The safety and effectiveness of percutaneous image‐guided ablations can be improved if the procedure could be assessed quantitatively and in real time. Using MRI’s ability to depict both the tumor and the iceball during cryoablations, we developed a novel computerized tool that utilizes fast automatic segmentation methods to compute ablation metrics and tested its accuracy in MRI guided cryoablations of renal cancer.
PURPOSE: To assess safety and effectiveness of percutaneous image-guided cryoablation of hepatic tumors adjacent to the gallbladder. MATERIALS AND METHODS: Twenty-one cryoablation procedures were performed to treat 19 hepatic tumors (mean size, 2.7 cm; range, 1.0-5.0 cm) adjacent to the gallbladder in 17 patients (11 male; mean age, 59.2 y; range, 40-82 y) under computed tomography (n = 15) or magnetic resonance imaging (n = 6) guidance in a retrospective study. All tumors (mean size, 2.67 cm; range, 1.0-5.0 cm) were within 1 cm (mean, 0.4 cm) of the gallbladder; seven (33%) were contiguous with the gallbladder. Primary outcomes included complication rate and severity and postprocedure gallbladder imaging findings. Secondary outcomes included technical success and technique effectiveness at 6 months. RESULTS: Complications occurred in six of 21 procedures (29%); one (5%) was severe. Ice balls extended into the gallbladder lumen in 20 of 21 procedures (95%); no gallbladder-related complications occurred. The most common gallbladder imaging finding was mild, asymptomatic focal wall thickening after nine of 21 procedures (42%), which resolved on follow-up. Technical success was achieved in 19 of 21 sessions (90%). Six-month follow-up was available for 16 tumors; of these, all but two (87%) had no imaging evidence of local tumor progression. CONCLUSIONS: Percutaneous cryoablation of hepatic tumors adjacent to the gallbladder can be performed safely and successfully. Although postprocedural gallbladder changes are common, they are self-limited and clinically inconsequential, even when the ice ball extends into the gallbladder lumen.
PURPOSE: To compare the safety of image-guided percutaneous cryoablation and radiofrequency ablation in the treatment of hepatocellular carcinoma in patients with cirrhosis. MATERIALS AND METHODS: This retrospective HIPAA-compliant study received institutional review board approval. Forty-two adult patients with cirrhosis underwent image-guided percutaneous ablation of hepatocellular carcinoma from 2003 to 2011. Twenty-five patients underwent 33 cryoablation procedures to treat 39 tumors, and 22 underwent 30 radiofrequency ablation procedures to treat 39 tumors. Five patients underwent both cryoablation and radiofrequency ablation procedures. Complication rates and severity per procedure were compared between the ablation groups. Potential confounding patient, procedure, and tumor-related variables were also compared. Statistical analyses included Kruskal-Wallis, Wilcoxon rank sum, and Fisher's exact tests. Two-sided P-values <0.05 were considered significant. RESULTS: The overall complication rates, 13 (39.4%) of 33 cryoablation procedures versus eight (26.7%) of 30 radiofrequency ablation procedures and severe/fatal complication rates, two (6.1%) of 33 cryoablation procedures versus one (3.3%) of 30 radiofrequency ablation procedures, were not significantly different between the ablation groups (both P=0.26). Severe complications included pneumothoraces requiring chest tube insertion during two cryoablation procedures. One death occurred within 90 days of a radiofrequency ablation procedure; all other complications were managed successfully. CONCLUSION: No significant difference was seen in the overall safety of image-guided percutaneous cryoablation and radiofrequency ablation in the treatment of hepatocellular carcinoma in patients with cirrhosis.
Percutaneous image-guided tumor ablation techniques have been used as an alternative method for patients with unresectable liver tumors. Although all techniques avoid morbidity and mortality of major surgery and have advantage of preserving non-tumoral liver parenchyma, cryoablation currently is the only percutaneous ablation technique allowing intraprocedural monitoring because of visibility of its ablation effect with computed tomography and MRI. Cryoablation uses extremely low temperatures to induce local tissue necrosis to treat both primary and metastatic liver tumors. This article discusses the principles of liver tumor percutaneous cryoablation, including mechanisms of tissue injury, technique, equipment, image-guidance used, patient selection criteria, clinical outcome and complications as well as current trends and future goals.
