PURPOSE: We report updated results of magnetic resonance imaging guided partial prostate brachytherapy and propose a definition of biochemical failure following focal therapy.
MATERIALS AND METHODS: From 1997 to 2007, 318 men with cT1c, prostate specific antigen less than 15 ng/ml, Gleason 3 + 4 or less prostate cancer received magnetic resonance imaging guided brachytherapy in which only the peripheral zone was targeted. To exclude benign prostate specific antigen increases due to prostatic hyperplasia, we investigated the usefulness of defining prostate specific antigen failure as nadir +2 with prostate specific antigen velocity greater than 0.75 ng/ml per year. Cox regression was used to determine the factors associated with prostate specific antigen failure.
RESULTS: Median followup was 5.1 years (maximum 12.1). While 36 patients met the nadir +2 criteria, 16 of 17 biopsy proven local recurrences were among the 26 men who also had a prostate specific antigen velocity greater than 0.75 ng/ml per year (16 of 26 vs 1 of 10, p = 0.008). Using the nadir +2 definition, prostate specific antigen failure-free survival for low risk cases at 5 and 8 years was 95.1% (91.0-97.3) and 80.4% (70.7-87.1), respectively. This rate improved to 95.6% (91.6-97.7) and 90.0% (82.6-94.3) using nadir +2 with prostate specific antigen velocity greater than 0.75 ng/ml per year. For intermediate risk cases survival was 73.0% (55.0-84.8) at 5 years and 66.4% (44.8-81.1) at 8 years (the same values as using nadir +2 with prostate specific antigen velocity greater than 0.75 ng/ml per year).
CONCLUSIONS: Requiring a prostate specific antigen velocity greater than 0.75 ng/ml per year in addition to nadir +2 appears to better predict clinical failure after therapies that target less than the whole gland. Further followup will determine whether magnetic resonance imaging guided brachytherapy targeting the peripheral zone produces comparable cancer control to whole gland treatment in men with low risk disease. However, at this time it does not appear adequate for men with even favorable intermediate risk disease.
In this study, we present pituitary adenoma volumetry using the free and open source medical image computing platform for biomedical research: (3D) Slicer. Volumetric changes in cerebral pathologies like pituitary adenomas are a critical factor in treatment decisions by physicians and in general the volume is acquired manually. Therefore, manual slice-by-slice segmentations in magnetic resonance imaging (MRI) data, which have been obtained at regular intervals, are performed. In contrast to this manual time consuming slice-by-slice segmentation process Slicer is an alternative which can be significantly faster and less user intensive. In this contribution, we compare pure manual segmentations of ten pituitary adenomas with semi-automatic segmentations under Slicer. Thus, physicians drew the boundaries completely manually on a slice-by-slice basis and performed a Slicer-enhanced segmentation using the competitive region-growing based module of Slicer named GrowCut. Results showed that the time and user effort required for GrowCut-based segmentations were on average about thirty percent less than the pure manual segmentations. Furthermore, we calculated the Dice Similarity Coefficient (DSC) between the manual and the Slicer-based segmentations to proof that the two are comparable yielding an average DSC of 81.97±3.39%.
The metabolism and composition of lipids is of increasing interest for understanding and detecting disease processes. Lipid signatures of tumor type and grade have been demonstrated using magnetic resonance spectroscopy. Clinical management and ultimate prognosis of brain tumors depend largely on the tumor type, subtype, and grade. Mass spectrometry, a well-known analytical technique used to identify molecules in a given sample based on their mass, can significantly improve the problem of tumor type classification. This work focuses on the problem of identifying lipid features to use as input for classification. Feature selection could result in improvements in classifier performance, discovery of biomarkers, improved data interpretation, and patient treatment.
Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open-source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future directions that can further facilitate development and validation of imaging biomarkers using 3D Slicer.
