Application of deep learning image reconstruction-high algorithm in one-stop coronary and carotid-cerebrovascular CT angiography with low radiation and contrast doses.

Background: For patients with suspected simultaneous coronary and cerebrovascular atherosclerosis, conventional single-site computed tomography angiography (CTA) for both sites can result in nonnegligible radiation and contrast agent dose. The purpose of this study was to validate the feasibility of one-stop coronary and carotid-cerebrovascular CTA (C&CC-CTA) with a "double-low" (low radiation and contrast) dose protocol reconstructed with deep learning image reconstruction with high setting (DLIR-H) algorithm. Methods: From February 2018 to January 2019, 60 patients referred to C&CC-CTA simultaneously in West China Hospital were recruited in this prospective cohort study. By random assignment, patients were divided into two groups: double-low dose group (n=30) used 80 kVp and 24 mgI/kg/s contrast dose with images reconstructed using DLIR-H; and routine-dose group (n=30) used 100 kVp and 32 mgI/kg/s contrast dose with images reconstructed using 50% adaptive statistical iterative reconstruction-V (ASIR-V50%). Radiation and contrast doses, subjective image quality score, CT attenuation values, noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured and compared between the groups. Results: The DLIR-H group used 30% less contrast dose (35.80±4.85 vs. 51.13±6.91 mL) and 48% less overall radiation dose (1.00±0.09 vs. 1.91±0.42 mSv) than the ASIR-V50% group (both P<0.001). There was no statistically significant difference on subjective quality score between the two groups (C-CTA: 4.38±0.67 vs. 4.17±0.81, P=0.337 and CC-CTA: 4.18±0.87 vs. 4.08±0.79, P=0.604). For coronary CTA, lower background noise (18.93±1.43 vs. 22.86±3.75 HU) was reached in DLIR-H group, and SNR and CNR at all assessed branches were significantly increased compared to ASIR-V50% group (all P<0.05), except SNR of left anterior descending (P>0.05). For carotid-cerebrovascular CTA, DLIR-H group was comparable in background noise (19.25±1.42 vs. 20.23±2.40 HU), SNR and CNR at all assessed branches with ASIR-V50% group (all P>0.05). Conclusions: The "double-low" dose one-stop C&CC-CTA with DLIR-H obtained higher image quality compared with the routine-dose protocol with ASIR-V50% while achieving 48% and 30% reduction in radiation and contrast dose, respectively.

Relationships between the coronary fat attenuation index for patients with heart-related disease measured automatically on coronary computed tomography angiography and coronary adverse events and degree of coronary stenosis.

Background: Pericoronary artery coronary tissue (PACT) is a type of epicardial fat that can reflect the state of the coronary artery (inflammation, etc.). However, it cannot be reasonably and efficiently utilized in routine computed tomography (CT) examination. The aim of this study was to use artificial intelligence (AI) software to analyze coronary computed tomography angiography (CCTA) and measure the coronary perivascular fat attenuation index (FAI) of patients. The relationship between FAI and the occurrence of coronary adverse events and the degree of coronary stenosis were further analyzed. Methods: This study involved patients who experienced CCTA in West China Hospital, Sichuan University, from January 2012 to December 2012. These patients were followed up to 2020 and classified according to the occurrence of coronary adverse events and the degree of stenosis of the lumen. For all patients, AI software was used to analyze the CCTA images of patients, and the FAI of 3 coronary arteries, the left anterior descending artery (LAD), the left circumflex artery (LCX), and the right coronary artery (RCA), was measured. Moreover, the relationship between FAI and patients with different degrees of coronary stenosis and adverse coronary events was determined. Results: Comparisons between any 2 groups showed that the differences in the FAI among the 4 groups for the LAD were significant (all P values <0.05). There were no significant differences between the group with less-than-moderate stenosis (Mb) without adverse events and the group with moderate-or-above stenosis (M) with no adverse events for the LCX (P>0.05). For the remaining groups, FAI values exhibited statistically significant differences (P<0.05). According to the degree of lumen stenosis, the patients were divided into groups according to LAD, LCX, and RCA and the sum of the 3 vessels. There were significant differences in coronary FAI among the groups with different degrees of lumen stenosis for the sum of the 3 vessels, the LAD, and the LCX (P<0.05). Conclusions: FAI can reflect the state of the coronary artery, which is related to inflammation of the coronary lumen. Moreover, there is a relationship between FAI and the degree of stenosis in the coronary lumen: the narrower the coronary lumen is, the higher the FAI around the lumen.

