Right Ventricular Function at Cardiac MRI Predicts Cardiovascular Events in Patients with an Implantable Cardioverter-Defibrillator.

Background Right ventricular ejection fraction (RVEF) is an independent predictor of death and adverse cardiovascular outcomes in patients with various cardiac conditions. Purpose To investigate whether RVEF, measured with cardiac MRI, is a predictor of appropriate shock or death in implantable cardioverter-defibrillator (ICD) recipients for primary and secondary prevention of sudden cardiac death. Materials and Methods This retrospective, multicenter, observational study included patients who underwent cardiac MRI before ICD implantation between January 2007 and May 2017. Right ventricular end-diastolic and end-systolic volumes and RVEF were measured with cardiac MRI. The primary end point was a composite of all-cause mortality or appropriate ICD shock. The secondary end point was all-cause mortality. The association between RVEF and primary and secondary outcomes was evaluated by using multivariable Cox regression analysis. Potential interactions were tested between primary prevention, ischemic cause, left ventricular ejection fraction (LVEF), and RVEF. Results Among 411 patients (mean age ± standard deviation, 60 years; 315 men) during a median follow-up of 63 months, 143 (35%) patients experienced an appropriate ICD shock or died. In univariable analysis, lower RVEF was associated with greater risks for appropriate ICD shock or death and for death alone (log-rank trend test, P = .003 and .005 respectively). In multivariable Cox regression analysis adjusting for age at ICD implantation, LVEF, ICD indication (primary vs secondary), ischemic heart disease, and late gadolinium enhancement, RVEF was an independent predictor of the primary outcome (hazard ratio [HR], 1.21 per 10% lower RVEF; 95% CI: 1.04, 1.41; P = .01) and all-cause mortality (HR, 1.25 per 10% lower RVEF; 95% CI: 1.01, 1.55; P = .04). No evidence of significant interactions was found between RVEF and primary or secondary prevention (P = .49), ischemic heart disease (P = .78), and LVEF (P = .29). Conclusion Right ventricular ejection fraction measured with cardiac MRI was a predictor of appropriate implantable cardioverter-defibrillator shock or death. © RSNA, 2021 See also the editorial by Nazarian and Zghaib in this issue. An earlier incorrect version of this article appeared online. This article was corrected on August 24, 2021.

Canadian Society of Thoracic Radiology/Canadian Association of Radiologists Clinical Practice Guidance for Non-Vascular Thoracic MRI.

Historically thoracic MRI has been limited by the lower proton density of lung parenchyma, cardiac and respiratory motion artifacts and long acquisition times. Recent technological advancements in MR hardware systems and improvement in MR pulse sequences have helped overcome these limitations and expand clinical opportunities for non-vascular thoracic MRI. Non-vascular thoracic MRI has been established as a problem-solving imaging modality for characterization of thymic, mediastinal, pleural chest wall and superior sulcus tumors and for detection of endometriosis. It is increasingly recognized as a powerful imaging tool for detection and characterization of lung nodules and for assessment of lung cancer staging. The lack of ionizing radiation makes thoracic MRI an invaluable imaging modality for young patients, pregnancy and for frequent serial follow-up imaging. Lack of familiarity and exposure to non-vascular thoracic MRI and lack of consistency in existing MRI protocols have called for clinical practice guidance. The purpose of this guide, which was developed by the Canadian Society of Thoracic Radiology and endorsed by the Canadian Association of Radiologists, is to familiarize radiologists, other interested clinicians and MR technologists with common and less common clinical indications for non-vascular thoracic MRI, discuss the fundamental imaging findings and focus on basic and more advanced MRI sequences tailored to specific clinical questions.

COVID-CAPS: A capsule network-based framework for identification of COVID-19 cases from X-ray images.

