Cell signaling and tissue remodeling in the pulmonary autograft after the Ross procedure: A computational study.

In the Ross procedure, a patient's pulmonary valve is transplanted in the aortic position. Despite advantages of this surgery, reoperation is still needed in many cases due to excessive dilatation of the pulmonary autograft. To further understand the failure mechanisms, we propose a multiscale model predicting adaptive processes in the autograft at the cell and tissue scale. The cell-scale model consists of a network model, that includes important signaling pathways and relations between relevant transcription factors and their target genes. The resulting gene activity leads to changes in the mechanical properties of the tissue, modeled as a constrained mixture of collagen, elastin and smooth muscle. The multiscale model is calibrated with findings from experiments in which seven sheep underwent the Ross procedure. The model is then validated against a different set of sheep experiments, for which a qualitative agreement between model and experiment is found. Model outcomes at the cell scale, including the activity of genes and transcription factors, also match experimentally obtained transcriptomics data.

Using YOLO v7 to Detect Kidney in Magnetic Resonance Imaging.

Introduction: This study explores the use of the latest You Only Look Once (YOLO V7) object detection method to enhance kidney detection in medical imaging by training and testing a modified YOLO V7 on medical image formats. Methods: Study includes 878 patients with various subtypes of renal cell carcinoma (RCC) and 206 patients with normal kidneys. A total of 5657 MRI scans for 1084 patients were retrieved. 326 patients with 1034 tumors recruited from a retrospective maintained database, and bounding boxes were drawn around their tumors. A primary model was trained on 80% of annotated cases, with 20% saved for testing (primary test set). The best primary model was then used to identify tumors in the remaining 861 patients and bounding box coordinates were generated on their scans using the model. Ten benchmark training sets were created with generated coordinates on not-segmented patients. The final model used to predict the kidney in the primary test set. We reported the positive predictive value (PPV), sensitivity, and mean average precision (mAP). Results: The primary training set showed an average PPV of 0.94 ± 0.01, sensitivity of 0.87 ± 0.04, and mAP of 0.91 ± 0.02. The best primary model yielded a PPV of 0.97, sensitivity of 0.92, and mAP of 0.95. The final model demonstrated an average PPV of 0.95 ± 0.03, sensitivity of 0.98 ± 0.004, and mAP of 0.95 ± 0.01. Conclusion: Using a semi-supervised approach with a medical image library, we developed a high-performing model for kidney detection. Further external validation is required to assess the model's generalizability.

A Prospective Study of the Diagnostic Performance of Photon-Counting CT Compared With MRI in the Characterization of Renal Masses.

OBJECTIVES: The aim of this study was to assess the interreader reliability and per-RCC sensitivity of high-resolution photon-counting computed tomography (PCCT) in the detection and characterization of renal masses in comparison to MRI. MATERIALS AND METHODS: This prospective study included 24 adult patients (mean age, 52 ± 14 years; 14 females) who underwent PCCT (using an investigational whole-body CT scanner) and abdominal MRI within a 3-month time interval and underwent surgical resection (partial or radical nephrectomy) with histopathology (n = 70 lesions). Of the 24 patients, 17 had a germline mutation and the remainder were sporadic cases. Two radiologists (R1 and R2) assessed the PCCT and corresponding MRI studies with a 3-week washout period between reviews. Readers recorded the number of lesions in each patient and graded each targeted lesion's characteristic features, dimensions, and location. Data were analyzed using a 2-sample t test, Fisher exact test, and weighted kappa. RESULTS: In patients with von Hippel-Lindau mutation, R1 identified a similar number of lesions suspicious for neoplasm on both modalities (51 vs 50, P = 0.94), whereas R2 identified more suspicious lesions on PCCT scans as compared with MRI studies (80 vs 56, P = 0.12). R1 and R2 characterized more lesions as predominantly solid in MRIs (R1: 58/70 in MRI vs 52/70 in PCCT, P < 0.001; R2: 60/70 in MRI vs 55/70 in PCCT, P < 0.001). R1 and R2 performed similarly in detecting neoplastic lesions on PCCT and MRI studies (R1: 94% vs 90%, P = 0.5; R2: 73% vs 79%, P = 0.13). CONCLUSIONS: The interreader reliability and per-RCC sensitivity of PCCT scans acquired on an investigational whole-body PCCT were comparable to MRI scans in detecting and characterizing renal masses. CLINICAL RELEVANCE STATEMENT: PCCT scans have comparable performance to MRI studies while allowing for improved characterization of the internal composition of lesions due to material decomposition analysis. Future generations of this imaging modality may reveal additional advantages of PCCT over MRI.