Gynecologic malignancies are a leading cause of death in women worldwide. Standard treatment for many primary and recurrent gynecologic cancer cases includes external-beam radiation followed by brachytherapy. Magnetic resonance (MR) imaging is beneficial in diagnostic evaluation, in mapping the tumor location to tailor radiation dose and in monitoring the tumor response to treatment. Initial studies of MR guidance in gynecologic brachytherapy demonstrate the ability to optimize tumor coverage and reduce radiation dose to normal tissues, resulting in improved outcomes for patients. In this article, we describe a methodology to aid applicator placement and treatment planning for 3 Tesla (3-T) MR-guided brachytherapy that was developed specifically for gynecologic cancers. This methodology has been used in 18 cases from September 2011 to May 2012 in the Advanced Multimodality Image Guided Operating (AMIGO) suite at Brigham and Women's Hospital. AMIGO comprises state-of-the-art tools for MR imaging, image analysis and treatment planning. An MR sequence using three-dimensional (3D)-balanced steady-state free precession in a 3-T MR scanner was identified as the best sequence for catheter identification with ballooning artifact at the tip. 3D treatment planning was performed using MR images. Items in development include software designed to support virtual needle trajectory planning that uses probabilistic bias correction, graph-based segmentation and image registration algorithms. The results demonstrate that 3-T MR image guidance has a role in gynecologic brachytherapy. These novel developments have the potential to improve targeted treatment to the tumor while sparing the normal tissues.
PURPOSE: This study introduces a probabilistic nonrigid registration method for use in image-guided prostate brachytherapy. Intraoperative imaging for prostate procedures, usually transrectal ultrasound (TRUS), is typically inferior to diagnostic-quality imaging of the pelvis such as endorectal magnetic resonance imaging (MRI). MR images contain superior detail of the prostate boundaries and provide substructure features not otherwise visible. Previous efforts to register diagnostic prostate images with the intraoperative coordinate system have been deterministic and did not offer a measure of the registration uncertainty. The authors developed a Bayesian registration method to estimate the posterior distribution on deformations and provide a case-specific measure of the associated registration uncertainty. METHODS: The authors adapted a biomechanical-based probabilistic nonrigid method to register diagnostic to intraoperative images by aligning a physician's segmentations of the prostate in the two images. The posterior distribution was characterized with a Markov Chain Monte Carlo method; the maximum a posteriori deformation and the associated uncertainty were estimated from the collection of deformation samples drawn from the posterior distribution. The authors validated the registration method using a dataset created from ten patients with MRI-guided prostate biopsies who had both diagnostic and intraprocedural 3 Tesla MRI scans. The accuracy and precision of the estimated posterior distribution on deformations were evaluated from two predictive distance distributions: between the deformed central zone-peripheral zone (CZ-PZ) interface and the physician-labeled interface, and based on physician-defined landmarks. Geometric margins on the registration of the prostate's peripheral zone were determined from the posterior predictive distance to the CZ-PZ interface separately for the base, mid-gland, and apical regions of the prostate. RESULTS: The authors observed variation in the shape and volume of the segmented prostate in diagnostic and intraprocedural images. The probabilistic method allowed us to convey registration results in terms of posterior distributions, with the dispersion providing a patient-specific estimate of the registration uncertainty. The median of the predictive distance distribution between the deformed prostate boundary and the segmented boundary was ≤3 mm (95th percentiles within ±4 mm) for all ten patients. The accuracy and precision of the internal deformation was evaluated by comparing the posterior predictive distance distribution for the CZ-PZ interface for each patient, with the median distance ranging from -0.6 to 2.4 mm. Posterior predictive distances between naturally occurring landmarks showed registration errors of ≤5 mm in any direction. The uncertainty was not a global measure, but instead was local and varied throughout the registration region. Registration uncertainties were largest in the apical region of the prostate. CONCLUSIONS: Using a Bayesian nonrigid registration method, the authors determined the posterior distribution on deformations between diagnostic and intraprocedural MR images and quantified the uncertainty in the registration results. The feasibility of this approach was tested and results were positive. The probabilistic framework allows us to evaluate both patient-specific and location-specific estimates of the uncertainty in the registration result. Although the framework was tested on MR-guided procedures, the preliminary results suggest that it may be applied to TRUS-guided procedures as well, where the addition of diagnostic MR information may have a larger impact on target definition and clinical guidance.
