Left atrial remodeling and voltage-guided ablation outcome in obese patients with persistent atrial fibrillation.

Background: Obesity is a risk factor for atrial fibrillation (AF). Data regarding left atrial (LA) remodeling in obese patients are scarce. Whether obesity favors AF recurrence after catheter ablation (CA) is still controversial. We assessed the distribution of epicardial atrial fat on computed tomography (CT), LA bipolar voltage, low-voltage zone (LVZ) extent, and the outcome of voltage-guided ablation of persistent AF in obese and non-obese patients. Methods: A total of 139 patients with persistent AF undergoing a first voltage-guided ablation were enrolled and divided into two groups: 74 were non-obese and 65 were obese. Epicardial adipose tissue (EAT) was assessed on a CT scanner. LA endocardial voltage maps were obtained using a 3D mapping system in sinus rhythm. LVZ was defined as a bipolar peak-to-peak voltage amplitude <0.5 mV. Results: LA volume, voltage, and EAT amount were similar in the two groups. LVZ was less frequent in obese patients [12 (18.8%) vs. 26 (35.1%), p = 0.05], particularly on the anterior wall. The posterior and lateral EATs were correlated with posterior and lateral LVZ extent, respectively, in obese patients. After 36 months of follow-up, the AF-free survival rate was similar. Lateral EAT [odds ratio (OR) 1.21, 95% confidence interval (CI) 1-1.4, p = 0.04] and P-wave duration (OR 1.03, 95% CI 1-1.05, p = 0.03), but not body mass index (BMI), were predictors of AF recurrence after CA. Conclusion: In obese patients, LVZ was less marked than in non-obese patients with similar LA volumes, voltage, and EAT amounts. In obese patients, posterior and lateral EATs were correlated with posterior and lateral LVZ extents. Obese patients had a similar and favorable 36-month outcome after AF ablation. BMI was not predictive of AF recurrence.

Survival and response to pulmonary vasodilator therapies in patients with chronic obstructive pulmonary disease and pulmonary vascular phenotype.

BACKGROUND: The aim of the study was to describe and investigate the effect of pulmonary arterial hypertension (PAH) therapies in a cohort of patients with severe precapillary pulmonary hypertension (PH) associated with chronic obstructive pulmonary disease (COPD; PH-COPD), and to assess factors predictive of treatment response and mortality. MATERIAL AND METHODS: We retrospectively included patients with severe incident PH-COPD who received PAH therapy and underwent RHC at diagnosis and on treatment. RESULTS: From 2015 to 2022, 35 severe PH-COPD patients, with clinical features of pulmonary vascular phenotype, were included. Seventeen (48.5%) patients were treated with combined PAH therapy. PAH therapy led to a significant improvement in hemodynamics (PVR -3.5 Wood Units (-39.3%); p < 0.0001), and in the simplified four-strata risk-assessment score, which improved by at least one category in 21 (60%) patients. This effect was more pronounced in patients on dual therapy. Kaplan-Meier estimated survival rates at 1, 3 and 5 years were 94%, 65% and 42% respectively. Univariate analysis showed a significant reduction in survival in patients with a higher simplified risk score at follow-up (Hazard ratio (HR) 2.88 [1.16-7.15]; p = 0.02). Hypoxemia <50 mmHg was correlated to mortality in multivariate analysis (HR 4.33 [1.08-17.42]; p = 0.04). CONCLUSIONS: Our study confirms the poor prognosis of patients with COPD and a pulmonary vascular phenotype and the potential interest of combined PAH therapy in this population, with good tolerability and greater clinical and hemodynamic improvement than monotherapy. Using the simplified risk score during follow-up could be of interest in this population.

Impact of a reduced iodine load with deep learning reconstruction on abdominal MDCT.

