Assessing the Impact of an Artificial Intelligence-Based Model for Intracranial Aneurysm Detection in CT Angiography on Patient Diagnosis and Outcomes (IDEAL Study)-a protocol for a multicenter, double-blinded randomized controlled trial.

BACKGROUND: This multicenter, double-blinded, randomized controlled trial (RCT) aims to assess the impact of an artificial intelligence (AI)-based model on the efficacy of intracranial aneurysm detection in CT angiography (CTA) and its influence on patients' short-term and long-term outcomes. METHODS: Study design: Prospective, multicenter, double-blinded RCT. SETTINGS: The model was designed for the automatic detection of intracranial aneurysms from original CTA images. PARTICIPANTS: Adult inpatients and outpatients who are scheduled for head CTA scanning. Randomization groups: (1) Experimental Group: Head CTA interpreted by radiologists with the assistance of the True-AI-integrated intracranial aneurysm diagnosis strategy (True-AI arm). (2) Control Group: Head CTA interpreted by radiologists with the assistance of the Sham-AI-integrated intracranial aneurysm diagnosis strategy (Sham-AI arm). RANDOMIZATION: Block randomization, stratified by center, gender, and age group. PRIMARY OUTCOMES: Coprimary outcomes of superiority in patient-level sensitivity and noninferiority in specificity for the True-AI arm to the Sham-AI arm in intracranial aneurysms. SECONDARY OUTCOMES: Diagnostic performance for other intracranial lesions, detection rates, workload of CTA interpretation, resource utilization, treatment-related clinical events, aneurysm-related events, quality of life, and cost-effectiveness analysis. BLINDING: Study participants and participating radiologists will be blinded to the intervention. SAMPLE SIZE: Based on our pilot study, the patient-level sensitivity is assumed to be 0.65 for the Sham-AI arm and 0.75 for the True-AI arm, with specificities of 0.90 and 0.88, respectively. The prevalence of intracranial aneurysms for patients undergoing head CTA in the hospital is approximately 12%. To establish superiority in sensitivity and noninferiority in specificity with a margin of 5% using a one-sided α = 0.025 to ensure that the power of coprimary endpoint testing reached 0.80 and a 5% attrition rate, the sample size was determined to be 6450 in a 1:1 allocation to True-AI or Sham-AI arm. DISCUSSION: The study will determine the precise impact of the AI system on the detection performance for intracranial aneurysms in a double-blinded design and following the real-world effects on patients' short-term and long-term outcomes. TRIAL REGISTRATION: This trial has been registered with the NIH, U.S. National Library of Medicine at ClinicalTrials.gov, ID: NCT06118840 . Registered 11 November 2023.

Inflammatory risk and cardiovascular events in patients without obstructive coronary artery disease: the ORFAN multicentre, longitudinal cohort study.

