Detection and Monitoring of Interstitial Lung Disease in Patients with Systemic Sclerosis.

PURPOSE OF REVIEW: Interstitial lung disease (ILD) is a common manifestation of systemic sclerosis (SSc). We explore the importance of early detection, monitoring, and management of SSc-ILD. RECENT FINDINGS: All patients with SSc are at risk of ILD and should be screened for ILD at diagnosis using a high-resolution computed tomography (HRCT) scan. Some patients with SSc-ILD develop a progressive phenotype characterized by worsening fibrosis on HRCT, decline in lung function, and early mortality. To evaluate progression and inform treatment decisions, regular monitoring is important and should include pulmonary function testing, evaluation of symptoms and quality of life, and, where indicated, repeat HRCT. Multidisciplinary discussion enables comprehensive evaluation of the available information and its implications for management. The first-line treatment for SSc-ILD is usually immunosuppression. The antifibrotic drug nintedanib has been approved for slowing lung function decline in patients with SSc-ILD. Optimal management of patients with SSc-ILD requires a multidisciplinary and patient-centered approach.

Robot-assisted Thoracoscopic Lobectomy of T4 Lung Cancer.

A 79-year-old male former smoker presented with a T4 (>7 cm) adenocarcinoma of the right upper lobe. The patient was staged at clinical T4N0M0 and underwent robot-assisted right upper lobectomy and mediastinal lymph node dissection. The patient was discharged home on postoperative day 3. Larger tumors are a relative contraindication for video-assisted thoracoscopic surgical lobectomy. The robot platform overcomes the technical limitations of video-assisted thoracoscopic surgery and allows for the successful resection of large tumors.

Pulmonary CTA Reporting: AJR Expert Panel Narrative Review.

Pulmonary CTA is a ubiquitous study interpreted by radiologists with different levels of experience in a variety of practice settings. Pulmonary embolism (PE) can range from an incidental and clinically insignificant finding to a clinically significant thrombus that can be managed on an outpatient basis to a potentially fatal condition requiring immediate medical or invasive management. Accordingly, a clear and concise pulmonary CTA report should effectively communicate the most pertinent findings to help the treating medical team diagnose or exclude PE and provide information to guide appropriate management. In this Expert Panel Narrative Review, we discuss the purpose of the radiology report for pulmonary CTA, the optimal report format, and the relevant findings that need to be addressed and their clinical significance.

Predictive Value of Cardiac CTA, Cardiac MRI, and Transthoracic Echocardiography for Cardioembolic Stroke Recurrence.

BACKGROUND. Transthoracic echocardiography (TTE) is the standard of care for initial evaluation of patients with suspected cardioembolic stroke. Although TTE is useful for assessing certain sources of cardiac emboli, its diagnostic capability is limited in the detection of other sources, including left atrial thrombus and aortic plaques. OBJECTIVE. The purpose of this article was to investigate sensitivity, specificity, and predictive value of cardiac CTA (CCTA), cardiac MRI (CMRI), and TTE for recurrence in patients with suspected cardioembolic stroke. METHODS. We retrospectively included 151 patients with suspected cardioembolic stroke who underwent TTE and either CMRI (n = 75) or CCTA (n = 76) between January 2013 and May 2017. We evaluated for the presence of left atrial thrombus, left ventricular thrombus, vulnerable aortic plaque, cardiac tumors, and valvular vegetation as causes of cardioembolic stroke. The end point was stroke recurrence. Sensitivity, specificity, PPV, and NPV for recurrent stroke were calculated; the diagnostic accuracy of CMRI, CCTA, and TTE was compared between and within groups using AUC. RESULTS. Twelve and 14 recurrent strokes occurred in the CCTA and CMRI groups, respectively. Sensitivity, specificity, PPV, and NPV were 33.3%, 93.7%, 50.0%, and 88.2% for CCTA; 14.3%, 80.3%, 14.3%, and 80.3% for CMRI; 14.3%, 83.6%, 16.7%, and 80.9% for TTE in the CMRI group; and 8.3%, 93.7%, 20.0%, and 84.5% for TTE in the CCTA group. Accuracy was not different (p > .05) between CCTA (AUC = 0.63; 95% CI, 0.49-0.77), CMRI (0.53; 95% CI, 0.42-0.63), TTE in the CMRI group (0.51; 95% CI, 0.40-0.61), and TTE in the CCTA group (0.51; 95% CI, 0.42-0.59). In the CCTA group, atrial and ventricular thrombus were detected by CCTA in three patients and TTE in one patient; in the CMRI group, thrombus was detected by CMRI in one patient and TTE in two patients. CONCLUSION. CCTA, CMRI, and TTE showed comparably high specificity and NPV for cardioembolic stroke recurrence. CCTA and CMRI may be valid alternatives to TTE. CCTA may be preferred given potentially better detection of atrial and ventricular thrombus. CLINICAL IMPACT. CCTA and CMRI have similar clinical performance as TTE for predicting cardioembolic stroke recurrence. This observation may be especially important when TTE provides equivocal findings.