Novel Coronavirus disease (COVID-19) has abruptly and undoubtedly changed the world as we know it at the end of the 2nd decade of the 21st century. COVID-19 is extremely contagious and quickly spreading globally making its early diagnosis of paramount importance. Early diagnosis of COVID-19 enables health care professionals and government authorities to break the chain of transition and flatten the epidemic curve. The common type of COVID-19 diagnosis test, however, requires specific equipment and has relatively low sensitivity. Computed tomography (CT) scans and X-ray images, on the other hand, reveal specific manifestations associated with this disease. Overlap with other lung infections makes human-centered diagnosis of COVID-19 challenging. Consequently, there has been an urgent surge of interest to develop Deep Neural Network (DNN)-based diagnosis solutions, mainly based on Convolutional Neural Networks (CNNs), to facilitate identification of positive COVID-19 cases. CNNs, however, are prone to lose spatial information between image instances and require large datasets. The paper presents an alternative modeling framework based on Capsule Networks, referred to as the COVID-CAPS, being capable of handling small datasets, which is of significant importance due to sudden and rapid emergence of COVID-19. Our results based on a dataset of X-ray images show that COVID-CAPS has advantage over previous CNN-based models. COVID-CAPS achieved an Accuracy of 95.7%, Sensitivity of 90%, Specificity of 95.8%, and Area Under the Curve (AUC) of 0.97, while having far less number of trainable parameters in comparison to its counterparts. To potentially and further improve diagnosis capabilities of the COVID-CAPS, pre-training and transfer learning are utilized based on a new dataset constructed from an external dataset of X-ray images. This is in contrary to existing works on COVID-19 detection where pre-training is performed based on natural images. Pre-training with a dataset of similar nature further improved accuracy to 98.3% and specificity to 98.6%.

Clinical Correlation of Early Atelectasis after Bilateral Internal Thoracic Artery Harvest for Coronary Artery Bypass Grafting.

BACKGROUND: Atelectasis is a significant complication after cardiac surgery. The current study was designed to assess the significance of atelectasis after bilateral internal thoracic artery (BITA) harvest. METHODS: The ICU admission chest x-ray of 565 patients undergoing BITA was reviewed. Linear regression modelling was used to assess the relationship between atelectasis and oxygenation as well as patient variables to length of ventilation and length of stay in the Intensive Care Unit (ICU). RESULTS: Eighty-nine patients (15.8%) had Grade 2/3 atelectasis which was significantly more common on the left as compared to the right (left 0.149 95% CI [0.119-0.178], right 0.027 95% CI [0.013-0.040], p<0.001). Grade 2/3 atelectasis on the right was associated with a significant drop in the pO2 (p=0.001) and the per cent O2-fractional O2 (PF) ratio (p=0.002). Factors associated with increased ventilation time included presence of Grade 2/3 atelectasis (p=0.001) and peripheral vascular disease (PVD) (p<0.001), both of which were predictors of prolonged ICU length of stay (p=0.002 and p<0.001 respectively). CONCLUSIONS: Early atelectasis is related to impaired oxygenation, prolonged ventilation and prolonged ICU stay. Future research should focus on strategies to minimise atelectasis and to determine if these changes translate into better patient outcomes.

Role of imaging in the diagnosis of diffuse and interstitial lung diseases.

PURPOSE OF REVIEW: This review aims to provide a literature update focused on the role of imaging in the diagnosis, prognosis and quantification of interstitial lung diseases (ILDs). Special emphasis is given in the management of atypical cases and in the multidisciplinary team approach in reaching the diagnosis of the various ILDs. RECENT FINDINGS: Accumulated knowledge on imaging has increased the accuracy of differential diagnosis in atypical cases, in overlap of findings and in secondary as opposed to idiopathic ILDs. There is increasing awareness about interstitial lung abnormalities in smokers' lungs from lung cancer screening and indirect evidence of linkage of fibrosis and smoking. Improvement in radiologic-pathologic correlation reveals less typical high-resolution computed tomography patterns to be predictive of pulmonary fibrosis. Major diagnostic criteria such as honeycombing may be hampered by the coexistence of emphysema. High-resolution computed tomography may predict clinical outcome and survival of patients in ILDs and is a decision maker in the multidisciplinary approach of diagnosis. SUMMARY: High-resolution computed tomography plays a crucial role in the diagnosis, prognosis, quantification and monitoring of ILDs. It provides a definite noninvasive diagnosis in typical findings and helps in reaching the most accurate diagnosis in a multidisciplinary discussion in equivocal cases.