BACKGROUND: Coronary computed tomography angiography (CCTA) is the first line investigation for chest pain, and it is used to guide revascularisation. However, the widespread adoption of CCTA has revealed a large group of individuals without obstructive coronary artery disease (CAD), with unclear prognosis and management. Measurement of coronary inflammation from CCTA using the perivascular fat attenuation index (FAI) Score could enable cardiovascular risk prediction and guide the management of individuals without obstructive CAD. The Oxford Risk Factors And Non-invasive imaging (ORFAN) study aimed to evaluate the risk profile and event rates among patients undergoing CCTA as part of routine clinical care in the UK National Health Service (NHS); to test the hypothesis that coronary arterial inflammation drives cardiac mortality or major adverse cardiac events (MACE) in patients with or without CAD; and to externally validate the performance of the previously trained artificial intelligence (AI)-Risk prognostic algorithm and the related AI-Risk classification system in a UK population. METHODS: This multicentre, longitudinal cohort study included 40 091 consecutive patients undergoing clinically indicated CCTA in eight UK hospitals, who were followed up for MACE (ie, myocardial infarction, new onset heart failure, or cardiac death) for a median of 2·7 years (IQR 1·4-5·3). The prognostic value of FAI Score in the presence and absence of obstructive CAD was evaluated in 3393 consecutive patients from the two hospitals with the longest follow-up (7·7 years [6·4-9·1]). An AI-enhanced cardiac risk prediction algorithm, which integrates FAI Score, coronary plaque metrics, and clinical risk factors, was then evaluated in this population. FINDINGS: In the 2·7 year median follow-up period, patients without obstructive CAD (32 533 [81·1%] of 40 091) accounted for 2857 (66·3%) of the 4307 total MACE and 1118 (63·7%) of the 1754 total cardiac deaths in the whole of Cohort A. Increased FAI Score in all the three coronary arteries had an additive impact on the risk for cardiac mortality (hazard ratio [HR] 29·8 [95% CI 13·9-63·9], p<0·001) or MACE (12·6 [8·5-18·6], p<0·001) comparing three vessels with an FAI Score in the top versus bottom quartile for each artery. FAI Score in any coronary artery predicted cardiac mortality and MACE independently from cardiovascular risk factors and the presence or extent of CAD. The AI-Risk classification was positively associated with cardiac mortality (6·75 [5·17-8·82], p<0·001, for very high risk vs low or medium risk) and MACE (4·68 [3·93-5·57], p<0·001 for very high risk vs low or medium risk). Finally, the AI-Risk model was well calibrated against true events. INTERPRETATION: The FAI Score captures inflammatory risk beyond the current clinical risk stratification and CCTA interpretation, particularly among patients without obstructive CAD. The AI-Risk integrates this information in a prognostic algorithm, which could be used as an alternative to traditional risk factor-based risk calculators. FUNDING: British Heart Foundation, NHS-AI award, Innovate UK, National Institute for Health and Care Research, and the Oxford Biomedical Research Centre.

Utility of Dual-Energy Computed Tomography in lesion characterization and treatment planning for peripheral Chronic Total Occlusions: A comprehensive analysis of crossing difficulty.

PURPOSE: To investigate whether Dual-Energy Computed Tomography (DECT) could be useful in the lesion characterization and endovascular treatment planning of symptomatic patients with peripheral arterial disease (PAD) due to Chronic Total Occlusions (CTO). MATERIALS AND METHODS: Between 2018 and 2022, 60 symptomatic patients (52 male, age 71 years) with peripheral arterial CTO underwent DECT angiography before percutaneous endovascular treatment. Patients were classified, according to guidewire crossing difficulty into four categories, which were subsequently correlated with DECT values, including Dual Energy Index (DEI) and Effective Z (Zeff). DECT values were also corelated with crossing time. The crossing difficulty was further correlated with the Trans-Atlantic Inter-Society Consensus Document (TASC II) classification. RESULTS: Technical success, defined as perceived antegrade true lumen or subintimal crossing, was achieved in 76.7 %. Among the cases, 20 were deemed easy, 14 moderate, 12 hard and 14 were failed attempts. Statistical analysis revealed a significant correlation between DEI, Zeff values, and the crossing difficulty categories (p < 0.001). Additionally, there was also a correlation between crossing time and DECT values. However, no significant correlation was recorded between difficulty categories and TASC II classification. CONCLUSION: Pre-procedural DECT angiography provides valuable information for patient selection and planning of the revascularization strategy. Moreover, it is helpful in the selection of the appropriate PTA materials, based on the lesion characteristics. Further research should be invested in this important field, to determine the optimal treatment approach in patients suffering from PAD due to CTOs.

Novel motion correction algorithm improves diagnostic performance of CT fractional flow reserve.

OBJECTIVES: This study aimed to investigate the diagnostic performance of computed tomography (CT) fractional flow reserve (CT-FFR) derived from standard images (STD) and images processed via first-generation (SnapShot Freeze, SSF1) and second-generation (SnapShot Freeze 2, SSF2) motion correction algorithms. METHODS: 151 patients who underwent coronary CT angiography (CCTA) and invasive coronary angiography (ICA)/FFR within 3 months were retrospectively included. CCTA images were reconstructed using an iterative reconstruction technique and then further processed through SSF1 and SSF2 algorithms. All images were divided into three groups: STD, SSF1, and SSF2. Obstructive stenosis was defined as a diameter stenosis of ≥ 50 % in the left main artery or ≥ 70 % in other epicardial vessels. Stenosis with an FFR of ≤ 0.8 or a diameter stenosis of ≥ 90 % (as revealed via ICA) was considered ischemic. In patients with multiple lesions, the lesion with lowest CT-FFR was used for patient-level analysis. RESULTS: The overall quality score in SSF2 group (median = 3.67) was markedly higher than that in STD (median = 3) and SSF1 (median = 3) groups (P < 0.001). The best correlation (r = 0.652, P < 0.001) and consistency (mean difference = 0.04) between the CT-FFR and FFR values were observed in the SSF2 group. At the per-lesion level, CT-FFRSSF2 outperformed CT-FFRSSF1 in diagnosing ischemic lesions (area under the curve = 0.887 vs. 0.795, P < 0.001). At the per-patient level, the SSF2 group also demonstrated the highest diagnostic performance. CONCLUSION: The SSF2 algorithm significantly improved CCTA image quality and enhanced its diagnostic performance for evaluating stenosis severity and CT-FFR calculations.

