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Artificial intelligence (AI) is having a significant impact in medical imaging, advancing almost every aspect of the field, from image acquisition and postprocessing to automated image analysis with outreach toward supporting decision making. Noninvasive cardiac imaging is one of the main and most exciting fields for AI development. The aim of this review is to describe the main applications of AI in cardiac imaging, including CT and MR imaging, and provide an overview of recent advancements and available clinical applications that can improve clinical workflow, disease detection, and prognostication in cardiac disease.

Cardiovascular imaging is exponentially increasing in the diagnosis, risk stratification, and therapeutic management of patients with cardiovascular disease. The European Society of Cardiovascular Radiology (ESCR) is a non-profit scientific medical society dedicated to promoting and coordinating activities in cardiovascular imaging. The purpose of this paper, written by ESCR committees and Executive board members and approved by the ESCR Executive Board and Guidelines committee, is to codify a standardized approach to creating ESCR scientific documents. Indeed, consensus development methods must be adopted to ensure transparent decision-making that optimizes national and global health and reaches a certain scientific credibility. ESCR consensus documents developed based on a rigorous methodology will improve their scientific impact on the management of patients with cardiac involvement. Critical relevance statement: This document aims to codify the methodology for producing consensus documents of the ESCR. These ESCR indications will broaden the scientific quality and credibility of further publications and, consequently, the impact on the diagnostic management of patients with cardiac involvement. Key Points: Cardiovascular imaging is exponentially increasing for diagnosis, risk stratification, and therapeutic management. The ESCR is committed to promoting cardiovascular imaging. A rigorous methodology for ESCR consensus documents will improve their scientific impact.

Background: Scar burden with late gadolinium enhancement (LGE) cardiac MRI (CMR) predicts arrhythmic events in patients with postinfarction in single-center studies. However, LGE analysis requires experienced human observers, is time consuming, and introduces variability. Purpose: To test whether postinfarct scar with LGE CMR can be quantified fully automatically by machines and to compare the ability of LGE CMR scar analyzed by humans and machines to predict arrhythmic events. Materials and Methods: This study is a retrospective analysis of the multicenter, multivendor CarDiac MagnEtic Resonance for Primary Prevention Implantable CardioVerter DebrillAtor ThErapy (DERIVATE) registry. Patients with chronic heart failure, echocardiographic left ventricular ejection fraction (LVEF) of less than 50%, and LGE CMR were recruited (from January 2015 through December 2020). In the current study, only patients with ischemic cardiomyopathy were included. Quantification of total, dense, and nondense scars was carried out by two experienced readers or a Ternaus network, trained and tested with LGE images of 515 and 246 patients, respectively. Univariable and multivariable Cox analyses were used to assess patient and cardiac characteristics associated with a major adverse cardiac event (MACE). Area under the receiver operating characteristic curve (AUC) was used to compare model performances. Results: In 761 patients (mean age, 65 years ± 11, 671 men), 83 MACEs occurred. With use of the testing group, univariable Cox-analysis found New York Heart Association class, left ventricle volume and/or function parameters (by echocardiography or CMR), guideline criterion (LVEF of ≤35% and New York Heart Association class II or III), and LGE scar analyzed by humans or the machine-learning algorithm as predictors of MACE. Machine-based dense or total scar conferred incremental value over the guideline criterion for the association with MACE (AUC: 0.68 vs 0.63, P = .02 and AUC: 0.67 vs 0.63

