Search Results (14)

Background/Objectives: Ischemic colitis, typically caused by thrombosis or reduced blood flow in the inferior mesenteric artery, is the most common ischemic lesion at the colorectal level. This case contributes to existing knowledge by highlighting the rare co-occurrence of a thrombosed aortic aneurysm and ischemic colitis, pointing to a direct vascular etiology rather than a multifactorial or idiopathic cause. Methods: A thorough electronic search was conducted on PubMed to identify risk factors and etiological determinants of ischemic colitis. Results: We present the case of a 70-year-old male with diffuse abdominal pain and multiple cardiac comorbidities. A CT scan revealed aeroenteritis, aerocolia, fusiform aneurysmal dilation of the abdominal aorta (18 cm long, 7.3 cm in diameter, from below the renal arteries to the bifurcation), parietal thrombosis, a circulating lumen of 2.7 cm, and inferior mesenteric artery thrombosis. Intraoperatively, necrosis was found in the upper rectum, sigmoid colon, descending colon, and the middle third of the left transverse colon, with clear demarcation between healthy and necrotic tissue. A subtotal proctocolectomy with transverse colostomy was performed. Conclusions: This case highlights ischemic colitis as a vascular disorder, urging broader differential diagnosis when common causes are unclear. Timely imaging, a multidisciplinary approach, and attention to vascular risks are key to identifying rare causes like aneurysmal thrombosis. While thrombosed abdominal aortic aneurysms can cause mesenteric ischemia, their link to ischemic and ulcerative colitis is unique, emphasizing the importance of accurate risk assessment in treatment planning. Full article

Background: Chest X-rays are among the most frequently used imaging tests in medical practice. We aimed to assess the prognostic value of the cardio–thoracic ratio (CTR) and transverse cardiac diameter (TCD) and compare them with novel chest X-ray parameters used in screening for cardiac enlargement. Methods: CTR, TCD, and five other non-standard new radiographic indexes, including basic spherical index (BSI), assessing changes in cardiac silhouette in chest radiographs in posterior–anterior projection were related to increased left ventricular end-diastolic volume (LVEDV) and left ventricular hypertrophy (LVH) assessed in cardiac magnetic resonance imaging (CMR). Results: TCD, CTR, and BSI were the best predictors of both LVH and increased LVEDV diagnosed in CMR. The best sensitivity, along with good specificity in LVH prediction, defined as left ventricular mass/body surface area (BSA) > 72 g/m² in men or >55 g/m² in women, was observed when TCD and BSI parameters were used jointly (69.2%, 95% confidence interval [CI]: 52.4–83.0% and 80.0%, 95% CI: 51.9–95.7%, respectively). In the prediction of cardiac enlargement defined as LVEDV/BSA > 117 mL/m² in men or >101 mL/m² in women, BSI > 137.5 had the best sensitivity and specificity (85.0%, 95% CI: 62.1–96.8% and 82.4%, 95% CI: 65.5–93.2%, respectively). Conclusions: TCD may be valuable in the assessment of patients suspected of having cardiac enlargement. CTR and BSI serve as complementary tools for a more precise approach. TCD appears particularly useful for the prediction of LVH, while BSI demonstrates greater utility as an indicator of increased LVEDV. Full article