Radiomics analysis of lesion-specific pericoronary adipose tissue to predict major adverse cardiovascular events in coronary artery disease.

OBJECTIVE: To investigate the prognostic performance of radiomics analysis of lesion-specific pericoronary adipose tissue (PCAT) for major adverse cardiovascular events (MACE) with the guidance of CT derived fractional flow reserve (CT-FFR) in coronary artery disease (CAD). MATERIALS AND METHODS: The study retrospectively analyzed 608 CAD patients who underwent coronary CT angiography. Lesion-specific PCAT was determined by the lowest CT-FFR value and 1691 radiomic features were extracted. MACE included cardiovascular death, nonfatal myocardial infarction, unplanned revascularization and hospitalization for unstable angina. Four models were generated, incorporating traditional risk factors (clinical model), radiomics score (Rad-score, radiomics model), traditional risk factors and Rad-score (clinical radiomics model) and all together (combined model). The model performances were evaluated and compared with Harrell concordance index (C-index), area under curve (AUC) of the receiver operator characteristic. RESULTS: Lesion-specific Rad-score was associated with MACE (adjusted HR = 1.330, p = 0.009). The combined model yielded the highest C-index of 0.718, which was higher than clinical model (C-index = 0.639), radiomics model (C-index = 0.653) and clinical radiomics model (C-index = 0.698) (all p < 0.05). The clinical radiomics model had significant higher C-index than clinical model (p = 0.030). There were no significant differences in C-index between clinical or clinical radiomics model and radiomics model (p values were 0.796 and 0.147 respectively). The AUC increased from 0.674 for clinical model to 0.721 for radiomics model, 0.759 for clinical radiomics model and 0.773 for combined model. CONCLUSION: Radiomics analysis of lesion-specific PCAT is useful in predicting MACE. Combination of lesion-specific Rad-score and CT-FFR shows incremental value over traditional risk factors.

Generalized Arterial Calcification of Infancy Mimicking Coarctation of Aorta in a Neonate.

Generalized arterial calcification of infancy (GACI) is a rare genetic condition with varied clinical presentation. Consequently, diagnosis is frequently delayed or missed. GACI has a poor prognosis, with more than half of patients dying before the age of 6 months. Early diagnosis and treatment with bisphosphonates have been shown to improve survival in these patients. This is a case report of a newborn with respiratory distress who was initially diagnosed with coarctation of the aorta at echocardiography. Further imaging with CT revealed the aortic narrowing to be associated with GACI. Keywords: Genetic Defects, Congenital, Vascular, Calcification/Calculi, Aorta, Pulmonary Arteries, CT Angiography, Echocardiography, Pediatrics © RSNA, 2024.

A case of right aortic arch type II combined with Kommerell's diverticulum and left innominate vein beneath the aortic arch.

The combination of the right aortic arch and aberrant left subclavian artery (ALSA) with Kommerell's diverticulum (KD) is rare to coexist with the left innominate vein (LINV) beneath the aortic arch. It escalates the surgical risk undoubtedly and increases the difficulty of clinical procedures. We report one case diagnosed by Ultrasound and Computed Tomography Angiography (CTA).

Delayed femoral artery injury caused by heterotopic ossification: a rare case report and review of the literature.

