On-Site Computed Tomography-Derived Fractional Flow Reserve to Guide the Management of Patients with Stable Coronary Artery Disease: the TARGET Randomized Trial

Background: Computed tomography-derived fractional flow reserve (CT-FFR) using on-site machine learning enables identification of both the presence of coronary artery disease and vessel-specific ischemia. However, it is unclear whether on-site CT-FFR improves clinical or economic outcomes when compared with the standard of care in patients with stable coronary artery disease. Methods: In total 1,216 patients with stable coronary artery disease and an intermediate stenosis of 30% to 90% on coronary computed tomographic angiography (CCTA) were randomized to an on-site CT-FFR care pathway using machine learning or to standard care in 6 Chinese medical centers. The primary endpoint was the proportion of patients undergoing invasive coronary angiography without obstructive coronary artery disease or with obstructive disease who did not undergo intervention within 90 days. Secondary endpoints included major adverse cardiovascular events (MACE), quality of life, symptoms of angina, and medical expenditure at 1 year. Results: Baseline characteristics were similar in both groups with 72.4% (881/1,216) having either typical or atypical anginal symptoms. A total of 421 of 608 patients (69.2%) in the CT-FFR care group and 483 of 608 patients (79.4%) in the standard care group underwent invasive coronary angiography. Compared to standard care, the proportion of patients undergoing invasive coronary angiography without obstructive coronary artery disease or with obstructive disease not undergoing intervention was significantly reduced in the CT-FFR care group (28.3% [119/421] vs. 46.2% [223/483] P<0.001). Overall more patients underwent revascularization in the CT-FFR care group than in the standard care group (49.7% [302/608] vs. 42.8% [260/608], P=0.02), but of MACE at 1 year did not differ (hazard ratio, 0.88; 95%CI, 0.59 to 1.30). Quality of life and symptoms improved similarly during follow-up in both groups and there was a trend towards lower costs in the CT-FFR care group (difference, -¥4233; 95%CI, -¥8165 to ¥973, P=0.07). Conclusions: On-site CT-FFR using machine learning reduced the proportion of patients with stable coronary artery disease undergoing invasive coronary angiography without obstructive disease or requiring intervention within 90 days, but increased revascularization overall without improving symptoms or quality of life, or reducing major adverse cardiovascular events.

A prospective randomized trial comparing microwave and radiofrequency ablation for the treatment of liver metastases using a dual ablation system ─ The Mira study

Purpose

The aim of this study was to prospectively compare the therapy response and safety of microwave (MWA) and radiofrequency ablation (RFA) for the treatment of liver metastases using a dual ablation system.

Methods

Fifty patients with liver metastases (23 men, mean age: 62.8 ± 11.8 years) were randomly assigned to MWA or RFA for thermal ablation using a one generator dual ablation system. Magnetic resonance imaging (MRI) was acquired before treatment and 24 h post ablation. The morphologic responses to treatment regarding size, volume, necrotic areas, and diffusion characteristics were evaluated by MRI. Imaging follow-up was obtained for one year in three months intervals, whereas clinical follow-up was obtained for two years in all patients.

Results

Twenty-six patients received MWA and 24 patients received RFA (mean diameter: 1.6 cm, MWA: 1.7 cm, RFA: 1.5 cm). The mean volume 24 h after ablation was 37.0 cm³ (MWA: 50.5 cm³, RFA: 22.9 cm³, P < 0.01). The local recurrence rate was 0% (0/26) in the MWA-group and 8.3% (2/24) in the RFA-group (P = 0.09). The rate of newly developed malignant formations was 38.0% (19/50) for both groups (MWA: 38.4%, RFA: 37.5%, P = 0.07). The overall survival rate was 70.0% (35/50) after two years (MWA: 76.9%, RFA: 62.5%, P = 0.60). No major complications were reported.

Conclusion

In conclusion, MWA and RFA are both safe and effective methods for the treatment of liver metastases with MWA generating greater volumes of ablation. No significant differences were found for overall survival, rate of neoplasm, or major complications between both groups.

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A dual ablation system allows for MWA and RFA treatment using the same hardware.

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Both methods are safe and effective for the treatment of liver metastases.

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MWA generates greater volumes of ablation and larger ablative margins compared to RFA.

Prevalence and Associated Risk Factors of Pulmonary Embolism in Children and Young Adults With Nephrotic Syndrome: A Chinese Large Cohort Study

PURPOSE

Nephrotic syndrome (NS) is highly associated with an increased risk of pulmonary embolism (PE) in children and young adults. However, few studies have specified the risk factors of PE in children and young adults with NS. We sought to determine the prevalence and associated factors of PE confirmed with computed tomography pulmonary angiography in Chinese children and young adults with NS.