The application of magnetic resonance image (MRI)-guided brachytherapy has demonstrated significant growth during the past 2 decades. Clinical improvements in cervix cancer outcomes have been linked to the application of repeated MRI for identification of residual tumor volumes during radiotherapy. This has changed clinical practice in the direction of individualized dose administration, and resulted in mounting evidence of improved clinical outcome regarding local control, overall survival as well as morbidity. MRI-guided prostate high-dose-rate and low-dose-rate brachytherapies have improved the accuracy of target and organs-at-risk delineation, and the potential exists for improved dose prescription and reporting for the prostate gland and organs at risk. Furthermore, MRI-guided prostate brachytherapy has significant potential to identify prostate subvolumes and dominant lesions to allow for dose administration reflecting the differential risk of recurrence. MRI-guided brachytherapy involves advanced imaging, target concepts, and dose planning. The key issue for safe dissemination and implementation of high-quality MRI-guided brachytherapy is establishment of qualified multidisciplinary teams and strategies for training and education.
INTRODUCTION/BACKGROUND: The GS is an established prostate cancer prognostic factor. Whether the presence of differing GSs at biopsy (eg, 4+3 and 3+3), which we term ComboGS, improves the prognosis that would be predicted based on the highest GS (eg, 4+3) because of decreased upgrading is unknown. Therefore, we evaluated the odds of upgrading at time of radical prostatectomy (RP) and the risk of PCSM when ComboGS was present versus absent. PATIENTS AND METHODS: Logistic and competing risks regression were performed to assess the effect that ComboGS had on the odds of upgrading at time of RP in the index (n = 134) and validation cohorts (n = 356) and the risk of PCSM after definitive therapy in a long-term cohort (n = 666), adjusting for known predictors of these end points. We calculated and compared the area under the curve using a receiver operating characteristic analysis when ComboGS was included versus excluded from the upgrading models. RESULTS: ComboGS was associated with decreased odds of upgrading (index: adjusted odds ratio [AOR], 0.14; 95% confidence interval [CI], 0.04-0.50; P = .003; validation: AOR, 0.24; 95% CI, 0.11-0.51; P < .001) and added significantly to the predictive value of upgrading for the in-sample index (P = .02), validation (P = .003), and out-of-sample prediction models (P = .002). ComboGS was also associated with a decreased risk of PCSM (adjusted hazard ratio, 0.40; 95% CI, 0.19-0.85; P = .02). CONCLUSION: Differing biopsy GSs are associated with a lower odds of upgrading and risk of PCSM. If validated, future randomized noninferiority studies evaluating deescalated treatment approaches in men with ComboGS could be considered.
Gynecologic malignancies, including cervical, endometrial, ovarian, vaginal and vulvar cancers, cause significant mortality in women worldwide. The standard care for many primary and recurrent gynecologic cancers consists of chemoradiation followed by brachytherapy. In high dose rate (HDR) brachytherapy, intracavitary applicators and/or interstitial needles are placed directly inside the cancerous tissue so as to provide catheters to deliver high doses of radiation. Although technology for the navigation of catheters and needles is well developed for procedures such as prostate biopsy, brain biopsy, and cardiac ablation, it is notably lacking for gynecologic HDR brachytherapy. Using a benchtop study that closely mimics the clinical interstitial gynecologic brachytherapy procedure, we developed a method for evaluating the accuracy of image-guided catheter placement. Future bedside translation of this technology offers the potential benefit of maximizing tumor coverage during catheter placement while avoiding damage to the adjacent organs, for example bladder, rectum and bowel. In the study, two independent experiments were performed on a phantom model to evaluate the targeting accuracy of an electromagnetic (EM) tracking system. The procedure was carried out using a laptop computer (2.1GHz Intel Core i7 computer, 8GB RAM, Windows 7 64-bit), an EM Aurora tracking system with a 1.3mm diameter 6 DOF sensor, and 6F (2 mm) brachytherapy catheters inserted through a Syed-Neblett applicator. The 3D Slicer and PLUS open source software were used to develop the system. The mean of the targeting error was less than 2.9mm, which is comparable to the targeting errors in commercial clinical navigation systems.