Objective: This study investigated the impact of maternal subclinical hypothyroidism on fetal thymus size and development and explored how inadequate thyroid hormone production in pregnant women affects the fetal thymus. Methods: Conducted at the Giresun Obstetrics, Gynecology, and Pediatrics Training and Research Hospital, this case–control study involved 86 pregnant women, 43 with hypothyroidism and 43 without. Maternal thyroid function was assessed using TSH and free T4 levels, and fetal thymus size and thymus–thorax ratio were measured using ultrasound. Exclusion criteria were chronic hypertension, gestational hypertension or eclampsia, multiple pregnancies, infectious diseases, renovascular diseases, diagnosed with hypothyroidism prior to pregnancy and other endocrine disorders, fetal cardiac diseases, and morbid obesity. Data collected included maternal age, gestational week, number of pregnancies, parity, number of living children, thyroid-stimulating hormone (TSH) and Free thyroxine 4 (T4) levels, and fetal thymus measurements (transverse diameter and thymus/thorax ratio). Statistical analyses were performed using the Mann–Whitney U test and logistic regression analysis. The relationships between TSH, thymus diameters, thorax diameters, and the thymus–thorax ratio were evaluated using Spearman’s correlation coefficient. Results: The thymus–thorax ratio was significantly reduced in the hypothyroid group (p = 0.003). Logistic regression analysis identified TSH as an independent risk factor for a low thymus–thorax ratio, with each unit increase in TSH associated with a 1.345-fold higher likelihood of having a low thymus–thorax ratio. A significant negative correlation was found between TSH levels and the TTR ratio (Spearman’s correlation coefficient r = −0.338, p = 0.001). Conclusions: An association was identified between maternal TSH levels and the thymus–thorax ratio, with increasing TSH levels correlating with a decrease in the thymus–thorax ratio. Regular monitoring of thyroid hormone levels during pregnancy and appropriate replacement treatment in cases of deficiency are crucial for optimal fetal thymus development. Further multicenter studies are needed to confirm these findings and investigate the long-term implications of altered fetal thymus development. Full article

Background: Cardiothoracic ratio (CTR) and transverse cardiac diameter (TCD) are parameters that are used to assess cardiac size on chest radiographs (CXRs). We aimed to investigate the performance and efficiency of artificial intelligence (AI) in screening for cardiomegaly on CXRs. Methods: The U-net architecture was designed for lung and heart segmentation. The CTR and TCD were then calculated using these labels and a mathematical algorithm. For the training set, we retrospectively included 65 randomly selected patients who underwent CXRs, while for the testing set, we chose 50 patients who underwent cardiac magnetic resonance (CMR) imaging and had available CXRs in the medical documentation. Results: Using U-net for the training set, the Dice coefficient for the lung was 0.984 ± 0.003 (min. 0.977), while for the heart it was 0.983 ± 0.004 (min. 0.972). For the testing set, the Dice coefficient for the lung was 0.970 ± 0.012 (min. 0.926), while for the heart it was 0.950 ± 0.021 (min. 0.871). The mean CTR and TCD measurements were slightly greater when calculated from either manual or automated segmentation than when manually read. Receiver operating characteristic analyses showed that both the CTR and TCD measurements calculated from either manual or automated segmentation, or when manually read, were good predictors of cardiomegaly diagnosed in CMR. However, McNemar tests have shown that diagnoses made with TCD, rather than CTR, were more consistent with CMR diagnoses. According to a different definition of cardiomegaly based on CMR imaging, accuracy for CTR measurements ranged from 62.0 to 74.0% for automatic segmentation (for TCD it ranged from 64.0 to 72.0%). Conclusion: The use of AI may optimize the screening process for cardiomegaly on CXRs. Future studies should focus on improving the accuracy of AI algorithms and on assessing the usefulness both of CTR and TCD measurements in screening for cardiomegaly. Full article

The three-vessel view (3VV) is a standardized transverse scanning plane used in fetal cardiac ultrasound screening to measure the absolute and relative diameters of the pulmonary artery (PA), ascending aorta (Ao), and superior vena cava, as required. The PA/Ao ratio is used to support the diagnosis of congenital heart disease (CHD). However, vascular diameters are measured manually by examiners, which causes intra- and interobserver variability in clinical practice. In the present study, we aimed to develop an artificial intelligence-based method for the standardized and quantitative evaluation of 3VV. In total, 315 cases and 20 examiners were included in this study. We used the object-detection software YOLOv7 for the automated extraction of 3VV images and compared three segmentation algorithms: DeepLabv3+, UNet3+, and SegFormer. Using the PA/Ao ratios based on vascular segmentation, YOLOv7 plus UNet3+ yielded the most appropriate classification for normal fetuses and those with CHD. Furthermore, YOLOv7 plus UNet3+ achieved an arithmetic mean value of 0.883 for the area under the receiver operating characteristic curve, which was higher than 0.749 for residents and 0.808 for fellows. Our automated method may support unskilled examiners in performing quantitative and objective assessments of 3VV images during fetal cardiac ultrasound screening. Full article