To evaluate the impact of a reduced iodine load using deep learning reconstruction (DLR) on the hepatic parenchyma compared to conventional iterative reconstruction (hybrid IR) and its consequence on the radiation dose and image quality. This retrospective monocentric intraindividual comparison study included 66 patients explored at the portal phase using different multidetector computed tomography parameters: Group A, hybrid IR algorithm (hybrid IR) and a nonionic low-osmolality contrast agent (350 mgI/mL); Group B, DLR algorithm (DLR) and a nonionic iso-osmolality contrast agent (270 mgI/mL). We recorded the attenuation of the liver parenchyma, image quality, and radiation dose parameters. The mean hounsfield units (HU) value of the liver parenchyma was significantly lower in group B, at 105.9 ± 10.9 HU versus 118.5 ± 14.6 HU in group A. However, the 90%IC of mean liver attenuation in the group B (DLR) was between 100.8 HU and 109.3 HU. The signal-to-noise ratio of the liver parenchyma was significantly higher on DLR images, increasing by 56%. However, for both the contrast-to-noise ratio (CNR) and CNR liver/PV no statistical difference was found, even if the CNR liver/PV ratio was slightly higher for group A. The mean dose-length product and computed tomography dose index volume values were significantly lower with DLR, corresponding to a radiation dose reduction of 36% for the DLR. Using a DLR algorithm for abdominal multidetector computed tomography with a low iodine load can provide sufficient enhancement of the liver parenchyma up to 100 HU in addition to the advantages of a higher image quality, a better signal-to-noise ratio and a lower radiation dose.

Deep Learning to Classify AL versus ATTR Cardiac Amyloidosis MR Images.

The aim of this work was to compare the classification of cardiac MR-images of AL versus ATTR amyloidosis by neural networks and by experienced human readers. Cine-MR images and late gadolinium enhancement (LGE) images of 120 patients were studied (70 AL and 50 TTR). A VGG16 convolutional neural network (CNN) was trained with a 5-fold cross validation process, taking care to strictly distribute images of a given patient in either the training group or the test group. The analysis was performed at the patient level by averaging the predictions obtained for each image. The classification accuracy obtained between AL and ATTR amyloidosis was 0.750 for cine-CNN, 0.611 for Gado-CNN and between 0.617 and 0.675 for human readers. The corresponding AUC of the ROC curve was 0.839 for cine-CNN, 0.679 for gado-CNN (p < 0.004 vs. cine) and 0.714 for the best human reader (p < 0.007 vs. cine). Logistic regression with cine-CNN and gado-CNN, as well as analysis focused on the specific orientation plane, did not change the overall results. We conclude that cine-CNN leads to significantly better discrimination between AL and ATTR amyloidosis as compared to gado-CNN or human readers, but with lower performance than reported in studies where visual diagnosis is easy, and is currently suboptimal for clinical practice.

Classification of Cardiomyopathies from MR Cine Images Using Convolutional Neural Network with Transfer Learning.

The automatic classification of various types of cardiomyopathies is desirable but has never been performed using a convolutional neural network (CNN). The purpose of this study was to evaluate currently available CNN models to classify cine magnetic resonance (cine-MR) images of cardiomyopathies. METHOD: Diastolic and systolic frames of 1200 cine-MR sequences of three categories of subjects (395 normal, 411 hypertrophic cardiomyopathy, and 394 dilated cardiomyopathy) were selected, preprocessed, and labeled. Pretrained, fine-tuned deep learning models (VGG) were used for image classification (sixfold cross-validation and double split testing with hold-out data). The heat activation map algorithm (Grad-CAM) was applied to reveal salient pixel areas leading to the classification. RESULTS: The diastolic-systolic dual-input concatenated VGG model cross-validation accuracy was 0.982 ± 0.009. Summed confusion matrices showed that, for the 1200 inputs, the VGG model led to 22 errors. The classification of a 227-input validation group, carried out by an experienced radiologist and cardiologist, led to a similar number of discrepancies. The image preparation process led to 5% accuracy improvement as compared to nonprepared images. Grad-CAM heat activation maps showed that most misclassifications occurred when extracardiac location caught the attention of the network. CONCLUSIONS: CNN networks are very well suited and are 98% accurate for the classification of cardiomyopathies, regardless of the imaging plane, when both diastolic and systolic frames are incorporated. Misclassification is in the same range as inter-observer discrepancies in experienced human readers.

