The multidirectional assessment of moderate caloric restriction and metformin treatment in obese patients

Obesity treatment is often burdensome for patients. We used the combination of moderate caloric restriction (CR) with hypoglycemic metformin to assess their multidirectional effect in obese patients. One group was treated only with moderate CR (n=21) the second was treated with moderate CR and 800 mg metformin twice daily (n=23). Serum was drawn before and after treatment. The following parameters were monitored: anthropometric, cardiovascular, inflammatory, metabolic, and markers characteristic for thyroid, liver, pancreas, and kidney functions. Both tested groups did not significantly differ in most tested parameters after the treatment. Two groups reduced anthropometric parameters (body mass, body mass index (BMI), waist circumference) and fat mass but also muscle and fat-free mass, improving systolic blood pressure, insulin and leptin concentration, insulin sensitivity, leptin to adiponectin ratio, and inflammatory markers. Unfortunately, there was little impact on improving dyslipidemia and the thyroid and liver parameters. Free triiodothyronine (fT3) and gamma glutamyl transferase (GGT) activity were decreased in both groups, but triglycerides were reduced only in patients treated with moderate CR. Metformin with CR treatment decreases uric acid and aspartate aminotransferase (AspAT) activity. Metformin treatment with moderate CR in obese patients mainly improved insulin sensitivity, resulting in a reduction of patients with glucose intolerance, improved anthropometric, cardiovascular, and inflammatory mediators, and only slightly enhanced liver and thyroid function. No changes in kidney and pancreas function were observed during the treatment. In conclusion, eight weeks of CR alone and CR with metformin in obese adults improved anthropometric and metabolic markers, reduced muscle mass, fT3, GGT, proinflammatory, and CV parameters, and displayed no changes in kidney and pancreas function. The group treated with metformin after the treatment was still more obese and had higher C-reactive protein (CRP) and homeostasis model assessment-an index of insulin resistance (HOMA-IR), but despite this, considerably reduced the number of patients with glucose intolerance.

METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII

PURPOSE

To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research quality of radiomics studies.

METHODS

We conducted an online modified Delphi study with a group of international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members to identify the items to be voted; and Stage#3, four rounds of the modified Delphi exercise by panelists to determine the items eligible for the METRICS and their weights. The consensus threshold was 75%. Based on the median ranks derived from expert panel opinion and their rank-sum based conversion to importance scores, the category and item weights were calculated.

RESULT

In total, 59 panelists from 19 countries participated in selection and ranking of the items and categories. Final METRICS tool included 30 items within 9 categories. According to their weights, the categories were in descending order of importance: study design, imaging data, image processing and feature extraction, metrics and comparison, testing, feature processing, preparation for modeling, segmentation, and open science. A web application and a repository were developed to streamline the calculation of the METRICS score and to collect feedback from the radiomics community.

CONCLUSION

In this work, we developed a scoring tool for assessing the methodological quality of the radiomics research, with a large international panel and a modified Delphi protocol. With its conditional format to cover methodological variations, it provides a well-constructed framework for the key methodological concepts to assess the quality of radiomic research papers.

CRITICAL RELEVANCE STATEMENT

A quality assessment tool, METhodological RadiomICs Score (METRICS), is made available by a large group of international domain experts, with transparent methodology, aiming at evaluating and improving research quality in radiomics and machine learning.

KEY POINTS

• A methodological scoring tool, METRICS, was developed for assessing the quality of radiomics research, with a large international expert panel and a modified Delphi protocol. • The proposed scoring tool presents expert opinion-based importance weights of categories and items with a transparent methodology for the first time. • METRICS accounts for varying use cases, from handcrafted radiomics to entirely deep learning-based pipelines. • A web application has been developed to help with the calculation of the METRICS score ( https://metricsscore.github.io/metrics/METRICS.html ) and a repository created to collect feedback from the radiomics community ( https://github.com/metricsscore/metrics ).

An Efficient Deep Neural Network to Classify Large 3D Images With Small Objects

3D imaging enables accurate diagnosis by providing spatial information about organ anatomy. However, using 3D images to train AI models is computationally challenging because they consist of 10x or 100x more pixels than their 2D counterparts. To be trained with high-resolution 3D images, convolutional neural networks resort to downsampling them or projecting them to 2D. We propose an effective alternative, a neural network that enables efficient classification of full-resolution 3D medical images. Compared to off-the-shelf convolutional neural networks, our network, 3D Globally-Aware Multiple Instance Classifier (3D-GMIC), uses 77.98%-90.05% less GPU memory and 91.23%-96.02% less computation. While it is trained only with image-level labels, without segmentation labels, it explains its predictions by providing pixel-level saliency maps. On a dataset collected at NYU Langone Health, including 85,526 patients with full-field 2D mammography (FFDM), synthetic 2D mammography, and 3D mammography, 3D-GMIC achieves an AUC of 0.831 (95% CI: 0.769-0.887) in classifying breasts with malignant findings using 3D mammography. This is comparable to the performance of GMIC on FFDM (0.816, 95% CI: 0.737-0.878) and synthetic 2D (0.826, 95% CI: 0.754-0.884), which demonstrates that 3D-GMIC successfully classified large 3D images despite focusing computation on a smaller percentage of its input compared to GMIC. Therefore, 3D-GMIC identifies and utilizes extremely small regions of interest from 3D images consisting of hundreds of millions of pixels, dramatically reducing associated computational challenges. 3D-GMIC generalizes well to BCS-DBT, an external dataset from Duke University Hospital, achieving an AUC of 0.848 (95% CI: 0.798-0.896).

Improving Information Extraction from Pathology Reports using Named Entity Recognition

Pathology reports are considered the gold standard in medical research due to their comprehensive and accurate diagnostic information. Natural language processing (NLP) techniques have been developed to automate information extraction from pathology reports. However, existing studies suffer from two significant limitations. First, they typically frame their tasks as report classification, which restricts the granularity of extracted information. Second, they often fail to generalize to unseen reports due to variations in language, negation, and human error. To overcome these challenges, we propose a BERT (bidirectional encoder representations from transformers) named entity recognition (NER) system to extract key diagnostic elements from pathology reports. We also introduce four data augmentation methods to improve the robustness of our model. Trained and evaluated on 1438 annotated breast pathology reports, acquired from a large medical center in the United States, our BERT model trained with data augmentation achieves an entity F1-score of 0.916 on an internal test set, surpassing the BERT baseline (0.843). We further assessed the model's generalizability using an external validation dataset from the United Arab Emirates, where our model maintained satisfactory performance (F1-score 0.860). Our findings demonstrate that our NER systems can effectively extract fine-grained information from widely diverse medical reports, offering the potential for large-scale information extraction in a wide range of medical and AI research. We publish our code at https://github.com/nyukat/pathology_extraction.

Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians

Predictive artificial intelligence (AI) systems based on deep learning have been shown to achieve expert-level identification of diseases in multiple medical imaging settings, but can make errors in cases accurately diagnosed by clinicians and vice versa. We developed Complementarity-Driven Deferral to Clinical Workflow (CoDoC), a system that can learn to decide between the opinion of a predictive AI model and a clinical workflow. CoDoC enhances accuracy relative to clinician-only or AI-only baselines in clinical workflows that screen for breast cancer or tuberculosis (TB). For breast cancer screening, compared to double reading with arbitration in a screening program in the UK, CoDoC reduced false positives by 25% at the same false-negative rate, while achieving a 66% reduction in clinician workload. For TB triaging, compared to standalone AI and clinical workflows, CoDoC achieved a 5-15% reduction in false positives at the same false-negative rate for three of five commercially available predictive AI systems. To facilitate the deployment of CoDoC in novel futuristic clinical settings, we present results showing that CoDoC's performance gains are sustained across several axes of variation (imaging modality, clinical setting and predictive AI system) and discuss the limitations of our evaluation and where further validation would be needed. We provide an open-source implementation to encourage further research and application.

A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis

IMPORTANCE

An accurate and robust artificial intelligence (AI) algorithm for detecting cancer in digital breast tomosynthesis (DBT) could significantly improve detection accuracy and reduce health care costs worldwide.

OBJECTIVES

To make training and evaluation data for the development of AI algorithms for DBT analysis available, to develop well-defined benchmarks, and to create publicly available code for existing methods.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study is based on a multi-institutional international grand challenge in which research teams developed algorithms to detect lesions in DBT. A data set of 22 032 reconstructed DBT volumes was made available to research teams. Phase 1, in which teams were provided 700 scans from the training set, 120 from the validation set, and 180 from the test set, took place from December 2020 to January 2021, and phase 2, in which teams were given the full data set, took place from May to July 2021.

MAIN OUTCOMES AND MEASURES

The overall performance was evaluated by mean sensitivity for biopsied lesions using only DBT volumes with biopsied lesions; ties were broken by including all DBT volumes.

RESULTS

A total of 8 teams participated in the challenge. The team with the highest mean sensitivity for biopsied lesions was the NYU B-Team, with 0.957 (95% CI, 0.924-0.984), and the second-place team, ZeDuS, had a mean sensitivity of 0.926 (95% CI, 0.881-0.964). When the results were aggregated, the mean sensitivity for all submitted algorithms was 0.879; for only those who participated in phase 2, it was 0.926.

CONCLUSIONS AND RELEVANCE

In this diagnostic study, an international competition produced algorithms with high sensitivity for using AI to detect lesions on DBT images. A standardized performance benchmark for the detection task using publicly available clinical imaging data was released, with detailed descriptions and analyses of submitted algorithms accompanied by a public release of their predictions and code for selected methods. These resources will serve as a foundation for future research on computer-assisted diagnosis methods for DBT, significantly lowering the barrier of entry for new researchers.

Application of HoloLens-based augmented reality and three-dimensional printed anatomical tooth reference models in dental education

Tooth anatomy is fundamental knowledge used in everyday dental practice to reconstruct the occlusal surface during cavity fillings. The main objective of this project was to evaluate the suitability of two types of anatomical tooth reference models used to support reconstruction of the occlusal anatomy of the teeth: (1) a three-dimensional (3D)-printed model and (2) a model displayed in augmented reality (AR) using Microsoft HoloLens. The secondary objective was to evaluate three aspects impacting the outcome: clinical experience, comfort of work, and other variables. The tertiary objective was to evaluate the usefulness of AR in dental education. Anatomical models of crowns of three different molars were made using cone beam computed tomography image segmentation, printed with a stereolithographic 3D-printer, and then displayed in the HoloLens. Each participant reconstructed the occlusal anatomy of three teeth. One without any reference materials and two with an anatomical reference model, either 3D-printed or holographic. The reconstruction work was followed by the completion of an evaluation questionnaire. The maximum Hausdorff distances (Hmax) between the superimposed images of the specimens after the procedures and the anatomical models were then calculated. The results showed that the most accurate but slowest reconstruction was achieved with the use of 3D-printed reference models and that the results were not affected by other aspects considered. For this method, the Hmax was observed to be 630 μm (p = 0.004). It was concluded that while AR models can be helpful in dental anatomy education, they are not suitable replacements for physical models.

Improving breast cancer diagnostics with deep learning for MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has a high sensitivity in detecting breast cancer but often leads to unnecessary biopsies and patient workup. We used a deep learning (DL) system to improve the overall accuracy of breast cancer diagnosis and personalize management of patients undergoing DCE-MRI. On the internal test set (n = 3936 exams), our system achieved an area under the receiver operating characteristic curve (AUROC) of 0.92 (95% CI: 0.92 to 0.93). In a retrospective reader study, there was no statistically significant difference (P = 0.19) between five board-certified breast radiologists and the DL system (mean ΔAUROC, +0.04 in favor of the DL system). Radiologists' performance improved when their predictions were averaged with DL's predictions [mean ΔAUPRC (area under the precision-recall curve), +0.07]. We demonstrated the generalizability of the DL system using multiple datasets from Poland and the United States. An additional reader study on a Polish dataset showed that the DL system was as robust to distribution shift as radiologists. In subgroup analysis, we observed consistent results across different cancer subtypes and patient demographics. Using decision curve analysis, we showed that the DL system can reduce unnecessary biopsies in the range of clinically relevant risk thresholds. This would lead to avoiding biopsies yielding benign results in up to 20% of all patients with BI-RADS category 4 lesions. Last, we performed an error analysis, investigating situations where DL predictions were mostly incorrect. This exploratory work creates a foundation for deployment and prospective analysis of DL-based models for breast MRI.

Radiological Features for Frailty Assessment in Patients Requiring Emergency Laparotomy

Introduction: As the number of elderly patients requiring surgical intervention rises, it is believed that frailty syndrome has a greater impact on perioperative course than on chronological age. The aim of this study was to evaluate the efficacy of various imaging features for frailty assessment in patients undergoing emergency laparotomy. Methods: The study included all patients that qualified for emergency surgery with preoperative CT scans between 2016 and 2020 in the Second Department of General Surgery. Multiple trauma patients were excluded from the analysis. The modified frailty index and brief geriatric assessment were used in the analysis. CT images were reviewed for the assessment of osteopenia, sarcopenia, sarcopenic obesity, renal volume and abdominal aorta calcification rate. Results: A total of 261 patients were included in the analysis. Multivariate logistic regression identified every next ASA class (OR: 4.161, 95%CI: 1.672–10.355, p = 0.002), intraoperative adverse events (OR: 12.397, 95%CI: 2.166–70.969, p = 0.005) and osteopenia (OR: 4.213, 95%CI: 1.235–14.367, p = 0.022) as a risk factor for 30-day mortality. Our study showed that every next ASA class (OR: 1.952, 95%Cl: 1.171–3.256, p = 0.010) and every point of the BGA score (OR: 1.496, 95%Cl: 1.110–2.016, p = 0.008) are risk factors for major complications. Conclusions: Osteopenia was the best parameter for perioperative mortality risk stratification in patients undergoing emergency surgical intervention. Sarcopenia (measured as psoas muscle area), sarcopenic obesity, aortic calcifications and mean kidney volume do not predict poor outcomes in those patients. None of the radiological markers appeared to be useful for the prediction of perioperative morbidity.