Using Claims Data to Predict Pre-Operative BMI Among Bariatric Surgery Patients: Development of the BMI Before Bariatric Surgery Scoring System (B3S3).

Background: Lack of body mass index (BMI) measurements limits the utility of claims data for bariatric surgery research, but pre-operative BMI may be imputed due to existence of weight-related diagnosis codes and BMI-related reimbursement requirements. We used a machine learning pipeline to create a claims-based scoring system to predict pre-operative BMI, as documented in the electronic health record (EHR), among patients undergoing a new bariatric surgery. Methods: Using the Optum Labs Data Warehouse, containing linked de-identified claims and EHR data for commercial or Medicare Advantage enrollees, we identified adults undergoing a new bariatric surgery between January 2011 and June 2018 with a BMI measurement in linked EHR data ≤30 days before the index surgery (n=3226). We constructed predictors from claims data and applied a machine learning pipeline to create a scoring system for pre-operative BMI, the B3S3. We evaluated the B3S3 and a simple linear regression model (benchmark) in test patients whose index surgery occurred concurrent (2011-2017) or prospective (2018) to the training data. Results: The machine learning pipeline yielded a final scoring system that included weight-related diagnosis codes, age, and number of days hospitalized and distinct drugs dispensed in the past 6 months. In concurrent test data, the B3S3 had excellent performance (R2 0.862, 95% confidence interval [CI] 0.815-0.898) and calibration. The benchmark algorithm had good performance (R2 0.750, 95% CI 0.686-0.799) and calibration but both aspects were inferior to the B3S3. Findings in prospective test data were similar. Conclusion: The B3S3 is an accessible tool that researchers can use with claims data to obtain granular and accurate predicted values of pre-operative BMI, which may enhance confounding control and investigation of effect modification by baseline obesity levels in bariatric surgery studies utilizing claims data.

Pre-operative BMI is an important potential confounder in comparative effectiveness studies of bariatric surgeries.Claims data lack clinical measurements, but insurance reimbursement requirements for bariatric surgery often result in pre-operative BMI being coded in claims data.We used a machine learning pipeline to create a model, the B3S3, to predict pre-operative BMI, as documented in the EHR, among bariatric surgery patients based on the presence of certain weight-related diagnosis codes and other patient characteristics derived from claims data.Researchers can easily use the B3S3 with claims data to obtain granular and accurate predicted values of pre-operative BMI among bariatric surgery patients.

Non-Invasive Tumor Grade Evaluation in Von Hippel-Lindau-Associated Clear Cell Renal Cell Carcinoma: A Magnetic Resonance Imaging-Based Study.

BACKGROUND: Pathology grading is an essential step for the treatment and evaluation of the prognosis in patients with clear cell renal cell carcinoma (ccRCC). PURPOSE: To investigate the utility of texture analysis in evaluating Fuhrman grades of renal tumors in patients with Von Hippel-Lindau (VHL)-associated ccRCC, aiming to improve non-invasive diagnosis and personalized treatment. STUDY TYPE: Retrospective analysis of a prospectively maintained cohort. POPULATION: One hundred and thirty-six patients, 84 (61%) males and 52 (39%) females with pathology-proven ccRCC with a mean age of 52.8 ± 12.7 from 2010 to 2023. FIELD STRENGTH AND SEQUENCES: 1.5 and 3 T MRIs. Segmentations were performed on the T1-weighted 3-minute delayed sequence and then registered on pre-contrast, T1-weighted arterial and venous sequences. ASSESSMENT: A total of 404 lesions, 345 low-grade tumors, and 59 high-grade tumors were segmented using ITK-SNAP on a T1-weighted 3-minute delayed sequence of MRI. Radiomics features were extracted from pre-contrast, T1-weighted arterial, venous, and delayed post-contrast sequences. Preprocessing techniques were employed to address class imbalances. Features were then rescaled to normalize the numeric values. We developed a stacked model combining random forest and XGBoost to assess tumor grades using radiomics signatures. STATISTICAL TESTS: The model's performance was evaluated using positive predictive value (PPV), sensitivity, F1 score, area under the curve of receiver operating characteristic curve, and Matthews correlation coefficient. Using Monte Carlo technique, the average performance of 100 benchmarks of 85% train and 15% test was reported. RESULTS: The best model displayed an accuracy of 0.79. For low-grade tumor detection, a sensitivity of 0.79, a PPV of 0.95, and an F1 score of 0.86 were obtained. For high-grade tumor detection, a sensitivity of 0.78, PPV of 0.39, and F1 score of 0.52 were reported. DATA CONCLUSION: Radiomics analysis shows promise in classifying pathology grades non-invasively for patients with VHL-associated ccRCC, potentially leading to better diagnosis and personalized treatment. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Deep learning algorithm (YOLOv7) for automated renal mass detection on contrast-enhanced MRI: a 2D and 2.5D evaluation of results.

