Background: Chest CT scan has an important role in the diagnosis and management of COVID-19 infection. A major concern in radiologic assessment of the patients is the radiation dose. Research has been done to evaluate low-dose chest CT in the diagnosis of pulmonary lesions with promising findings. We decided to determine diagnostic performance of ultra-low-dose chest CT in comparison to low-dose CT for viral pneumonia during the COVID-19 pandemic. Results: 167 patients underwent both low-dose and ultra-low-dose chest CT scans. Two radiologists blinded to the diagnosis independently examined ultra-low-dose chest CT scans for findings consistent with COVID-19 pneumonia. In case of any disagreement, a third senior radiologist made the final diagnosis. Agreement between two CT protocols regarding ground-glass opacity, consolidation, reticulation, and nodular infiltration were recorded. On low-dose chest CT, 44 patients had findings consistent with COVID-19 infection. Ultra-low-dose chest CT had sensitivity and specificity values of 100% and 98.4%, respectively for diagnosis of viral pneumonia. Two patients were falsely categorized to have pneumonia on ultra-low-dose CT scan. Positive predictive value and negative predictive value of ultra-low-dose CT scan were respectively 95.7% and 100%. There was good agreement between low-dose and ultra-low-dose methods (kappa = 0.97; P < 0.001). Perfect agreement between low-dose and ultra-low-dose scans was found regarding diagnosis of ground-glass opacity (kappa = 0.83, P < 0.001), consolidation (kappa = 0.88, P < 0.001), reticulation (kappa = 0.82, P < 0.001), and nodular infiltration (kappa = 0.87, P < 0.001). Conclusion: Ultra-low-dose chest CT scan is comparable to low-dose chest CT for detection of lung infiltration during the COVID-19 outbreak while maintaining less radiation dose. It can also be used instead of low-dose chest CT scan for patient triage in circumstances where rapid-abundant PCR tests are not available.

Background: Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent type of pancreas cancer with a high mortality rate and its staging is highly dependent on the extent of involvement between the tumor and surrounding vessels, facilitating treatment response assessment in PDAC. Objective: This study aims at detecting and visualizing the tumor region and the surrounding vessels in PDAC CT scan since, despite the tumors in other abdominal organs, clear detection of PDAC is highly difficult. Material and Methods: This retrospective study consists of three stages: 1) a patch-based algorithm for differentiation between tumor region and healthy tissue using multi-scale texture analysis along with L1-SVM (Support Vector Machine) classi-fier, 2) a voting-based approach, developed on a standard logistic function, to mitigate false detections, and 3) 3D visualization of the tumor and the surrounding vessels using ITK-SNAP software. Results: The results demonstrate that multi-scale texture analysis strikes a balance between recall and precision in tumor and healthy tissue differentiation with an overall accuracy of 0.78±0.12 and a sensitivity of 0.90±0.09 in PDAC. Conclusion: Multi-scale texture analysis using statistical and wavelet-based features along with L1-SVM can be employed to differentiate between healthy and pancreatic tissues. Besides, 3D visualization of the tumor region and surrounding vessels can facilitate the assessment of treatment response in PDAC. However, the 3D visualization software must be further developed for integrating with clinical applications.

Background: There is an increasing body of evidence indicating Y90 dose thresholds for tumor response and treatment-related toxicity. These thresholds are poorly studied in resin Y90, particularly in hepatocellular carcinoma (HCC). Purpose: To evaluate the efficacy of prospective voxel-based dosimetry for predicting treatment response and adverse events (AEs) in patients with HCC undergoing resin-based Y90 radioembolization. Materials and methods: This correlative study was based on a prospective single-arm clinical trial (NCT04172714), which evaluated the efficacy of low/scout (555 MBq) activity of resin-based Y90 for treatment planning. Partition model was used with goal of tumor dose (TD) > 200 Gy and non-tumoral liver dose (NTLD) < 70 Gy for non-segmental therapies. Single compartment dose of 200 Gy was used for segmentectomies. Prescribed Y90 activity minus scout activity was administered for therapeutic Y90 followed by Y90-PET/CT. Sureplan® (MIM Software, Cleveland, OH) was used for dosimetry analysis. Treatment response was evaluated at 3 and 6 months. Receiver operating characteristic curve determined TD response threshold for objective response (OR) and complete response (CR) as well as non-tumor liver dose (NTLD) threshold that predicted AEs. Results: N = 30 patients were treated with 33 tumors (19 segmental and 14 non-segmental). One patient died before the first imaging, and clinical follow-up was excluded from this analysis. Overall, 26 (81%) of the tumors had an OR and 23 (72%) had a CR. A mean TD of 253 Gy predicted an OR with 92% sensitivity and 83% specificity (area under the curve (AUC = 0.929, p < 0.001). A mean TD of 337 Gy predicted a CR with 83% sensitivity and 89% specificity (AUC = 0.845, p < 0.001). A mean NTLD of 81 and 87 Gy predicted grade 3 AEs with 100% sensitivity and 100% specificity in the non-segmental cohort at 3- and 6-month post Y90, respectively. Conclusion: In patients with HCC undergoing resin-based Y90, there are dose response and dose toxicity thresholds directly affecting outcomes. Clinical trial number: NCT04172714.

