Visualization modes for CT colonography using cylindrical and planar map projections

An AI-Based Colonic Polyp Classifier for Colorectal Cancer Screening Using Low-Dose Abdominal CT

Among the non-invasive Colorectal cancer (CRC) screening approaches, Computed Tomography Colonography (CTC) and Virtual Colonoscopy (VC), are much more accurate. This work proposes an AI-based polyp detection framework for virtual colonoscopy (VC). Two main steps are addressed in this work: automatic segmentation to isolate the colon region from its background, and automatic polyp detection. Moreover, we evaluate the performance of the proposed framework on low-dose Computed Tomography (CT) scans. We build on our visualization approach, Fly-In (FI), which provides "filet"-like projections of the internal surface of the colon. The performance of the Fly-In approach confirms its ability with helping gastroenterologists, and it holds a great promise for combating CRC. In this work, these 2D projections of FI are fused with the 3D colon representation to generate new synthetic images. The synthetic images are used to train a RetinaNet model to detect polyps. The trained model has a 94% f1-score and 97% sensitivity. Furthermore, we study the effect of dose variation in CT scans on the performance of the the FI approach in polyp visualization. A simulation platform is developed for CTC visualization using FI, for regular CTC and low-dose CTC. This is accomplished using a novel AI restoration algorithm that enhances the Low-Dose CT images so that a 3D colon can be successfully reconstructed and visualized using the FI approach. Three senior board-certified radiologists evaluated the framework for the peak voltages of 30 KV, and the average relative sensitivities of the platform were 92%, whereas the 60 KV peak voltage produced average relative sensitivities of 99.5%.

LMap: Shape-Preserving Local Mappings for Biomedical Visualization

Visualization of medical organs and biological structures is a challenging task because of their complex geometry and the resultant occlusions. Global spherical and planar mapping techniques simplify the complex geometry and resolve the occlusions to aid in visualization. However, while resolving the occlusions these techniques do not preserve the geometric context, making them less suitable for mission-critical biomedical visualization tasks. In this paper, we present a shape-preserving local mapping technique for resolving occlusions locally while preserving the overall geometric context. More specifically, we present a novel visualization algorithm, LMap, for conformally parameterizing and deforming a selected local region-of-interest (ROI) on an arbitrary surface. The resultant shape-preserving local mappings help to visualize complex surfaces while preserving the overall geometric context. The algorithm is based on the robust and efficient extrinsic Ricci flow technique, and uses the dynamic Ricci flow algorithm to guarantee the existence of a local map for a selected ROI on an arbitrary surface. We show the effectiveness and efficacy of our method in three challenging use cases: (1) multimodal brain visualization, (2) optimal coverage of virtual colonoscopy centerline flythrough, and (3) molecular surface visualization.

ADR--Anatomy-Driven Reformation

Dedicated visualization methods are among the most important tools of modern computer-aided medical applications. Reformation methods such as Multiplanar Reformation or Curved Planar Reformation have evolved as useful tools that facilitate diagnostic and therapeutic work. In this paper, we present a novel approach that can be seen as a generalization of Multiplanar Reformation to curved surfaces. The main concept is to generate reformatted medical volumes driven by the individual anatomical geometry of a specific patient. This process generates flat views of anatomical structures that facilitate many tasks such as diagnosis, navigation and annotation. Our reformation framework is based on a non-linear as-rigid-as-possible volumetric deformation scheme that uses generic triangular surface meshes as input. To manage inevitable distortions during reformation, we introduce importance maps which allow controlling the error distribution and improving the overall visual quality in areas of elevated interest. Our method seamlessly integrates with well-established concepts such as the slice-based inspection of medical datasets and we believe it can improve the overall efficiency of many medical workflows. To demonstrate this, we additionally present an integrated visualization system and discuss several use cases that substantiate its benefits.

Virtual colon flattening method based on colonic outer surface

Virtual colon flattening (VF) is a minimally invasive viewing mode used to detect colorectal polyps on the colonic inner surface in virtual colonoscopy. Compared with conventional colonoscopy, inspecting a flattened colonic inner surface is faster and results in fewer uninspected regions. Unfortunately, the deformation distortions of flattened colonic inner surface impede the performance of VF. Conventionally, the deformation distortions can be corrected by using the colonic inner surface. However, colonic curvatures and haustral folds make correcting deformation distortions using only the colonic inner surface difficult. Therefore, we propose a VF method that is based on the colonic outer surface. The proposed method includes two novel algorithms, namely, the colonic outer surface extraction algorithm and the colonic outer surface-based distortion correction algorithm. Sixty scans involving 77 annotated polyps were used for the validation. The flattened colons were independently inspected by three operators and then compared with three existing VF methods. The correct detection rates of the proposed method and the three existing methods were 79.6%, 67.1%, 71.9%, and 72.7%, respectively, and the false positives per scan were 0.16, 0.32, 0.21, and 0.26, respectively. The experimental results demonstrate that our proposed method has better performance than existing methods that are based on the colonic inner surface.

