MRI-derived extracellular volume as a biomarker of cancer therapy cardiotoxicity: systematic review and meta-analysis.

OBJECTIVES: MRI-derived extracellular volume (ECV) allows characterization of myocardial changes before the onset of overt pathology, which may be caused by cancer therapy cardiotoxicity. Our purpose was to review studies exploring the role of MRI-derived ECV as an early cardiotoxicity biomarker to guide timely intervention. MATERIALS AND METHODS: In April 2022, we performed a systematic search on EMBASE and PubMed for articles on MRI-derived ECV as a biomarker of cancer therapy cardiotoxicity. Two blinded researchers screened the retrieved articles, including those reporting ECV values at least 3 months from cardiotoxic treatment. Data extraction was performed for each article, including clinical and technical data, and ECV values. Pooled ECV was calculated using the random effects model and compared among different treatment regimens and among those who did or did not experience overt cardiac dysfunction. Meta-regression analyses were conducted to appraise which clinical or technical variables yielded a significant impact on ECV. RESULTS: Overall, 19 studies were included. Study populations ranged from 9 to 236 patients, for a total of 1123 individuals, with an average age ranging from 12.5 to 74 years. Most studies included patients with breast or esophageal cancer, treated with anthracyclines and chest radiotherapy. Pooled ECV was 28.44% (95% confidence interval, CI, 26.85-30.03%) among subjects who had undergone cardiotoxic cancer therapy, versus 25.23% (95%CI 23.31-27.14%) among those who had not (p = .003). CONCLUSION: A higher ECV in patients who underwent cardiotoxic treatment could imply subclinical changes in the myocardium, present even before overt cardiac pathology is detectable. CLINICAL RELEVANCE STATEMENT: The ability to detect subclinical changes in the myocardium displayed by ECV suggests its use as an early biomarker of cancer therapy-related cardiotoxicity. KEY POINTS: • Cardiotoxicity is a common adverse effect of cancer therapy; therefore, its prompt detection could improve patient outcomes. • Pooled MRI-derived myocardial extracellular volume was higher in patients who underwent cardiotoxic cancer therapy than in those who did not (28.44% versus 25.23%, p = .003). • MRI-derived myocardial extracellular volume represents a potential early biomarker of cancer therapy cardiotoxicity.

Cardiovascular involvement in Erdheim-Chester diseases is associated with myocardial fibrosis and atrial dysfunction.

PURPOSE: Erdheim-Chester disease (ECD) is a rare multisystem histiocytosis, whose cardiovascular involvement has not been systematically characterized so far. We aimed to systematically (qualitatively and quantitatively) describe the features of cardiovascular involvement in a large cohort of ECD patients and to evaluate its impact on myocardial fibrosis extension and cardiac function. MATERIAL AND METHODS: Among 54 patients with biopsy-proven ECD, 29 patients (59 ± 12 years, 79% males) underwent 1.5-T CMR using a standardized protocol for qualitative and quantitative assessment of disease localization, evaluation of atrial and ventricular function, and assessment of non-dense and dense myocardial fibrosis. RESULTS: The right atrioventricular (AV) groove was the most commonly affected cardiac site (76%) followed by the right atrial walls (63%), thoracic aorta (59%), and superior vena cava (38%). Right AV groove involvement, encasing the right ventricular artery, was associated with non-dense myocardial fibrosis in the infero-septal (20/26 patients) and the inferior (14/26 patients) mid-basal left ventricular (LV) wall. In two patients with right AV groove localization, LGE revealed myocardial infarction in the same myocardial segments. Three out of five patients with left AV groove involvement had non-dense LGE on the lateral LV mid-basal wall. Bulky right atrial pseudomass was associated with atrial dysfunction and superior and inferior vena cava stenosis. CONCLUSIONS: In ECD patients, AV groove localization is associated with LV wall fibrosis in the downstream coronary territories, suggesting hemodynamic alterations due to coronary encasement. Conversely, atrial pseudomass ECD localizations impact on atrial contractility causing atrial dysfunction and are associated with atrio-caval junction stenosis.

Mammography biomarkers of cardiovascular and musculoskeletal health: A review.