PURPOSE: High-fidelity 12-lead electrocardiogram (ECG) is important for physiological monitoring of patients during MR-guided intervention and cardiac MRI. Issues in obtaining noncorrupted ECGs inside MRI include a superimposed magneto-hydro-dynamic voltage, gradient switching-induced voltages, and radiofrequency heating. These problems increase with magnetic field. The aim of this study is to develop and clinically validate a 1.5T MRI-conditional 12-lead ECG system. METHODS: The system was constructed with transmission lines to reduce radiofrequency induction and switching circuits to remove induced voltages. Adaptive filters, trained by 12-lead measurements outside MRI and in two orientations inside MRI, were used to remove the magneto-hydro-dynamic voltage. The system was tested on 10 (one exercising) volunteers and four arrhythmia patients. RESULTS: Switching circuits removed most imaging-induced voltages (residual noise <3% of the R-wave). Magneto-hydro-dynamic voltage removal provided intra-MRI ECGs that varied by <3.8% from those outside the MRI, preserving the true S-wave to T-wave segment. In premature ventricular contraction (PVC) patients, clean ECGs separated premature ventricular contraction and sinus rhythm beats. Measured heating was <1.5°C. The system reliably acquired multiphase (steady-state free precession) wall-motion-cine and phase-contrast-cine scans, including subjects in whom 4-lead gating failed. The system required a minimum repetition time of 4 ms to allow robust ECG processing. CONCLUSION: High-fidelity intra-MRI 12-lead ECG is possible.
PURPOSE: To develop a technique that accurately detects the QRS complex in 1.5 Tesla (T), 3T, and 7T MRI scanners. METHODS: During early systole, blood is rapidly ejected into the aortic arch, traveling perpendicular to the MRI's main field, which produces a strong voltage (V(MHD)) that eclipses the QRS complex. Greater complexity arises in arrhythmia patients, since V(MHD) varies between sinus-rhythm and arrhythmic beats. The 3DQRS method uses a kernel consisting of 6 electrocardiogram (ECG) precordial leads (V1-V6), compiled from a 12-lead ECG performed outside the magnet. The kernel is cross-correlated with signals acquired inside the MRI to identify the QRS complex in real time. The 3DQRS method was evaluated against a vectorcardiogram (VCG)-based approach in two premature ventricular contraction (PVC) and two atrial fibrillation (AF) patients, a healthy exercising athlete, and eight healthy volunteers, within 1.5T and 3T MRIs, using a prototype MRI-conditional 12-lead ECG system. Two volunteers were recorded at 7T using a Holter recorder. RESULTS: For QRS complex detection, 3DQRS subject-averaged sensitivity levels, relative to VCG were: 1.5T (100% versus 96.7%), 3T (98.9% versus 92.2%), and 7T (96.2% versus 77.7%). CONCLUSION: The 3DQRS method was shown to be more effective in cardiac gating than a conventional VCG-based method.
PURPOSE: To reduce image distortion in MR diffusion imaging using an accelerated multi-shot method. METHODS: The proposed method exploits the fact that diffusion-encoded data tend to be sparse when represented in the kb-kd space, where kb and kd are the Fourier transform duals of b and d, the b-factor and the diffusion direction, respectively. Aliasing artifacts are displaced toward under-used regions of the kb-kd plane, allowing nonaliased signals to be recovered. A main characteristic of the proposed approach is how thoroughly the navigator information gets used during reconstruction: The phase of navigator images is used for motion correction, while the magnitude of the navigator signal in kb-kd space is used for regularization purposes. As opposed to most acceleration methods based on compressed sensing, the proposed method reduces the number of ky lines needed for each diffusion-encoded image, but not the total number of images required. Consequently, it tends to be most effective at reducing image distortion rather than reducing total scan time. RESULTS: Results are presented for three volunteers with acceleration factors ranging from 4 to 8, with and without the inclusion of parallel imaging. CONCLUSION: An accelerated motion-corrected diffusion imaging method was introduced that achieves good image quality at relatively high acceleration factors.
