Side specific differences of Hounsfield-Units in the osteoporotic lumbar spine.

Background: Gold standard for determining bone density as a surrogate parameter of bone quality is measurement of bone mineral density (BMD) by dual energy X-ray absorptiometry (DXA), most commonly performed on the lumbar spine (L1-L4). Computed tomography (CT) data are often available for surgical planning prior to spine procedures, but currently this information is not standardized for bone quality assessment. Besides, measuring the Hounsfield-Units (HU) is also of great importance in the context of biomechanical studies. This in vitro study aims in comparing BMD from DXA and HU based on diagnostic CT scans. In addition, methods are presented to quantify local density variations within bones. Methods: One hundred and seventy-six vertebrae (L1-L4) from 44 body donors (age 84.0±8.7 years) were studied. DXA measurements were obtained on the complete vertebrae to determine BMD, as well as axial CT scans with a slice thickness of 1 mm. Using Mimics Innovation Suite image processing software (Materialise NV, Leuven, Belgium), two volumes (whole vertebra vs. spongious bone) were formed for each vertebra, which in turn were divided in their left and right sides. From these total of six volumes, the respective mean HU was determined. HU of the whole vertebra and just spongious HU were compared with the BMD of the corresponding vertebrae. Side specific differences were calculated as relative values. Results: Whole bone and spongious HU correlated significantly (P>0.001; α=0.01) with BMD. A positive linear correlation was found, which was more pronounced for whole bone HU (R=0.72) than for spongious HU (R=0.62). When comparing the left and right sides within each vertebra, the HU was found to be 10% larger on average on one side compared to the opposite side. In some cases, the difference of left and right spongious bone can be up to 170%. There is a tendency for the side comparison to be larger for the spongious HU than for the whole vertebra. Conclusions: Determination of HU from clinical CT scans is an important tool for assessing bone quality, primarily by including the cortical portion in the calculation of HU. Unlike BMD, HU can be used to distinguish precisely between individual regions. Some of the very large side-specific gradients of the HU indicate an enormous application potential for preoperative patient-specific planning.

Latarjet procedure restores range of motion at six months postoperatively: a prospective cohort study utilizing motion capture analysis.

BACKGROUND: There is a common concern that range of motion (ROM) is negatively affected by the Latarjet procedure. We hypothesize that the Latarjet procedure results in full recuperation of ROM postoperatively and significantly improved patient reported outcome measures. METHODS: Patient data were prospectively collected from a randomized controlled trial to analyze outcomes after open Latarjet procedure. Inclusion criteria involved a minimum follow-up of six months and unilateral shoulder instability. Study outcome was assessed by postoperative ROM at six months postoperatively and compared to the preoperative ROM of the ipsilateral shoulder as well as the ROM of the unaffected contralateral shoulder. All ROM measurements were performed utilizing a motion capture system to ensure consistent and reliable measurements. RESULTS: The study included a total of 84 patients. ROM was measured in external rotation with the shoulder adducted (ER1), external rotation with the shoulder abducted 90 degrees (ER2), internal rotation with the arm abducted 90 degrees (IR2), and active forward elevation (AE). The average difference in ROM between the operated arm vs. the contralateral healthy arm at six months postoperatively was 3.4 degrees in ER1 (p=0.19), 4.2 degrees in ER2 (p=0.086), 2.2 degrees in IR2 (p=0.36), and 2.4 degrees in AE (p=0.045). Sub-analysis of patients with and without sling use revealed no significant difference in ROM between the operated shoulder and contralateral shoulder at six months in either group, with the exception of ER2 in the sling group. In this latter group, ROM was 71 degrees in the operated arm and 79 degrees in the contralateral arm (p=0.0094). Average preoperative pain score was 25.7 (21.4-30.1, 95%CI) vs. 13.0 postoperatively at six months (9.50-16.5, 95%CI) (p <0.00001). Average preoperative SANE instability was 42.9 (38.4-47.3, 95%CI) vs. 86.2 postoperatively at six months (83.6-88.7, 95%CI) (p <0.00001). Average preoperative Rowe score was 38.5 (34.3-42.7, 95%CI) vs. 84.3 at six postoperative months (81.1-87.4, 95%CI) (p<0.00001). CONCLUSIONS: Latarjet procedure performed for anterior instability utilizing a capsular repair result in complete ROM recovery in ER1, ER2, and IR2 at six months postoperatively, with only a slight discrepancy in active elevation. Sling use after the Latarjet procedure results in no benefit over postoperative recovery without the use of a sling. Sling use negatively affects the ROM in ER2, taking as reference the contralateral arm of the same patient, when compared to patients that did not use a sling postoperatively.