Background: Implantable cardioverter-defibrillator (ICD) therapy is the most effective prophylactic strategy against sudden cardiac death (SCD) in patients with ischemic cardiomyopathy (ICM) and left ventricle ejection fraction (LVEF) ≤35% as detected by transthoracic echocardiograpgy (TTE). This approach has been recently questioned because of the low rate of ICD interventions in patients who received implantation and the not-negligible percentage of patients who experienced SCD despite not fulfilling criteria for implantation. Objectives: The DERIVATE-ICM registry (CarDiac MagnEtic Resonance for Primary Prevention Implantable CardioVerter DebrillAtor ThErapy; NCT03352648) is an international, multicenter, and multivendor study to assess the net reclassification improvement (NRI) for the indication of ICD implantation by the use of cardiac magnetic resonance (CMR) as compared to TTE in patients with ICM. Methods: A total of 861 patients with ICM (mean age 65 ± 11 years, 86% male) with chronic heart failure and TTE-LVEF <50% participated. Major adverse arrhythmic cardiac events (MAACE) were the primary endpoints. Results: During a median follow-up of 1,054 days, MAACE occurred in 88 (10.2%). Left ventricular end-diastolic volume index (HR: 1.007 [95% CI: 1.000-1.011]; P = 0.05), CMR-LVEF (HR: 0.972 [95% CI: 0.945-0.999]; P = 0.045) and late gadolinium enhancement (LGE) mass (HR: 1.010 [95% CI: 1.002-1.018]; P = 0.015) were independent predictors of MAACE. A multiparametric CMR weighted predictive derived score identifies subjects at high risk for MAACE compared with TTE-LVEF cutoff of 35% with a NRI of 31.7% (P = 0.007). Conclusions: The DERIVATE-ICM registry is a large multicenter registry showing the additional value of CMR to stratify the risk for MAACE in a large cohort of patients with ICM compared with standard of care.

Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its implementation will be focused on the automatization tasks, improving diagnostic accuracy and reducing reading time. Many studies investigate the potential role of AI to support cardiac radiologist in their day-to-day tasks, assisting in segmentation, quantification, and reporting tasks. In addition, AI algorithms can be also utilized to optimize image reconstruction and image quality. Since these algorithms will play an important role in the field of cardiac radiology, it is increasingly important for radiologists to be familiar with the potential applications of AI.The main focus of this article is to provide an overview of cardiac-related AI applications for CT and MRI studies, as well as non-imaging-based applications for reporting and image optimization.

Ischemic chronic cardiomyopathy (ICC) is still one of the most common cardiac diseases leading to the development of myocardial ischemia, infarction, or heart failure. The application of several imaging modalities can provide information regarding coronary anatomy, coronary artery disease, myocardial ischemia and tissue characterization. In particular, coronary computed tomography angiography (CCTA) can provide information regarding coronary plaque stenosis, its composition, and the possible evaluation of myocardial ischemia using fractional flow reserve CT or CT perfusion. Cardiac magnetic resonance (CMR) can be used to evaluate cardiac function as well as the presence of ischemia. In addition, CMR can be used to characterize the myocardial tissue of hibernated or infarcted myocardium. Echocardiography is the most widely used technique to achieve information regarding function and myocardial wall motion abnormalities during myocardial ischemia. Nuclear medicine can be used to evaluate perfusion in both qualitative and quantitative assessment. In this review we aim to provide an overview regarding the different noninvasive imaging techniques for the evaluation of ICC, providing information ranging from the anatomical assessment of coronary artery arteries to the assessment of ischemic myocardium and myocardial infarction. In particular this review is going to show the different noninvasive approaches based on the specific clinical history of patients with ICC.

Ischemic cardiomyopathy (ICM) is one of the most common causes of congestive heart failure. In patients with ICM, tissue characterization with cardiac magnetic resonance imaging (CMR) allows for evaluation of myocardial abnormalities in acute and chronic settings. Myocardial edema, microvascular obstruction (MVO), intracardiac thrombus, intramyocardial hemorrhage, and late gadolinium enhancement of the myocardium are easily depicted using standard CMR sequences. In the acute setting, tissue characterization is mainly focused on assessment of ventricular thrombus and MVO, which are associated with poor prognosis. Conversely, in chronic ICM, it is important to depict late gadolinium enhancement and myocardial ischemia using stress perfusion sequences. Overall, with CMR's ability to accurately characterize myocardial tissue in acute and chronic ICM, it represents a valuable diagnostic and prognostic imaging method for treatment planning. In particular, tissue characterization abnormalities in the acute setting can provide information regarding the patients that may develop major adverse cardiac event and show the presence of ventricular thrombus; in the chronic setting, evaluation of viable myocardium can be fundamental for planning myocardial revascularization. In this review, the main findings on tissue characterization are illustrated in acute and chronic settings using qualitative and quantitative tissue characterization.

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.