Distinguishing tumor from normal glandular breast tissue is an important step in breast-conserving surgery. Because this distinction can be challenging in the operative setting, up to 40% of patients require an additional operation when traditional approaches are used. Here, we present a proof-of-concept study to determine the feasibility of using desorption electrospray ionization mass spectrometry imaging (DESI-MSI) for identifying and differentiating tumor from normal breast tissue. We show that tumor margins can be identified using the spatial distributions and varying intensities of different lipids. Several fatty acids, including oleic acid, were more abundant in the cancerous tissue than in normal tissues. The cancer margins delineated by the molecular images from DESI-MSI were consistent with those margins obtained from histological staining. Our findings prove the feasibility of classifying cancerous and normal breast tissues using ambient ionization MSI. The results suggest that an MS-based method could be developed for the rapid intraoperative detection of residual cancer tissue during breast-conserving surgery.
Deformable image registration is used increasingly in image-guided interventions and other applications. However, validation and characterization of registration performance remain areas that require further study. We propose an analysis methodology for deriving tolerance limits on the initial conditions for deformable registration that reliably lead to a successful registration. This approach results in a concise summary of the probability of registration failure, while accounting for the variability in the test data. The (β, γ) tolerance limit can be interpreted as a value of the input parameter that leads to successful registration outcome in at least 100β% of cases with the 100γ% confidence. The utility of the methodology is illustrated by summarizing the performance of a deformable registration algorithm evaluated in three different experimental setups of increasing complexity. Our examples are based on clinical data collected during MRI-guided prostate biopsy registered using publicly available deformable registration tool. The results indicate that the proposed methodology can be used to generate concise graphical summaries of the experiments, as well as a probabilistic estimate of the registration outcome for a future sample. Its use may facilitate improved objective assessment, comparison and retrospective stress-testing of deformable.
PURPOSE: To accurately segment invasive ductal carcinomas (IDCs) from dynamic contrast-enhanced MRI (DCE-MRI) using time series analysis based on linear dynamic system (LDS) modeling. MATERIALS AND METHODS: Quantitative segmentation methods based on black-box modeling and pharmacokinetic modeling are highly dependent on imaging pulse sequence, timing of bolus injection, arterial input function, imaging noise, and fitting algorithms. We modeled the underlying dynamics of the tumor by an LDS and used the system parameters to segment the carcinoma on the DCE-MRI. Twenty-four patients with biopsy-proven IDCs were analyzed. The lesions segmented by the algorithm were compared with an expert radiologist's segmentation and the output of a commercial software, CADstream. The results are quantified in terms of the accuracy and sensitivity of detecting the lesion and the amount of overlap, measured in terms of the Dice similarity coefficient (DSC). RESULTS: The segmentation algorithm detected the tumor with 90% accuracy and 100% sensitivity when compared with the radiologist's segmentation and 82.1% accuracy and 100% sensitivity when compared with the CADstream output. The overlap of the algorithm output with the radiologist's segmentation and CADstream output, computed in terms of the DSC was 0.77 and 0.72, respectively. The algorithm also shows robust stability to imaging noise. Simulated imaging noise with zero mean and standard deviation equal to 25% of the base signal intensity was added to the DCE-MRI series. The amount of overlap between the tumor maps generated by the LDS-based algorithm from the noisy and original DCE-MRI was DSC = 0.95. CONCLUSION: The time-series analysis based segmentation algorithm provides high accuracy and sensitivity in delineating the regions of enhanced perfusion corresponding to tumor from DCE-MRI.
PURPOSE: Simplified models of non-monoexponential diffusion signal decay are of great interest to study the basic constituents of complex diffusion behavior in tissues. The latebra, a unique structure uniformly present in the yolk of avian eggs, exhibits a non-monoexponential diffusion signal decay. This model is more complex than simple phantoms based on differences between water and lipid diffusion, but is also devoid of microscopic structures with preferential orientation or perfusion effects. METHODS: Diffusion scans with multiple b-values were performed on a clinical 3 Tesla system in raw and boiled chicken eggs equilibrated to room temperature. Diffusion encoding was applied over the ranges 5-5,000 and 5-50,000 s/mm(2). A low read-out bandwidth and chemical shift was used for reliable lipid/water separation. Signal decays were fitted with exponential functions. RESULTS: The latebra, when measured over the 5-5,000 s/mm(2) range, exhibited independent of preparation clearly biexponential diffusion, with diffusion parameters similar to those typically observed in in vivo human brain. For the range 5-50,000 s/mm(2), there was evidence of a small third, very slow diffusing water component. CONCLUSION: The latebra of the avian egg contains membrane structures, which may explain a deviation from a simple monoexponential diffusion signal decay, which is remarkably similar to the deviation observed in brain tissue.