Impact of Morphotype on Image Quality and Diagnostic Performance of Ultra-Low-Dose Chest CT.

OBJECTIVES: The image quality of an Ultra-Low-Dose (ULD) chest CT depends on the patient's morphotype. We hypothesize that there is a threshold beyond which the diagnostic performance of a ULD chest CT is too degraded. This work assesses the influence of morphotype (Body Mass Index BMI, Maximum Transverse Chest Diameter MTCD and gender) on image quality and the diagnostic performance of a ULD chest CT. METHODS: A total of 170 patients from three prior prospective monocentric studies were retrospectively included. Renewal of consent was waived by our IRB. All the patients underwent two consecutive unenhanced chest CT acquisitions with a full dose (120 kV, automated tube current modulation) and a ULD (135 kV, fixed tube current at 10 mA). Image noise, subjective image quality and diagnostic performance for nine predefined lung parenchyma lesions were assessed by two independent readers, and correlations with the patient's morphotype were sought. RESULTS: The mean BMI was 26.6 ± 5.3; 20.6% of patients had a BMI > 30. There was a statistically significant negative correlation of the BMI with the image quality (ρ = -0.32; IC95% = (-0.468; -0.18)). The per-patient diagnostic performance of ULD was sensitivity, 77%; specificity, 99%; PPV, 94% and NPV, 65%. There was no statistically significant influence of the BMI, the MTCD nor the gender on the per-patient and per-lesion diagnostic performance of a ULD chest CT, apart from a significant negative correlation for the detection of emphysema. CONCLUSIONS: Despite a negative correlation between the BMI and the image quality of a ULD chest CT, we did not find a correlation between the BMI and the diagnostic performance of the examination, suggesting a possible use of the ULD protocol in obese patients.

Evaluation of the female bladder neck and urethra using MRI with fiber tractography: Prospective study on a large cohort of continent women.

AIMS: To prospectively evaluate the performance of a last generation magnetic resonance imaging (MRI) device with tractography to identify the normal female urethral sphincters in terms of morphology and quantification on a large cohort of continent women. METHODS: We have recorded the data of 75 continent women who underwent a diffusion tensor imaging (DTI) sequence with fiber tractography during a pelvic MR examination. Three groups of age were analyzed in terms of color fiber tracking quality and quantitative parameters (fractional anisotropy [FA] and mean diffusibility [MD]). Statistical analysis was done for the qualitative assessment using weighted kappa statistics of Cohen and for the quantitative parameters using a non-parametric Kruskal-Wallis test. RESULTS: For all cases, fiber-tracking resulted in a satisfactory representation of the complexity of the orientation of the fibers. The interobserver concordance of qualitative data was substantial, calculated at 0.78 (confidence interval: 0.71-0.85). For FA, there was no statistically significant difference with the age between the three urethral segments (p > 0.05). However, we registered a significant difference inside each group between the different segments (p < 0.05), corresponding to different orientation of fibers. For MD, we have found a statistically significant difference both between levels inside each group and according the age, meaning a variation of the water mobility for each type of musculature and with age (p < 0.05). CONCLUSION: DTI with fiber tractography performed on a recent MR unit is a robust method for the three-dimensional visualization of the details and connections of the urethral female sphincters. Quantitative variations with age need to be considered.

Radiomics in the evaluation of lung nodules: Intrapatient concordance between full-dose and ultra-low-dose chest computed tomography.