Aims: The aim of this registry was to evaluate the additional prognostic value of a composite cardiac magnetic resonance (CMR)-based risk score over standard-of-care (SOC) evaluation in a large cohort of consecutive unselected non-ischaemic cardiomyopathy (NICM) patients. Methods and results: In the DERIVATE registry (www.clinicaltrials.gov/registration: RCT#NCT03352648), 1000 (derivation cohort) and 508 (validation cohort) NICM patients with chronic heart failure (HF) and left ventricular ejection fraction [removed]3 segments with midwall fibrosis on late gadolinium enhancement (LGE) were the only independent predictors of all-cause mortality (HR: 1.036, 95% CI: 1.0117-1.056, P < 0.001 and HR: 2.077, 95% CI: 1.211-3.562, P = 0.008, respectively). For MAACE, the independent predictors were male gender, left ventricular end-diastolic volume index by CMR (CMR-LVEDVi), and >3 segments with midwall fibrosis on LGE (HR: 2.131, 95% CI: 1.231-3.690, P = 0.007; HR: 3.161, 95% CI: 1.750-5.709, P < 0.001; and HR: 1.693, 95% CI: 1.084-2.644, P = 0.021, respectively). A composite clinical and CMR-based risk score provided a net reclassification improvement of 63.7% (P < 0.001) for MAACE occurrence when added to the model based on SOC evaluation. These findings were confirmed in the validation cohort. Conclusion: In a large multicentre, multivendor cohort registry reflecting daily clinical practice in NICM work-up, a composite clinical and CMR-based risk score provides incremental prognostic value beyond SOC evaluation, which may have impact on the indication of implantable cardioverter-defibrillator implantation.

Cardiac computed tomography angiography (CCTA) is widely used as a diagnostic tool for evaluation of coronary artery disease (CAD). Despite the excellent capability to rule-out CAD, CCTA may overestimate the degree of stenosis; furthermore, CCTA analysis can be time consuming, often requiring advanced postprocessing techniques. In consideration of the most recent ESC guidelines on CAD management, which will likely increase CCTA volume over the next years, new tools are necessary to shorten reporting time and improve the accuracy for the detection of ischemia-inducing coronary lesions. The application of artificial intelligence (AI) may provide a helpful tool in CCTA, improving the evaluation and quantification of coronary stenosis, plaque characterization, and assessment of myocardial ischemia. Furthermore, in comparison with existing risk scores, machine-learning algorithms can better predict the outcome utilizing both imaging findings and clinical parameters. Medical AI is moving from the research field to daily clinical practice, and with the increasing number of CCTA examinations, AI will be extensively utilized in cardiac imaging. This review is aimed at illustrating the state of the art in AI-based CCTA applications and future clinical scenarios.

Because of a recent increase in survival rates and life expectancy of patients with congenital heart disease (CHD), radiologists are facing new challenges when imaging the peculiar anatomy of individuals with repaired CHD. Cardiac computed tomography and magnetic resonance are paramount noninvasive imaging tools that are useful in assessing patients with repaired CHD, and both techniques are increasingly performed in centers where CHD is not the main specialization. This review provides general radiologists with insight into the main issues of imaging patients with repaired CHD, and the most common findings and complications of each individual pathology and its repair.

Prevalence of patients with congenital heart disease (CHD) is rapidly increasing due to continuous advancements in diagnostic techniques and medical or surgical treatment approaches. Along with cardiac computed tomography angiography, cardiac magnetic resonance (CMR) serves as a fundamental imaging modality for pre-surgical planning in patients with CHD, as CMR allows for the evaluation of cardiac and great vessel anatomy, biventricular function, flow dynamics, and tissue characterization. This information is essential for risk-assessment and optimal timing of surgical interventions. This article discusses the current role of pediatric cardiac MR imaging as a practical preoperative assessment tool in the pediatric population.

Myocardial T1-mapping has become feasible over the past decade as emerging technological magnetic resonance imaging advances enable increasingly rapid and reliable acquisition techniques. A variety of T1-mapping sequences are in development, with most allowing for the acquisition of a single-slice T1-map in a single breath-hold. The development of these protocols has spurred investigation into a wide range of potential clinical uses, including the characterization of cardiomyopathies. Although native T1-mapping provides superior tissue characterization, postcontrast T1-mapping is still indispensable for extracellular volume quantification. Ongoing and future studies should investigate the reliability, reproducibility, accuracy, and precision of available techniques and establish disease-specific reference values for T1-mapping-based parameters.

