The Fontan operation is a surgical treatment for patients with severe congenital heart diseases, where a biventricular correction of the heart can't be achieved. In these cases, a uni-ventricular system is established. During the last step of surgery a tunnel segment is placed to connect the inferior caval vein directly with the pulmonary artery, bypassing the right atrium and ventricle. Thus, the existing ventricle works for the body circulation, while the venous blood is passively directed to the pulmonary arteries. Fontan tunnels can be placed intra- and extracardially. The location, length and shape of the tunnel must be planned accurately. Furthermore, if the tunnel is placed extracardially, it must be positioned between other anatomical structures without constraining them. We developed a software system to support planning of the tunnel location, shape, and size, making pre-operative preparation of the tunnel material possible. The system allows for interactive placement and adjustment of the tunnel, affords a three-dimensional visualization of the virtual Fontan tunnel inside the thorax, and provides a quantification of the length, circumferences and diameters of the tunnel segments. The visualization and quantification can be used to plan and prepare the tunnel material for surgery in order to reduce the intra-operative time and to improve the fit of the tunnel patch.
Between five and eight percent of all children born with congenitally malformed hearts suffer from coarctations
of the aorta. Some severe coarctations can only be treated by surgical repair. Untreated, this defect can cause
serious damage to organ development or even lead to death. Patch repair requires open surgery. It can affect
patients of any age: newborns with severe coarctation and/or hypoplastic aortic arch as well as older patients with
late diagnosis of coarctation of the aorta. Another patient group are patients of varying age with re-coarctation
of the aorta or hypoplastic aortic arch after surgical and/or interventional repair. If anatomy is complex and
interventional treatment by catheterization, balloon angioplasty or stent placement is not possible, surgery is
The choice of type of surgery depends not only on the given anatomy but also on the experience the surgical
team has with each method. One surgical approach is patch repair. A patch of a suitable shape and size is sewed
into the aorta to expand the aortic lumen at the site of coarctation. At present, the shape and size of the patch
are estimated intra-operatively by the surgeon.
We have developed a software application that allows planning of the patch pre-operatively on the basis of
magnetic resonance angiographic data. The application determines the diameter of the coarctation and/or
hypoplastic segment and constructs a patch proposal by calculating the difference to the normal vessel diameter
pre-operatively. Evaluation of MR angiographic datasets from 12 test patients with different kinds of aortic
arch stenosis shows a divergence of only (1.5±1.2) mm in coarctation diameters between manual segmentations
and our approach, with comparable time expenditure. Following this proposal the patch can be prepared and
adapted to the patient's anatomy pre-operatively. Ideally, this leads to shorter operation times and a better
long-term outcome with a reduced rate of residual stenosis and re-stenosis and aneurysm formation.
In this paper, we evaluate the target position estimation accuracy of a novel soft tissue navigation system with a
custom-designed respiratory liver motion simulator. The system uses a real-time deformation model to estimate
the position of the target (e.g. a tumor) during a minimally invasive intervention from the location of a set of
optically tracked needle-shaped navigation aids which are placed in the vicinity of the target.
A respiratory liver motion simulator was developed to evaluate the performance of the system in-vitro. It
allows the mounting of an explanted liver which can be moved along the longitudinal axis of a corpus model to
simulate breathing motion. In order to assess the accuracy of our system we utilized an optically trackable tool
as target and estimated its position continuously from the current position of the navigation aids. Four different
transformation types were compared as base for the real-time deformation model: Rigid transformations, thinplate
splines, volume splines, and elastic body splines. The respective root-mean-square target position estimation
errors are 2.15 mm, 1.60 mm, 1.88 mm, and 1.92 mm averaged over a set of experiments obtained from a total
of six navigation aid configurations in two pig livers. The error is reduced by 76.3%, 82.4%, 79.3%, and 78.8%,
respectively, compared to the case when no deformation model is applied, i.e., a constant organ position is
assumed throughout the breathing cycle.
Precise knowledge of the individual cardiac anatomy is essential for diagnosis and treatment of congenital heart disease. Complex malformations of the heart can best be comprehended not from images but from anatomic specimens. Physical models can be created from data using rapid prototyping techniques, e.g., lasersintering or 3D-printing. We have developed a system for obtaining data that show the relevant cardiac anatomy from high-resolution CT/MR images and are suitable for rapid prototyping. The challenge is to preserve all relevant details unaltered in the produced models. The main anatomical structures of interest are the four heart cavities (atria, ventricles), the valves and the septum separating the cavities, and the great vessels. These can be shown either by reproducing the morphology itself or by producing a model of the blood-pool, thus creating a negative of the morphology. Algorithmically the key issue is segmentation. Practically, possibilities allowing the cardiologist or cardiac surgeon to interactively check and correct the segmentation are even more important due to the complex, irregular anatomy and imaging artefacts. The paper presents the algorithmic and interactive processing steps implemented in the system, which is based on the open-source Medical Imaging Interaction Toolkit (MITK, www.mitk.org). It is shown how the principles used in MITK enable to assemble the system from modules (functionalities) developed independently from each other. The system allows to produce models of the heart (and other anatomic structures) of individual patients as well as to reproduce unique specimens from pathology collections for teaching purposes.