Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions

PURPOSE: Advances in technology and computing play an increasingly important role in the evolution of modern surgical techniques and paradigms. This article reviews the current role of machine learning (ML) techniques in the context of surgery with a focus on surgical robotics (SR). Also, we provide a perspective on the future possibilities for enhancing the effectiveness of procedures by integrating ML in the operating room. METHODS: The review is focused on ML techniques directly applied to surgery, surgical robotics, surgical training and assessment. The widespread use of ML methods in diagnosis and medical image computing is beyond the scope of the review. Searches were performed on PubMed and IEEE Explore using combinations of keywords: ML, surgery, robotics, surgical and medical robotics, skill learning, skill analysis and learning to perceive. RESULTS: Studies making use of ML methods in the context of surgery are increasingly being reported. In particular, there is an increasing interest in using ML for developing tools to understand and model surgical skill and competence or to extract surgical workflow. Many researchers begin to integrate this understanding into the control of recent surgical robots and devices. CONCLUSION: ML is an expanding field. It is popular as it allows efficient processing of vast amounts of data for interpreting and real-time decision making. Already widely used in imaging and diagnosis, it is believed that ML will also play an important role in surgery and interventional treatments. In particular, ML could become a game changer into the conception of cognitive surgical robots. Such robots endowed with cognitive skills would assist the surgical team also on a cognitive level, such as possibly lowering the mental load of the team. For example, ML could help extracting surgical skill, learned through demonstration by human experts, and could transfer this to robotic skills. Such intelligent surgical assistance would significantly surpass the state of the art in surgical robotics. Current devices possess no intelligence whatsoever and are merely advanced and expensive instruments

PHD3 regulates differentiation, tumour growth and angiogenesis in pancreatic cancer

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The Function of Hypoxia-Inducible Factor (HIF) Is Independent of the Endoplasmic Reticulum Protein OS-9

The protein “amplified in osteosarcoma-9” (OS-9) has been shown previously to interact with the prolyl hydroxylases PHD2 and PHD3. These enzymes initiate oxygen-dependent degradation of the α-subunit of hypoxia-inducible factor (HIF), a transcription factor that adapts cells to insufficient oxygen supply (hypoxia). A new model has been proposed where OS-9 triggers PHD dependent degradation of HIF-α. It was the aim of our study to define the molecular mode of action of OS-9 in the regulation of PHD and HIF activity. Although initial co-immunoprecipitation experiments confirmed physical interaction between OS-9 and PHD2, neither overexpression nor lentiviral inhibition of OS-9 expression affected HIF regulation. Subcellular localization experiments revealed a distinct reticular staining pattern for OS-9 while PHD2 was mainly localized in the cytoplasm. Further cell fractionation experiments and glycosylation tests indicated that OS-9 is a luminal ER protein. In vivo protein interaction analysis by fluorescence resonance energy transfer (FRET) showed no significant physical interaction of overexpressed PHD2-CFP and OS-9-YFP. We conclude that OS-9 plays no direct functional role in HIF degradation since physical interaction of OS-9 with oxygen sensing HIF prolyl hydroxylases cannot occur in vivo due to their different subcellular localization

Hypoxia-inducible factor-1α expression in the gastric carcinogenesis sequence and its prognostic role in gastric and gastro-oesophageal adenocarcinomas

Hypoxia-inducible factor-1 (HIF-1)α expression was studied in the gastric carcinogenesis sequence and as a prognostic factor in surgically resected gastric and gastro-oesophageal junction tumours. Protein expression was examined using immunohistochemistry on formalin-fixed biopsies of normal mucosa (n=20), Helicobacter pylori associated gastritis (n=24), intestinal metaplasia (n=24), dysplasia (n=12) and intestinal (n=19) and diffuse (n=21) adenocarcinoma. The relationship between HIF-1α expression and prognosis was assessed in resection specimens from 177 patients with gastric and gastro-oesophageal junction adenocarcinoma. Hypoxia-inducible factor-1α expression was not observed in normal gastric mucosa but increased in density (P<0.01) and intensity (P<0.01) with progression from H. pylori-associated gastritis, intestinal metaplasia, dysplasia to adenocarcinoma. The pattern of staining in the resection specimens was focally positive in 49 (28%) and at the invasive tumour edge in 41 (23%). Invasive edge expression was associated with lymph node metastases (P=0.034), advanced TNM stage (P=0.001) and was an adverse prognostic factor for cancer-specific survival (P=0.019). In univariate analysis and in comparison with tumours not expressing HIF-1α, invasive edge staining was associated with a hazard ratio of 1.6 (95% CI 1.0−2.5) and focally positive staining a hazard ratio of 0.7 (95% CI 0.5−1.2). Hypoxia-inducible factor-1α lost prognostic significance in multivariate analysis. The results suggest HIF-1α is involved in gastric carcinogenesis and disease progression, but is only a weak prognostic factor for survival

Give me your attention: dot-product attention considered harmful for adversarial patch robustness