Case report: Concurrent low-volume subdural hematoma and ipsilateral ischemic stroke presenting as capsular warning syndrome: a complex case with anticoagulation dilemma and dual pathology.

Background: The simultaneous emergence of low-volume subdural hematoma and ipsilateral ischemic stroke in an atrial fibrillation patient who is under anticoagulation therapy is a rare and intricate clinical case. This report accentuates the diagnostic and treatment complexities associated with these consecutive neurological conditions. Case presentation: An 83 years-old male patient initially presented with acute dyspnea, raising the suspicion of pulmonary embolism. After exclusion of pulmonary embolism through CT angiography, the patient experienced a sudden onset of left-sided hemiparesis without prior history of head trauma but with chronic intake of apixaban due to atrial fibrillation. Subsequent cranial CT tomography revealed a small right parietal subdural hematoma. After reversal of the anticoagulation therapy, surgical evacuation of the subdural hematoma was successfully performed. However, in the postoperative period, the patient developed new neurological symptoms that could not be explained by the reduced size of the subdural hematoma on a follow-up CT scan. Cranial MRI revealed the coexistence of acute ischemic stroke in the right corona radiata. The recent surgical procedure precluded guideline-recommended stroke treatment. Discussion: This case underscores the complexities of diagnosing and treating concomitant small volume subdural hematoma and ischemic stroke, especially if the latter occurs in the corona radiata resulting in fluctuating symptoms known as "capsular warning syndrome." Reversal and secondary discontinuation of anticoagulant therapy for surgical intervention highlight the inherent risk of thrombotic events in anticoagulated patients. The development of tailored treatment strategies requires a multidisciplinary approach, and further research and guidelines are required in similar complex scenarios. Conclusion: The presence of both a small subdural hematoma and an ipsilateral ischemic stroke presenting as capsular warning syndrome in an anticoagulated patient highlights the intricacy of their care. This case calls for a comprehensive and collaborative strategy to address complicated clinical scenarios.

Computer Tomography (CT)-Based Study to Investigate Feasibility and Efficacy of Thoracoscopic Surgery in the Treatment of Penetrating Chest Wall Tuberculosis.

BACKGROUND: Chest wall tuberculosis may develop if tuberculous (TB) lesions spread through the chest wall and invade the thoracic cavity. The presence of a mass on the patient's chest wall may be the first indication of TB, and a chest CT scan can help diagnose external penetrating chest wall TB, the incursion of tuberculosis from the lungs into the chest wall. OBJECTIVE: This study examines the safety and efficacy of thoracoscopic-assisted surgery for the treatment of penetrating chest wall tuberculosis as a means of exploring novel concepts of minimally invasive surgery. METHODS: Our hospital conducted a retrospective study of 25 patients with penetrating chest wall TB who underwent thoracoscopic surgery between January 2020 and June 2021. General demographics, CT scan data linked to surgery, and postoperative patient outcomes were compared between the two groups. The data was also evaluated to determine the range of operation time and the volume of bleeding from different foci in the thoracic cavity. RESULTS: All procedures went well after patients took conventional antituberculosis medication for at least two weeks prior to surgery. CT scans showed that thoracoscopic surgery needed a smaller incision than traditional chest wall TB surgery, with no discernible increase in surgical time. Postoperative tube use, length of hospital stay, and blood loss were all significantly lower than they would have been with conventional surgery. In addition, thoracoscopy was associated with a significantly reduced rate of subsequent treatment. Fibrous plate development and calcification caused the longest operation times in the thoracoscopic surgery group, whereas multiple pleural tuberculomas generated the most hemorrhage. Thoracoscopic surgery usually reveals tuberculous foci hiding in the thoracic cavity. CONCLUSION: Thethoracic surgery can eliminate the TB focus in the chest wall and intrathoracic while treating penetrating chest wall tuberculosis. The CT scan is a crucial part of the diagnostic process for these patients. Minor surgical trauma, low complication and recurrence rates, and good results. There is a greater distinction between the two surgical approaches for patients with penetrating chest wall TB as opposed to those with basic chest wall tuberculosis.