METHODS

Data from 444 children and young adults with NS who had computed tomography pulmonary angiography from December 2010 to October 2018 were retrospectively analyzed. The prevalence of PE was estimated for different age, sex, and histopathologic types of NS. Multivariable logistic regression was used to identify independent risk factors of PE in children and young adults with NS. Models incorporating the independent risk factors were evaluated using receiver operation characteristic curves. Area under the curve was used to determine the best-performing prognosticators for predicting PE.

RESULTS

There were 444 patients in the study cohort (310 male patients, 134 female patients; mean age 19±3 y; range: 6 to 25 y). PE was present in 24.8% of the participants (110 of 444, 18.2% female). Children and young adult NS patients with PE tend to be older, male, to have a previous thromboembolism history and smoking, and have a higher level of proteinuria, D-dimer, and serum albumin (P<0.05 for all). Children and young adults with membranous nephropathy are likely to have a higher incidence of PE than those with other types of nephropathy. Membranous nephropathy and proteinuria were significant predictors of PE in children and young adults with NS (P<0.05 for all). The area under the curves of each model for the presence of PE in children and young adults with NS based on biochemical parameters and clinical information (model 1), adjusted for proteinuria (model 2), and adjusted for membranous nephropathy (model 3) were 0.578, 0.657, and 0.709, respectively. Compared with model 1, model 2, and model 3 showed statistically significant differences (model 1 vs. model 2, P=0.0336; model 1 vs. model 3, P=0.0268). There was no statistically significant difference between model 2 and model 3 (P=0.2947).

CONCLUSION

This study identified membranous nephropathy and proteinuria as independent associated factors of PE in children and young adults with NS, which can be noted as a risk factor to guide clinician management in this population.

Influence of coronary stenosis location on diagnostic performance of machine learning-based fractional flow reserve from CT angiography

BACKGROUND

Compared with invasive fractional flow reserve (FFR), coronary CT angiography (cCTA) is limited in detecting hemodynamically relevant lesions. cCTA-based FFR (CT-FFR) is an approach to overcome this insufficiency by use of computational fluid dynamics. Applying recent innovations in computer science, a machine learning (ML) method for CT-FFR derivation was introduced and showed improved diagnostic performance compared to cCTA alone. We sought to investigate the influence of stenosis location in the coronary artery system on the performance of ML-CT-FFR in a large, multicenter cohort.

METHODS

Three hundred and thirty patients (75.2% male, median age 63 years) with 502 coronary artery stenoses were included in this substudy of the MACHINE (Machine Learning Based CT Angiography Derived FFR: A Multi-Center Registry) registry. Correlation of ML-CT-FFR with the invasive reference standard FFR was assessed and pooled diagnostic performance of ML-CT-FFR and cCTA was determined separately for the following stenosis locations: RCA, LAD, LCX, proximal, middle, and distal vessel segments.

RESULTS

ML-CT-FFR correlated well with invasive FFR across the different stenosis locations. Per-lesion analysis revealed improved diagnostic accuracy of ML-CT-FFR compared with conventional cCTA for stenoses in the RCA (71.8% [95% confidence interval, 63.0%-79.5%] vs. 54.8% [45.7%-63.8%]), LAD (79.3 [73.9-84.0] vs. 59.6 [53.5-65.6]), LCX (84.1 [76.0-90.3] vs. 63.7 [54.1-72.6]), proximal (81.5 [74.6-87.1] vs. 63.8 [55.9-71.2]), middle (81.2 [75.7-85.9] vs. 59.4 [53.0-65.6]) and distal stenosis location (67.4 [57.0-76.6] vs. 51.6 [41.1-62.0]).

CONCLUSION

In a multicenter cohort with high disease prevalence, ML-CT-FFR offered improved diagnostic performance over cCTA for detecting hemodynamically relevant stenoses regardless of their location.

Machine Learning/Deep Neuronal Network: Routine Application in Chest Computed Tomography and Workflow Considerations

The constantly increasing number of computed tomography (CT) examinations poses major challenges for radiologists. In this article, the additional benefits and potential of an artificial intelligence (AI) analysis platform for chest CT examinations in routine clinical practice will be examined. Specific application examples include AI-based, fully automatic lung segmentation with emphysema quantification, aortic measurements, detection of pulmonary nodules, and bone mineral density measurement. This contribution aims to appraise this AI-based application for value-added diagnosis during routine chest CT examinations and explore future development perspectives.

