PURPOSE: We propose two software tools for non-rigid registration of MRI and transrectal ultrasound (TRUS) images of the prostate. Our ultimate goal is to develop an open-source solution to support MRI-TRUS fusion image guidance of prostate interventions, such as targeted biopsy for prostate cancer detection and focal therapy. It is widely hypothesized that image registration is an essential component in such systems. METHODS: The two non-rigid registration methods are: (1) a deformable registration of the prostate segmentation distance maps with B-spline regularization and (2) a finite element-based deformable registration of the segmentation surfaces in the presence of partial data. We evaluate the methods retrospectively using clinical patient image data collected during standard clinical procedures. Computation time and Target Registration Error (TRE) calculated at the expert-identified anatomical landmarks were used as quantitative measures for the evaluation. RESULTS: The presented image registration tools were capable of completing deformable registration computation within 5 min. Average TRE was approximately 3 mm for both methods, which is comparable with the slice thickness in our MRI data. Both tools are available under nonrestrictive open-source license. CONCLUSIONS: We release open-source tools that may be used for registration during MRI-TRUS-guided prostate interventions. Our tools implement novel registration approaches and produce acceptable registration results. We believe these tools will lower the barriers in development and deployment of interventional research solutions and facilitate comparison with similar tools.
Whole-body computed tomography (CT) image registration is important for cancer diagnosis, therapy planning and treatment. Such registration requires accounting for large differences between source and target images caused by deformations of soft organs/tissues and articulated motion of skeletal structures. The registration algorithms relying solely on image processing methods exhibit deficiencies in accounting for such deformations and motion. We propose to predict the deformations and movements of body organs/tissues and skeletal structures for whole-body CT image registration using patient-specific non-linear biomechanical modelling. Unlike the conventional biomechanical modelling, our approach for building the biomechanical models does not require time-consuming segmentation of CT scans to divide the whole body into non-overlapping constituents with different material properties. Instead, a Fuzzy C-Means (FCM) algorithm is used for tissue classification to assign the constitutive properties automatically at integration points of the computation grid. We use only very simple segmentation of the spine when determining vertebrae displacements to define loading for biomechanical models. We demonstrate the feasibility and accuracy of our approach on CT images of seven patients suffering from cancer and aortic disease. The results confirm that accurate whole-body CT image registration can be achieved using a patient-specific non-linear biomechanical model constructed without time-consuming segmentation of the whole-body images.
OBJECTIVES: This study was conducted to validate the accuracy of image-based pre-operative segmentation using the gold standard endoscopic and microscopic findings for localization and pre-operative diagnosis of the offensive vessel. PATIENTS AND METHODS: Fourteen TN and 6 HS cases were randomly selected. All patients had 3T MRI, which included thin-sectioned 3D space T2, 3D Time of Flight and MPRAGE Sequences. Imaging sequences were loaded in BrainLab iPlanNet and fused. Individual segmentation of the affected cranial nerves and the compressing vascular structure was performed by a neurosurgeon, and the results were compared with the microscopic and endoscopic findings by two blinded neurosurgeons. For each case, at least three neurovascular landmarks were targeted. Each segmented neurovascular element was validated by manual placement of the navigation probe over each target, and errors of localization were measured in mm. RESULTS: All patients underwent retro-sigmoid craniotomy and MVD using both microscope and endoscope. Based on image segmentation, the compressing vessel was identified in all cases except one, which was also negative intraoperatively. Perfect correspondence was found between image-based segmentation and endoscopic and microscopic images and videos (Dice coefficient of 1). Measurement accuracy was 0.45±0.21mm (mean±SD). CONCLUSION: Image-based segmentation is a promising method for pre-operative identification and localization of offending blood vessels causing HFS and TN. Using this method may prevent some unnecessary explorations on especially atypical cases with no vascular contacts. However, negative pre-operative image segmentation may not preclude one from exploration in classic cases of TN or HFS. A multicenter study with larger number of cases is recommended.