A Novel Colon Wall Flattening Model for Computed Tomographic Colonography: Method and Validation

Computed tomographic colonography (CTC) has been developed for screening of colon cancer. Flattening the three-dimensional (3D) colon wall into two-dimensional (2D) image is believed to (1) provide supplementary information to the endoscopic views and further (2) facilitate colon registration, taniae coli (TC) detection, and haustral fold segmentation. Though the previously-used conformal mapping-based flattening methods can preserve the angular geometry, they have the limitations in providing accurate information of the 3D inner colon wall due to the lack of undulating topography. In this paper, we present a novel colon-wall flattening method using a strategy of 2.5D approach. Coupling with the conformal flattening model, the presented new approach builds an elevation distance map to depict the neighborhood characteristics of the inner colon wall. We validated the new method via two CTC applications: TC detection and haustral fold segmentation. Experimental results demonstrated the effectiveness of our strategy for CTC studies.

Colon flattening using heat diffusion Riemannian metric

We propose a new colon flattening algorithm that is efficient, shape-preserving, and robust to topological noise. Unlike previous approaches, which require a mandatory topological denoising to remove fake handles, our algorithm directly flattens the colon surface without any denoising. In our method, we replace the original Euclidean metric of the colon surface with a heat diffusion metric that is insensitive to topological noise. Using this heat diffusion metric, we then solve a Laplacian equation followed by an integration step to compute the final flattening. We demonstrate that our method is shape-preserving and the shape of the polyps are well preserved. The flattened colon also provides an efficient way to enhance the navigation and inspection in virtual colonoscopy. We further show how the existing colon registration pipeline is made more robust by using our colon flattening. We have tested our method on several colon wall surfaces and the experimental results demonstrate the robustness and the efficiency of our method.

An improved method of automatic colon segmentation for virtual colon unfolding

The technique of virtual colon unfolding (VU) is a non-invasive procedure to detect polyps on the colon inner wall. Compared with conventional virtual colonoscopy, VU is faster and results in fewer uninspected regions. However, the performance of VU is more vulnerable to the quality of colon segmentation. In this paper, an improved colon segmentation method is proposed to enhance the performance of VU. The improved method is with the use of a novel post-processing scheme, which is composed of two parts: attain more accurate centerlines with the help of scalar complementary geodesic distance field and compensate gap-like artifacts based on local morphological information. We validated the improved method on twenty colon cases via two widely used VU techniques, the ray-casting technique and the conformal-mapping technique. Experimental results indicated that with the use of the improved method, the rates of correct response via ray-casting and conformal-mapping techniques were respectively elevated by 14.9% and 13.1%, while the rates of false response were respectively reduced by 8.4% and 10.8%.

Volumetric Colon Wall Unfolding Using Harmonic Differentials

Volumetric colon wall unfolding is a novel method for virtual colon analysis and visualization with valuable applications in virtual colonoscopy (VC) and computer-aided detection (CAD) systems. A volumetrically unfolded colon enables doctors to visualize the entire colon structure without occlusions due to haustral folds, and is critical for performing efficient and accurate texture analysis on the volumetric colon wall. Though conventional colon surface flattening has been employed for these uses, volumetric colon unfolding offers the advantages of providing the needed quantities of information with needed accuracy. This work presents an efficient and effective volumetric colon unfolding method based on harmonic differentials. The colon volumes are reconstructed from CT images and are represented as tetrahedral meshes. Three harmonic 1-forms, which are linearly independent everywhere, are computed on the tetrahedral mesh. Through integration of the harmonic 1-forms, the colon volume is mapped periodically to a canonical cuboid. The method presented is automatic, simple, and practical. Experimental results are reported to show the performance of the algorithm on real medical datasets. Though applied here specifically to the colon, the method is general and can be generalized for other volumes.

Virtual eversion and rotation of colon based on outer surface centerline

PURPOSE

Virtual eversion turns the colon's inner surface to its outside while maintaining the original colon path. The virtually everted colon allows both global and local views of the mucosal surface for observation. However, the conventional colon's inner surface centerline commonly used in virtual colonoscopy and virtual flattening is not suitable for virtual eversion. Therefore, the colon's outer surface centerline is introduced for virtual eversion to produce a more accurate representation.

METHODS

An improved level set segmentation method is presented for generating the colon's outer surface. To achieve eversion with fewer errors, the centerline of the colon's outer surface is employed in the proposed virtual eversion method instead of the inner surface centerline. A hybrid sampling method is designed to accelerate the eversion. Virtual rotation is introduced to visualize the lateral and rear views of the colon better. The gathered structures in the high curvature regions can be separated by virtual rotation.

