An anthropomorphic polyvinyl alcohol brain phantom based on Colin27 for use in multimodal imaging.

PURPOSE: In this paper, the method for the creation of an anatomically and mechanically realistic brain phantom from polyvinyl alcohol cryogel (PVA-C) is proposed for validation of image processing methods such as segmentation, reconstruction, registration, and denoising. PVA-C is material widely used in medical imaging phantoms because of its mechanical similarities to soft tissues. METHODS: The phantom was cast in a mold designed using the left hemisphere of the Colin27 brain dataset [C. Holmes et al., "Enhancement of MR images using registration for signal averaging," J. Comput. Assist. Tomogr. 22(2), 324 (1998)]. Marker spheres and inflatable catheters were also implanted to enable good registration comparisons and to simulate tissue deformation, respectively. RESULTS: The phantom contained deep sulci, a complete insular region, and an anatomically accurate left ventricle. It was found to provide good contrast in triple modality imaging, consisting of computed tomography, ultrasound, and magnetic resonance imaging. Multiple sets of multimodal data were acquired from this phantom. CONCLUSIONS: The methods for building the anatomically accurate, multimodality phantom were described in this work. All multimodal data are made available freely to the image processing community (http://pvabrain.inria.fr). We believe the phantom images could allow for the validation and further aid in the development of novel medical image processing techniques.

Impact of Simulation Training on Radiology Resident Performance in Neonatal Head Ultrasound.

RATIONALE AND OBJECTIVES: The aim of this study was to determine whether resident performance in head ultrasound on neonates improves following brain phantom simulation training. MATERIALS AND METHODS: Ten junior radiology residents with at least one year of radiology training were divided into two equal groups. Both groups received a detailed head ultrasound protocol sheet and observed a technologist perform a head ultrasound on a neonatal patient at the beginning of their first pediatric radiology rotation. Both groups of residents also received teaching with a brain phantom model. Group A residents independently performed one head ultrasound exam, subsequently received phantom simulation training, and then performed a post-training head ultrasound exam. Group B residents received phantom simulation training prior to their first head ultrasound exam. Three pediatric radiologists independently and blindly reviewed the ultrasound images of each head ultrasound exam for proficiency of image acquisition using a validated scoring system. Scores of Group A residents prior to phantom training were compared to their scores after phantom training as well as to scores of Group B residents using simple linear regression. RESULTS: There was a statistically significant improvement in the performance of head ultrasound on neonates when comparing the same residents pre- and postphantom training (p = 0.003). Residents who initially trained with the phantom performed significantly better on their first head ultrasound examination on a neonate than those residents who did not (p = 0.005). CONCLUSION: Our novel head ultrasound phantom training model significantly improves radiology resident performance of head ultrasound on neonates and may, therefore, be beneficial for residency education.

Automatic deformable MR-ultrasound registration for image-guided neurosurgery.

In this work, we present a novel algorithm for registration of 3-D volumetric ultrasound (US) and MR using Robust PaTch-based cOrrelation Ratio (RaPTOR). RaPTOR computes local correlation ratio (CR) values on small patches and adds the CR values to form a global cost function. It is therefore invariant to large amounts of spatial intensity inhomogeneity. We also propose a novel outlier suppression technique based on the orientations of the RaPTOR gradients. Our deformation is modeled with free-form cubic B-splines. We analytically derive the derivatives of RaPTOR with respect to the transformation, i.e., the displacement of the B-spline nodes, and optimize RaPTOR using a stochastic gradient descent approach. RaPTOR is validated on MR and tracked US images of neurosurgery. Deformable registration of the US and MR images acquired, respectively, preoperation and postresection is of significant clinical significance, but challenging due to, among others, the large amount of missing correspondences between the two images. This work is also novel in that it performs automatic registration of this challenging dataset. To validate the results, we manually locate corresponding anatomical landmarks in the US and MR images of tumor resection in brain surgery. Compared to rigid registration based on the tracking system alone, RaPTOR reduces the mean initial mTRE over 13 patients from 5.9 to 2.9 mm, and the maximum initial TRE from 17.0 to 5.9 mm. Each volumetric registration using RaPTOR takes about 30 sec on a single CPU core. An important challenge in the field of medical image analysis is the shortage of publicly available dataset, which can both facilitate the advancement of new algorithms to clinical settings and provide a benchmark for comparison. To address this problem, we will make our manually located landmarks available online.

