Simple renal cysts and bovine aortic arch: markers for aortic disease

Partial Arch Replacement Using Common Trunk Perfusion in Type A Acute Aortic Dissection

An 80-year-old woman was referred to our hospital following a syncope. Contrast-enhanced computed tomography revealed an acute type A aortic dissection with a bovine aortic arch and an enlarged innominate artery. The dissection affected only the ascending aorta and not the common trunk, which is composed of the innominate and left common carotid arteries. Cardiopulmonary bypass was established using common trunk perfusion and vena cava drainage. Following a thorough evaluation, a surgical intervention involving the replacement of the ascending aorta and partial arch, accompanied by the excision of the dilated innominate artery, was meticulously carried out. In instances where the common trunk remains unaffected by the dissection, it presents as a viable alternative perfusion site. Therefore, opting for an approach involving the resection of the common trunk followed by the separate reconstruction of the innominate and left common carotid arteries during the replacement of the ascending aorta and partial arch may serve as a preventative measure against potential vascular events in the future.

Kidney Diseases Classification using Hybrid Transfer-Learning DenseNet201-Based and Random Forest Classifier

There are several disease kinds in global populations that may be related to human lifestyles, social, genetic, economic, and other factors related to the nature of the country they live in. Most of the recent studies have focused on investigating prevalent diseases that spread in the population in order to minimize mortality risks, choose the best method for treatment, and improve community healthcare. Kidney disease is one of the most widespread health problems in modern society. This study focuses on kidney stones, cysts, and tumors, the three most common types of renal illness, using a dataset of 12,446 CT urogram and whole abdomen images, aiming to move toward an AI-based kidney disease diagnosis system while contributing to the wider field of artificial intelligence research. In this study, a hybrid technique is used by utilizing both pre-train models for feature extraction and classification using machine learning algorithms for the task of kidney disease image diagnosis. The pre-trained model used in this study is the Densenet-201 model. As well as using Random Forest for classification, the Densenet-201-Random-Forest approach has outperformed many of the previous models used in other studies, having an accuracy rate of 99.719 percent.

Existing and Emerging Approaches to Risk Assessment in Patients with Ascending Thoracic Aortic Dilatation

Ascending thoracic aortic aneurysm is a life-threatening disease, which is difficult to detect prior to the occurrence of a catastrophe. Epidemiology patterns of ascending thoracic aortic dilations/aneurysms remain understudied, whereas the risk assessment of it may be improved. The electronic databases PubMed/Medline 1966–2022, Web of Science 1975–2022, Scopus 1975–2022, and RSCI 1994–2022 were searched. The current guidelines recommend a purely aortic diameter-based assessment of the thoracic aortic aneurysm risk, but over 80% of the ascending aorta dissections occur at a size that is lower than the recommended threshold of 55 mm. Moreover, a 55 mm diameter criterion could exclude a vast majority (up to 99%) of the patients from preventive surgery. The authors review several visualization-based and alternative approaches which are proposed to better predict the risk of dissection in patients with borderline dilated thoracic aorta. The imaging-based assessments of the biomechanical aortic properties, the Young’s elastic modulus, the Windkessel function, compliance, distensibility, wall shear stress, pulse wave velocity, and some other parameters have been proposed to improve the risk assessment in patients with ascending thoracic aortic aneurysm. While the authors do not argue for shifting the diameter threshold to the left, they emphasize the need for more personalized solutions that integrate the imaging data with the patient’s genotypes and phenotypes in this heterogeneous pathology.

The Correlation and Copathogenesis of Coronary Aortic Sandwich and Renal Cysts

Objective

To determine the correlation for aortic occlusion and hydronephrosis and the pathogenesis of copathogenesis.

Methods

A retrospective census was established to probe the correlation with renal cysts by gathering aortic coarctation details concerning generic symptoms, diabetes, and liver and kidney profiles from 244 hospitalized aortic clinographers from April 2014 to December 2021 (study category, SG category), 150 hypertensive clients with primary hypertension attending our institution in the same period (matched category, MG category), and 150 able-bodied volunteers (control category, CG category).