Objectives: To assess the image quality and diagnostic accuracy of a noise-optimized virtual monoenergetic imaging (VMI+) algorithm compared with standard virtual monoenergetic imaging (VMI) and linearly-blended (M_0.6) reconstructions for the detection of hypervascular liver lesions in dual-energy CT (DECT). Methods: Thirty patients who underwent clinical liver MRI were prospectively enrolled. Within 60 days of MRI, arterial phase DECT images were acquired on a third-generation dual-source CT and reconstructed with M_0.6, VMI and VMI+ algorithms from 40 to 100 keV in 5-keV intervals. Liver parenchyma and lesion contrast-to-noise-ratios (CNR) were calculated. Two radiologists assessed image quality. Lesion sensitivity, specificity and area under the receiver operating characteristic curves (AUCs) were calculated for the three algorithms with MRI as the reference standard. Results: VMI+ datasets from 40 to 60 keV provided the highest liver parenchyma and lesion CNR (p ≤0.021); 50 keV VMI+ provided the highest subjective image quality (4.40±0.54), significantly higher compared to VMI and M_0.6 (all p <0.001), and the best diagnostic accuracy in < 1-cm diameter lesions (AUC=0.833 vs. 0.777 and 0.749, respectively; p ≤0.003). Conclusions: 50-keV VMI+ provides superior image quality and diagnostic accuracy for the detection of hypervascular liver lesions with a diameter < 1cm compared to VMI or M_0.6 reconstructions. Key Points: • Low-keV VMI+ are characterized by higher contrast resulting from maximum iodine attenuation. • VMI+ provides superior image quality compared with VMI or M_0.6. • 50-keV_VMI+ provides higher accuracy for the detection of hypervascular liver lesions < 1cm.

DECT applications in liver imaging are based on two distinct capabilities: (1) material differentiation and (2) material identification and quantification. The possibility to obtain different material-specific (iodine mapping and virtual unenhanced (VU) images) or energy-specific (virtual monoenergetic images) datasets during a single scan may provide several advantages in oncological imaging. The calculation of VU images may replace the acquisition of pre-contrast images, therefore substantially lowering the radiation burden. Iodine maps can be useful to improve visualization and detection of contrast uptake, potentially increasing the diagnostic confidence for assessment of lesion contrast enhancement. Virtual monoenergetic images at low energy levels are beneficial in increasing image contrast, thus potentially improving the visualization and assessment of both hypovascular and hypervascular liver lesions. All these applications, if routinely applied, could improve the safety of CT examinations by reducing the radiation dose and contrast medium amount administered, while at the same time enhancing the detection and characterization of liver lesions.

Objectives: An increased dispersion of myocardial repolarization represents one of the mechanisms underlying the arrhythmic risk in hypertrophic cardiomyopathy (HCM). We investigated spatial myocardial repolarization dispersion indices in HCM patients with nonsustained ventricular tachycardia (NSVT) and, contextually, their main clinical determinants. Methods: Fifty-two well-matched HCM outpatients were categorized into two groups according to the presence or the absence of NSVT at 24-hour Holter electrocardiogram (ECG) monitoring. Each patient underwent a clinical examination, including Doppler echocardiogram integrated with tissue Doppler imaging, cardiac magnetic resonance, and 12-lead surface ECG to calculate the dispersion for the following intervals: QRS, Q-Tend (QTe), Q-Tpeak, Tpeak-Tend (TpTe), J-Tpeak, and J-Tend. Results: The NSVT group showed only QTe dispersion and TpTe dispersion values to be significantly higher than their counterparts. NSVT occurrence was independently predicted by late gadolinium enhancement presence (p = 0.021) and QTe Bazett dispersion (p = 0.030), the latter strongly associated with the myocardial performance index (MPI) obtained at the basal segment of the interventricular septum (p = 0.0004). Conclusion: Our data support QTe dispersion as an easy and noninvasive tool for identifying HCM patients with NSVT propensity. The strong relationship between QTe dispersion and MPI allows us to hypothesize an intriguing link between electrical instability and confined myocardial areas of systodiastolic dysfunction.

