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Objective To assess diagnostic validity and reliability of VI-RADS in predicting muscle invasion by bladder cancer (BCa) and evaluate reviewer acceptance of VI-RADS for clinical routine. Methods A prospective multicenter study enrolled 331 patients with suspected/untreated BCa who underwent preoperative multiparametric MRI examination (mp-MRI) of the urinary bladder. Four experienced radiologists independently evaluated all mp-MRI using VI-RADS. The diagnostic validity of VI-RADS for predicting muscle invasion by BCa was calculated using histopathology of the first transurethral resection bladder tumor (TURBT) and second TURBT as the reference standards. The kappa statistics ( κ ) were applied to assess the interreader agreement (IRA). Reviewer acceptance was evaluated with questionnaires. Results The risk of muscle invasion in VI-RADS 2, 3, 4, and 5 after the first and second TURBT was 21.8%, 45.8%, 69.6%, and 96.4% and 24.4%, 58.3%, 87%, and 99.2%, respectively. The overall diagnostic validity of VI-RADS was high. The optimal cut-off value for predicting muscle invasion after first TURBT was > VI-RADS 3 (sensitivity = 84.1% and specificity = 92.3%), and after second TURBT was > VI-RADS 2 (sensitivity = 89.9% and specificity = 90.1%). VI-RADS categorization showed a very good IRA ( κ = 0.93). Reviewers fully agreed with the statement, “The application of structured reporting of bladder tumor should be encouraged” (score = 20). Conclusions VI-RADS showed high diagnostic validity and reliability for predicting muscle invasion by BCa, especially VI-RADS 4 and 5. However, VI-RADS 2 and 3 require further modifications to enhance their diagnostic validity. VI-RADS is highly encouraged to be used in daily practice. Key Points • VI-RADS showed high diagnostic validity and reliability in predicting BCa muscle invasion, especially VI-RADS 4 and 5. • In VI-RADS 2 and 3, we observed a notable percentage of BCa with muscle invasion and this would require further modifications to enhance the diagnostic validity for these scores. • Overall VI-RADS is well-accepted by radiologists who recommend it for daily practice.

The Coronavirus disease 2019 (COVID-19) is an infectious disease spreading rapidly and uncontrollably throughout the world. The critical challenge is the rapid detection of Coronavirus infected people. The available techniques being utilized are body-temperature measurement, along with anterior nasal swab analysis. However, taking nasal swabs and lab testing are complex, intrusive, and require many resources. Furthermore, the lack of test kits to meet the exceeding cases is also a major limitation. The current challenge is to develop some technology to non-intrusively detect the suspected Coronavirus patients through Artificial Intelligence (AI) techniques such as deep learning (DL). Another challenge to conduct the research on this area is the difficulty of obtaining the dataset due to a limited number of patients giving their consent to participate in the research study. Looking at the efficacy of AI in healthcare systems, it is a great challenge for the researchers to develop an AI algorithm that can help health professionals and government officials automatically identify and isolate people with Coronavirus symptoms. Hence, this paper proposes a novel method CoVIRNet (COVID Inception-ResNet model), which utilizes the chest X-rays to diagnose the COVID-19 patients automatically. The proposed algorithm has different inception residual blocks that cater to information by using different depths feature maps at different scales, with the various layers. The features are concatenated at each proposed classification block, using the average-pooling layer, and concatenated features are passed to the fully connected layer. The efficient proposed deep-learning blocks used different regularization techniques to minimize the overfitting due to the small COVID-19 dataset. The multiscale features are extracted at different levels of the proposed deep-learning model and then embedded into various machine-learning models to validate the combination of deep-learning and machine-learning models. The proposed CoVIR-Net model achieved 95.7% accuracy, and the CoVIR-Net feature extractor with random-forest classifier produced 97.29% accuracy, which is the highest, as compared to existing state-of-the-art deep-learning methods. The proposed model would be an automatic solution for the assessment and classification of COVID-19. We predict that the proposed method will demonstrate an outstanding performance as compared to the state-of-the-art techniques being used currently.

