Despite the increased use of robotic catheter navigation systems, and the growing interest in surgical skill evaluation in the field of endovascular intervention, there is a lack of objective and ...quantitative metrics for performance evaluation. So far very little research has studied operator behavioral patterns using catheter kinematics, operator forces and motions, and catheter-tissue interactions. This paper proposes a framework for automated and objective assessment of performance by measuring catheter-tissue contact forces and operator motion patterns across different skill levels, and using language models to learn the underlying force and motion patterns that are characteristic of skill. Discrete HMMs are utilized to model operator behavior for varying skill levels performing different catheterization tasks, resulting in cross-validation classification accuracies of 94% (expert) and 98% (novice) using the force-based skill models, as well as 83% (expert) and 94% (novice) using the motion-based models. The results motivate the design of improved metrics for endovascular skill assessment with further applications towards performance evaluation of robot-assisted endovascular catheterization.
The current standard of intra-operative navigation during Fenestrated Endovascular Aortic Repair (FEVAR) calls for need of 3D alignments between inserted devices and aortic branches. The navigation ...commonly via 2D fluoroscopic images, lacks anatomical information, resulting in longer operation hours and radiation exposure. In this paper, a framework for real-time 3D robotic path planning from a single 2D fluoroscopic image of Abdominal Aortic Aneurysm (AAA) is introduced. A graph matching method is proposed to establish the correspondence between the 3D preoperative and 2D intra-operative AAA skeletons, and then the two skeletons are registered by skeleton deformation and regularization in respect to skeleton length and smoothness. Furthermore, deep learning was used to segment 3D pre-operative AAA from Computed Tomography (CT) scans to facilitate the framework automation. Simulation, phantom and patient AAA data sets have been used to validate the proposed framework. 3D distance error of 2mm was achieved in the phantom setup. Performance advantages were also achieved in terms of accuracy, robustness and time-efficiency. All the code will be open source.
Accurate real-time catheter segmentation is an important pre-requisite for robot-assisted endovascular intervention. Most of the existing learning-based methods for catheter segmentation and tracking ...are only trained on small-scale datasets or synthetic data due to the difficulties of ground-truth annotation. Furthermore, the temporal continuity in intraoperative imaging sequences is not fully utilised. In this paper, we present FW-Net, an end-to-end and real-time deep learning framework for endovascular intervention. The proposed FW-Net has three modules: a segmentation network with encoder-decoder architecture, a flow network to extract optical flow information, and a novel flow-guided warping function to learn the frame-to-frame temporal continuity. We show that by effectively learning temporal continuity, the network can successfully segment and track the catheters in real-time sequences using only raw ground-truth for training. Detailed validation results confirm that our FW-Net outperforms state-of-the-art techniques while achieving real-time performance.
Pre-operative Abdominal Aortic Aneurysm (AAA) 3D shape is critical for customized stent-graft design in Fenestrated Endovascular Aortic Repair (FEVAR). Traditional segmentation approaches implement ...expert-designed feature extractors while recent deep neural networks extract features automatically with multiple non-linear modules. Usually, a large training dataset is essential for applying deep learning on AAA segmentation. In this paper, the AAA was segmented using U-net with a small number (two) of training subjects. Firstly, Computed Tomography Angiography (CTA) slices were augmented with gray value variation and translation to avoid the overfitting caused by the small number of training subjects. Then, U-net was trained to segment the AAA. Dice Similarity Coefficients (DSCs) over 0.8 were achieved on the testing subjects. The PLZ, DLZ and aortic branches are all reconstructed reasonably, which will facilitate stent graft customization and help shape instantiation for intra-operative surgery navigation in FEVAR.
Robot-assisted deployment of fenestrated stent grafts in Fenestrated Endovascular Aortic Repair (FEVAR) requires accurate geometrical alignment. Currently, this process is guided by 2D fluoroscopy, ...which is uninformative and error prone. In this paper, a real-time framework is proposed to instantiate the 3D shape of a fenestrated stent graft based on only a single low-dose 2D fluoroscopic image. Firstly, the fenestrated stent graft was placed with markers. Secondly, the 3D pose of each stent segment was instantiated by the RPnP (Robust Perspective-n-Point) method. Thirdly, the 3D shape of the whole stent graft was instantiated via graft gap interpolation. Focal-Unet was proposed to segment the markers from 2D fluoroscopic images to achieve semi-automatic marker detection. The proposed framework was validated on five patient-specific 3D printed phantoms of aortic aneurysms and three stent grafts with new marker placements, showing an average distance error of 1-3mm and an average angle error of 4 degree.
Despite significant advances in surgical technique and perioperative critical care, the traditional open repair of thoraco-abdominal aortic aneurysms (TAAA) is still associated with high rates of ...morbidity and mortality. Hybrid procedures represent a viable treatment alternative for patients with type I, II, and III TAAA, unsuitable for an endovascular approach. Between 2002 and 2009, 81 patients underwent a hybrid procedure for TAAA at St Mary’s hospital, Imperial College London. The elective 30-day mortality rate was 11.8% (7/59). Other complications included paraplegia (10%), prolonged respiratory support (>5 days) (32%), myocardial infarction (7%), stroke (1%), renal impairment requiring temporary hemofiltration (30%) and permanent dialysis (6%). At a follow-up of 17 months, the primary patency rate was 94%. There were 8 type I, 11 type II and 6 type III endoleaks. In this chapter, published studies of hybrid procedures are reviewed and the current status of hybrid procedures in the management of thoraco-abdominal aneurysms is discussed.
Kudzu, the dried root of an important edible plant (Pueraria lobata), is used in Traditional Chinese Medicine for the important nutritional value strictly related to its isoflavone derivatives. These ...compounds characterize the quality of kudzu contained in different preparations, as pharmaceutical ingredient as well as dietary/food supplement (e.g. starch). The optimization of the isoflavones recovery, monitored by HPLC-PDA, through different innovative and conventional extraction techniques, e.g. microwave-assisted, ultrasound-assisted and conventional extraction, represented a suitable challenge in food industry and natural products evaluation. The impact on the isoflavone extraction by using an ionic liquid-assisted procedure was also considered. Furthermore, the inhibitory activity of the most representative isoflavones, isolated from kudzu, was evaluated using four isoforms (I, II, IX and XII) of human carbonic anhydrase (hCA) due to their role in several physiopathological processes.
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•P. lobata root and starch were extracted using various innovative techniques.•Isoflavone content was detected using a validated HPLC-PDA method.•1-Butyl-3-methylimidazolium bromide enhanced the isoflavone extraction.•Evaluation of inhibitory activity of isoflavones against hCA IX and XII isoforms.
The functional and biological significance of the selected CASP12 targets are described by the authors of the structures. The crystallographers discuss the most interesting structural features of the ...target proteins and assess whether these features were correctly reproduced in the predictions submitted to the CASP12 experiment.
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