The Feasibility, Tolerability, Safety, and Accuracy of Low-radiation Dynamic Computed Tomography Myocardial Perfusion Imaging With Regadenoson Compared With Single-photon Emission Computed Tomography.

OBJECTIVES: Computed tomography (CT) myocardial perfusion imaging (CT-MPI) with hyperemia induced by regadenoson was evaluated for the detection of myocardial ischemia, safety, relative radiation exposure, and patient experience compared with single-photon emission computed tomography (SPECT) imaging. MATERIALS AND METHODS: Twenty-four patients (66.5 y, 29% male) who had undergone clinically indicated SPECT imaging and provided written informed consent were included in this phase II, IRB-approved, and FDA-approved clinical trial. All patients underwent coronary CT angiography and CT-MPI with hyperemia induced by the intravenous administration of regadenoson (0.4 mg/5 mL). Patient experience and findings on CT-MPI images were compared to SPECT imaging. RESULTS: Patient experience and safety were similar between CT-MPI and SPECT procedures and no serious adverse events due to the administration of regadenoson occurred. SPECT resulted in a higher number of mild adverse events than CT-MPI. Patient radiation exposure was similar during the combined coronary computed tomography angiography and CT-MPI (4.4 [2.7] mSv) and SPECT imaging (5.6 [1.7] mSv) (P-value 0.401) procedures. Using SPECT as the reference standard, CT-MPI analysis showed a sensitivity of 58.3% (95% confidence interval [CI]: 27.7-84.8), a specificity of 100% (95% CI: 73.5-100), and an accuracy of 79.1% (95% CI: 57.9-92.87). Low apparent sensitivity occurred when the SPECT defects were small and highly suspicious for artifacts. CONCLUSIONS: This study demonstrated that CT-MPI is safe, well tolerated, and can be performed with comparable radiation exposure to SPECT. CT-MPI has the benefit of providing both complete anatomic coronary evaluation and assessment of myocardial perfusion.

Lung parenchymal and airway changes on CT imaging following allergen challenge and bronchoalveolar lavage in atopic and asthmatic subjects.

BACKGROUND: Computed tomography (CT) imaging findings in the lungs in the setting of an acute allergic response and following bronchoalveolar lavage (BAL) are not well established. Our goals are to characterize the pulmonary CT findings of acute allergic response in both asthmatic and non-asthmatic subjects and, secondarily, to characterize the pulmonary imaging findings following BAL. METHODS: In this prospective observational (cohort) study, we identified atopic, asthmatic (AA) and atopic, non-asthmatic (ANA) subjects. CT of the chest was performed following BAL and instillation of an allergen (AL) and of an inert diluent (DL). Two radiologists analyzed the CT examinations for airway and parenchymal changes. RESULTS: We had a cohort of 20 atopic subjects (AA=10, ANA=10; F=11, M=9; median age: 23.5 years, range: 18-48 years). Compared to diluent instillation and BAL, allergen instillation resulted in more significant bronchial wall thickening (AL=70%, DL=0%, BAL=0%, P<0.01), consolidations (AL=55%, DL=0%, BAL=15%, P<0.05), and septal thickening (AL=35%, DL=0%, BAL=0%, P<0.01). When present, consolidations tended to be more common in asthmatic subjects compared to non-asthmatics following instillation of the allergen, although this did not reach statistical significance (AA=80% vs. ANA=30%; P=0.07). BAL, on the other hand, resulted in more ground-glass opacities (BAL=15/20, 75% vs. AL=2/20, 10%, vs. DL=0/20, 0%; P<0.01). CONCLUSIONS: Acute allergic response in the lungs can result in significant bronchial wall thickening, septal thickening, and consolidations in those with atopy, particularly those with asthma. Localized ground-glass opacities may be expected following BAL, and care should be taken so as to not misinterpret these as significant pathology.