Objectives: This study aimed to evaluate the prevalence of colonic diverticula according to age, gender, distribution, disease extension and symptoms with CT colonography (CTC). Methods: The study population included 1091 consecutive patients who underwent CTC. Patients with diverticula were retrospectively stratified according to age, gender, clinical symptoms and colonic segment involvement. Extension of colonic diverticula was evaluated using a three-point quantitative scale. Using this data, a multivariate regression analysis was applied to investigate the existence of any correlation among variables. Results: Colonic diverticula were observed in 561 patients (240 men, mean age 68 ± 12 years). Symptomatic uncomplicated diverticular disease (SUDD) was present in 47.4 % of cases. In 25.6 % of patients ≤40 years, at least one diverticulum in the colon was observed. Prevalence of right-sided diverticula in patients >60 years was 14.2 % in caecum and 18.5 % in ascending colon. No significant difference was found between symptomatic and asymptomatic patients regarding diverticula prevalence and extension. No correlation was present between diverticula extension and symptoms. Conclusion: The incidence of colonic diverticula appears to be greater than expected. Right colon diverticula do not appear to be an uncommon finding, with their prevalence increasing with patient age. SUDD does not seem to be related to diverticula distribution and extension. Key Points: • Incidence of colonic diverticula appears to be greater than expected. • Right colon diverticula do not appear to be an uncommon finding. • SUDD does not seem to be related to diverticula distribution and extension.

T1 mapping with cardiac MRI has gained an important role in myocardial tissue characterization over the past decade as emerging technological developments enable reliable myocardial T1 assessment with a reasonably short acquisition time. Fast mapping approaches can acquire a single-slice T1 map in a single breath-hold even in patients with low compliance and low breath-holding capacity. Improvements in T1 mapping sequences have extended the clinical utility of this technique to a broad range of myocardial diseases. Indeed, native T1 mapping and extracellular volume fraction mapping seem to have superior value over conventional late gadolinium enhancement techniques in assessing certain myocardial diseases. Ongoing studies look to establish inter-vendor reference values, to further shorten the acquisition time, to develop 3D T1 mapping, and to improve reliability and reproducibility.

Background: Growing evidence suggests that late gadolinium enhancement (LGE) at cardiac magnetic resonance (CMR) is an additive marker of disease severity, and possibly of arrhythmic risk, in hypertrophic cardiomyopathy (HCM). We investigated the possible relationship between LGE and markers of myocardial repolarization dispersion in HCM. Methods and Results: Eighty-five HCM outpatients underwent CMR and short-period electrocardiogram analysis to calculate the temporal myocardial repolarization dispersion through the QT variance normalized for QT mean (QTVN) and the QT variability index (QTVI). The QT dispersion in the spatial domain was also obtained. Patients with LGE (62%) had higher left atrial volume, maximum wall thickness, and left ventricular mass (P<0.0001), as well as a greater prevalence of non-sustained ventricular tachycardia (P<0.0001) and hypotensive blood pressure response (P=0.044). Both QTVN and QTVI were higher in the group with LGE (P<0.0001). At multivariate analysis, using QTVI as the dependent variable, %LGE (P<0.0001), age (P<0.0001), left ventricular outflow obstruction (P=0.038), and sudden cardiac death risk factor burden (P=0.020) reached statistical significance. Otherwise, only %LGE (P=0.005) and left ventricular mass index (P=0.015) remained associated with QTVN. Conclusions: Temporal myocardial repolarization dispersion correlates with LGE extent. Whether these variables could be useful in HCM clinical management warrants confirmation by larger prospective studies.