First described for use in mapping the human visual cortex in 1991, functional magnetic resonance imaging (fMRI) is based on blood-oxygen level dependent (BOLD) changes in cortical regions that occur during specific tasks. Typically, an overabundance of oxygenated (arterial) blood is supplied during activation of brain areas. Consequently, the venous outflow from the activated areas contains a higher concentration of oxyhemoglobin, which changes the paramagnetic properties of the tissue that can be detected during a T2-star acquisition. fMRI data can be acquired in response to specific tasks or in the resting state. fMRI has been widely applied to studying physiologic and pathophysiologic diseases of the brain. This review will discuss the most common current clinical applications of fMRI as well as emerging directions.
The overall goal of this research is the design of statistical atlas models that can be created from normal subjects, but may generalize to be applicable to abnormal brains. We present a new style of joint modeling of fMRI, DTI, and structural MRI. Motivated by the fact that a white matter tract and related cortical areas are likely to displace together in the presence of a mass lesion (brain tumor), in this work we propose a rotation and translation invariant model that represents the spatial relationship between fiber tracts and anatomic and functional landmarks. This landmark distance model provides a new basis for representation of fiber tracts and can be used for detection and prediction of fiber tracts based on landmarks. Our results indicate that the measured model is consistent across normal subjects, and thus suitable for atlas building. Our experiments demonstrate that the model is robust to displacement and missing data, and can be successfully applied to a small group of patients with mass lesions.
The efficient extraction of the cryoablation iceball from a time series of 3D images is crucial during cryoablation to assist the interventionalist in determining the coverage of the tumor by the ablated volume. Conventional semi-automatic segmentation tools such as ITK-SNAP and 3D Slicer's Fast Marching Segmentation can attain accurate iceball segmentation in retrospective studies, however, they are not ideal for intraprocedure real time segmentation, as they require time-consuming manual operations, such as the input of fiducials and the extent of the segmented region growth. In this paper, we present an innovative approach for the segmentation of the iceball during cryoablation, that executes a fully automatic computation. Our approach is based on the graph cuts segmentation framework, and incorporates prior information of iceball shape evolving in time, modeled using experimentally-derived iceball growth parameters. Modeling yields a shape prior mask image at each timepoint of the imaging time series for use in the segmentation. Segmentation results of our method and the ITK-SNAP method are compared for 8 timepoints in 2 cases. The results indicate that our fully automatic approach is accurate, robust and highly efficient compared to manual and semi-automatic approaches.
PURPOSE: To develop and evaluate image registration methodology for automated re-identification of tumor-suspicious foci from preprocedural MR exams during MR-guided transperineal prostate core biopsy. MATERIALS AND METHODS: A hierarchical approach for automated registration between planning and intra-procedural T2-weighted prostate MRI was developed and evaluated on the images acquired during 10 consecutive MR-guided biopsies. Registration accuracy was quantified at image-based landmarks and by evaluating spatial overlap for the manually segmented prostate and sub-structures. Registration reliability was evaluated by simulating initial mis-registration and analyzing the convergence behavior. Registration precision was characterized at the planned biopsy targets. RESULTS: The total computation time was compatible with a clinical setting, being at most 2 min. Deformable registration led to a significant improvement in spatial overlap of the prostate and peripheral zone contours compared with both rigid and affine registration. Average in-slice landmark registration error was 1.3 ± 0.5 mm. Experiments simulating initial mis-registration resulted in an estimated average capture range of 6 mm and an average in-slice registration precision of ±0.3 mm. CONCLUSION: Our registration approach requires minimum user interaction and is compatible with the time constraints of our interventional clinical workflow. The initial evaluation shows acceptable accuracy, reliability and consistency of the method.