Breast density (BD) and breast arterial calcifications (BAC) can expand the role of mammography. In premenopause, BD is related to body fat composition: breast adipose tissue and total volume are potential indicators of fat storage in visceral depots, associated with higher risk of cardiovascular disease (CVD). Women with fatty breast have an increased likelihood of hypercholesterolemia. Women without cardiometabolic diseases with higher BD have a lower risk of diabetes mellitus, hypertension, chest pain, and peripheral vascular disease, while those with lower BD are at increased risk of cardiometabolic diseases. BAC, the expression of Monckeberg sclerosis, are associated with CVD risk. Their prevalence, 13 % overall, rises after menopause and is reduced in women aged over 65 receiving hormonal replacement therapy. Due to their distinct pathogenesis, BAC are associated with hypertension but not with other cardiovascular risk factors. Women with BAC have an increased risk of acute myocardial infarction, ischemic stroke, and CVD death; furthermore, moderate to severe BAC load is associated with coronary artery disease. The clinical use of BAC assessment is limited by their time-consuming manual/visual quantification, an issue possibly solved by artificial intelligence-based approaches addressing BAC complex topology as well as their large spectrum of extent and x-ray attenuations. A link between BD, BAC, and osteoporosis has been reported, but data are still inconclusive. Systematic, standardised reporting of BD and BAC should be encouraged.

Quantification of epicardial adipose tissue in obese patients using an open-bore MR scanner.

BACKGROUND: Our aim was to evaluate the reproducibility of epicardial adipose tissue (EAT) volume, measured on scans performed using an open-bore magnetic resonance scanner. METHODS: Consecutive patients referred for bariatric surgery, aged between 18 and 65 years who agreed to undergo cardiac imaging (MRI), were prospectively enrolled. All those with cardiac pathology or contraindications to MRI were excluded. MRI was performed on a 1.0-T open-bore scanner, and EAT was segmented on all scans at both systolic and diastolic phase by two independent readers (R1 with four years of experience and R2 with one year). Data were reported as median and interquartile range; agreement and differences were appraised with Bland-Altman analyses and Wilcoxon tests, respectively. RESULTS: Fourteen patients, 11 females (79%) aged 44 (41-50) years, underwent cardiac MRI. For the first and second readings, respectively, EAT volume was 86 (78-95) cm3 and 85 (79-91) cm3 at systole and 82 (74-95) cm3 and 81 (75-94) cm3 at diastole for R1, and 89 (79-99) cm3 and 93 (84-98) cm3 at systole and 92 (85-103) cm3 and 93 (82-94) cm3 at diastole for R2. R1 had the best reproducibility at diastole (bias 0.3 cm3, standard deviation of the differences (SD) 3.3 cm3). R2 had the worst reproducibility at diastole (bias 3.9 cm3, SD 12.1 cm3). The only significant difference between systole and diastole was at the first reading by R1 (p = 0.016). The greatest bias was that of inter-reader reproducibility at diastole (-9.4 cm3). CONCLUSIONS: Reproducibility was within clinically acceptable limits in most instances.

Development and Validation of an AI-driven Mammographic Breast Density Classification Tool Based on Radiologist Consensus.

Mammographic breast density (BD) is commonly visually assessed using the Breast Imaging Reporting and Data System (BI-RADS) four-category scale. To overcome inter- and intraobserver variability of visual assessment, the authors retrospectively developed and externally validated a software for BD classification based on convolutional neural networks from mammograms obtained between 2017 and 2020. The tool was trained using the majority BD category determined by seven board-certified radiologists who independently visually assessed 760 mediolateral oblique (MLO) images in 380 women (mean age, 57 years ± 6 [SD]) from center 1; this process mimicked training from a consensus of several human readers. External validation of the model was performed by the three radiologists whose BD assessment was closest to the majority (consensus) of the initial seven on a dataset of 384 MLO images in 197 women (mean age, 56 years ± 13) obtained from center 2. The model achieved an accuracy of 89.3% in distinguishing BI-RADS a or b (nondense breasts) versus c or d (dense breasts) categories, with an agreement of 90.4% (178 of 197 mammograms) and a reliability of 0.807 (Cohen κ) compared with the mode of the three readers. This study demonstrates accuracy and reliability of a fully automated software for BD classification. Keywords: Mammography, Breast, Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms Supplemental material is available for this article. © RSNA, 2022.

Evaluating the Performance of a Convolutional Neural Network Algorithm for Measuring Thoracic Aortic Diameters in a Heterogeneous Population.