BACKGROUND: Arterial injury caused by heterotopic ossification (HO) following fractures is rarely reported, yet it can have catastrophic consequences. This case report presents a unique instance of femoral artery injury and hematoma organization, occurring a decade after intramedullary nail fixation for a femoral shaft fracture complicated by HO. CASE PRESENTATION: A 56-year-old male presented with right femoral artery injury and organized hematoma, a decade after suffering bilateral femoral shaft fractures with mild head injury in a traffic accident. He had received intramedullary nailing for the right femoral shaft fracture and plate fixation for the left side in a local hospital. Physical examination revealed two firm, palpable masses with clear boundaries, limited mobility, and no tenderness. Peripheral arterial pulses were intact. Radiography demonstrated satisfactory fracture healing, while a continuous high-density shadow was evident along the inner and posterior aspect of the right thigh. Computed tomography angiography identified a large mixed-density mass (16.8 × 14.8 × 20.7 cm) on the right thigh's medial side, featuring central calcification and multiple internal calcifications. The right deep femoral artery coursed within this mass, with a smaller lesion noted on the posterior thigh. Surgical consultation with a vascular surgeon led to planned intervention. The smaller mass was completely excised, but the larger one partially, as it encased the femoral artery. The inability to remove all HO was due to excessive bleeding. Postoperatively, the patient experienced no complications, and one-year follow-up revealed a favorable recovery with restoration of full right lower limb mobility. CONCLUSION: This case underscores the potential gravity of vascular injury associated with heterotopic ossification. Surgeons should remain vigilant regarding the risk of vascular injury during HO excision.

A single-center experience of type B aortic intramural hematoma.

OBJECTIVE: The outcomes of the best medical treatment (BMT) and intervention treatment (INT) in a single-center experience were reported in type B intramural hematoma (IMH). METHODS: From February 2015 to February 2021, a total of 195 consecutive patients with type B IMH were enrolled in the study. The primary end point was mortality, and the secondary end points included clinical and imaging outcomes. The clinical outcomes were aortic-related death, retrograde type A aortic dissection, stent graft-induced new entry tear, endoleak, and reintervention. The imaging outcome was evaluated through the latest follow-up computed tomography angiography, which included aortic rupture, aortic dissection, aortic aneurysm, rapid growth of aortic diameter, newly developed or enlarged penetrating aortic ulcer or ulcer-like projection (ULP) and increased aortic wall thickness. Kaplan-Meier curves were used to assess the association between different treatments. RESULTS: Among the enrolled patients, 115 received BMT, and 80 received INT. There was no significant difference in early (1.7% vs 2.5%; P = 1.00) and midterm all-cause death (8.3% vs 5.2%; P = .42) between the BMT and INT groups. However, patients who underwent INT were at risk of procedure-related complications such as stent graft-induced new entry tear and endoleaks. The INT group was associated with a profound decrease in the risk of ULP, including newly developed ULP (4.3% vs 26.9%; P < .05), ULP enlargement (6.4% vs 31.3%; P < .05), and a lower proportion of high-risk ULP (10.9% vs 45.6%; P < .05). Although there was no significant difference in the incidence of IMH regression between the two groups, the maximum diameter of the descending aorta in patients receiving INT was larger compared with those treated with BMT. CONCLUSIONS: Based on our limited experience, patients with type B IMH treated with BMT or INT shared similar midterm clinical outcome. Patients who underwent INT may have a decreased risk of ULPs, but a higher risk of procedure-related events and patients on BMT should be closely monitored for ULP progression.

Diagnostic value of multimodal cardiovascular imaging technology coupled with biomarker detection in elderly patients with coronary heart disease.

