Laparoscopic versus Open Surgery in Complicated Appendicitis in Children Less Than 5 Years Old: A Six-Year Single-Centre Experience

Introduction. Acute appendicitis is the most common surgical emergency in the pediatric population. The peak incidence occurs in the first decade of life, while it is uncommon to face appendicitis in children younger than 5 years of age. Laparoscopy is now demonstrated to be the optimal approach also to treat complicated appendicitis, but in very young children this standardized operation is not always easy to perform. Material and Methods. From January 2009 to December 2015 we operated on 525 acute appendicitis, with 120 patients less than 5 years of age. Results. 90 children had a complicated appendicitis (localized or diffuse peritonitis): 43 (48%) were operated on by open approach and 47 (52%) by laparoscopy. The overall incidence of postoperative complications was greater in the open appendectomy group (63% versus 26%) and all severe complications requiring reintervention (6% of cases: 3 postoperative abscesses resolved with ultrasound guided percutaneous abscess drainage; 1 tubal surgery for salpingitis; 1 adhesion-related ileus requiring relaparotomy) were mostly associated with open surgery. Conclusions. Laparoscopic surgery resulted as the best approach for treating complicated appendicitis also in younger children, with minor and less severe postoperative complications compared to open surgery

High stretch induces endothelial dysfunction accompanied by oxidative stress and actin remodeling in human saphenous vein endothelial cells

The rate of the remodeling of the arterialized saphenous vein conduit limits the outcomes of coronary artery bypass graft surgery (CABG), which may be influenced by endothelial dysfunction. We tested the hypothesis that high stretch (HS) induces human saphenous vein endothelial cell (hSVEC) dysfunction and examined candidate underlying mechanisms. Our results showed that in vitro HS reduces NO bioavailability, increases inflammatory adhesion molecule expression (E-selectin and VCAM1) and THP-1 cell adhesion. HS decreases F-actin in hSVECs, but not in human arterial endothelial cells, and is accompanied by G-actin and cofilin’s nuclear shuttling and increased reactive oxidative species (ROS). Pre-treatment with the broad-acting antioxidant N-acetylcysteine (NAC) supported this observation and diminished stretch-induced actin remodeling and inflammatory adhesive molecule expression. Altogether, we provide evidence that increased oxidative stress and actin cytoskeleton remodeling play a role in HS-induced saphenous vein endothelial cell dysfunction, which may contribute to predisposing saphenous vein graft to failure

Deep learning segmentation of fibrous cap in intravascular optical coherence tomography images

Thin-cap fibroatheroma (TCFA) is a prominent risk factor for plaque rupture. Intravascular optical coherence tomography (IVOCT) enables identification of fibrous cap (FC), measurement of FC thicknesses, and assessment of plaque vulnerability. We developed a fully-automated deep learning method for FC segmentation. This study included 32,531 images across 227 pullbacks from two registries. Images were semi-automatically labeled using our OCTOPUS with expert editing using established guidelines. We employed preprocessing including guidewire shadow detection, lumen segmentation, pixel-shifting, and Gaussian filtering on raw IVOCT (r,theta) images. Data were augmented in a natural way by changing theta in spiral acquisitions and by changing intensity and noise values. We used a modified SegResNet and comparison networks to segment FCs. We employed transfer learning from our existing much larger, fully-labeled calcification IVOCT dataset to reduce deep-learning training. Overall, our method consistently delivered better FC segmentation results (Dice: 0.837+/-0.012) than other deep-learning methods. Transfer learning reduced training time by 84% and reduced the need for more training samples. Our method showed a high level of generalizability, evidenced by highly-consistent segmentations across five-fold cross-validation (sensitivity: 85.0+/-0.3%, Dice: 0.846+/-0.011) and the held-out test (sensitivity: 84.9%, Dice: 0.816) sets. In addition, we found excellent agreement of FC thickness with ground truth (2.95+/-20.73 um), giving clinically insignificant bias. There was excellent reproducibility in pre- and post-stenting pullbacks (average FC angle: 200.9+/-128.0 deg / 202.0+/-121.1 deg). Our method will be useful for multiple research purposes and potentially for planning stent deployments that avoid placing a stent edge over an FC.Comment: 24 pages, 9 figures, 2 tables, 2 supplementary figures, 3 supplementary table

