHD vectors in the vectorcardiogram (VCG) frame of reference (VMHDVCG).
METHODS AND RESULTS: To estimate a subject-specific BF-VMHD model, VMHDVCG was acquired during a 20-s breath-hold and calibrated versus aortic BF measured using phase-contrast magnetic resonance in 10 subjects (n=10) and 1 subject diagnosed with premature ventricular contractions. Beat-to-beat validation of VMHDVCG-derived BF was performed using real-time phase-contrast imaging in 7 healthy subjects (n=7) during 15-minute cardiac exercise stress tests and 30 minutes after stress relaxation in 3T MRIs. Subject-specific equations were derived to correlate VMHDVCG with BF at rest and validated using real-time phase-contrast. An average error of 7.22% and 3.69% in stroke volume estimation, respectively, was found during peak stress and after complete relaxation. Measured beat-to-beat BF time history derived from real-time phase-contrast and VMHD was highly correlated using a Spearman rank correlation coefficient during stress tests (0.89) and after stress relaxation (0.86).
CONCLUSIONS: Accurate beat-to-beat stroke volume and BF were estimated using VMHDVCG extracted from intra-MRI 12-lead ECGs, providing a means to enhance patient monitoring during MR imaging and MR-guided interventions.
Contrast-enhanced breast MR imaging is increasingly being used to diagnose breast cancer and to perform biopsy procedures. The American Cancer Society has advised women at high risk for breast cancer to have breast MR imaging screening as an adjunct to screening mammography. This article places special emphasis on biopsy and operative planning involving MR imaging and reviews use of breast MR imaging in monitoring response to neoadjuvant chemotherapy. Described are peer-reviewed data on currently accepted MR imaging-guided procedures for addressing benign and malignant breast diseases, including intraoperative imaging.
Several advantages of MR imaging compared with other imaging modalities have provided the rationale for increased attention to MR-guided interventions, including its excellent soft tissue contrast, its capability to show both anatomic and functional information, and no use of ionizing radiation. An important aspect of MR-guided intervention is to provide visualization and navigation of interventional devices relative to the surrounding tissues. This article focuses on the methods for MR-guided active tracking in catheter-based interventions. Practical issues about implementation of active catheter tracking in a clinical setting are discussed and several current application examples are highlighted.
PURPOSE: In gynecologic cancers, magnetic resonance (MR) imaging is the modality of choice for visualizing tumors and their surroundings because of superior soft-tissue contrast. Real-time MR guidance of catheter placement in interstitial brachytherapy facilitates target coverage, and would be further improved by providing intraprocedural estimates of dosimetric coverage. A major obstacle to intraprocedural dosimetry is the time needed for catheter trajectory reconstruction. Herein the authors evaluate an active MR tracking (MRTR) system which provides rapid catheter tip localization and trajectory reconstruction. The authors assess the reliability and spatial accuracy of the MRTR system in comparison to standard catheter digitization using magnetic resonance imaging (MRI) and CT. METHODS: The MRTR system includes a stylet with microcoils mounted on its shaft, which can be inserted into brachytherapy catheters and tracked by a dedicated MRTR sequence. Catheter tip localization errors of the MRTR system and their dependence on catheter locations and orientation inside the MR scanner were quantified with a water phantom. The distances between the tracked tip positions of the MRTR stylet and the predefined ground-truth tip positions were calculated for measurements performed at seven locations and with nine orientations. To evaluate catheter trajectory reconstruction, fifteen brachytherapy catheters were placed into a gel phantom with an embedded catheter fixation framework, with parallel or crossed paths. The MRTR stylet was then inserted sequentially into each catheter. During the removal of the MRTR stylet from within each catheter, a MRTR measurement was performed at 40 Hz to acquire the instantaneous stylet tip position, resulting in a series of three-dimensional (3D) positions along the catheter's trajectory. A 3D polynomial curve was fit to the tracked positions for each catheter, and equally spaced dwell points were then generated along the curve. High-resolution 3D MRI of the phantom was performed followed by catheter digitization based on the catheter's imaging artifacts. The catheter trajectory error was characterized in terms of the mean distance between corresponding dwell points in MRTR-generated catheter trajectory and MRI-based catheter digitization. The MRTR-based catheter trajectory reconstruction process was also performed on three gynecologic cancer patients, and then compared with catheter digitization based on MRI and CT. RESULTS: The catheter tip localization error increased as the MRTR stylet moved further off-center and as the stylet's orientation deviated from the main magnetic field direction. Fifteen catheters' trajectories were reconstructed by MRTR. Compared with MRI-based digitization, the mean 3D error of MRTR-generated trajectories was 1.5 ± 0.5 mm with an in-plane error of 0.7 ± 0.2 mm and a tip error of 1.7 ± 0.5 mm. MRTR resolved ambiguity in catheter assignment due to crossed catheter paths, which is a common problem in image-based catheter digitization. In the patient studies, the MRTR-generated catheter trajectory was consistent with digitization based on both MRI and CT. CONCLUSIONS: The MRTR system provides accurate catheter tip localization and trajectory reconstruction in the MR environment. Relative to the image-based methods, it improves the speed, safety, and reliability of the catheter trajectory reconstruction in interstitial brachytherapy. MRTR may enable in-procedural dosimetric evaluation of implant target coverage.
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.
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.