One of the most basic trade-offs in ultrasound imaging involves frame rate, depth, and number of lines. Achieving good spatial resolution and coverage requires a large number of lines, leading to decreases in frame rate. An even more serious imaging challenge occurs with imaging modes involving spatial compounding and 3-D/4-D imaging, which are severely limited by the slow speed of sound in tissue. The present work can overcome these traditional limitations, making ultrasound imaging many-fold faster. By emitting several beams at once, and by separating the resulting overlapped signals through spatial and temporal processing, spatial resolution and/or coverage can be increased by many-fold while leaving frame rates unaffected. The proposed approach can also be extended to imaging strategies that do not involve transmit beamforming, such as synthetic aperture imaging. Simulated and experimental results are presented where imaging speed is improved by up to 32-fold, with little impact on image quality. Object complexity has little impact on the method's performance, and data from biological systems can readily be handled. The present work may open the door to novel multiplexed and/or multidimensional protocols considered impractical today.
Recent papers have demonstrated that acoustic standing waves can be inhibited by frequency-modulated spread-spectrum excitation. An alternative method is studied here that is designed to be more practical for implementation in phased arrays. The method operates using phase-shift-keying (PSK), which introduces phase shifts into the driving signal to break wave symmetry. Sequential and random binary-PSK (BPSK) and quadrature-PSK (QPSK) excitations are studied in water, using a carrier frequency of 250 kHz and a time segment of 10 cycles. The resulting acoustic field is measured with a transducer inside a plastic-walled chamber and compared with continuous wave excitation. Results indicate that both the random BPSK and QPSK methods can reduce time-averaged spatial intensity variation caused by standing waves by approximately six times.
The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta and alpha rhythms that are sleep onset-related EEG signatures along with the subsequent neural circuitries from a sleep-deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable.
We describe a method for atlas-based segmentation of structural MRI for calculation of magnetic fieldmaps. CT data sets are used to construct a probabilistic atlas of the head and corresponding MR is used to train a classifier that segments soft tissue, air, and bone. Subject-specific fieldmaps are computed from the segmentations using a perturbation field model. Previous work has shown that distortion in echo-planar images can be corrected using predicted fieldmaps. We obtain results that agree well with acquired fieldmaps: 90% of voxel shifts from predicted fieldmaps show subvoxel disagreement with those computed from acquired fieldmaps. In addition, our fieldmap predictions show statistically significant improvement following inclusion of the atlas.
Automated interpretation and classification of functional MRI (fMRI) data is an emerging research field that enables the characterization of underlying cognitive processes with minimal human intervention. In this work, we present a method for the automated classification of human thoughts reflected on a trial-based paradigm using fMRI with a significantly shortened data acquisition time (less than one minute). Based on our preliminary experience with various cognitive imagery tasks, six characteristic thoughts were chosen as target tasks for the present work: right-hand motor imagery, left-hand motor imagery, right foot motor imagery, mental calculation, internal speech/word generation, and visual imagery. These six tasks were performed by five healthy volunteers and functional images were obtained using a T(*)(2)-weighted echo planar imaging (EPI) sequence. Feature vectors from activation maps, necessary for the classification of neural activity, were automatically extracted from the regions that were consistently and exclusively activated for a given task during the training process. Extracted feature vectors were classified using the support vector machine (SVM) algorithm. Parameter optimization, using a k-fold cross validation scheme, allowed the successful recognition of the six different categories of administered thought tasks with an accuracy of 74.5% (mean)+/-14.3% (standard deviation) across all five subjects. Our proposed study for the automated classification of fMRI data may be utilized in further investigations to monitor/identify human thought processes and their potential link to hardware/computer control.