Pulmonary extranodal natural killer/T-cell lymphoma: clinical presentation, CT characteristics, and patient outcomes.

Background: Due to the extreme rarity of pulmonary extranodal natural killer/T-cell lymphoma (ENKTCL), studies on this lymphoma type are limited. We aimed to investigate the clinical presentations, computed tomography (CT) findings, CT dynamic changes, and outcomes of patients diagnosed with pulmonary ENKTCL. Methods: We conducted a retrospective cohort study on ENKTCL, nasal type, at West China Hospital, from January 2010 to January 2023. Out of 27 initial cases with pulmonary ENKTCL, we excluded 4 due to the lack of chest CT images, resulting in a final cohort of 23 patients. Our evaluation covered clinical features, laboratory findings, CT presentations, treatment strategies, and survival outcomes. Survival analyses were performed using the Kaplan-Meier method, with log-rank tests for survival curve comparisons. Given the small sample size, our interpretation of the data is mainly descriptive. Results: The most common CT presentations in our institution was solitary or multiple nodules (7/23, 30.4%). The halo sign (78.3%) and floating vessels sign (83.3%) were commonly observed in pulmonary ENKTCL. Elevated lactate dehydrogenase (LDH) levels were observed in 20 (86.9%) patients. The median overall survival (OS) for pulmonary ENKTCL patients was 1 month; 3 cases displayed a favorable prognosis, maintaining complete remission (CR) status for 1.5-7 years after receiving chemotherapy. Chemotherapy led to improved prognosis, with a median survival of 5 months seen in patients who received chemotherapy. Patients with bilateral lung involvement had worse outcomes compared to those with unilateral lesions. Conclusions: Pulmonary ENKTCL is a rare and aggressive disease, often misdiagnosed due to nonspecific clinical and CT features. Laboratory tests, failure of antibiotic treatment, and "floating vessels sign" on enhanced CT scans may aid in diagnosis. Timely chemotherapy may improve survival, emphasizing the importance of early detection and prompt treatment.

The Association of Coronary Fat Attenuation Index Quantified by Automated Software on Coronary Computed Tomography Angiography with Adverse Events in Patients with Less than Moderate Coronary Artery Stenosis.

OBJECTIVE: This study analyzed the relationship between the coronary FAI on CCTA and coronary adverse events in patients with moderate coronary artery disease based on machine learning. METHODS: A total of 172 patients with coronary artery disease with moderate or lower coronary artery stenosis were included. According to whether the patients had coronary adverse events, the patients were divided into an adverse group and a non-adverse group. The coronary FAI of patients was quantified via machine learning, and significant differences between the two groups were analyzed via t-test. RESULTS: The age difference between the two groups was statistically significant (p < 0.001). The group that had adverse reactions was older, and there was no statistically significant difference between the two groups in terms of sex and smoking status. There was no statistical significance in the blood biochemical indexes between the two groups (p > 0.05). There was a significant difference in the FAIs between the two groups (p < 0.05), with the FAI of the defective group being greater than that of the nonperforming group. Taking the age of patients as a covariate, an analysis of covariance showed that after excluding the influence of age, the FAIs between the two groups were still significantly different (p < 0.001).

Monitoring small airway dysfunction in connective tissue disease-related interstitial lung disease: a retrospective and prospective study.