INTRODUCTION: Accurate diagnosis and treatment of kidney tumors greatly benefit from automated solutions for detection and classification on MRI. In this study, we explore the application of a deep learning algorithm, YOLOv7, for detecting kidney tumors on contrast-enhanced MRI. MATERIAL AND METHODS: We assessed the performance of YOLOv7 tumor detection on excretory phase MRIs in a large institutional cohort of patients with RCC. Tumors were segmented on MRI using ITK-SNAP and converted to bounding boxes. The cohort was randomly divided into ten benchmarks for training and testing the YOLOv7 algorithm. The model was evaluated using both 2-dimensional and a novel in-house developed 2.5-dimensional approach. Performance measures included F1, Positive Predictive Value (PPV), Sensitivity, F1 curve, PPV-Sensitivity curve, Intersection over Union (IoU), and mean average PPV (mAP). RESULTS: A total of 326 patients with 1034 tumors with 7 different pathologies were analyzed across ten benchmarks. The average 2D evaluation results were as follows: Positive Predictive Value (PPV) of 0.69 ± 0.05, sensitivity of 0.39 ± 0.02, and F1 score of 0.43 ± 0.03. For the 2.5D evaluation, the average results included a PPV of 0.72 ± 0.06, sensitivity of 0.61 ± 0.06, and F1 score of 0.66 ± 0.04. The best model performance demonstrated a 2.5D PPV of 0.75, sensitivity of 0.69, and F1 score of 0.72. CONCLUSION: Using computer vision for tumor identification is a cutting-edge and rapidly expanding subject. In this work, we showed that YOLOv7 can be utilized in the detection of kidney cancers.

Kidney scoring surveillance: predictive machine learning models for clear cell renal cell carcinoma growth using MRI.

INTRODUCTION: Classification of clear cell renal cell carcinoma (ccRCC) growth rates in patients with Von Hippel-Lindau (VHL) syndrome has several ramifications for tumor monitoring and surgical planning. Using two separate machine-learning algorithms, we sought to produce models to predict ccRCC growth rate classes based on qualitative MRI-derived characteristics. MATERIAL AND METHODS: We used a prospectively maintained database of patients with VHL who underwent surgical resection for ccRCC between January 2015 and June 2022. We employed a threshold growth rate of 0.5 cm per year to categorize ccRCC tumors into two distinct groups-'slow-growing' and 'fast-growing'. Utilizing a questionnaire of qualitative imaging features, two radiologists assessed each lesion on different MRI sequences. Two machine-learning models, a stacked ensemble technique and a decision tree algorithm, were used to predict the tumor growth rate classes. Positive predictive value (PPV), sensitivity, and F1-score were used to evaluate the performance of the models. RESULTS: This study comprises 55 patients with VHL with 128 ccRCC tumors. Patients' median age was 48 years, and 28 patients were males. Each patient had an average of two tumors, with a median size of 2.1 cm and a median growth rate of 0.35 cm/year. The overall performance of the stacked and DT model had 0.77 ± 0.05 and 0.71 ± 0.06 accuracies, respectively. The best stacked model achieved a PPV of 0.92, a sensitivity of 0.91, and an F1-score of 0.90. CONCLUSION: This study provides valuable insight into the potential of machine-learning analysis for the determination of renal tumor growth rate in patients with VHL. This finding could be utilized as an assistive tool for the individualized screening and follow-up of this population.

Skeletal involvement in Erdheim-Chester disease: Multimodality imaging features and association with the BRAFV600E mutation.

