Tissue water molecules reside in different biophysical compartments. For example, water molecules in the vasculature reside for variable periods of time within arteries, arterioles, capillaries, venuoles and veins, and may be within blood cells or blood plasma. Water molecules outside of the vasculature, in the extravascular space, reside, for a time, either within cells or within the interstitial space between cells. Within these different compartments, different types of microscopic motion that water molecules may experience have been identified and discussed. These range from Brownian diffusion to more coherent flow over the time scales relevant to functional magnetic resonance imaging (fMRI) experiments, on the order of several 10s of milliseconds. How these different types of motion are reflected in magnetic resonance imaging (MRI) methods developed for "diffusion" imaging studies has been an ongoing and active area of research. Here we briefly review the ideas that have developed regarding these motions within the context of modern "diffusion" imaging techniques and, in particular, how they have been accessed in attempts to further our understanding of the various contributions to the fMRI signal changes sought in studies of human brain activation.
The integration of medical devices with software applications is crucial for image-guided medical applications. This work describes a general device interface that has been designed for high-frequency streaming of multi-modal events, thus providing maximum performance and flexibility for such applications. Several sample applications and performance tests are provided to demonstrate the usability of the concept.
Regional investigations of newborn MRI are important to understand the appearance and consequences of early brain injury. Previously, regionalization in neonates has been achieved with a Talairach parcellation, using internal landmarks of the brain. Non-synostotic dolichocephaly defines a bi-temporal narrowing of the preterm infant's head caused by pressure on the immature skull. The impact of dolichocephaly on brain shape and regional brain shift, which may compromise the validity of the parcellation scheme, has not yet been investigated. Twenty-four preterm and 20 fullterm infants were scanned at term equivalent. Skull shapes were investigated by cephalometric measurements and population registration. Brain tissue volumes were calculated to rule out brain injury underlying skull shape differences. The position of Talairach landmarks was evaluated. Cortical structures were segmented to determine a positional shift between both groups. The preterm group displayed dolichocephalic head shapes and had similar brain volumes compared to the mesocephalic fullterm group. In preterm infants, Talairach landmarks were consistently positioned relative to each other and to the skull base, but were displaced with regard to the calvarium. The frontal and superior region was enlarged; central and temporal gyri and sulci were shifted comparing preterm and fullterm infants. We found that, in healthy preterm infants, dolichocephaly led to a shift of cortical structures, but did not influence deep brain structures. We concluded that the validity of a Talairach parcellation scheme is compromised and may lead to a miscalculation of regional brain volumes and inconsistent parcel contents when comparing infant populations with divergent head shapes.
This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of our multiscale prior and 2) a segmentation task. In the reconstruction task, our results show that for a given training set size, our algorithm significantly improves the approximation of shapes in a testing set over the Point Distribution Model, which tends to oversmooth data. In the segmentation task, our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm, by capturing finer shape details.
A system was developed for real-time electrocardiogram (ECG) analysis and artifact correction during magnetic resonance (MR) scanning, to improve patient monitoring and triggering of MR data acquisitions. Based on the assumption that artifact production by magnetic field gradient switching represents a linear time invariant process, a noise cancellation (NC) method is applied to ECG artifact linear prediction. This linear prediction is performed using a digital finite impulse response (FIR) matrix, that is computed employing ECG and gradient waveforms recorded during a training scan. The FIR filters are used during further scanning to predict artifacts by convolution of the gradient waveforms. Subtracting the artifacts from the raw ECG signal produces the correction with minimal delay. Validation of the system was performed both off-line, using prerecorded signals, and under actual examination conditions. The method is implemented using a specially designed Signal Analyzer and Event Controller (SAEC) computer and electronics. Real-time operation was demonstrated at 1 kHz with a delay of only 1 ms introduced by the processing. The system opens the possibility of automatic monitoring algorithms for electrophysiological signals in the MR environment.
OBJECTIVE: Virtual endoscopic simulations using volume rendering (VR) have been proposed as a tool for training and understanding intraventricular anatomy. It is not known whether surface rendering (SR), an alternative to VR, can visualize intraventricular and subependymal structures better and thus making the virtual endoscope more useful for simulating the intraventricular endoscopy. We sought to develop SR-virtual endoscopy and compared the visibility of anatomical structures in SR and VR using retrospective cases.