We propose a novel Bayesian registration formulation in which image location is represented as a latent random variable. Location is marginalized to determine the maximum a priori (MAP) transform between images, which results in registration that is more robust than the alternatives of omitting locality (i.e. global registration) or jointly maximizing locality and transform (i.e. iconic registration). A mathematical link is established between the Bayesian registration formulation and the mutual information (MI) similarity measure. This leads to a novel technique for selecting informative image regions for registration, based on the MI of image intensity and spatial location. Experimental results demonstrate the effectiveness of the marginalization formulation and the MI-based region selection technique for ultrasound (US) to magnetic resonance (MR) registration in an image-guided neurosurgical application.
Real-time functional MRI (rtfMRI) has been used as a basis for brain-computer interface (BCI) due to its ability to characterize region-specific brain activity in real-time. As an extension of BCI, we present an rtfMRI-based brain-machine interface (BMI) whereby 2-dimensional movement of a robotic arm was controlled by the regulation (and concurrent detection) of regional cortical activations in the primary motor areas. To do so, the subjects were engaged in the right- and/or left-hand motor imagery tasks. The blood oxygenation level dependent (BOLD) signal originating from the corresponding hand motor areas was then translated into horizontal or vertical robotic arm movement. The movement was broadcasted visually back to the subject as a feedback. We demonstrated that real-time control of the robotic arm only through the subjects' thought processes was possible using the rtfMRI-based BMI trials.
Quantitative, apparent T(2) values of suspected prostate cancer and healthy peripheral zone tissue in men with prostate cancer were measured using a Carr-Purcell-Meiboom-Gill (CPMG) imaging sequence in order to assess the cancer discrimination potential of tissue T(2) values. The CPMG imaging sequence was used to image the prostates of 18 men with biopsy-proven prostate cancer. Whole gland coverage with nominal voxel volumes of 0.54 x 1.1 x 4 mm(3) was obtained in 10.7 min, resulting in data sets suitable for generating high-quality images with variable T(2)-weighting and for evaluating quantitative T(2) values on a pixel-by-pixel basis. Region-of-interest analysis of suspected healthy peripheral zone tissue and suspected cancer, identified on the basis of both T(1)- and T(2)-weighted signal intensities and available histopathology reports, yielded significantly (P<.0001) longer apparent T(2) values in suspected healthy tissue (193+/-49 ms) vs. suspected cancer (100+/-26 ms), suggesting potential utility of this method as a tissue specific discrimination index for prostate cancer. We conclude that CPMG imaging of the prostate can be performed in reasonable scan times and can provide advantages over T(2)-weighted fast spin echo (FSE) imaging alone, including quantitative T(2) values for cancer discrimination as well as proton density maps without the point spread function degradation associated with short effective echo time FSE sequences.
Language functional magnetic resonance imaging (fMRI) is a promising non-invasive technique for pre-surgical planning in patients whose lesions are adjacent to or within critical language areas. Most language fMRI studies in patients use blocked experimental design. In this study, we compared a blocked design and a rapid event-related design with a jittered inter-stimulus-interval (ISI) (or stochastic design) for language fMRI in six healthy controls, and eight brain tumor patients, using a vocalized antonym generation task. Comparisons were based on visual inspection of fMRI activation maps and degree of language lateralization, both of which were assessed at a constant statistical threshold for each design. The results indicated a relatively high degree of discordance between the two task designs. In general, the event-related design provided maps with more robust activations in the putative language areas than the blocked design, especially for brain tumor patients. Our results suggest that the rapid event-related design has potential for providing comparable or even higher detection power over the blocked design for localizing language function in brain tumor patients, and therefore may be able to generate more sensitive language maps. More patient studies, and further investigation and optimization of language fMRI paradigms will be needed to determine the utility and validity of this approach for pre-surgical planning.
BACKGROUND: A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning.
RESULTS: We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications.
CONCLUSION: Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.
