Handling Topological Changes during Elastic Registration: Application to Augmented Reality in Laparoscopic Surgery

International audiencePurpose: Locating the internal structures of an organ is a critical aspect of many surgical procedures. Minimally invasive surgery, associated with augmented reality techniques, offers the potential to visualize inner structures, allowing for improved analysis, depth perception or for supporting planning and decision systems.Methods: Most of the current methods dealing with rigid or non-rigid augmented reality make the assumption that the topology of the organ is not modified. As surgery relies essentially on cutting and dissection of anatomical structures, such methods are limited to the early stages of the surgery.We solve this shortcoming with the introduction of a method for physics-based elastic registration using a single view from a monocular camera.Singularities caused by topological changes are detected and propagated to the pre-operative model. This significantly improves the coherence between the actual laparoscopic view and the model, and provides added value in terms of navigation and decision-making, e.g. by overlaying the internal structures of an organ on the laparoscopic view.Results: Our real time augmentation method is assessed on several scenarios, using synthetic objects and real organs. In all cases, the impact of our approach is demonstrated, both qualitatively and quantitatively.Conclusion: The presented approach tackles the challenge of localizing internal structures throughout a complete surgical procedure, even after surgical cuts. This information is crucial for surgeons to improve the outcome for their surgical procedure and avoid complications

Incidence and risk factors of subsyndromal delirium after curative resection of gastric cancer

Background: Subsyndromal delirium, a condition in which patients exhibit some, but not all, of the symptoms of delirium, can negatively affect the outcomes of patients with cancer. However, the incidence of subsyndromal delirium in patients with gastric cancer is unknown. Here, we investigated the incidence and risk factors of subsyndromal delirium after curative resection of gastric cancer. Methods: We recruited consecutive patients with gastric cancer who were scheduled for curative resection at a tertiary hospital. Patients' subsyndromal delirium symptoms were serially assessed preoperatively and 1, 2, 3, and 7 days postoperatively using the Delirium Rating Scale-Revised-98 (DRS-R-98). A DRS-R-98 score of 8-14 at any postoperative assessment was considered to indicate subsyndromal delirium. Sociodemographic and pre-/intraoperative clinical data were also assessed. Logistic regression analyses were used to determine the associated risk factors. Results: Data were analysed from 163 out of 217 eligible patients. Postoperative delirium occurred in one patient (0.6%) and subsyndromal delirium occurred in 19 patients (11.7%). Age >= 70 years (odds ratio, [OR] 3.85; 95% confidence interval [0], 136-10.92; p = 0.011) and education level <= 9 years (OR, 3.98; 95% CI, 139-11.41; p= 0.010) were independent risk factors of subsyndromal delirium after adjusting for preoperative cognitive function. Other pre-/intra-operative variables including anxiety/depression, poor sleep quality, and anaesthesia duration were not associated with subsyndromal delirium. Conclusions: In contrast to the low incidence of delirium among patients undergoing curative resection of gastric cancer, a substantial proportion of such patients experienced subsyndromal delirium. Considering the prognostic implications, more careful detection and management of subsyndromal delirium may be warranted in patients with gastric cance

An Arrhythmia Classification-Guided Segmentation Model for Electrocardiogram Delineation

Accurate delineation of key waveforms in an ECG is a critical initial step in extracting relevant features to support the diagnosis and treatment of heart conditions. Although deep learning based methods using a segmentation model to locate P, QRS and T waves have shown promising results, their ability to handle signals exhibiting arrhythmia remains unclear. In this study, we propose a novel approach that leverages a deep learning model to accurately delineate signals with a wide range of arrhythmia. Our approach involves training a segmentation model using a hybrid loss function that combines segmentation with the task of arrhythmia classification. In addition, we use a diverse training set containing various arrhythmia types, enabling our model to handle a wide range of challenging cases. Experimental results show that our model accurately delineates signals with a broad range of abnormal rhythm types, and the combined training with classification guidance can effectively reduce false positive P wave predictions, particularly during atrial fibrillation and atrial flutter. Furthermore, our proposed method shows competitive performance with previous delineation algorithms on the Lobachevsky University Database (LUDB)

CD44v6 high membranous expression is a predictive marker of therapy response in gastric cancer patients