MRI-guided prostate biopsy in conventional closed-bore scanners requires transferring the patient outside the bore during needle insertion due to the constrained in-bore space, causing a safety hazard and limiting image feedback. To address this issue, we present our custom-made in-bore setup and software to support MRI-guided transperineal prostate biopsy in a wide-bore 3 T MRI scanner. The setup consists of a specially designed tabletop and a needle-guiding template with a Z-frame that gives a physician access to the perineum of the patient at the imaging position and allows the physician to perform MRI-guided transperineal biopsy without moving the patient out of the scanner. The software and Z-frame allow registration of the template, target planning and biopsy guidance. Initially, we performed phantom experiments to assess the accuracy of template registration and needle placement in a controlled environment. Subsequently, we embarked on our clinical trial (N = 10). The phantom experiments showed that the translational errors of the template registration along the right-left (RP) and anterior-posterior (AP) axes were 1.1 ± 0.8 and 1.4 ± 1.1 mm, respectively, while the rotational errors around the RL, AP and superior-inferior axes were (0.8 ± 1.0)°, (1.7 ± 1.6)° and (0.0 ± 0.0)°, respectively. The 2D root-mean-square (RMS) needle-placement error was 3 mm. The clinical biopsy procedures were safely carried out in all ten clinical cases with a needle-placement error of 5.4 mm (2D RMS). In conclusion, transperineal prostate biopsy in a wide-bore 3T scanner is feasible using our custom-made tabletop setup and software, which supports manual needle placement without moving the patient out of the magnet.
BACKGROUND: OpenIGTLink is a new, open, simple and extensible network communication protocol for image-guided therapy (IGT). The protocol provides a standardized mechanism to connect hardware and software by the transfer of coordinate transforms, images, and status messages. MeVisLab is a framework for the development of image processing algorithms and visualization and interaction methods, with a focus on medical imaging. METHODS: The paper describes the integration of the OpenIGTLink network protocol for IGT with the medical prototyping platform MeVisLab. The integration of OpenIGTLink into MeVisLab has been realized by developing a software module using the C++ programming language. RESULTS: The integration was evaluated with tracker clients that are available online. Furthermore, the integration was used to connect MeVisLab to Slicer and a NDI tracking system over the network. The latency time during navigation with a real instrument was measured to show that the integration can be used clinically. CONCLUSIONS: Researchers using MeVisLab can interface their software to hardware devices that already support the OpenIGTLink protocol, such as the NDI Aurora magnetic tracking system. In addition, the OpenIGTLink module can also be used to communicate directly with Slicer, a free, open source software package for visualization and image analysis.
Capsule endoscopy is a promising technique for diagnosing diseases in the digestive system. Here we design and characterize a miniature swimming mechanism that uses the magnetic fields of the MRI for both propulsion and wireless powering of the capsule. Our method uses both the static and the radio frequency (RF) magnetic fields inherently available in MRI to generate a propulsive force. Our study focuses on the evaluation of the propulsive force for different swimming tails and experimental estimation of the parameters that influence its magnitude. We have found that an approximately 20 mm long, 5 mm wide swimming tail is capable of producing 0.21 mN propulsive force in water when driven by a 20 Hz signal providing 0.85 mW power and the tail located within the homogeneous field of a 3 T MRI scanner. We also analyze the parallel operation of the swimming mechanism and the scanner imaging. We characterize the size of artifacts caused by the propulsion system. We show that while the magnetic micro swimmer is propelling the capsule endoscope, the operator can locate the capsule on the image of an interventional scene without being obscured by significant artifacts. Although this swimming method does not scale down favorably, the high magnetic field of the MRI allows self propulsion speed on the order of several millimeter per second and can propel an endoscopic capsule in the stomach.
Neuronavigation has become an ubiquitous tool in the surgical management of brain tumors. This review describes the use and limitations of current neuronavigational systems for brain tumor biopsy and resection. Methods for integrating intraoperative imaging into neuronavigational datasets developed to address the diminishing accuracy of positional information that occurs over the course of brain tumor resection are discussed. In addition, the process of integration of functional MRI and tractography into navigational models is reviewed. Finally, emerging concepts and future challenges relating to the development and implementation of experimental imaging technologies in the navigational environment are explored.