MATERIALS AND METHODS: Fourteen patients who underwent endoscopic intraventricular surgery of third ventricle enrolled the study. SR-virtual endoscopy module was developed in open-source software 3D Slicer and virtual endoscopic scenes from the retrospective cases were created. VR virtual endoscopy of the same cases was prepared in commercial software. Three neurosurgeons scored the visibility of substructures in lateral and third ventricle, arteries, cranial nerves, and other lesions Results: We found that VR and SR-virtual endoscopy performed similarly in visualization of substructures in lateral and third ventricle (not significant statistically). However, the SR was statistically significantly better in visualizing subependymal arteries, cranial nerves, and other lesions (p<0.05, respectively).
CONCLUSIONS: We concluded that SR-virtual endoscopy is a promising tool to visualize critical anatomical structures in simulated endoscopic intraventricular surgery. The results lead us to propose a hybrid technique of volume and surface rendering to balance the strength of surface rendering alone in visualizing arteries, nerves and lesions, with fast volume rendering of third and lateral ventricles.
The clinical application of chemotherapy to brain tumors has been severely limited because antitumor agents are typically unable to penetrate an intact blood-brain barrier (BBB). Although doxorubicin (DOX) has been named as a strong candidate for chemotherapy of the central nervous system (CNS), the BBB often prevents cytotoxic levels from being achieved. In this study, we demonstrate a noninvasive method for the targeted delivery of DOX through the BBB, such that drug levels shown to be therapeutic in human tumors are achieved in the normal rat brain. Using MRI-guided focused ultrasound with preformed microbubbles (Optison) to locally disrupt the BBB and systemic administration of DOX, we achieved DOX concentrations of 886 +/- 327 ng/g tissue in the brain with minimal tissue effects. Tissue DOX concentrations of up to 5,366 +/- 659 ng/g tissue were achieved with higher Optison doses, but with more significant tissue damage. In contrast, DOX accumulation in nontargeted contralateral brain tissue remained significantly lower for all paired samples (p < 0.001). These results suggest that targeted delivery by focused ultrasound may render DOX chemotherapy a viable treatment option against CNS tumors, despite previous accessibility limitations. In addition, MRI signal enhancement in the sonicated region correlated strongly with tissue DOX concentration (r = 0.87), suggesting that contrast-enhanced MRI could perhaps indicate drug penetration during image-guided interventions. Our technique using MRI-guided focused ultrasound to achieve therapeutic levels of DOX in the brain offers a large step forward in the use of chemotherapy to treat patients with CNS malignancies.
PURPOSE: To prospectively assess patient response (after 12 months) to magnetic resonance (MR) imaging-guided focused ultrasound surgery in treatment of uterine leiomyomas by using two treatment protocols.
MATERIALS AND METHODS: This prospective clinical trial was approved by institutional review boards and was HIPAA compliant. After giving informed consent, patients with symptomatic leiomyomas were consecutively enrolled and treated at one of five U.S. centers by using an original or a modified protocol. Outcomes were assessed with the symptom severity score (SSS) obtained at baseline and 3, 6, and 12 months after treatment. Adverse events (AEs) were recorded. Statistical analysis included Student t test, Fisher exact test, analysis of covariance, Spearman correlation, and logistic regression.
RESULTS: One hundred sixty patients had a mean SSS of 62.1 +/- 16.3 (standard deviation) at baseline, which decreased to 35.5 +/- 19.5 at 3 months (P<.001) and to 32.3 +/- 19.8 at 6 months (P<.001) and was 32.7 +/- 21.0 at 12 months (P<.001). Ninety-six patients (mean age, 46.0 years +/- 4.6) were treated with an original protocol, and 64 (mean age, 45.9 years +/- 3.9) were treated with a modified protocol. Patients in the modified group had a significantly greater SSS decrease at 3 months (P=.037) than those in the original group, and 73% of those in the original group and 91% of those in the modified group reported a significant decrease in SSS (of 10 points or greater) at 12 months. No serious AEs were recorded. Fewer AEs were reported in the modified group than in the original group (25% vs 13% reporting no event). Of evaluable patients, fewer in the modified group chose alternative treatment (28%) than in the original group (37%).
CONCLUSION: MR imaging-guided focused ultrasound surgery results in symptomatic improvement, sustained to 12 months after treatment. Treatment with a modified protocol results in greater clinical effectiveness and fewer AEs.