Soluble receptor for advanced glycation end products (sRAGE) correlates with obesity-related parameters, and it is not easy to be modified by moderate caloric restriction in obese humans

Deficiency of a soluble form of the advanced glycation end products receptor (sRAGE) is implicated in obesity-induced complications. Serum sRAGE is inclined to be modified by changes in body weight. We analysed serum sRAGE concentrations in patients with obesity undergoing moderate calorie restriction, which mimics the real-life situation and is not harmful to obese humans. Serum sRAGE was measured by immunoassay in 50 patients with obesity who underwent calorie restriction by 300-500 kcal/day for 8 weeks. In effect calorie restriction resulted in an expected decrease in body weight (by 2.1 kg for an 8-week intervention, p<0.0001), as well as reduced systolic blood pressure, modified dyslipidemia (cholesterol, triglycerides), reduced obesity-related inflammation (tumor necrosis factor-alfa, interleukin-6, C-reactive protein), improved insulin sensitivity. However, it was not accompanied by any significant change in sRAGE concentration. There was a strong negative correlation between BMI and the sRAGE level. Accordingly, the levels of sRAGE were the highest in lean control. In conclusion: a modest weight reduction is unlikely to improve decreased sRAGE levels.

Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams

Though consistently shown to detect mammographically occult cancers, breast ultrasound has been noted to have high false-positive rates. In this work, we present an AI system that achieves radiologist-level accuracy in identifying breast cancer in ultrasound images. Developed on 288,767 exams, consisting of 5,442,907 B-mode and Color Doppler images, the AI achieves an area under the receiver operating characteristic curve (AUROC) of 0.976 on a test set consisting of 44,755 exams. In a retrospective reader study, the AI achieves a higher AUROC than the average of ten board-certified breast radiologists (AUROC: 0.962 AI, 0.924 ± 0.02 radiologists). With the help of the AI, radiologists decrease their false positive rates by 37.3% and reduce requested biopsies by 27.8%, while maintaining the same level of sensitivity. This highlights the potential of AI in improving the accuracy, consistency, and efficiency of breast ultrasound diagnosis.

MarkIt: A Collaborative Artificial Intelligence Annotation Platform Leveraging Blockchain For Medical Imaging Research

Current research on medical image processing relies heavily on the amount and quality of input data. Specifically, supervised machine learning methods require well-annotated datasets. A lack of annotation tools limits the potential to achieve high-volume processing and scaled systems with a proper reward mechanism. We developed MarkIt, a web-based tool, for collaborative annotation of medical imaging data with artificial intelligence and blockchain technologies. Our platform handles both Digital Imaging and Communications in Medicine (DICOM) and non-DICOM images, and allows users to annotate them for classification and object detection tasks in an efficient manner. MarkIt can accelerate the annotation process and keep track of user activities to calculate a fair reward. A proof-of-concept experiment was conducted with three fellowship-trained radiologists, each of whom annotated 1,000 chest X-ray studies for multi-label classification. We calculated the inter-rater agreement and estimated the value of the dataset to distribute the reward for annotators using a crypto currency. We hypothesize that MarkIt allows the typically arduous annotation task to become more efficient. In addition, MarkIt can serve as a platform to evaluate the value of data and trade the annotation results in a more scalable manner in the future. The platform is publicly available for testing on https://markit.mgh.harvard.edu.

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department

During the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. We propose a data-driven approach for automatic prediction of deterioration risk using a deep neural network that learns from chest X-ray images and a gradient boosting model that learns from routine clinical variables. Our AI prognosis system, trained using data from 3661 patients, achieves an area under the receiver operating characteristic curve (AUC) of 0.786 (95% CI: 0.745-0.830) when predicting deterioration within 96 hours. The deep neural network extracts informative areas of chest X-ray images to assist clinicians in interpreting the predictions and performs comparably to two radiologists in a reader study. In order to verify performance in a real clinical setting, we silently deployed a preliminary version of the deep neural network at New York University Langone Health during the first wave of the pandemic, which produced accurate predictions in real-time. In summary, our findings demonstrate the potential of the proposed system for assisting front-line physicians in the triage of COVID-19 patients.

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department

During the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. We propose a data-driven approach for automatic prediction of deterioration risk using a deep neural network that learns from chest X-ray images and a gradient boosting model that learns from routine clinical variables. Our AI prognosis system, trained using data from 3,661 patients, achieves an area under the receiver operating characteristic curve (AUC) of 0.786 (95% CI: 0.745-0.830) when predicting deterioration within 96 hours. The deep neural network extracts informative areas of chest X-ray images to assist clinicians in interpreting the predictions and performs comparably to two radiologists in a reader study. In order to verify performance in a real clinical setting, we silently deployed a preliminary version of the deep neural network at New York University Langone Health during the first wave of the pandemic, which produced accurate predictions in real-time. In summary, our findings demonstrate the potential of the proposed system for assisting front-line physicians in the triage of COVID-19 patients.

Mixed reality interactive visualization of cardiovascular anatomy in interventional lab – clinical implementation in transvascular patent ductus arteriosus closure

Aim

Three-dimensional (3D) noninvasively acquired datasets containing anatomical information about the heart are a modern option for procedural support during percutaneous cardiac interventions. We present initial experience of patent ductus arteriosus (PDA) closure with workflow integrated with innovative mixed reality display (MRD) to improve 3D perception and navigation in 3D computed tomography angiographic (CTA) datasets.

Methods

We report incorporation of intraprocedural mixed-reality display of segmented CTA (computed tomography angiography) data using a voice- and gesture controlled head-mounted display during routine percutaneous occlusions of PDA in adults. A dedicated software pathway was used for files conversion, real-time Wi-Fi streaming of 3D rendering from PC to device and manipulation of spatial data during the procedures.

Results

Pre-recorded CTA studies of aorta and ductus were manually segmented and uploaded into custom designed 3D DICOM for realtime export to MRD device. 3D holograms were successfully displayed during the procedure by commercially available head-mounted display allowing touchless control and image sharing within cath-lab. Wiring of PDA aortic orifice was assisted by 3D hologram controlled by the imaging specialist and shared by the operator. Thus, MRD using evolving versions of custom software was successfully executed with segmented data presented as a semitransparent cubic hologram positioned in a convenient part of visual field allowing real-world action and with touchless control by medical team. Operator appreciated the use of MRD hologram realistically visualizing spatial relationships as practical aid to establish anatomical relationships and facilitate entry into ductus orifice. Procedures were successfully completed using arteriovenous guidewire loop to implant vascular occluders.

Conclusions

We demonstrate the methodology and software evolution (segmentation, data fusion) allowing practical implementation of intraprocedural mixed reality display of 3D CTA data, with sterile, touchless control of holographic image shared by interventional and imaging team to support percutaneous PDA closure.

Funding Acknowledgement

Type of funding source: Private company. Main funding source(s): MEDAPP

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department

During the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. We propose a data-driven approach for automatic prediction of deterioration risk using a deep neural network that learns from chest X-ray images and a gradient boosting model that learns from routine clinical variables. Our AI prognosis system, trained using data from 3,661 patients, achieves an area under the receiver operating characteristic curve (AUC) of 0.786 (95% CI: 0.745-0.830) when predicting deterioration within 96 hours. The deep neural network extracts informative areas of chest X-ray images to assist clinicians in interpreting the predictions and performs comparably to two radiologists in a reader study. In order to verify performance in a real clinical setting, we silently deployed a preliminary version of the deep neural network at New York University Langone Health during the first wave of the pandemic, which produced accurate predictions in real-time. In summary, our findings demonstrate the potential of the proposed system for assisting front-line physicians in the triage of COVID-19 patients.