An evaluation of depth enhancing perceptual cues for vascular volume visualization in neurosurgery.

Cerebral vascular images obtained through angiography are used by neurosurgeons for diagnosis, surgical planning, and intraoperative guidance. The intricate branching of the vessels and furcations, however, make the task of understanding the spatial three-dimensional layout of these images challenging. In this paper, we present empirical studies on the effect of different perceptual cues (fog, pseudo-chromadepth, kinetic depth, and depicting edges) both individually and in combination on the depth perception of cerebral vascular volumes and compare these to the cue of stereopsis. Two experiments with novices and one experiment with experts were performed. The results with novices showed that the pseudo-chromadepth and fog cues were stronger cues than that of stereopsis. Furthermore, the addition of the stereopsis cue to the other cues did not improve relative depth perception in cerebral vascular volumes. In contrast to novices, the experts also performed well with the edge cue. In terms of both novice and expert subjects, pseudo-chromadepth and fog allow for the best relative depth perception. By using such cues to improve depth perception of cerebral vasculature, we may improve diagnosis, surgical planning, and intraoperative guidance.

Validation of a hybrid Doppler ultrasound vessel-based registration algorithm for neurosurgery.

PURPOSE: We describe and validate a novel hybrid nonlinear vessel registration algorithm for intra-operative updating of preoperative magnetic resonance (MR) images using Doppler ultrasound (US) images acquired on the dura for the correction of brain-shift and registration inaccuracies. We also introduce an US vessel appearance simulator that generates vessel images similar in appearance to that acquired with US from MR angiography data. METHODS: Our registration uses the minimum amount of preprocessing to extract vessels from the raw volumetric images. This prevents the removal of important registration information and minimizes the introduction of artifacts that may affect robustness, while reducing the amount of extraneous information in the image to be processed, thus improving the convergence speed of the algorithm. We then completed 3 rounds of validation for our vessel registration method for robustness and accuracy using (i) a large number of synthetic trials generated with our US vessel simulator, (ii) US images acquired from a real physical phantom made from polyvinyl alcohol cryogel, and (iii) real clinical data gathered intra-operatively from 3 patients. RESULTS: Resulting target registration errors (TRE) of less than 2.5 mm are achieved in more than 90 % of the synthetic trials when the initial TREs are less than 20 mm. TREs of less than 2 mm were achieved when the technique was applied to the physical phantom, and TREs of less than 3 mm were achieved on clinical data. CONCLUSIONS: These test trials show that the proposed algorithm is not only accurate but also highly robust to noise and missing vessel segments when working with US images acquired in a wide range of real-world conditions.

Validation of automated ultrasound-CT registration of vertebrae.

PURPOSE: Image-guided spine surgery requires registration of the patient anatomy and preoperative computed tomography (CT) images. A technique for intraoperative ultrasound image registration to preoperative CT scans was developed and tested. Validation of the ultrasound-CT registration technique was performed using porcine cadavers. METHODS: An ultrasound-CT registration technique was evaluated using 18 thoracic and lumbar vertebrae of 3 porcine cadavers with 10 different sweep patterns for ultrasound acquisition. For each sweep pattern at each vertebra, 100 randomly simulated initial misalignments were introduced. Each misalignment was registered. The resulting registration transformations were compared to gold standard registrations based on implanted fiducials to assess accuracy and robustness of the technique. RESULTS: The orthogonal-sweep acquisition was found to perform best and yielded a registration accuracy of 1.65 mm across all vertebrae on all porcine cadavers, where 82.5% of the registrations resulted in target registration errors below the 2 mm threshold recommended by a joint report from the experts in the field. In addition, we found that registration accuracy varies by the sweep pattern and vertebral level, but neighboring vertebrae tend to result in statistically similar accuracy. Ultrasound-CT registration took an average of 2.5 min to run, and the total registration time per vertebra (also including time for ultrasound acquisition and reconstruction) is approximately 8 min. CONCLUSIONS: A previously described ultrasound-CT registration technique yields clinically acceptable accuracy and robustness on multiple vertebrae across multiple porcine cadavers. The total registration time is shorter than that of surface point-based manual registration.