Minimally invasive applications of thermal and mechanical energy to selective areas of the human anatomy have led to significant advances in treatment of and recovery from typical surgical interventions. Image-guided focused ultrasound allows energy to be deposited deep into the tissue, completely noninvasively. There has long been interest in using this focal energy delivery to block nerve conduction for pain control and local anesthesia. In this study, we have performed an in vitro study to further extend our knowledge of this potential clinical application. The sciatic nerves from the bullfrog (Rana catesbeiana) were subjected to focused ultrasound (at frequencies of 0.661 MHz and 1.986 MHz) and to heated Ringer's solution. The nerve action potential was shown to decrease in the experiments and correlated with temperature elevation measured in the nerve. The action potential recovered either completely, partially or not at all, depending on the parameters of the ultrasound exposure. The reduction of the baseline nerve temperature by circulating cooling fluid through the sonication chamber did not prevent the collapse of the nerve action potential; but higher power was required to induce the same endpoint as without cooling. These results indicate that a thermal mechanism of focused ultrasound can be used to block nerve conduction, either temporarily or permanently.
Interest in the manner in which brain tissue signal decays with b factor in diffusion imaging schemes has grown in recent years following the observation that the decay curves depart from purely monoexponential decay behavior. Regardless of the model or fitting function proposed for characterizing sufficiently sampled decay curves (vide infra), the departure from monoexponentiality spells increased tissue characterization potential. The degree to which this potential can be harnessed to improve specificity, sensitivity and spatial localization of diseases in brain, and other tissues, largely remains to be explored. Furthermore, the degree to which currently popular diffusion tensor imaging methods, including visually impressive white matter fiber "tractography" results, have almost completely ignored the nonmonoexponential nature of the basic signal decay with b factor is worthy of communal introspection. Here we limit our attention to a review of the basic experimental features associated with brain water signal diffusion decay curves as measured over extended b-factor ranges, the simple few parameter fitting functions that have been proposed to characterize these decays and the more involved models, e.g.,"ruminations," which have been proposed to account for the nonmonoexponentiality to date.
PURPOSE: To investigate the utility of a proposed clinical diffusion imaging scheme for rapidly generating multiple b-value diffusion contrast in brain magnetic resonance imaging (MRI) with high signal-to-noise ratio (SNR).
MATERIALS AND METHODS: Our strategy for efficient image acquisition relies on the invariance property of the diffusion tensor eigenvectors to b-value. A simple addition to the conventional diffusion tensor MR imaging (DTI) data acquisition scheme used for tractography yields diffusion-weighted images at twice and three times the conventional b-value. An example from a neurosurgical brain tumor is shown. Apparent diffusion-weighted (ADW) images were calculated for b-values 800, 1600, and 2400 s/mm(2), and a map of excess diffusive kurtosis was computed from the three ADWs.
RESULTS: High b-value ADW images demonstrated decreased contrast between normal gray and white matter, while the heterogeneity and contrast of the lesion was emphasized relative to conventional b-value data. Kurtosis maps indicated the deviation from Gaussian diffusive behavior.
CONCLUSION: DTI data with multiple b-values and good SNR can be acquired in clinically reasonable times. High b-value ADW images show increased contrast and add information to conventional DWI. Ambiguity in conventional b-value images over whether hyperintense signal results from abnormally low diffusion, or abnormally long T(2), is better resolved in high b-value images.
The field of magnetic resonance imaging-guided high-intensity focused ultrasound surgery (MRgFUS) is a rapidly evolving one, with many potential applications in neurosurgery. The first of 3 articles on MRgFUS, this article focuses on the historical development of the technology and its potential applications in modern neurosurgery. The evolution of MRgFUS has occurred in parallel with modern neurological surgery, and the 2 seemingly distinct disciplines share many of the same pioneering figures. Early studies on focused ultrasound treatment in the 1940s and 1950s demonstrated the ability to perform precise lesioning in the human brain, with a favorable risk-benefit profile. However, the need for a craniotomy, as well as the lack of sophisticated imaging technology, resulted in limited growth of high-intensity focused ultrasound for neurosurgery. More recently, technological advances have permitted the combination of high-intensity focused ultrasound along with magnetic resonance imaging guidance to provide an opportunity to effectively treat a variety of central nervous system disorders. Although challenges remain, high-intensity focused ultrasound-mediated neurosurgery may offer the ability to target and treat central nervous system conditions that were previously extremely difficult to address. The remaining 2 articles in this series will focus on the physical principles of modern MRgFUS as well as current and future avenues for investigation.