BACKGROUND: Small airway dysfunction (SAD), a hallmark of early lung function abnormality, is a major component of several chronic respiratory disorders. The role of SAD in patients with connective tissue disease-related interstitial lung disease (CTD-ILD) has not been explored. METHODS: We conducted a two-parts (retrospective and prospective) study to collect pulmonary function tests from CTD-ILD patients. SAD was defined as at least two of the three measures (MMEF, FEF 50%, and FEF 75%) must be 65% of predicted values. Spearman correlation coefficient was used to evaluate association between SAD and other pulmonary function parameters. Mixed effects regression modeling analysis was used to assess response to treatment. RESULTS: CTD-ILD patients with SAD and without SAD were compared in this study. In the retrospective study, pulmonary function tests (PFTs) from 491 CTD-ILD patients were evaluated, SAD were identified in 233 (47.5%). CTD-ILD patients with SAD were less smokers (17.6% vs. 27.9%, p = 0.007) and more females (74.3% vs. 64.0%, p = 0.015) than those without SAD. CTD-ILD patients with SAD had lower vital capacity (% predicted FVC, 70.4 ± 18.3 vs. 80.0 ± 20.9, p < 0.001) and lower diffusion capacity (% predicted DLCO, 58.8 ± 19.7 vs. 63.8 ± 22.1, p = 0.011) than those without SAD. Among 87 CTD-ILD patients prospectively enrolled, significant improvement in % predicted FVC was observed at 12-months follow-up (6.37 ± 1.53, p < 0.001 in patients with SAD; 5.13 ± 1.53, p = 0.002 in patients without SAD), but not in diffusion capacity and SAD parameters. CONCLUSION: In our cohort, about half of CTD-ILD patients have SAD, which is less frequent in smokers and more common in female patients. CTD-ILD patients with SAD have worse pulmonary function compared to those without SAD. Improvement of FVC but no improvement of SAD was observed in CTD-ILD patients after treatment.

Primary Pulmonary Artery Leiomyosarcoma with Pulmonary Metastasis Depicted on Enhanced Computer Tomography: A Case Description and an Analysis of the Literature.

Pulmonary artery leiomyosarcoma is an extremely rare disease, with only a few dozen cases reported worldwide to date. This disease is easily misdiagnosed as pulmonary thromboembolism, leading to improper treatment and accurate diagnosis in the later stages of the disease. Furthermore, this delayed diagnosis may also be the reason for the extremely high mortality rate of patients suffering from it. Early invasive surgery with the goal of complete surgical resection is the standard treatment method. Chemotherapy and radiation therapy have been tried with variable outcomes.

A Man in His 20s With Gradually Enlarging Mediastinal Mass and Intermittent Hemoptysis.

This case report describes a diagnosis of ruptured coronary artery aneurysm after a patient presentation of chest pain and new-onset intermittent hemoptysis.

Feasibility of Using High-Resolution Computed Tomography Features for Invasiveness Differentiation of Malignant Nodules Manifesting as Ground-Glass Nodules.

Ground-glass nodule (GGN)-like adenocarcinoma is a special subtype of lung cancer. The invasiveness of the nodule correlates well with the patient's prognosis. This study aimed to establish a radiomic model for invasiveness differentiation of malignant nodules manifesting as ground glass on high-resolution computed tomography (HRCT). Between January 2014 and July 2019, 276 pulmonary nodules manifesting as GGNs on preoperative HRCTs, whose histological results were available, were collected. The nodules were randomly classified into training (n = 221) and independent testing (n = 55) cohorts. Three logistic models using features derived from HRCT were fit in the training cohort and validated in both aforementioned cohorts for invasive adenocarcinoma and preinvasive-minimally invasive adenocarcinoma (MIA) differentiation. The model with the best performance was presented as a nomogram and was validated using a calibration curve before performing a decision curve analysis. The benefit of using the proposed model was also shown by groups of management strategies recommended by The Fleischner Society. The combined model showed the best differentiation performance (area under the curve (AUC), training set = 0.89, and testing set = 0.92). The quantitative texture model showed better performance (AUC, training set = 0.87, and testing set = 0.91) than the semantic model (AUC, training set = 0.83, and testing set = 0.79). Of the 94 type 2 nodules that were IACs, 66 were identified by this model. Models using features derived from imaging are effective for differentiating between preinvasive-MIA and IACs among lung adenocarcinomas appearing as GGNs on CT images.