Objectives: The purpose of this study is to evaluate the performance of our deep learning algorithm in calculating cardiothoracic ratio (CTR) and thus in the assessment of cardiomegaly or pericardial effusion occurrences on chest radiography (CXR). Methods: From a database of 8000 CXRs, 13 folders with a comparable number of images were created. Then, 1020 images were chosen randomly, in proportion to the number of images in each folder. Afterward, CTR was calculated using RadiAnt Digital Imaging and Communications in Medicine (DICOM) Viewer software (2023.1). Next, heart and lung anatomical areas were marked in 3D Slicer. From these data, we trained an AI model which segmented heart and lung anatomy and determined the CTR value. Results: Our model achieved an Intersection over Union metric of 88.28% for the augmented training subset and 83.06% for the validation subset. F1-score for subsets were accordingly 90.22% and 90.67%. In the comparative analysis of artificial intelligence (AI) vs. humans, significantly lower transverse thoracic diameter (TTD) (p < 0.001), transverse cardiac diameter (TCD) (p < 0.001), and CTR (p < 0.001) values obtained using the neural network were observed. Conclusions: Results confirm that there is a significant correlation between the measurements made by human observers and the neural network. After validation in clinical conditions, our method may be used as a screening test or advisory tool when a specialist is not available, especially on Intensive Care Units (ICUs) or Emergency Departments (ERs) where time plays a key role. Full article

Background: Irreversible electroporation (IRE) is a non-thermal form of ablation based on the delivery of pulsed electrical fields. It has been used to treat liver lesions, particularly those in proximity to major hepatic vasculature. The role of this technique in the portfolio of treatments for colorectal hepatic metastases has not been clearly defined. This study undertakes a systematic review of IRE for treatment of colorectal hepatic metastases. Methods: The study protocol was registered with the PROSPERO register of systematic reviews (CRD42022332866) and reports in compliance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA). The Ovid MEDLINE^®, EMBASE, Web of Science and Cochrane databases were queried in April 2022. The search terms ‘irreversible electroporation’, ‘colon cancer’, ‘rectum cancer’ and ‘liver metastases’ were used in combinations. Studies were included if they provided information on the use of IRE for patients with colorectal hepatic metastases and reported procedure and disease-specific outcomes. The searches returned 647 unique articles and the exclusions left a total of eight articles. These were assessed for bias using the methodological index for nonrandomized studies (MINORS criteria) and reported using the synthesis without meta-analysis guideline (SWiM). Results: One hundred eighty patients underwent treatment for liver metastases from colorectal cancer. The median transverse diameter of tumours treated by IRE was <3 cm. Ninety-four (52%) tumours were adjacent to major hepatic inflow/outflow structures or the vena cava. IRE was undertaken under general anaesthesia with cardiac cycle synchronisation and with the use of either CT or ultrasound for lesion localisation. Probe spacing was less than 3.2 cm for all ablations. There were two (1.1%) procedure-related deaths in 180 patients. There was one (0.5%) post-operative haemorrhage requiring laparotomy, one (0.5%) bile leak, five (2.8%) post-procedure biliary strictures and a zero incidence of post-IRE liver failure. Conclusions: This systematic review shows that IRE for colorectal liver metastases can be accomplished with low procedure-related morbidity and mortality. Further prospective study is required to assess the role of IRE in the portfolio of treatments for patients with liver metastases from colorectal cancer. Full article