OBJECTIVES: To evaluate the performance of T2 mapping in discriminating prostate cancer from normal prostate tissue in the peripheral zone using a practical reduced field-of-view MRI sequence requiring less than 3 minutes of scan time. MATERIALS AND METHODS: Thirty-six patients with biopsy-proven peripheral zone prostate cancer without prior treatment underwent routine multiparametric MRI at 3.0T with an endorectal coil. An Inner-Volume Carr-Purcell-Meiboom-Gill imaging sequence that required 2.8 minutes to obtain data for quantitative T2 mapping covering the entire prostate gland was added to the routine multiparametric protocol. Suspected cancer (SC) and suspected healthy (SH) tissue in the peripheral zone were identified in consensus by three radiologists and were correlated with available biopsy results. Differences in mean T2 values in SC and SH regions-of-interest (ROIs) were tested for significance using unpaired Student's two-tailed t-test. The area under the receiver operating characteristic curve was used to assess the optimal threshold T2 value for cancer discrimination. RESULTS: ROI analyses revealed significantly (p<0.0001) shorter T2 values in SC (85.4±12.3ms) compared to SH (169.6±38.7ms). An estimated T2 threshold of 99ms yielded a sensitivity of 92% and a specificity of 97% for prostate cancer discrimination. CONCLUSIONS: Quantitative values derived from this clinically practical T2-mapping sequence allow high precision discrimination between healthy and cancerous peripheral zone in the prostate.
Accurate pharmacokinetic (PK) modeling of dynamic contrast enhanced MRI (DCE-MRI) in prostate cancer (PCa) requires knowledge of the concentration time course of the contrast agent in the feeding vasculature, the so-called arterial input function (AIF). The purpose of this study was to compare AIF choice in differentiating peripheral zone PCa from non-neoplastic prostatic tissue (NNPT), using PK analysis of high temporal resolution prostate DCE-MRI data and whole-mount pathology (WMP) validation. This prospective study was performed in 30 patients who underwent multiparametric endorectal prostate MRI at 3.0T and WMP validation. PCa foci were annotated on WMP slides and MR images using 3D Slicer. Foci ≥0.5cm(3) were contoured as tumor regions of interest (TROIs) on subtraction DCE (early-arterial - pre-contrast) images. PK analyses of TROI and NNPT data were performed using automatic AIF (aAIF) and model AIF (mAIF) methods. A paired t-test compared mean and 90th percentile (p90) PK parameters obtained with the two AIF approaches. Receiver operating characteristic (ROC) analysis determined diagnostic accuracy (DA) of PK parameters. Logistic regression determined correlation between PK parameters and histopathology. Mean TROI and NNPT PK parameters were higher using aAIF vs. mAIF (p<0.05). There was no significant difference in DA between AIF methods: highest for p90 volume transfer constant (K(trans)) (aAIF differences in the area under the ROC curve (Az) = 0.827; mAIF Az=0.93). Tumor cell density correlated with aAIF K(trans) (p=0.03). Our results indicate that DCE-MRI using both AIF methods is excellent in discriminating PCa from NNPT. If quantitative DCE-MRI is to be used as a biomarker in PCa, the same AIF method should be used consistently throughout the study.
There is increasing evidence that iron deposition occurs in specific regions of the brain in normal aging and neurodegenerative disorders such as Parkinson's, Huntington's, and Alzheimer's disease. Iron deposition changes the magnetic susceptibility of tissue, which alters the MR signal phase, and allows estimation of susceptibility differences using quantitative susceptibility mapping (QSM). We present a method for quantifying susceptibility by inversion of a perturbation model, or "QSIP." The perturbation model relates phase to susceptibility using a kernel calculated in the spatial domain, in contrast to previous Fourier-based techniques. A tissue/air susceptibility atlas is used to estimate B0 inhomogeneity. QSIP estimates in young and elderly subjects are compared to postmortem iron estimates, maps of the Field-Dependent Relaxation Rate Increase, and the L1-QSM method. Results for both groups showed excellent agreement with published postmortem data and in vivo FDRI: statistically significant Spearman correlations ranging from Rho=0.905 to Rho=1.00 were obtained. QSIP also showed improvement over FDRI and L1-QSM: reduced variance in susceptibility estimates and statistically significant group differences were detected in striatal and brainstem nuclei, consistent with age-dependent iron accumulation in these regions.