RESULTS

The proposed methods were validated using two three-dimensional phantoms and 87 CT data sets. A study on the observation performance of the everted data showed that the reading times were (63% of time reduction for phantom A, 65% of time reduction for phantom B, and 77% of time reduction for CT data) less than those using virtual colonoscopy, while maintaining the sensibility. The incidence of improperly everted regions in the virtual eversion based on the outer surface centerline was 71% less than that based on the inner surface centerline.

CONCLUSIONS

The virtual eversion based on the outer surface centerline is more accurate than the one based on the inner surface centerline whether the colon's inner surface is smooth or ragged. The time required for polyp detection using the virtual eversion is considerably less than that using the conventional virtual endoscopy. Virtual eversion and virtual rotation are promising methods for the rapid location of colonic polyps. Together with virtual colonoscopy and virtual flattening, virtual eversion and virtual rotation can be integrated to produce a powerful system for diagnosing colonic lesions.

Reversible projection technique for colon unfolding

Colon unfolding provides an efficient way to navigate the colon in computed tomographic colonography (CTC). Most existing unfolding techniques only compute forward projections. When radiologists find abnormalities or conduct measurements on the unfolded view (which is often quicker and easier), it is difficult to locate the corresponding region on the 3-D view for further examination (which is more accurate and reliable). To address this, we propose a reversible projection technique for colon unfolding. The method makes use of advanced algorithms including rotation-minimizing frames, recursive ring sets, mesh skinning, and cylindrical projection. Both forward and reverse mapping can be computed for points on the colon surface. Therefore, it allows for detecting and measuring polyps on the unfolded view and mapping them back to the 3-D surface. We generated realistic colon simulation data incorporating most colon characteristics, such as curved centerline, variable distention, haustral folds, teniae coli, and colonic polyps. Our method was tested on both simulated data and data from 110 clinical CTC studies. The results showed submillimeter accuracy in simulated data and -0.23 ± 1.67 mm in the polyp measurement using clinical CTC data. The major contributions of our technique are: 1) the use of a recursive ring set method to solve the centerline and surface correspondence problem; 2) reverse transformation from the unfolded view to the 3-D view; and 3) quantitative validation using a realistic colon simulation and clinical CTC polyp measurement.

Improving the accuracy of CTC interpretation: computer-aided detection

Computer-aided polyp detection aims to improve the accuracy of the colonography interpretation. The computer searches the colonic wall to look for polyplike protrusions and presents a list of suspicious areas to a physician for further analysis. Computer-aided polyp detection has developed rapidly in the past decade in the laboratory setting and has sensitivities comparable with those of experts. Computer-aided polyp detection tends to help inexperienced readers more than experienced ones and may also lead to small reductions in specificity. In its currently proposed use as an adjunct to standard image interpretation, computer-aided polyp detection serves as a spellchecker rather than an efficiency enhancer.

Current techniques in the performance, interpretation, and reporting of CT colonography

The technical objective of computed tomographic colonography (CTC) is to acquire high-quality computed tomography images of the cleansed, well-distended colon for polyp detection. In this article the authors provide an overview of the technical components of CTC, from preparation of the patient to acquisition of the imaging data and basic methods of interpretation. In each section, the best evidence for current practices and recommendations is reviewed. Each of the technical components must be optimized to achieve high sensitivity in polyp detection.

Colon unfolding via skeletal subspace deformation

We present an efficient method to digitally straighten a colon volume using mesh skinning, a technique well known in computer graphics to deform a polygonal mesh attached to a skeleton hierarchy. In our case, the colon centerline is used as the skeleton structure and the polyhedral model of the lumen as the skin that is to be deformed as the centerline is straightened. Once the colon has been straightened, we use standard rendering techniques to compute the virtual dissection. Our approach is significantly more efficient than previously proposed techniques.

Digital eversion of a hollow structure: an application in virtual colonography

A new methodology is presented for digital eversion of a hollow structure. The digital eversion is advantageous for better visualization of a larger portion of the inner surface with preservation of geometric relationship and without time-consuming navigation. Together with other techniques, digital eversion may help improve screening, diagnosis, surgical planning, and medical education. Two eversion algorithms are proposed and evaluated in numerical simulation to demonstrate the feasibility of the approach.

Two- versus Three-dimensional Colon Evaluation with Recently Developed Virtual Dissection Software for CT Colonography

This retrospective study was institutional review board approved; the requirement for informed patient consent was waived. The purpose of this study was to retrospectively compare a two-dimensional (2D) data interpretation technique with a three-dimensional (3D) colon dissection technique in terms of interpretation time and sensitivity for colonic polyp detection, with colonoscopy as the reference standard. Ninety-six patients (56 men, 40 women; mean age, 54.8 years) underwent colonoscopy and multidetector computed tomographic (CT) colonography on the same day. Two radiologists independently analyzed the data on a per-polyp and per-patient basis. The sensitivity of both approaches was compared by using the McNemar test. The time required to interpret CT colonographic data with each technique was also assessed. Compared with the conventional 2D colonic polyp detection method, primary 3D interpretation with use of virtual dissection software for CT colonography revealed comparable per-polyp (77% and 69% for two readers) and per-patient (77% and 73% for two readers) sensitivities and comparable per-patient specificity (99% and 89% for two readers) for the detection of polyps 6 mm in diameter or larger and involved a shorter interpretation time.

