Laparoscopic computer-navigated ablation of liver metastases

Objective In order to benefit from the obvious advantages of minimally invasive liver surgery there is a need to develop high precision tools for intraoperative anatomical orientation, navigation and safety control. In a pilot study we adapted a newly developed system for computer-assisted liver surgery (CALS) in terms of accuracy and technical feasibility to the specific requirements of laparoscopy. Here, we present practical aspects related to laparoscopic computer assisted liver surgery (LCALS). Methods Our video relates to a patient presenting with 3 colorectal liver metastases in Seg. II, III and IVa who was selected in an appropriate oncological setting for LCALS using the CAScination system combined with 3D MEVIS reconstruction. After minimal laparoscopic mobilization of the liver, a 4- landmark registration method was applied to enable navigation. Placement of microwave needles was performed using the targeting module of the navigation system and correct needle positioning was confirmed by intraoperative sonography. Ablation of each lesion was carried out by application of microwave energy at 100 Watts for 1 minute. Results To acquire an accurate (less 0.5 cm) registration, 4 registration cycles were necessary. In total, seven minutes were required to accomplish precise registration. Successful ablation with complete response in all treated areas was assessed by intraoperative sonography and confirmed by postoperative CT scan. Conclusions This teaching video demonstrates the theoretical and practical key points of LCALS with a special emphasis on preoperative planning, intraoperative registration and accuracy testing by laparoscopic methodology. In contrast to mere ultrasound-guided ablation of liver lesions, LCALS offers a more dimensional targeting and higher safety control. This is currently also in routine use to treat vanishing lesions and other difficult to target focal lesions within the liver.

A novel computer test to assess driving-relevant cognitive functions - a pilot study

BACKGROUND: The assessment of driving-relevant cognitive functions in older drivers is a difficult challenge as there is no clear-cut dividing line between normal cognition and impaired cognition and not all cognitive functions are equally important for driving. METHODS: To support decision makers, the Bern Cognitive Screening Test (BCST) for older drivers was designed. It is a computer-assisted test battery assessing visuo-spatial attention, executive functions, eye-hand coordination, distance judgment, and speed regulation. Here we compare the performance in BCST with the performance in paper and pencil cognitive screening tests and the performance in the driving simulator testing of 41 safe drivers (without crash history) and 14 unsafe drivers (with crash history). RESULTS: Safe drivers performed better than unsafe drivers in BCST (Mann-Whitney U test: U = 125.5; p = 0.001) and in the driving simulator (Student's t-test: t(44) = -2.64, p = 0.006). No clear group differences were found in paper and pencil screening tests (p > 0.05; ns). BCST was best at identifying older unsafe drivers (sensitivity 86%; specificity 61%) and was also better tolerated than the driving simulator test with fewer dropouts. CONCLUSIONS: BCST is more accurate than paper and pencil screening tests, and better tolerated than driving simulator testing when assessing driving-relevant cognition in older drivers.

Patient-Specific Semi-Supervised Learning for Postoperative Brain Tumor Segmentation

In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.

Comparison of gadoteric acid and gadobutrol for detection as well as morphologic and dynamic characterization of lesions on breast dynamic contrast-enhanced magnetic resonance imaging

OBJECTIVE In contrast to conventional breast imaging techniques, one major diagnostic benefit of breast magnetic resonance imaging (MRI) is the simultaneous acquisition of morphologic and dynamic enhancement characteristics, which are based on angiogenesis and therefore provide insights into tumor pathophysiology. The aim of this investigation was to intraindividually compare 2 macrocyclic MRI contrast agents, with low risk for nephrogenic systemic fibrosis, in the morphologic and dynamic characterization of histologically verified mass breast lesions, analyzed by blinded human evaluation and a fully automatic computer-assisted diagnosis (CAD) technique. MATERIALS AND METHODS Institutional review board approval and patient informed consent were obtained. In this prospective, single-center study, 45 women with 51 histopathologically verified (41 malignant, 10 benign) mass lesions underwent 2 identical examinations at 1.5 T (mean time interval, 2.1 days) with 0.1-mmol kg doses of gadoteric acid and gadobutrol. All magnetic resonance images were visually evaluated by 2 experienced, blinded breast radiologists in consensus and by an automatic CAD system, whereas the morphologic and dynamic characterization as well as the final human classification of lesions were performed based on the categories of the Breast imaging reporting and data system MRI atlas. Lesions were also classified by defining their probability of malignancy (morpho-dynamic index; 0%-100%) by the CAD system. Imaging results were correlated with histopathology as gold standard. RESULTS The CAD system coded 49 of 51 lesions with gadoteric acid and gadobutrol (detection rate, 96.1%); initial signal increase was significantly higher for gadobutrol than for gadoteric acid for all and the malignant coded lesions (P < 0.05). Gadoteric acid resulted in more postinitial washout curves and fewer continuous increases of all and the malignant lesions compared with gadobutrol (CAD hot spot regions, P < 0.05). Morphologically, the margins of the malignancies were different between the 2 agents, whereas gadobutrol demonstrated more spiculated and fewer smooth margins (P < 0.05). Lesion classifications by the human observers and by the morpho-dynamic index compared with the histopathologic results did not significantly differ between gadoteric acid and gadobutrol. CONCLUSIONS Macrocyclic contrast media can be reliably used for breast dynamic contrast-enhanced MRI. However, gadoteric acid and gadobutrol differed in some dynamic and morphologic characterization of histologically verified breast lesions in an intraindividual, comparison. Besides the standardization of technical parameters and imaging evaluation of breast MRI, the standardization of the applied contrast medium seems to be important to receive best comparable MRI interpretation.

2D-3D Reconstruction-Based Planning of Total Hip Arthroplasty

This chapter proposed a personalized X-ray reconstruction-based planning and post-operative treatment evaluation framework called iJoint for advancing modern Total Hip Arthroplasty (THA). Based on a mobile X-ray image calibration phantom and a unique 2D-3D reconstruction technique, iJoint can generate patient-specific models of hip joint by non-rigidly matching statistical shape models to the X-ray radiographs. Such a reconstruction enables a true 3D planning and treatment evaluation of hip arthroplasty from just 2D X-ray radiographs whose acquisition is part of the standard diagnostic and treatment loop. As part of the system, a 3D model-based planning environment provides surgeons with hip arthroplasty related parameters such as implant type, size, position, offset and leg length equalization. With this newly developed system, we are able to provide true 3D solutions for computer assisted planning of THA using only 2D X-ray radiographs, which is not only innovative but also cost-effective.

Prediction of Trabecular Bone Anisotropy from Quantitative Computed Tomography using Supervised Learning and a Novel Morphometric Feature Descriptor

Patient-specific biomechanical models including local bone mineral density and anisotropy have gained importance for assessing musculoskeletal disorders. However the trabecular bone anisotropy captured by high-resolution imaging is only available at the peripheral skeleton in clinical practice. In this work, we propose a supervised learning approach to predict trabecular bone anisotropy that builds on a novel set of pose invariant feature descriptors. The statistical relationship between trabecular bone anisotropy and feature descriptors were learned from a database of pairs of high resolution QCT and clinical QCT reconstructions. On a set of leave-one-out experiments, we compared the accuracy of the proposed approach to previous ones, and report a mean prediction error of 6% for the tensor norm, 6% for the degree of anisotropy and 19◦ for the principal tensor direction. These findings show the potential of the proposed approach to predict trabecular bone anisotropy from clinically available QCT images.