Computed Tomography-Based Radiomics for Differentiation of Thymic Epithelial Tumors and Lymphomas in Anterior Mediastinum.

Objective: To investigate the differential diagnostic performance of computed tomography (CT)-based radiomics in thymic epithelial tumors (TETs) and lymphomas in anterior mediastinum. Methods: There were 149 patients with TETs and 93 patients with lymphomas enrolled. These patients were assigned to a training set (n = 171) and an external validation set (n = 71). Dedicated radiomics prototype software was used to segment lesions on preoperative chest enhanced CT images and extract features. The multivariable logistic regression algorithm was used to construct three models according to clinico-radiologic features, radiomics features, and combined features, respectively. Performance of the three models was compared by using the area under the receiver operating characteristic curves (AUCs). Decision curve analysis was used to evaluate clinical utility of the three models. Results: For clinico-radiologic model, radiomics signature model, and combined model, the AUCs were 0.860, 0.965, 0.975 and 0.843, 0.961, 0.955 in the training cohort and the test cohort, respectively (all P<0.05). The accuracies of each model were 0.836, 0.895, 0.918 and 0.845, 0.901, 0.859 in the two cohorts, respectively (all P<0.05). Compared with the clinico-radiologic model, better diagnostic performances were found in the radiomics signature model and the combined model. Conclusions: Radiomics signature model and combined model exhibit outstanding and comparable differential diagnostic performances between TETs and lymphomas. The CT-based radiomics analysis might serve as an effective tool for accurately differentiating TETs from lymphomas before treatment.

Computed tomography-based radiomics for identifying pulmonary cryptococcosis mimicking lung cancer.

BACKGROUND: Pulmonary cryptococcosis (PC) is an invasive pulmonary fungal disease, and nodule/mass-type PC may mimic lung cancer (LC) in imaging appearance. Thus, an accurate diagnosis of nodule/mass-type PC is beneficial for appropriate management. However, the differentiation of nodule/mass-type PC from LC through computed tomography (CT) is still challenging. PURPOSE: To develop and externally test a CT-based radiomics model for differentiating nodule/mass-type PC from LC. METHODS: In this retrospective study, patients with nodule/mass-type PC or LC who underwent non-enhanced chest CT were included: Institution 1 was for the training set, and institutions 2 and 3 were for the external test set. Large quantities of radiomics features were extracted. The radiomics score (Rad-score) was calculated using the linear discriminant analysis, and a subsequent fivefold cross-validation was performed. A combined model was developed by incorporating Rad-score and clinical factors. Finally, the models were tested with an external test set and compared using the area under the receiver operating characteristic curve (AUC). RESULTS: A total of 168 patients (45 with PC and 123 with LC) were in the training set, and 72 (36 with PC and 36 with LC) were in the external test set. Of the 81 patients with PC, 30 were immunocompromised (37%). Rad-score, comprising 18 features, had an AUC of 0.844 after fivefold cross-validation, which was lower than that (AUC = 0.943, p = 0.003) of the combined model integrating Rad-score, age, lobulation, pleural retraction, and patches. In the external test set, Rad-score and the combined model obtained good predictive performance (AUC = 0.824 for Rad-score, and 0.869 for the combined model). Moreover, the combined model outperformed the clinical model in the cross-validation and external test (0.943 vs. 0.810, p <0.001; 0.869 vs. 0.769, p = 0.011). CONCLUSIONS: The proposed combined model exhibits a good differential diagnostic performance between nodule/mass-type PC and LC. The CT-based radiomics analysis has the potential to serve as an effective tool for the differentiation of nodule/mass-type PC from LC in clinical practice.

Regional Fat Distributions Are Associated With Subclinical Right Ventricular Dysfunction in Adults With Uncomplicated Obesity.

