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OBJECTIVES: To compare clinical image quality and perceived impact on diagnostic interpretation of chest CT findings between ultra-high-resolution photon-counting CT (UHR-PCCT) and conventional high-resolution energy-integrating-detector CT (HR-EIDCT) using visual grading analysis (VGA) scores. MATERIALS AND METHODS: Fifty patients who underwent a UHR-PCCT (matrix 512 × 512, 768 × 768, or 1024 × 1024; FOV average 275 × 376 mm, 120 × 0.2 mm; focal spot size 0.6 × 0.7 mm) between November 2021 and February 2022 and with a previous HR-EIDCT within the last 14 months were included. Four readers evaluated central and peripheral airways, lung vasculature, nodules, ground glass opacities, inter- and intralobular lines, emphysema, fissures, bullae/cysts, and air trapping on PCCT (0.4 mm) and conventional EIDCT (1 mm) via side-by-side reference scoring using a 5-point diagnostic quality score. The median VGA scores were compared and tested using one-sample Wilcoxon signed rank tests with hypothesized median values of 0 (same visibility) and 2 (better visibility on PCCT with impact on diagnostic interpretation) at a 2.5% significance level. RESULTS: Almost all lung structures had significantly better visibility on PCCT compared to EIDCT (p < 0.025; exception for ground glass nodules (N = 2/50 patients, p = 0.157)), with the highest scores seen for peripheral airways, micronodules, inter- and intralobular lines, and centrilobular emphysema (mean VGA > 1). Although better visibility, a perceived difference in diagnostic interpretation could not be demonstrated, since the median VGA was significantly different from 2. CONCLUSION: UHR-PCCT showed superior visibility compared to HR-EIDCT for central and peripheral airways, lung vasculature, fissures, ground glass opacities, macro- and micronodules, inter- and intralobular lines, paraseptal and centrilobular emphysema, bullae/cysts, and air trapping. CLINICAL RELEVANCE STATEMENT: UHR-PCCT has emerged as a promising technique for thoracic imaging, offering improved spatial resolution and lower radiation dose. Implementing PCCT into daily practice may allow better visibility of multiple lung structures and optimization of scan protocols for specific pathology. KEY POINTS: ⢠The aim of this study was to verify if the higher spatial resolution of UHR-PCCT would improve the visibility and detection of certain lung structures and abnormalities. ⢠UHR-PCCT was judged to have superior clinical image quality compared to conventional HR-EIDCT in the evaluation of the lungs. UHR-PCCT showed better visibility for almost all tested lung structures (except for ground glass nodules). ⢠Despite superior image quality, the readers perceived no significant impact on the diagnostic interpretation of the studied lung structures and abnormalities.
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Cistos , Pneumopatias , Enfisema Pulmonar , Humanos , Enfisema Pulmonar/diagnóstico por imagem , Vesícula , Imagens de Fantasmas , Pulmão/diagnóstico por imagem , Tomografia Computadorizada por Raios X/métodos , FótonsRESUMO
BACKGROUND: Several immune mechanisms activate in COVID-19 pathogenesis. Usually, coronavirus infection is characterized by dysregulated host immune responses, interleukine-6 increase, hyper-activation of cytotoxic CD8 T lymphocytes. Interestingly, Vitamin D deficiency has been often associated with altered immune responses and infections. In the present study, we evaluated Vitamin D plasma levels in patients affected with different lung involvement during COVID-19 infection. METHODS: Lymphocyte phenotypes were assessed by flow cytometry. Thoracic CT scan involvement was obtained by an image analysis program. RESULTS: Vitamin D levels were deficient in (80%) of patients, insufficient in (6.5%) and normal in (13.5%). Patients with very low Vitamin D plasma levels had more elevated D-Dimer values, a more elevated B lymphocyte cell count, a reduction of CD8 + T lymphocytes with a low CD4/CD8 ratio, more compromised clinical findings (measured by LIPI and SOFA scores) and thoracic CT scan involvement. CONCLUSIONS: Vitamin D deficiency is associated with compromised inflammatory responses and higher pulmonary involvement in COVID-19 affected patients. Vitamin D assessment, during COVID-19 infection, could be a useful analysis for possible therapeutic interventions. TRIAL REGISTRATION: 'retrospectively registered'.