We describe a new approach for estimating the posterior probability of tissue labels. Conventional likelihood models are combined with a curve length prior on boundaries, and an approximate posterior distribution on labels is sought via the Mean Field approach. Optimizing the resulting estimator by gradient descent leads to a level set style algorithm where the level set functions are the logarithm-of-odds encoding of the posterior label probabilities in an unconstrained linear vector space. Applications with more than two labels are easily accommodated. The label assignment is accomplished by the Maximum A Posteriori rule, so there are no problems of "overlap" or "vacuum". We test the method on synthetic images with additive noise. In addition, we segment a magnetic resonance scan into the major brain compartments and subcortical structures.
The investigation of inertial cavitation in micro-tunnels has significant implications for the development of therapeutic applications of ultrasound such as ultrasound-mediated drug and gene delivery. The threshold for inertial cavitation was investigated using a passive cavitation detector with a center frequency of 1 MHz. Micro-tunnels of various diameters (90 to 800 microm) embedded in gel were fabricated and injected with a solution of Optison(trade mark) contrast agent of concentrations 1.2% and 0.2% diluted in water. An ultrasound pulse of duration 500 ms and center frequency 1.736 MHz was used to insonate the microbubbles. The acoustic pressure was increased at 1-s intervals until broadband noise emission was detected. The pressure threshold at which broadband noise emission was observed was found to be dependent on the diameter of the micro-tunnels, with an average increase of 1.2 to 1.5 between the smallest and the largest tunnels, depending on the microbubble concentration. The evaluation of inertial cavitation in gel tunnels rather than tubes provides a novel opportunity to investigate microbubble collapse in a situation that simulates in vivo blood vessels better than tubes with solid walls do.
Since the introduction of diffusion weighted imaging (DWI) as a method for examining neural connectivity, its accuracy has not been formally evaluated. In this study, we directly compared connections that were visualized using injected neural tract tracers (WGA-HRP) with those obtained using in-vivo diffusion tensor imaging (DTI) tractography. First, we injected the tracer at multiple sites in the brain of a macaque monkey; second, we reconstructed the histological sections of the labeled fiber tracts in 3D; third, we segmented and registered the fibers (somatosensory and motor tracts) with the anatomical in-vivo MRI from the same animal; and last, we conducted fiber tracing along the same pathways on the DTI data using a classical diffusion tracing technique with the injection sites as seeds. To evaluate the performance of DTI fiber tracing, we compared the fibers derived from the DTI tractography with those segmented from the histology. We also studied the influence of the parameters controlling the tractography by comparing Dice superimposition coefficients between histology and DTI segmentations. While there was generally good visual agreement between the two methods, our quantitative comparisons reveal certain limitations of DTI tractography, particularly for regions at remote locations from seeds. We have thus demonstrated the importance of appropriate settings for realistic tractography results.
We formalize the pair-wise registration problem in a maximum a posteriori (MAP) framework that employs a multinomial model of joint intensities with parameters for which we only have a prior distribution. To obtain an MAP estimate of the aligning transformation alone, we treat the multinomial parameters as nuisance parameters, and marginalize them out. If the prior on those is uninformative, the marginalization leads to registration by minimization of joint entropy. With an informative prior, the marginalization leads to minimization of the entropy of the data pooled with pseudo observations from the prior. In addition, we show that the marginalized objective function can be optimized by the Expectation-Maximization (EM) algorithm, which yields a simple and effective iteration for solving entropy-based registration problems. Experimentally, we demonstrate the effectiveness of the resulting EM iteration for rapidly solving a challenging intra-operative registration problem.
Using direct cortical stimulation to map language function during awake craniotomy is a well-described and useful technique. However, the optimum neuropsychological tasks to use have not been detailed. We used both functional MRI (fMRI) and direct cortical stimulation to compare the sensitivity of two behavioral paradigms, number counting and object naming, in the demonstration of eloquent cortical language areas. Fifteen patients with left hemisphere lesions and seven healthy control subjects participated. Patients had both preoperative fMRI at 3 T and direct cortical stimulation. Patients and controls performed object naming and number counting during fMRI at 3 T. Laterality indices were calculated from the fMRI maps for the Number-counting>Object-naming and Object-naming>Number-counting contrasts. The same number-counting and object-naming paradigms were tested during awake craniotomy and assessed for sensitivity to speech disruption. In all patients during intraoperative cortical stimulation, speech disruption occurred at more sites during object naming than during number counting. Subtle speech errors were only elicited with the object-naming paradigm, whereas only speech arrest and/or hypophonia were measured using the number counting paradigm. In both patients and controls, fMRI activation maps demonstrated greater left lateralization for object naming as compared to number counting in both frontal and temporal language areas. Number counting resulted in a more bihemispheric distribution of activations than object naming. Both cortical stimulation testing and fMRI suggest that automated speech tasks such as number counting may not fully engage putative language networks and therefore are not optimal for language localization for surgical planning.