Multi-parametric Magnetic Resonance Imaging, and specifically Dynamic Contrast Enhanced (DCE) MRI, play increasingly important roles in detection and staging of prostate cancer (PCa). One of the actively investigated approaches to DCE MRI analysis involves pharmacokinetic (PK) modeling to extract quantitative parameters that may be related to microvascular properties of the tissue. It is well-known that the prescribed arterial blood plasma concentration (or Arterial Input Function, AIF) input can have significant effects on the parameters estimated by PK modeling. The purpose of our study was to investigate such effects in DCE MRI data acquired in a typical clinical PCa setting. First, we investigated how the choice of a semi-automated or fully automated image-based individualized AIF (iAIF) estimation method affects the PK parameter values; and second, we examined the use of method-specific averaged AIF (cohort-based, or cAIF) as a means to attenuate the differences between the two AIF estimation methods. Two methods for automated image-based estimation of individualized (patient-specific) AIFs, one of which was previously validated for brain and the other for breast MRI, were compared. cAIFs were constructed by averaging the iAIF curves over the individual patients for each of the two methods. Pharmacokinetic analysis using the Generalized kinetic model and each of the four AIF choices (iAIF and cAIF for each of the two image-based AIF estimation approaches) was applied to derive the volume transfer rate (K(trans)) and extravascular extracellular volume fraction (ve) in the areas of prostate tumor. Differences between the parameters obtained using iAIF and cAIF for a given method (intra-method comparison) as well as inter-method differences were quantified. The study utilized DCE MRI data collected in 17 patients with histologically confirmed PCa. Comparison at the level of the tumor region of interest (ROI) showed that the two automated methods resulted in significantly different (p<0.05) mean estimates of ve, but not of K(trans). Comparing cAIF, different estimates for both ve, and K(trans) were obtained. Intra-method comparison between the iAIF- and cAIF-driven analyses showed the lack of effect on ve, while K(trans) values were significantly different for one of the methods. Our results indicate that the choice of the algorithm used for automated image-based AIF determination can lead to significant differences in the values of the estimated PK parameters. K(trans) estimates are more sensitive to the choice between cAIF/iAIF as compared to ve, leading to potentially significant differences depending on the AIF method. These observations may have practical consequences in evaluating the PK analysis results obtained in a multi-site setting.
In this paper, we present a graph-based concurrent brain tumor segmentation and atlas to diseased patient registration framework. Both segmentation and registration problems are modeled using a unified pairwise discrete Markov Random Field model on a sparse grid superimposed to the image domain. Segmentation is addressed based on pattern classification techniques, while registration is performed by maximizing the similarity between volumes and is modular with respect to the matching criterion. The two problems are coupled by relaxing the registration term in the tumor area, corresponding to areas of high classification score and high dissimilarity between volumes. In order to overcome the main shortcomings of discrete approaches regarding appropriate sampling of the solution space as well as important memory requirements, content driven samplings of the discrete displacement set and the sparse grid are considered, based on the local segmentation and registration uncertainties recovered by the min marginal energies. State of the art results on a substantial low-grade glioma database demonstrate the potential of our method, while our proposed approach shows maintained performance and strongly reduced complexity of the model.
In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors.