Different posterior hippocampus and default mode network modulation in young APOE ε4 carriers: a functional connectome-informed phenotype longitudinal study

To determine the functional connectome change pattern based on subregions of the hippocampus in young APOEε4 carriers during a 3-year follow-up. All the participants (n = 213) were tested for resting-state functional MRI, neuropsychological scales, and APOE genotype. The age- and sex-matched APOE ε4/ε3 (23.9 ± 3.2 years old, 6 female/7 male) carriers and APOE ε3/ε3 (22.9 ± 1.6 years old, 7 female/12 male) carriers were finally followed up. The hippocampus and its anterior/middle/posterior subregion-based functional connectivity (FC) patterns were compared between APOEε4 and APOEε3 groups by a two-sample t-test at baseline and mixed-effect analysis at follow-up. The effective connectivity (EC) patterns among the altered regions of interaction effect were examined in the APOEε4 groups. APOEε4 carries displayed saliently enhanced FC in the right anterior/middle hippocampus and core regions of the default mode network (DMN) (P < 0.05 by Gaussian Random Fields (GRF) correction). However, the APOEε4-by-time interaction was evident in the middle/posterior hippocampus with connection to the lateral temporal lobe and anterior cingulate cortex (ACC) (P < 0.05 by GRF correction). Moreover, the APOEε4 group at follow-up showed increased EC separately from both the left middle hippocampus and lateral temporal lobe to the left posterior hippocampus, and its changes of FC/EC significantly correlated with altered memory function. The posterior hippocampus might be especially vulnerable to early modulation in young APOEε4 carriers. Its connection with the lateral temporal lobe, rather than with DMN, might be the early compensative mechanism of memory function regulation influenced by APOE ε4 in the young adults.

A clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images

Intracranial aneurysm is a common life-threatening disease. Computed tomography angiography is recommended as the standard diagnosis tool; yet, interpretation can be time-consuming and challenging. We present a specific deep-learning-based model trained on 1,177 digital subtraction angiography verified bone-removal computed tomography angiography cases. The model has good tolerance to image quality and is tested with different manufacturers. Simulated real-world studies are conducted in consecutive internal and external cohorts, in which it achieves an improved patient-level sensitivity and lesion-level sensitivity compared to that of radiologists and expert neurosurgeons. A specific cohort of suspected acute ischemic stroke is employed and it is found that 99.0% predicted-negative cases can be trusted with high confidence, leading to a potential reduction in human workload. A prospective study is warranted to determine whether the algorithm could improve patients' care in comparison to clinicians' assessment.

Current Status of Etiology, Epidemiology, Clinical Manifestations and Imagings for COVID-19

Coronavirus disease 2019 (COVID-19) is a transmissible respiratory disease that was initially reported in Wuhan, China in December 2019. With the alarming levels of COVID-19 spread worldwide, the World Health Organization characterized COVID-19 as a pandemic. Over the past several months, chest CT has played a vital role in early identification, disease severity assessment, and dynamic disease course monitoring of COVID-19. The published data has enriched our knowledge on the etiology, epidemiology, clinical manifestations, and pathologic findings of COVID-19. Additionally, as the imaging spectrum of the disease continues to be defined, extrapulmonary infections or other complications will require further attention. This review aims to provide an updated framework and essential knowledge with which radiologists can better understand COVID-19.

Artificial Intelligence in the Management of Intracranial Aneurysms: Current Status and Future Perspectives

Intracranial aneurysms with subarachnoid hemorrhage lead to high morbidity and mortality. It is of critical importance to detect aneurysms, identify risk factors of rupture, and predict treatment response of aneurysms to guide clinical interventions. Artificial intelligence has received worldwide attention for its impressive performance in image-based tasks. Artificial intelligence serves as an adjunct to physicians in a series of clinical settings, which substantially improves diagnostic accuracy while reducing physicians' workload. Computer-assisted diagnosis systems of aneurysms based on MRA and CTA using deep learning have been evaluated, and excellent performances have been reported. Artificial intelligence has also been used in automated morphologic calculation, rupture risk stratification, and outcomes prediction with the implementation of machine learning methods, which have exhibited incremental value. This review summarizes current advances of artificial intelligence in the management of aneurysms, including detection and prediction. The challenges and future directions of clinical implementations of artificial intelligence are briefly discussed.

Uric Acid Has Different Effects on Spontaneous Brain Activities of Males and Females: A Cross-Sectional Resting-State Functional MR Imaging Study

Objective

To explore the relationship among serum uric acid (SUA) levels in different states of disease, human cognition, and spontaneous brain activities by resting-state functional MRI (rs-fMRI).

Methods

We prospectively recruited 100 subjects (age 58 ± 11 years, 55 females) who underwent fasting blood sampling, cognitive tests and rs-fMRI scans. The subjects were divided into two groups by sex and each sex group was further stratified into three subgroups according to SUA level in different states of disease. The amplitude of low-frequency fluctuation (ALFF) method was applied to assess spontaneous brain activity among groups. Pearson’s correlation analysis was used to investigate the relationships between the mean ALFF values (mALFF) and cognitive tests.