Purpose: To evaluate a new dark-blood late gadolinium enhancement (LGE) technique called “T(Rho) And Magnetization transfer and INvErsion Recovery” (TRAMINER) for the ability to detect myocardial LGE versus standard “bright-blood” inversion recovery (SIR) imaging. Materials and Methods: This Institutional Review Board (IRB)-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant prospective study included 40 patients (62 ± 14 years [mean ± standard deviation (SD)], 29 males) with suspected myocardial infarction (MI) referred for the assessment of myocardial viability. The patients underwent a 1.5T cardiac magnetic resonance imaging (MRI) including postcontrast SIR and TRAMINER acquisitions. Normalized images were evaluated by two readers. Subjective (3-point Likert scale) and objective image qualities were compared using Mann–Whitney U-test and paired t-test, respectively. Interobserver agreement, LGE detection rate, and level of certainty were compared using Cohen's kappa, Wilcoxon-test, and Mann–Whitney U-test, respectively. Results are reported as mean ± SD or mean [95% confidence interval]. Results: Overall, image quality was rated similar between TRAMINER and SIR; however, TRAMINER performed better on a visual assessment of the ability to differentiate LGE from blood (Likert scale: 3.0 [3.0–3.0] vs. 2.0 [1.7–2.2], P < 0.0001). TRAMINER provided significantly higher signal intensity range (69.8 ± 10.2 vs. 9.6 ± 7.6, P < 0.0001) and a 4-fold higher signal intensity ratio (4.2 ± 1.9 vs. 1.1 ± 0.1, P < 0.0001) between LGE and blood signals. TRAMINER detected more patients (19/40 vs. 17/40) and segments (91/649 vs. 79/649) with LGE with higher level of certainty (2.9 [2.8–3.0] vs. 2.7 [2.5–2.8], P = 0.0185). Interobserver agreement was good to excellent for LGE detection. Conclusion: TRAMINER provides better contrast between LGE and blood and consequently may have increased ability to discriminate thin subendocardial and papillary mu

The survival rate of patients with congenital heart disease (CHD) has dramatically improved over the last 2 decades because of technological and surgical advances in diagnosis and treatment, respectively. The vast majority of CHD patients are, in fact, amenable to treatment by either device closure or surgery. Considering the wide spectrum of surgical procedures and complex native and derived anatomy, continuous and detailed follow-up is of paramount importance. Cardiac magnetic resonance and cardiac computed tomography angiography are the cornerstones of diagnosis and follow-up of CHD, allowing for comprehensive noninvasive assessment of the heart, coronary tree, and intrathoracic great vessels, along with both morphological and functional evaluation. The aim of this pictorial review is to provide an overview of the most common CHDs and their related surgical procedures as familiarity with the radiological findings of grown-up congenital heart disease patients is crucial for proper diagnostic and follow-up pathways.

Objectives: To evaluate the influence of inversion time (TI) on the precision of myocardial late gadolinium enhancement (LGE) quantification using synthetic inversion recovery (IR) imaging in patients with myocardial infarction (MI). Methods: Fifty-three patients with suspected prior MI underwent 1.5-T cardiac MRI with conventional magnitude (MagIR) and phase-sensitive IR (PSIR) LGE imaging and T1 mapping at 15 min post-contrast. T1-based synthetic MagIR and PSIR images were calculated with a TI ranging from −100 to +150 ms at 5-ms intervals relative to the optimal TI (TI0). LGE was quantified using a five standard deviation (5SD) and full width at half-maximum (FWHM) thresholds. Measurements were compared using one-way analysis of variance. Results: The MagIRsy technique provided precise assessment of LGE area at TIs ≥ TI0, while precision was decreased below TI0. The LGE area showed significant differences at ≤ −25 ms compared to TI0 using 5SD (P < 0.001) and at ≤ −65 ms using the FWHM approach (P < 0.001). LGE measurements did not show significant difference over the analysed TI range in the PSIRsy images using either of the quantification methods. Conclusions: T1 map-based PSIRsy images provide precise quantification of MI independent of TI at the investigated time point post-contrast. MagIRsy-based MI quantification is precise at TI0 and at longer TIs while showing decreased precision at TI values below TI0. Key Points: • Synthetic IR imaging retrospectively generates LGE images at any theoretical TI • Synthetic IR imaging can simulate the effect of TI on LGE quantification • Fifteen minutes post-contrast MagIRsyaccurately quantifies infarcts from TI0to TI0 + 150 ms • Fifteen minutes post-contrast PSIRsyprovides precise infarct size independent of TI • Synthetic IR imaging has further advantages in reducing operator dependence.