Results

(1) Intercategory discrepancies in regard to aortic occlusion, diabetic malfunction, and kidney and liver abnormality were neither mutually nor predominantly measured (P > 0.05); (2) 244 enrolled SG for aortic occlusion and 150 CG for aortic occlusion were categorized by whether or not aortic occlusion was manifested, and the correlation between maternal age, gender, diabetic malfunction, and kidney and liver abnormality and renal cysts was estimated. The correlation of clogged aorta was demonstrated by a multifactorial logistic regression with gender and the presence of renal cysts (P < 0.05); (3) the correlation of clogged aorta was demonstrated by a multifactorial logistic regression with renal cysts as an independent risk factor for clogged aorta (95% CI: 1.028–10.291;P = 0.031).

Conclusion

As renal cysts are an autonomous risk of aortic coarctation, it is recommendable to strengthen clinical investigations such as monitoring of clinical blood pressures in kidney cyst recipients to assess their aortic function in order to evaluate their prognosis and minimize the prevalence of aortic coarctation.

Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from CT-radiography

Renal failure, a public health concern, and the scarcity of nephrologists around the globe have necessitated the development of an AI-based system to auto-diagnose kidney diseases. This research deals with the three major renal diseases categories: kidney stones, cysts, and tumors, and gathered and annotated a total of 12,446 CT whole abdomen and urogram images in order to construct an AI-based kidney diseases diagnostic system and contribute to the AI community's research scope e.g., modeling digital-twin of renal functions. The collected images were exposed to exploratory data analysis, which revealed that the images from all of the classes had the same type of mean color distribution. Furthermore, six machine learning models were built, three of which are based on the state-of-the-art variants of the Vision transformers EANet, CCT, and Swin transformers, while the other three are based on well-known deep learning models Resnet, VGG16, and Inception v3, which were adjusted in the last layers. While the VGG16 and CCT models performed admirably, the swin transformer outperformed all of them in terms of accuracy, with an accuracy of 99.30 percent. The F1 score and precision and recall comparison reveal that the Swin transformer outperforms all other models and that it is the quickest to train. The study also revealed the blackbox of the VGG16, Resnet50, and Inception models, demonstrating that VGG16 is superior than Resnet50 and Inceptionv3 in terms of monitoring the necessary anatomy abnormalities. We believe that the superior accuracy of our Swin transformer-based model and the VGG16-based model can both be useful in diagnosing kidney tumors, cysts, and stones.

Individualized prediction of risk of ascending aortic syndromes

Objectives

Although ascending aortic diameter changes acutely after dissection, recommendation for prophylactic surgery of thoracic aortic aneurysms rely on data from dissected aortas. In this case-control study we aim to identify risk markers for acute and chronic aortic syndromes of the ascending aorta (ACAS-AA). Furthermore, to develop a predictive model for ACAS-AA.

Methods

We collected data of 188 cases of ACAS-AA and 376 controls standardized to age- and sex of the background population. Medical history and CT-derived aortic morphology were collected. For the dependent outcome ACAS-AA, potential independent risk factors were identified by univariate logistic regression and confirmed in multivariate logistic regression. As post-dissection tubular ascending aortic diameter is prone to expand, this factor was not included in the first model. The individual calculated adjusted odds ratios were then used in ROC-curve analysis to evaluate the diagnostic accuracy of the model. To test the influence of post-ACAS-AA tubular ascending aortic diameter, this was added to the model.

Results

The following risk factors were identified as independent risk factors for ACAS-AA in multivariate analysis: bicuspid aortic valve (OR 20.41, p = 0.03), renal insufficiency (OR 2.9, p<0.01), infrarenal abdominal aortic diameter (OR 1.08, p<0.01), left common carotid artery diameter (OR 1.40, p<0.01) and aortic width (OR 1.07, p<0.01). Area under the curve was 0.88 (p<0.01). Adding post-ACAS-AA tubular ascending aortic diameter to the model, negated the association of bicuspid aortic valve, renal insufficiency, and left common carotid artery diameter. Area under the curve changed to 0.98 (p<0.01).