Thermal ablation is an established treatment for tumors. The merging of newly developed imaging techniques has allowed precise targeting and real-time thermal mapping. This article provides an overview of the image-guided thermal ablation techniques in the treatment of uterine fibroids. Background on uterine fibroids, including epidemiology, histology, symptoms, imaging findings, and current treatment options, is first outlined. After describing the principle of magnetic resonance thermal imaging, we introduce the applications of image-guided thermal therapies, including laser ablation, radiofrequency ablation, cryotherapy, and in particular, magnetic resonance-guided focused ultrasound surgery, and how they apply to uterine fibroid treatment.
The diffusion coefficient of lipids, D(l), within bone marrow, fat deposits and metabolically active intracellular lipids in vivo will depend on several factors including the precise chemical composition of the lipid distribution (chain lengths, degree of unsaturation, etc.) as well as the temperature. As such, D(l) may ultimately prove of value in assessing abnormal fatty acid distributions linked to diseases such as cystic fibrosis, diabetes and coronary heart disease. A sensitive temperature dependence of D(l) may also prove of value for MR-guided thermal therapies for bone tumors or disease within other fatty tissues like the breast. Measuring diffusion coefficients of high molecular weight lipids in vivo is, however, technically difficult for a number of reasons. For instance, due to the much lower diffusion coefficients compared to water, much higher b factors than those used for central nervous system applications are needed. In addition, the pulse sequence design must incorporate, as much as possible, immunity to motion, susceptibility and chemical shift effects present whenever body imaging is performed. In this work, high b-factor line scan diffusion imaging sequences were designed, implemented and tested for D(l) measurement using a 4.7-T horizontal bore animal scanner. The gradient set available allowed for b factors as high as 0.03 micros/nm(2) (30,000 s/mm(2)) at echo times as short as 42 ms. The methods were used to measure lipid diffusion coefficients within the marrow of rat paws in vivo, yielding lipid diffusion coefficients approximately two orders of magnitude smaller than typical tissue water diffusion coefficients. Phantom experiments that demonstrate the sensitivity of lipid diffusion coefficients to chain length and temperature were also performed.
OBJECTIVE: Various methods of intraoperative structural monitoring during neurosurgery are used to localize lesions after brain shift and to guide surgically introduced probes such as biopsy needles or stimulation electrodes. With its high temporal resolution, portability, and nonionizing mode of radiation, ultrasound has potential advantages over other existing imaging modalities for intraoperative monitoring, yet ultrasound is rarely used during neurosurgery largely because of the craniotomy requirement to achieve sufficiently useful signals. METHODS: Prompted by results from recent studies on transcranial ultrasound, a prototype device that aims to use the shear mode of transcranial ultrasound transmission for intraoperative monitoring was designed, constructed, and tested with 10 human participants. Magnetic resonance images were then obtained with the device spatially registered to the magnetic resonance imaging (MRI) reference coordinates. Peaks in both the ultrasound and MRI signals were identified and analyzed for both spatial localization and signal-to-noise ratio (SNR). RESULTS: The first results aimed toward validating the prototype device with MRI showed an excellent correlation (n = 38; R(2) = 0.9962) between the structural localization abilities of the two modalities. In addition, the overall SNR of the ultrasound backscatter signals (n = 38; SNR = 25.4 +/- 5.2 dB, mean +/- SD) was statistically equivalent to that of the MRI data (n = 38; SNR = 22.5 +/- 4.8 dB). CONCLUSIONS: A statistically significant correlation of localized intracranial structures between intraoperative transcranial ultrasound monitoring and MRI data was achieved with 10 human participants. We have shown and validated a prototype device incorporating transcranial shear mode ultrasound for clinical monitoring applications.