A novel framework for joint clustering and point-by-point mapping of white matter fiber pathways is presented. Accurate clustering of the trajectories into fiber bundles requires point correspondence determined along the fiber pathways. This knowledge is also crucial for any tract-oriented quantitative analysis. We employ an expectation-maximization (EM) algorithm to cluster the trajectories in a Gamma mixture model context. The result of clustering is the probabilistic assignment of the fiber trajectories to each cluster, an estimate of the cluster parameters, and point correspondences along the trajectories. Point-by-point correspondence of the trajectories within a bundle is obtained by constructing a distance map and a label map from each cluster center at every iteration of the EM algorithm. This offers a time-efficient alternative to pairwise curve matching of all trajectories with respect to each cluster center. Probabilistic assignment of the trajectories to clusters is controlled by imposing a minimum threshold on the membership probabilities, to remove outliers in a principled way. The presented results confirm the efficiency and effectiveness of the proposed framework for quantitative analysis of diffusion tensor MRI.
Geometric models of white matter architecture play an increasing role in neuroscientific applications of diffusion tensor imaging, and the most popular method for building them is fiber tractography. For some analysis tasks, however, a compelling alternative may be found in the first and second derivatives of diffusion anisotropy. We extend to tensor fields the notion from classical computer vision of ridges and valleys, and define anisotropy creases as features of locally extremal tensor anisotropy. Mathematically, these are the loci where the gradient of anisotropy is orthogonal to one or more eigenvectors of its Hessian. We propose that anisotropy creases provide a basis for extracting a skeleton of the major white matter pathways, in that ridges of anisotropy coincide with interiors of fiber tracts, and valleys of anisotropy coincide with the interfaces between adjacent but distinctly oriented tracts. The crease extraction algorithm we present generates high-quality polygonal models of crease surfaces, which are further simplified by connected-component analysis. We demonstrate anisotropy creases on measured diffusion MRI data, and visualize them in combination with tractography to confirm their anatomic relevance.
PURPOSE: To assess the feasibility of dynamic MRI of swallowing in a seated position using an open-configuration MRI scanner, and to compare its capacity for motion analysis around the pharyngeal wall with that of videofluorography.
MATERIALS AND METHODS: Six healthy individuals (four women and two men, mean age = 31.4 +/- 7.5 years) were examined with an open-configuration MRI system using a fast spoiled gradient-recalled echo (SPGR) sequence. Dynamic imaging was performed while the subjects were in a seated position after they swallowed oral contrast medium from a cup. An oral and maxillofacial radiologist measured the motion of six structures: the hyoid bone (HB), larynx (LX), upper oropharynx (UOP), lower oropharynx (LOP), pharyngoesophageal segment (PES) behind the vocal folds, and upper esophagus (ESO). The measured motions were compared with reported values from videofluorography-based observations.
RESULTS: Open-configuration MRI depicted the anatomic structures related to swallowing (lip, tongue, soft palate, mandible, pharynx, HB, LX, and PES), and the course of the mylohyoid muscle (MM). The vertical and anteroposterior displacements of these structures did not differ significantly from those measured by videofluorography.
CONCLUSION: Dynamic imaging of swallowing using open-configuration MRI provides image information comparable to that obtained from videofluorography.
OBJECTIVE: The objective of our study was to report the occurrence of benign inflammatory nodules that develop in or near applicator tracks after percutaneous radiofrequency ablation and cryoablation of renal tumors.
CONCLUSION: Benign inflammatory nodules occur rarely after percutaneous ablation of renal tumors and may mimic tumor seeding of the applicator track.