The purpose of this work was to assess the performance of a convolutional neural network (CNN) for automatic thoracic aortic measurements in a heterogeneous population. From June 2018 to May 2019, this study retrospectively analyzed 250 chest CT scans with or without contrast enhancement and electrocardiographic gating from a heterogeneous population with or without aortic pathologic findings. Aortic diameters at nine locations and maximum aortic diameter were measured manually and with an algorithm (Artificial Intelligence Rad Companion Chest CT prototype, Siemens Healthineers) by using a CNN. A total of 233 examinations performed with 15 scanners from three vendors in 233 patients (median age, 65 years [IQR, 54-72 years]; 144 men) were analyzed: 68 (29%) without pathologic findings, 72 (31%) with aneurysm, 51 (22%) with dissection, and 42 (18%) with repair. No evidence of a difference was observed in maximum aortic diameter between manual and automatic measurements (P = .48). Overall measurements displayed a bias of -1.5 mm and a coefficient of repeatability of 8.0 mm at Bland-Altman analyses. Contrast enhancement, location, pathologic finding, and positioning inaccuracy negatively influenced reproducibility (P < .003). Sites with dissection or repair showed lower agreement than did sites without. The CNN performed well in measuring thoracic aortic diameters in a heterogeneous multivendor CT dataset. Keywords: CT, Vascular, Aorta © RSNA, 2022.

CT-derived epicardial adipose tissue density: Systematic review and meta-analysis.

PURPOSE: The aim of our work was to systematically review and meta-analyze epicardial adipose tissue (EAT) density values reported in literature, assessing potential correlations of EAT density with segmentation thresholds and other technical and clinical variables. METHOD: A systematic search was performed, aiming for papers reporting global EAT density values in Hounsfield Units (HU) in patients undergoing chest CT for any clinical indication. After screening titles, abstract and full text of each retrieved work, studies reporting mean and standard deviation for EAT density were ultimately included. Technical, clinical and EAT data were extracted, and divided into subgroups according to clinical conditions of reported subjects. Pooled density analyses were performed both overall and for subgroups according to clinical conditions. Metaregression analyses were done to appraise the impact of clinical and technical variables on EAT volume. RESULTS: Out of 152 initially retrieved works, 13 were ultimately included, totaling for 7683 subjects. EAT density showed an overall pooled value of -85.86 HU (95% confidence interval [95% CI] -91.84, -79.89 HU), being -86.40 HU (95% CI -112.69, -60.12 HU) in healthy subjects and -80.71 HU (95% CI -87.43, -73.99 HU) in patients with coronary artery disease. EAT volume and lower and higher segmentation thresholds were found to be significantly correlated with EAT density (p = 0.044, p < 0.001 and p< 0.001 respectively). CONCLUSIONS: Patients with coronary artery disease appear to present with higher EAT density values, while the correlations observed at metaregression highlight the need for well-established, shared thresholds for EAT segmentation.

Prospective Evaluation of the First Integrated Positron Emission Tomography/Dual-Energy Computed Tomography System in Patients With Lung Cancer.

PURPOSE: The aim of this pilot study was to prospectively evaluate the first integrated positron emission tomography (PET)/dual-energy computed tomography (DECT) system performance in patients with non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: In this single-center, prospective trial, consecutive patients with NSCLC referred for a PET study between May 2017 and June 2018 were enrolled. All patients received contrast-enhanced imaging on a clinical PET/DECT system. Data analysis included PET-based standard uptake values (SUVmax) and DECT-based iodine densities of tumor masses, lymph nodes, and distant metastases. Results were analyzed using correlation tests and receiver operating characteristics curves. RESULTS: The study population was composed of 21 patients (median age 62 y, 14 male patients). A moderate positive correlation was found between iodine density values (2.2 mg/mL) and SUVmax (10.5) in tumor masses (ρ=0.53, P<0.01). Iodine density values (2.3 mg/mL) and SUVmax (5.4) of lymph node metastases showed a weak positive correlation (ρ=0.23, P=0.14). In addition, iodine quantification analysis provided no added value in differentiating between pathologic and nonpathologic lymph nodes with an area under the curve (AUC) of 0.55 using PET-based SUVmax as the reference standard. A weak positive correlation was observed between iodine density (2.2 mg/mL) and SUVmax in distant metastases (14.9, ρ=0.23, P=0.52). CONCLUSIONS: The application of an integrated PET/DECT system in lung cancer might provide additional insights in the assessment of tumor masses. However, the added value of iodine density quantification for the evaluation of lymph nodes and distant metastases seems limited.