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).In gastric cancer (GC), biomarkers that define prognosis and predict treatment response remain scarce. We hypothesized that the extent of CD44v6 membranous tumor expression could predict prognosis and therapy response in GC patients. Two GC surgical cohorts, from Portugal and South Korea (n = 964), were characterized for the extension of CD44v6 membranous immuno-expression, clinicopathological features, patient survival, and therapy response. The value of CD44v6 expression in predicting response to treatment and its impact on prognosis was determined. High CD44v6 expression was associated with invasive features (perineural invasion and depth of invasion) in both cohorts and with worse survival in the Portuguese GC cohort (HR 1.461; 95% confidence interval 1.002-2.131). Patients with high CD44v6 tumor expression benefited from conventional chemotherapy in addition to surgery (p < 0.05), particularly those with heterogeneous CD44v6-positive and -negative populations (CD44v6_3+) (p < 0.007 and p < 0.009). Our study is the first to identify CD44v6 high membranous expression as a potential predictive marker of response to conventional treatment, but it does not clarify CD44v6 prognostic value in GC. Importantly, our data support selection of GC patients with high CD44v6-expressing tumors for conventional chemotherapy in addition to surgery. These findings will allow better stratification of GC patients for treatment, potentially improving their overall survival.This work was funded by FEDER-Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020–Operacional Programme for Competitiveness and Internationalization (POCI), Portugal 2020, and by Portuguese funds through FCT–Fundação para a Ciência e a Tecnologia/Ministério da Ciência, Tecnologia e Inovação in the framework of the project “Institute for Research and Innovation in Health Sciences” (POCI-01-0145-FEDER-007274). This work was also financed by the projects NORTE-01-0145-FEDER-000003 and NORTE-01-0145-FEDER-000029, supported by the Norte Portugal Regional Programme (NORTE 2020) under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF); project POCI-01-0145-FEDER-016390 and SAICTPAC/0022/2015, funded by ERDF, POCI, and FCT; project PTDC/CTM-NAN/120958/2010, from FCT; and by project PTDC/BTM-TEC/30164/2017 funded by ERDF funds through the COMPETE 2020–POCI, Portugal 2020, and by FCT. Salary support to G.M.A. by PTDC/BTM-TEC/30164/2017 project; C.P. was supported by the grant SFRH/BD/113031/2015 from FCT.info:eu-repo/semantics/publishedVersio

Robust Augmented Reality registration method for Localization of Solid Organs’ Tumors Using CT-derived Virtual Biomechanical Model and Fluorescent Fiducials

Presented at the SAGES 2016 Annual Meeting, March 16–19, 2016, Boston, MAInternational audienceAccurate localization of solid organs tumors is crucial to ensure both radicality and organ function preservation. Augmented Reality (AR) is the fusion of computer-generated and real-time images. AR can be used in surgery as a navigation tool, by creating a patient-specific virtual model through 3D software manipulation of DICOM imaging (e.g. CT-scan). The virtual model can be superimposed to the real-time images to obtain the enhanced real-time localization. However, the 3D virtual model is rigid, and does not take into account inner structures’ deformations. We present a concept of automated navigation system, enabling transparency visualization of internal anatomy and tumor’s margins, while the organs undergo deformation during breathing or surgical manipulation

Predictive biomarkers for 5-fluorouracil and oxaliplatin-based chemotherapy in gastric cancers via profiling of patient-derived xenografts.

Gastric cancer (GC) is commonly treated by chemotherapy using 5-fluorouracil (5-FU) derivatives and platinum combination, but predictive biomarker remains lacking. We develop patient-derived xenografts (PDXs) from 31 GC patients and treat with a combination of 5-FU and oxaliplatin, to determine biomarkers associated with responsiveness. When the PDXs are defined as either responders or non-responders according to tumor volume change after treatment, the responsiveness of PDXs is significantly consistent with the respective clinical outcomes of the patients. An integrative genomic and transcriptomic analysis of PDXs reveals that pathways associated with cell-to-cell and cell-to-extracellular matrix interactions enriched among the non-responders in both cancer cells and the tumor microenvironment (TME). We develop a 30-gene prediction model to determine the responsiveness to 5-FU and oxaliplatin-based chemotherapy and confirm the significant poor survival outcomes among cases classified as non-responder-like in three independent GC cohorts. Our study may inform clinical decision-making when designing treatment strategies

NEPSC2, the North Ecliptic Pole SCUBA-2 survey: 850-<i>μ</i>m map and catalogue of 850-<i>μ</i>m selected sources over 2 deg²

Abstract We present an 850-μm mosaic map and extracted catalogue of submillimetre sources in the extended North Ecliptic Pole (NEP) region over about 2 deg2. The 850-μm map is constructed using newly obtained observations by SCUBA-2 at the East Asian Observatory’s James Clerk Maxwell Telescope, carried out using the observatory’s large programme opportunities. The recent 850-μm survey has extended the submillimetre data coverage by almost a factor of 4 compared to previous surveys, with a depth of σrms = 1.0–2.3 mJy beam−1. The catalogue contains 549 sources selected above a significance level of 4σ, where the false-detection rate is 10 per cent; a higher threshold of 4.5σ is required in order to achieve a false-detection rate below 3 per cent, which results in 342 sources being selected. Despite the large spatial variation of the noise, the deboosted flux density of sources is comparable to results from the SCUBA-2 Cosmology Legacy Survey (S2CLS), which covered the central 0.6 deg2 of our survey area with better sensitivity. We construct the source counts at 850 μm, finding results in agreement with other 850-μm surveys in cosmological blank fields over S850 = 4–15 mJy. We find a slight excess of bright galaxies (S850 > 15 mJy), which can be considered to be at ɀphot = 2–4. The 850-μm data adds valuable long-wavelength information to mid-infrared-selected sources from the AKARI NEP-deep and NEP-wide surveys, which will be helpful in preparing for future near-infrared to millimetre wavelength observations in the NEP region. Our 850-μm mosaic map and source catalogue will be made publicly available