The logarithm of the odds ratio (LogOdds) is frequently used in areas such as artificial neural networks, economics, and biology, as an alternative representation of probabilities. Here, we use LogOdds to place probabilistic atlases in a linear vector space. This representation has several useful properties for medical imaging. For example, it not only encodes the shape of multiple anatomical structures but also captures some information concerning uncertainty. We demonstrate that the resulting vector space operations of addition and scalar multiplication have natural probabilistic interpretations. We discuss several examples for placing label maps into the space of LogOdds. First, we relate signed distance maps, a widely used implicit shape representation, to LogOdds and compare it to an alternative that is based on smoothing by spatial Gaussians. We find that the LogOdds approach better preserves shapes in a complex multiple object setting. In the second example, we capture the uncertainty of boundary locations by mapping multiple label maps of the same object into the LogOdds space. Third, we define a framework for non-convex interpolations among atlases that capture different time points in the aging process of a population. We evaluate the accuracy of our representation by generating a deformable shape atlas that captures the variations of anatomical shapes across a population. The deformable atlas is the result of a principal component analysis within the LogOdds space. This atlas is integrated into an existing segmentation approach for MR images. We compare the performance of the resulting implementation in segmenting 20 test cases to a similar approach that uses a more standard shape model that is based on signed distance maps. On this data set, the Bayesian classification model with our new representation outperformed the other approaches in segmenting subcortical structures.
RATIONALE AND OBJECTIVES: We introduce a validation framework for the segmentation of brain tumors from magnetic resonance (MR) images. A novel unsupervised semiautomatic brain tumor segmentation algorithm is also presented.
MATERIALS AND METHODS: The proposed framework consists of 1) T1-weighted MR images of patients with brain tumors, 2) segmentation of brain tumors performed by four independent experts, 3) segmentation of brain tumors generated by a semiautomatic algorithm, and 4) a software tool that estimates the performance of segmentation algorithms.
RESULTS: We demonstrate the validation of the novel segmentation algorithm within the proposed framework. We show its performance and compare it with existent segmentation. The image datasets and software are available at http://www.brain-tumor-repository.org/.
CONCLUSIONS: We present an Internet resource that provides access to MR brain tumor image data and segmentation that can be openly used by the research community. Its purpose is to encourage the development and evaluation of segmentation methods by providing raw test and image data, human expert segmentation results, and methods for comparing segmentation results.
Patient-mounted needle guide devices for percutaneous ablation are vulnerable to patient motion. The objective of this study is to develop and evaluate a software system for an MRI-compatible patient-mounted needle guide device that can adaptively compensate for displacement of the device due to patient motion using a novel image-based automatic device-to-image registration technique. We have developed a software system for an MRI-compatible patient-mounted needle guide device for percutaneous ablation. It features fully-automated image-based device-to-image registration to track the device position, and a device controller to adjust the needle trajectory to compensate for the displacement of the device. We performed: (a) a phantom study using a clinical MR scanner to evaluate registration performance; (b) simulations using intraoperative time-series MR data acquired in 20 clinical cases of MRI-guided renal cryoablations to assess its impact on motion compensation; and (c) a pilot clinical study in three patients to test its feasibility during the clinical procedure. FRE, TRE, and success rate of device-to-image registration were [Formula: see text] mm, [Formula: see text] mm, and 98.3% for the phantom images. The simulation study showed that the motion compensation reduced the targeting error for needle placement from 8.2 mm to 5.4 mm (p < 0.0005) in patients under general anesthesia (GA), and from 14.4 mm to 10.0 mm ([Formula: see text]) in patients under monitored anesthesia care (MAC). The pilot study showed that the software registered the device successfully in a clinical setting. Our simulation study demonstrated that the software system could significantly improve targeting accuracy in patients treated under both MAC and GA. Intraprocedural image-based device-to-image registration was feasible.
PURPOSE: To develop and evaluate an approach to estimate the respiratory-induced motion of lesions in the chest and abdomen. MATERIALS AND METHODS: The proposed approach uses the motion of an initial reference needle inserted into a moving organ to estimate the lesion (target) displacement that is caused by respiration. The needles position is measured using an inertial measurement unit (IMU) sensor externally attached to the hub of an initially placed reference needle. Data obtained from the IMU sensor and the target motion are used to train a learning-based approach to estimate the position of the moving target. An experimental platform was designed to mimic respiratory motion of the liver. Liver motion profiles of human subjects provided inputs to the experimental platform. Variables including the insertion angle, target depth, target motion velocity and target proximity to the reference needle were evaluated by measuring the error of the estimated target position and processing time. RESULTS: The mean error of estimation of the target position ranged between 0.86 and 1.29 mm. The processing maximum training and testing time was 5 ms which is suitable for real-time target motion estimation using the needle position sensor. CONCLUSION: The external motion of an initially placed reference needle inserted into a moving organ can be used as a surrogate, measurable and accessible signal to estimate in real-time the position of a moving target caused by respiration; this technique could then be used to guide the placement of subsequently inserted needles directly into the target.