Diagnostic workup for esophageal cancer patients can be improved with checklists and clearer protocols; a comparative study between two tertiary centers in Europe.

BACKGROUND: Rapid and complete workup of newly diagnosed esophageal cancer is vital for a timely, individual and high-quality treatment strategy. The aim of this study was to uncover potential delay, inefficiencies and non-contributing investigations in the diagnostic process in two tertiary referral centers. METHODS: This retrospective cohort study included all newly diagnosed esophageal cancer patients referred to or diagnosed in the Amsterdam UMC and Karolinska University Hospital between July 2020 and July 2021. Radiology, pathological assessment and multidisciplinary team meeting reports were reviewed. To assess time interval from diagnosis to treatment, dates of diagnosis, admittance to referral hospital, MDT meeting and start of treatment were collected. RESULTS: In total, 252 esophageal cancer patients were included, 187 were treated with curative intent. Curatively treated patients had a mean age of 66 years, were predominantly male (74.9 %) with an adenocarcinoma (71.1 %). Curatively treated patients had a median time from diagnosis to referral of seven days (IQR:0-11) and of 35 days (IQR:28-45) between diagnosis and start of treatment. Main reasons for the significant (P < 0.001) differences in time between diagnosis and treatment between centers, Amsterdam UMC (39 days) vs Karolinska (27 days), were need for additional diagnostics (47.8 %) and differences in referral routine. Gastroscopy was repeated in 32.2 % of patients, mainly for further anatomical mapping. CONCLUSION: Significant time differences between centers in the path from diagnosis to start treatment can be explained by differences in workup approach, referral routines and MDT meeting regulations. Repeat of gastroscopy can be prevented with clearer endoscopy guidelines.

A pathological lesion or a postmortem artefact? An interdisciplinary approach to deal with an interesting early medieval case.

OBJECTIVE: This study evaluates a case of pseudopathology and the effects that postmortem taphonomic changes and environmental influences can have on bone. MATERIAL: A skeleton of a young male from the early medieval site Staré Mesto, dated to the 9th-10th century CE. METHODS: The skeletal remains were subjected to detailed macroscopic and X-ray examination, and then a CT scan and XRF analysis were performed. RESULTS: X-ray examination of the mandible revealed unusually dense structures, whose appearance was not consistent with any known pathology. Based on the results of CT scanning, it was hypothesized that these were cavities filled with alluvial sediment. X-ray fluorescence spectrometry (XRF), focusing on the determination of the silica content, revealed a high intensity of silica in the samples of the affected area of the bone. CONCLUSION: The hypothesis that the inclusions were composed of waterborne sediment was supported. SIGNIFICANCE: Although it is well known that soil can infiltrate bones buried in the ground, its appearance on plain radiographs is not that commonly known. The case illustrates the usefulness of differentiating true pathologies from postmortem alterations to avoid inappropriate interpretations. LIMITATIONS: No similar cases have been described. SUGGESTION FOR FURTHER RESEARCH: In palaeopathological evaluation, the use of multiple imaging and evaluative techniques should be implemented to differentiate pathological lesions from pseudopathology.

Evaluating the Potential of Delta Radiomics for Assessing Tyrosine Kinase Inhibitor Treatment Response in Non-Small Cell Lung Cancer Patients.