PURPOSE: The purpose of this study was to retrospectively evaluate the quantitative and qualitative intrapatient concordance of pulmonary nodule risk assessment by commercially available radiomics software between full-dose (FD) chest-CT and ultra-low-dose (ULD) chest CT. MATERIALS AND METHODS: Between July 2013 and September 2015, 68 patients (52 men and16 women; mean age, 65.5±10.6 [SD] years; range: 35-87 years) with lung nodules≥5mm and<30mm who underwent the same day FD chest CT (helical acquisition; 120kV; automated tube current modulation) and ULD chest CT (helical acquisition; 135kV; 10mA fixed) were retrospectively included. Each nodule on each acquisition was assessed by a commercial radiomics software providing a similarity malignancy index (mSI), classifying it as "benign-like" (mSI<0.1); "malignant-like" (mSI>0.9) or "undetermined" (0.1≤mSI≤0.9). Intrapatient qualitative agreement was evaluated with weighted Cohen-Kappa test and quantitative agreement with intraclass correlation coefficient (ICC). RESULTS: Ninety-nine lung nodules with a mean size of 9.14±4.3 (SD) mm (range: 5-25mm) in 68 patients (mean 1.46 nodule per patient; range: 1-5) were assessed; mean mSI was 0.429±0.331 (SD) (range: 0.001-1) with FD chest CT (22/99 [22%] "benign-like", 67/99 [68%] "undetermined" and 10/99 [10%] "malignant-like") and mean mSI was 0.487±0.344 (SD) (range: 0.002-1) with ULD chest CT (20/99 [20%] "benign-like", 59/99 [60%] "undetermined" and 20/99 [20%] "malignant-like"). Qualitative and quantitative agreement of FD chest CT with ULD chest CT were "good" with Kappa value of 0.60 (95% CI: 0.46-0.74) and ICC of 0.82 (95% CI: 0.73-0.87), respectively. CONCLUSION: A good agreement in malignancy similarity index can be obtained between ULD chest CT and FD chest CT using radiomics software. However, further studies must be done with more case material to confirm our results and elucidate the diagnostic capabilities of radiomics software using ULD chest CT for lung nodule characterization by comparison with FD chest CT.

Deep Learning Supplants Visual Analysis by Experienced Operators for the Diagnosis of Cardiac Amyloidosis by Cine-CMR.

BACKGROUND: Diagnosing cardiac amyloidosis (CA) from cine-CMR (cardiac magnetic resonance) alone is not reliable. In this study, we tested if a convolutional neural network (CNN) could outperform the visual diagnosis of experienced operators. METHOD: 119 patients with cardiac amyloidosis and 122 patients with left ventricular hypertrophy (LVH) of other origins were retrospectively selected. Diastolic and systolic cine-CMR images were preprocessed and labeled. A dual-input visual geometry group (VGG ) model was used for binary image classification. All images belonging to the same patient were distributed in the same set. Accuracy and area under the curve (AUC) were calculated per frame and per patient from a 40% held-out test set. Results were compared to a visual analysis assessed by three experienced operators. RESULTS: frame-based comparisons between humans and a CNN provided an accuracy of 0.605 vs. 0.746 (p < 0.0008) and an AUC of 0.630 vs. 0.824 (p < 0.0001). Patient-based comparisons provided an accuracy of 0.660 vs. 0.825 (p < 0.008) and an AUC of 0.727 vs. 0.895 (p < 0.002). CONCLUSION: based on cine-CMR images alone, a CNN is able to discriminate cardiac amyloidosis from LVH of other origins better than experienced human operators (15 to 20 points more in absolute value for accuracy and AUC), demonstrating a unique capability to identify what the eyes cannot see through classical radiological analysis.

Acute Myopericarditis in a Patient With Mild SARS-CoV-2 Respiratory Infection.

Herein is presented a case of a 71-year-old woman with mild SARS-CoV-2 respiratory infection who experienced acute myopericarditis diagnosed using clinical, biological, and electrocardiogram data and cardiac magnetic resonance imaging. The presented case highlights the risk of cardiac involvement, even in the absence of severe respiratory COVID-19 infection. The mechanisms involved in acute myocardial injury in SARS-CoV-2 infection are not well known and requires further studies to determine whether it is related to direct myocardial damage by the virus or to a systemic condition.