BACKGROUND: Treatment of high-risk localized prostate cancer remains inadequate. The authors performed a phase 2 multicenter trial of neoadjuvant docetaxel plus bevacizumab before radical prostatectomy. METHODS: Eligibility included any of the following: prostate-specific antigen (PSA) >20 ng/mL or PSA velocity >2 ng/mL/y, cT3 disease, any biopsy Gleason score 8 to 10, and Gleason score 7 with T3 disease by endorectal magnetic resonance imaging (MRI) at 1.5 T. Also, those with ≥50% biopsy cores involved and either Gleason score 7, PSA >10, or cT2 disease were eligible. Patients were treated with docetaxel 70 mg/m(2) every 3 weeks for 6 cycles and bevacizumab 15 mg/m(2) every 3 weeks for 5 cycles. The primary endpoint was partial response by endorectal MRI. RESULTS: Forty-one patients were treated. Median age was 55 years (range, 40-66 years). Baseline characteristics included: median PSA, 10.1 ng/mL; cT2, 49%, cT3, 32%; and Gleason score 8 to 10, 73%. Thirty-eight of 41 (93%) patients completed all 6 cycles. Grade ≥3 adverse events were rare, although 3 of 41 (7%) experienced febrile neutropenia. Twelve patients (29%; 95% confidence interval [CI], 16%-45%) achieved a >50% reduction in tumor volume, and 9 patients (22%; 95% CI, 11%-38%) achieved a >50% post-treatment decline in PSA. Thirty-seven of the 41 patients underwent radical prostatectomy; there were no complete pathologic responses. CONCLUSIONS: Neoadjuvant docetaxel and bevacizumab is safe, and results in reductions in both tumor volume and serum PSA, in men with high-risk localized prostate cancer. The role of neoadjuvant chemotherapy in prostate cancer, and perioperative antiangiogenic therapy in general, requires further elucidation through ongoing and planned trials.
BACKGROUND: Natural orifice transluminal endoscopic surgery (NOTES) is technically challenging owing to endoscopic short-sighted visualization, excessive scope flexibility and lack of adequate instrumentation. Augmented reality may overcome these difficulties. This study tested whether an image registration system for NOTES procedures (IR-NOTES) can facilitate navigation. METHODS: In three human cadavers 15 intra-abdominal organs were targeted endoscopically with and without IR-NOTES via both transgastric and transcolonic routes, by three endoscopists with different levels of expertise. Ease of navigation was evaluated objectively by kinematic analysis, and navigation complexity was determined by creating an organ access complexity score based on the same data. RESULTS: Without IR-NOTES, 21 (11·7 per cent) of 180 targets were not reached (expert endoscopist 3, advanced 7, intermediate 11), compared with one (1 per cent) of 90 with IR-NOTES (intermediate endoscopist) (P = 0·002). Endoscope movements were significantly less complex in eight of the 15 listed organs when using IR-NOTES. The most complex areas to access were the pelvis and left upper quadrant, independently of the access route. The most difficult organs to access were the spleen (5 failed attempts; 3 of 7 kinematic variables significantly improved) and rectum (4 failed attempts; 5 of 7 kinematic variables significantly improved). The time needed to access the rectum through a transgastric approach was 206·3 s without and 54·9 s with IR-NOTES (P = 0·027). CONCLUSION: The IR-NOTES system enhanced both navigation efficacy and ease of intra-abdominal NOTES exploration for operators of all levels. The system rendered some organs accessible to non-expert operators, thereby reducing one impediment to NOTES procedures.
Transrectal ultrasound (TRUS) facilitates intra-treatment delineation of the prostate gland (PG) to guide insertion of brachytherapy seeds, but the prostate substructure and apex are not always visible which may make the seed placement sub-optimal. Based on an elastic model of the prostate created from MRI, where the prostate substructure and apex are clearly visible, we use a Bayesian approach to estimate the posterior distribution on deformations that aligns the pre-treatment MRI with intra-treatment TRUS. Without apex information in TRUS, the posterior prediction of the location of the prostate boundary, and the prostate apex boundary in particular, is mainly determined by the pseudo stiffness hyper-parameter of the prior distribution. We estimate the optimal value of the stiffness through likelihood maximization that is sensitive to the accuracy as well as the precision of the posterior prediction at the apex boundary. From a data-set of 10 pre- and intra-treatment prostate images with ground truth delineation of the total PG, 4 cases were used to establish an optimal stiffness hyper-parameter when 15% of the prostate delineation was removed to simulate lack of apex information in TRUS, while the remaining 6 cases were used to cross-validate the registration accuracy and uncertainty over the PG and in the apex.