Our study aimed to harness the power of CT scans, observed over time, in predicting how lung adenocarcinoma patients might respond to a treatment known as EGFR-TKI. Analyzing scans from 322 advanced stage lung cancer patients, we identified distinct image-based patterns. By integrating these patterns with comprehensive clinical information, such as gene mutations and treatment regimens, our predictive capabilities were significantly enhanced. Interestingly, the precision of these predictions, particularly related to radiomics features, diminished when data from various centers were combined, suggesting that the approach requires standardization across facilities. This novel method offers a potential pathway to anticipate disease progression in lung adenocarcinoma patients treated with EGFR-TKI, laying the groundwork for more personalized treatments. To further validate this approach, extensive studies involving a larger cohort are pivotal.

Characterizing the Effect of Freeze-Thaw Cycling on Pore Structure of Asphalt Concrete Mixtures Using X-ray CT Scanning.

Freeze-thaw (F-T) cycling presents a challenge when building durable pavement structures in cold regions. Understanding the changes within the microstructure of asphalt concrete (AC) due to F-T conditions is crucial for developing a resilient pavement design. This study investigates the impact of F-T cycles on five AC mixtures using X-ray computed tomography (CT) scanning. Image analysis was completed to evaluate the changes in the microstructure of the AC samples before and after exposure to 30, 60, and 90 F-T cycles. The changes/degradation in the microstructure were evaluated based on analyzing the distribution and properties of air voids within the AC samples. The results showed that an X-ray CT scan can successfully capture the impact of F-T cycles on the structure of air voids in different AC mixtures. The findings of this research provide guidelines for understanding the mechanism of F-T damage within AC, which can assist in optimizing the performance of AC in cold regions.

Development of unilateral renal peripelvic lymphangiectasia after renal vein thrombosis.

Renal peripelvic lymphangiectasia is a rare entity that can mimic hydronephrosis on routine contrast-enhanced computer tomography (CT). While it may remain asymptomatic, symptomatic cases can exhibit refractory hypertension (HTN) and recurrent abdominal pain. Diagnostic challenges stem from its nonspecific symptoms and imaging characteristics, which can overlap with other renal disorders. Thereby, adequate protocolling of CT or magnetic resonance (MR) imaging is important for accurate diagnosis. In this report, we present a case of renal lymphangiectasia that developed in a medically complex patient following renal vein thrombosis.

Computer Tomography (CT)-based Screening of Hospitalized Patients with Moderate to Severe Chronic Obstructive Pulmonary Disease Complicated by Bronchiectasis Phenotype During Acute Exacerbation: A Clinical Analysis.

BACKGROUND: In the past, many experts considered chronic obstructive pulmonary disease (COPD) and bronchiectasis to be separate, chronic respiratory diseases. Nonetheless, the widespread use of high-resolution lung computed tomography (CT) has led to the discovery that these diseases can occur alone or together. AIM: The current study aimed to compare the effects of nutritional status on the clinical outcomes in moderate to severe COPD patients with bronchiectasis. OBJECTIVE: This study identifies the nutritional risk in hospitalized patients with moderate to severe COPD complicated by bronchiectasis phenotype during acute exacerbation screened using computer tomography (CT). Also, determines its correlation with disease progression. MATERIALS AND METHODS: NRS 2002 (Nutrition Risk Screening Evaluation Tool) was used to determine and evaluate the nutritional risk status in 182 hospitalized patients with moderate to severe COPD complicated by bronchiectasis phenotype during an acute exacerbation. Selected patients were divided into the nutritional risk (NR) group and the non-nutritional risk (NNR) group according to their nutritional status determined by NRS 2002. The body mass index (BMI), serum albumin (ALB), pre albumin (PAB), lymphocyte count (TLC), FEV1/FVC, FEV1% predicted, PEF% predicted, blood gas analysis, number of acute exacerbations in the past year, number of respiratory failure cases, number of anti-infection days, and length of hospitalization of the two groups were observed. RESULTS: The hospitalized patients in acute exacerbation of moderate to severe COPD complicated by bronchiectasis phenotype had a nutritional risk of 62.64%. BMI, ALB, PAB, TLC, FEV1% predicted, FEV1/FVC, PEF% predicted, blood gas analysis, number of acute exacerbations in the past year, number of respiratory failure cases, number of anti-infection days, and length of hospitalization were statistically significantly different between the NR group and NNR group (P<0.05). CONCLUSION: Hospitalized patients with moderate to severe COPD complicated by bronchiectasis phenotype during acute exacerbation are often associated with nutritional risk. An increase in nutritional risk reduces the level of pulmonary function of the patient and elevates the risk for repeated acute exacerbations, which predispose the patient to respiratory failure, thereby increasing the length of hospitalization. Therefore, the nutritional risk status of COPD patients with bronchiectasis was closely related to the occurrence, development, and prognosis of the disease.