Neural architectures based on attention such as vision transformers are revolutionizing image recognition. Their main benefit is that attention allows reasoning about all parts of a scene jointly. In this paper, we show how the global reasoning of (scaled) dot-product attention can be the source of a major vulnerability when confronted with adversarial patch attacks. We provide a theoretical understanding of this vulnerability and relate it to an adversary’s ability to misdirect the attention of all queries to a single key token under the control of the adversarial patch. We propose novel adversarial objectives for crafting adversarial patches which target this vulnerability explicitly. We show the effectiveness of the proposed patch attacks on popular image classification (ViTs and DeiTs) and object detection models (DETR). We find that adversarial patches occupying 0.5% of the input can lead to robust accuracies as low as 0% for ViT on ImageNet, and reduce the mAP of DETR on MS COCO to less than 3%

Airway Segmentation, Skeletonization, and Tree Matching to Improve Registration of 3D CT Images with Large Opacities in the Lungs

International audienceIn this work, we address the registration of pulmonary images, representing the same subject, with large opaque regions within the lungs, and with possibly large displacements. We propose a hybrid method combining alignment based on gray levels and landmarks within the same cost function. The landmarks are nodes of the airway tree obtained by specially developed segmentation and skeletonization algorithms. The former uses the random walker approach, whereas the latter exploits the minimum spanning tree constructed by the Dijkstra’s algorithm, in order to detect end-points and bifurcations. Airway trees from different images are matched by a modified best-first-search algorithm with a specially designed distance function. The proposed method was evaluated on computed-tomography images of subjects with acute respiratory distress syndrome, acquired at significantly different mechanical ventilation conditions. It achieved better results than registration based only on gray levels, but also better than hybrid registration using a standard airway-segmentation method

Prolyl hydroxylase 2 dependent and Von-Hippel-Lindau independent degradation of Hypoxia-inducible factor 1 and 2 alpha by selenium in clear cell renal cell carcinoma leads to tumor growth inhibition

<p>Abstract</p> <p>Background</p> <p>Clear cell renal cell carcinoma (ccRCC) accounts for more than 80% of the cases of renal cell carcinoma. In ccRCC deactivation of Von-Hippel-Lindau (VHL) gene contributes to the constitutive expression of hypoxia inducible factors 1 and 2 alpha (HIF-α), transcriptional regulators of several genes involved in tumor angiogenesis, glycolysis and drug resistance. We have demonstrated inhibition of HIF-1α by Se-Methylselenocysteine (MSC) via stabilization of prolyl hydroxylases 2 and 3 (PHDs) and a significant therapeutic synergy when combined with chemotherapy. This study was initiated to investigate the expression of PHDs, HIF-α, and VEGF-A in selected solid cancers, the mechanism of HIF-α inhibition by MSC, and to document antitumor activity of MSC against human ccRCC xenografts.</p> <p>Methods</p> <p>Tissue microarrays of primary human cancer specimens (ccRCC, head & neck and colon) were utilized to determine the incidence of PHD2/3, HIF-α, and VEGF-A by immunohistochemical methods. To investigate the mechanism(s) of HIF-α inhibition by MSC, VHL mutated ccRCC cells RC2 (HIF-1α positive), 786–0 (HIF-2α positive) and VHL wild type head & neck cancer cells FaDu (HIF-1α) were utilized. PHD2 and VHL gene specific siRNA knockdown and inhibitors of PHD2 and proteasome were used to determine their role in the degradation of HIF-1α by MSC.</p> <p>Results</p> <p>We have demonstrated that ccRCC cells express low incidence of PHD2 (32%), undetectable PHD3, high incidence of HIF-α (92%), and low incidence of VEGF-A compared to head & neck and colon cancers. This laboratory was the first to identify MSC as a highly effective inhibitor of constitutively expressed HIF-α in ccRCC tumors. MSC did not inhibit HIF-1α protein synthesis, but facilitated its degradation. The use of gene knockdown and specific inhibitors confirmed that the inhibition of HIF-1α was PHD2 and proteasome dependent and VHL independent. The effects of MSC treatment on HIF-α were associated with significant antitumor activity against ccRCC xenograft.</p> <p>Conclusions</p> <p>Our results show the role of PHD2/3 in stable expression of HIF-α in human ccRCC. Furthermore, HIF-1α degradation by MSC is achieved through PHD2 dependent and VHL independent pathway which is unique for HIF-α regulation. These data provide the basis for combining MSC with currently used agents for ccRCC.</p

Cognitive AutonomouS CAtheters Operating in Dynamic Environments

Advances in miniaturized surgical instrumentation are key to less demanding and safer medical interventions. In cardiovascular procedures interventionalists turn towards catheter-based interventions, treating patients considered unfit for more invasive approaches. A positive outcome is not guaranteed. The risk for calcium dislodgement, tissue damage or even vessel rupture cannot be eliminated when instruments are maneuvered through fragile and diseased vessels. This paper reports on the progress made in terms of catheter design, vessel reconstruction, catheter shape modeling, surgical skill analysis, decision-making and control. These efforts are geared towards the development of the necessary technology to autonomously steer catheters through the vasculature, a target of the EU-funded project CASCADE (Cognitive AutonomouS CAtheters operating in Dynamic Environments). Whereas autonomous placement of an aortic valve implant forms the ultimate and concrete goal, the technology of individual building blocks to reach such ambitious goal is expected to be much sooner impacting and assisting interventionalists in their daily clinical practice