Ultrasound-guided prostate interventions could benefit from incorporating the radiologic localization of the tumor which can be acquired from multiparametric MRI. To enable this integration, we propose and compare two solutions for registration of T2 weighted MR images with transrectal ultrasound. Firstly, we propose an innovative and practical approach based on deformable registration of binary label maps obtained from manual segmentation of the gland in the two modalities. This resulted in a target registration error of 3.6±1.7 mm. Secondly, we report a novel surface-based registration method that uses a biomechanical model of the tissue and results in registration error of 3.2±1.3 mm. We compare the two methods in terms of accuracy, clinical use and technical limitations.
We present what we believe to be the first investigation into unbiased multi-subject registration of whole brain diffusion tractography of the white matter. To our knowledge, this is also the first entropy-based objective function applied to fiber tract registration. To define the probability of fiber trajectories for the computation of entropy, we take advantage of a pairwise fiber distance used as the basis for a Gaussian-like kernel. By employing several values of the kernel's scale parameter, the method is inherently multi-scale. Results of experiments using synthetic and real datasets demonstrate the potential of the method for simultaneous joint registration of tractography.
OBJECTIVE: Accurate biopsy sampling of the suspected lesions is critical for the diagnosis and clinical management of prostate cancer (PCa). Transperineal in-bore MRI-guided prostate biopsy (tpMRgBx) is a targeted biopsy technique that was shown to be safe, efficient and accurate. Our goal was to develop an open source software platform to support evaluation, refinement and translation of this biopsy approach. METHODS: We developed SliceTracker, a 3D Slicer extension to support tpMRgBx. We followed modular design of the implementation to enable customization of the interface, and interchange of image segmentation and registration components to assess their effect on the processing time, precision and accuracy of the biopsy needle placement. The platform and supporting documentation were developed to enable the use of software by an operator with minimal technical training to facilitate translation. Retrospective evaluation studied registration accuracy, effect of the prostate segmentation approach, and re-identification time of biopsy targets. Prospective evaluation focused on the total procedure time and biopsy targeting error (BTE). RESULTS: Evaluation utilized data from 73 retrospective and 10 prospective tpMRgBx cases. Mean Landmark Registration Error (LRE) for retrospective evaluation was 1.88 ±2.63 mm and was not sensitive to the approach used for prostate gland segmentation. Prospectively, we observed target re-identification time of 4.60 ±2.40 min, and BTE of 2.40 ±0.98 mm. CONCLUSION: SliceTracker is modular and extensible open source platform for supporting image processing aspects of the tpMRgBx procedure. It has been successfully utilized to support clinical research procedures at our site.
Patient-mounted needle guide devices for percutaneous ablation are vulnerable to patient motion. The objective of this study is to develop and evaluate a software system for an MRI-compatible patient-mounted needle guide device that can adaptively compensate for displacement of the device due to patient motion using a novel image-based automatic device-to-image registration technique. We have developed a software system for an MRI-compatible patient-mounted needle guide device for percutaneous ablation. It features fully-automated image-based device-to-image registration to track the device position, and a device controller to adjust the needle trajectory to compensate for the displacement of the device. We performed: (a) a phantom study using a clinical MR scanner to evaluate registration performance; (b) simulations using intraoperative time-series MR data acquired in 20 clinical cases of MRI-guided renal cryoablations to assess its impact on motion compensation; and (c) a pilot clinical study in three patients to test its feasibility during the clinical procedure. FRE, TRE, and success rate of device-to-image registration were [Formula: see text] mm, [Formula: see text] mm, and 98.3% for the phantom images. The simulation study showed that the motion compensation reduced the targeting error for needle placement from 8.2 mm to 5.4 mm (p < 0.0005) in patients under general anesthesia (GA), and from 14.4 mm to 10.0 mm ([Formula: see text]) in patients under monitored anesthesia care (MAC). The pilot study showed that the software registered the device successfully in a clinical setting. Our simulation study demonstrated that the software system could significantly improve targeting accuracy in patients treated under both MAC and GA. Intraprocedural image-based device-to-image registration was feasible.
