Development of Prediction Models for Cardiac Compression in Pectus Excavatum Based on Three-Dimensional Surface Images

In pectus excavatum, three-dimensional (3D) surface imaging provides an accurate and radiation-free alternative to computed tomography (CT) to determine severity. Yet, it does not allow for cardiac evaluation since 3D imaging solely captures the chest wall surface. The objective was to develop a 3D image-based prediction model for cardiac compression in patients evaluated for pectus excavatum. A prospective cohort study was conducted including consecutive patients referred for pectus excavatum who received a thoracic CT. Additionally, 3D images were acquired. The external pectus depth, its length, craniocaudal position, cranial slope, asymmetry, anteroposterior distance and chest width were calculated from 3D images. Together with baseline patient characteristics they were submitted to forward multivariable logistic regression to identify predictors for cardiac compression. Cardiac compression on CT was used as reference. The model's performance was depicted by the area under the receiver operating characteristic (AUROC) curve. Internal validation was performed using bootstrapping. Sixty-one patients were included of whom 41 had cardiac compression on CT. A combination of the 3D image derived external pectus depth and external anteroposterior distance was identified as predictive for cardiac compression, yielding an AUROC of 0.935 (95% confidence interval [CI]: 0.878-0.992) with an optimism of 0.006. In a second model for males alone, solely the external pectus depth was identified as predictor, yielding an AUROC of 0.947 (95% CI: 0.892-1.000) with an optimism of 0.0002. We have developed two 3D image-based prediction models for cardiac compression in patients evaluated for pectus excavatum which provide an outstanding discriminatory performance between the presence and absence of cardiac compression with negligible optimism

Cyclooxygenase-2 Is Essential for Colorectal Anastomotic Healing

Objective: To study the effects of COX-2 on colonic surgical wound healing. Background: Cyclooxygenase-2 (COX-2) is a key enzyme in gastrointestinal homeostasis. COX-2 inhibitors have been associated with colonic anastomotic leakage. Methods: Wildtype, COX-2 knockout and COX-2 heterozygous mice were subjected to a model of colonic anastomotic leakage, and were treated with vehicle, diclofenac, or prostaglandin E2 (PGE2), the most important COX-2 product in the intestine. We assessed anastomotic leakage, mortality, angiogenesis, and inflammation. Furthermore, we investigated the association between anastomotic leakage and a human polymorphism of the COX-2 gene resulting in low COX-2 levels. Results: Diclofenac, a nonsteroidal anti-inflammatory drug inhibiting COX-2, increased anastomotic leakage compared to vehicle-treated mice (100% vs 25%, respectively). Similarly, 92% of COX-2-deficient mice developed anastomotic leakage (P = 0.003) compared to WT. PGE2 partly rescued this severe phenotype because only 46% of PGE2-administered COX-2 knockout mice developed anastomotic leakage (P = 0.02). This may be related to decreased neovascularization, because decreased CD31 staining, indicating less blood vessels, was observed in COX-2(-/-) mice (2 vessels/mm(2) vs 6 vessels/mm(2) in controls (P = 0.03)). This effect could partly be reversed by administration of PGE2 to COX-2(-/-) mice. No significant differences in inflammation were found. PTGS2-765G>C polymorphism in humans, associated with reduced COX-2 expression, was associated with higher anastomotic leakage rates. Conclusions: COX-2-induced PGE2 production is essential for intestinal wound healing after colonic surgery, possibly via its effects on angiogenesis. These data emphasize that COX-2 inhibitors should be avoided after colonic surgery, and administration of PGE2 might be favorable for a selection of patient

Three-dimensional Surface Imaging for Clinical Decision Making in Pectus Excavatum

To evaluate pectus excavatum, 3-dimensional surface imaging is a promising radiation-free alternative to computed tomography and plain radiographs. Given that 3-dimensional images concern the external surface, the conventional Haller index, and correction index are not applicable as these are based on internal diameters. Therefore, external equivalents have been introduced for 3-dimensional images. However, cut-off values to help determine surgical candidacy using external indices are lacking. A prospective cohort study was conducted. Consecutive patients referred for suspected pectus excavatum received a computed tomography (≥18 years) or plain radiographs (<18 years). The external Haller index and external correction index were calculated from additionally acquired 3-dimensional images. Cut-off values for the 3-dimensional image derived indices were obtained by receiver-operating characteristic curve analyses, using a conventional Haller index ≥3.25, and computed tomography derived correction index ≥28.0% as indicative for surgery. Sixty-one and 63 patients were included in the computed tomography and radiograph group, respectively. To determine potential surgical candidacy, receiver-operating characteristic analyses found an optimum cut-off of ≥1.83 for the external Haller index in both the computed tomography and radiograph group with a positive predictive value between 0.90 and 0.97 and a negative predictive value between 0.72 and 0.81. The optimal cut-off for the external correction index was ≥15.2% with a positive predictive value of 0.86 and negative predictive value of 0.93. The 3-dimensional image derived external Haller index and external correction index are accurate radiation-free alternatives to facilitate surgical decision-making among patients suspected of pectus excavatum with values of ≥1.83 and ≥15.2% indicative for surgery

Optical imaging versus CT and plain radiography to quantify pectus severity: A systematic review and meta-analysis