Deep learning based synthetic CT from cone beam CT generation for abdominal paediatric radiotherapy.

Objective. Adaptive radiotherapy workflows require images with the quality of computed tomography (CT) for re-calculation and re-optimisation of radiation doses. In this work we aim to improve the quality of on-board cone beam CT (CBCT) images for dose calculation using deep learning.Approach. We propose a novel framework for CBCT-to-CT synthesis using cycle-consistent Generative Adversarial Networks (cycleGANs). The framework was tailored for paediatric abdominal patients, a challenging application due to the inter-fractional variability in bowel filling and small patient numbers. We introduced to the networks the concept of global residuals only learning and modified the cycleGAN loss function to explicitly promote structural consistency between source and synthetic images. Finally, to compensate for the anatomical variability and address the difficulties in collecting large datasets in the paediatric population, we applied a smart 2D slice selection based on the common field-of-view (abdomen) to our imaging dataset. This acted as a weakly paired data approach that allowed us to take advantage of scans from patients treated for a variety of malignancies (thoracic-abdominal-pelvic) for training purposes. We first optimised the proposed framework and benchmarked its performance on a development dataset. Later, a comprehensive quantitative evaluation was performed on an unseen dataset, which included calculating global image similarity metrics, segmentation-based measures and proton therapy-specific metrics.Main results. We found improved performance for our proposed method, compared to a baseline cycleGAN implementation, on image-similarity metrics such as Mean Absolute Error calculated for a matched virtual CT (55.0 ± 16.6 HU proposed versus 58.9 ± 16.8 HU baseline). There was also a higher level of structural agreement for gastrointestinal gas between source and synthetic images measured using the dice similarity coefficient (0.872 ± 0.053 proposed versus 0.846 ± 0.052 baseline). Differences found in water-equivalent thickness metrics were also smaller for our method (3.3 ± 2.4% proposed versus 3.7 ± 2.8% baseline).Significance. Our findings indicate that our innovations to the cycleGAN framework improved the quality and structure consistency of the synthetic CTs generated.

Incidence and oncological implication of adrenal incidentalomas in esophageal cancer patients.

Adrenal incidentalomas are regularly encountered during imaging for esophageal cancer patients, but their oncological significance remains unknown. This study aimed to describe the incidence and etiology of adrenal incidentalomas observed throughout the diagnostic workup. This retrospective cohort study included all esophageal cancer patients referred to or diagnosed in the Amsterdam UMC between January 2012 and December 2016. Radiology and multidisciplinary team meeting reports were reviewed for adrenal incidentalomas. In case of adrenal incidentaloma, the 18FDG-PET/CT was reassessed by a radiologist blinded for the original report. In case of a metachronous incidentaloma during follow-up, visibility on previous imaging was reassessed. Primary outcome was the incidence, etiology and oncological consequence of synchronous adrenal incidentalomas. This study included 1,164 esophageal cancer patients, with a median age of 66 years. Patients were predominantly male (76.1%) and the majority had an adenocarcinoma (69.0%). Adrenal incidentalomas were documented in 138 patients (11.9%) during the diagnostic workup. At primary esophageal cancer workup, 22 incidentalomas proved malignant. However, follow-up showed that four incidentalomas were inaccurately diagnosed as benign and three malignant incidentalomas were visible on staging imaging but initially missed. Stage migration occurred in 15 of 22 (68.2%), but this would have been higher if none were missed or inaccurately diagnosed. The oncological impact of adrenal incidentalomas in patients with esophageal cancer is significant as a considerable part of incidentalomas changed treatment intent from curative to palliative. As stage migration is likely, pathological examination of a synchronous adrenal incidentaloma should be weighted in mind.