Aims/Background Coronary heart disease is a common disease in the elderly and has a complex pathogenesis, which complicates the clinical diagnostic process. Thus, enhancing the diagnostic efficiency for coronary heart disease is imperative to improve the life expectancy of the elderly. This study aimed to explore the diagnostic value of multimodal cardiovascular imaging technology coupled with biomarker detection in elderly patients with coronary heart disease. Methods The medical records of 421 patients with suspected coronary heart disease obtained from the geriatric department of the First Affiliated Hospital of Hebei North University from February 2020 to February 2023 were retrospectively analysed. After excluding 10 patients who did not meet the inclusion criteria, the remaining 411 patients were included in this study. The included subjects had undergone coronary computed tomography angiography and were divided into coronary heart disease group (n=208) and non-coronary heart disease group (n=203) according to the diagnostic results. Multimodal cardiovascular imaging (coronary computed tomography angiography and echocardiography) and detection of serum biomarkers such as small dense low-density lipoprotein, lipoprotein a, and gamma-glutamyl transferase were performed in both groups. The clinical indicators of the two groups were compared, and the combined diagnostic efficacy of multimodal cardiovascular imaging and biomarker detection was evaluated. Results Compared to the non-coronary heart disease group, the coronary heart disease group had significantly higher levels of maximum area stenosis, total plaque volume, total plaque burden and fibrotic plaque volume (p < ..001), and lower left ventricular ejection fraction level (p < ..001). Additionally, the coronary heart disease group exhibited higher levels of left ventricular end-diastolic volume, left ventricular end-systolic volume and stroke volume than the non-coronary heart disease group (p < ..001), and had higher levels of small dense low-density lipoprotein, lipoprotein a and gamma-glutamyl transferase (p < ..001). Our results demonstrated that combined diagnosis had better diagnostic efficacy than individual approaches, marked by higher area under the curve and sensitivity of the former (p < ..001). Conclusion Multimodal cardiovascular imaging technology combined with biomarker detection can distinctly improve the accuracy of coronary heart disease diagnosis in elderly patients.

Echocardiography of persistent fifth aortic arch confirmed by computed tomography angiography or surgery in children: a case series.

BACKGROUND: The purpose of this study was to review echocardiography-based diagnosis of persistent fifth aortic arch (PFAA) in children. METHODS: From January 2015 to December 2022, we retrospectively analyzed the echocardiographic findings and the relevant clinical data during follow-up of patients with PFAA who were treated in the Third Affiliated Hospital of Zhengzhou University. The diagnosis was confirmed by computed tomography angiography or surgery. RESULTS: Seven PFAA cases included two Weinberg type A and five Weinberg type B. The anatomical details of PFAA were assessed using a combination of the long-axis view of the left ventricular outflow tract (from the left high parasternal window) and the long-axis view of the aortic arch (from the suprasternal window). In Weinberg type A, the distal fifth and fourth aortic arches were connected to the descending aorta, which was associated with aortic coarctation. In Weinberg type B, the upper arch of the fourth aorta was interrupted, and only the lower arch of the fifth aorta was connected to the descending aorta. Surgical repair of PFAA was indicated in five patients with blood flow disruption, among which four had good postoperative results and one refused surgery. Two patients with unobstructed PFAA blood flow required follow-up rather than surgery. CONCLUSIONS: It is feasible to diagnose PFAA by echocardiography. Combined application of the high parasternal left ventricular outflow tract view and the suprasternal aortic arch view can improve timely detection of different types of PFAA in children.

Establishing the distribution of cerebrovascular resistance using computational fluid dynamics and 4D flow MRI.

Cerebrovascular resistance (CVR) regulates blood flow in the brain, but little is known about the vascular resistances of the individual cerebral territories. We present a method to calculate these resistances and investigate how CVR varies in the hemodynamically disturbed brain. We included 48 patients with stroke/TIA (29 with symptomatic carotid stenosis). By combining flow rate (4D flow MRI) and structural computed tomography angiography (CTA) data with computational fluid dynamics (CFD) we computed the perfusion pressures out from the circle of Willis, with which CVR of the MCA, ACA, and PCA territories was estimated. 56 controls were included for comparison of total CVR (tCVR). CVR were 33.8 ± 10.5, 59.0 ± 30.6, and 77.8 ± 21.3 mmHg s/ml for the MCA, ACA, and PCA territories. We found no differences in tCVR between patients, 9.3 ± 1.9 mmHg s/ml, and controls, 9.3 ± 2.0 mmHg s/ml (p = 0.88), nor in territorial CVR in the carotid stenosis patients between ipsilateral and contralateral hemispheres. Territorial resistance associated inversely to territorial brain volume (p < 0.001). These resistances may work as reference values when modelling blood flow in the circle of Willis, and the method can be used when there is need for subject-specific analysis.

Mid-aortic syndrome presented as dilated cardiomyopathy.