Background: Computed tomography (CT) and two-view chest radiographies are the most commonly used imaging techniques to quantify the severity of pectus excavatum (PE) and pectus carinatum (PC). Both modalities expose patients to ionizing radiation that should ideally be avoided, especially in pediatric patients. In an effort to diminish this exposure, three-dimensional (3D) optical surface imaging has recently been proposed as an alternative method. To assess its clinical value as a tool to determine pectus severity we conducted a systematic review in which we assessed all studies that compared 3D scan-based pectus severity measurements with those derived from CT-scans and radiographies. Methods: Six scientific databases and three registries were searched through April 30th, 2019. Data regarding the correlation between severity measures was extracted and submitted to meta-analysis using the random-effects model and I2-test for heterogeneity. Results: Five observational studies were included, enrolling 75 participants in total. Pooled analysis of participants with PE demonstrated a high positive correlation coefficient of 0.89 [95% confidence interval (CI): 0.81 to 0.93; P<0.001] between the CT-derived Haller index (HI) and its 3D scan equivalent based on external measures. No heterogeneity was detected (I2=0.00%; P=0.834). Conclusions: 3D optical surface scanning is an attractive and promising imaging technique to determine the severity of PE without exposure to ionizing radiation. However, further research is needed to determine novel cut-off values for 3D scans to facilitate clinical decision making and help determine surgical candidacy. No evidence was found that supports nor discards the use of 3D scans to determine PC severity

Predicting Aesthetic Outcome of the Nuss Procedure in Patients with Pectus Excavatum

Patients suffering from pectus excavatum often experience psychosocial distress due to perceived anomalies in their physical appearance. The ability to visually inform patients about their expected aesthetic outcome after surgical correction is still lacking. This study aims to develop an automatic, patient-specific model to predict aesthetic outcome after the Nuss procedure. Patients prospectively received preoperative and postoperative 3-dimensional optical surface scanning of their chest during the Nuss procedure. A prediction model was composed based on nonlinear least squares data-fitting, regression methods and a 2-dimensional Gaussian function with adjustable amplitude, variance, rotation, skewness, and kurtosis components. Morphological features of pectus excavatum were extracted from preoperative images using a previously developed surface analysis tool to generate a patient-specific model. Prediction accuracy was evaluated through cross-validation, utilizing the mean root squared deviation and maximum positive and negative deviations as performance measures. The prediction model was evaluated on 30 (90% male) prospectively imaged patients. The model achieved an average root mean squared deviation of 6.3 ± 2.0 mm, with average maximum positive and negative deviations of 12.7 ± 6.1 and -10.2 ± 5.7 mm, respectively, between the predicted and actual postoperative aesthetic result. Our developed 2-dimensional Gaussian model based on 3-dimensional optical surface images is a clinically promising tool to predict postsurgical aesthetic outcome in patients with pectus excavatum. Prediction of the aesthetic outcome after the Nuss procedure potentially improves information provision and expectation management among patients. Further research should assess whether increasing the sample size may reduce deviations and improve performance

Three-Dimensional Imaging of the Chest Wall: A Comparison Between Three Different Imaging Systems

Background: Three-dimensional (3D) imaging is being used progressively to create models of patients with anterior chest wall deformities. Resulting models are used for clinical decision-making, surgical planning, and analysis. However, given the broad range of 3D imaging systems available and the fact that planning and analysis techniques are often only validated for a single system, it is important to analyze potential intrasystem and intersystem differences. The objective of this study was to investigate the accuracy and reproducibility of three commercially available 3D imaging systems that are used to obtain images of the anterior chest wall. Methods: Among 15 healthy volunteers, 3D images of the anterior chest wall were acquired twice per imaging device. Reproducibility was determined by comparison of consecutive images acquired per device while the true accuracy was calculated by comparison of 3D image derived and calipered anthropometric measurements. A maximum difference of 1.00 mm. was considered clinically acceptable. Results: All devices demonstrated statistically comparable (P = 0.21) reproducibility with a mean absolute difference of 0.59 mm. (SD: 1.05), 0.54 mm. (SD: 2.08), and 0.48 mm. (SD: 0.60) for the 3dMD, EinScan Pro 2X Plus, and Artec Leo, respectively. The true accuracy was, respectively, 0.89 mm. (SD: 0.66), 1.27 mm. (SD: 0.94), and 0.81 mm. (SD: 0.71) for the 3dMD, EinScan, and Artec device and did not statistically differ (P = 0.085). Conclusions: Three-dimensional imaging of the anterior chest wall utilizing the 3dMD and Artec Leo is feasible with comparable reproducibility and accuracy, whereas the EinScan Pro 2X Plus is reproducible but not clinically accurate

Learning Curve of Laparoscopic Gastrectomy: A Multicenter Study

Objective: To evaluate the learning curve of laparoscopic gastrectomy (LG) after an implementation program. Background: Although LG is increasingly being performed worldwide, little is known about the learning curve. Methods: Consecutive patients who underwent elective LG for gastric adenocarcinoma with curative intent in each of the 5 highest-volume centers in the Netherlands were enrolled. Generalized additive models and a 2-piece model with a break point were used to determine the learning curve length. Analyses were corrected for casemix and were performed for LG and for the subgroups distal gastrectomy (LDG) and total gastrectomy (LTG). The learning curve effect was assessed for (1) anastomotic leakage; and (2) the occurrence of postoperative complications, conversions to open surgery, and short-term oncological parameters. Results: In total 540 patients were included for analysis, 108 patients from each center; 268 patients underwent LDG and 272 underwent LTG. First, for LG, no learning effect regarding anastomotic leakage could be identified: the rate of anastomotic leakage initially increased, then reached a plateau after 36 cases at 10% anastomotic leakage. Second, the level of overall complications reached a plateau after 20 cases, at 38% overall complications, and at 5% conversions. For both LDG and LTG, each considered separately, fluctuations in secondary outcomes and anastomotic leakage followed fluctuations in casemix. Conclusion: On the basis of our study of the first 108 procedures of LG in 5 high-volume centers with well-trained surgeons, no learning curve effect could be identified regarding anastomotic leakage. A learning curve effect was found with respect to overall complications and conversion rate