OBJECTIVE: The aim of this study was to characterize the distribution of skeletal involvement in Erdheim-Chester disease (ECD) by using radiography, computed tomography (CT), 18F-FDG positron emission tomography/computed tomography (PET/CT), and bone scans, as well as looking for associations with the BRAFV600E mutation. MATERIAL AND METHODS: Prospective study of 50 consecutive patients with biopsy-confirmed ECD who had radiographs, CT, 18F-FDG PET/CT, and Tc-99m MDP bone scans. At least two experienced radiologists with expertise in the relevant imaging studies analyzed the images. Summary statistics were expressed as the frequency with percentages for categorical data. Fisher's exact test, as well as odds ratios (OR) with 95 % confidence intervals (CI), were used to link imaging findings to BRAFV600E mutation. The probability for co-occurrence of bone involvement at different locations was calculated and graphed as a heat map. RESULTS: All 50 cases revealed skeletal involvement at different regions of the skeleton. The BRAFV600E mutation, which was found in 24 patients, was correlated with femoral and tibial involvement on 18F-FDG PET/CT and bone scan. The appearance of changes on the femoral, tibial, fibular, and humeral involvement showed correlation with each other based on heat maps of skeletal involvement on CT. CONCLUSION: This study reports the distribution of skeletal involvement in a cohort of patients with ECD. CT is able to detect the majority of ECD skeletal involvement. Considering the complementary nature of information from different modalities, imaging of ECD skeletal involvement is optimized by using a multi-modality strategy.

Mortality Trends in Alzheimer's Disease in Mississippi, 2011-2021.

Alzheimer's disease is the sixth most common cause of death in the United States (U.S.), with one in three adults 65 years of age and older dying of the disease each year. Deaths from Alzheimer's have more than doubled between 2000 and 2019, killing more adults than both breast cancer and prostate cancer. In 2021, Alzheimer's disease resulted in 36 deaths per 100,000 in the U.S. In Mississippi, deaths from Alzheimer's have almost doubled between 2011 and 2021, resulting in 52.9 deaths per 100,000. Women have a higher mortality rate from Alzheimer's than men. Alzheimer's is a progressive disease that develops through seven stages. There are effective strategies to prevent the onset of Alzheimer's. METHODS: This paper reviews the risk factors, mortality trends, etiology, and prognosis of Alzheimer's in Mississippi with a focus on prevention. RESULTS: The southern diet with foods high in sugar and sodium, along with sedentary and poor lifestyle choices, increases mortality risk from Alzheimer's disease for women in Mississippi, specifically due to women over 65 having higher rates of obesity and hypertension. CONCLUSION: Understanding the epidemiology and risk factors of Alzheimer's in Mississippi will help inform communities, policies, and programs to prevent disease occurrence.

Hepatocyte-specific deletion of small heterodimer partner protects mice against acetaminophen-induced hepatotoxicity via activation of Nrf2.

Acetaminophen (APAP) overdose stands as the primary cause of acute liver failure in the United States. APAP hepatotoxicity involves hepatic glutathione (GSH) depletion and mitochondrial damage. To counteract the toxicity of APAP, the nuclear factor erythroid 2 like 2 (Nrf2) activates the expression of genes responsible for drug detoxification and GSH synthesis. In this study, we present evidence that the elimination of hepatocyte small heterodimer partner, a critical transcriptional repressor for liver metabolism, results in Nrf2 activation and protects mice from APAP-induced acute liver injury. Initial investigations conducted on wildtype (WT) mice revealed a swift downregulation of Shp mRNA within the first 24 h after APAP administration. Subsequent treatment of hepatocyte-specific Shp knockout (ShpHep-/-) mice with 300 mg/kg APAP for 2 h exhibited comparable bioactivation of APAP with that observed in the WT controls. However, a significant reduction in liver injury was observed in ShpHep-/- after APAP treatment for 6 and 24 h. The decreased liver injury correlated with a faster recovery of GSH, attributable to heightened expression of Nrf2 target genes involved in APAP detoxification and GSH synthesis. Moreover, in vitro studies revealed that SHP protein interacted with NRF2 protein, inhibiting the transcription of Nrf2 target genes. These findings hold relevance for humans, as overexpression of SHP hindered APAP-induced NRF2 activation in primary human hepatocytes. In conclusion, our studies have unveiled a novel regulatory axis involving SHP and NRF2 in APAP-induced acute liver injury, emphasizing SHP as a promising therapeutic target in APAP overdose-induced hepatotoxicity.