Mid-aortic syndrome (MAS) is a rare vascular disease that usually leads to renovascular hypertension. With the predominant manifestations being intractable arterial hypertension and lower extremity arterial insufficiency, it has rarely been associated with dilated cardiomyopathy. We report a young girl with congestive heart failure, where the cause was initially attributed to dilated cardiomyopathy. A repeated echocardiogram 6 months later brought the physician's suspicion of MAS because of the abnormal colour of Doppler from the subcostal view. Further assessment using CT angiography revealed discrete thoracic coarctation at the level of T10, with the narrowest diameter of 2.1 mm, thus confirming the diagnosis. Her inflammatory markers and connective tissue screening were negative. She underwent successful stenting of coarctation of the aorta, which later caused improvement in her cardiac function. We highlighted the importance of looking for treatable causes of dilated cardiomyopathy and vigilant clinical and echocardiogram assessment with high suspicion to diagnose MAS.

Brachial plexopathy as a complication of axillary artery aneurysm in a case of Takayasu arteritis.

Takayasu arteritis is an inflammatory disease of unknown aetiology affecting large vessels. Medium vessel involvement is also well documented; however, neuropathy as a presenting manifestation is rare. In this case report, a young woman in her 20s presented with an 8-month history of intermittent claudication in the right upper limb progressing to rest pain with allodynia in C5-C8 distribution and painless right axillary mass. On examination, she had absent pulses in the right radial, brachial and subclavian artery with audible bruit in the right subclavian and abdominal aorta. CT angiogram showed features suggestive of Takayasu arteritis with a partially thrombosed aneurysm arising from the right axillary artery leading to compression of the right brachial plexus. This patient received treatment with methotrexate and oral corticosteroids. At 3 months follow-up, there was a reduction in the size of the aneurysm, resolution of compressive symptoms and normalisation of inflammatory markers.

The Plaque Analysis Classifies the Coronary Artery Disease-Reporting and Data System (CAD-RADS) Stenosis and Plaque Burden Categories: Association of the Plaque Features, Fat Attenuation Index, Coronary Computed Tomography Fractional Flow Reserve, and the Combination of Stenosis and Calcification.

BACKGROUND: The coronary artery disease-reporting and data system (CAD-RADS) 2.0 is used to standardize the reporting of coronary computed tomography angiography (CCTA) results. Artificial intelligence software can quantify the plaque composition, fat attenuation index, and fractional flow reserve. OBJECTIVE: To analyze plaque features of varying severity in patients with a combination of CAD-RADS stenosis and plaque burden categorization and establish a random forest classification model. METHODS: The data of 100 patients treated between April 2021 and February 2022 were retrospectively collected. The most severe plaque observed in each patient was the target lesion. Patients were categorized into three groups according to CAD-RADS: CAD-RADS 1-2 + P0-2, CAD-RADS 3-4B + P0-2, and CAD-RADS 3-4B + P3-4. Differences and correlations between variables were assessed between groups. AUC, accuracy, precision, recall, and F1 score were used to evaluate the diagnostic performance. RESULTS: A total of 100 patients and 178 arteries were included. The differences of computed tomography fractional flow reserve (CT-FFR) (H = 23.921, p < 0.001), the volume of lipid component (H = 12.996, p = 0.002), the volume of fibro-lipid component (H = 8.692, p = 0.013), the proportion of lipid component volume (H = 22.038, p < 0.001), the proportion of fibro-lipid component volume (H = 11.731, p = 0.003), the proportion of calcification component volume (H = 11.049, p = 0.004), and plaque type (χ2 = 18.110, p = 0.001) was statistically significant. CONCLUSION: CT-FFR, volume and proportion of lipid and fibro-lipid components of plaques, the proportion of calcified components, and plaque type were valuable for CAD-RADS stenosis + plaque burden classification, especially CT-FFR, volume, and proportion of lipid and fibro-lipid components. The model built using the random forest was better than the clinical model (AUC: 0.874 vs. 0.647).

Machine Learning Detects Symptomatic Plaques in Patients With Carotid Atherosclerosis on CT Angiography.