Nous présentons le cas d'une femme de 71 ans qui présentait une infection respiratoire légère causée par le virus SRAS-CoV-2 et qui a subi une myopéricardite aiguë diagnostiquée à partir de données cliniques, biologiques et électrocardiographiques et d'un examen d'imagerie par résonance magnétique cardiaque. Ce cas met en lumière le risque d'atteinte cardiaque chez les patients atteints de COVID-19, même en l'absence d'infection respiratoire grave. On ne connaît pas bien les mécanismes qui participent à l'atteinte myocardique aiguë chez les patients infectés par le virus SRAS-CoV-2, et des recherches plus poussées sont nécessaires pour déterminer si cette atteinte est causée directement par le virus ou si elle est due à un trouble systémique.

SARS-CoV-2 Pneumonia in Hospitalized Asthmatic Patients Did Not Induce Severe Exacerbation.

BACKGROUND: Viral infections are known to exacerbate asthma in adults. Previous studies have found few patients with asthma among severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia cases. However, the relationship between SARS-CoV-2 infection and severe asthma exacerbation is not known. OBJECTIVE: To assess the frequency of asthma exacerbation in patients with asthma hospitalized for SARS-CoV-2 pneumonia and compare symptoms and laboratory and radiological findings in patients with and without asthma with SARS-CoV-2 pneumonia. METHODS: We included 106 patients between March 4 and April 6, 2020, who were hospitalized in the Chest Diseases Department of Strasbourg University Hospital; 23 had asthma. To assess the patients' asthma status, 3 periods were defined: the last month before the onset of COVID-19 symptoms (p1), prehospitalization (p2), and during hospitalization (p3). Severe asthma exacerbations were defined according to Global INitiative for Asthma guidelines during p1 and p2. During p3, we defined severe asthma deterioration as the onset of breathlessness and wheezing requiring systemic corticosteroids and inhaled ß2 agonist. RESULTS: We found no significant difference between patients with and without asthma in terms of severity (length of stay, maximal oxygen flow needed, noninvasive ventilation requirement, and intensive care unit transfer); 52.2% of the patients with asthma had Global INitiative for Asthma step 1 asthma. One patient had a severe exacerbation during p1, 2 patients during p2, and 5 patients were treated with systemic corticosteroids and inhaled ß2 agonist during p3. CONCLUSIONS: Our results demonstrate that patients with asthma appeared not to be at risk for severe SARS-CoV-2 pneumonia. Moreover, SARS-CoV-2 pneumonia did not induce severe asthma exacerbation.

CT lung lesions as predictors of early death or ICU admission in COVID-19 patients.

OBJECTIVE: The main objective of this study was to investigate the prognostic value of early systematic chest computed tomography (CT) with quantification of lung lesions in coronavirus disease 2019 (COVID-19) patients. METHODS: We studied 572 patients diagnosed with COVID-19 (confirmed using polymerase chain reaction) for whom a chest CT was performed at hospital admission. Visual quantification was used to classify patients as per the percentage of lung parenchyma affected by COVID-19 lesions: normal CT, 0-10%, 11-25%, 26-50%, 51-75% and >75%. The primary endpoint was severe disease, defined by death or admission to the intensive care unit in the 7 days following first admission. RESULTS: The mean patient age was 66.0 ± 16.0 years, and 343/572 (60.0%) were men. The primary endpoint occurred in 206/572 patients (36.0%). The extent of lesions on initial CT was independently associated with prognosis (odds ratio = 2.35, 95% confidence interval 1.24-4.46; p < 0.01). Most patients with lung involvement >50% (66/95, 69.5%) developed severe disease compared to patients with lung involvement of 26-50% (70/171, 40.9%) and ≤25% (70/306, 22.9%) (p < 0.01 and p < 0.01, respectively). None of the patients with normal CT (0/14) had severe disease. CONCLUSION: Chest CT findings at admission are associated with outcome in COVID-19 patients.