Small Heterodimer Partner Modulates Macrophage Differentiation during Innate Immune Response through the Regulation of Peroxisome Proliferator Activated Receptor Gamma, Mitogen-Activated Protein Kinase, and Nuclear Factor Kappa B Pathways.

Hepatic macrophages act as the liver's first line of defense against injury. Their differentiation into proinflammatory or anti-inflammatory subpopulations is a critical event that maintains a delicate balance between liver injury and repair. In our investigation, we explored the influence of the small heterodimer partner (SHP), a nuclear receptor primarily associated with metabolism, on macrophage differentiation during the innate immune response. During macrophage differentiation, we observed significant alterations in Shp mRNA expression. Deletion of Shp promoted M1 differentiation while interfering with M2 polarization. Conversely, overexpression of SHP resulted in increased expression of peroxisome proliferator activated receptor gamma (Pparg), a master regulator of anti-inflammatory macrophage differentiation, thereby inhibiting M1 differentiation. Upon lipopolysaccharide (LPS) injection, there was a notable increase in the proinflammatory M1-like macrophages, accompanied by exacerbated infiltration of monocyte-derived macrophages (MDMs) into the livers of Shp myeloid cell specific knockout (Shp-MKO). Concurrently, we observed significant induction of tumor necrosis factor alpha (Tnfa) and chemokine (C-C motif) ligand 2 (Ccl2) expression in LPS-treated Shp-MKO livers. Additionally, the mitogen-activated protein kinase (MAPK) and nuclear factor kappa B (NF-κB) pathways were activated in LPS-treated Shp-MKO livers. Consistently, both pathways were hindered in SHP overexpression macrophages. Finally, we demonstrated that SHP interacts with p65, thereby influencing macrophage immune repones. In summary, our study uncovered a previously unrecognized role of SHP in promoting anti-inflammatory macrophage differentiation during the innate immune response. This was achieved by SHP acting as a regulator for the Pparg, MAPK, and NF-κB pathways.

CT radiomics for differentiating fat poor angiomyolipoma from clear cell renal cell carcinoma: Systematic review and meta-analysis.

PURPOSE: Differentiation of fat-poor angiomyolipoma (fp-AMLs) from renal cell carcinoma (RCC) is often not possible from just visual interpretation of conventional cross-sectional imaging, typically requiring biopsy or surgery for diagnostic confirmation. However, radiomics has the potential to characterize renal masses without the need for invasive procedures. Here, we conducted a systematic review on the accuracy of CT radiomics in distinguishing fp-AMLs from RCCs. METHODS: We conducted a search using PubMed/MEDLINE, Google Scholar, Cochrane Library, Embase, and Web of Science for studies published from January 2011-2022 that utilized CT radiomics to discriminate between fp-AMLs and RCCs. A random-effects model was applied for the meta-analysis according to the heterogeneity level. Furthermore, subgroup analyses (group 1: RCCs vs. fp-AML, and group 2: ccRCC vs. fp-AML), and quality assessment were also conducted to explore the possible effect of interstudy differences. To evaluate CT radiomics performance, the pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were assessed. This study is registered with PROSPERO (CRD42022311034). RESULTS: Our literature search identified 10 studies with 1456 lesions in 1437 patients. Pooled sensitivity was 0.779 [95% CI: 0.562-0.907] and 0.817 [95% CI: 0.663-0.910] for groups 1 and 2, respectively. Pooled specificity was 0.933 [95% CI: 0.814-0.978]and 0.926 [95% CI: 0.854-0.964] for groups 1 and 2, respectively. Also, our findings showed higher sensitivity and specificity of 0.858 [95% CI: 0.742-0.927] and 0.886 [95% CI: 0.819-0.930] for detecting ccRCC from fp-AML in the unenhanced phase of CT scan as compared to the corticomedullary and nephrogenic phases of CT scan. CONCLUSION: This study suggested that radiomic features derived from CT has high sensitivity and specificity in differentiating RCCs vs. fp-AML, particularly in detecting ccRCCs vs. fp-AML. Also, an unenhanced CT scan showed the highest specificity and sensitivity as compared to contrast CT scan phases. Differentiating between fp-AML and RCC often is not possible without biopsy or surgery; radiomics has the potential to obviate these invasive procedures due to its high diagnostic accuracy.