CT colonography: visualization methods, interpretation, and pitfalls

Virtual colonoscopy interpretation is improving rapidly with the development of efficient software using two-dimensional, three-dimensional (3D) endoluminal, and 3D novel views such as those that seem to cut the colon open and lay it flat for interpretation. Comparison of these various views, comparisons of supine and prone positioning, and comparisons of lung and soft tissue windows aid in the recognition of various pitfalls of interpretation.

Virtual fly-over: a new visualization technique for virtual colonoscopy

In this paper, we propose a new visualization technique for virtual colonoscopy (VC). The proposed method is called Virtual Fly-Over, which splits the entire colon anatomy into exactly two halves. Then, it assigns a virtual camera to each half to perform fly-over navigation, which has several advantages over both traditional fly-through and related methods. First, by controlling the elevation of the camera, there is no restriction on its field of view (FOV) angle (e.g., >90 degrees) to maximize visualized surface areas, and hence no perspective distortion. Second, the camera viewing volume is perpendicular to each colon half, so potential polyps that are hidden behind haustral folds are easily found. Finally, because the orientation of the splitting surface is controllable, the navigation can be repeated at a different split orientation to overcome the problem of having a polyp that is divided between the two halves of the colon. Quantitative experimental results on 15 clinical datasets have shown that the average surface visibility coverage is 99.59 +/- 0.2%.

Feature-based texture display for detection of polyps on flattened colon volume

This paper presents a volume-based algorithm to flatten the colon. Based on the flattened colon volume, three different display schemes are adapted to transfer the three-different imensional (3D) flattened colon volume into a 2D image. One display scheme is surface-based rendering, one is volume-based rendering, and the third one is feature-based texture display. These three displays generate not only a traditional flattened-colon surface image, but also a feature-based texture image which can be utilized to characterize and detect the colonic polyps, resulting in a new way to visualize the entire colon.

Three-dimensional virtual dissection at CT colonography: unraveling the colon to search for lesions

Computed tomographic (CT) colonography is a promising noninvasive examination for colorectal cancer screening; however, the optimal interpretation strategy remains undecided. Virtual dissection is an innovative technique whereby the three-dimensional (3D) model of the colon is virtually unrolled, sliced open, and displayed as a flat 3D rendering of the mucosal surface, similar to a gross pathologic specimen. This technique has the potential to reduce evaluation time by providing a more rapid 3D image assessment than is possible with an antegrade and retrograde 3D endoluminal fly-through. It may also ultimately improve accuracy by reducing blind spots present with 3D endoluminal displays and by reducing reader fatigue. A disadvantage of virtual dissection is the potential for distortion of colonic lesions and normal anatomy. To avoid potential pitfalls in image interpretation, the radiologist must be familiar with the unique appearance of the normal colon anatomy and of various pathologic findings when using virtual dissection with two-dimensional axial and 3D endoluminal CT colonographic image data sets.

A comparison of primary two- and three-dimensional methods to review CT colonography

The aim of our study was to compare primary three-dimensional (3D) and primary two-dimensional (2D) review methods for CT colonography with regard to polyp detection and perceptive errors. CT colonography studies of 77 patients were read twice by three reviewers, first with a primary 3D method and then with a primary 2D method. Mean numbers of true and false positives, patient sensitivity and specificity and perceptive errors were calculated with colonoscopy as a reference standard. A perceptive error was made if a polyp was not detected by all reviewers. Mean sensitivity for large (> or = 10 mm) polyps for primary 3D and 2D review was 81% (14.7/18) and 70%(12.7/18), respectively (p-values > or = 0.25). Mean numbers of large false positives for primary 3D and 2D were 8.3 and 5.3, respectively. With primary 3D and 2D review 1 and 6 perceptive errors, respectively, were made in 18 large polyps (p = 0.06). For medium-sized (6-9 mm) polyps these values were for primary 3D and 2D, respectively: mean sensitivity: 67%(11.3/17) and 61%(10.3/17; p-values > or = 0.45), number of false positives: 33.3 and 15.6, and perceptive errors : 4 and 6 (p = 0.53). No significant differences were found in the detection of large and medium-sized polyps between primary 3D and 2D review.

Multislice CT Colonography: Current Status and Limitations

CT colonography (CTC) is a promising method for colorectal cancer screening because it provides a full structural evaluation of the entire colon. It has a superior safety profile, a low rate of complications, and high patient acceptance. In addition, CTC offers the real possibility of eliminating the cathartic bowel preparation, one of the biggest obstacles to patient compliance with colorectal cancer screening. Results of CTC studies in recently published literature are extremely encouraging, demonstrating that this method of screening can detect lesions equal to or larger than 8 mm with few false-positive findings.