Artificial Intelligence-based Fully Automated Per Lobe Segmentation and Emphysema-quantification Based on Chest Computed Tomography Compared With Global Initiative for Chronic Obstructive Lung Disease Severity of Smokers.

OBJECTIVES: The objective of this study was to evaluate an artificial intelligence (AI)-based prototype algorithm for the fully automated per lobe segmentation and emphysema quantification (EQ) on chest-computed tomography as it compares to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) severity classification of chronic obstructive pulmonary disease (COPD) patients. METHODS: Patients (n=137) who underwent chest-computed tomography acquisition and spirometry within 6 months were retrospectively included in this Institutional Review Board-approved and Health Insurance Portability and Accountability Act-compliant study. Patient-specific spirometry data, which included forced expiratory volume in 1 second, forced vital capacity, and the forced expiratory volume in 1 second/forced vital capacity ratio (Tiffeneau-Index), were used to assign patients to their respective GOLD stage I to IV. Lung lobe segmentation was carried out using AI-RAD Companion software prototype (Siemens Healthineers), a deep convolution image-to-image network and emphysema was quantified in each lung lobe to detect the low attenuation volume. RESULTS: A strong correlation between the whole-lung-EQ and the GOLD stages was found (ρ=0.88, P<0.0001). The most significant correlation was noted in the left upper lobe (ρ=0.85, P<0.0001), and the weakest in the left lower lobe (ρ=0.72, P<0.0001) and right middle lobe (ρ=0.72, P<0.0001). CONCLUSIONS: AI-based per lobe segmentation and its EQ demonstrate a very strong correlation with the GOLD severity stages of COPD patients. Furthermore, the low attenuation volume of the left upper lobe not only showed the strongest correlation to GOLD severity but was also able to most clearly distinguish mild and moderate forms of COPD. This is particularly relevant due to the fact that early disease processes often elude conventional pulmonary function diagnostics. Earlier detection of COPD is a crucial element for positively altering the course of disease progression through various therapeutic options.

Accuracy of an Artificial Intelligence Deep Learning Algorithm Implementing a Recurrent Neural Network With Long Short-term Memory for the Automated Detection of Calcified Plaques From Coronary Computed Tomography Angiography.

PURPOSE: The purpose of this study was to evaluate the accuracy of a novel fully automated deep learning (DL) algorithm implementing a recurrent neural network (RNN) with long short-term memory (LSTM) for the detection of coronary artery calcium (CAC) from coronary computed tomography angiography (CCTA) data. MATERIALS AND METHODS: Under an IRB waiver and in HIPAA compliance, a total of 194 patients who had undergone CCTA were retrospectively included. Two observers independently evaluated the image quality and recorded the presence of CAC in the right (RCA), the combination of left main and left anterior descending (LM-LAD), and left circumflex (LCx) coronary arteries. Noncontrast CACS scans were allowed to be used in cases of uncertainty. Heart and coronary artery centerline detection and labeling were automatically performed. Presence of CAC was assessed by a RNN-LSTM. The algorithm's overall and per-vessel sensitivity, specificity, and diagnostic accuracy were calculated. RESULTS: CAC was absent in 84 and present in 110 patients. As regards CCTA, the median subjective image quality, signal-to-noise ratio, and contrast-to-noise ratio were 3.0, 13.0, and 11.4. A total of 565 vessels were evaluated. On a per-vessel basis, the algorithm achieved a sensitivity, specificity, and diagnostic accuracy of 93.1% (confidence interval [CI], 84.3%-96.7%), 82.76% (CI, 74.6%-89.4%), and 86.7% (CI, 76.8%-87.9%), respectively, for the RCA, 93.1% (CI, 86.4%-97.7%), 95.5% (CI, 88.77%-98.75%), and 94.2% (CI. 90.2%-94.6%), respectively, for the LM-LAD, and 89.9% (CI, 80.2%-95.8%), 90.0% (CI, 83.2%-94.7%), and 89.9% (CI, 85.0%-94.1%), respectively, for the LCx. The overall sensitivity, specificity, and diagnostic accuracy were 92.1% (CI, 92.1%-95.2%), 88.9% (CI. 84.9%-92.1%), and 90.3% (CI, 88.0%-90.0%), respectively. When accounting for image quality, the algorithm achieved a sensitivity, specificity, and diagnostic accuracy of 76.2%, 87.5%, and 82.2%, respectively, for poor-quality data sets and 93.3%, 89.2% and 90.9%, respectively, when data sets rated adequate or higher were combined. CONCLUSION: The proposed RNN-LSTM demonstrated high diagnostic accuracy for the detection of CAC from CCTA.