PURPOSE: To develop an active MR-tracking system to guide placement of metallic devices for radiation therapy. METHODS: An actively tracked metallic stylet for brachytherapy was constructed by adding printed-circuit micro-coils to a commercial stylet. The coil design was optimized by electromagnetic simulation, and has a radio-frequency lobe pattern extending ∼5 mm beyond the strong B0 inhomogeneity region near the metal surface. An MR-tracking sequence with phase-field dithering was used to overcome residual effects of B0 and B1 inhomogeneities caused by the metal, as well as from inductive coupling to surrounding metallic stylets. The tracking system was integrated with a graphical workstation for real-time visualization. The 3 Tesla MRI catheter-insertion procedures were tested in phantoms and ex vivo animal tissue, and then performed in three patients during interstitial brachytherapy. RESULTS: The tracking system provided high-resolution (0.6 × 0.6 × 0.6 mm(3) ) and rapid (16 to 40 frames per second, with three to one phase-field dithering directions) catheter localization in phantoms, animals, and three gynecologic cancer patients. CONCLUSION: This is the first demonstration of active tracking of the shaft of metallic stylet in MR-guided brachytherapy. It holds the promise of assisting physicians to achieve better targeting and improving outcomes in interstitial brachytherapy.
BACKGROUND: Diffusion imaging tractography is increasingly used to trace critical fiber tracts in brain tumor patients to reduce the risk of post-operative neurological deficit. However, the effects of peritumoral edema pose a challenge to conventional tractography using the standard diffusion tensor model. The aim of this study was to present a novel technique using a two-tensor unscented Kalman filter (UKF) algorithm to track the arcuate fasciculus (AF) in brain tumor patients with peritumoral edema. METHODS: Ten right-handed patients with left-sided brain tumors in the vicinity of language-related cortex and evidence of significant peritumoral edema were retrospectively selected for the study. All patients underwent 3-Tesla magnetic resonance imaging (MRI) including a diffusion-weighted dataset with 31 directions. Fiber tractography was performed using both single-tensor streamline and two-tensor UKF tractography. A two-regions-of-interest approach was applied to perform the delineation of the AF. Results from the two different tractography algorithms were compared visually and quantitatively. RESULTS: Using single-tensor streamline tractography, the AF appeared disrupted in four patients and contained few fibers in the remaining six patients. Two-tensor UKF tractography delineated an AF that traversed edematous brain areas in all patients. The volume of the AF was significantly larger on two-tensor UKF than on single-tensor streamline tractography (p < 0.01). CONCLUSIONS: Two-tensor UKF tractography provides the ability to trace a larger volume AF than single-tensor streamline tractography in the setting of peritumoral edema in brain tumor patients.
RATIONALE AND OBJECTIVES: Development of imaging biomarkers often relies on their correlation with histopathology. Our aim was to compare two approaches for correlating pathology to multiparametric magnetic resonance (MR) imaging (mpMRI) for localization and quantitative assessment of prostate cancer (PCa) index tumor using whole mount (WM) pathology (WMP) as the reference. MATERIALS AND METHODS: Patients (N = 30) underwent mpMRI that included diffusion-weighted imaging and dynamic contrast-enhanced (DCE) MRI at 3 T before radical prostatectomy (RP). RP specimens were processed using WM technique (WMP) and findings summarized in a standard surgical pathology report (SPR). Histology index tumor volumes (HTVs) were compared to MR tumor volumes (MRTVs) using two approaches for index lesion identification on mpMRI using annotated WMP slides as the reference (WMP) and using routine SPR as the reference. Consistency of index tumor localization, tumor volume, and mean values of the derived quantitative parameters (mean apparent diffusion coefficient [ADC], K(trans), and ve) were compared. RESULTS: Index lesions from 16 of 30 patients met the selection criteria. There was WMP/SRP agreement in index tumor in 13 of 16 patients. ADC-based MRTVs were larger (P < .05) than DCE-based MRTVs. ADC MRTVs were smaller than HTV (P < .005). There was a strong correlation between HTV and MRTV (Pearson ρ > 0.8; P < .05). No significant differences were observed in the mean values of K(trans) and ADC between the WMP and SPR. CONCLUSIONS: WMP correlation is superior to SPR for accurate localization of all index lesions. The use of WMP is however not required to distinguish significant differences of mean values of quantitative MRI parameters within tumor volume.