Radiological Society of North America (RSNA) 3D Printing Special Interest Group (SIG) clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: abdominal, hepatobiliary, and gastrointestinal conditions

Background

Medical 3D printing has demonstrated value in anatomic models for abdominal, hepatobiliary, and gastrointestinal conditions. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (SIG) provides appropriateness criteria for abdominal, hepatobiliary, and gastrointestinal 3D printing indications.

Methods

A literature search was conducted to identify all relevant articles using 3D printing technology associated with a number of abdominal pathologic processes. Each included study was graded according to published guidelines.

Results

Evidence-based appropriateness guidelines are provided for the following areas: intra-hepatic masses, hilar cholangiocarcinoma, biliary stenosis, biliary stones, gallbladder pathology, pancreatic cancer, pancreatitis, splenic disease, gastric pathology, small bowel pathology, colorectal cancer, perianal fistula, visceral trauma, hernia, abdominal sarcoma, abdominal wall masses, and intra-abdominal fluid collections.

Conclusion

This document provides initial appropriate use criteria for medical 3D printing in abdominal, hepatobiliary, and gastrointestinal conditions.

Simulation and Training of Needle Puncture Procedure with a Patient-Specific 3D Printed Gluteal Artery Model

The puncture of the gluteal artery (GA) is a rare and difficult procedure. Less experienced clinicians do not always have the opportunity to practice and prepare for it, which creates a need for novel training tools. We aimed to investigate the feasibility of developing a 3D-printed, patient-specific phantom of the GA and its surrounding tissues to determine the extent to which the model can be used as an aid in needle puncture planning, simulation, and training. Computed tomography angiography scans of a patient with an endoleak to an internal iliac artery aneurysm with no intravascular antegrade access were processed. The arterial system, including the superior GA with its division branches, and pelvic area bones were 3D printed. The 3D model was embedded in the buttocks-shaped, patient-specific mold and cast. The manufactured, life-sized phantom was used to simulate the GA puncture procedure and was validated by 13 endovascular specialists. The printed GA was visible in the fluoroscopy, allowing for a needle puncture procedure simulation. The contrast medium was administered, simulating a digital subtraction angiography. Participating doctors suggested that the model could make a significant impact on preprocedural planning and resident training programs. Although the results are promising, we recommend that further studies be used to adjust the design and assess its clinical value.

Automatic aorta and left ventricle segmentation for TAVI procedure planning using convolutional neural networks

Transcatheter aortic valve implantation (TAVI) is a minimally invasive procedure which is performed on patients with aortic valve defects that are posing a high-risk for conducting a surgical treatment. Preoperative surgical planning and valve sizing play a crucial role in reducing surgery complications and adverse effects such as paravalvular leakage or stroke. Planning process incorporates performing measurements, detecting landmarks and visualizing relevant structures in 3D. To automatize this process, a segmentation is required. Due to the lack of methods enabling parallel aorta and left ventricle segmentation we propose a fully automatic neural network approach based on 2D U-Net architecture. Convolutional neural network architecture was trained on 44 studies (22 raw CTA datasets and 22 elastic deformed scans) and tested on another 18 stacks of data. During every epoch of network learning process cross validation was performed on 8 stacks. As a result, we achieve 0.95 mean Dice coefficient score with standard deviation 0.02 determining high precision of predicted aorta and left ventricle label maps.

A systematic review and meta-analysis of laparoscopic versus robotic rectal surgery with primary anastomosis

PURPOSE

Rectal cancer is one of the most common malignancies of the gastrointestinal tract. The gold standard method is surgical resection. The approach to rectal cancer is still controversial. Nowadays, robotic approach gains popularity in comparison to traditional laparoscopy. However, there is lack of studies assessing rectal resections with primary anastomosis.

METHODS

We performed a systematic review and meta-analysis according to the PRISMA guidelines. The primary outcomes of interest were morbidity and short-term complications.

RESULTS

An initial reference search yielded 1250 articles. Finally, we chose six studies covering 1580 patients that we included in the quantitative analysis. In our study, we demonstrated that laparoscopic and robotic surgery are non-inferior to one another in terms of morbidity (RR=1.1 95% CI: 0.89-1.39), major complication rate (RR=1.01, 95% CI: 0.60-1.69) or in length of hospitalization (MD=0,15 95% CI: -0.60-0.90). The latter has slight advantage in quality of mesorectal excision (RD = -0.19, 95% CI: -0.35 - -0.03. I2=69%) and anastomotic leakage rate (OR=2.25, 95% CI: 1.23-4.09, I2=0%).

CONCLUSION

In certain cases Robotic Surgery provide better quality of resected specimen and lower leakage ratio, nevertheless due to heterogeneity the results are uncertain. There is substantial need for large randomized controlled studies.

Functional outcomes after resections for low rectal tumors: comparison of Transanal with laparoscopic Total Mesorectal excision

Background

Aim of this study was to evaluate functional outcomes of transanal total mesorectal excision (TaTME) in comparison to conventional laparoscopic approach (LaTME) in terms of low anterior resection syndrome (LARS).

Methods

Forty-six patients who underwent total mesorectal excision for low rectal cancer between 2013 and 2017 were enrolled. Primary outcome was the severity of faecal incontinence, assessed both before the treatment and 6 months after ileostomy reversal. LARS score and Jorge-Wexner scale were utilized to analyze its severity.

Results

Twenty (87%) from TaTME and 21 (91%) from LaTME group developed LARS postoperatively. There were no significant differences between groups in terms of LARS occurrence (p = 0.63) and severity. The median Wexner score was comparable in both groups (8 [IQR: 4–12] vs 7 [3–11], p = 0.83). Univariate analysis revealed that postoperative complications were a risk factor for LARS development (p = 0.02). Perioperative outcomes, including operative time, blood loss and intraoperative adverse events did not differ significantly between groups either. Five TaTME patients developed postoperative complications, while there were morbidity 6 cases in LaTME group. Quality of mesorectal excision was comparable with 20 and 19 complete cases in TaTME and LaTME groups, respectively.

Conclusions

TaTME provided comparable outcomes in terms of functional outcomes in comparison to LaTME for total mesorectal excision in low rectal cancers. Having said that, LARS prevalence is still high and requires further evaluation of the technique.

Holographically-Guided Endovascular Aneurysm Repair

Purpose: To demonstrate the feasibility of augmented reality visualization in planning and navigating endovascular aortic repair. Technique: A 77-year-old patient with abdominal aortic aneurysm was treated with endovascular repair. An augmented reality head-mounted display was used during the procedure. The aneurysm and bones were projected as 3-dimensional holograms. The operator controlled the device with gestures and voice commands (movement, rotation, cutting through, and zooming). Moreover, the hologram was placed in front of the angiography monitor and manually registered with fluoroscopy. Conclusion: Augmented reality with holographic rendering is feasible and helpful during endovascular aortic repair. Its routine use could possibly lead to shorter operating time, reduced contrast volume, and lower radiation dose; however, larger studies are required to obtain statistically significant results on the outcomes.