Objective: Obesity is a prominent public health problem that has increased cardiovascular mortality risks. However, the specific effects of obesity, independent of comorbidities, on cardiac structure and function have not been well clarified, especially those effects on the right ventricle (RV). Cardiovascular magnetic resonance (CMR) tissue tracking can assess detailed RV mechanical features. This study aimed to evaluate RV strain using CMR in uncomplicated obese adults and assess its association with fat distributions. Methods: A total of 49 obese patients and 30 healthy controls were included. The RV global systolic function and strain parameters based on CMR were assessed. Body fat distributions were measured with dual X-ray absorptiometry. RV function indices of obese patients were compared with those of healthy controls. Correlations among related body fat distribution parameters and RV function indices were conducted with multivariable linear regression. Results: Compared with healthy controls, the obese group had impaired RV strain with lower global longitudinal peak strain (PS), longitudinal peak systolic strain rate (PSSR), circumferential and longitudinal peak diastolic strain rates (PDSR) (all P < 0.05), while LV and RV ejection fractions were not significantly different between the two groups (P > 0.05). Multivariable linear regression analysis demonstrated that android fat% was independently associated with longitudinal PS (ß = -0.468, model R2 = 0.219), longitudinal PDSR (ß = -0.487, model R2 = 0.237), and circumferential PSSR (ß = -0.293, model R2 = 0.086). Trunk fat% was independently associated with longitudinal PSSR (ß = -0.457, model R2 = 0.209). In addition, the strongest correlations of circumferential PDSR were BMI and gynoid fat% (ß = -0.278, ß = 0.369, model R2 = 0.324). Conclusions: Extensive subclinical RV dysfunction is found in uncomplicated obese adults. BMI, as an index of overall obesity, is independently associated with subclinical RV dysfunction. In addition, central obesity (android fat and trunk fat distributions) has a negative effect on subclinical RV function, while peripheral obesity (gynoid fat distribution) may have a positive effect on it. Clinical Trials Registration: Effect of lifestyle intervention on metabolism of obese patients based on smart phone software (ChiCTR1900026476).

Myocardial extracellular volume assessed by cardiovascular magnetic resonance may predict adverse left ventricular remodeling in rheumatic heart disease after valvular surgery.

Background: Only a few studies to date have focused on the application of cardiovascular magnetic resonance (CMR) in rheumatic heart disease (RHD); in particular, research on the application of T1-mapping CMR sequences is limited. This study aimed to investigate whether diffuse myocardial fibrosis evaluated using preoperative T1 mapping and extracellular volume (ECV) fraction measurement could predict the progression of adverse left ventricular remodeling (LVR) after surgery. Methods: A total of 32 adult patients with RHD and 30 healthy controls were recruited. Baseline clinical characteristics, CMR findings, and T1 mapping measurements were compared between the two groups. Transthoracic echocardiography measurements were collected before and after surgery. Patients with an increase in left ventricular end-diastolic volume of >15% or a decrease in left ventricular ejection fraction of >10% were classified into the adverse remodeling group; otherwise, patients were categorized into the non-adverse remodeling group. Results: Compared with the healthy controls, patients with RHD had impaired biventricular function, enlarged ventricular volume, and increased native T1 and ECV values. Patients in the adverse remodeling group had higher ECV values than those in the non-adverse remodeling group (33.25%±3.67% vs. 28.45%±4.46%, P=0.002). Binary logistic regression analysis showed that the ECV value was associated with adverse LVR (odds ratio: 1.273, P=0.045). ECV was found to be a sensitive biomarker for predicting adverse LVR (area under the curve: 0.78; sensitivity: 75.0%; specificity: 77.3%). Conclusions: ECV has potential value for predicting the progression of adverse LVR and for identifying non-responders among patients with RHD undergoing surgery.

Image quality assessment of artificial intelligence iterative reconstruction for low dose aortic CTA: A feasibility study of 70 kVp and reduced contrast medium volume.