BACKGROUND: Placement accuracy of ventriculostomy catheters is reported in a wide and variable range. Development of an efficient image-guidance system may improve physician performance and patient safety. OBJECTIVE: We evaluate the prototype of Smart Stylet, a new electromagnetic image-guidance system for use during bedside ventriculostomy. METHODS: Accuracy of the Smart Stylet system was assessed. System operators were evaluated for their ability to successfully target the ipsilateral frontal horn in a phantom model. RESULTS: Target registration error across 15 intracranial targets ranged from 1.3 to 4.6 mm (mean 3.1 mm). Using Smart Stylet guidance, a test operator successfully passed a ventriculostomy catheter to a shifted ipsilateral frontal horn 20/20 (100%) times from the frontal approach in a skull phantom. Without Smart Stylet guidance, the operator was successful 4/10 (40%) times from the right frontal approach and 6/10 (60%) times from the left frontal approach. In a separate experiment, resident operators were successful 2/4 (50%) times when targeting the shifted ipsilateral frontal horn with Smart Stylet guidance and 0/4 (0%) times without image guidance using a skull phantom. CONCLUSIONS: Smart Stylet may improve the ability to successfully target the ventricles during frontal ventriculostomy.
In this paper, we present a tendon-driven continuum robot for endoscopic surgery. The robot has two sections for articulation actuated by tendon wires. By actuating the two sections independently, the robot can generate a variety of tip positions while maintaining the tip direction. This feature offers more flexibility in positioning the tip for large viewing angles of up to 180 degrees than does a conventional endoscope. To accurately estimate the tip position at large viewing angles, we employed kinematic mapping with a tension propagation model including friction between the tendon wires and the robot body. In a simulation study using this kinematic-mapping, the two-section robot at a target scale (outer diameter 1.7 mm and length 60 mm) produced a variety of tip positions within 50-mm ranges at the 180°-angle view. In the experimental validation, a 10:1 scale prototype performed three salient postures with different tip positions at the 180°-angle view. The proposed forward kinematic mapping (FKM) predicted the tip position within a tip-to-tip error of 6 mm over the 208-mm articulating length. The tip-to-tip error by FKM was significantly less than the one by conventional piecewise-constant-curvature approximation (PCCA) (FKM: 5.9 ± 2.9 mm vs. PCCA: 23.7 ± 3.6 mm, n=15, P < 0.01).
To enhance neuro-navigation, high quality pre-operative images must be registered onto intra-operative configuration of the brain. Therefore evaluation of the degree to which structures may remain misaligned after registration is critically important. We consider two Hausdorff Distance (HD)-based evaluation approaches: the edge-based HD (EBHD) metric and the Robust HD (RHD) metric as well as various commonly used intensity-based similarity metrics such as Mutual Information (MI), Normalised Mutual Information (NMI), Entropy Correlation Coefficient (ECC), Kullback-Leibler Distance (KLD) and Correlation Ratio (CR). We conducted the evaluation by applying known deformations to simple sample images and real cases of brain shift. We conclude that the intensity-based similarity metrics such as MI, NMI, ECC, KLD and CR do not correlate well with actual alignment errors, and hence are not useful for assessing misalignment. On the contrary, the EBHD and the RHD metrics correlated well with actual alignment errors; however, they have been found to underestimate the actual misalignment. We also note that it is beneficial to present HD results as a percentile-HD curve rather than a single number such as the 95-percentile HD. Percentile-HD curves present the full range of alignment errors and also facilitate the comparison of results obtained using different approaches. Furthermore, the qualities that should be possessed by an ideal evaluation metric were highlighted. Future studies could focus on developing such an evaluation metric.