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COVID-19/sangue , COVID-19/epidemiologia , Deficiência de Vitamina D/sangue , Deficiência de Vitamina D/epidemiologia , Vitamina D/sangue , Adulto , Idoso , Idoso de 80 Anos ou mais , Linfócitos T CD8-Positivos/metabolismo , COVID-19/diagnóstico por imagem , Feminino , Humanos , Itália/epidemiologia , Pulmão/diagnóstico por imagem , Masculino , Pessoa de Meia-Idade , Prognóstico , Deficiência de Vitamina D/diagnóstico por imagemRESUMO
INTRODUCTION: COVID-19 pneumonia is characterized by ground-glass opacities (GGOs) and consolidations on Chest CT, although these CT features cannot be considered specific, at least on a qualitative analysis. The aim is to evaluate if Quantitative Chest CT could provide reliable information in discriminating COVID-19 from non-COVID-19 patients. MATERIALS AND METHODS: From March 31, 2020 until April 18, 2020, patients with Chest CT suggestive for interstitial pneumonia were retrospectively enrolled and divided into two groups based on positive/negative COVID-19 RT-PCR results. Patients with pulmonary resection and/or CT motion artifacts were excluded. Quantitative Chest CT analysis was performed with a dedicated software that provides total lung volume, healthy parenchyma, GGOs, consolidations and fibrotic alterations, expressed both in liters and percentage. Two radiologists in consensus revised software analysis and adjusted areas of lung impairment in case of non-adequate segmentation. Data obtained were compared between COVID-19 and non-COVID-19 patients and p < 0.05 were considered statistically significant. Performance of statistically significant parameters was tested by ROC curve analysis. RESULTS: Final population enrolled included 190 patients: 136 COVID-19 patients (87 male, 49 female, mean age 66 ± 16) and 54 non-COVID-19 patients (25 male, 29 female, mean age 63 ± 15). Lung quantification in liters showed significant differences between COVID-19 and non-COVID-19 patients for GGOs (0.55 ± 0.26L vs 0.43 ± 0.23L, p = 0.0005) and fibrotic alterations (0.05 ± 0.03 L vs 0.04 ± 0.03 L, p < 0.0001). ROC analysis of GGOs and fibrotic alterations showed an area under the curve of 0.661 (cutoff 0.39 L, 68% sensitivity and 59% specificity, p < 0.001) and 0.698 (cutoff 0.02 L, 86% sensitivity and 44% specificity, p < 0.001), respectively. CONCLUSIONS: Quantification of GGOs and fibrotic alterations on Chest CT could be able to identify patients with COVID-19.
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COVID-19/diagnóstico por imagem , Doenças Pulmonares Intersticiais/diagnóstico por imagem , Pulmão/diagnóstico por imagem , Fibrose Pulmonar/diagnóstico por imagem , SARS-CoV-2 , Adulto , Idoso , Idoso de 80 Anos ou mais , COVID-19/sangue , COVID-19/complicações , Teste de Ácido Nucleico para COVID-19 , Tosse/etiologia , Diagnóstico Diferencial , Dispneia/etiologia , Feminino , Febre/etiologia , Humanos , Doenças Pulmonares Intersticiais/sangue , Doenças Pulmonares Intersticiais/complicações , Masculino , Pessoa de Meia-Idade , Probabilidade , Curva ROC , Radiografia Torácica/métodos , Estudos Retrospectivos , Software , Tomografia Computadorizada por Raios X/métodos , Adulto JovemRESUMO
Kidney transplant is the treatment of choice for end-stage chronic kidney disease. Kidneys generate 1,25-dihydroxyvitamin D (calcitriol) from 25-hydroxyvitamin D (calcidiol) for circulation in the blood to regulate calcium levels. Transplant patients with low calcidiol levels have an increased risk of metabolic and endocrine problems, cardiovascular disease, type 2 diabetes mellitus, poor graft survival, bone disorders, cancer, and mortality rate. The recommended calcidiol level after transplant is at least 30 ng/mL (75 nmol/L), which could require 1000-3000 IU/d vitamin D3 to achieve. Vitamin D3 supplementation studies have found improved endothelial function and acute rejection episodes. However, since kidney function may still be impaired, raising calcidiol levels may not lead to normal calcitriol levels. Thus, supplementation with calcitriol or an analog, alfacalcidiol, is often employed. Some beneficial effects found include possible improved bone health and reduced risk of chronic allograft nephropathy and cancer.