Background: To assess the long-term patency of the biologic prosthetic conduit used for reconstruction of the superior vena cava (SVC) by magnetic resonance imaging (MRI). Methods: Patients undergoing oncologic resection and reconstruction of the SVC by a bovine pericardial prosthesis (January 2003 to April 2010) have been studied after 1 year (if surviving) by MRI for the assessment of the conduit long-term patency. Results were compared with those of a control group of patients with normal SVC. Blood flow and area of lumen section at 3 different levels (proximal, middle, distal) were analyzed. Results: Sixteen consecutive patients surviving after 1 year from surgery out of 17 (9 lung cancer, 8 mediastinal malignancy) undergoing SVC reconstruction were included. One patient died postoperatively and was not included. Sixteen patients with similar demographic characteristics were studied in the control group. Mean blood flow was 18.4 ± 3.5 mL/sec (range 14.3 to 25.7) in patients with reconstructed SVC and 20.8 ± 4.1 mL/sec (range 15.3 to 27.7) in the control group. Mean area of the conduit lumen section was 2.2 ± 0.6 cm2 (range 1.6 to 3.6) at proximal level, 2.9 ± 1.3 cm2 at middle level (range 1.3 to 5.7), and 2.1 ± 0.9 cm2 (range 0.5 to 4) at distal level in the reconstructed group, and 2.6 ± 0.7 cm2 (range 1.8 to 4.2), 2.7 ± 0.7 cm 2 (range 1.9 to 4.3), and 2.4 ± 0.3 cm2 (range 1.8 to 3.1), respectively, at proximal, middle, and distal levels in the control group. Differences between the 2 groups were not significant (p > 0.05). Conclusions: The MRI assessment in terms of blood flow and area of lumen section at 3 different levels confirms that bovine pericardial conduit used for SVC replacement shows an optimal patency over the long term. © 2013 by The Society of Thoracic Surgeons.

OBJECTIVE: Dual-energy CT (DECT) is an innovative imaging technique that operates on the basic principle of application of two distinct energy settings that make the transition from CT attenuation-based imaging to material-specific or spectral imaging. The purpose of this review is to describe the use of DECT in oncology. CONCLUSION: Applications of DECT in clinical practice are based on two capabilities: material differentiation and material identification and quantification. The capability of obtaining different material-specific datasets (iodine map, virtual unenhanced, and monochromatic images) in the same acquisition can improve lesion detection and characterization. This approach can also affect evaluation of the response to therapy and detection of oncology-related disorders. DECT is an innovative imaging technique that can dramatically affect the care of oncologic patients.

Purpose: To compare the accuracy of detection and quantification of myocardial late gadolinium enhancement (LGE) with a synthetic inversion-recovery (IR) approach with that of conventional IR techniques. Materials and Methods: This prospective study was approved by the institutional review board and compliant with HIPAA. All patients gave written informed consent. Between June and November 2014, 43 patients (25 men; mean age, 54 years 6 16) suspected of having previous myocardial infarction underwent magnetic resonance (MR) imaging, including contrast material-enhanced LGE imaging and T1 mapping. Synthetic magnitude and phase-sensitive IR images were generated on the basis of T1 maps. Images were assessed by two readers. Differences in the per-patient and persegment LGE detection rates between the synthetic and conventional techniques were analyzed with the McNemar test, and the accuracy of LGE quantification was calculated with the paired t test and Bland-Altman statistics. Interreader agreement for the detection and quantification of LGE was analyzed with k and Bland-Altman statistics, respectively. Results: Seventeen of the 43 patients (39%) had LGE patterns consistent with myocardial infarction. The sensitivity and specificity of synthetic magnitude and phase-sensitive IR techniques in the detection of LGE were 90% and 95%, respectively, with patient-based analysis and 94% and 99%, respectively, with segment-based analysis. The area of LGE measured with synthetic IR techniques showed excellent agreement with that of conventional techniques (4.35 cm2 6 1.88 and 4.14 cm26 1.62 for synthetic magnitude and phase-sensitive IR, respectively, compared with 4.25 cm2 6 1.92 and 4.22 cm2 6 1.86 for conventional magnitude and phase-sensitive IR, respectively; P <05). Interreader agreement was excellent for the detection (k . 0.81) and quantification (bias range, 20.34 to 0.40; P <05) of LGE. Conclusion: The accuracy of the T1 map-based synthetic IR approach in the de