Acute Pulmonary Embolism in Patients with COVID-19 at CT Angiography and Relationship to d-Dimer Levels.

Online supplemental material is available for this article.

Wide-volume versus helical acquisition in unenhanced chest CT: prospective intra-patient comparison of diagnostic accuracy and radiation dose in an ultra-low-dose setting.

OBJECTIVES: Diagnostic performance and potential radiation dose reduction of wide-area detector CT sequential acquisition ("wide-volume" acquisition (WV)) in unenhanced chest examination are unknown. This study aims to assess the image quality, the diagnostic performance, and the radiation dose reduction of WV mode compared with the classical helical acquisition for lung parenchyma analysis in an ultra-low-dose (ULD) protocol. METHODS: After Institutional Review Board Approval and written informed consent, 64 patients (72% men; 67.6 ± 9.7 years old; BMI 26.1 ± 5.3 kg/m2) referred for a clinically indicated unenhanced chest CT were prospectively included. All patients underwent, in addition to a standard helical acquisition (120 kV, automatic tube current modulation), two ULD acquisitions (135 kV, fixed tube current at 10 mA): one in helical mode and one in WV mode. Image noise, subjective image quality (5-level Likert scale), and diagnostic performance for the detection of 9 predetermined parenchymal abnormalities were assessed by two radiologists and compared using the chi-square or Fisher non-parametric tests. RESULTS: Subjective image quality (4.2 ± 0.7 versus 4.2 ± 0.8, p = 0.56), image noise (41.7 ± 8 versus 40.9 ± 8.7, p = 0.3), and diagnostic performance were equivalent between ULD WV and ULD helical. Radiation dose was significantly lower for the ULD WV acquisition (mean dose-length product 14.1 ± 1.3 mGy cm versus 15.8 ± 1.3, p < 0.0001). CONCLUSION: An additional 11% dose reduction is achieved with the WV mode in ULD chest CT with fixed tube current, with equivalent image quality and diagnostic performance when compared with the helical acquisition. KEY POINTS: • Image quality and diagnostic performance of ultra-low-dose unenhanced chest CT are identical between wide-volume mode and the reference helical acquisition. • Wide-volume mode allows an additional radiation dose reduction of 11% (mean dose-length product 14.1 ± 1.3 mGy cm versus 15.8 ± 1.3, p < 0.0001).

Prospective evaluation of ultra-low-dose contrast-enhanced 100-kV abdominal computed tomography with tin filter: effect on radiation dose reduction and image quality with a third-generation dual-source CT system.

OBJECTIVES: To investigate the radiation dose exposure, image quality, and diagnostic performance of enhanced 100-kVp abdominopelvic single-energy CT protocol with tin filter (TF). METHODS: Ninety-three consecutive patients referred for a single-phase enhanced abdominopelvic CT were prospectively included after informed consent. They underwent in addition to a standard protocol (SP) an acquisition with TF. Both examinations were performed on a third-generation dual-source CT system (DSCT), in single energy, using automatic tube current modulation, identical pitch, and identical level of iterative reconstruction. Radiation metrics were compared. Size-specific dose estimates (SSDE), contrast to noise ratio (CNR), and figure of merit (FOM) were calculated. Diagnostic confidence for the assessment of a predetermined list of abdominal lesions was rated by two independent readers. RESULTS: The mean dose of the TF protocol was significantly lower (CDTI 1.56 ± 0.43 mGy vs. 8.13 ± 3.32, p < 0.001; SSDE 9.94 ± 3.08 vs. 1.93 ± 0.39, p < 0.001), with an effective dose close to 1 mSv (1.14 mSv ± 0.34; p < 0.001). TF group exhibited non-significant lower liver CNR (2.76 vs. 3.03, p = 0.56) and was more dose efficient (FOM 10.6 vs. 2.49/mSv, p < 0.001) in comparison to SP. The mean diagnostic confidence for visceral, bone, and peritoneal tumors was equivalent between both groups. CONCLUSIONS: Enhanced 100-kVp abdominopelvic CT acquired after spectral shaping with tin filtration can achieve similar diagnostic performance and CNR compared to a standard CT protocol, while reducing the radiation dose by 81%. KEY POINTS: • 100-kVp spectral filtration enables enhanced abdominal CT with high-dose efficiency. • The radiation dose reaches the 1-mSv range. • Predetermined abdominopelvic lesions can be assessed without impairing on diagnostic confidence.