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Falência Renal Crônica/terapia , Transplante de Rim/efeitos adversos , Deficiência de Vitamina D/etiologia , Calcitriol/metabolismo , Suplementos Nutricionais , Humanos , Rim/metabolismo , Falência Renal Crônica/sangue , Falência Renal Crônica/metabolismo , Vitamina D/administração & dosagem , Vitamina D/análogos & derivados , Vitamina D/metabolismo , Deficiência de Vitamina D/metabolismo , Deficiência de Vitamina D/prevenção & controleRESUMO
Pulmonary embolism (PE) is a pathological entity characterised by venous thromboembolism in the pulmonary arteries. It is a common entity in daily clinical practice and is the third most common cause of cardiovascular death. Correct diagnostic work-up is pivotal to ensure timely institution of appropriate therapy. This requires recognition of the characteristic imaging findings and awareness of the role and peculiarities of the different imaging techniques involved in the diagnostic and therapeutic process. This review aims to showcase the most commonly encountered imaging findings associated with pulmonary thromboembolism for each imaging modality, outline their advantages and disadvantages, and define the specific role of these techniques in the clinical setting. The latest innovations concerning the diagnostic work-up of PE will be also briefly discussed, yielding a perspective on the future developments and challenges that the radiologist will have to face in the coming years.
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Artificial intelligence (AI) is having a significant impact in medical imaging, advancing almost every aspect of the field, from image acquisition and postprocessing to automated image analysis with outreach toward supporting decision making. Noninvasive cardiac imaging is one of the main and most exciting fields for AI development. The aim of this review is to describe the main applications of AI in cardiac imaging, including CT and MR imaging, and provide an overview of recent advancements and available clinical applications that can improve clinical workflow, disease detection, and prognostication in cardiac disease.
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Inteligência Artificial , Cardiopatias , Humanos , Cardiopatias/diagnóstico por imagem , Imageamento por Ressonância Magnética , Processamento de Imagem Assistida por ComputadorRESUMO
In this study, we present a method based on Monte Carlo Dropout (MCD) as Bayesian neural network (BNN) approximation for confidence-aware severity classification of lung diseases in COVID-19 patients using chest X-rays (CXRs). Trained and tested on 1208 CXRs from Hospital 1 in the USA, the model categorizes severity into four levels (i.e., normal, mild, moderate, and severe) based on lung consolidation and opacity. Severity labels, determined by the median consensus of five radiologists, serve as the reference standard. The model's performance is internally validated against evaluations from an additional radiologist and two residents that were excluded from the median. The performance of the model is further evaluated on additional internal and external datasets comprising 2200 CXRs from the same hospital and 1300 CXRs from Hospital 2 in South Korea. The model achieves an average area under the curve (AUC) of 0.94 ± 0.01 across all classes in the primary dataset, surpassing human readers in each severity class and achieves a higher Kendall correlation coefficient (KCC) of 0.80 ± 0.03. The performance of the model is consistent across varied datasets, highlighting its generalization. A key aspect of the model is its predictive uncertainty (PU), which is inversely related to the level of agreement among radiologists, particularly in mild and moderate cases. The study concludes that the model outperforms human readers in severity assessment and maintains consistent accuracy across diverse datasets. Its ability to provide confidence measures in predictions is pivotal for potential clinical use, underscoring the BNN's role in enhancing diagnostic precision in lung disease analysis through CXR.
