Intra-operative virtual endoscopy for image guided endonasal transsphenoidal pituitary surgery.

PURPOSE: Virtual endoscopy has already proven its benefit for pre-operative planning of endoscopic pituitary surgery. The translation of such a system into the operating room is a logical consequence, but only a few general intra-operative image guided systems providing virtual endoscopic images have been proposed so far. A discussion of related visualization and interaction problems occurring during sinus and pituitary surgery is still missing. METHODS: This paper aims at filling this gap and proposes a system that integrates an existing virtual endoscopy system originally designed for pre-operative planning of pituitary surgery with a professional intra-operative navigation system. Visualization and interaction possibilities of the pre-operative planning system have been extended to fulfill the special requirements to the system if used for intra-operative navigation of endonasal transsphenoidal pituitary surgery. RESULTS: The feasibility of the system has been successfully tested on 1 cadaver and 12 patients. The virtual endoscopic images were found useful (1) during the endonasal transsphenoidal approach in cases of anatomic variations and for the individually tailored opening of the sellar floor, and (2) during tumor resection for respecting the internal carotid artery. The visualization of hidden anatomical structures behind the bony walls of the sphenoid sinus during the sellar phase of the surgery has been found most beneficial. DISCUSSION: According to our data, intra-operative virtual endoscopy provides additional anatomical information to the surgeon. By depicting individual anatomical variations in advance, it may add to the safety of this frequent neurosurgical procedure.

LiveSync: deformed viewing spheres for knowledge-based navigation.

Although real-time interactive volume rendering is available even for very large data sets, this visualization method is used quite rarely in the clinical practice. We suspect this is because it is very complicated and time consuming to adjust the parameters to achieve meaningful results. The clinician has to take care of the appropriate viewpoint, zooming, transfer function setup, clipping planes and other parameters. Because of this, most often only 2D slices of the data set are examined. Our work introduces LiveSync, a new concept to synchronize 2D slice views and volumetric views of medical data sets. Through intuitive picking actions on the slice, the users define the anatomical structures they are interested in. The 3D volumetric view is updated automatically with the goal that the users are provided with expressive result images. To achieve this live synchronization we use a minimal set of derived information without the need for segmented data sets or data-specific pre-computations. The components we consider are the picked point, slice view zoom, patient orientation, viewpoint history, local object shape and visibility. We introduce deformed viewing spheres which encode the viewpoint quality for the components. A combination of these deformed viewing spheres is used to estimate a good viewpoint. Our system provides the physician with synchronized views which help to gain deeper insight into the medical data with minimal user interaction.

Multipath curved planar reformation of the peripheral arterial tree in CT angiography.

The study was approved by the institutional review board, and informed consent was obtained. The purpose of the study was to prospectively quantify the angular visibility range, determine the existence of orthogonal viewing pairs, and characterize the conditions that cause artifacts in multipath curved planar reformations (MPCPRs) of the peripheral arterial tree in 10 patients (eight men and two women; mean age, 69 years; range, 54-80 years) with peripheral arterial occlusive disease. Percentage of segments with the maximal possible visibility score of 1 was significantly greater (odds ratio, 1.42; P<.001) for MPCPRs than for maximum intensity projections. One or more orthogonal viewing pairs were identified for all above-knee arterial segments, and artifactual vessel distortion was observed when the vessel axis approached a horizontal course in MPCPRs.

Automated CTA quantification of internal carotid artery stenosis: a pilot trial.

PURPOSE: To evaluate the feasibility and accuracy of automated analysis software for use with multidetector computed tomographic angiography (CTA) in the exact grading of internal carotid artery stenosis. METHODS: A retrospective pilot trial was performed using CTA datasets from 87 stenotic carotid arteries in 46 consecutive patients (34 men; median age 73.5 years) with known cerebrovascular disease. Internal carotid artery (ICA) stenosis was graded according to NASCET criteria by 2 experienced vascular radiologists in consensus using axial source images as well as curved planar reformations and digital subtraction angiography (DSA). These results were then compared to those obtained from the automated CTA analysis software and the results of manually adapted automated CTA analysis. RESULTS: Measurements from automated CTA analysis as well as manually adapted automated CTA analysis correlated significantly to those of axial/reformatted CTA and DSA (r=0.53 and r=0.82, r=0.58 and 0.70, respectively, all p<0.05). Compared to axial/reformatted CTA measurements, automated CTA analysis had a median difference of -16%, while manually adapted automated CTA had a difference of -10%. Corresponding differences in a comparison with DSA were +4% and -2%, respectively. Circumferential calcification or kinking of the ICA origin did not significantly interfere with these differences (all p>0.05). Sensitivities for the detection of ICA stenosis >70% by manually adapted automated CTA analysis and automated measurement were 44.2% and 34.9%, respectively, versus axial/reformatted CTA. Compared with DSA as the gold standard, the sensitivities were 54.2% and 62.5%, respectively. Specificities for both methods and gold standards all exceeded 90%. CONCLUSION: Commercially available automated CTA analysis is a feasible tool, but sensitivities are still not sufficient for clinical application.

Illustrative context-preserving exploration of volume data.

In volume rendering, it is very difficult to simultaneously visualize interior and exterior structures while preserving clear shape cues. Highly transparent transfer functions produce cluttered images with many overlapping structures, while clipping techniques completely remove possibly important context information. In this paper, we present a new model for volume rendering, inspired by from illustration. It provides a means of interactively inspecting the interior of a volumetric data set in a feature-driven way which retains context information. The context-preserving volume rendering model uses a function of shading intensity, gradient magnitude, distance to the eye point, and previously accumulated opacity to selectively reduce the opacity in less important data regions. It is controlled by two user-specified parameters. This new method represents an alternative to conventional clipping techniques, sharing their easy and intuitive user control, but does not suffer from the drawback of missing context information.

Importance-driven feature enhancement in volume visualization.

This paper presents importance-driven feature enhancement as a technique for the automatic generation of cut-away and ghosted views out of volumetric data. The presented focus+context approach removes or suppresses less important parts of a scene to reveal more important underlying information. However, less important parts are fully visible in those regions, where important visual information is not lost, i.e., more relevant features are not occluded. Features within the volumetric data are first classified according to a new dimension, denoted as object importance. This property determines which structures should be readily discernible and which structures are less important. Next, for each feature, various representations (levels of sparseness) from a dense to a sparse depiction are defined. Levels of sparseness define a spectrum of optical properties or rendering styles. The resulting image is generated by ray-casting and combining the intersected features proportional to their importance (importance compositing). The paper includes an extended discussion on several possible schemes for levels of sparseness specification. Furthermore, different approaches to importance compositing are treated.