Defining a master curve of abdominal aortic aneurysm growth and its potential utility of clinical management.

OBJECTIVE: The maximum diameter measurement of an abdominal aortic aneurysm (AAA), which depends on orthogonal and axial cross-sections or maximally inscribed spheres within the AAA, plays a significant role in the clinical decision making process. This study aims to build a total of 21 morphological parameters from longitudinal CT scans and analyze their correlations. Furthermore, this work explores the existence of a "master curve" of AAA growth, and tests which parameters serve to enhance its predictability for clinical use. METHODS: 106 CT scan images from 25 Korean AAA patients were retrospectively obtained. We subsequently computed morphological parameters, growth rates, and pair-wise correlations, and attempted to enhance the predictability of the growth for high-risk aneurysms using non-linear curve fitting and least-square minimization. RESULTS: An exponential AAA growth model was fitted to the maximum spherical diameter, as the best representative of the growth among all parameters (r-square: 0.94) and correctly predicted to 15 of 16 validation scans based on a 95% confidence interval. AAA volume expansion rates were highly correlated (r=0.75) with thrombus accumulation rates. CONCLUSIONS: The exponential growth model using spherical diameter provides useful information about progression of aneurysm size and enables AAA growth rate extrapolation during a given surveillance period.

A Novel Negative Pressure Isolation Device for Aerosol Transmissible COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic creates a need to protect health care workers (HCWs) from patients undergoing aerosol-generating procedures which may transmit the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Existing personal containment devices (PCDs) may protect HCWs from respiratory droplets but not from potentially dangerous respiratory-generated aerosols. We describe a new PCD and its aerosol containment capabilities. The device ships flat and folds into a chamber. With its torso drape and protective arm sleeves mounted, it provides contact, droplet, and aerosol isolation during intubation and cardiopulmonary resuscitation (CPR). Significantly improved ergonomics, single-use workflow, and ease of removal distinguish this device from previously published designs.

Predicting abdominal aortic aneurysm growth using patient-oriented growth models with two-step Bayesian inference.

OBJECTIVE: For small abdominal aortic aneurysms (AAAs), a regular follow-up examination is recommended every 12 months for AAAs of 30-39 mm and every six months for AAAs of 40-55 mm. Follow-up diameters can determine if a patient follows the common growth model of the population. However, the rapid expansion of an AAA, often associated with higher rupture risk, may be overlooked even though it requires surgical intervention. Therefore, the prognosis of abdominal aortic aneurysm growth is clinically important for planning treatment. This study aims to build enhanced Bayesian inference methods to predict maximum aneurysm diameter. METHODS: 106 CT scans from 25 Korean AAA patients were retrospectively obtained. A two-step approach based on Bayesian calibration was used, and an exponential abdominal aortic aneurysm growth model (population-based) was specified according to each individual patient's growth (patient-specific) and morphologic characteristics of the aneurysm sac (enhanced). The distribution estimates were obtained using a Markov Chain Monte Carlo (MCMC) sampler. RESULTS: The follow-up diameters were predicted satisfactorily (i.e. the true follow-up diameter was in the 95% prediction interval) for 79% of the scans using the population-based growth model, and 83% of the scans using the patient-specific growth model. Among the evaluated geometric measurements, centerline tortuosity was a significant (p = 0.0002) predictor of growth for AAAs with accelerated and stable expansion rates. Using the enhanced prediction model, 86% of follow-up scans were predicted satisfactorily. The average prediction errors of population-based, patient-specific, and enhanced models were ±2.67, ±2.61 and ± 2.79 mm, respectively. CONCLUSION: A computational framework using patient-oriented growth models provides useful tools for per-patient basis treatment and enables better prediction of AAA growth.

Evaluation of acute and chronic pain outcomes after robotic, video-assisted thoracoscopic surgery, or open anatomic pulmonary resection.

OBJECTIVES: Although robotic-assisted thoracic surgery (RATS) provides improved dexterity, the effect of RATS on pain compared with video-assisted thoracoscopic surgery (VATS) or open lobectomy is poorly understood. This study evaluated acute and chronic pain following RATS, VATS, and open anatomic pulmonary resection. METHODS: A retrospective review of 498 patients (502 procedures) who underwent RATS (74), VATS (227), and open (201) anatomic pulmonary resection including lobectomy and segmentectomy from 2010 to 2014 was performed to identify factors related to acute and chronic pain. Acute pain scores were analyzed over the first 9 postoperative days. Chronic pain was assessed using the validated PainDETECT survey. RESULTS: There were no significant differences in acute or chronic pain between RATS and VATS. There was a significant decrease in acute pain for patients with minimally invasive surgery (P = .0004). Chronic numbness was significantly higher after open resection (25.5% vs 11.6%; P = .0269) but with no difference in other symptoms of chronic pain. Despite no significant difference in pain scores, 69.2% of patients who received RATS felt the approach affected pain versus 44.2% VATS (P = .0330). On multivariable analysis, younger age (P < .0001), female gender (P = .0364), and baseline narcotic use (P = .0142) were associated with acute pain, whereas younger age (P = .0021) and major complications (P = .0003) were associated with chronic numbness in patients who received MIS. CONCLUSIONS: Although minimally invasive approaches resulted in less acute pain and chronic numbness, there were no significant differences between RATS and VATS. In contrast, more RATS patients believed the approach affected their pain, suggesting a difference between reality and perception.