The year 2021 in the European Heart Journal-Cardiovascular Imaging: Part I.

The European Heart Journal-Cardiovascular Imaging was introduced in 2012 and has during these 10 years become one of the leading multimodality cardiovascular imaging journals. The journal is currently ranked as Number 19 among all cardiovascular journals. It has an impressive impact factor of 9.130 and our journal is well established as one of the top cardiovascular journals. The most important studies published in our Journal in 2021 will be highlighted in two reports. Part I of the review will focus on studies about myocardial function and risk prediction, myocardial ischaemia, and emerging techniques in cardiovascular imaging, while Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease.

Early Prediction of Lung Cancers Using Deep Saliency Capsule and Pre-Trained Deep Learning Frameworks.

Lung cancer is the cellular fission of abnormal cells inside the lungs that leads to 72% of total deaths worldwide. Lung cancer are also recognized to be one of the leading causes of mortality, with a chance of survival of only 19%. Tumors can be diagnosed using a variety of procedures, including X-rays, CT scans, biopsies, and PET-CT scans. From the above techniques, Computer Tomography (CT) scan technique is considered to be one of the most powerful tools for an early diagnosis of lung cancers. Recently, machine and deep learning algorithms have picked up peak energy, and this aids in building a strong diagnosis and prediction system using CT scan images. But achieving the best performances in diagnosis still remains on the darker side of the research. To solve this problem, this paper proposes novel saliency-based capsule networks for better segmentation and employs the optimized pre-trained transfer learning for the better prediction of lung cancers from the input CT images. The integration of capsule-based saliency segmentation leads to the reduction and eventually reduces the risk of computational complexity and overfitting problem. Additionally, hyperparameters of pretrained networks are tuned by the whale optimization algorithm to improve the prediction accuracy by sacrificing the complexity. The extensive experimentation carried out using the LUNA-16 and LIDC Lung Image datasets and various performance metrics such as accuracy, precision, recall, specificity, and F1-score are evaluated and analyzed. Experimental results demonstrate that the proposed framework has achieved the peak performance of 98.5% accuracy, 99.0% precision, 98.8% recall, and 99.1% F1-score and outperformed the DenseNet, AlexNet, Resnets-50, Resnets-100, VGG-16, and Inception models.

Segmentation of CT Lung Images Using FCM with Active Contour and CNN Classifier.

OBJECTIVE: Lung cancer is one of the unsafe diseases for human which reduces the patient life time. Generally, most of the lung cancers are identified after it has been spread into the lung parts and moreover it is difficult to find the lung cancer at the early stage. It requires radiologist and special doctors to find the tumoral tissue of the lung cancer. For this reason, the recommended work helps to segment the tumoral tissue of CT lung image in an effective way. METHODS:  The research work uses hybrid segmentation technique to separate the lung cancer cells to diagnose the lung tumour. It is a technique which combines active contour along with Fuzzy c means to diagnose the tumoral tissue. Further the segmented portion was trained by Convolutional Neural Network (CNN) in order to classify the segmented region as normal or abnormal. RESULTS: The evaluation of the proposed method was done by analyzing the results of test image with the ground truth image. Finally, the results of the implemented technique provided good accuracy, Peak signal to noise ratio (PSNR), Mean Square Error (MSE) value. In future the other techniques can be utilized to improve the details before segmentation. The proposed work provides 96.67 % accuracy. CONCLUSION: Hybrid segmentation technique involves several steps like preprocessing, binarization, thresholding, segmentation and feature extraction using GLCM.

Study of Different Deep Learning Methods for Coronavirus (COVID-19) Pandemic: Taxonomy, Survey and Insights.