Conclusions

A high performing predictive model for ACAS-AA, free of ascending aortic diameter, can be achieved. Furthermore, we have identified abdominal aortic ectasia as an independent risk factor of ACAS-AA. Integration of potential biomarkers and morphologic variables, derived from undissected aortas, would probably improve the model.

Revisiting the Death and Autopsy of King George II

It is commonly accepted that King George II died of an acute aortic dissection. The origin of this association derives from retelling of the official autopsy performed by Dr. Frank Nicholls. While there is no doubt that King George II did have a Stanford Type A dissection, critical descriptions in the report point to a more likely cause of death.

Unicommissural Unicuspid Aortic Valve, Ascending Aortic Aneurysm, and Bovine Arch: A Rare Case Report

A 24-year-old man presented with rapidly progressive dyspnea due to mixed aortic stenosis and insufficiency. Unicommissural unicuspid aortic valve, ascending aortic aneurysm, and a bovine arch were identified on computed tomography angiography. Uncomplicated surgical mechanical valve replacement and ascending aortic graft placement improved his symptoms. Aortopathy is common in unicuspid valve patients.

Association of Abdominal Aortic Aneurysm and Simple Renal Cysts: A Systematic Review and Meta-Analysis

BACKGROUND-OBJECTIVE

Prior studies have suggested a higher prevalence of simple renal cysts (SRC) among patients with aortic disease, including abdominal aortic aneurysms (AAA). Thus, the aim of this study was to systematically review all currently available literature and investigate whether patients with AAA are more likely to have SRC.

METHODS

This study was performed according to the PRISMA guidelines. A meta-analysis was conducted with the use of random effects modeling and the I-square was used to assess heterogeneity. Odds ratios (OR) and the corresponding 95% confidence intervals (CI) were synthesized to compare the prevalence of several patients' characteristics between AAA vs. no-AAA cases.

RESULTS

Eleven retrospective studies, 9 comparative (AAA vs. no-AAA groups) and 3 single-arm (AAA group), were included in this meta-analysis, enrolling patients (AAA: N = 2,297 vs. no-AAA: N = 35,873) who underwent computed tomography angiography as part of screening or preoperative evaluation for reasons other than AAA. The cumulative incidence of SRC among patients with AAA and no-AAA was 55% (95% CI: 49%-61%) and 32% (95% CI: 22%-42%) respectively, with a statistically higher odds of SRC among patients with AAA (OR: 3.02; 95% CI: 2.01-4.56; P< 0.001). The difference in SRC prevalence remained statistically significant in a sensitivity analysis, after excluding the study with the largest sample size (OR: 2.71; 95% CI: 1.91-3.84; P< 0.001).

CONCLUSIONS

Our meta-analysis demonstrated a 3-fold increased prevalence of SRC in patients with AAA compared to no-AAA cases, indicating that the pathogenic processes underlying SRC and AAA could share a common pathophysiologic mechanism. Thus, patients with SRC could be considered at high risk for AAA formation, potentially warranting an earlier AAA screening.

Association of renal cyst and type A acute aortic dissection with hypertension

Background

Type A acute aortic dissection (TA-AAD) has high mortality, with 50% of patients dying before hospital admission. Hypertension is the most common comorbidity for acute aortic dissection, and effective antihypertensive therapy is still unable to predict the risk of aortic rupture at the medium- and long-term stages. While the presence of renal cyst has been found to increases the risk of thoracic aortic disease, the correlation between renal cyst and TA-AAD with hypertension remains poorly understood. Thus, this study aimed to determine the relationship of renal cyst and TA-AAD with hypertension.

Methods

A retrospective analysis was performed in 464 hypertension patients from August 2014 to August 2019. A total of 230 TA-AAD patients were enrolled in the AD with hypertension group (age 53.79±11.31 years, male 90.87%), and matched by age, sex, and hypertension control to 234 patients without TA-AAD who were enrolled in the non-AD with hypertension group. Patients were divided into three subgroups according to the numbers of renal cysts: no renal cyst, single renal cyst, and multiple renal cysts.