Artificial Intelligence Applied to Chest X-ray for Differential Diagnosis of COVID-19 Pneumonia.

We assessed the role of artificial intelligence applied to chest X-rays (CXRs) in supporting the diagnosis of COVID-19. We trained and cross-validated a model with an ensemble of 10 convolutional neural networks with CXRs of 98 COVID-19 patients, 88 community-acquired pneumonia (CAP) patients, and 98 subjects without either COVID-19 or CAP, collected in two Italian hospitals. The system was tested on two independent cohorts, namely, 148 patients (COVID-19, CAP, or negative) collected by one of the two hospitals (independent testing I) and 820 COVID-19 patients collected by a multicenter study (independent testing II). On the training and cross-validation dataset, sensitivity, specificity, and area under the curve (AUC) were 0.91, 0.87, and 0.93 for COVID-19 versus negative subjects, 0.85, 0.82, and 0.94 for COVID-19 versus CAP. On the independent testing I, sensitivity, specificity, and AUC were 0.98, 0.88, and 0.98 for COVID-19 versus negative subjects, 0.97, 0.96, and 0.98 for COVID-19 versus CAP. On the independent testing II, the system correctly diagnosed 652 COVID-19 patients versus negative subjects (0.80 sensitivity) and correctly differentiated 674 COVID-19 versus CAP patients (0.82 sensitivity). This system appears promising for the diagnosis and differential diagnosis of COVID-19, showing its potential as a second opinion tool in conditions of the variable prevalence of different types of infectious pneumonia.

Dual-energy CT performance in acute pulmonary embolism: a meta-analysis.

OBJECTIVES: To evaluate the diagnostic performance of dual-energy computed tomography (DECT) with regard to its post-processing techniques, namely linear blending (LB), iodine maps (IM), and virtual monoenergetic (VM) reconstructions, in diagnosing acute pulmonary embolism (PE). METHODS: This meta-analysis was conducted according to PRISMA. A systematic search on MEDLINE and EMBASE was performed in December 2019, looking for articles reporting the diagnostic performance of DECT on a per-patient level. Diagnostic performance meta-analyses were conducted grouping study parts according to DECT post-processing methods. Correlations between radiation or contrast dose and publication year were appraised. RESULTS: Seventeen studies entered the analysis. Only lobar and segmental acute PE were considered, subsegmental acute PE being excluded from analysis due to data heterogeneity or lack of data. LB alone was assessed in 6 study parts accounting for 348 patients, showing a pooled sensitivity of 0.87 and pooled specificity of 0.93. LB and IM together were assessed in 14 study parts accounting for 1007 patients, with a pooled sensitivity of 0.89 and pooled specificity of 0.90. LB, IM, and VM together were assessed in 2 studies (for a total 144 patients) and showed a pooled sensitivity of 0.90 and pooled specificity of 0.90. The area under the curve for LB alone, and LB together with IM was 0.93 (not available for studies using LB, IM and VM because of paucity of data). Radiation and contrast dose did not decrease with increasing year of publication. CONCLUSIONS: Considering the published performance of single-energy CT in diagnosing acute PE, either dual-energy or single-energy computed tomography can be comparably used for the detection of acute PE. KEY POINTS: • Dual-energy CT displayed pooled sensitivity and specificity of 0.87 and 0.93 for linear blending alone, 0.89 and 0.90 for linear blending and iodine maps, and 0.90 and 0.90 for linear blending iodine maps, and virtual monoenergetic reconstructions. • The performance of dual-energy CT for patient management is not superior to that reported in literature for single-energy CT (0.83 sensitivity and 0.96 specificity). • Dual-energy CT did not yield substantial advantages in the identification of patients with acute pulmonary embolism compared to single-energy techniques.

Right and left ventricle native T1 mapping in systolic phase in patients with congenital heart disease.