Results

A total of 97 patients completed the study protocol successfully. Significant differences in age, education level, number connection test (NCT), and word fluency were observed among the three subgroups in males (all P < 0.05). Results of group-by-sex interaction were distributed in bilateral pallidum and putamen [voxel P-value < 0.001, cluster P-value < 0.05, Gaussian random field (GRF)-corrected]. The tendency of the SUA effect on mALFF was different in males and females, particularly in corresponding High SUA subgroups (that is pre-hyperuricemia, both P < 0.001). Among the male subjects, mALFF values of the bilateral pallidum and putamen negatively correlated with attention/executive function.

Conclusion

Our results suggest that elevated SUA levels have different effects on spontaneous brain activities and cognitive function in males and females. Males with pre-hyperuricemia and hyperuricemia are more susceptible to changes in spontaneous brain activities and lower neuropsychological assessment scores, particularly in word fluency tests and NCT, compared to females.

Coronary CT angiography-derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia

OBJECTIVES

We sought to investigate the diagnostic performance of coronary CT angiography (cCTA)-derived plaque markers combined with deep machine learning-based fractional flow reserve (CT-FFR) to identify lesion-specific ischemia using invasive FFR as the reference standard.

METHODS

Eighty-four patients (61 ± 10 years, 65% male) who had undergone cCTA followed by invasive FFR were included in this single-center retrospective, IRB-approved, HIPAA-compliant study. Various plaque markers were derived from cCTA using a semi-automatic software prototype and deep machine learning-based CT-FFR. The discriminatory value of plaque markers and CT-FFR to identify lesion-specific ischemia on a per-vessel basis was evaluated using invasive FFR as the reference standard.

RESULTS

One hundred three lesion-containing vessels were investigated. 32/103 lesions were hemodynamically significant by invasive FFR. In a multivariate analysis (adjusted for Framingham risk score), the following markers showed predictive value for lesion-specific ischemia (odds ratio [OR]): lesion length (OR 1.15, p = 0.037), non-calcified plaque volume (OR 1.02, p = 0.007), napkin-ring sign (OR 5.97, p = 0.014), and CT-FFR (OR 0.81, p < 0.0001). A receiver operating characteristics analysis showed the benefit of identifying plaque markers over cCTA stenosis grading alone, with AUCs increasing from 0.61 with ≥ 50% stenosis to 0.83 with addition of plaque markers to detect lesion-specific ischemia. Further incremental benefit was realized with the addition of CT-FFR (AUC 0.93).

CONCLUSION

Coronary CTA-derived plaque markers portend predictive value to identify lesion-specific ischemia when compared to cCTA stenosis grading alone. The addition of CT-FFR to plaque markers shows incremental discriminatory power.

KEY POINTS

• Coronary CT angiography (cCTA)-derived quantitative plaque markers of atherosclerosis portend high discriminatory power to identify lesion-specific ischemia. • Coronary CT angiography-derived fractional flow reserve (CT-FFR) shows superior diagnostic performance over cCTA alone in detecting lesion-specific ischemia. • A combination of plaque markers with CT-FFR provides incremental discriminatory value for detecting flow-limiting stenosis.

Dual-energy CT-based iodine quantification to differentiate abdominal malignant lymphoma from lymph node metastasis

PURPOSE

To investigate the value of dual-energy computed tomography (DECT)-derived iodine and fat quantification in differentiating malignant abdominal lymphoma from lymph node metastasis.

MATERIALS AND METHODS

In this retrospective study, 59 patients (39 men; mean age, 62.7 years) with histopathologically-confirmed diagnosis of either malignant lymphoma or lymph node metastasis were included. For each lesion, contrast-enhanced attenuation, as well as DECT-derived iodine density and fat fraction measurements were recorded. Mean attenuation and material density values were compared between malignant lymphomas and lymph node metastases. The receiver operating characteristic (ROC) curve analysis was adopted to estimate the optimal threshold for discriminating between both entities. A control group (n = 60) was analyzed for comparison of attenuation and material density values of normal abdominal lymph nodes.

RESULTS

Assessment of DECT-derived iodine density and fat fraction values revealed significant differences between lymph node metastases (1.7 ± 0.4 mg/ml and 15.5 ± 7.3%) and malignant lymphomas (2.5 ± 0.5 mg/ml and 26.7 ± 12.2%) as well as normal lymph nodes (2.4 ± 0.8 mg/ml and 24.1 ± 10.8%) (P ≤ 0.013). An iodine concentration of 2.0 mg/ml represented the optimal threshold to discriminate between lymphoma and lymph node metastasis (sensitivity, 87%; specificity, 89%). Moreover, a significant correlation was found between iodine concentration and fat fraction for both lymphomas and lymph node metastases (P = 0.001).

CONCLUSION

DECT enables characterization of abdominal masses as derived iodine and fat fraction values differ significantly between malignant abdominal lymphomas and lymph node metastases.