Acute bowel ischemia (ABI) can be life threatening with high mortality rate. In spite of the advances made in diagnosis and treatment of ABI, no significant change has occurred in the mortality over the past decade. ABI is potentially reversible with prompt diagnosis. The radiologist plays a central role in the initial diagnosis and preventing progression to irreversible intestinal ischemic injury or bowel necrosis. The most single imaging findings described in the literature are either non-specific or only present in the late stages of ABI, urging the use of a constellation of features to reach a more confident diagnosis. While ABI has been traditionally categorized based on the etiology with a wide spectrum of imaging findings overlapped with each other, the final decision for patient’s management is usually made on the stage of the ABI with respect to the underlying pathophysiology. In this review, we first discuss the pathologic stages of ischemia and then summarize the various imaging signs and causes of ABI. We also emphasize on the correlation of imaging findings and pathological staging of the disease. Finally, a management approach is proposed using combined clinical and radiological findings to determine whether the patient may benefit from surgery or not.

Diagnosis of intestinal vasculitis is often challenging due to the non-specific clinical and imaging findings. Vasculitides with gastrointestinal (GI) manifestations are rare, but their diagnosis holds immense significance as late or missed recognition can result in high mortality rates. Given the resemblance of radiologic findings with some other entities, GI vasculitis is often overlooked on small bowel studies done using computed tomography/magnetic resonance enterography (CTE/MRE). Hereon, we reviewed radiologic findings of vasculitis with gastrointestinal involvement on CTE and MRE. The variety of findings on MRE/CTE depend upon the size of the involved vessels. Signs of intestinal ischemia, e.g., mural thickening, submucosal edema, mural hyperenhancement, and restricted diffusion on diffusion-weighted imaging, are common in intestinal vasculitis. Involvement of the abdominal aorta and the major visceral arteries is presented as concentric mural thickening, transmural calcification, luminal stenosis, occlusion, aneurysmal changes, and collateral vessels. Such findings can be observed particularly in large- and medium-vessel vasculitis. The presence of extra-intestinal findings, including within the liver, kidneys, or spleen in the form of focal areas of infarction or heterogeneous enhancement due to microvascular involvement, can be another radiologic clue in diagnosis of vasculitis. The link between the clinical/laboratory findings and MRE/CTE abnormalities needs to be corresponded when it comes to the diagnosis of intestinal vasculitis.

Fully automated and volumetric segmentation of critical tumors may play a crucial role in diagnosis and surgical planning. One of the most challenging tumor segmentation tasks is localization of pancreatic ductal adenocarcinoma (PDAC). Exclusive application of conventional methods does not appear promising. Deep learning approaches has achieved great success in the computer aided diagnosis, especially in biomedical image segmentation. This paper introduces a framework based on convolutional neural network (CNN) for segmentation of PDAC mass and surrounding vessels in CT images by incorporating powerful classic features, as well. First, a 3D-CNN architecture is used to localize the pancreas region from the whole CT volume using 3D Local Binary Pattern (LBP) map of the original image. Segmentation of PDAC mass is subsequently performed using 2D attention U-Net and Texture Attention U-Net (TAU-Net). TAU-Net is introduced by fusion of dense Scale-Invariant Feature Transform (SIFT) and LBP descriptors into the attention U-Net. An ensemble model is then used to cumulate the advantages of both networks using a 3D-CNN. In addition, to reduce the effects of imbalanced data, a multi-objective loss function is proposed as a weighted combination of three classic losses including Generalized Dice Loss (GDL), Weighted Pixel-Wise Cross Entropy loss (WPCE) and boundary loss. Due to insufficient sample size for vessel segmentation, we used the above-mentioned pre-trained networks and fine-tuned them. Experimental results show that the proposed method improves the Dice score for PDAC mass segmentation in portal-venous phase by 7.52% compared to state-of-the-art methods in term of DSC. Besides, three dimensional visualization of the tumor and surrounding vessels can facilitate the evaluation of PDAC treatment response.

Background: Chest computed tomography (CT) scan is frequently used in the diagnosis of COVID-19 pneumonia. Objectives: This study investigates the predictive value of CT severity score (CSS) for length-of-stay (LOS) in hospital, initial disease severity, ICU admission, intubation, and mortality. Methods: In this retrospective study, initial CT scans of consecutively admitted patients with COVID-19 pneumonia were reviewed in a tertiary hospital. The association of CSS with the severity of disease upon admission and the final adverse outcomes was assessed using Pearson's correlation test and logistic regression, respectively. Results: Total of 121 patients (60±16 years), including 54 women and 67 men, with positive RT-PCR tests were enrolled. We found a significant but weak correlation between CSS and qSOFA, as a measure of disease severity (r: 0.261, p = 0.003). No significant association was demonstrated between CSS and LOS. Patients with CSS>8 had at least three-fold higher risk of ICU admission, intubation, and mortality. Conclusions: CSS in baseline CT scan of patients with COVID-19 pneumonia can predict adverse outcomes and is weakly correlated with initial disease severity.