Objectives: To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based segmentation and aortic flow measurements. Methods: Short-axis cine images of 148 patients (55 ± 18 years, 81 men) were used to evaluate left ventricular (LV) volumes and mass (LVM) using conventional and threshold-based segmentations. Phase-contrast images were used to independently measure stroke volume (SV). LV parameters were evaluated by two independent readers. Results: Evaluation times using the conventional and threshold-based methods were 8.4 ± 1.9 and 4.2 ± 1.3 min, respectively (P < 0.0001). LV parameters measured by the conventional and threshold-based methods, respectively, were end-diastolic volume (EDV) 146 ± 59 and 134 ± 53 ml; end-systolic volume (ESV) 64 ± 47 and 59 ± 46 ml; SV 82 ± 29 and 74 ± 28 ml (flow-based 74 ± 30 ml); ejection fraction (EF) 59 ± 16 and 58 ± 17 %; and LVM 141 ± 55 and 159 ± 58 g. Significant differences between the conventional and threshold-based methods were observed in EDV, ESV, and LVM mesurements; SV from threshold-based and flow-based measurements were in agreement (P > 0.05) but were significantly different from conventional analysis (P < 0.05). Excellent inter-observer agreement was observed. Conclusions: Threshold-based LV segmentation provides improved accuracy and faster assessment compared to conventional contour-based methods. Key Points: • Threshold-based left ventricular segmentation provides time-efficient assessment of left ventricular parameters • The threshold-based method can discriminate between blood and papillary muscles • This method provides improved accuracy compared to aortic flow measurements as a reference

Objectives To compare image quality and diagnostic accuracy for the detection of liver lesions of virtual unenhanced (VU) images based on third-generation dual-source dual- energy computed tomography (DECT) compared to conventional unenhanced (CU) images. Methods Thirty patients underwent triphasic abdominal CT consisting of single-energy CU (120 kV, 147 ref.mAs) and dual-energy CT arterial and portal-venous phase acquisitions (100/Sn150 kV, 180/90 ref.mAs). VU images were generated from arterial (AVU) and portal venous (PVU) phases. CU, AVU and PVU datasets were reconstructed. Quantitative image quality analysis was performed and two abdominal radiologists independently analyzed all datasets to evaluate image quality and identify liver lesions. Radiation dose was recorded and potential radiation dose reduction was estimated. Results Image quality was rated diagnostic in 100% of the VU datasets. The mean subjective image quality of the CU datasets was higher than that of VU images (p < 0.0001). No significant difference was observed in the mean attenuation values of the liver parenchyma (p > 0.99) and hypoattenuating liver lesions (p ≥ 0.21) between CU, AVU and PVU. However, a significant reduction in the attenuation values of calcified lesions (p < 0.0001), metallic clips (p < 0.0001) and gallstones (p ≤ 0.047) was observed in the AVU and PVU images compared with CU images. A total of 122 liver lesions were found in 25 patients. VU images were more sensitive than CU images for detection of small hypoattenuating liver lesions (≤1 cm). However, CU images were more sensitive than VU for calcified liver lesions. The mean radiation dose reduction achievable by avoiding the unenhanced acquisition was 32.9% ± 1.1% (p < 0.01). Conclusions Third-generation DSCT VU images of the liver provide diagnostic image quality and improve small (≤1 cm) liver lesion detection; however calcified liver lesions can be missed due to complete subtraction.

Rationale and Objectives: To evaluate the diagnostic accuracy of semiautomated global quantification of left ventricular myocardial perfusion derived from stress dynamic computed tomography myocardial perfusion imaging (CTMPI) for detection of territorial perfusion deficits (PD). Materials and Methods: Dynamic CTMPI datasets of 71 patients were analyzed using semiautomated volume-based software to calculate global myocardial blood flow (MBF), myocardial blood volume, and volume transfer constant. Optimal cutoff values to assess the diagnostic accuracy of these parameters for detection of one- to three-vessel territories with PD in comparison to visual analysis were calculated. Results: Nonsignificant differences (P = 0.694) were found for average global MBF in patients without PD and single-territorial PD. Significant differences were found for mean global MBF in patients with PD in two (P < 0.0058) and three territories (P < 0.0003). Calculated optimal thresholds for global MBF and myocardial blood volume resulted in a sensitivity, specificity, and negative predictive value of 100% for detection of three-vessel territory PD. For detection of ≥2 territories with PD, global MBF was superior to other parameters (sensitivity 81.3%, specificity 90.9%, and negative predictive value 94.3%). Conclusions: Semiautomated global quantification of left ventricular MBF during stress dynamic CTMPI shows high diagnostic accuracy for detection of ≥2 vessel territories with PD, facilitating identification of patients with multi-territorial myocardial PD.