Background Anterior knee pain (AKP) is a problematic complaint, considered to be the most frequent cause of orthopedic consultancy for knee problems. This study aimed to highlight diagnostic accuracy of ultrasonography as a fast imaging technique in assessment of patients with AKP. Methods and results A prospective study was conducted on 143 patients with clinically confirmed AKP. All patients underwent ultrasonography and MRI examinations of the knee. The diagnostic accuracy of ultrasonography compared to MRI for evaluating different findings of possible causes of AKP were analyzed using receiver operating characteristic (ROC) curve and judged by area under curve (AUC). A total of 155 knees were included in the study; 26 knees showed no abnormalities, 19 knees showed positive MRI only, and 110 knees showed positive ultrasonography and MRI. Ultrasonography and MRI reported 11 different findings of possible causes of AKP or related to it. Joint effusion was the most common finding (38%) followed by trochlear cartilage defect (20.6%) and superficial infrapatellar subcutaneous edema (20%). The overall accuracy of ultrasonography was 85.3% sensitivity and 100% specificity. The ultrasonography provided the highest sensitivity (100%) in detecting bipartite patella, followed by 91.5% for joint effusion, and 87.5% for quadriceps tendinopathy. The ROC curve analysis of overall accuracy of ultrasonography showed an AUC of 0.93. The overall Kappa agreement between ultrasonography and MRI was good ( k = 0.66). Conclusion Ultrasonography can be used to make a swift screening and assessment of painful anterior knee and as an alternative to MRI when it is unavailable or contraindicated.

Background Mammographic findings are seen more clearly in tomographic images with consequent improvement of Breast Imaging Reporting and Data System (BI-RADS) in categorization of indeterminate breast lesions. This study aimed to evaluate the added value of digital breast tomosynthesis (DBT) to BI-RADS classification in categorization of indeterminate breast lesions after digital mammography (DM) as an initial approach. Methods and results We prospectively evaluated 296 women with BI-RADS indeterminate breast lesions (BI-RADS 0, 3, and 4) by DM between January 2018 and October 2019. All patients underwent DBT. Two radiologists evaluated lesions and assigned a BI-RADS category to each lesion according to BI-RADS lexicon 2013 classification using DM, DBT, and combined DM and DBT. The results were compared in terms of main radiological features, diagnostic performance, and BI-RADS classification using histopathology as the reference standard. A total of 355 lesions were detected on DBT and 318 lesions on DM. Thirty-seven lesions were detected by DBT and not seen by DM. The final diagnoses of 355 lesions were 58.3% benign and 41.7% malignant. In comparison to DM, DBT produced 31.5% upgrading and 35.2% downgrading of BI-RADS scoring of breast lesions. DBT reduced number of BI-RADS 3 and 4, compared to DM. All upgraded BI-RADS 4 were malignant. The combination of DBT and DM significantly increased the performance of BI-RADS in the diagnosis of indeterminate breast lesions versus DM or DBT alone ( p < 0.001). Conclusion Adding DBT to BI-RADS improves its diagnostic performance in detection and characterization of mammography indeterminate breast lesions.