COVID-19-Induced Acute Laryngitis: A Case Series.

OBJECTIVES: The objective of this study is to present a novel clinical manifestation of COVID-19 with characteristic endoscopic laryngeal findings. A group of patients who reported similar symptoms, displayed akin laryngoscopic features, and received appropriate treatment is analyzed. Endoscopic images are provided and the pattern of this entity is discussed. STUDY DESIGN: This single-center descriptive analysis of a case series was performed in the General Hospital of Volos (Greece), during a 6-month period (from April 2022 to September 2022). Twenty-three patients who suffered from COVID-19 and were simultaneously diagnosed with acute laryngitis were enrolled. METHODS: Demographic data, clinical and endoscopic findings, laboratory results, and treatment courses were recorded. Descriptive statistics were performed with the statistical package SPSS (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.). RESULTS: The majority of the patients were male and fully vaccinated, as defined by Greek legislation at the time. None of them was a smoker. All patients were infected with Severe Acute Respiratory Syndrome Coronavirus 2 for the first time and presented with acute odynophagia. The characteristic endoscopic finding was an erythematous larynx with white undetachable lesions mainly in the supraglottic area. Pooling of saliva in the pyriform fossae was an independent predicting factor for patients' hospitalization (P < 0.001). None of the patients required intubation or tracheostomy and all responded to the systemic treatment with corticosteroids and antibiotics. CONCLUSIONS: COVID-19-induced laryngitis should be considered in any patient with positive COVID-19 who complains of acute odynophagia. Fiberoptic laryngoscopy is necessary to confirm the diagnosis. In our series, timely initiation of treatment minimized the need to secure the airway and ensured a favorable prognosis.

A prospective, non-randomized, no placebo-controlled, phase Ib clinical trial to study the safety of the adipose derived stromal cells-stromal vascular fraction in idiopathic pulmonary fibrosis.

INTRODUCTION: Regenerative medicine and particular adult stem cells represent an alternative option with several fruitful therapeutic applications in patients suffering from chronic lung diseases including idiopathic pulmonary fibrosis (IPF). Nevertheless, lack of knowledge regarding the origin and the potential of mesenchymal stem cells (MSCs) to differentiate into fibroblasts has limited their use for the treatment of this dismal disease. PATIENTS AND METHODS: To this end, we conducted a phase Ib, non-randomized, clinical trial to study the safety of three endobronchial infusions of autologous adipose derived stromal cells (ADSCs)-stromal vascular fraction (SVF) (0.5 million cells per kgr of body weight per infusion) in patients with IPF (n=14) of mild to moderate disease severity (forced vital capacity -FVC>50% predicted value and diffusion lung capacity for carbon monoxide-DLCO>35% of predicted value). Our primary end-point was incidence of treatment emergent adverse events within 12 months. Alterations of functional, exercise capacity and quality of life parameters at serial time points (baseline, 6 and 12 months after first infusion) were exploratory secondary end-points. RESULTS: No cases of serious or clinically meaningful adverse events including short-term infusional toxicities as well as long-term ectopic tissue formation were recorded in all patients. Detailed safety monitoring through several time-points indicated that cell-treated patients did not deteriorate in both functional parameters and indicators of quality of life. CONCLUSIONS: The clinical trial met its primary objective demonstrating an acceptable safety profile of endobronchially administered autologous ADSCs-SVF. Our findings accelerate the rapidly expanded scientific knowledge and indicate a way towards future efficacy trials.

Increased incidence of autoimmune markers in patients with combined pulmonary fibrosis and emphysema.