PURPOSE: To investigate the image quality and feasibility of a novel artificial intelligence iterative reconstruction (AIIR) algorithm for aortic computer tomography angiography (CTA) with a low radiation dose and contrast material (CM) dosage protocol in comparison with hybrid iterative reconstruction (HIR) algorithm for standard-of-care aortic CTA. METHODS: Fifty consecutive patients (mean age 58 ± 14 years, mean BMI 24.5 ± 4.7 kg/m2) with aortic diseases were prospectively enrolled. All patients underwent at least twice follow-up aortic CTA examinations. Standard dose CT (SDCT) was applied in the initial follow-up examination (100 kVp, auto mAs, contrast dose 0.8 mgL/kg), images were reconstructed with HIR (SDCT-HIR). In the second follow-up examination, patients underwent scanning with low dose CT (LDCT) (70 kVp, auto mAs, contrast dose 0.5 mgL/kg), images were reconstructed with HIR (LDCT-HIR) as well as AIIR (LDCT-AIIR). Attenuation values, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured for objective analysis. Subjective image quality was rated by two blinded radiologists using a 5-point scale. The effective radiation dose and CM dosage were also recorded. RESULTS: The effective radiation dose (1.58 ± 0.17 mSv vs. 9.96 ± 1.05 mSv, P < 0.001) and CM dosage (34.38 ± 5.43 ml vs. 54.64 ± 8.63 ml, P < 0.001) achieved a remarkable reduction of 84.14% and 37.08% in the LDCT compared to the SDCT. The attenuation was similar among the three reconstructed images (P > 0.05). Compared to LDCT-HIR images, LDCT-AIIR showed a lower noise and higher SNR and CNR. For qualitative analysis, there were no significant differences between the LDCT-AIIR and the SDCT-HIR images among four metrics (P > 0.05). CONCLUSIONS: Compared to standard-of-care aortic CTA with HIR, the application of the AIIR algorithm allows for radiation dose and CM dosage reduction while preserving image quality on low dose aortic CTA.

High-strength deep learning image reconstruction in coronary CT angiography at 70-kVp tube voltage significantly improves image quality and reduces both radiation and contrast doses.

OBJECTIVES: To explore the use of 70-kVp tube voltage combined with high-strength deep learning image reconstruction (DLIR-H) in reducing radiation and contrast doses in coronary CT angiography (CCTA) in patients with body mass index (BMI) < 26 kg/m2, in comparison with the conventional scan protocol using 120 kVp and adaptive statistical iterative reconstruction (ASIR-V). METHODS: A total of 100 patients referred to CCTA were prospectively enrolled and randomly divided into two groups: low-dose group (n = 50) with 70 kVp, Smart mA for noise index (NI) of 36HU, contrast dose rate of 16mgI/kg/s, and DLIR-H, and conventional group (n = 50) with 120 kV, Smart mA for NI of 25HU, contrast dose rate of 32mgI/kg/s, and 60%ASIR-V. Radiation and contrast dose, subjective image quality score, and objective image quality measurement (image noise, contrast-noise-ratio (CNR), and signal-noise-ratio (SNR) for vessel) were compared between the two groups. RESULTS: Low-dose group used significantly reduced contrast dose (23.82 ± 3.69 mL, 50.6% reduction) and radiation dose (0.75 ± 0.14 mSv, 54.5% reduction) compared to the conventional group (48.23 ± 6.38 mL and 1.65 ± 0.66 mSv, respectively) (all p < 0.001). Both groups had similar enhancement in vessels. However, the low-dose group had lower background noise (23.57 ± 4.74 HU vs. 35.04 ± 8.41 HU), higher CNR in RCA (48.63 ± 10.76 vs. 29.32 ± 5.52), LAD (47.33 ± 10.20 vs. 29.27 ± 5.12), and LCX (46.74 ± 9.76 vs. 28.58 ± 5.12) (all p < 0.001) compared to the conventional group. CONCLUSIONS: The use of 70-kVp tube voltage combined with DLIR-H for CCTA in normal size patients significantly reduces radiation dose and contrast dose while further improving image quality compared with the conventional 120-kVp tube voltage with 60%ASIR-V. KEY POINTS: • The combination of 70-kVp tube voltage and high-strength deep learning image reconstruction (DLIR-H) algorithm protocol reduces approximately 50% of radiation and contrast doses in coronary computed tomography angiography (CCTA) compared with the conventional scan protocol. • CCTA of normal size (BMI < 26 kg/m2) patients acquired at sub-mSv radiation dose and 24 mL contrast dose through the combination of 70-kVp tube voltage and DLIR-H algorithm achieves excellent diagnostic image quality with a good inter-rater agreement. • DLIR-H algorithm shows a higher capacity of significantly reducing image noise than adaptive statistical iterative reconstruction algorithm in CCTA examination.