320-row CT transcatheter aortic valve replacement planning with a single reduced contrast media bolus injection.

OBJECTIVE: To reduce the iodine load required for CT Transcatheter Aortic Valve Replacement (TAVR) planning on a 320-row scanner by acquiring the two CT TAVR steps (ECG-gated aortic root CTA and non-gated aorto-ilio-femoral CTA) within a single contrast media bolus injection. METHODS: 50 consecutive patients (82.6±6.9 years; 56% female) were prospectively enrolled and underwent a TAVR planning using a 320-row CT, with ECG-gated aortic root CTA immediately followed by a non-gated aorto-iliac acquisition, all within a single bolus of 40-70mL of Iohexol 350mgI/mL. The Iodine load, image quality, SNR, CNR and radiation dose were compared using a Mann-Whitney test to that of 24 consecutive patients (84.3±4.8 years, 58% female) previously imaged on a 64-row scanner with a conventional two-step protocol. RESULTS: Iodine load was reduced by 44%. All examinations were of diagnostic quality, with improvement of the aortic root CTA image quality (4.9±0.3 versus 4.6±0.5, p<0.01) and a non-significant decrease of the aorto-iliac CTA image quality (4.7±0.6 versus 4.9±0.3, p = 0.07). SNR and CNR were significantly improved in the aortic root CTA (14.0±5.3 and 10.4±4.5 versus 10.3±4.2 and 6.8±3.3, p<0.01 for both) and non-significantly higher in the aorto-iliac CTA (16.5±8.0 and 14.1±7.9 versus 14.7±5.5 and 12.5±5.0, p = 0.42 and p = 0.66). Total radiation dose was reduced by 32%. CONCLUSION: 320-row CT scanner enables a 44% reduction of iodine load in TAVR planning, while maintaining excellent aorto-ilio-femoral arterial enhancement and lowering radiation dose.

Computed Tomography Perfusion Measurements in Renal Lesions Obtained by Bayesian Estimation, Advanced Singular-Value Decomposition Deconvolution, Maximum Slope, and Patlak Models: Intermodel Agreement and Diagnostic Accuracy of Tumor Classification.

OBJECTIVES: The aims of this study were to evaluate the agreement of computed tomography (CT)-perfusion parameter values of the normal renal cortex and various renal tumors, which were obtained by different mathematical models, and to evaluate their diagnostic accuracy. MATERIALS AND METHODS: Perfusion imaging was performed prospectively in 35 patients to analyze 144 regions of interest of the normal renal cortex and 144 regions of interest of renal tumors, including 21 clear-cell renal cell carcinomas (RCC), 6 papillary RCCs, 5 oncocytomas, 1 chromophobe RCC, 1 angiomyolipoma with minimal fat, and 1 tubulocystic RCC. Identical source data were postprocessed and analyzed on 2 commercial software applications with the following implemented mathematical models: maximum slope, Patlak plot, standard singular-value decomposition (SVD), block-circulant SVD, oscillation-limited block-circulant SVD, and Bayesian estimation technique. Results for blood flow (BF), blood volume (BV), and mean transit time (MTT) were recorded. Agreement and correlation between pairs of models and perfusion parameters were assessed. Diagnostic accuracy was evaluated by receiver operating characteristic (ROC) analysis. RESULTS: Significant differences and poor agreement of BF, BV, and MTT values were noted for most of model comparisons in both the normal renal cortex and different renal tumors. The correlations between most model pairs and perfusion parameters ranged between good and perfect (Spearman ρ = 0.79-1.00), except for BV values obtained by Patlak method (ρ = 0.61-0.72). All mathematical models computed BF and BV values, which differed significantly between clear cell RCCs, papillary RCCs, and oncocytomas, which introduces them as useful diagnostic tests to differentiate between different histologic subgroups (areas under ROC curve, 0.83-0.99). The diagnostic accuracy to discriminate between clear-cell RCCs and the renal cortex was the lowest based on the Patlak plot model (area under ROC curve, 0.76); BF and BV values obtained by other algorithms did not differ significantly in their diagnostic accuracy. CONCLUSIONS: Quantitative perfusion parameters obtained from different mathematical models cannot be used interchangeably. Based on BF and BV estimates, all models are a useful tool in the differential diagnosis of kidney tumors, with the Patlak plot model yielding a significantly lower diagnostic accuracy.