BACKGROUND: Combined pulmonary fibrosis and emphysema (CPFE) is an umbrella term encompassing upper lobe emphysema and lower lobe pulmonary fibrosis with pathogenesis elusive. The aim of our study was to investigate the incidence of autoimmune markers in patients with CPFE. METHODS: In this multicenter study we retrospectively evaluated records from patients with CPFE (n=40) and IPF (n=60) without emphysema. Baseline demographic characteristics, high-resolution computed tomography (HRCT), spirometry, histopathological, treatment, serum immunologic and survival data were investigated. B cell presence was estimated with CD20 immunostaining in representative lung biopsy samples from CPFE patients and control subjects. RESULTS: A statistically significant increased number of CPFE patients with elevated serum ANA with or without positive p-ANCA titers compared to patients with IPF without emphysema was observed. Patients with CPFE and positive autoimmune markers exhibited improved survival compared to patients with a negative autoimmune profile. A massive infiltration of clusters of CD20+ B cells forming lymphoid follicles within the fibrotic lung in CPFE patients with positive serum immunologic profile compared to patients with negative profile, was noted and positively correlated with improved survival. CONCLUSIONS: A significant proportion of patients with CPFE may present with underlying auto-immune disorders that may reside insidiously and be associated with favorable prognosis. Early identification of these patients using a panel of auto-antibodies may lead to more targeted and effective therapeutic applications.

A Case of Idiopathic First Bite Syndrome, Possibly Linked to Type I Diabetes Mellitus.

We present a rare case of a 34-year-old male with poorly regulated type I diabetes and three-month history of excruciating pain in the right condylar process of the mandible, occurring only during the first bite of each meal. The patient had no history of surgery or trauma in the head and neck region. Clinical and imaging examination revealed no tumor or pathology deriving from the dentures, the temporomandibular joint (TMJ), or the salivary glands. Idiopathic first bite syndrome (FBS) was suspected and treated with pregabalin and glycemic control. This case highlights how a detailed pain history and clinical examination can lead to a rare diagnosis and indicates the potential involvement of diabetic neuropathy in idiopathic FBS, as well as the importance of glycemic regulation in treatment.

Mediastinal Hemangioma Masquerading as a Simple Cyst.

ABSTRACT: This report presents imaging from a mediastinal mass in a patient with colon cancer. At baseline and surveillance chest computed tomography examinations, it was characterized as a pericardial cyst. However, during chemotherapy, complications arose and this mass was further characterized with a chest MRI. It was then decided to be removed, and histopathology confirmed the diagnosis of a hemangioma.

Detection of solid and subsolid pulmonary nodules with lung MRI: performance of UTE, T1 gradient-echo, and single-shot T2 fast spin echo.

BACKGROUND: Although MRI is a radiation-free imaging modality, it has historically been limited in lung imaging due to inherent technical restrictions. The aim of this study is to explore the performance of lung MRI in detecting solid and subsolid pulmonary nodules using T1 gradient-echo (GRE) (VIBE, Volumetric interpolated breath-hold examination), ultrashort time echo (UTE) and T2 Fast Spin Echo (HASTE, Half fourier Single-shot Turbo spin-Echo). METHODS: Patients underwent a lung MRI in a 3 T scanner as part of a prospective research project. A baseline Chest CT was obtained as part of their standard of care. Nodules were identified and measured on the baseline CT and categorized according to their density (solid and subsolid) and size (> 4 mm/ ≤ 4 mm). Nodules seen on the baseline CT were classified as present or absent on the different MRI sequences by two thoracic radiologists independently. Interobserver agreement was determined using the simple Kappa coefficient. Paired differences were compared using nonparametric Mann-Whitney U tests. The McNemar test was used to evaluate paired differences in nodule detection between MRI sequences. RESULTS: Thirty-six patients were prospectively enrolled. One hundred forty-nine nodules (100 solid/49 subsolid) with mean size 10.8 mm (SD = 9.4) were included in the analysis. There was substantial interobserver agreement (k = 0.7, p = 0.05). Detection for all nodules, solid and subsolid nodules was respectively; UTE: 71.8%/71.0%/73.5%; VIBE: 61.6%/65%/55.1%; HASTE 72.4%/72.2%/72.7%. Detection rate was higher for nodules > 4 mm in all groups: UTE 90.2%/93.4%/85.4%, VIBE 78.4%/88.5%/63.4%, HASTE 89.4%/93.8%/83.8%. Detection of lesions ≤4 mm was low for all sequences. UTE and HASTE performed significantly better than VIBE for detection of all nodules and subsolid nodules (diff = 18.4 and 17.6%, p = < 0.01 and p = 0.03, respectively). There was no significant difference between UTE and HASTE. There were no significant differences amongst MRI sequences for solid nodules. CONCLUSIONS: Lung MRI shows adequate performance for the detection of solid and subsolid pulmonary nodules larger than 4 mm and can serve as a promising radiation-free alternative to CT.