What Makes Bariatric Operations Difficult-Results of a National Survey

Background and objective: The most commonly performed bariatric procedures include laparoscopic sleeve gastrectomy (LSG), laparoscopic Roux-en-Y gastric bypass (LRYGB), and one anastomosis gastric bypass-mini gastric bypass (OAGB-MGB). A study comparing the degree of difficulty among those procedures could serve as a guide for decision making in bariatric surgery and further improve training programs for general surgery trainees. The aim of this study was to compare the subjective level of technical difficulty of LSG, LRYGB, and OAGB-MGB as perceived by surgeons and surgical residents. Materials and Methods: An anonymous internet-based survey was designed to evaluate the subjective opinions of surgeons and surgical residents in training in Poland. It covered baseline characteristics of the participants, difficulty of LSG, OAGB-MGB, LRYGB and particular stages of each operation assessed on a 1-5 scale. Results: Overall, 70 surgeons and residents participated in our survey. The mean difficulty degree of LSG was 2.34 ± 0.89. The reinforcing staple line with sutures was considered most difficult stage of this operation (3.17 ± 1.19). The LRYGB operation had an average difficulty level of 3.87 ± 1.04. Creation of the gastrojejunostomy was considered the most difficult stage of LRYGB with a mean difficulty level (3.68 ± 1.16). Responders to our survey assessed the mean degree of difficulty of OAGB-MGB as 2.34 ± 0.97. According to participating surgeons, creating the gastrojejunostomy is the most difficult phase of this operation (3.68 ± 1.16). Conclusion: The LSG is perceived by surgeons as a relatively easy operation. The LRYGB was considered to be the most technically challenging procedure in our survey. Operative stages, which require intra-abdominal suturing with laparoscopic instruments, seem to be the most difficult phases of each operation.

Enhanced recovery after surgery (ERAS) programs for esophagectomy

A perioperative treatment protocol, enhanced recovery after surgery (ERAS) focuses on accelerating patient recovery. Previous studies confirmed that ERAS decreases surgical trauma and the stress response, which improved outcomes including reduced length of hospital stay (LOS) and decreased postoperative morbidity. While ERAS protocols have been successfully implemented in a variety of surgical disciplines (colorectal, bariatric, orthopedic, and gynecologic surgery), its use in esophageal surgery is still limited. This paper analyzes the feasibility and value of the ERAS protocol for esophageal surgery. Reviewing the literature found that implementation of ERAS resulted in decreased costs, length of stay and pulmonary specific complication reduction, but not overall morbidity. The evidence lacks randomized control trials. Further, the ERAS Society published recommendations for esophageal resection. This opportunity for unification of the protocol would make the studies more comparable and leads to stronger conclusions. Surgery specific items also require further confirmation. Nonetheless, the successful introduction of the ERAS protocol into a wide variety of surgical disciplines provides optimism for ERAS's effectiveness in esophageal surgery.

Augmented reality and three-dimensional printing in percutaneous interventions on pulmonary arteries

Background

Percutaneous pulmonary interventions require extensive and accurate navigation planning and guidance, especially in regard to the three-dimensional (3D) relationships between anatomical structures. In this study, we are demonstrating the feasibility of novel visualization techniques: 3D printing (3DP) and augmented reality (AR) in planning transcatheter pulmonary interventions.

Methods

Two patients were qualified for balloon pulmonary angioplasty (BPA) for treatment of chronic thromboembolic pulmonary hypertension (CTEPH) and stent implantation for pulmonary artery stenosis, respectively. Computed tomography images of both patients were processed with segmentation algorithms and subsequently submitted to 3D modelling software. Microsoft HoloLens^® AR headsets with dedicated CarnaLife Holo^® software were utilized to display surface and volume rendering of pulmonary vessels as holograms.

Results

Personalized life-sized models of the same structures were additionally 3D-printed for preoperative planning. Holograms were shown to physicians throughout the procedure and were used as a guidance and navigation tool. Operative team was able to manipulate the hologram and multiple users of the AR system could share the same image in real time. Clinicians expressed their satisfaction with the quality of imaging and potential clinical benefits.

Conclusions

This study reports the potential value of AR in pulmonary interventions, however, prospective trials need to be conducted to decide on whether novel 3D visualization techniques affect perioperative treatment and outcomes.

Investigating accuracy of 3D printed liver models with computed tomography

Background

The aim of this study was to evaluate the accuracy of three-dimensional (3D) printed liver models developed by a cost-effective approach for establishing validity of using these models in a clinical setting.

Methods

Fifteen patients undergoing laparoscopic liver resection in a single surgical department were included. Patient-specific, 1-1 scale 3D printed liver models including the liver, tumor, and vasculature were created from contrast-enhanced computed tomography (CT) images using a cost-effective approach. The 3D models were subsequently CT scanned, 3D image post-processing was performed, and these 3D computer models (MCT) were compared to the original 3D models created from the original patient images (PCT). 3D computer models of each type were co-registered using a point set registration method. 3D volume measurements of the liver and lesions were calculated and compared for each set. In addition, Hausdorff distances were calculated and surface quality was compared by generated heatmaps.

Results

The median liver volume in MCT was 1,281.84 [interquartile range (IQR) =296.86] cm³, and 1,448.03 (IQR =413.23) cm³ in PCT. Analysis of differences between surfaces showed that the median value of mean Hausdorff distances for liver parenchyma was 1.92 mm. Bland-Altman plots revealed no significant bias in liver volume and diameters of hepatic veins and tumor location. Median errors of all measured vessel diameters were smaller than CT slice height. There was a slight trend towards undersizing anatomical structures, although those errors are most likely due to source imaging.

Conclusions

We have confirmed the accuracy of 3D printed liver models created by using the low-cost method. 3D models are useful tools for pre-operative planning and intra-operative guidance. Future research in this field should continue to move towards clinical trials for assessment of the impact of these models on pre-surgical planning decisions and perioperative outcomes.

Postoperative Care and Functional Recovery After Laparoscopic Sleeve Gastrectomy vs. Laparoscopic Roux-en-Y Gastric Bypass Among Patients Under ERAS Protocol

Background

The most commonly performed bariatric procedures are laparoscopic sleeve gastrectomy (LSG) and laparoscopic Roux-en-Y gastric bypass (LRYGB). There are major differences between LSG and LRYGB during postoperative period. Optimization of the postoperative care may be achieved by using enhanced recovery after surgery (ERAS) protocol, which allows earlier functional recovery.

Purpose

The aim was to assess differences in the course of postoperative care conducted in accordance with ERAS protocol among patients after LSG and LRYGB.

Material and Methods

Data concerning patients treated for morbid obesity were prospectively gathered in one academic center. Patients were divided into two groups: LSG (n = 364, 63.41%) and LRYGB (n = 210, 36.59%). Multiple factors were used as endpoints to determine the influence of the type of bariatric procedure on postoperative course.