PURPOSE: To develop and evaluate an approach to estimate the respiratory-induced motion of lesions in the chest and abdomen. MATERIALS AND METHODS: The proposed approach uses the motion of an initial reference needle inserted into a moving organ to estimate the lesion (target) displacement that is caused by respiration. The needles position is measured using an inertial measurement unit (IMU) sensor externally attached to the hub of an initially placed reference needle. Data obtained from the IMU sensor and the target motion are used to train a learning-based approach to estimate the position of the moving target. An experimental platform was designed to mimic respiratory motion of the liver. Liver motion profiles of human subjects provided inputs to the experimental platform. Variables including the insertion angle, target depth, target motion velocity and target proximity to the reference needle were evaluated by measuring the error of the estimated target position and processing time. RESULTS: The mean error of estimation of the target position ranged between 0.86 and 1.29 mm. The processing maximum training and testing time was 5 ms which is suitable for real-time target motion estimation using the needle position sensor. CONCLUSION: The external motion of an initially placed reference needle inserted into a moving organ can be used as a surrogate, measurable and accessible signal to estimate in real-time the position of a moving target caused by respiration; this technique could then be used to guide the placement of subsequently inserted needles directly into the target.
Brain shift during tumor resection compromises the spatial validity of registered preoperative imaging data that is critical to image-guided procedures. One current clinical solution to mitigate the effects is to reimage using intraoperative magnetic resonance (iMR) imaging. Although iMR has demonstrated benefits in accounting for preoperative-to-intraoperative tissue changes, its cost and encumbrance have limited its widespread adoption. While iMR will likely continue to be employed for challenging cases, a cost-effective model-based brain shift compensation strategy is desirable as a complementary technology for standard resections. We performed a retrospective study of [Formula: see text] tumor resection cases, comparing iMR measurements with intraoperative brain shift compensation predicted by our model-based strategy, driven by sparse intraoperative cortical surface data. For quantitative assessment, homologous subsurface targets near the tumors were selected on preoperative MR and iMR images. Once rigidly registered, intraoperative shift measurements were determined and subsequently compared to model-predicted counterparts as estimated by the brain shift correction framework. When considering moderate and high shift ([Formula: see text], [Formula: see text] measurements per case), the alignment error due to brain shift reduced from [Formula: see text] to [Formula: see text], representing [Formula: see text] correction. These first steps toward validation are promising for model-based strategies.
OBJECTIVE: The purpose of this article is to report our intermediate to long-term outcomes with image-guided percutaneous hepatic tumor cryoablation and to evaluate its technical success, technique efficacy, local tumor progression, and adverse event rate. MATERIALS AND METHODS: Between 1998 and 2014, 299 hepatic tumors (243 metastases and 56 primary tumors; mean diameter, 2.5 cm; median diameter, 2.2 cm; range, 0.3-7.8 cm) in 186 patients (95 women; mean age, 60.9 years; range, 29-88 years) underwent cryoablation during 236 procedures using CT (n = 126), MRI (n = 100), or PET/CT (n = 10) guidance. Technical success, technique efficacy at 3 months, local tumor progression (mean follow-up, 2.5 years; range, 2 months to 14.6 years), and adverse event rates were calculated. RESULTS: The technical success rate was 94.6% (279/295). The technique efficacy rate was 89.5% (231/258) and was greater for tumors smaller than 4 cm (93.4%; 213/228) than for larger tumors (60.0%; 18/30) (p < 0.0001). Local tumor progression occurred in 23.3% (60/258) of tumors and was significantly more common after the treatment of tumors 4 cm or larger (63.3%; 19/30) compared with smaller tumors (18.0%; 41/228) (p < 0.0001). Adverse events followed 33.8% (80/236) of procedures and were grade 3-5 in 10.6% (25/236) of cases. Grade 3 or greater adverse events more commonly followed the treatment of larger tumors (19.5%; 8/41) compared with smaller tumors (8.7%; 17/195) (p = 0.04). CONCLUSION: Image-guided percutaneous cryoablation of hepatic tumors is efficacious; however, tumors smaller than 4 cm are more likely to be treated successfully and without an adverse event.