Predictors of persistent symptoms after mRNA SARS-CoV-2 vaccine-related myocarditis (myovacc registry).

Aims: Epidemiological surveillance has raised safety concerns for mRNA SARS-CoV-2-vaccination-related myocarditis. We aimed to analyze epidemiological, clinical and imaging findings associated with clinical outcomes in these patients in an international multi-center registry (NCT05268458). Methods and results: Patients with clinical and CMR diagnosis of acute myocarditis within 30 days after mRNA SARS-CoV-2-vaccination were included from five centers in Canada and Germany between 05/21 and 01/22. Clinical follow-up on persistent symptoms was collected. We enrolled 59 patients (80% males, mean age 29 years) with CMR-derived mild myocarditis (hs-Troponin-T 552 [249-1,193] ng/L, CRP 28 [13-51] mg/L; LVEF 57 ± 7%, LGE 3 [2-5] segments). Most common symptoms at baseline were chest pain (92%) and dyspnea (37%). Follow-up data from 50 patients showed overall symptomatic burden improvement. However, 12/50 patients (24%, 75% females, mean age 37 years) reported persisting symptoms (median interval 228 days) of chest pain (n = 8/12, 67%), dyspnea (n = 7/12, 58%), with increasing occurrence of fatigue (n = 5/12, 42%) and palpitations (n = 2/12, 17%). These patients had initial lower CRP, lower cardiac involvement in CMR, and fewer ECG changes. Significant predictors of persisting symptoms were female sex and dyspnea at initial presentation. Initial severity of myocarditis was not associated with persisting complaints. Conclusion: A relevant proportion of patients with mRNA SARS-CoV-2-vaccination-related myocarditis report persisting complaints. While young males are usually affected, patients with persisting symptoms were predominantly females and older. The severity of the initial cardiac involvement not predicting these symptoms may suggest an extracardiac origin.

Robust framework for COVID-19 identication from a multicenter dataset of chest CT scans.