Complications after Nephron-sparing Interventions for Renal Tumors: Imaging Findings and Management.

The two primary nephron-sparing interventions for treating renal masses such as renal cell carcinoma are surgical partial nephrectomy (PN) and image-guided percutaneous thermal ablation. Nephron-sparing surgery, such as PN, has been the standard of care for treating many localized renal masses. Although uncommon, complications resulting from PN can range from asymptomatic and mild to symptomatic and life-threatening. These complications include vascular injuries such as hematoma, pseudoaneurysm, arteriovenous fistula, and/or renal ischemia; injury to the collecting system causing urinary leak; infection; and tumor recurrence. The incidence of complications after any nephron-sparing surgery depends on many factors, such as the proximity of the tumor to blood vessels or the collecting system, the skill or experience of the surgeon, and patient-specific factors. More recently, image-guided percutaneous renal ablation has emerged as a safe and effective treatment option for small renal tumors, with comparable oncologic outcomes to those of PN and a low incidence of major complications. Radiologists must be familiar with the imaging findings encountered after these surgical and image-guided procedures, especially those indicative of complications. The authors review cross-sectional imaging characteristics of complications after PN and image-guided thermal ablation of kidney tumors and highlight the respective management strategies, ranging from clinical observation to interventions such as angioembolization or repeat surgery. Work of the U.S. Government published under an exclusive license with the RSNA. Online supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article. Quiz questions for this article are available in the Online Learning Center. See the invited commentary by Chung and Raman in this issue.

Clinical, genetic, epidemiologic, evolutionary, and functional delineation of TSPEAR-related autosomal recessive ectodermal dysplasia 14.

TSPEAR variants cause autosomal recessive ectodermal dysplasia (ARED) 14. The function of TSPEAR is unknown. The clinical features, the mutation spectrum, and the underlying mechanisms of ARED14 are poorly understood. Combining data from new and previously published individuals established that ARED14 is primarily characterized by dental anomalies such as conical tooth cusps and hypodontia, like those seen in individuals with WNT10A-related odontoonychodermal dysplasia. AlphaFold-predicted structure-based analysis showed that most of the pathogenic TSPEAR missense variants likely destabilize the ß-propeller of the protein. Analysis of 100000 Genomes Project (100KGP) data revealed multiple founder TSPEAR variants across different populations. Mutational and recombination clock analyses demonstrated that non-Finnish European founder variants likely originated around the end of the last ice age, a period of major climatic transition. Analysis of gnomAD data showed that the non-Finnish European population TSPEAR gene-carrier rate is ∼1/140, making it one of the commonest AREDs. Phylogenetic and AlphaFold structural analyses showed that TSPEAR is an ortholog of drosophila Closca, an extracellular matrix-dependent signaling regulator. We, therefore, hypothesized that TSPEAR could have a role in enamel knot, a structure that coordinates patterning of developing tooth cusps. Analysis of mouse single-cell RNA sequencing (scRNA-seq) data revealed highly restricted expression of Tspear in clusters representing enamel knots. A tspeara -/-;tspearb -/- double-knockout zebrafish model recapitulated the clinical features of ARED14 and fin regeneration abnormalities of wnt10a knockout fish, thus suggesting interaction between tspear and wnt10a. In summary, we provide insights into the role of TSPEAR in ectodermal development and the evolutionary history, epidemiology, mechanisms, and consequences of its loss of function variants.

Automatic segmentation of clear cell renal cell tumors, kidney, and cysts in patients with von Hippel-Lindau syndrome using U-net architecture on magnetic resonance images.