BACKGROUND: T1 mapping is emerging as a powerful tool in cardiac magnetic resonance (CMR) to evaluate diffuse fibrosis. However, right ventricular (RV) T1 mapping proves difficult due to the limited wall thickness in diastolic phase. Several studies focused on systolic T1 mapping, albeit only on the left ventricle (LV). PURPOSE: To estimate intra- and inter-observer variability of native T1 (nT1) mapping of the RV, and its correlations with biventricular and pulmonary function in patients with congenital heart disease (CHD). MATERIAL AND METHODS: In this retrospective, observational, cross-sectional study we evaluated 36 patients with CHD, having undergone CMR on a 1.5-T scanner. LV and RV functional evaluations were performed. A native modified look-locker inversion recovery short-axis sequence was acquired in the systolic phase. Intra- and inter-reader reproducibility were reported as complement to 100% of the ratio between coefficient of reproducibility and mean. Spearman ρ and Mann-Whitney U-test were used to compare distributions. RESULTS: Intra- and inter-reader reproducibility was 84% and 82%, respectively. Median nT1 was 1022 ms (interquartile range [IQR] 1108-972) for the RV and 947 ms (IQR 986-914) for the LV. Median RV-nT1 was 1016 ms (IQR 1090-1016) in patients with EDVI ≤100 mL/m2 and 1100 ms (IQR 1113-1100) in patients with EDVI >100 mL/m2 (P = 0.049). A significant negative correlation was found between RV ejection fraction and RV-nT1 (ρ = -0.284, P = 0.046). CONCLUSION: Systolic RV-nT1 showed a high reproducibility and a negative correlation with RV ejection fraction, potentially reflecting an adaptation of the RV myocardium to pulmonary valve/conduit (dys)-function.

Diagnosis of left atrial appendage thrombus in patients with atrial fibrillation: delayed contrast-enhanced cardiac CT.

OBJECTIVES: The current reference standard for diagnosing LAA thrombi is transesophageal echocardiography (TEE), a semi-invasive technique. We aimed to devise an optimal protocol for cardiac computed tomography (CCT) in diagnosing left atrial appendage (LAA) thrombus in patients with atrial fibrillation (AF), using TEE as reference standard. METHODS: Two hundred sixty consecutive patients referred for radiofrequency ablation for AF were prospectively enrolled. All patients underwent CCT and TEE within 2 hours. The CCT protocol included one standard angiographic phase and three delayed acquisitions at 1-, 3-, and 6-min after contrast injection. Thrombi were defined as persisting defects at 6-min delayed acquisition. RESULTS: TEE demonstrated spontaneous contrast in 52 (20%) patients and thrombus in 10 (4%). In 63 patients (24%), CCT demonstrated LAA early filling defects at angiographic phase. Among them, 15 (6%) had a persistent defect at 1-min, 12 (5%) at 3-min, and 10 (4%) at 6-min. All 10 thrombi diagnosed on TEE were correctly identified by delayed CCT, without any false positives. For all phases, sensitivity and negative predictive were 100%. Specificity increased from 79% for the angiographic phase to 100% at 6-min. Positive predictive value increased from 16% to 100%. Estimated radiation exposure was 2.08 ± 0.76 mSv (mean ± standard deviation) for the angiographic phase and 0.45 ± 0.23 mSv for each delayed phase. CONCLUSION: A CCT protocol adding a 6-min delayed phase to the angiographic phase can be considered optimized for the diagnosis of LAA thrombi, with a low radiation dose. KEY POINTS: • In patients with persistent atrial fibrillation referred for ablation procedures, a cardiac CT examination comprising an angiographic-phase acquisition and, in case of filling defects, a 6-min delayed phase may help reduce the need for transesophageal echocardiography. • Cardiac CT would provide morphological and volumetric data, along with the potential to exclude the presence of thrombi in the left atrial appendage.

Repaired Congenital Heart Disease in Older Children and Adults: Up-to-Date Practical Assessment and Characteristic Imaging Findings.

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.

Machine Learning and Deep Neural Networks Applications in Computed Tomography for Coronary Artery Disease and Myocardial Perfusion.