PurposeTo compare effectiveness of three widely used embolic agents in partial splenic embolization (PSE) by analyzing their clinical, laboratory, and radiological outcomes within one year of follow-up.Materials and methodsThis retrospective study examined 179 patients who underwent PSE to manage hypersplenism secondary to cirrhosis. Patients were divided into 3 groups according to embolic agent used. Group 1 (gelatin sponge) included 65 patients, group 2 (embospheres) included 58 patients, and group 3 (PVA) included 56 patients. Clinical, laboratory, and radiological outcomes were compared between groups.ResultsThe technical success rate was 100% in all groups. Pain as a major complication was lower in the gelatin sponge group (20%) compared to the embosphere group (31%) and PVA group (32.3%). Major complications other than pain were found in 20.1%; 24.6% in gelatin sponge group, 15.5% in embosphere group and 19.6% in PVA group (p = 0.045). WBCs and platelet counts showed a significant increase after PSE in all groups. Entire splenic volume as measured by computed tomography after PSE showed no significant difference among the 3 groups; however, the volume of infarcted spleen was significantly lower in the gelatin sponge group compared to other two groups (p = 0.001). The splenic span was significantly reduced one-year post-procedure in three groups (p = 0.006), and it was significantly less in embosphere and PVA groups compared to gelatin sponge group (p < 0.05). Recurrent bleeding was higher in gelatin sponge group (p < 0.05).ConclusionsPermanent embolic materials achieved better laboratory and radiological outcomes than gelatin sponge particles in PSE of cirrhotic hypersplenism patients. However, permanent particles were associated with greater abdominal pain.

BackgroundThere are limited data discussing long-term pain relief and comparability of different image-guided sacroiliac joint (SIJ) injection. This study compared CT and fluoroscopic-guided SIJ injections regarding statistically and clinically significant differences in numeric pain reduction, radiation doses, and patient’s satisfaction.MethodsA prospective study conducted on 52 patients who met specific inclusion criteria of SIJ pain. A mixture of 1 ml of 40 mg methylprednisolone acetate diluted in 2 ml of lidocaine 2% was injected under either CT or fluoroscopic guidance. Numeric rating score (NRS) and Oswestry disability index (ODI) were assessed and recorded for each patient before procedure and one-week, and one-, three-, six-, and 12-months after procedure. The results were compared between both groups.ResultsAnalysis of NRS one-month post-procedure showed a significant decrease from baseline in both groups: 12.5% in CT group (p = 0.002) and 9.5% in fluoroscopic group (p = 0.006). No significant difference in NRS between two groups at one- and three-months post-procedure (p = 0.11 and 0.1, respectively). There was a significant difference in NRS between two groups at six- and 12-months post-procedure (p = 0.001 and < 0.0001, respectively). Comparison of ODI at six-month post-procedure revealed that both groups had a statistically significant improvement (p < 0.0001). There was a significant difference in ODI between two groups at six-months post-procedure (p = 0.01).ConclusionsCT-guided SIJ injection compares favorably with fluoroscopic guidance and offers statistically and clinically significant long-term pain relief. The use of dose reduction protocol in CT is important for decreasing the radiation dose.

BackgroundThe Radiological Society of North America (RSNA) recently published a chest CT classification system and Dutch Association for Radiology has announced Coronavirus disease 2019 (COVID-19) reporting and data system (CO-RADS) to provide guidelines to radiologists who interpret chest CT images of patients with suspected COVID-19 pneumonia. This study aimed to compare CO-RADS and RSNA classification with respect to their sensitivity and reliability for diagnosis of COVID-19 pneumonia.ResultsA retrospective study assessed consecutive CT chest imaging of 359 COVID-19-positive patients. Three experienced radiologists who were aware of the final diagnosis of all patients, independently categorized each patient according to CO-RADS and RSNA classification. RT-PCR test performed within one week of chest CT scan was used as a reference standard for calculating sensitivity of each system. Kappa statistics and intraclass correlation coefficient were used to assess reliability of each system. The study group included 359 patients (180 men, 179 women; mean age, 45 ± 16.9 years). Considering combination of CO-RADS 3, 4 and 5 and combination of typical and indeterminate RSNA categories as positive predictors for COVID-19 diagnosis, the overall sensitivity was the same for both classification systems (72.7%). Applying both systems in moderate and severe/critically ill patients resulted in a significant increase in sensitivity (94.7% and 97.8%, respectively). The overall inter-reviewer agreement was excellent for CO-RADS (κ = 0.801), and good for RSNA classification (κ = 0.781).ConclusionCO-RADS and RSNA chest CT classification systems are comparable in diagnosis of COVID-19 pneumonia with similar sensitivity and reliability.