The main objective of this study is to develop a robust deep learning-based framework to distinguish COVID-19, Community-Acquired Pneumonia (CAP), and Normal cases based on volumetric chest CT scans, which are acquired in different imaging centers using different scanners and technical settings. We demonstrated that while our proposed model is trained on a relatively small dataset acquired from only one imaging center using a specific scanning protocol, it performs well on heterogeneous test sets obtained by multiple scanners using different technical parameters. We also showed that the model can be updated via an unsupervised approach to cope with the data shift between the train and test sets and enhance the robustness of the model upon receiving a new external dataset from a different center. More specifically, we extracted the subset of the test images for which the model generated a confident prediction and used the extracted subset along with the training set to retrain and update the benchmark model (the model trained on the initial train set). Finally, we adopted an ensemble architecture to aggregate the predictions from multiple versions of the model. For initial training and development purposes, an in-house dataset of 171 COVID-19, 60 CAP, and 76 Normal cases was used, which contained volumetric CT scans acquired from one imaging center using a single scanning protocol and standard radiation dose. To evaluate the model, we collected four different test sets retrospectively to investigate the effects of the shifts in the data characteristics on the model's performance. Among the test cases, there were CT scans with similar characteristics as the train set as well as noisy low-dose and ultra-low-dose CT scans. In addition, some test CT scans were obtained from patients with a history of cardiovascular diseases or surgeries. This dataset is referred to as the "SPGC-COVID" dataset. The entire test dataset used in this study contains 51 COVID-19, 28 CAP, and 51 Normal cases. Experimental results indicate that our proposed framework performs well on all test sets achieving total accuracy of 96.15% (95%CI: [91.25-98.74]), COVID-19 sensitivity of 96.08% (95%CI: [86.54-99.5]), CAP sensitivity of 92.86% (95%CI: [76.50-99.19]), Normal sensitivity of 98.04% (95%CI: [89.55-99.95]) while the confidence intervals are obtained using the significance level of 0.05. The obtained AUC values (One class vs Others) are 0.993 (95%CI: [0.977-1]), 0.989 (95%CI: [0.962-1]), and 0.990 (95%CI: [0.971-1]) for COVID-19, CAP, and Normal classes, respectively. The experimental results also demonstrate the capability of the proposed unsupervised enhancement approach in improving the performance and robustness of the model when being evaluated on varied external test sets.

Host Expression Profiling From Diagnostic Coronavirus Disease 2019 Swabs Associates Upper Respiratory Tract Immune Responses With Radiologic Lung Pathology and Clinical Severity.

Background: COVID-19 presents with a breadth of symptomatology including a spectrum of clinical severity requiring intensive care unit (ICU) admission. We investigated the mucosal host gene response at the time of gold standard COVID-19 diagnosis using clinical surplus RNA from upper respiratory tract swabs. Methods: Host response was evaluated by RNA-sequencing, and transcriptomic profiles of 44 unvaccinated patients including outpatients and in-patients with varying levels of oxygen supplementation were included. Additionally, chest X-rays were reviewed and scored for patients in each group. Results: Host transcriptomics revealed significant changes in the immune and inflammatory response. Patients destined for the ICU were distinguished by the significant upregulation of immune response pathways and inflammatory chemokines, including cxcl2 which has been linked to monocyte subsets associated with COVID-19 related lung damage. In order to temporally associate gene expression profiles in the upper respiratory tract at diagnosis of COVID-19 with lower respiratory tract sequalae, we correlated our findings with chest radiography scoring, showing nasopharygeal or mid-turbinate sampling can be a relevant surrogate for downstream COVID-19 pneumonia/ICU severity. Conclusions: This study demonstrates the potential and relevance for ongoing study of the mucosal site of infection of SARS-CoV-2 using a single sampling that remains standard of care in hospital settings. We highlight also the archival value of high quality clinical surplus specimens, especially with rapidly evolving COVID-19 variants and changing public health/vaccination measures.

Basal ganglia hyperintensity on T1-weighted MRI in Rendu-Osler-Weber disease.

The purpose of this study was to evaluate possible central nervous system (CNS) involvement in Rendu-Osler-Weber (ROW) disease in magnetic resonance imaging (MRI). Three patients with symptomatic ROW disease underwent brain MRI. Brain MRI depicted in all three of them increased signal intensity on T1-weighted images involving the globus pallidus and cerebral crura bilaterally. Laboratory studies of the two men showed iron deficiency anemia, while all three of them had normal liver function tests and increased manganese blood concentration. Gastroscopy and colonoscopy revealed a gastric and a cecal arteriovenous malformation (AVM) in the first one, while pulmonary and hepatic computed tomography (CT) angiography did not detect any intrahepatic shunts. Liver ultrasound in the second one revealed dilatation of intrahepatic artery branches consistent with intrahepatic shunts, while it was normal in the third patient. Chest radiographs were normal in all three patients. Pallidal T1 hyperintensity on T1-weighted imaging may be a biomarker of manganese overload in ROW disease.