Background and objectives: The optic nerve sheath diameter (ONSD) is indicative of elevated intracranial pressure. However, the usefulness of the ONSD for predicting neurologic outcomes in cardiac arrest survivals has been debatable. Reportedly, the ONSD/eyeball transverse diameter (ETD) ratio is a more reliable marker for identifying intracranial pressure than sole use of ONSD. Materials and Methods: This retrospective study aimed to investigate the prognostic value of the ONSD/ETD ratio in out-of-hospital cardiac arrest (OHCA) patients. We studied the brain computed tomography scans of adult OHCA patients with return of spontaneous circulation, who visited a single hospital connected with a Korean university between January 2015 and September 2020. We collected baseline characteristics and patient information from electronic medical records and ONSD and ETD were measured by two physicians with a pre-defined protocol. According to their neurologic outcome upon hospital discharge, patients were divided into good neurologic outcome (GNO; cerebral performance category [CPC] 1–2) and poor neurologic outcome (PNO; CPC 3–5) groups. We evaluated the ONSD/ETD ratio between the GNO and PNO groups to establish its prognostic value for neurologic outcomes. Results: Of the 100 included patients, 28 had GNO. Both the ONSD and ETD were not significantly different between the two groups (ONSD, 5.48 mm vs. 5.66 mm, p = 0.054; ETD, 22.98 mm vs. 22.61 mm, p = 0.204). However, the ONSD/ETD ratio was significantly higher in the PNO group in the univariate analysis (0.239 vs. 0.255, p = 0.014). The area under the receiver operating characteristic curve of ONSD/ETD ratio for predicting PNO was 0.66 (95% confidence interval, 0.56–0.75; p = 0.006). There was no independent relationship between the ONSD/ETD ratio and PNO in multivariate analysis (aOR = 0.000; p = 0.173). Conclusions: The ONSD/ETD ratio was more reliable than sole use of ONSD and might be used to predict neurologic outcomes in OHCA survivors. Full article

Left ventricular hypertrophy (LVH) is associated with adverse clinical outcomes and implicates clinical decision-making. The aim of our study was to assess the importance of different approaches in the screening for LVH. We included patients who underwent cardiac magnetic resonance (CMR) imaging and had available chest radiograph in medical documentation. Cardiothoracic ratio (CTR), transverse cardiac diameter (TCD), clinical and selected electrocardiographic (ECG)-LVH data, including the Peguero-Lo Presti criterion, were assessed. CMR–LVH was defined based on indexed left ventricular mass-to-body surface area. Receiver operating characteristics analyses showed that both the CTR and TCD (CTR: area under the curve: [AUC] = 0.857, p < 0.001; TCD: AUC = 0.788, p = 0.001) were predictors for CMR–LVH. However, analyses have shown that diagnoses made with TCD, but not CTR, were consistent with CMR–LVH. From the analyzed ECG–LVH criteria, the Peguero-Lo Presti criterion was the best predictor of LVH. The best sensitivity for screening for LVH was observed when the presence of heart failure, ≥40 years in age (each is assigned 1 point), increased TCD and positive Peguero-Lo Presti criterion (each is assigned 2 points) were combined (CAR₂E₂ score ≥ 3 points). CAR₂E₂ score may improve prediction of LVH compared to other approaches. Therefore, it may be useful in the screening for LVH in everyday clinical practice in patients with prevalent cardiovascular diseases. Full article