Results

The rate of postoperative nausea and vomiting and incidence of intravenous fluid administration during the operation was higher in LSG group. LRYGB patients were able to tolerate higher oral fluid intake volumes during the first and the second postoperative day. Mean diuresis during the second and the third postoperative day was significantly higher in LRYGB group. Administration of diuretics and painkillers was comparable between groups, while the risk of fever after the operation was higher in LRYGB group. Mean length of stay was higher in LSG group (LRYGB vs. LSG, 3.46 days ± 1.58 vs. 3.64 days ± 4.41, p = 0.039).

Conclusions

In our opinion, postoperative treatment after LSG requires more supervision and longer time until functional recovery is achieved.

The role of purinergic P2Y12 receptor blockers on the angiogenic properties of endothelial cells: an in vitro study

Pharmacotherapy with agents that inhibit platelet function has proven to be effective in the treatment of acute coronary syndrome. Proper re-endothelization after angioplasty prevents adverse cardiovascular events. Therefore, in this in vitro study we examined how antiplatelet P2Y₁₂ receptor blockers can affect endothelial cells' angiogenic properties. Endothelial cells were exposed to ticagrelor, prasugrel and clopidogrel in their highest concentrations obtained in serum after the treatment with loading and clinical doses. Further, the viability, apoptosis, and necrosis were tested and the following angiogenic properties such as proliferation, migration, invasiveness, tube formation, wound healing and the production of angiogenic mediators (bFGF, PDGF, MMP-2, Ang-2, TIMP-1). The results of this study showed that P2Y₁₂ receptor blockers in the tested concentrations are safe for endothelial cells. They neither induced necrosis or apoptosis nor changed the endothelial cell viability, migration, invasiveness, tube formation, wound healing, the production of VEGF or its receptors. However, they reduced cell proliferation. It was shown that out of these three drugs, ticagrelor in its loading concentration had the most potent angiogenic property. It reduced cell proliferation and changed the production of angiogenic (bFGF, MMP-2) and angiostatic mediators (Ang-2). In conclusion, P2Y₁₂ receptor blockers in the concentrations obtained in the serum during standard therapy reduced endothelial cell proliferation. Despite this slight antimitogenic effect, they did not change endothelial cell tube formation or wound healing. Out of the three tested drugs, ticagrelor had the most potent angiogenic effect in vitro, but not strong enough to disturb tube formation and wound healing.

From ideas to long-term studies: 3D printing clinical trials review

PURPOSE

Although high costs are often cited as the main limitation of 3D printing (3DP) in the medical field, current lack of clinical evidence is asserting itself as an impost as the field begins to mature. The aim is to review clinical trials in the field of 3DP, an area of research which has grown dramatically in recent years.

METHODS

We surveyed clinical trials registered in 15 primary registries worldwide, including ClinicalTrials.gov. All trials which utilized 3DP in a clinical setting were included in this review. Our search was performed on December 15, 2017. Data regarding the purpose of the study, inclusion criteria, number of patients enrolled, primary outcomes, centers, start and estimated completion dates were extracted.

RESULTS

A total of 92 clinical trials with [Formula: see text]252 patients matched the criteria and were included in the study. A total of 42 (45.65%) studies cited China as their location. Only 10 trials were multicenter and 2 were registered as international. The discipline that most commonly utilized 3DP was Orthopedic Surgery, with 25 (27.17%) registered trials. At the time of data extraction, 17 (18.48%) clinical trials were complete.

CONCLUSIONS

After several years of case reports, feasibility studies and technical reports in the field, larger-scale studies are beginning to emerge. There are almost no international register entries. Although there are new emerging areas of study in disciplines that may benefit from 3DP, it is likely to remain limited to very specific applications.

Current status of enhanced recovery after surgery (ERAS) protocol in gastrointestinal surgery

Enhanced Recovery After Surgery (ERAS) is an evidence-based paradigm shift in perioperative care, proven to lower both recovery time and postoperative complication rates. The role of ERAS in several surgical disciplines was reviewed. In colorectal surgery, ERAS protocol is currently well established as the best care. In gastric surgery, 2014 saw an establishment of ERAS protocol for gastrectomies with resulting meta-analysis showing ERAS effectiveness. ERAS has also been shown to be beneficial in liver surgery with many centers starting implementation. The advantages of ERAS in pancreatic surgery have been strongly established, but there is still a need for large-scale, multicenter randomized trials. Barriers to implementation were analyzed, with recent studies concluding that successful implementation requires a multidisciplinary team, a willingness to change and a clear understanding of the protocol. Additionally, the difficulty in accomplishing necessary compliance to all protocol items calls for new implementation strategies. ERAS success in different patient populations was analyzed, and it was found that in the elderly population, ERAS shortened the length of hospitalization and did not lead to a higher risk of postoperative complications or readmissions. ERAS utilization in the emergency setting is possible and effective; however, certain changes to the protocol may need to be adapted. Therefore, further research is needed. There remains insufficient evidence on whether ERAS actually improves patients’ course in the long term. However, since most centers started to implement ERAS protocol less than 5 years ago, more data are expected.

Defunctioning ileostomy reduces leakage rate in rectal cancer surgery - systematic review and meta-analysis

Objectives

The role of a defunctioning ileostomy in every anterior rectal resection with total mesorectal excision (TME) is still controversial. In this study, we aimed to review the current literature to determine the impact of ileostomy creation on postoperative outcomes in patients undergoing anterior rectal resection with TME.

Methods

MEDLINE, Embase and Cochrane Library were searched for eligible studies. We analyzed data up to October 2017. Eligible studies had to compare patients with vs. without a defunctioning ileostomy in rectal cancer surgery and comprise data on anastomotic leakage in both groups. The primary outcome was anastomotic leakage. Secondary outcomes included the complication rate, mortality, reoperation rate, length of hospital stay and 30-day readmission.

Results

Initial search yielded 1,966 articles. Thorough evaluation resulted in 13 eligible articles which were analyzed. Leakage rate (RR = 0.43, 95% CI 0.28-0.67) and the number of reoperations (RR = 0.62, 95% CI 0.40-0.94) were significantly lower in the defunctioning stoma group. Morbidity was significantly higher in the stoma group (RR = 1.32, 95% CI 1.05–1.65). Analysis of mortality, length of hospital stay and readmission rate did not show any significant differences.

Conclusion

A defunctioning ileostomy may decrease the anastomotic leakage rate, additionally significantly reducing the risk of reoperations but it may also increase the overall complication rate. The presence of the protective stoma has no effect on mortality, length of hospital stay and readmission rate.

Correlation between HSP-72 Expression and IL-8 Secretion in Human Mesothelial Cells

Background

Cytotoxicity of peritoneal dialysis fluid (PDF) and peritoneal inflammation are currently regarded as the two major culprits for chronic mesothelial injury and peritoneal membrane failure. In this study, we correlated induction of HSP-72, as a marker of the cellular stress response, to secretion of IL-8, as a marker for pro-inflammatory cytokines, in mesothelial cells upon sublethal PDF exposure.

Methods

Primary omental cell cultures of human mesothelial cells were subjected to sublethal PDF exposure times (CAPD2, Fresenius, Germany). At the end of a 24 hour recovery period, induction of HSP-72 in the cell homogenate and IL-8 secretion in the supernatant was assessed by immunodensitometry and ELISA, respectively.