TAVR in a Patient With Anomalous Origin and Course of the Left Main Coronary Artery.

In patients with anomalous coronary arteries with high-risk features, corrective cardiac surgery should be considered. We report the first case of transcatheter aortic valve replacement using a self-expanding Evolut valve, in a patient with a single coronary artery arising from the right coronary cusp and an intramural course of the left main. (Level of Difficulty: Intermediate.).

CT patterns and serial CT Changes in lung Cancer patients post stereotactic body radiotherapy (SBRT).

BACKGROUND: To evaluate computed tomography (CT) patterns of post-SBRT lung injury in lung cancer and identify time points of serial CT changes. MATERIALS AND METHODS: One hundred eighty-three tumors in 170 patients were evaluated on sequential CTs within 29 months (median). Frequencies of post-SBRT CT patterns and time points of initiation and duration were assessed. Duration of increase of primary lesion or surrounding injury without evidence of local recurrence and time to stabilization or local recurrence were evaluated. RESULTS: Post-SBRT CT patterns could overlap in the same patient and were nodule-like pattern (69%), consolidation with ground glass opacity (GGO) (41%), modified conventional pattern (39%), peribronchial/patchy consolidation (42%), patchy GGO (24%), diffuse consolidation (16%), "orbit sign" (21%), mass-like pattern (19%), scar-like pattern (15%) and diffuse GGO (3%). Patchy GGO started at 4 months post-SBRT. Peribronchial/patchy consolidation and consolidation with GGO started at 4 and 5 months respectively. Diffuse consolidation, diffuse GGO and orbit sign started at 5, 6 and 8 months respectively. Mass-like, modified conventional and scar-like pattern started at 8, 12 and 12 months respectively. Primary lesion (n = 11) or surrounding injury (n = 85) increased up to 13 months. Primary lesion (n = 119) or surrounding injury (n = 115) started to decrease at 4 and 9 months respectively. Time to stabilization was 20 months. The most common CT pattern at stabilization was modified conventional pattern (49%), scar-like pattern (23%) and mass-like pattern (12%). Local recurrence (n = 15) occurred at a median time of 18 months. CONCLUSION: Different CT patterns of lung injury post-SBRT appear in predictable time points and have variable but predictable duration. Familiarity with these patterns and timeframes of appearance helps differentiate them from local recurrence.

COVID-rate: an automated framework for segmentation of COVID-19 lesions from chest CT images.

Novel Coronavirus disease (COVID-19) is a highly contagious respiratory infection that has had devastating effects on the world. Recently, new COVID-19 variants are emerging making the situation more challenging and threatening. Evaluation and quantification of COVID-19 lung abnormalities based on chest Computed Tomography (CT) images can help determining the disease stage, efficiently allocating limited healthcare resources, and making informed treatment decisions. During pandemic era, however, visual assessment and quantification of COVID-19 lung lesions by expert radiologists become expensive and prone to error, which raises an urgent quest to develop practical autonomous solutions. In this context, first, the paper introduces an open-access COVID-19 CT segmentation dataset containing 433 CT images from 82 patients that have been annotated by an expert radiologist. Second, a Deep Neural Network (DNN)-based framework is proposed, referred to as the [Formula: see text], that autonomously segments lung abnormalities associated with COVID-19 from chest CT images. Performance of the proposed [Formula: see text] framework is evaluated through several experiments based on the introduced and external datasets. Third, an unsupervised enhancement approach is introduced that can reduce the gap between the training set and test set and improve the model generalization. The enhanced results show a dice score of 0.8069 and specificity and sensitivity of 0.9969 and 0.8354, respectively. Furthermore, the results indicate that the [Formula: see text] model can efficiently segment COVID-19 lesions in both 2D CT images and whole lung volumes. Results on the external dataset illustrate generalization capabilities of the [Formula: see text] model to CT images obtained from a different scanner.