Semantic segmentation for diagnosing chest-related diseases like cardiomegaly, emphysema, pleural effusions, and pneumothorax is a critical yet understudied tool for identifying the chest anatomy. A dangerous disease among these is cardiomegaly, in which sudden death is a high risk. An expert medical practitioner can diagnose cardiomegaly early using a chest radiograph (CXR). Cardiomegaly is a heart enlargement disease that can be analyzed by calculating the transverse cardiac diameter (TCD) and the cardiothoracic ratio (CTR). However, the manual estimation of CTR and other chest-related diseases requires much time from medical experts. Based on their anatomical semantics, artificial intelligence estimates cardiomegaly and related diseases by segmenting CXRs. Unfortunately, due to poor-quality images and variations in intensity, the automatic segmentation of the lungs and heart with CXRs is challenging. Deep learning-based methods are being used to identify the chest anatomy segmentation, but most of them only consider the lung segmentation, requiring a great deal of training. This work is based on a multiclass concatenation-based automatic semantic segmentation network, CardioNet, that was explicitly designed to perform fine segmentation using fewer parameters than a conventional deep learning scheme. Furthermore, the semantic segmentation of other chest-related diseases is diagnosed using CardioNet. CardioNet is evaluated using the JSRT dataset (Japanese Society of Radiological Technology). The JSRT dataset is publicly available and contains multiclass segmentation of the heart, lungs, and clavicle bones. In addition, our study examined lung segmentation using another publicly available dataset, Montgomery County (MC). The experimental results of the proposed CardioNet model achieved acceptable accuracy and competitive results across all datasets. Full article

The transcription factor EB (TFEB) promotes protein degradation by the autophagy and lysosomal pathway (ALP) and overexpression of TFEB was suggested for the treatment of ALP-related diseases that often affect the heart. However, TFEB-mediated ALP induction may perturb cardiac stress response. We used adeno-associated viral vectors type 9 (AAV9) to overexpress TFEB (AAV9-Tfeb) or Luciferase-control (AAV9-Luc) in cardiomyocytes of 12-week-old male mice. Mice were subjected to transverse aortic constriction (TAC, 27G; AAV9-Luc: n = 9; AAV9-Tfeb: n = 14) or sham (AAV9-Luc: n = 9; AAV9-Tfeb: n = 9) surgery for 28 days. Heart morphology, echocardiography, gene expression, and protein levels were monitored. AAV9-Tfeb had no effect on cardiac structure and function in sham animals. TAC resulted in compensated left ventricular hypertrophy in AAV9-Luc mice. AAV9-Tfeb TAC mice showed a reduced LV ejection fraction and increased left ventricular diameters. Morphological, histological, and real-time PCR analyses showed increased heart weights, exaggerated fibrosis, and higher expression of stress markers and remodeling genes in AAV9-Tfeb TAC compared to AAV9-Luc TAC. RNA-sequencing, real-time PCR and Western Blot revealed a stronger ALP activation in the hearts of AAV9-Tfeb TAC mice. Cardiomyocyte-specific TFEB-overexpression promoted ALP gene expression during TAC, which was associated with heart failure. Treatment of ALP-related diseases by overexpression of TFEB warrants careful consideration. Full article

Background: The extent of aortic replacement for aneurysms of the distal ascending aorta remains controversial and opinions vary between standard cross-clamp resection and open hemiarch anastomosis in circulatory arrest and selective cerebral perfusion. As the deleterious effects of extended circulatory arrest are well-known, borderline indication for distal ascending aorta aneurysm repair must be outweighed against the potential risk of complications related to the open anastomosis. In the present study, we describe our own approach consisting of “transversal arch clamping” for exhaustive resection of aneurysms of the distal ascending aorta without open anastomosis and we present the postoperative outcomes. Methods: Between May 2017 and December 2019, 35 patients with aneurysm of the ascending aorta (20 male, 15 female) underwent replacement with repair of the lesser curvature without circulatory arrest. Pre-operative, intraoperative, and postoperative clinical outcomes were retrospectively withdrawn from our institutional database and analyzed. Results: Maximal diameter of distal ascending aorta was 47.5 mm. Patient median age was 66 years (IQR 14) (range 42–86). Preoperative logistic median EuroSCORE II was 17% (IQR 11.3). Median duration of cardiopulmonary bypass and cardiac arrest were 137 (IQR 64) and 93 (IQR 59) min, respectively. In-hospital and 30-day mortality were 0%. There were no cases with acute low output syndrome, surgical re-exploration for bleeding, kidney injury requiring dialysis, or wound infection. Disabling stroke was observed in one patient (2.9%). There was one case of major ventricular arrhythmia (2.9%). Conclusions: Our institutional experience suggests that this novel technique is safe and feasible. It facilitates complete resection of the aortic ascending aneurysm avoiding circulatory arrest, antegrade cerebral perfusion, additional peripheral cannulation, and all related complications. Full article