CT colonography: comparison of a colon dissection display versus 3D endoluminal view for the detection of polyps

The purpose of this study was to compare sensitivity, specificity, and postprocessing time of a colon dissection approach to regular 3D-endoluminal workup of computed tomography (CT) colonography for the detection of polypoid lesions. Twenty-one patients who had received conventional colonoscopy after CT colonography were selected; 18 patients had either colon polyps or colon cancer and three had no findings. CT colonography was performed using a 4-channel multi-detector-row (MDR) CT in ten cases and a 16-channel MDR-CT in 11 cases. A blinded reader retrospectively evaluated all colonographies using both viewing methods in a randomized order. Thirty-seven polyps were identified by optical colonoscopy. An overall per-lesion sensitivity of 47.1% for lesions smaller than 5 mm, 56.3% for lesions between 5 mm and 10 mm, and 75.0% for lesion larger than 10 mm was calculated using the colon dissection approach. This compared to an overall per-lesion sensitivity of 35.3% (<5 mm), 81.5% (5-10 mm), and 100.0% (>10 mm) using the endoluminal view. The average time consumption for CT colonography evaluation with the colon dissection software was 10 min versus 38 min using the endoluminal view. A colon dissection approach may provide a significant time advantage for evaluation of CT colonography while obtaining a high sensitivity. It is especially superior in the detection of lesions smaller than 5 mm.

3D reconstruction techniques made easy: know-how and pictures

Three-dimensional reconstructions represent a visual-based tool for illustrating the basis of three-dimensional post-processing such as interpolation, ray-casting, segmentation, percentage classification, gradient calculation, shading and illumination. The knowledge of the optimal scanning and reconstruction parameters facilitates the use of three-dimensional reconstruction techniques in clinical practise. The aim of this article is to explain the principles of multidimensional image processing in a pictorial way and the advantages and limitations of the different possibilities of 3D visualisation.

Flattening maps for the visualization of multibranched vessels

In this paper, we present two novel algorithms which produce flattened visualizations of branched physiological surfaces, such as vessels. The first approach is a conformal mapping algorithm based on the minimization of two Dirichlet functionals. From a triangulated representation of vessel surfaces, we show how the algorithm can be implemented using a finite element technique. The second method is an algorithm which adjusts the conformal mapping to produce a flattened representation of the original surface while preserving areas. This approach employs the theory of optimal mass transport. Furthermore, a new way of extracting center lines for vessel fly-throughs is provided.

Colorectal cancer screening and surveillance with CT colonography: current controversies and obstacles

Computed tomographic (CT) colonography has been advocated as an alternative colorectal screening method because studies in populations with a high prevalence of polyps have demonstrated that sensitivity for patients with large (> or =10 mm) polyps is generally high (approximately 90%). In three recent studies in low-prevalence populations, however, these values vary from 55% to 94%. Many questions have been raised as to the cause of this remarkable variability, which hampers the implementation of CT colonography in colorectal cancer screening and surveillance. We provide an overview of some potential causes and discuss the available, often indirect, evidence. In addition, several other obstacles that may influence implementation are discussed. Many differences between the study with high sensitivity (94%) and the two studies with low sensitivity (55% and 64%) exist: the primary method to review the data (two or three dimensional), bowel preparation (with or without oral contrast agents), study design (verification method and analysis of adenomas only), reader's experience, and scanning technique (single vs. multislice, thin vs. thick sections). Additional obstacles for implementation in prevention of colorectal cancer may be controversial results concerning patient acceptance, the large-scale use of ionizing radiation, difficulties in detecting flat adenomas, and extracolonic findings. Use of primary three-dimensional review methods, addition of oral contrast agents to bowel preparation, and endoscopic verification of false-positive results on CT colonography are speculated to have a positive influence on sensitivity. Future investigations should demonstrate the influence of these potential factors on sensitivity of CT colonography. Despite a growing body of evidence, it remains uncertain to what extent patient acceptance, radiation issues, flat lesions, and extracolonic findings will be a stumbling block to using CT colonography for colorectal cancer screening.