Practice-Based Learning Using Smart Class: A Competency-Based Model in Undergraduate Radiology Education.

RATIONALE AND OBJECTIVES: A need for adequate and early exposure to radiology practice is rising in undergraduate students, taking competency development as the orientation. We aimed to develop a competency-based model of practice-based learning for undergraduate radiology education. MATERIALS AND METHODS: The model of practice-based learning was constructed upon an e-learning smart class environment, with case-based learning and simulators for competency development. To assess the model effectiveness, a randomized controlled experiment was performed, where 57 third-year medical students received the model (Smart-Class group) and another 57 received traditional teaching (Traditional group). Seven quizzes, a final exam, and a survey were performed in both groups. RESULTS: Smart-Class group achieved higher mean score in the quizzes (r = -0.4, p < 0.001) and application subscore in the final exam (r = -0.3, p = 0.005) compared to Traditional group. Smart-Class group also gave higher ratings in students' perceptions concerning promotion of learning interests, radiology skills, and diagnostic reasoning (r = -0.2 to -0.3, p = 0.001-0.034). CONCLUSION: Practice-based learning using smart class improved students' application ability and satisfactions in undergraduate radiology education, suggesting it a practical model for early exposure to radiology practice and competency development for undergraduate medical students.

Radiomic analysis of enhanced CMR cine images predicts left ventricular remodeling after TAVR in patients with symptomatic severe aortic stenosis.

Objective: This study aimed to develop enhanced cine image-based radiomic models for non-invasive prediction of left ventricular adverse remodeling following transcatheter aortic valve replacement (TAVR) in symptomatic severe aortic stenosis. Methods: A total of 69 patients (male:female = 37:32, median age: 66 years, range: 47-83 years) were retrospectively recruited, and severe aortic stenosis was confirmed via transthoracic echocardiography detection. The enhanced cine images and clinical variables were collected, and three types of regions of interest (ROIs) containing the left ventricular (LV) myocardium from the short-axis view at the basal, middle, and apical LV levels were manually labeled, respectively. The radiomic features were extracted and further selected by using the least absolute shrinkage and selection operator (LASSO) regression analysis. Clinical variables were also selected through univariate regression analysis. The predictive models using logistic regression classifier were developed and validated through leave-one-out cross-validation. The model performance was evaluated with respect to discrimination, calibration, and clinical usefulness. Results: Five basal levels, seven middle levels, eight apical level radiomic features, and three clinical factors were finally selected for model development. The radiomic models using features from basal level (Rad I), middle level (Rad II), and apical level (Rad III) had achieved areas under the curve (AUCs) of 0.761, 0.909, and 0.913 in the training dataset and 0.718, 0.836, and 0.845 in the validation dataset, respectively. The performance of these radiomic models was improved after integrating clinical factors, with AUCs of the Combined I, Combined II, and Combined III models increasing to 0.906, 0.956, and 0.959 in the training dataset and 0.784, 0.873, and 0.891 in the validation dataset, respectively. All models showed good calibration, and the decision curve analysis indicated that the Combined III model had a higher net benefit than other models across the majority of threshold probabilities. Conclusion: Radiomic models and combined models at the mid and apical slices showed outstanding and comparable predictive effectiveness of adverse remodeling for patients with symptomatic severe aortic stenosis after TAVR, and both models were significantly better than the models of basal slice. The cardiac magnetic resonance radiomic analysis might serve as an effective tool for accurately predicting left ventricular adverse remodeling following TAVR in patients with symptomatic severe aortic stenosis.

A better understanding of testicular and/or epididymal tuberculosis based on clinical, ultrasonic, computed tomography, and magnetic resonance imaging features at a high-volume institute in the modern era.