Comparison of Artificial Intelligence-Based Fully Automatic Chest CT Emphysema Quantification to Pulmonary Function Testing.

OBJECTIVE. The purpose of this study was to evaluate an artificial intelligence (AI)-based prototype algorithm for fully automated quantification of emphysema on chest CT compared with pulmonary function testing (spirometry). MATERIALS AND METHODS. A total of 141 patients (72 women, mean age ± SD of 66.46 ± 9.7 years [range, 23-86 years]; 69 men, mean age of 66.72 ± 11.4 years [range, 27-91 years]) who underwent both chest CT acquisition and spirometry within 6 months were retrospectively included. The spirometry-based Tiffeneau index (TI; calculated as the ratio of forced expiratory volume in the first second to forced vital capacity) was used to measure emphysema severity; a value less than 0.7 was considered to indicate airway obstruction. Segmentation of the lung based on two different reconstruction methods was carried out by using a deep convolution image-to-image network. This multilayer convolutional neural network was combined with multilevel feature chaining and depth monitoring. To discriminate the output of the network from ground truth, an adversarial network was used during training. Emphysema was quantified using spatial filtering and attenuation-based thresholds. Emphysema quantification and TI were compared using the Spearman correlation coefficient. RESULTS. The mean TI for all patients was 0.57 ± 0.13. The mean percentages of emphysema using reconstruction methods 1 and 2 were 9.96% ± 11.87% and 8.04% ± 10.32%, respectively. AI-based emphysema quantification showed very strong correlation with TI (reconstruction method 1, ρ = -0.86; reconstruction method 2, ρ = -0.85; both p < 0.0001), indicating that AI-based emphysema quantification meaningfully reflects clinical pulmonary physiology. CONCLUSION. AI-based, fully automated emphysema quantification shows good correlation with TI, potentially contributing to an image-based diagnosis and quantification of emphysema severity.

In-Hospital Cost Comparison of Triple-Rule-Out Computed Tomography Angiography Versus Standard of Care in Patients With Acute Chest Pain.

PURPOSE: The purpose of this study was to evaluate the utilization of invasive and noninvasive tests and compare cost in patients presenting with chest pain to the emergency department (ED) who underwent either triple-rule-out computed tomography angiography (TRO-CTA) or standard of care. MATERIALS AND METHODS: We performed a retrospective single-center analysis of 2156 ED patients who presented with acute chest pain with a negative initial troponin and electrocardiogram for myocardial injury. Patient cohorts matched by patient characteristics who had undergone TRO-CTA as a primary imaging test (n=1139) or standard of care without initial CTA imaging (n=1017) were included in the study. ED visits, utilization of tests, and costs during the initial episode of hospital care were compared. RESULTS: No significant differences in the diagnosis of coronary artery disease, pulmonary embolism, or aortic dissection were observed. Median ED waiting time (4.5 vs. 7.0 h, P<0.001), median total length of hospital stay (5.0 vs. 32.0 h, P<0.001), hospital admission rate (12.6% vs. 54.2%, P<0.001), and ED return rate to our hospital within 30 days (3.5% vs. 14.6%, P<0.001) were significantly lower in the TRO-CTA group. Moreover, reduced rates of additional testing and invasive coronary angiography (4.9% vs. 22.7%, P<0.001), and ultimately lower total cost per patient (11,783$ vs. 19,073$, P<0.001) were observed in the TRO-CTA group. CONCLUSIONS: TRO-CTA as an initial imaging test in ED patients presenting with acute chest pain was associated with shorter ED and hospital length of stay, fewer return visits within 30 days, and ultimately lower ED and hospitalization costs.

Deep learning to convert unstructured CT pulmonary angiography reports into structured reports.