COVID-19 has evolved into one of the most severe and acute illnesses. The number of deaths continues to climb despite the development of vaccines and new strains of the virus have appeared. The early and precise recognition of COVID-19 are key in viably treating patients and containing the pandemic on the whole. Deep learning technology has been shown to be a significant tool in diagnosing COVID-19 and in assisting radiologists to detect anomalies and numerous diseases during this epidemic. This research seeks to provide an overview of novel deep learning-based applications for medical imaging modalities, computer tomography (CT) and chest X-rays (CXR), for the detection and classification COVID-19. First, we give an overview of the taxonomy of medical imaging and present a summary of types of deep learning (DL) methods. Then, utilizing deep learning techniques, we present an overview of systems created for COVID-19 detection and classification. We also give a rundown of the most well-known databases used to train these networks. Finally, we explore the challenges of using deep learning algorithms to detect COVID-19, as well as future research prospects in this field.

Acute Respiratory Failure, Ischemic Modifications on Electrocardiogram: Alternative Etiology-A Case of Morgagni Hernia.

We discovered a rare pathology described in adulthood, followed by the development of a long asymptomatic evolution, which underlined the importance of multidisciplinary collaboration. We present the case of a 62-year-old female smoker patient, with a known previous medical history of chronic ischemic heart disease, hypertension, chronic obstructive pulmonary disease (COPD), gastric ulcer and gastritis. The patient was rushed to the emergency room (ER) with acute respiratory failure, chest discomfort, ankle and facial edema and a chest X-ray showing a right lower pulmonary lobe consolidation, with an alarming ischemic electrocardiogram (ECG) modification without increasing myocardial cytolysis indicators. This led our medical team to investigate a possible cardiovascular event that might have been in development. After immediate admission, thoracic computer tomography (CT) imaging was carried out, which found a Morgagni diaphragmatic hernia, containing adipose tissue and the hepatic flexure of the colon with approximate dimensions of 50/100 mm. We faced differential diagnostic problems. We knew the subject's existing cardiac and chronic respiratory tract pathologies from their previous medical history; therefore, multiple investigations and check-ups were carried out. A chest CT and surgery intervention were needed to resolve this case. Subsequently, the acute respiratory failure and alarming ischemic ECG modification disappeared.

Time-Based Decision Making for Reperfusion in Acute Ischemic Stroke.

Decision making in the extended time windows for acute ischemic stroke can be a complex and time-consuming process. The process of making the clinical decision to treat has been compounded by the availability of different imaging modalities. In the setting of acute ischemic stroke, time is of the essence and chances of a good outcome diminish by each passing minute. Navigating the plethora of advanced imaging modalities means that treatment in some cases can be inefficaciously delayed. Time delays and individually based non-programmed decision making can prove challenging for clinicians. Visual aids can assist such decision making aimed at simplifying the use of advanced imaging. Flow charts are one such visual tool that can expedite treatment in this setting. A systematic review of existing literature around imaging modalities based on site of occlusion and time from onset can be used to aid decision making; a more program-based thought process. The use of an acute reperfusion flow chart helping navigate the myriad of imaging modalities can aid the effective treatment of patients.

A Three-Dimensional Imaging Method for the Quantification and Localization of Dynamic Cell Tracking Posttransplantation.

Cell transplantation has been proposed as a promising therapeutic strategy for curing the diseases requiring tissue repairing and functional restoration. A preclinical method to systematically evaluate the fates of donor cells in recipients, spatially and temporally, is demanded for judging therapeutic potentials for the particularly designed cell transplantation. Yet, the dynamic cell tracking methodology for tracing transplanted cells in vivo is still at its early phase. Here, we created a practical protocol for dynamically tracking cell via a three-dimensional (3D) technique which enabled us to localize, quantify, and overall evaluate the transplanted hepatocytes within a liver failure mouse model. First, the capacity of 3D bioluminescence imaging for quantifying transplanted hepatocytes was defined. Images obtained from the 3D bioluminescence imaging module were then combined with the CT scanner to reconstruct structure images of host mice. With those reconstructed images, precise locations of transplanted hepatocytes in the liver of the recipient were dynamically monitored. Immunohistochemistry staining of transplanted cells, and the serology assay of liver panel of the host mice were applied to verify the successful engraftment of donor cells in the host livers. Our protocol was practical for evaluating the engraftment efficiency of donor cells at their preclinical phases, which is also applicable as a referable standard for studying the fates of other transplanted cells, such as stem cell-derived cell types, during preclinical studies with cell transplantation therapy.