In this study, we assess the power of MRI radiomic features for prediction of locally advanced rectal cancer (LARC) patients' response to neoadjuvant chemoradiation. T2-Weighted MR images acquired 2 ...weeks before and 4 weeks after treatment of 50 patients were used. The tumor volume was delineated by an experienced radiologist on T2-weighted MR images followed by the extraction of radiomics features, including morphology, first-order, histogram, and texture from volumes of interest (VOI). First, univariate analysis was applied on features to identify predictive power of features. To build a predictive model, we used Random Forest (RF) algorithm along with Max-Relevance-Min-Redundancy (MRMR) feature selection algorithm for reducing complexity and improving generalization. Finally, the model was evaluated through the area under the receiver operator characteristic (ROC) curve (AVC), sensitivity, specificity and accuracy metrics. In univariate analysis, delta radiomics of LAE and LALGLE features from GLSZM had the highest predictive performance (AUC=0.67). In multivariate analysis, the highest predictive performance for response prediction in LARC patients was achieved using delta-radiomic features with AUC of 0.92 and 0.88 in training and validation datasets, respectively. The achieved results were promising to move towards personalized treatment for LARC patients.
Chest computed tomography (CT) imaging was widely used for diagnosis and staging of severe acute respiratory syndrome coronavirus (SARS-CoV-2). CT can be utilized for initial diagnosis, severity ...scoring, serial monitoring, and patient status follow-up. For serial monitoring and follow-up, patients need to be scanned multiple times. The tendency in CT imaging is to minimize patient radiation dose. However, CT imaging is still considered as a high radiation dose modality. In this work, we proposed a deep residual neural network-based high quality (full dose) generation from ultra low-dose CT images to decrease the radiation dose for COVID-19 patients. In this multicenter study, we enrolled 1140 subjects with 313 PCR positive COVID-19 patients. The ultra low-dose CT images were analytically simulated, and then a deep residual neural network employed to estimate/generate full-dose images from the corresponding ultra-low-dose images. Various quantitative parameters, including the root mean square error (RMSE), structural similarity index (SSIM), and qualitative visual scoring were implemented to evaluate image quality of the generated CT images. The mean CTDI vol for full-dose images were 6.5 Gy (4.16-10.5 mGy), while, the simulated low-dose images were intended for a mean CTDI vol of 0.72 mGy (0.66-1.02 mGy). Regarding the external validation set (test set), the RMSE declined from 0.16±0.06 to 0.08±0.02 in low-dose and predicted standard-dose CT images, while the SSIM metric increased from 0.89±0.07 to 0.97±0.01, respectively. The highest visual scores (out of 5) were achieved by full-dose images (4.72±0.57) and predicted full-dose images (4.42±0.08). Conversely, ultra-low-dose images received the lowest score (2.78±0.9). In can be concluded that the proposed deep residual network improved image quality of ultra low-dose CT images, thus recovering their diagnostic value.
BackgroundIn COVID-19 pneumonia, chest CT scan plays a crucial role in diagnosing and closely monitoring lung parenchyma. The main reportedly chest CT features of novel coronavirus pneumonia (NCP) ...have been fully discussed in the literature, but there is still a paucity of reports on uncommon CT manifestations. Case presentationHerewith, we have reported ten rRT-PCR confirmed COVID-19 patients with CT target signs (bull's eye appearance); additionally, we have reviewed previously reported cases. Reviewing the literature, we found eight COVID-19 patients with target sign in the literature. 18 patients were included with a median age of 43. 11 (61%) patients were males. In 87% of patients, the lesions developed within the second-week post symptom onset. These patients mostly experienced an extended hospital stay (median = 10 days), with 53.8% of cases being admitted in ICU. The in-hospital mortality rate was 23%. ConclusionOur findings indicate that lesions with a bull's eye appearance are not significantly associated with higher mortality in hospitalized COVID-19 patients.
Erdheim-Chester disease (ECD) is a rare non-Langerhans histiocytosis. ECD is detected more frequently due to increased awareness of healthcare providers and improved diagnostic tools. This report ...describes a 51-year-old woman with a history of weakness, bone pain, xanthelasma palpebrarum, and diabetes insipidus. ECD is a multisystemic condition with a poor prognosis. This disease should be considered in patients with diabetes insipidus, bone pain, and multiorgan involvements.
BACKGROUNDA textiloma is a rare retained surgical swab with probable serious post-operation complications. CASE REPORTHere, we reported an asymptomatic patient who had past history of coronary artery ...bypass grafting (CABG) fourteen months ago and referred to our institute for left atrial mass removal. Echocardiography and chest computed tomography (CT) scan revealed a non-homogenous non-mobile mass and a heterogeneous lesion with low-density as well as high-density areas with spot calcification and gas bubbles at left atrium level, respectively. CONCLUSIONDespite being rare after CABG, textiloma should be considered in the differential diagnosis in case of any suspicious chest mass even in asymptomatic patients.
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