Predictors of operative failure in parathyroidectomy for primary hyperparathyroidism.

INTRODUCTION: Many adjuncts guide surgical decision making in parathyroidectomy, yet their independent associations with outcome are poorly characterized. We examined a broad range of perioperative factors and used multivariate techniques to identify independent predictors of operative failure (persistent disease) after parathyroidectomy. METHODS: This was a retrospective review of 2239 patients with primary hyperparathyroidism who underwent parathyroidectomy at a single-center from 1999 to 2014. We used multivariate logistic regress to measure associations between multiple perioperative factors and an operative failure (persistent hypercalcemia). RESULTS: Operative failure was identified in 67 patients (3.0%). The following variables were independently associated with operative failure on multivariate analysis: IOPTH criteria met (protective, OR = 0.22, P < 0.001), preoperative calcium (risk factor, OR = 2.27 per unit increase, P < 0.001), weight of excised gland(s) (protective, OR = 0.70 per two-fold increase, P = 0.003), and preoperative PTH (protective, OR = 0.55 per two-fold increase, P = 0.008). CONCLUSION: In addition to the well-established IOPTH criteria, we suggest that consideration of the above independent perioperative risk factors may further inform surgical decision-making in parathyroidectomy.

Interaction of expanding abdominal aortic aneurysm with surrounding tissue: Retrospective CT image studies.

OBJECTIVES: Abdominal aortic aneurysms (AAA) that rupture have a high mortality rate. Rupture occurs when local mechanical stress exceeds the local mechanical strength of an AAA, so stress profiles such as those from finite element analysis (FEA) are useful. The role and effect of surrounding tissues, like the vertebral column, which have not been extensively studied, are examined in this paper. METHODS: Longitudinal CT scans from ten patients with AAAs were studied to see the effect of surrounding tissues on AAAs. Segmentation was performed to distinguish the AAA from other tissues and we studied how these surrounding tissues affected the shape and curvature of the AAA. Previously established methods by Veldenz et al. were used to split the AAA into 8 sections and examine the specific effects of surrounding tissues on these sections [1]. Three-dimensional models were created to better examine these effects over time. Registration was done in order to compare AAAs longitudinally. RESULTS: The vertebral column and osteophytes were observed to have been affecting the shape and the curvature of the AAA. Interaction with the spine caused focal flattening in certain areas of the AAA. In 16 of the 41 CT scans, the right posterior dorsal section (section 5), had the highest radius of curvature, which was by far the section that had the maximum radius for a specified CT scan. Evolution of the growing AAA showed increased flattening in this section when comparing the last CT scan to the first scan. CONCLUSION: Surrounding tissues have a clear influence on the geometry of an AAA, which may in turn affect the stress profile of AAA. Incorporating these structures in FEA and G&R models will provide a better estimate of stress. CLINICAL RELEVANCE: Currently, size is the only variable considered when deciding whether to undergo elective surgery to repair AAA since it is an easy enough measure for clinicians to utilize. However, this may not be the best indicator of rupture risk because small aneurysms also contribute to a high mortality rate. AAA's wall stress is a superior indicator and may be better predicted with the inclusion of these surrounding tissues, which then could be used by clinicians in their decision-making process on whether to operate on an AAA.

Influence of surrounding tissues on biomechanics of aortic wall.

The present study investigates effects of surrounding tissues and non-uniform wall thickness on the biomechanics of the thoracic aorta. We construct two idealised computational models exemplifying the importance of surrounding tissues and non-uniform wall thickness, namely the uniform-thickness model and the histology image-based model. While the former neglects a connective tissue layer surrounding the aorta, the latter takes it into account with non-uniform wall thickness. Using plane strain finite element analysis, stress distributions in the aortic media between the two models are compared. The histology image-based model substantially enhances the uniformity of stress throughout the aortic media. Furthermore, the altered mechanical properties of surrounding tissues change the stress distribution. These results suggest that surrounding tissues and non-uniform wall thickness should be included in biomechanical analysis to better understand regional adaptation of the aortic wall during normal physiological conditions or pathological conditions such as aortic aneurysms and dissections.