During the latest years, artificial intelligence, and especially machine learning (ML), have experienced a growth in popularity due to their versatility and potential in solving complex problems. In fact, ML allows the efficient handling of big volumes of data, allowing to tackle issues that were unfeasible before, especially with deep learning, which utilizes multilayered neural networks. Cardiac computed tomography (CT) is also experiencing a rise in examination numbers, and ML might help handle the increasing derived information. Moreover, cardiac CT presents some fields wherein ML may be pivotal, such as coronary calcium scoring, CT angiography, and perfusion. In particular, the main applications of ML involve image preprocessing and postprocessing, and the development of risk assessment models based on imaging findings. Concerning image preprocessing, ML can help improve image quality by optimizing acquisition protocols or removing artifacts that may hinder image analysis and interpretation. ML in image postprocessing might help perform automatic segmentations and shorten examination processing times, also providing tools for tissue characterization, especially concerning plaques. The development of risk assessment models from ML using data from cardiac CT could aid in the stratification of patients who undergo cardiac CT in different risk classes and better tailor their treatment to individual conditions. While ML is a powerful tool with great potential, applications in the field of cardiac CT are still expanding, and not yet routinely available in clinical practice due to the need for extensive validation. Nevertheless, ML is expected to have a big impact on cardiac CT in the near future.

Novel imaging biomarkers: epicardial adipose tissue evaluation.

Epicardial adipose tissue (EAT) is a metabolically activated beige adipose tissue, non-homogeneously surrounding the myocardium. Physiologically, EAT regulates toxic fatty acids, protects the coronary arteries against mechanical strain, regulates proinflammatory cytokines, stimulates the production of nitric oxide, reduces oxidative stress, and works as a thermogenic source against hypothermia. Conversely, EAT has pathologic paracrine interactions with the surrounded vessels, and might favour the onset of atrial fibrillation. In addition, initial atherosclerotic lesions can promote inflammation and trigger the EAT production of cytokines increasing vascular inflammation, which, in turn, may help the development of collateral vessels but also of self-stimulating, dysregulated inflammatory process, increasing coronary artery disease severity. Variations in EAT were also linked to metabolic syndrome. Echocardiography first estimated EAT measuring its thickness on the free wall of the right ventricle but does not allow accurate volumetric EAT estimates. Cardiac CT (CCT) and cardiac MR (CMR) allow for three-dimensional EAT estimates, the former showing higher spatial resolution and reproducibility but being limited by radiation exposure and long segmentation times, the latter being radiation-free but limited by lower spatial resolution and reproducibility, higher cost, and difficulties for obese patients. EAT radiodensity at CCT could to be related to underlying metabolic processes. The correlation between EAT and response to certain pharmacological therapies has also been investigated, showing promising results. In the future, semi-automatic or fully automatic techniques, machine/deep-learning methods, if validated, will facilitate research for various EAT measures and may find a place in CCT/CMR reporting.

Pulmonary Insufficiency: Advantage of Pulmonary Regurgitation Volume Versus Pulmonary Regurgitation Fraction in a Congenital Heart Disease Mixed Population.

OBJECTIVE: The objective of this study was to compare the use of pulmonary regurgitation volume (PRV) or indexed PRV (PRVi) with that of pulmonary regurgitation fraction (PRF) in the assessment of patients with pulmonary regurgitation (PR) undergoing cardiac magnetic resonance (CMR) imaging. MATERIALS AND METHODS: CMR of 176 patients with PR were retrospectively evaluated. Their right ventricular diastolic (end-diastolic volume index [EDVi]) and systolic (end-systolic volume index) volume indexes, stroke volume, and ejection fraction were obtained from cine CMR sequences, whereas phase-contrast flow sequences were analyzed to obtain PRV, PRVi, and PRF. Patients were divided into subgroups, according to underlying pathology and according to PR severity. Correlations between PRV or PRF and RV parameters were studied through Spearman ρ, both in the main group and subgroups. Follow-up examinations were analyzed, and correlations between PRV or PRF from the first CMR examination and volume data from the second were calculated. RESULTS: Tetralogy of Fallot was the main setting of PR (98/179). Overall, EDVi strongly correlates with PRV (ρ=0.592, P<0.001) than with PRF (ρ=0.522, P<0.001), and end-systolic volume index strongly correlates with PRV (ρ=0.454, P<0.001) and PRF (ρ=0.406, P <0.001). As regards subgroup analysis, in moderate or severe PR patients, EDVi strongly correlates (P=0.043) with PRV (ρ=0.499, P<0.001) than with PRF (ρ=0.317, P<0.001). Follow-up EDVi correlates with PRV (ρ=0.450, P=0.031), but not with PRF. CONCLUSIONS: Especially when assessing moderate to severe PR, PRV and PRVi may be better indicators of right ventricular dysfunction than PRF. Moreover, PRV may be a predictor of worsening RV dilation.