Results

PDF exposure times from 15 min to 60 min resulted in progressively increased HSP-72 expression levels (267 vs 320 vs 419% of controls, p<0.05 vs controls) as well as increased IL-8 secretion (323 vs 528 vs 549% of controls, p<0.05 vs controls) with full cell viability (MTT unchanged to control). HSP-72 expression was statistically significantly correlated with IL-8 secretion. Conclusions: The significant correlation between HSP-72 expression and IL-8 secretion suggests that the regulation of pro-inflammatory pathways in mesothelial cells exposed to PDF may represent an integral part of their stress response. Future studies to investigate the cellular regulatory mechanism involved are warranted.

Primary tumor resection in stage IV unresectable colorectal cancer: what has changed?

Most current guidelines do not recommend primary tumor resection in stage IV unresectable colorectal cancer. Rapid chemotherapy development over the last decade has substantially changed the decision making. However, results of recently published trials and meta-analyses suggest that primary tumor resection may in fact be beneficial, principally in terms of prolonged survival. Additional factors, such as use of minimally invasive approach or protocols of enhanced recovery after surgery, affect clinical outcomes as well, but are often neglected when discussing the state of the art in this area. There are still no randomized studies determining the legitimacy of upfront surgery in asymptomatic patients. Also, quality of life also plays an important role in choosing appropriate treatment. Having said that, there is no data that would prove whether primary tumor resection has an advantage on that issue. With all the uncertainty, currently decision making in unresectable stage IV colorectal cancer is primarily up to clinicians' knowledge, common sense and patients' preferences.

There is no difference in outcome between laparoscopic and open surgery for rectal cancer: a systematic review and meta-analysis on short- and long-term oncologic outcomes

Background

Until recently there has been little data available about long-term outcomes of laparoscopic rectal cancer surgery. But new randomized controlled trials regarding laparoscopic colorectal surgery have been published. The aim of this study was to compare the short- and long-term oncologic outcomes of laparoscopy and open surgery for rectal cancer through a systematic review of the literature and a meta-analysis of relevant RCTs.

Methods

A systematic review of Medline, Embase and the Cochrane library from January 1966 to October 2016 with a subsequent meta-analysis was performed. Only randomized controlled trials with data on circumferential resection margins were included. The primary outcome was the status of circumferential resection margins. Secondary outcomes included lymph node yield, distal resection margins, disease-free and overall survival rates for 3 and 5 years and local recurrence rates.

Results

Eleven studies were evaluated, involving a total of 2018 patients in the laparoscopic group and 1526 patients in the open group. The presence of involved circumferential margins was reported in all studies. There were no statistically significant differences in the number of positive circumferential margins between the laparoscopic group and open group, RR 1.16, 95% CI 0.89–1.50 and no significant differences in involvement of distal margins (RR 1.13 95% CI 0.35–3.66), completeness of mesorectal excision (RR 1.22, 95% CI 0.82–1.82) or number of harvested lymph nodes (mean difference = −0.01, 95% CI −0.89 to 0.87). Disease-free survival rates at 3 and 5 years were not different (p = 0.26 and p = 0.71 respectively), and neither were overall survival rates (p = 0.19 and p = 0.64 respectively), nor local recurrence rates (RR 0.88, 95% CI 0.63–1.23).

Conclusions

Laparoscopic surgery for rectal cancer is associated with similar short-term and long-term oncologic outcomes compared to open surgery. The oncologic quality of extracted specimens seems comparable regardless of the approach used.

Electronic supplementary material

The online version of this article (doi:10.1007/s10151-017-1662-4) contains supplementary material, which is available to authorized users.

Weight loss-dependent and -independent effects of moderate calorie restriction on endothelial cell markers in obesity

Endothelial cell dysfunction in obesity can be reduced by calorie restriction (CR), however it is unclear whether this benefit requires a concomitant weight loss or is it simply related to the reduced calorie intake per se. In our study serum was drawn from 41 obese women who were undergoing an 8-week dietary intervention with 15 - 30% energy deficit, and from 48 age- and sex-matched controls of normal weight. Serum was analysed for biomarkers of endothelial cell function, oxidative stress and inflammation. Compared with non-obese individuals, the obese patients had lower serum levels of nitric oxide (NO), adiponectin, and decreased serum antioxidant status. They also had significantly higher levels of adhesive molecules, thrombomodulin (TM), von Wilebrand factor (vWF), asymmetric dimethylarginine (ADMA), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and leptin. To further characterize the effect of moderate CR, the patients were ranked into two comparable groups according to the extent of weight loss - below and above the median (-5.8 kg). A moderate dietary intervention did not correct adiponectin, antioxidant status, vWF, TM, and plasminogen activator inhibitor-1 (PAI-1) but ameliorated changes in other parameters. Only changes in NO and - to a lesser degree - in sE-selectin showed a clear relationship with the magnitude of weight reduction. By contrast, a beneficial reduction in TNF-α occurred equally in patients who lost more or less weight after caloric restriction. We concluded that moderate calorie restriction could still improve several parameters of endothelial cell function irrespective of whether it was accompanied by changes in body mass. However, a significant improvement in nitric oxide, a key mediator of endothelial well-being, requires a substantial reduction in body weight.

The role of mTOR inhibitors and HMG-CoA reductase inhibitors on young and old endothelial cell functions, critical for re-endothelialisation after percutaneous coronary intervention: an in vitro study

Percutaneous coronary intervention (PCI) has become a standard treatment in patients with acute coronary syndrome. However, it is associated with endothelial cell denudation, which may predispose to in-stent thrombosis and restenosis. Pharmacological methods which prevent restenosis can delay post-PCI re-endothelialisation. We have therefore examined how atorvastatin (HMG-CoA reductase inhibitor), sirolimus and everolimus (mTOR inhibitors) affect young and old endothelial cell functions which are responsible for wound healing after PCI. Replicative senescence was induced by serial passages of human umbilical vein endothelial cells (HUVECs). The cells which were examined at their first passages and last passages were designated as 'young' and 'old' respectively. Young and old endothelium were grown to confluence and were wounded by scraping. Scratch healing in the presence or absence of atorvastatin (AT), rapamycin (SR) and everolimus (EV) was monitored by time-lapse microscopy. In addition cells were assessed for viability (MTT assay), migration (chemotaxis chamber), proliferation (³H-thymidine), and cytokine production (immunoassays). Senescent endothelial cells produce more proinflammatory cytokines, angiogenic VEGF and extracellular matrix proteins. They stop proliferating and have diminished migration. When compared to young endothelium, they have similar viability and can regenerate wounds in comparable time. The drugs that have been tested have anti-inflammatory properties but even after pretreatment old cells still produced significantly higher concentration of tested mediators in comparison with young ones. In the concentration obtained in serum after stent implantation, mTOR inhibitors in dose-dependent manner reduced cell proliferation, migration and wound healing. Reduced healing is more pronounced in young endothelium. Atorvastatin, at clinically relevant concentration, is safe for young and old cells. Atorvastatin, sirolimus and everolimus inhibited the secretion of pro-inflammatory mediators in young and old endothelium. In concentrations seen in serum during standard therapy, rapalogs impair endothelial cell regeneration after injuries mimicking those occurring during PCI, while atorvastatin does not affect the healing.