BACKGROUND: This study aimed to develop and validate a computed tomography angiography based machine learning model that uses plaque composition data and degree of carotid stenosis to detect symptomatic carotid plaques in patients with carotid atherosclerosis. METHODS: The machine learning based model was trained using degree of stenosis and the volumes of 13 computed tomography angiography derived intracarotid plaque subcomponents (eg, lipid, intraplaque hemorrhage, calcium) to identify plaques associated with cerebrovascular events. The model was internally validated through repeated 10-fold cross-validation and tested on a dedicated testing cohort according to discrimination and calibration. RESULTS: This retrospective, single-center study evaluated computed tomography angiography scans of 268 patients with both symptomatic and asymptomatic carotid atherosclerosis (163 for the derivation set and 106 for the testing set) performed between March 2013 and October 2019. The area-under-receiver-operating characteristics curve by machine learning on the testing cohort (0.89) was significantly higher than the areas under the curve of traditional logit analysis based on the degree of stenosis (0.51, P<0.001), presence of intraplaque hemorrhage (0.69, P<0.001), and plaque composition (0.78, P<0.001), respectively. Comparable performance was obtained on internal validation. The identified plaque components and associated cutoff values that were significantly associated with a higher likelihood of symptomatic status after adjustment were the ratio of intraplaque hemorrhage to lipid volume (≥50%, 38.5 [10.1-205.1]; odds ratio, 95% CI) and percentage of intraplaque hemorrhage volume (≥10%, 18.5 [5.7-69.4]; odds ratio, 95% CI). CONCLUSIONS: This study presented an interpretable machine learning model that accurately identifies symptomatic carotid plaques using computed tomography angiography derived plaque composition features, aiding clinical decision-making.

Spontaneous hepatic artery pseudoaneurysm rupture as a first presentation of polyarteritis nodosa.

A man in his 70s presented with a sudden onset stabbing back pain radiating to the chest and pre-syncopal symptoms. He underwent urgent investigations, including a CT angiogram aorta which did not reveal any abnormalities within the thorax, abdomen or pelvis and no cause of symptoms was identified. After being discharged, he re-presented 2 days later with syncopal episodes, abdominal pain and a significant drop in haemoglobin levels. This time, a CT mesenteric angiogram showed two hepatic artery pseudoaneurysms and a large haemoperitoneum. Following a hepatic artery embolisation, a workup showed that the likely cause of the pseudoaneurysms was a rare first presentation of polyarteritis nodosa. This case highlights the importance of considering the possibility of an aneurysmal rupture, especially when common causes of an acute abdomen have been excluded, and not relying on previous negative investigations to exclude pathology, as the outcomes can be detrimental.

Radiomics of pericoronary adipose tissue on computed tomography angiography predicts coronary heart disease in patients with type 2 diabetes mellitus.

BACKGROUND: Diabetes is a common chronic metabolic disease. The progression of the disease promotes vascular inflammation and the formation of atherosclerosis, leading to cardiovascular disease. The coronary artery perivascular adipose tissue attenuation index based on CCTA is a new noninvasive imaging biomarker that reflects the spatial changes in perivascular adipose tissue attenuation in CCTA images and the inflammation around the coronary arteries. In this study, a radiomics approach is proposed to extract a large number of image features from CCTA in a high-throughput manner and combined with clinical diagnostic data to explore the predictive ability of vascular perivascular adipose imaging data based on CCTA for coronary heart disease in diabetic patients. METHODS: R language was used for statistical analysis to screen the variables with significant differences. A presegmentation model was used for CCTA vessel segmentation, and the pericoronary adipose region was screened out. PyRadiomics was used to calculate the radiomics features of pericoronary adipose tissue, and SVM, DT and RF were used to model and analyze the clinical data and radiomics data. Model performance was evaluated using indicators such as PPV, FPR, AAC, and ROC. RESULTS: The results indicate that there are significant differences in age, blood pressure, and some biochemical indicators between diabetes patients with and without coronary heart disease. Among 1037 calculated radiomic parameters, 18.3% showed significant differences in imaging omics features. Three modeling methods were used to analyze different combinations of clinical information, internal vascular radiomics information and pericoronary vascular fat radiomics information. The results showed that the dataset of full data had the highest ACC values under different machine learning models. The support vector machine method showed the best specificity, sensitivity, and accuracy for this dataset. CONCLUSIONS: In this study, the clinical data and pericoronary radiomics data of CCTA were fused to predict the occurrence of coronary heart disease in diabetic patients. This provides information for the early detection of coronary heart disease in patients with diabetes and allows for timely intervention and treatment.