BACKGROUND: Structured reports have been shown to improve communication between radiologists and providers. However, some radiologists are concerned about resultant decreased workflow efficiency. We tested a machine learning-based algorithm designed to convert unstructured computed tomography pulmonary angiography (CTPA) reports into structured reports. METHODS: A self-supervised convolutional neural network-based algorithm was trained on a dataset of 475 manually structured CTPA reports. Labels for individual statements included "pulmonary arteries," "lungs and airways," "pleura," "mediastinum and lymph nodes," "cardiovascular," "soft tissues and bones," "upper abdomen," and "lines/tubes." The algorithm was applied to a test set of 400 unstructured CTPA reports, generating a predicted label for each statement, which was evaluated by two independent observers. Per-statement accuracy was calculated based on strict criteria (algorithm label counted as correct if the statement unequivocally contained content only related to that particular label) and a modified criteria, accounting for problematic statements, including typographical errors, statements that did not fit well into the classification scheme, statements containing content for multiple labels, etc. RESULTS: Of the 4,157 statements, 3,806 (91.6%) and 3,986 (95.9%) were correctly labeled by the algorithm using strict and modified criteria, respectively, while 274 (6.6%) were problematic for the manual observers to label, the majority of which (n = 173) were due to more than one section being included in one statement. CONCLUSION: This algorithm showed high accuracy in converting free-text findings into structured reports, which could improve communication between radiologists and clinicians without loss of productivity and provide more structured data for research/data mining applications.

Review of Clinical Applications for Virtual Monoenergetic Dual-Energy CT.

In this article, the authors discuss the technical background and summarize the current body of literature regarding virtual monoenergetic (VM) images derived from dual-energy CT data, which can be reconstructed between 40 and 200 keV. Substantially improved iodine attenuation at lower kiloelectron volt levels and reduced beam-hardening artifacts at higher kiloelectron volt levels have been demonstrated from all major manufacturers of dual-energy CT units. Improved contrast attenuation with VM imaging at lower kiloelectron volt levels enables better delineation and diagnostic accuracy in the detection of various vascular or oncologic abnormalities. Low-kiloelectron-volt VM imaging may be useful for salvaging CT studies with suboptimal contrast material delivery or providing additional information on the arterial vasculature obtained from venous phase acquisitions. For patients with renal impairment, substantial reductions in the use of iodinated contrast material can be achieved by using lower-energy VM imaging. The authors recommend routine reconstruction of VM images at 50 keV when using dual-energy CT to exploit the increased contrast properties. For reduction of beam-hardening artifacts, VM imaging at 120 keV is useful for the initial assessment.

Design of CTP-PRO study (impact of stress Cardiac computed Tomography myocardial Perfusion on downstream resources and PROgnosis in patients with suspected or known coronary artery disease: A multicenter international study).

BACKGROUND: CT myocardial perfusion imaging (CTP) represents one of the newly developed CT-based techniques but its cost-effectiveness in the clinical pathway is undefined. The aim of the study is to evaluate the usefulness of combined evaluation of coronary anatomy and myocardial perfusion in intermediate to high-risk patients for suspected CAD or with known disease in terms of clinical decision-making, resource utilization and outcomes in a broad variety of geographic areas and patient subgroups. METHODS: CTP-PRO study is a cooperative, international, multicentre, prospective, open-label, randomized controlled study evaluating the cost-effectiveness of a CCTA+CTP strategy (Group A) versus usual care (Group B) in intermediate-high risk patients with suspected or known CAD who undergo clinically indicated diagnostic evaluation. A total sample size of 2000 subjects will be enrolled and followed up for 24 months. The primary endpoint is the reclassification rate of CCTA in group A due to the addition of CTP. The secondary endpoint will be the comparison between groups in terms of non-invasive and invasive downstream testing, prevalence of obstructive CAD at ICA, revascularization, cumulative ED and overall cost during the follow-up at 1- and 2-years. The tertiary endpoint will be the comparison between each group in terms of MACE and cost-effectiveness at 1- and 2-years. CONCLUSIONS: The study will provide information to patients, health care providers and other stakeholders about which strategy could be more effective in the diagnosis of suspected CAD in intermediate to high-risk patients or in the symptomatic patients with known CAD and previous history of revascularization.

Modified calcium subtraction in dual-energy CT angiography of the lower extremity runoff: impact on diagnostic accuracy for stenosis detection.