We introduce a framework for computing geometrical properties of white matter fibres directly from diffusion tensor fields. The key idea is to isolate the portion of the gradient of the tensor field corresponding to local variation in tensor orientation, and to project it onto a coordinate frame of tensor eigenvectors. The resulting eigenframe-centered representation makes it possible to define scalar geometrical measures that describe the underlying white matter fibres, directly from the diffusion tensor field and its gradient, without requiring prior tractography. We define two new scalar measures of (1) fibre dispersion and (2) fibre curving, and we demonstrate them on synthetic and in-vivo datasets. Finally, we illustrate their applicability in a group study on schizophrenia.
RATIONALE AND OBJECTIVES: The authors present their initial experience using a 3-T whole-body scanner equipped with a 128-channel coil applied to lung motion assessment. Recent improvements in fast magnetic resonance imaging (MRI) technology have enabled several trials of free-breathing three-dimensional (3D) imaging of the lung. A large number of image frames necessarily increases the difficulty of image analysis and therefore warrants automatic image processing. However, the intensity homogeneities of images of prior dynamic 3D lung MRI studies have been insufficient to use such methods. In this study, initial data were obtained at 3 T with a 128-channel coil that demonstrate the feasibility of acquiring multiple sets of 3D pulmonary scans during free breathing and that have sufficient quality to be amenable to automatic segmentation.
MATERIALS AND METHODS: Dynamic 3D images of the lungs of two volunteers were acquired with acquisition times of 0.62 to 0.76 frames/s and an image matrix of 128 x 128, with 24 to 30 slice encodings. The volunteers were instructed to take shallow and deep breaths during the scans. The variation of lung volume was measured from the segmented images.
RESULTS: Dynamic 3D images were successfully acquired for both respiratory conditions for each subject. The images showed whole-lung motion, including lifting of the chest wall and the displacement of the diaphragm, with sufficient contrast to distinguish these structures from adjacent tissues. The average time to complete segmentation for one 3D image was 4.8 seconds. The tidal volume measured was consistent with known tidal volumes for healthy subjects performing deep-breathing maneuvers. The temporal resolution was insufficient to measure tidal volumes for shallow breathing.
CONCLUSION: This initial experience with a 3-T whole-body scanner and a 128-channel coil showed that the scanner and imaging protocol provided dynamic 3D images with spatial and temporal resolution sufficient to delineate the diaphragmatic domes and chest wall during active breathing. In addition, the intensity homogeneities and signal-to-noise ratio were adequate to perform automatic segmentation.
Conventional spectral-spatial pulses used for water-selective excitation in proton resonance frequency-shift MR thermometry require increased sequence length compared to shorter wideband pulses. This is because spectral-spatial pulses are longer than wideband pulses, and the echo time period starts midway through them. Therefore, for a fixed echo time, one must increase sequence length to accommodate conventional spectral-spatial pulses in proton resonance frequency-shift thermometry. We introduce improved water-selective spectral-spatial pulses for which the echo time period starts near the beginning of excitation. Instead of requiring increased sequence length, these pulses extend into the long echo time periods common to PRF sequences. The new pulses therefore alleviate the traditional tradeoff between sequence length and fat suppression. We experimentally demonstrate an 11% improvement in frame rate in a proton resonance frequency imaging sequence compared to conventional spectral-spatial excitation. We also introduce a novel spectral-spatial pulse design technique that is a hybrid of previous model- and filter-based techniques and that inherits advantages from both. We experimentally validate the pulses' performance in suppressing lipid signal and in reducing sequence length compared to conventional spectral-spatial pulses.
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.
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.