Fetal Heart Quantification (FetalHQ^®) is a novel speckle tracking software that permits the study of global and regional ventricular shape and function from a 2D four-chamber-view loop. The 4D-Spatio Temporal Image Correlation (STIC) modality enables the offline analysis of optimized and perfectly aligned cardiac planes. We aimed to evaluate the feasibility and reproducibility of 4D-STIC speckle tracking echocardiography (STE) using FetalHQ^® and to compare it to 2D STE. We conducted a prospective study including 31 low-risk singleton pregnancies between 20 and 40 weeks of gestation. Four-chamber view volumes and 2D clips were acquired with an apex pointing at 45° and with a frame rate higher than 60 Hz. Morphometric and functional echocardiography was performed by FetalHQ^®. Intra- and interobserver reproducibility were evaluated by the intraclass correlation coefficient (ICC). Our results showed excellent reproducibility (ICC > 0.900) for morphometric evaluation (biventricular area, longitudinal and transverse diameters). Reproducibility was also good (ICC > 0.800) for functional evaluation (biventricular strain, Fractional Area Change, left ventricle volumes, ejection fraction and cardiac output). On the contrary, the study of the sphericity index and shortening fraction of the different ventricular segments showed lower reproducibility (ICC < 0.800). To conclude, 4D-STIC is feasible, reproducible and comparable to 2D echocardiography for the assessment of cardiac morphometry and function. Full article

Automatic chest anatomy segmentation plays a key role in computer-aided disease diagnosis, such as for cardiomegaly, pleural effusion, emphysema, and pneumothorax. Among these diseases, cardiomegaly is considered a perilous disease, involving a high risk of sudden cardiac death. It can be diagnosed early by an expert medical practitioner using a chest X-Ray (CXR) analysis. The cardiothoracic ratio (CTR) and transverse cardiac diameter (TCD) are the clinical criteria used to estimate the heart size for diagnosing cardiomegaly. Manual estimation of CTR and other diseases is a time-consuming process and requires significant work by the medical expert. Cardiomegaly and related diseases can be automatically estimated by accurate anatomical semantic segmentation of CXRs using artificial intelligence. Automatic segmentation of the lungs and heart from the CXRs is considered an intensive task owing to inferior quality images and intensity variations using nonideal imaging conditions. Although there are a few deep learning-based techniques for chest anatomy segmentation, most of them only consider single class lung segmentation with deep complex architectures that require a lot of trainable parameters. To address these issues, this study presents two multiclass residual mesh-based CXR segmentation networks, X-RayNet-1 and X-RayNet-2, which are specifically designed to provide fine segmentation performance with a few trainable parameters compared to conventional deep learning schemes. The proposed methods utilize semantic segmentation to support the diagnostic procedure of related diseases. To evaluate X-RayNet-1 and X-RayNet-2, experiments were performed with a publicly available Japanese Society of Radiological Technology (JSRT) dataset for multiclass segmentation of the lungs, heart, and clavicle bones; two other publicly available datasets, Montgomery County (MC) and Shenzhen X-Ray sets (SC), were evaluated for lung segmentation. The experimental results showed that X-RayNet-1 achieved fine performance for all datasets and X-RayNet-2 achieved competitive performance with a 75% parameter reduction. Full article