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Majno P.E.,University of Geneva | Peitgen H.-O.,Fraunhofer Institute for Medical Image Computing
Surgical and Radiologic Anatomy | Year: 2010

Background and purpose: An increasing number of surgical and radiological observations call Couinaud's concept of eight liver segments into question and such inconsistencies are commonly explained with anatomical variations. This paper was intended to demonstrate that, beyond variability, another anatomical principle may allow to understand supposedly differing concepts on liver segmentation. Materials and methods: The study was performed on 25 portal vein casts scanned by helical CT. The branches of the right and left portal vein and their corresponding territories were determined both anatomically and mathematically (MEVIS LiverAnalyzer, MEVISLab). Results: The number of branches coming-off the right and left portal vein was never 8, but many more (mean number 20, range 9-44). Different combinations of these branches and their respective territories, carried out in this study, yielded larger entities and supposedly contradictory subdivisions (including Couinaud's eight segments), without calling upon anatomical variability. Conclusions: We suggest the human liver to be considered as corresponding to 1 portal venous territory at the level of the portal vein, to 2 territories at the level of the right and left branch of the portal vein, and to 20 at the level of the rami of the right and left branch. This "1-2-20-concept" is a rationale for reconciling apparent discrepancies with the eight-segment concept. On a pragmatic level, in cases in which imaging or surgical observations do not fit with Couinaud's scheme, we propose clinicians not to autonomically conclude to the presence of an anatomical variation, but to become aware of the presence of an average of 20 (and not 8) second-order portal venous territories within the human liver. © 2010 Springer-Verlag.


Fasel J.,University Hospitals Geneva Medical Center | Schenk A.,Fraunhofer Institute for Medical Image Computing
Journal of Clinical Imaging Science | Year: 2013

Concepts dealing with the subdivision of the human liver into independent vascular and biliary territories are applied routinely in radiological, surgical, and gastroenterological practice. Despite Couinaud′s widely used eight-segments scheme, opinions on the issue differ considerably between authors. The aim of this article is to illustrate the scientific basis for understanding and harmonizing inconsistencies between seemingly contradictory observations. Possible clinical implications are addressed.


Jenne J.W.,Fraunhofer Institute for Medical Image Computing
Frontiers of Neurology and Neuroscience | Year: 2015

The idea to ablate brain tissue with high-intensity focused ultrasound (HIFU) in a highly precise and localized manner is relatively old. For HIFU tissue ablation, ultrasound (US) waves are concentrated to a focal point. Due to US absorption, the focal area will be heated and consequently thermally destroyed. The spatial accuracy of the non-invasive procedure and the sharp delineation of the induced tissue lesions have led to the term 'focused ultrasound surgery' (FUS). The major obstacle for HIFU ablation in the brain is the skull bone, which absorbs most of the US energy and disturbs the focused US field. The development of large-sized phased array US transducers and adaptive focusing techniques based on computed tomography images have allowed these difficulties to be overcome. With the combination of FUS and MR-imaging and MR-thermometry (MR-guided Focused Ultrasound Surgery, MRgFUS), real-time therapy guidance and control has been established. The safety, feasibility and effectiveness of transcranial MRgFUS were investigated in four initial clinical studies including 4 to 15 patients each. In the first study, which dealt with the treatment of inoperable recurrent glioblastoma, MR was used to monitor localized tissue heating, but no tissue ablation was possible due to technical restrictions of the treatment setup. With improved equipment, the precise induction of thermal lesions in the target area was achieved in studies on neuropathic pain and essential tremor. An instantaneous and persistent significant improvement of disease symptoms was observed in most patients. However, there were serious adverse effects in two cases, where intracranial hemorrhages appeared due to the induction of cavitation. Based on these encouraging clinical results, more extensive clinical studies have been initiated. Transcranial MRgFUS is a fast-growing field of neurological research with high clinical potential. © 2015 S. Karger AG, Basel.


Schwenke M.,Fraunhofer Institute for Medical Image Computing
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention | Year: 2011

In this paper, anisotropic Fast Marching is employed to compute blood flow trajectories as minimal paths in 3D phase-contrast MRI images. Uncertainty in the estimated blood flow vectors is incorporated in a tensor which is used as metric for the anisotropic Fast Marching. A flow connectivity distribution is computed simultaneously to the Fast Marching. Based on the connectivity distribution the most likely flow trajectories can be identified. Results are presented for several PC MRI data sets and the capability of the method to indicate uncertainty of the flow trajectories is shown.


Jacobs C.,Fraunhofer Institute for Medical Image Computing
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention | Year: 2011

Ground glass nodules (GGNs) occur less frequent in computed tomography (CT) scans than solid nodules but have a much higher chance of being malignant. Accurate detection of these nodules is therefore highly important. A complete system for computer-aided detection of GGNs is presented consisting of initial segmentation steps, candidate detection, feature extraction and a two-stage classification process. A rich set of intensity, shape and context features is constructed to describe the appearance of GGN candidates. We apply a two-stage classification approach using a linear discriminant classifier and a GentleBoost classifier to efficiently classify candidate regions. The system is trained and independently tested on 140 scans that contained one or more GGNs from around 10,000 scans obtained in a lung cancer screening trial. The system shows a high sensitivity of 73% at only one false positive per scan.

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