Simple obesity and renal function

Increasing evidence accumulate to suggest that obesity increases the risk of chronic kidney disease independently of dyslipidemia, diabetes, and hypertension. This so-called obesity-related glomerulopathy is characterized at early stages by glomerular hypertrophy with or without secondary focal segmental glomerulosclerosis. Since, however, kidney biopsies are usually not performed at this phase, an early diagnosis of the disease is often difficult. Here, we review new developments in the pathophysiology of obesity-associated kidney dysfunction and discuss the potential of appropriate monitoring of glomerular filtration rate and albuminuria for early detection of the disease. We also present the benefits conferred by even moderate dietary restriction on the course of the disease.

Atorvastatin does not impair endothelial cell wound healing in an in vitro model of vascular injury

Percutaneous coronary intervention (PCI) became standard treatment modality for coronary revascularization. However, it is associated with endothelial cell denudation, which may predispose to in-stent thrombosis and restenosis. Since statins may inhibit vascular cell proliferation, one may fear that their early administration will delay post-PCI re-endothelialization. We have therefore employed an in vitro scratch assay to examine how atorvastatin affects endothelial cell wound healing. Human umbilical vein endothelial cells (HUVEC) were grown to confluence and wounded by scraping. Scratch healing in the presence or absence of atorvastatin was monitored by time-lapse photo-microscopy. In addition cells were assessed for viability (MTT assay), migration (chemotaxis chamber), proliferation ((3)H-thymidine and bromodeoxyuridine incorporation), and cytokine production (immunoassays). The exposure of HUVEC to atorvastatin resulted in a dose-dependent decrease in cell viability and proliferation. However, this effect was observed only at doses ≥1 μM, which is well above the concentrations seen in vivo. At clinically relevant doses (≤0.1 μM) atorvastatin did not impair wound closure, nor did it inhibit cell viability, proliferation, and migration. It did however reduce the constitutive and the stimulated release of cytokines (IL-6, IL-8, MCP-1), adhesion molecules (sICAM-1) and matrix proteins (fibronectin). We conclude that atorvastatin at doses corresponding to concentrations seen in serum during standard therapy does not impair endothelial cell regeneration after injuries mimicking those occurring during PCI. It does, however, inhibits the secretion of pro-inflammatory mediators.

Comparison of icodextrin- and glucose-based peritoneal dialysis fluids in their acute and chronic effects on human peritoneal mesothelial cells

BACKGROUND

Icodextrin-based peritoneal dialysis fluids (PDFs) display several features that may potentially improve their biocompatibility compared to conventional glucose-containing solutions. So far, however, the studies assessing the biocompatibility profile of icodextrin toward human peritoneal mesothelial cells (HPMC) has produced mixed results. The present study was performed to examine the acute and chronic impact of icodextrin on HPMC in vitro in comparison with standard glucose-based PDF.

METHODS

Omentum-derived HPMC were either acutely pre-exposed to or incubated chronically (for up to 10 days) in the presence of icodextrin-PDF. Parallel cultures were treated with conventional PDFs containing either 1.5% or 4.25% glucose. All fluids were tested at neutral pH. HPMC were assessed for viability, proliferation, IL-6 secretion and generation of reactive oxygen species (ROS).

RESULTS

Incubation in the presence of icodextrin-PDF significantly reduced HPMC proliferation in a manner similar to that of 1.5% glucose-PDF. In addition, exposure to icodextrin-PDF impaired viability and IL-6 release from HPMC. This effect occurred both after the short pre-treatment with neat icodextrin-PDF for 1-4 hours and after prolonged incubation (up to 10 days) in media supplemented with icodextrin-PDF (1:1). The dysfunction of icodextrin-treated HPMC was of the magnitude that was between the effects exerted by 1.5%- and 4.25%-glucose PDF. Furthermore, exposure of HPMC to icodextrin-PDF induced a dose-dependent increase in ROS generation which was comparable to that produced by 1.5%-glucose PDF.

CONCLUSION

Exposure to icodextrin-PDF may impair viability and function of HPMC. The detrimental effects of icodextrin-PDF are at least as serious as those produced by conventional heat-sterilized low glucose-based PDF.

PD and loss of peritoneal function

During long-term treatment with peritoneal dialysis both peritoneal membrane structure and function undergo significant changes that not only correlate with the time under treatment, but also with the frequency and severity of infections. In addition, peritoneal dialysis fluid bio-incompatibility may constitute a hazard for the longevity of the peritoneum as the dialysis membrane. In particular, the presence of glucose degradation products may lead to impaired peritoneal cell function as well as to increased protein glycation and peritoneal AGE deposition. Results from recent prospective randomised studies suggest that treatment with new GDP-depleted PD fluids may lead to a significant improvement of clinical outcomes in PD patients.

Role of mesothelial cell-derived granulocyte colony-stimulating factor in interleukin-17-induced neutrophil accumulation in the peritoneum

Recent studies suggest that peritoneal CD4(+) T lymphocytes may control recruitment of polymorphonuclear leukocytes (PMN) during peritonitis by an interleukin-17 (IL-17)-dependent mechanism. IL-17 and granulocyte colony-stimulating factor (G-CSF) have been proposed to form an axis that regulates PMN transmigration. Here we report on the role of G-CSF released by human peritoneal mesothelial cells (HPMCs) in IL-17A-mediated peritoneal PMN accumulation. In vitro exposure of HPMCs to IL-17A resulted in a time- and dose-dependent release of G-CSF. This effect was related to the induction of G-CSF mRNA and mediated through the nuclear factor-kappaB (NF-kappaB) pathway. The novel observation was that IL-17A-stimulated NF-kappaB activation in HPMCs followed a biphasic profile, with an early induction (45 min), followed by the return to basal levels (90 min), and a delayed induction (3 h). Tumor necrosis factor alpha synergistically amplified IL-17A-induced G-CSF production by enhanced NF-kappaB activation and through stabilization of G-CSF mRNA. Intraperitoneal (i.p.) administration of IL-17A in Balb/c mice resulted in increased local levels of G-CSF and selective PMN accumulation. Administration of anti-G-CSF blocking antibody before IL-17A injection significantly reduced the IL-17A-triggered PMN infiltration. This effect occurred despite increased i.p. levels of PMN-specific chemokines KC and macrophage inflammatory protein-2 seen in animals treated with anti-G-CSF antibody. These data demonstrate that the mesothelium-derived G-CSF plays an important role in IL-17A-induced PMN recruitment into the peritoneum.

Interleukin-17: a mediator of inflammatory responses

Interleukin-17 (IL-17) is a prototype member of a new cytokine family with six species identified to date. IL-17 is secreted mainly by activated CD4(+) and CD8(+) T lymphocytes, while its receptor is distributed ubiquitously. IL-17 has been classified as a proinflammatory cytokine because of its ability to induce the expression of many mediators of inflammation, most strikingly those that are involved in the proliferation, maturation and chemotaxis of neutrophils. Increased levels of IL-17 have been associated with several conditions, including airway inflammation, rheumatoid arthritis, intraperitoneal abscesses and adhesions, inflammatory bowel disease, allograft rejection, psoriasis, cancer and multiple sclerosis. This review provides an overview of IL-17 activities, concentrating on those that lead to neutrophil recruitment.