Presurgical language mapping for patients with lesions close to language areas is critical to neurosurgical decision-making for preservation of language function. As a clinical noninvasive imaging technique, functional MRI (fMRI) is used to identify language areas by measuring blood-oxygen-level dependent (BOLD) signal change while patients perform carefully timed language vs. control tasks. This task-based fMRI critically depends on task performance, excluding many patients who have difficulty performing language tasks due to neurologic deficits. On the basis of recent discovery of resting-state fMRI (rs-fMRI), we propose a "task-free" paradigm acquiring fMRI data when patients simply are at rest. This paradigm is less demanding for patients to perform and easier for technologists to administer. We investigated the feasibility of this approach in right-handed healthy control subjects. First, group independent component analysis (ICA) was applied on the training group (14 subjects) to identify group level language components based on expert rating results. Then, four empirically and structurally defined language network templates were assessed for their ability to identify language components from individuals' ICA output of the testing group (18 subjects) based on spatial similarity analysis. Results suggest that it is feasible to extract language activations from rs-fMRI at the individual subject level, and two empirically defined templates (that focuses on frontal language areas and that incorporates both frontal and temporal language areas) demonstrated the best performance. We propose a semi-automated language component identification procedure and discuss the practical concerns and suggestions for this approach to be used in clinical fMRI language mapping.
OBJECTIVE: The purpose of this article is to report the translational process of an implantable microdevice platform with an emphasis on the technical and engineering adaptations for patient use, regulatory advances, and successful integration into clinical workflow. METHODS: We developed design adaptations for implantation and retrieval, established ongoing monitoring and testing, and facilitated regulatory advances that enabled the administration and examination of a large set of cancer therapies simultaneously in individual patients. RESULTS: Six applications for oncology studies have successfully proceeded to patient trials, with future applications in progress. CONCLUSION: First-in-human translation required engineering design changes to enable implantation and retrieval that fit with existing clinical workflows, a regulatory strategy that enabled both delivery and response measurement of up to 20 agents in a single patient, and establishment of novel testing and quality control processes for a drug/device combination product without clear precedents. SIGNIFICANCE: This manuscript provides a real-world account and roadmap on how to advance from animal proof-of-concept into the clinic, confronting the question of how to use research to benefit patients.
Optimal resection of breast tumors requires removing cancer with a rim of normal tissue while preserving uninvolved regions of the breast. Surgical and pathological techniques that permit rapid molecular characterization of tissue could facilitate such resections. Mass spectrometry (MS) is increasingly used in the research setting to detect and classify tumors and has the potential to detect cancer at surgical margins. Here, we describe the ex vivo intraoperative clinical application of MS using a liquid micro-junction surface sample probe (LMJ-SSP) to assess breast cancer margins. In a midpoint analysis of a registered clinical trial, surgical specimens from 21 women with treatment naïve invasive breast cancer were prospectively collected and analyzed at the time of surgery with subsequent histopathological determination. Normal and tumor breast specimens from the lumpectomy resected by the surgeon were smeared onto glass slides for rapid analysis. Lipidomic profiles were acquired from these specimens using LMJ-SSP MS in negative ionization mode within the operating suite and post-surgery analysis of the data revealed five candidate ions separating tumor from healthy tissue in this limited dataset. More data is required before considering the ions as candidate markers. Here, we present an application of ambient MS within the operating room to analyze breast cancer tissue and surgical margins. Lessons learned from these initial promising studies are being used to further evaluate the five candidate biomarkers and to further refine and optimize intraoperative MS as a tool for surgical guidance in breast cancer.