OBJECTIVES: To investigate the diagnostic accuracy of a modified three-material decomposition calcium subtraction (CS) algorithm for the detection of arterial stenosis in dual-energy CT angiography (DE-CTA) of the lower extremity runoff compared to standard image reconstruction, using digital subtraction angiography (DSA) as the reference standard. METHODS: Eighty-eight patients (53 males; mean age, 65.9 ± 11 years) with suspected peripheral arterial disease (PAD) who had undergone a DE-CTA examination of the lower extremity runoff between May 2014 and May 2015 were included in this IRB-approved, HIPAA-compliant retrospective study. Standard linearly blended and CS images were reconstructed and vascular contrast-to-noise ratios (CNR) were calculated. Two independent observers assessed subjective image quality using a 5-point Likert scale. Diagnostic accuracy for ≥ 50% stenosis detection was analyzed in a subgroup of 45 patients who had undergone additional DSA. Diagnostic accuracy parameters were estimated with a random-effects logistic regression analysis and compared using generalized estimating equations. RESULTS: CS datasets showed higher CNR (15.3 ± 7.3) compared to standard reconstructions (13.5 ± 6.5, p < 0.001). Both reconstructions showed comparable qualitative image quality scores (CS, 4.64; standard, 4.57; p = 0.220). Diagnostic accuracy (sensitivity, specificity, positive and negative predictive values) for CS reconstructions was 96.5% (97.5%, 95.6%, 90.9%, 98.1) and 93.1% (98.8%, 90.4%, 82.3%, 99.1%) for standard images. CONCLUSIONS: A modified three-material decomposition CS algorithm provides increased vascular CNR, equivalent qualitative image quality, and greater diagnostic accuracy for the detection of significant arterial stenosis of the lower extremity runoff on DE-CTA compared with standard image reconstruction. KEY POINTS: • Calcified plaques may lead to overestimation of stenosis severity and false positive results, requiring additional invasive digital subtraction angiography (DSA). • A modified three-material decomposition algorithm for calcium subtraction provides greater diagnostic accuracy for the detection of significant arterial stenosis of the lower extremity runoff compared with standard image reconstruction. • The application of this algorithm in patients with heavily calcified vessels may be helpful to potentially reduce inconclusive CT angiography examinations and the need for subsequent invasive DSA.

Diagnostic Accuracy of Noncontrast Self-navigated Free-breathing MR Angiography versus CT Angiography: A Prospective Study in Pediatric Patients with Suspected Anomalous Coronary Arteries.

RATIONALE AND OBJECTIVES: To evaluate the diagnostic accuracy of a prototype noncontrast, free-breathing, self-navigated 3D (SN3D) MR angiography (MRA) technique for the assessment of coronary artery anatomy in children with known or suspected coronary anomalies, using CT angiography (CTA) as the reference standard. MATERIALS AND METHODS: Twenty-one children (15 male, 12.3 ± 2.6 years) were prospectively enrolled between July 2014 and August 2016 in this IRB-approved, HIPAA-compliant study. Patients underwent same-day unenhanced SN3D-MRA and contrast-enhanced CTA. Two observers rated the visualization of coronary artery segments and diagnostic confidence on a 3-point scale and assessed coronary arteries for anomalous origin, as well as interarterial and intramural course. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of SN3D-MRA for the detection of coronary artery abnormalities were calculated. Interobserver agreement was assessed using Intraclass Correlation Coefficients (ICC). RESULTS: Fourteen children showed coronary artery abnormalities on CTA. The visualization of coronary segments was rated significantly higher for CTA compared to MRA (p <0.015), except for the left main coronary artery (p = 0.301), with good to excellent interobserver agreement (ICC = 0.62-0.94). Diagnostic confidence was higher for CTA (p = 0.046). Sensitivity, specificity, PPV, and NPV of MRA were 92%, 92%, 96%, and 87% for the detection of coronary artery anomalies, 85%, 85%, 74%, and 92% for high origin, 71%, 92%, 82%, and 87% for interarterial, and 41%, 96%, 87%, and 80% for intramural course. CONCLUSIONS: Noncontrast SN3D-MRA is highly accurate for the detection of coronary artery anomalies in pediatric patients while diagnostic confidence and coronary artery visualization remain superior with CTA.

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.