Fast and robust computation of colon centerline in CT colonography

Although several methods for generating the centerline of a colon from CT colonographic scans have been proposed, in general they are time-consuming and do not take into account that the images of the colon may be of nonoptimal quality, with collapsed regions, and stool within the colon. Furthermore, the colonic lumen or wall, which is often used as a basis for computation of a centerline, is not always precisely segmented. In this study, we have developed an algorithm for computation of a colon centerline that is fast compared to the centerline algorithms presented in the reviewed literature, and that relies little on a complete colon segments identification. The proposed algorithm first extracts local maxima in a distance map of a segmented colonic lumen. The maxima are considered to be nodes in a set of graphs, and are iteratively linked together, based on a set of connection criteria, giving a minimum distance spanning tree. The connection criteria are computed from the distance from object boundary, the Euclidean distance between nodes and the voxel values on the pathway between pairs of nodes. After the last iteration, redundant branches are removed and end segments are recovered for each remaining graph. A subset of the initial maxima is used for distinguishing between the colon and noncolonic centerline segments among the set of graphs, giving the final centerline representation. A phantom study showed that, with respect to phantom variations, the algorithm achieved nearly constant computation time (2.3-2.9 s) except for the most extreme setting (20.2 s). The algorithm successfully found all, or most of, the centerline (93% - 100%). Displacement from optimum varied with colon diameter (1.2-6.6 mm). By use of 40 CT colonographic scans, the computer-generated centerlines were compared with the centerlines generated by three radiologists. The similarity was measured based on percent coverage and average displacement. The computer-generated centerlines, when compared with human-generated centerlines, had approximately the same displacement as when the human-generated centerlines were compared among each other (3.8 mm versus 4.0 mm). The coverage of the computer-generated centerlines was slightly less than that of the human-generated centerlines (92% versus 94%). The 40 centerlines were, on average, computed in 10.5 seconds, including computation time for the distance transform, with an Intel Pentium-based 800 MHz computer, as compared with 12-17 seconds or more (excluding computation time for the distance transform needed) per centerline as reported in other studies.

Computed Tomography Colonography

OBJECTIVE

: To determine the feasibility of a computer-aided detection (CAD) algorithm as the "first reader" in computed tomography colonography (CTC).

METHODS

: In phase 1 of a 2-part blind trial, we measured the performance of 3 radiologists reading 41 CTC studies without CAD. In phase 2, readers interpreted the same cases using a CAD list of 30 potential polyps.

RESULTS

: Unassisted readers detected, on average, 63% of polyps > or =10 mm in diameter. Using CAD, the sensitivity was 74% (not statistically different). Per-patient analysis showed a trend toward increased sensitivity for polyps > or =10 mm in diameter, from 73% to 90% with CAD (not significant) without decreasing specificity. Computer-aided detection significantly decreased interobserver variability (P = 0.017). Average time to detection of the first polyp decreased significantly with CAD, whereas total reading case reading time was unchanged.

CONCLUSION

: Computer-aided detection as a first reader in CTC was associated with similar per-polyp and per-patient detection sensitivity to unassisted reading. Computer-aided detection decreased interobserver variability and reduced the time required to detect the first polyp.

Virtual Colon Dissection with CT Colonography Compared with Axial Interpretation and Conventional Colonoscopy:Preliminary Results

OBJECTIVE

The aim of this study was to determine whether a new virtual colon dissection 3D visualization technique for CT colonography has a shorter analysis time and better sensitivity for detection of colonic polyps than interpretation of axial CT images. SUBJECTS AND METHODS. CT colonography was performed in 22 patients using 4-MDCT followed by conventional colonoscopy on the same day. The CT colonography data sets were analyzed by virtual colon dissection, which virtually bisects and unfolds the colon along its longitudinal axis to inspect the inner colonic surface for polyps. The same CT data sets were independently evaluated using axial interpretation. All data sets were independently interpreted by two radiologists in a blinded manner.

RESULTS

Conventional colonoscopy revealed 31 colonic lesions in 20 patients. Twenty two of the lesions were smaller than 10 mm; nine were 10 mm or larger. Two of the original 22 patients were excluded, one because of residual stool and fluid and the other because of an impassable stenosing rectal wall cancer. For virtual colon dissection, the per-lesion sensitivity was 42% for observer 1 and 68% for observer 2; for axial interpretation, the respective sensitivities were 48% and 61%. For polyps 10 mm or larger, the respective sensitivities were 67% and 89% for virtual colon dissection and 89% and 100% for axial interpretation. The average time for reconstruction and analysis of virtual colon dissection was 36.8 min versus 29.2 min for axial images. Virtual colon dissection was feasible in both the supine and the prone positions in 45.5% of colonic segments, in either the supine or the prone position in 24.5%, and in neither position in 30% of segments.

CONCLUSION

Although virtual colon dissection may facilitate detection of colonic polyps in isolated cases, its detection rate is not superior to axial interpretation, which is mainly attributable to failed rendering of insufficiently distended colonic segments or regions with residual feces. Virtual colon dissection is also the more time-consuming of the two procedures. With further improvement of path-finding and image segmentation, however, virtual colon dissection has the potential to be a useful interpretation tool for CT colonography.

