Random expert sampling for deep learning segmentation of acute ischemic stroke on non-contrast CT.

Outlining acutely infarcted tissue on non-contrast CT is a challenging task for which human inter-reader agreement is limited. We explored two different methods for training a supervised deep learning algorithm: one that used a segmentation defined by majority vote among experts and another that trained randomly on separate individual expert segmentations. The data set consisted of 260 non-contrast CT studies in 233 patients with acute ischemic stroke recruited from the multicenter DEFUSE 3 (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke 3) trial. Additional external validation was performed using 33 patients with matched stroke onset times from the University Hospital Lausanne. A benchmark U-Net was trained on the reference annotations of three experienced neuroradiologists to segment ischemic brain tissue using majority vote and random expert sampling training schemes. The median of volume, overlap, and distance segmentation metrics were determined for agreement in lesion segmentations between (1) three experts, (2) the majority model and each expert, and (3) the random model and each expert. The two sided Wilcoxon signed rank test was used to compare performances (1) to 2) and (1) to (3). We further compared volumes with the 24 hour follow-up diffusion weighted imaging (DWI, final infarct core) and correlations with clinical outcome (modified Rankin Scale (mRS) at 90 days) with the Spearman method. The random model outperformed the inter-expert agreement ((1) to (2)) and the majority model ((1) to (3)) (dice 0.51±0.04 vs 0.36±0.05 (P<0.0001) vs 0.45±0.05 (P<0.0001)). The random model predicted volume correlated with clinical outcome (0.19, P<0.05), whereas the median expert volume and majority model volume did not. There was no significant difference when comparing the volume correlations between random model, median expert volume, and majority model to 24 hour follow-up DWI volume (P>0.05, n=51). The random model for ischemic injury delineation on non-contrast CT surpassed the inter-expert agreement ((1) to (2)) and the performance of the majority model ((1) to (3)). We showed that the random model volumetric measures of the model were consistent with 24 hour follow-up DWI

Managing Peripheral Artery Disease in Diabetic Patients: A Questionnaire Survey from Vascular Centers of the Mediterranean Federation for the Advancing of Vascular Surgery (MeFAVS)

Background: The Mediterranean Federation for the Advancing of Vascular Surgery (MeFAVS) was founded on October 1, 2018, to enhance cooperation among vascular professionals within Mediterranean countries. Due to its prominent social and economic impact on national health systems, diabetic arteriopathy has been selected as the very first topic to be investigated by the federation. Methods: MeFAVS members were asked to reply to a questionnaire on the management of diabetic ischemic foot. Results were collected and analyzed statistically. The questionnaire consisted of 15 multiple choice answers regarding diabetic foot (DF) diagnosis and treatment. The questionnaire was submitted to 21 centers on April 20, 2019. Results: Response rate was 62%. The survey revealed that vascular surgeons, diabetologists, and wound care nurses made-up the core of the diabetic teams present in 76.9%, 69.3%, and 92.3% of the centers, respectively. Diabetic teams were most often led by vascular surgeons (53.8%) and diabetologists (42.2%), but only in 7.9% of cases by nurses. Duplex ultrasonography and computed tomographic angiography were the most commonly available tools used to assess diabetic peripheral arterial disease (PAD). Surgical wound care was undertaken by vascular surgeons in the majority of cases, and only in 46.2% of the cases to orthopedic or plastic surgeons, while nonsurgical wound care was handled by specialized nurses (76.6%) and diabetologists (53.8%). First-line revascularization was preferred over conservative treatment (61.5% vs 53.8%) and endovascular strategy (45.3%) over open (33.7%) or hybrid (21.0%) surgery. Vascular surgeons and interventional radiologists were found to be the most common performers of endovascular revascularization (92.3% and 53.8%, respectively). Amputations had an overall rate of 16.6% (range 4\u201330%) and a mean reintervention rate of 22.5%, and were usually performed by vascular surgeons for both minor and major interventions (84.6%) followed by orthopedic surgeons (15.4% minor and 30.8% major). The availability of a DF clinic (84.6%) and endovascular (53.8%) and open surgery (46.2%) capabilities were considered fundamental to reduce amputation rates. Conclusions: Especially since the introduction and spreading of new endovascular techniques for the treatment of DF, it is a common consensus amongst vascular surgeons that a standardized approach to the discipline is necessary in order to improve outcomes such as amputation-free survival and mortality and it is with this perspective and purpose that transnational cooperation amongst vascular professionals and residents in training are aiming for greater proficiency in endovascular and open surgery

Classification and structure of echovirus 5 '-UTR sequences

Enteroviruses are classified into two genetic clusters on the basis of 5'-UTR and all echoviruses (ECV) are classified together with coxsackie B viruses (CBV), coxsackie A viruses (CAV) types 2-10, 12, 14 and 16, and enteroviruses (EV) 68, 69, 71 and 73. During the present study, 5'-UTR-derived sequences constituting the largest part of the Internal Ribosome Entry Site (IRES) of ECVs were studied with respect to their possible secondary structures, which were predicted following the phenomenon of "covariance", i.e. the existence of evolutionary pressure in favour of structural conservation in the light of nucleotide sequence variability. In this and previous studies, no correlation between overall 5'-UTR identity and the currently recognised Human Enterovirus species was found, implying that notwithstanding their divergent protein-encoding regions, these species are free to exchange 5'-UTRs by recombination. Secondary structure features which are known to be highly conserved amongst enteroviruses and specifically the GNRA tetraloop in secondary structure domain IV, involved in long-term tertiary interactions and loop B in secondary structure domain V with an as yet unknown function were also conserved in ECVs. In contrast, the C(NANCCA)G motif, which is considered to be important in virus transcription and translation, was not conserved in all ECVs and sequence patterns observed in other enterovirus groups and rhinoviruses were recorded