Nonbacterial thrombotic endocarditis (NBTE) is a rare entity most commonly diagnosed postmortem with rates in autopsy series ranging from 0.9 to 1.6%. A 63-year-old female with past medical history of hypertension and mitral valve prolapse presented to the hospital with shortness of breath, headache, and necrotic skin lesions on her hands and feet. Computed tomography (CT) scan of her chest demonstrated a pulmonary embolus in the right lower lung segmental artery and right upper lobe lobar to segmental pulmonary artery, a mass-like consolidation in the left upper lung field impeding the hilum. CT scan of the abdomen demonstrated metastatic disease in liver and bone and bilateral femoral deep vein thrombosis. Transesophageal echocardiography revealed severe mitral regurgitation with two small mobile plaques on the mitral valve and two immobile plaques on the descending aorta. Magnetic resonance imaging of the brain was consistent with subacute infarcts and metastatic disease. Bronchoscopy was performed and pathology revealed primary adenocarcinoma of the lung. She was treated with anticoagulation and systemic chemotherapy. The patient and family elected to proceed with hospice due to her clinical decline, poor performance status, and poor prognosis after a prolonged hospital stay. Underlying malignancy is detected in approximately 40-85% of patients with NBTE. Lung cancer is the most frequently associated malignancy followed by pancreatic, stomach, breast, and ovarian cancer. Widespread necrotic skin lesions as presenting symptoms of primary lung adenocarcinoma are rare. In the present case, the diagnosis of necrotic skin lesions and NBTE preceded that of the neoplastic disease. Necrotic skin lesions and NBTE can be the first manifestations of an occult malignancy causing extensive multi-organ infarcts. NBTE can present with such extensive skin lesions as a first presenting sign of malignancy. To the best of our knowledge, this is the first case to present with such extensive skin lesions as the first presenting symptom of lung adenocarcinoma.

Background: Currently no effective antiviral therapy has been found to treat COVID-19. The aim of this trial was to assess if the addition of sofosbuvir and daclatasvir improved clinical outcomes in patients with moderate or severe COVID-19. Methods: This was an open-label, multicentre, randomized controlled clinical trial in adults with moderate or severe COVID-19 admitted to four university hospitals in Iran. Patients were randomized into a treatment arm receiving sofosbuvir and daclatasvir plus standard care, or a control arm receiving standard care alone. The primary endpoint was clinical recovery within 14 days of treatment. The study is registered with IRCT.ir under registration number IRCT20200128046294N2. Results: Between 26 March and 26 April 2020, 66 patients were recruited and allocated to either the treatment arm (n = 33) or the control arm (n = 33). Clinical recovery within 14 days was achieved by 29/33 (88%) in the treatment arm and 22/33 (67%) in the control arm (P = 0.076). The treatment arm had a significantly shorter median duration of hospitalization [6 days (IQR 4-8)] than the control group [8 days (IQR 5-13)]; P = 0.029. Cumulative incidence of hospital discharge was significantly higher in the treatment arm versus the control (Gray's P = 0.041). Three patients died in the treatment arm and five in the control arm. No serious adverse events were reported. Conclusions: The addition of sofosbuvir and daclatasvir to standard care significantly reduced the duration of hospital stay compared with standard care alone. Although fewer deaths were observed in the treatment arm, this was not statistically significant. Conducting larger scale trials seems prudent.

We investigated significant predictors of poor in-hospital outcomes for patients admitted with viral pneumonia during the COVID-19 outbreak in Tehran, Iran. Between February 22 and March 22, 2020, patients who were admitted to three university hospitals during the COVID-19 outbreak in Tehran, Iran were included. Demographic, clinical, laboratory, and chest CT scan findings were gathered. Two radiologists evaluated the distribution and CT features of the lesions and also scored the extent of lung involvement as the sum of three zones in each lung. Of 228 included patients, 45 patients (19.7%) required ICU admission and 34 patients (14.9%) died. According to regression analysis, older age (OR = 1.06; P < 0.001), blood oxygen saturation (SpO2) < 88% (OR = 2.88; P = 0.03), and higher chest CT total score (OR = 1.10; P = 0.03) were significant predictors for in-hospital death. The same three variables were also recognized as significant predictors for invasive respiratory support: SpO2 < 88% (OR = 3.97, P = 0.002), older age (OR = 1.05, P < 0.001), and higher CT total score (OR = 1.13, P = 0.008). Potential predictors of invasive respiratory support and in-hospital death in patients with viral pneumonia were older age, SpO2 < 88%, and higher chest CT score.