Introduction: Neuronavigation greatly improves the surgeons ability to approach, assess and operate on brain tumors, but tends to lose its accuracy as the surgery progresses and substantial brain shift and deformation occurs. Intraoperative MRI (iMRI) can partially address this problem but is resource intensive and workflow disruptive. Intraoperative ultrasound (iUS) provides real-time information that can be used to update neuronavigation and provide real-time information regarding the resection progress. We describe the intraoperative use of 3D iUS in relation to iMRI, and discuss the challenges and opportunities in its use in neurosurgical practice. Methods: We performed a retrospective evaluation of patients who underwent image-guided brain tumor resection in which both 3D iUS and iMRI were used. The study was conducted between June 2020 and December 2020 when an extension of a commercially available navigation software was introduced in our practice enabling 3D iUS volumes to be reconstructed from tracked 2D iUS images. For each patient, three or more 3D iUS images were acquired during the procedure, and one iMRI was acquired towards the end. The iUS images included an extradural ultrasound sweep acquired before dural incision (iUS-1), a post-dural opening iUS (iUS-2), and a third iUS acquired immediately before the iMRI acquisition (iUS-3). iUS-1 and preoperative MRI were compared to evaluate the ability of iUS to visualize tumor boundaries and critical anatomic landmarks; iUS-3 and iMRI were compared to evaluate the ability of iUS for predicting residual tumor. Results: Twenty-three patients were included in this study. Fifteen patients had tumors located in eloquent or near eloquent brain regions, the majority of patients had low grade gliomas (11), gross total resection was achieved in 12 patients, postoperative temporary deficits were observed in five patients. In twenty-two iUS was able to define tumor location, tumor margins, and was able to indicate relevant landmarks for orientation and guidance. In sixteen cases, white matter fiber tracts computed from preoperative dMRI were overlaid on the iUS images. In nineteen patients, the EOR (GTR or STR) was predicted by iUS and confirmed by iMRI. The remaining four patients where iUS was not able to evaluate the presence or absence of residual tumor were recurrent cases with a previous surgical cavity that hindered good contact between the US probe and the brainsurface. Conclusion: This recent experience at our institution illustrates the practical benefits, challenges, and opportunities of 3D iUS in relation to iMRI.
OBJECTIVE: Accurate biopsy sampling of the suspected lesions is critical for the diagnosis and clinical management of prostate cancer. Transperineal in-bore MRI-guided prostate biopsy (tpMRgBx) is a targeted biopsy technique that was shown to be safe, efficient, and accurate. Our goal was to develop an open source software platform to support evaluation, refinement, and translation of this biopsy approach. METHODS: We developed SliceTracker, a 3D Slicer extension to support tpMRgBx. We followed modular design of the implementation to enable customization of the interface and interchange of image segmentation and registration components to assess their effect on the processing time, precision, and accuracy of the biopsy needle placement. The platform and supporting documentation were developed to enable the use of software by an operator with minimal technical training to facilitate translation. Retrospective evaluation studied registration accuracy, effect of the prostate segmentation approach, and re-identification time of biopsy targets. Prospective evaluation focused on the total procedure time and biopsy targeting error (BTE). RESULTS: Evaluation utilized data from 73 retrospective and ten prospective tpMRgBx cases. Mean landmark registration error for retrospective evaluation was 1.88 ± 2.63 mm, and was not sensitive to the approach used for prostate gland segmentation. Prospectively, we observed target re-identification time of 4.60 ± 2.40 min and BTE of 2.40 ± 0.98 mm. CONCLUSION: SliceTracker is modular and extensible open source platform for supporting image processing aspects of the tpMRgBx procedure. It has been successfully utilized to support clinical research procedures at our site.
Patient-mounted needle guide devices for percutaneous ablation are vulnerable to patient motion. The objective of this study is to develop and evaluate a software system for an MRI-compatible patient-mounted needle guide device that can adaptively compensate for displacement of the device due to patient motion using a novel image-based automatic device-to-image registration technique. We have developed a software system for an MRI-compatible patient-mounted needle guide device for percutaneous ablation. It features fully-automated image-based device-to-image registration to track the device position, and a device controller to adjust the needle trajectory to compensate for the displacement of the device. We performed: (a) a phantom study using a clinical MR scanner to evaluate registration performance; (b) simulations using intraoperative time-series MR data acquired in 20 clinical cases of MRI-guided renal cryoablations to assess its impact on motion compensation; and (c) a pilot clinical study in three patients to test its feasibility during the clinical procedure. FRE, TRE, and success rate of device-to-image registration were [Formula: see text] mm, [Formula: see text] mm, and 98.3% for the phantom images. The simulation study showed that the motion compensation reduced the targeting error for needle placement from 8.2 mm to 5.4 mm (p < 0.0005) in patients under general anesthesia (GA), and from 14.4 mm to 10.0 mm ([Formula: see text]) in patients under monitored anesthesia care (MAC). The pilot study showed that the software registered the device successfully in a clinical setting. Our simulation study demonstrated that the software system could significantly improve targeting accuracy in patients treated under both MAC and GA. Intraprocedural image-based device-to-image registration was feasible.