Three-dimensional display modes for CT colonography: conventional 3D virtual colonoscopy versus unfolded cube projection

The authors compared a conventional two-directional three-dimensional (3D) display for computed tomography (CT) colonography with an alternative method they developed on the basis of time efficiency and surface visibility. With the conventional technique, 3D ante- and retrograde cine loops were obtained (hereafter, conventional 3D). With the alternative method, six projections were obtained at 90 degrees viewing angles (unfolded cube display). Mean evaluation time per patient with the conventional 3D display was significantly longer than that with the unfolded cube display. With the conventional 3D method, 93.8% of the colon surface came into view; with the unfolded cube method, 99.5% of the colon surface came into view. Sensitivity and specificity were not significantly different between the two methods. Agreements between observers were kappa = 0.605 for conventional 3D display and kappa = 0.692 for unfolded cube display. Consequently, the latter method enhances the 3D endoluminal display with improved time efficiency and higher surface visibility.

Multislice CT colonography: current status and limitations

CT colonography (CTC) is a promising method for colorectal screening providing a full structural evaluation of the entire colon and gaining in popularity due to a superior safety profile, a low rate of complications, and high patient acceptance. Multislice CT (MSCT) has further improved the diagnostic potential of CTC by generating high-resolution CT images of the abdomen and pelvis in shorter acquisition times than was previously possible. Over the past year, multiple studies have been published on every aspect of CTC including techniques, image display, image reconstruction, and clinical trial results assessing the feasibility of CTC as a screening tool. Yet despite increasing clinical use, the appropriate role of CTC in colorectal cancer screening remains undefined and barriers to widespread adoption remain. In particular, though the test is generally regarded as easy to perform, accurate interpretation requires a steep learning curve. While several large studies have found high sensitivity and specificity, the accuracy of CTC in a screening population has yet to be verified and almost no health insurance plans reimburse for its use in colorectal screening. Ongoing research in computer-aided detection and new software tools, however, have the potential to increase accuracy and ease of interpretation significantly, accelerating its acceptance as a colorectal screening tool.

Edge displacement field-based classification for improved detection of polyps in CT colonography

Colorectal cancer can easily be prevented provided that the precursors to tumors, small colonic polyps, are detected and removed. Currently, the only definitive examination of the colon is fiber-optic colonoscopy, which is invasive and expensive. Computed tomographic colonography (CTC) is potentially a less costly and less invasive alternative to FOC. It would be desirable to have computer-aided detection (CAD) algorithms to examine the large amount of data CTC provides. Most current CAD algorithms have high false positive rates at the required sensitivity levels. We developed and evaluated a postprocessing algorithm to decrease the false positive rate of such a CAD method without sacrificing sensitivity. Our method attempts to model the way a radiologist recognizes a polyp while scrolling a cross-sectional plane through three-dimensional computed tomography data by classification of the changes in the location of the edges in the two-dimensional plane. We performed a tenfold cross-validation study to assess its performance using sensitivity/specificity analysis on data from 48 patients. The mean specificity over all experiments increased from 0.19 (0.35) to 0.47 (0.56) for a sensitivity of 1.00 (0.95).

Computed tomography colonography (virtual colonoscopy): review

Computed tomography examination of the colon performed after bowel cleansing and distension of the lumen with gas goes by several different names--CT colonography (CTC) and CT colography perhaps being the most common. Strictly, the term 'virtual colonoscopy' (VC), should be reserved for the process of examining 3-D, simulated endoluminal images with a capability to navigate through the bowel using appropriate software. Computed tomography colonography appears to be the name that has gained favour among radiologists, although it is suspected that 'virtual colonoscopy' will persist as a generic term due to its attractive 'high-tech' connotations for non-radiological medical and lay persons. Whatever the name, the technique has been made possible through the advent of fast helical CT scanners which allow acquisition of a volume of data, and of proprietary software which enables multiplanar reformatting and 3-D endoluminal reconstructions. It is evident that if CTC/VC can be shown to be acceptable to patients, safe, affordable and accurate, it has enormous potential as a diagnostic and screening tool for colorectal neoplasia.

Computerized detection of colonic polyps at CT colonography on the basis of volumetric features: pilot study

PURPOSE

To develop a computer-aided diagnosis (CAD) scheme for automated detection of colonic polyps on the basis of volumetric features and to assess its accuracy on the basis of colonoscopy, the standard.

MATERIALS AND METHODS

Computed tomographic (CT) colonography was performed in patients with use of standard bowel cleansing, air insufflation, and helical scanning in supine and prone positions. The colon was extracted from volumetric data sets generated from transverse CT sections. Volumetric features characterizing polyps were computed at each point in the extracted colon. Polyps were detected by means of hysteresis thresholding and fuzzy clustering followed by a rule-based test on the basis of feature values. Locations of the detected polyps were compared with those detected at conventional colonoscopy.