BACKGROUND: There is a concerning underdiagnosis of testicular and/or epididymal tuberculosis (TB). A lack of clinician awareness has led to many patients undergoing unnecessary surgeries. The purpose of this series was to enhance understanding of testicular and/or epididymal TB based on clinical, ultrasonic, computed tomography (CT), and magnetic resonance imaging (MRI) features from the past decade. METHODS: We retrospectively investigated the medical records of 69 patients diagnosed with testicular and/or epididymal TB from 2008 to 2019. All participants were diagnosed by confirmation of Mycobacterium tuberculosis in the histopathology of resected samples. Baseline characteristics, ultrasonic, CT, and MRI features were collected for analysis. RESULTS: A total of 69 patients with a median age of 43.5 years were included in the study. Testicular-epididymis TB, epididymal TB, and testicular TB were confirmed in 31 (44.9%), 26 (37.7%), and 12 (17.4%) patients, respectively. In sonography, testicular TB and epididymal TB imaging features are significantly different (P<0.001). Diffusely enlarged lesion heterogeneously (33/58, 56.9%) is most common in the epididymis, and miliary type (18/39, 46.2%) is most common in the testis. On enhanced CT, annular or multilocular enhancement pattern (19/21, 90.5%) was the characteristic manifestation of our patients. CONCLUSIONS: Laboratory findings [especially T lymphocyte spot test for tuberculosis infection (T-SPOT.TB)], accompanied by scrotal sonography and enhanced CT examinations, can help distinguish testicular and/or epididymal TB from other etiologies.

Inflammatory Myofibroblastic Tumor of the Urinary System on Computed Tomography at a High-Volume Institution in China.

OBJECTIVE: Inflammatory myofibroblastic tumors (IMTs) of the urinary system are relatively rare and often misdiagnosed. We aimed to summarize and analyze the clinical manifestations, imaging features, management, and follow-up of renal and bladder IMTs. METHODS: In this retrospective study, 22 patients with IMT pathologically verified between 2009 and 2018 were included. Epidemiologic, clinical, pathologic, and imaging findings were recorded. Tumor size, location, and shape were analyzed and summarized. RESULTS: There were 22 patients with a median age of 45 years (range: 20-74), including 14 patients with renal IMT and 8 patients with bladder IMT, who met the eligibility criteria. In 21 patients, IMT appeared as a single lesion, whereas 1 patient showed bilateral renal lesions. Surgical resection was the sole therapy, and follow-up information was acquired from 13 individuals with no evidence of recurrence or metastasis. In our study, a slightly hypodense or isodense homogeneous tumor with a clear boundary was more often seen. On contrast-enhanced computed tomography (CT), they were often manifesting as a slightly heterogeneous enhancement. CONCLUSIONS: The nature of IMTs might cause a lack of generalizability. However, it will be useful to know that there are various CT demonstrations of IMTs. CT images are useful for the detection, location, and characterization of urinary IMTs, which can help in better clinical decision-making and can also be an optimal imaging technique for follow-up.

Quantitative Analysis of Enhancement Intensity and Patterns on Contrast-enhanced Spectral Mammography.

CESM is an emerging digital mammography technology with a high breast cancer detection and a limited diagnostic specificity. In order to improve specificity, we quantitatively assessed enhancement intensity of breast lesions with different pathological types and hormonal receptor status and evaluated the consistency of enhancement patterns between CESM and DCE-MRI. A total of 145 lesions were enrolled, consisting of 43 malignant (17 non-infiltrating cancers and 26 infiltrating cancers) and 99 benign lesions. The diagnostic performance of enhancement intensity in the former positions was significantly higher than that in the latter positions (AUC: 0.834 vs. 0.755, p = 0.0008). Infiltrating cancers showed the highest enhancement intensity, while benign lesions the lowest (mean CNR1: 7.6% vs. 2.7%; median CNR1: 6.8% vs. 2.7%). Enhancement intensity of ER or PR positive group was weaker than negative group, while HER-2 positive group was stronger than negative group. 28 patients with 28 lesions performed both CESM and DCE-MRI examinations, showing a coincidence rate of 64.2% and moderate agreement (k = 0.515) between CESM and DCE-MRI. In conclusion, quantitative analysis of enhancement characteristics is feasible to the diagnosis practice on CESM.