Towards accurate, robust and practical ultrasound-CT registration of vertebrae for image-guided spine surgery.

PURPOSE: Accurate registration of patient anatomy and preoperative computed tomography (CT) images is key to successful image-guided spine surgery. Current manual landmark and surface-based techniques are time-consuming and not always accurate. Intraoperative ultrasound imaging of the vertebrae, combined with automated registration, could improve surgery by improving accuracy, reducing operative time, and decreasing invasiveness. METHODS: We present a simple ultrasound-CT registration technique that is automated, accurate, and robust. Registration is achieved by aligning the posterior vertebral surface, extracted from both CT and ultrasound images, using a forward and a backward scan line tracing method, respectively. The registration technique is validated using a simple plastic phantom in a water bath and a more realistic porcine cadaver in a simulation of open back surgery. RESULTS: Clinically relevant accuracy was estimated by comparing automated registrations with gold standard imaging fiducial-based reference transformations, which yielded target registration errors of under 1 mm for the plastic phantom and under 1.6 mm for the porcine cadaver. CONCLUSIONS: Our registration technique demonstrates good accuracy and robustness under clinically realistic conditions and thus warrants further studies on its surgical application.

New prototype neuronavigation system based on preoperative imaging and intraoperative freehand ultrasound: system description and validation.

PURPOSE: The aim of this report is to present IBIS (Interactive Brain Imaging System) NeuroNav, a new prototype neuronavigation system that has been developed in our research laboratory over the past decade that uses tracked intraoperative ultrasound to address surgical navigation issues related to brain shift. The unique feature of the system is its ability, when needed, to improve the initial patient-to-preoperative image alignment based on the intraoperative ultrasound data. Parts of IBIS Neuronav source code are now publicly available on-line. METHODS: Four aspects of the system are characterized in this paper: the ultrasound probe calibration, the temporal calibration, the patient-to-image registration and the MRI-ultrasound registration. In order to characterize its real clinical precision and accuracy, the system was tested in a series of adult brain tumor cases. RESULTS: Three metrics were computed to evaluate the precision and accuracy of the ultrasound calibration. 1) Reproducibility: 1.77 mm and 1.65 mm for the bottom corners of the ultrasound image, 2) point reconstruction precision 0.62-0.90 mm: and 3) point reconstruction accuracy: 0.49-0.74 mm. The temporal calibration error was estimated to be 0.82 ms. The mean fiducial registration error (FRE) of the homologous-point-based patient-to-MRI registration for our clinical data is 4.9 ± 1.1 mm. After the skin landmark-based registration, the mean misalignment between the ultrasound and MR images in the tumor region is 6.1 ± 3.4 mm. CONCLUSIONS: The components and functionality of a new prototype system are described and its precision and accuracy evaluated. It was found to have an accuracy similar to other comparable systems in the literature.

An anthropomorphic polyvinyl alcohol triple-modality brain phantom based on Colin27.

We propose a method for the creation of an anatomically and mechanically realistic brain phantom from polyvinyl alcohol cryogel (PVA-C) for validation of image processing methods for segmentation, reconstruction, registration, and denoising. PVA-C is material widely used in medical imaging phantoms for its mechanical similarities to soft tissues. The phantom was cast in a mold designed using the left hemiphere of the Colin27 brain dataset and contains deep sulci, a complete insular region, and an anatomically accurate left ventricle. Marker spheres and inflatable catheters were also implanted to enable good registration and simulate tissue deformation, respectively. The phantom was designed for triple modality imaging, giving good contrast images in computed tomography, ultrasound, and magnetic resonance imaging. Multimodal data acquired from this phantom are made freely available to the image processing community (http://pvabrain. inria.fr) and will aid in the validation and further development of medical image processing techniques.