Automated analysis of fibrous cap in intravascular optical coherence tomography images of coronary arteries

Thin-cap fibroatheroma (TCFA) and plaque rupture have been recognized as the most frequent risk factor for thrombosis and acute coronary syndrome. Intravascular optical coherence tomography (IVOCT) can identify TCFA and assess cap thickness, which provides an opportunity to assess plaque vulnerability. We developed an automated method that can detect lipidous plaque and assess fibrous cap thickness in IVOCT images. This study analyzed a total of 4,360 IVOCT image frames of 77 lesions among 41 patients. To improve segmentation performance, preprocessing included lumen segmentation, pixel-shifting, and noise filtering on the raw polar (r, theta) IVOCT images. We used the DeepLab-v3 plus deep learning model to classify lipidous plaque pixels. After lipid detection, we automatically detected the outer border of the fibrous cap using a special dynamic programming algorithm and assessed the cap thickness. Our method provided excellent discriminability of lipid plaque with a sensitivity of 85.8% and A-line Dice coefficient of 0.837. By comparing lipid angle measurements between two analysts following editing of our automated software, we found good agreement by Bland-Altman analysis (difference 6.7+/-17 degree; mean 196 degree). Our method accurately detected the fibrous cap from the detected lipid plaque. Automated analysis required a significant modification for only 5.5% frames. Furthermore, our method showed a good agreement of fibrous cap thickness between two analysts with Bland-Altman analysis (4.2+/-14.6 micron; mean 175 micron), indicating little bias between users and good reproducibility of the measurement. We developed a fully automated method for fibrous cap quantification in IVOCT images, resulting in good agreement with determinations by analysts. The method has great potential to enable highly automated, repeatable, and comprehensive evaluations of TCFAs.Comment: 18 pages, 9 figure

Neoatherosclerosis prediction using plaque markers in intravascular optical coherence tomography images

IntroductionIn-stent neoatherosclerosis has emerged as a crucial factor in post-stent complications including late in-stent restenosis and very late stent thrombosis. In this study, we investigated the ability of quantitative plaque characteristics from intravascular optical coherence tomography (IVOCT) images taken just prior to stent implantation to predict neoatherosclerosis after implantation.MethodsThis was a sub-study of the TRiple Assessment of Neointima Stent FOrmation to Reabsorbable polyMer with Optical Coherence Tomography (TRANSFORM-OCT) trial. Images were obtained before and 18 months after stent implantation. Final analysis included images of 180 lesions from 90 patients; each patient had images of two lesions in different coronary arteries. A total of 17 IVOCT plaque features, including lesion length, lumen (e.g., area and diameter); calcium (e.g., angle and thickness); and fibrous cap (FC) features (e.g., thickness, surface area, and burden), were automatically extracted from the baseline IVOCT images before stenting using dedicated software developed by our group (OCTOPUS). The predictive value of baseline IVOCT plaque features for neoatherosclerosis development after stent implantation was assessed using univariate/multivariate logistic regression and receiver operating characteristic (ROC) analyses.ResultsFollow-up IVOCT identified stents with (n = 19) and without (n = 161) neoatherosclerosis. Greater lesion length and maximum calcium angle and features related to FC were associated with a higher prevalence of neoatherosclerosis after stent implantation (p < 0.05). Hierarchical clustering identified six clusters with the best prediction p-values. In univariate logistic regression analysis, maximum calcium angle, minimum calcium thickness, maximum FC angle, maximum FC area, FC surface area, and FC burden were significant predictors of neoatherosclerosis. Lesion length and features related to the lumen were not significantly different between the two groups. In multivariate logistic regression analysis, only larger FC surface area was strongly associated with neoatherosclerosis (odds ratio 1.38, 95% confidence interval [CI] 1.05–1.80, p < 0.05). The area under the ROC curve was 0.901 (95% CI 0.859–0.946, p < 0.05) for FC surface area.ConclusionPost-stent neoatherosclerosis can be predicted by quantitative IVOCT imaging of plaque characteristics prior to stent implantation. Our findings highlight the additional clinical benefits of utilizing IVOCT imaging in the catheterization laboratory to inform treatment decision-making and improve outcomes

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

ICAR: endoscopic skull‐base surgery

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