Results

In this study, the AD with hypertension group had significantly more single renal cyst and multiple renal cyst cases than did the non-AD with hypertension group. The mean age of the multiple renal cyst subgroup was significantly older than that of the single renal cyst subgroup (57.25±13.00 vs. 51.57±10.75 years) in the AD with hypertension group. There was significantly different distribution of dissection starting points and dissection ending points across three renal cyst subgroups. Multivariate logistic regression analysis indicated that having no renal cyst significantly decreased the risk of TA-AAD in middle-aged and elderly patents, but showed no correlations with those of younger ages. Single renal cyst status also significantly decreased the risk of TA-AAD in elderly patients [odds ratio (OR) =0.129, 95% confidence interval (CI): 0.029–0.575, P=0.007].

Conclusions

Renal cyst status correlates with the risk of TA-AAD with hypertension in middle-aged and elderly patients, and exhibits different degrees of vascular lesion in aortic dissection. We therefore suggest that different antihypertensive standards should be adopted in different renal cyst status to more effectively prevent aortic dissection.

The association between simple renal cyst and aortic diseases: A systematic review and meta-analysis of observational studies

OBJECTIVE

The objective of this meta-analysis of observational studies was to evaluate the association between simple renal cysts (SRC) and presence of aortic pathology such as aortic aneurysms and dissection.

METHODS

We conducted searches in Ovid MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials from January 1960 to August 2019 to identify observational studies that examined the association between SRCs and any aortic diseases, including aortic aneurysms and dissection. Two reviewers independently extracted the data and assessed the risk of bias. The meta-analysis was performed by STATA 14.1.

RESULTS

In total, 11 observational studies with 19 719 participants were included in this meta-analysis. Compared to individuals without SRCs, patients with SRCs had higher odds of abdominal aortic aneurysm (AAA) (adjusted OR = 2.61, 95% CI 2.34-2.91, P < 0.001, I²   = 0%), ascending thoracic aortic aneurysm (TAA) (adjusted OR = 1.98, 95% CI 1.09-3.63, P = 0.03, I²   = 90.1%), descending TAA (adjusted OR = 3.44, 95% CI, 2.67-4.43, P < 0.001, I²   = 0%), type A aortic dissection (AD) (adjusted OR = 1.98, 95% CI 1.32-2.96, P = 0.001, I²   = 12.9%), and type B AD (adjusted OR = 2.55, 95% CI, 1.31-4.96, P = 0.006, I²   = 76.2%). There was a higher average in the sum of diameter of SRCs among AAA compared to patients without AAA (WMD = 19.80 mm, 95% CI 13.92-25.67, P < 0.001, I²   = 63.8%).

CONCLUSION

SRC is associated with higher odds of aortic diseases including AAA, ascending and descending TAA, type A and type B dissection even after adjusting for confounders.

Association of simple renal cysts and chronic kidney disease with large abdominal aortic aneurysm

Background

Abdominal aortic aneurysms (AAA) primarily affect men over 65 years old who often have many other diseases, with similar risk factors and pathobiological mechanisms to AAA. The aim of this study was to assess the prevalence of simple renal cysts (SRC), chronic kidney disease (CKD), and other kidney diseases (e.g. nephrolithiasis) among patients presenting with AAA.

Methods

Two groups of patients (97 AAA and 100 controls), with and without AAA, from the Surgical Clinic Charité, Berlin, Germany, were selected for the study. The control group consisted of patients who were evaluated for a kidney donation (n = 14) and patients who were evaluated for an early detection of a melanoma recurrence (n = 86). The AAA and control groups were matched for age and sex. Medical records were analyzed and computed tomography scans were reviewed for the presence of SRC and nephrolithiasis.

Results

SRC (74% vs. 57%; p<0.016) and CKD (30% vs. 8%; p<0.001) were both more common among AAA than control group patients. On multivariate analysis, CKD, but not SRC, showed a strong association with AAA.

Conclusions

Knowledge about pathobiological mechanisms and association between CKD and AAA could provide better diagnostic and therapeutic approaches for these patients.