Brain shift during tumor resection compromises the spatial validity of registered preoperative imaging data that is critical to image-guided procedures. One current clinical solution to mitigate the effects is to reimage using intraoperative magnetic resonance (iMR) imaging. Although iMR has demonstrated benefits in accounting for preoperative-to-intraoperative tissue changes, its cost and encumbrance have limited its widespread adoption. While iMR will likely continue to be employed for challenging cases, a cost-effective model-based brain shift compensation strategy is desirable as a complementary technology for standard resections. We performed a retrospective study of [Formula: see text] tumor resection cases, comparing iMR measurements with intraoperative brain shift compensation predicted by our model-based strategy, driven by sparse intraoperative cortical surface data. For quantitative assessment, homologous subsurface targets near the tumors were selected on preoperative MR and iMR images. Once rigidly registered, intraoperative shift measurements were determined and subsequently compared to model-predicted counterparts as estimated by the brain shift correction framework. When considering moderate and high shift ([Formula: see text], [Formula: see text] measurements per case), the alignment error due to brain shift reduced from [Formula: see text] to [Formula: see text], representing [Formula: see text] correction. These first steps toward validation are promising for model-based strategies.
OBJECTIVE: The purpose of this article is to report our intermediate to long-term outcomes with image-guided percutaneous hepatic tumor cryoablation and to evaluate its technical success, technique efficacy, local tumor progression, and adverse event rate. MATERIALS AND METHODS: Between 1998 and 2014, 299 hepatic tumors (243 metastases and 56 primary tumors; mean diameter, 2.5 cm; median diameter, 2.2 cm; range, 0.3-7.8 cm) in 186 patients (95 women; mean age, 60.9 years; range, 29-88 years) underwent cryoablation during 236 procedures using CT (n = 126), MRI (n = 100), or PET/CT (n = 10) guidance. Technical success, technique efficacy at 3 months, local tumor progression (mean follow-up, 2.5 years; range, 2 months to 14.6 years), and adverse event rates were calculated. RESULTS: The technical success rate was 94.6% (279/295). The technique efficacy rate was 89.5% (231/258) and was greater for tumors smaller than 4 cm (93.4%; 213/228) than for larger tumors (60.0%; 18/30) (p < 0.0001). Local tumor progression occurred in 23.3% (60/258) of tumors and was significantly more common after the treatment of tumors 4 cm or larger (63.3%; 19/30) compared with smaller tumors (18.0%; 41/228) (p < 0.0001). Adverse events followed 33.8% (80/236) of procedures and were grade 3-5 in 10.6% (25/236) of cases. Grade 3 or greater adverse events more commonly followed the treatment of larger tumors (19.5%; 8/41) compared with smaller tumors (8.7%; 17/195) (p = 0.04). CONCLUSION: Image-guided percutaneous cryoablation of hepatic tumors is efficacious; however, tumors smaller than 4 cm are more likely to be treated successfully and without an adverse event.
OBJECTIVE: We report nine consecutive percutaneous image-guided cryoablation procedures of head and neck tumors in seven patients (four men and three women; mean age, 68 years; age range, 50-78 years). Ablation of the entire tumor for local control or ablation of a region of tumor for pain relief or preservation of function was achieved in eight of nine procedures. One patient experienced intraprocedural bradycardia, and another developed a neopharyngeal abscess. There were no deaths, permanent neurologic or functional deficits, vascular complications, or adverse cosmetic sequelae due to the procedures. CONCLUSION: Percutaneous image-guided cryoablation offers a potentially less morbid minimally invasive treatment option than salvage head and neck surgery. The complications that we encountered may be avoidable with increased experience. Further work is needed to continue improving the safety and efficacy of cryoablation of head and neck tumors and to continue expanding the use of cryoablation in patients with head and neck tumors that cannot be treated surgically.