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PURPOSE: We sought to clinically validate a fully automated deep learning (DL) algorithm for coronary artery disease (CAD) detection and classification in a heterogeneous multivendor cardiac computed tomography angiography data set. MATERIALS AND METHODS: In this single-centre retrospective study, we included patients who underwent cardiac computed tomography angiography scans between 2010 and 2020 with scanners from 4 vendors (Siemens Healthineers, Philips, General Electrics, and Canon). Coronary Artery Disease-Reporting and Data System (CAD-RADS) classification was performed by a DL algorithm and by an expert reader (reader 1, R1), the gold standard. Variability analysis was performed with a second reader (reader 2, R2) and the radiologic reports on a subset of cases. Statistical analysis was performed stratifying patients according to the presence of CAD (CAD-RADS >0) and obstructive CAD (CAD-RADS ≥3). RESULTS: Two hundred ninety-six patients (average age: 53.66 ± 13.65, 169 males) were enrolled. For the detection of CAD only, the DL algorithm showed sensitivity, specificity, accuracy, and area under the curve of 95.3%, 79.7%, 87.5%, and 87.5%, respectively. For the detection of obstructive CAD, the DL algorithm showed sensitivity, specificity, accuracy, and area under the curve of 89.4%, 92.8%, 92.2%, and 91.1%, respectively. The variability analysis for the detection of obstructive CAD showed an accuracy of 92.5% comparing the DL algorithm with R1, and 96.2% comparing R1 with R2 and radiology reports. The time of analysis was lower using the DL algorithm compared with R1 (P < 0.001). CONCLUSIONS: The DL algorithm demonstrated robust performance and excellent agreement with the expert readers' analysis for the evaluation of CAD, which also corresponded with significantly reduced image analysis time.
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Positron emission tomography/computed tomography (PET/CT) with 18F-fluorodeoxyglucose (18F-FDG) has become the method of choice for tumor staging in lung cancer patients with improved diagnostic accuracy for the evaluation of lymph node involvement and distant metastasis. Due to its spectral capabilities, dual-energy CT (DECT) employs a material decomposition algorithm enabling precise quantification of iodine concentrations in distinct tissues. This technique enhances the characterization of tumor blood supply and has demonstrated promising results for the assessment of therapy response in patients with lung cancer. Several studies have demonstrated that DECT provides additional value to the PET-based evaluation of glycolytic activity, especially for the evaluation of therapy response and follow-up of patients with lung cancer. The combination of PET and DECT in a single scanner system enables the simultaneous assessment of glycolytic activity and iodine enhancement, offering further insight to the characterization of tumorous tissues. Recently a new approach of a novel integrated PET/DECT was investigated in a pilot study on patients with non-small cell lung cancer (NSCLC). The study showed a moderate correlation between PET-based standard uptake values (SUV) and DECT-based iodine densities in the evaluation of lung tumorous tissue but with limited assessment of lymph nodes. The following review on tumorous tissue characterization using PET and DECT imaging describes the strengths and limitations of this novel technique.
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Carcinoma Pulmonar de Células não Pequenas , Iodo , Neoplasias Pulmonares , Carcinoma Pulmonar de Células não Pequenas/diagnóstico por imagem , Carcinoma Pulmonar de Células não Pequenas/patologia , Fluordesoxiglucose F18 , Humanos , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/patologia , Estadiamento de Neoplasias , Projetos Piloto , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada/métodos , Tomografia por Emissão de Pósitrons/métodos , Compostos Radiofarmacêuticos , Tomografia Computadorizada por Raios X/métodosRESUMO
The aim of the study is to verify the feasibility of a radiomics based approach for the detection of LV remodeling in patients with arterial hypertension. Cardiac Computed Tomography (CCT) and clinical data of patients with and without history of arterial hypertension were collected. In one image per patient, on a 4-chamber view, left ventricle (LV) was segmented using a polygonal region of interest by two radiologists in consensus. A total of 377 radiomics features per region of interest were extracted. After dataset splitting (70:30 ratio), eleven classification models were tested for the discrimination of patients with and without arterial hypertension based on radiomics data. An Ensemble Machine Learning (EML) score was calculated from models with an accuracy >60%. Boruta algorithm was used to extract radiomic features discriminating between patients with and without history of hypertension. Pearson correlation coefficient was used to assess correlation between EML score and septum width in patients included in the test set. EML showed an accuracy, sensitivity and specificity of 0.7. Correlation between EML score and LV septum width was 0.53 (p-value < 0.0001). We considered LV septum width as a surrogate of myocardial remodeling in our population, and this is the reason why we can consider the EML score as a possible tool to evaluate myocardial remodeling. A CCT-based radiomic approach for the identification of LV remodeling is possible in patients with past medical history of arterial hypertension.