The interaction of ultrasonically-controlled microbubble oscillations with tissues and biological media has been shown to induce a wide range of bioeffects that may have significant impact on therapy and diagnosis of brain diseases and disorders. However, the inherently non-linear microbubble oscillations combined with the micrometer and microsecond scales involved in these interactions and the limited methods to assess and visualize them transcranially hinder both their optimal use and translation to the clinics. To overcome these challenges, we present a framework that combines numerical simulations with multimodality imaging to assess and visualize the microbubble oscillations transcranially. In the present work, microbubble oscillations were studied with an integrated US and MR imaging guided clinical FUS system. A high-resolution brain CT scan was also co-registered to the US and MR images and the derived acoustic properties were used as inputs to two- and three-dimensional Finite Difference Time Domain simulations that matched the experimental conditions and geometry. Synthetic point sources by either a Gaussian function or the output of a microbubble dynamics model were numerically excited and propagated through the skull towards a virtual US imaging array. Using passive acoustic mapping (PAM) that was refined to incorporate variable speed of sound, we were able to correct the aberrations introduced by the skull and substantially improve the PAM resolution. The good agreement between the simulations incorporating microbubble emissions and experimentally-determined PAMs suggest that this integrated approach can provide a clinically-relevant framework and more control over this nonlinear and dynamic process.
PURPOSE: To determine the detection rate, clinical relevance, Gleason grade, and location of prostate cancer ( PCa prostate cancer ) diagnosed with and the safety of an in-bore transperineal 3-T magnetic resonance (MR) imaging-guided prostate biopsy in a clinically heterogeneous patient population. MATERIALS AND METHODS: This prospective retrospectively analyzed study was HIPAA compliant and institutional review board approved, and informed consent was obtained. Eighty-seven men (mean age, 66.2 years ± 6.9) underwent multiparametric endorectal prostate MR imaging at 3 T and transperineal MR imaging-guided biopsy. Three subgroups of patients with at least one lesion suspicious for cancer were included: men with no prior PCa prostate cancer diagnosis, men with PCa prostate cancer who were undergoing active surveillance, and men with treated PCa prostate cancer and suspected recurrence. Exclusion criteria were prior prostatectomy and/or contraindication to 3-T MR imaging. The transperineal MR imaging-guided biopsy was performed in a 70-cm wide-bore 3-T device. Overall patient biopsy outcomes, cancer detection rates, Gleason grade, and location for each subgroup were evaluated and statistically compared by using χ(2) and one-way analysis of variance followed by Tukey honestly significant difference post hoc comparisons. RESULTS: Ninety biopsy procedures were performed with no serious adverse events, with a mean of 3.7 targets sampled per gland. Cancer was detected in 51 (56.7%) men: 48.1% (25 of 52) with no prior PCa prostate cancer , 61.5% (eight of 13) under active surveillance, and 72.0% (18 of 25) in whom recurrence was suspected. Gleason pattern 4 or higher was diagnosed in 78.1% (25 of 32) in the no prior PCa prostate cancer and active surveillance groups. Gleason scores were not assigned in the suspected recurrence group. MR targets located in the anterior prostate had the highest cancer yield (40 of 64, 62.5%) compared with those for the other parts of the prostate (P < .001). CONCLUSION: In-bore 3-T transperineal MR imaging-guided biopsy, with a mean of 3.7 targets per gland, allowed detection of many clinically relevant cancers, many of which were located anteriorly.
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.