Objective The American College of Radiology (ACR) recently published the ovarian-adnexal reporting and data system (O-RADS) to provide guidelines to physicians who interpret ultrasound (US) examinations of adnexal masses (AM). This study aimed to compare the O-RADS with two other well-established US classification systems for diagnosis of AM. Methods This retrospective multicenter study between May 2016 and December 2019 assessed consecutive women with AM detected by the US. Five experienced consultant radiologists independently categorized each AM according to O-RADS, gynecologic imaging reporting and data system (GI-RADS), and international ovarian tumor analysis (IOTA) simple rules. Pathology and adequate follow-up were used as reference standards for calculating the validity of three US classification systems for diagnosis of AM. Kappa statistics were used to assess the inter-reviewer agreement (IRA). Results A total of 609 women (mean age, 48 ± 13.7 years; range, 18–72 years) with 647 AM were included. Of the 647 AM, 178 were malignant and 469 were benign. Malignancy rates were comparable to recommended rates by previous literature in O-RADS and IOTA, but higher in GI-RADS. O-RADS had significantly higher sensitivity for malignancy than GI-RAD and IOTA ( p = 0.003 and 0.0007, respectively), but non-significant slightly lower specificity ( p > 0.05). O-RADS, GI-RADS, and IOTA showed similar overall IRA ( κ = 0.77, 0.69, and 0.63, respectively) with a tendency toward higher IRA with O-RADS than with GI-RADS and IOTA. Conclusions O-RADS compares favorably with GI-RADS and IOTA. O-RADS had higher sensitivity than GI-RADS and IOTA simple rules with relatively similar specificity and reliability. Key Points • The malignancy rates were comparable to recommended rates by previous literature in O-RADS and IOTA, but higher in GI-RADS. • The O-RADS had significantly higher sensitivity for malignancy than GI-RADS and IOTA (96.8% vs 92.7% and 92.1%; p = 0.003 and 0.0007, respectively), but non-significant slightly lower specificity (92.8% vs 93.6% and 93.2%, respectively; p > 0.05). • The O-RADS, GI-RADS, and IOTA showed similar overall inter-reviewer agreement (IRA) (κ = 0.77, 0.69, and 0.63, respectively), with a tendency toward higher IRA with O-RADS than with GI-RADS and IOTA.

ObjectiveTo compare diagnostic performance and agreement between CT, MRI and combined CT/MRI in reference to LI-RADS classification system to categorize hepatic observations detected in hepatic patients during screening ultrasound.Methods240 patients with 296 liver observations detected during ultrasound surveillance underwent hepatic CT and MRI examinations, histopathology, and clinical and radiological follow-up. Using LI-RADS v2014, six radiologists evaluated the observations independently and assigned a LI-RADS category to each observation using CT, MRI and combined CT/MRI.ResultsCombined CT and MRI in LI-RADS yielded better accuracy (91.29 %), sensitivity (90.71 %) and specificity (92.31 %) for hepatocellular carcinoma (HCC) diagnosis than using MRI or CT alone; accuracy, sensitivity and specificity decreased to 85.37 %, 86.34 %, and 83.65 %, respectively, for MRI and 67.6 %, 54.10 % and 91.35 %, respectively, for CT. The intraclass agreement of the LI-RADS scores between CT, MRI and combined CT/MRI was excellent (κ=0.9624 (95 % CI: 0.9318–0.9806)).ConclusionCT and MRI are complementary to each other. Combined CT/MRI enabled a more precise determination of LI-RADS category of hepatic observations; however, due to the expense and minor increase in accuracy, the combined methodology should only be utilized in cases of suspected HCC.Key Points• Hepatic observation may be categorized differently depending on the imaging modality used.• We compared LI-RADS categorization between CT, MRI and combined CT/MRI.• MRI produces higher accuracy and sensitivity, while CT produces higher specificity.• Combining CT and MRI improves LIRADS categorization reports.• Considering additional cost, combined methodology could be restricted to challenging cases.