RESULTS

Forty-one cases were analyzed: nine cases with polyps and 32 without polyps. Each case with polyps had one polyp of clinically important size (six were 5-9 mm; three, 10 mm). Thus, there were 82 volumetric data sets, 18 included polyps. Eighty-nine percent (16 of 18) of the polyps were detected. Each of the two false-negative findings was detected in the other position; thus, 100% of polyp cases were detected, with 2.5 false-positive findings per patient. The false-positive findings were similar to those due to common perceptual errors. Most of the false-positive findings were easily distinguishable from true polyps by experienced radiologists.

CONCLUSION

The CAD scheme has the potential to depict polyps with high sensitivity and an acceptable false-positive rate.

Automatic fusion of freehand endoscopic brain images to three-dimensional surfaces: creating stereoscopic panoramas

A major limitation of the use of endoscopes in minimally invasive surgery is the lack of relative context between the endoscope and its surroundings. The purpose of this work was to fuse images obtained from a tracked endoscope to surfaces derived from three-dimensional (3-D) preoperative magnetic resonance or computed tomography (CT) data, for assistance in surgical planning, training and guidance. We extracted polygonal surfaces from preoperative CT images of a standard brain phantom and digitized endoscopic video images from a tracked neuro-endoscope. The optical properties of the endoscope were characterized using a simple calibration procedure. Registration of the phantom (physical space) and CT images (preoperative image space) was accomplished using fiducial markers that could be identified both on the phantom and within the images. The endoscopic images were corrected for radial lens distortion and then mapped onto the extracted surfaces via a two-dimensional 2-D to 3-D mapping algorithm. The optical tracker has an accuracy of about 0.3 mm at its centroid, which allows the endoscope tip to be localized to within 1.0 mm. The mapping operation allows multiple endoscopic images to be "painted" onto the 3-D brain surfaces, as they are acquired, in the correct anatomical position. This allows panoramic and stereoscopic visualization, as well as navigation of the 3-D surface, painted with multiple endoscopic views, from arbitrary perspectives.

Colon cancer screening with virtual colonoscopy: promise, polyps, politics

Virtual colonoscopy (CT colonography) promises to become a primary method for colorectal cancer screening and return radiologists to a major role in colon cancer prevention. Results from major centers in the United States show accuracy to be comparable to conventional colonoscopy for detection of polyps of significant size--that is, greater than 10 mm--with few false-positives. The advent of virtual colonoscopy has also heightened awareness of the natural history of colonic polyps, particularly in terms of identifying an appropriate target size for detection in colorectal screening programs. Small polyps (<10 mm) are often either hyperplastic on histology or are unlikely to progress to frank cancer in the patient's lifetime and are therefore of little clinical significance for the average adult. Thus, the rationale for detecting and removing each and every colonic polyp regardless of size has come under increasing scrutiny in the context of cost-benefit analysis of various test strategies for colorectal cancer screening. Virtual colonoscopy may allow patients to obtain reliable information about the status of their colonic mucosa noninvasively and thus make a more informed decision as to whether to proceed to conventional colonoscopy for polypectomy.

Feasibility of planar virtual pathology: a new paradigm in volume-rendered CT colonography

Planar virtual pathology (PVP) is an isometric rendering method for examining the CT colonography dataset, which renders the colon in discrete colonic segments. Ten patients with 36 polyps were evaluated using traditional 2D axial, 2D multiplanar reformatted, and 3D endoluminal images as well as PVP. PVP displayed 13 of 17 (76%) polyps of >1 cm, whereas 11 of 17 (65%) were detected using traditional rendering methods. PVP may be a useful adjunct in detecting additional polyps at CT colonography.

Virtual colonoscopy: a new tool for colorectal cancer screening

Virtual colonoscopy or computed-tomography colonography is a promising new method for colorectal cancer screening. Helical computed tomography is used to generate high-resolution, two-dimensional axial images of the abdomen and pelvis. Three-dimensional images of the colon simulating those obtained with conventional colonoscopy can be reconstructed from the data obtained. Favorable attributes of virtual colonoscopy include its safety, high patient acceptance, and ability to provide a full structural evaluation of the entire colon. Multiple studies of virtual colonoscopy have been published in the literature in the past year regarding technique, image display, image reconstruction, clinical trial results, and feasibility as a screening tool. This manuscript will review the various studies in each of these areas.

Colonography using multislice CT

Computed tomography (CT) represents the preferred imaging modality for imaging the large bowel when virtual endoscopic reconstructions are desired. Using the spiral acquisition technique, it has become possible to scan the entire abdomen within a single breathhold, however, slice thicknesses of 5 mm or more are necessary should the breathhold not last longer than 30-40 s. With the advent of multislice CT, contiguous 1-mm slices can be obtained through the entire abdomen while even shortening the breathhold to 25-30 s. The improved speed and spatial resolution of multislice CT results in remarkably sharp virtual reconstructions allowing detection of polyps with sizes less than 3 mm. The disadvantages must still be considered including a dataset consisting of up to 800 images representing a new challenge for postprocessing hard- and software.