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Pulmonary anomalous venous return (PAPVR) is defined as a congenital anomaly in which at least one but not all of the pulmonary veins abnormally drain into a systemic vein or directly into the right atrium. Signs and symptoms related to this condition are due to the hemodynamic abnormalities secondary to left-to-right shunt and the possible presence of other associated cardiac anomalies (e.g., sinus venous atrial septal defect). Therefore, depending on the extent of the shunt, the clinical presentation of PAPVR is variable, ranging from asymptomatic patients to patients affected by severe heart failure with right-sided volume overload. PAPVR with a clinically significant shunt should be referred for surgical correction with different techniques depending on the presence of associated cardiac anomalies. We are presenting a case of partial anomalous venous return (PAPVR) in a 66-year-old man who underwent surgery 26 years ago to correct an anomalous venous connection between the right superior pulmonary vein (RSPV) and the superior vena cava (SVC) through a veno-atrial baffle. The patient was admitted to the emergency department due to atrial tachycardia. Trans-thoracic echocardiography (TTE) showed a dilated right ventricle (RV) with mild RV systolic dysfunction and pulmonary hypertension. Cardiac magnetic resonance (CMR) further confirmed the findings described by TTE and also demonstrated areas of fibrosis replacement in the hinge points. Cardiac computed tomography (CCT) was able to accurately depict and evaluate the surgically created veno-atrial baffle and also showed an anomalous connection between the left superior pulmonary vein (LSPV) and the brachiocephalic vein (BCV) through a vertical vein. The patient was successfully treated with radiofrequency ablation for his arrhythmia.
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The Coronavirus disease 2019 (COVID-19) is caused by the human severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus. The most common clinical findings related to COVID-19 are fever and cough, with the proportion of patients developing interstitial pneumonia. Other symptoms include dyspnea, expectoration, headache, anosmia, ageusia, myalgia and malaise. To date, the diagnostic criteria for COVID-19 include nasopharyngeal and oropharyngeal swabs. Computed tomography (CT) scans of the thorax showing signs of interstitial pneumonia are important in the management of respiratory disease and in the evaluation of lung involvement. In the literature, there are few cases of COVID-19 pneumonia diagnosis made using magnetic resonance imaging (MRI). In our report, we describe a case of accidental detection of findings related to interstitial pneumonia in a patient who underwent abdominal MRI for other clinical reasons. A 71-year-old woman was referred to our department for an MRI scan of the abdomen as her oncological follow-up. She was asymptomatic at the time of the examination and had passed the triage carried out on all the patients prior to diagnostic tests during the COVID-19 pandemic. The images acquired in the upper abdomen showed the presence of areas of altered signal intensity involving asymmetrically both pulmonary lower lobes, with a patchy appearance and a preferential peripheral subpleural distribution. We considered these features as highly suspicious for COVID-19 pneumonia. The nasopharyngeal swab later confirmed the diagnosis of SARS-CoV-2 infection. There are limited reports about MRI features of COVID-19 pneumonia, considering that high-resolution chest CT is the imaging technique of choice to diagnose pneumonia. Nevertheless, this clinical case confirmed that it is possible to detect MRI signs suggestive of COVID-19 pneumonia. The imaging features described could help in the evaluation of the lung parenchyma to assess the presence of signs suggestive of COVID-19 pneumonia, especially in asymptomatic patients during the pandemic phase of the disease.
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BACKGROUND: To present a case of anomalous origin of the left coronary artery evaluated with invasive coronary angiography (ICA) and ECG-gated coronary computed tomography (CCT). CASE PRESENTATION: A patient (55 years old, male) with a past medical history of respiratory failure and atrial fibrillation underwent ICA to rule out coronary artery disease. Subsequently, the patient underwent ECG-gated CCT to evaluate a suspected anomalous aortic origin of the left coronary artery, since the interventional cardiologist was not able to properly identify the left coronary artery and its distal branches. CCT showed left coronary artery originating from the right coronary Valsalva sinus, coursing within the interventricular septum and emerging at the middle segment of the interventricular sulcus, where the left anterior descending and circumflex arteries originated. CONCLUSION: The case we presented highlights the value of ECG-gated CCT in the evaluation of coronary anomaly anatomy and thus risk stratification derived by proper coronary anatomy assessment. Although ICA was not helpful in the diagnosis, it also has a pivotal role regarding the therapeutic management of this condition.