We demonstrate automated segmentation of clear cell renal cell carcinomas (ccRCC), cysts, and surrounding normal kidney parenchyma in patients with von Hippel-Lindau (VHL) syndrome using convolutional neural networks (CNN) on Magnetic Resonance Imaging (MRI). We queried 115 VHL patients and 117 scans (3 patients have two separate scans) with 504 ccRCCs and 1171 cysts from 2015 to 2021. Lesions were manually segmented on T1 excretory phase, co-registered on all contrast-enhanced T1 sequences and used to train 2D and 3D U-Net. The U-Net performance was evaluated on 10 randomized splits of the cohort. The models were evaluated using the dice similarity coefficient (DSC). Our 2D U-Net achieved an average ccRCC lesion detection Area under the curve (AUC) of 0.88 and DSC scores of 0.78, 0.40, and 0.46 for segmentation of the kidney, cysts, and tumors, respectively. Our 3D U-Net achieved an average ccRCC lesion detection AUC of 0.79 and DSC scores of 0.67, 0.32, and 0.34 for kidney, cysts, and tumors, respectively. We demonstrated good detection and moderate segmentation results using U-Net for ccRCC on MRI. Automatic detection and segmentation of normal renal parenchyma, cysts, and masses may assist radiologists in quantifying the burden of disease in patients with VHL.

Use of immersive virtual reality to reduce anxiety during complex paediatric dressing changes.

In recent years, there has been an increasing interest in the practical applications of virtual reality (VR) in healthcare. One discussed application of this technology is to reduce anxiety during procedures for paediatric patients. Following skin loss in paediatric patients, careful management of the wound with appropriate dressings and frequent dressing changes is a key part of the treatment process. In children, continued dressing changes are often a source of anxiety, which complicates procedures causing distress to the child, their parents and staff members. VR systems have the potential to not only reduce anxiety but also pain in children requiring frequent dressing changes. Although our knowledge of this technology is improving, further research is needed to evaluate its full potential in this population and to establish guidelines to take advantage of the full potential of VR technology.

Evaluation of Microvascular Rarefaction in Vascular Cognitive Impairment and Heart Failure (CRUCIAL): Study Protocol for an Observational Study.

INTRODUCTION: Microvascular rarefaction, the functional reduction in perfused microvessels and structural reduction of microvascular density, seems to be an important mechanism in the pathophysiology of small blood vessel-related disorders including vascular cognitive impairment (VCI) due to cerebral small vessel disease and heart failure with preserved ejection fraction (HFpEF). Both diseases share common risk factors including hypertension, diabetes mellitus, obesity, and ageing; in turn, these comorbidities are associated with microvascular rarefaction. Our consortium aims to investigate novel non-invasive tools to quantify microvascular health and rarefaction in both organs, as well as surrogate biomarkers for cerebral and/or cardiac rarefaction (via sublingual capillary health, vascular density of the retina, and RNA content of circulating extracellular vesicles), and to determine whether microvascular density relates to disease severity. METHODS: The clinical research program of CRUCIAL consists of four observational cohort studies. We aim to recruit 75 VCI patients, 60 HFpEF patients, 60 patients with severe aortic stenosis (AS) undergoing surgical aortic valve replacement as a pressure overload HFpEF model, and 200 elderly participants with mixed comorbidities to serve as controls. Data collected will include medical history, physical examination, cognitive testing, advanced brain and cardiac MRI, ECG, echocardiography, sublingual capillary health, optical coherence tomography angiography (OCTa), extracellular vesicles RNA analysis, and myocardial remodelling-related serum biomarkers. The AS cohort undergoing surgery will also have myocardial biopsy for histological microvascular assessment. DISCUSSION: CRUCIAL will examine the pathophysiological role of microvascular rarefaction in VCI and HFpEF using advanced brain and cardiac MRI techniques. Furthermore, we will investigate surrogate biomarkers for non-invasive, faster, easier, and cheaper assessment of microvascular density since these are more likely to be disseminated into widespread clinical practice. If microvascular rarefaction is an early marker of developing small vessel diseases, then measuring rarefaction may allow preclinical diagnosis, with implications for screening, risk stratification, and prevention. Further knowledge of the relevance of microvascular rarefaction and its underlying mechanisms may provide new avenues for research and therapeutic targets.

Discrepancy in the use and interpretation of marker sutures among plastic surgeons and pathologists.

Marker sutures are often used for excised cutaneous lesions to aid histological analysis, however, there are no current guidelines to facilitate this in practice. The authors hypothesised that a lack of guidelines causes a variation in clinical practice and confusion of meaning between plastic surgeons and pathologists. This questionnaire-based study confirms the authors' hypothesis and highlights a discrepancy both between surgeons and in individual surgical practice. More importantly, we identify discord between histopathologists and plastic surgeons in relation to marker suture placement and report interpretation, leading to potential undertreatment of patients. This paper adds to the growing literature calling for guidelines regarding marker suture placement for cutaneous excision biopsies.