A dual flip angle 3D bSSFP magnetization transfer-like method to differentiate between recent and old myocardial infarction.

BACKGROUND: Magnetic resonance imaging (MRI) tissue signal is modulated by magnetization transfer (MT) phenomena, intrinsically induced by balanced steady-state free precession (bSSFP) imaging. PURPOSE: To investigate the possible value of such a MT-like bSSFP approach in two clinical settings involving focal myocardial lesions highligthed by late gadolinium enhancement (LGE+): edema induced by recent myocardial infarction (MI) and fibrotic scar related to chronic infarction. MATERIALS AND METHODS: Population: 48 LGE + patients were studied: 26 with recent MI, 22 with chronic MI. 20 LGE-normal subjects were considered the control group. Field strength/sequence: Navigator-based short axis 3D-bSSFP sequences with 20° and 90° excitation flip angles were acquired (1.5T). ASSESSMENT: Pixel-wise normalized MT Ratio (nMTR) parametric images were calculated according to: nMTR = 100*(S20 -S90 *k)/S20 , with S20 and S90 signal intensity in 20° and 90° flip angle images and k = Blood20 /Blood90 as a normalization ratio. Statistical tests: analysis of variance (ANOVA), receiver operating characteristic (ROC) analysis. RESULTS: Overall normal myocardial nMTR was 50.2 ± 3.6%. In recent MI, nMTR values were significantly reduced in LGE + regions (-22.3 ± 9.9%, P < 0.0001). In cases of chronic infarct, nMTR was significantly increased in LGE + regions (14.2 ± 11.4%, P < 0.0001). Comparison between observed results and theoretical values obtained with the Freeman-Hill formula showed that most variations observed in MI are related to MT effects instead of relaxation effects. CONCLUSION: In contrast to LGE imaging, which may show a similar hyperenhancement in recent and old infarctions, nMTR imaging demonstrates an opposite pattern: decreased values for recent infarction and increased values for old infarction, thus allowing to discriminate between these two clinical conditions without gadolinium injection. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:798-808.

Magnetic resonance evaluation of cardiac thrombi and masses by T1 and T2 mapping: an observational study.

The purpose of this work was to evaluate CMR T1 and T2 mapping sequences in patients with intracardiac thrombi and masses in order to assess T1 and T2 relaxometry usefulness and to allow better etiological diagnosis. This observational study of patients scheduled for routine CMR was performed from September 2014 to August 2015. All patients referred to our department for a 1.5 T CMR were screened to participate. T1 mapping were acquired before and after Gadolinium injection; T2 mapping images were obtained before injection. 41 patients were included. 22 presented with cardiac thrombi and 19 with cardiac masses. The native T1 of thrombi was 1037 ± 152 ms (vs 1032 ± 39 ms for myocardium, p = 0.88; vs 1565 ± 88 ms for blood pool, p < 0.0001). T2 were 74 ± 13 ms (vs 51 ± 3 ms for myocardium, p < 0.0001; vs 170 ± 32 ms for blood pool, p < 0.0001). Recent thrombi had a native T1 shorter than old thrombi (911 ± 177 vs 1169 ± 107 ms, p = 0.01). The masses having a shorter T1 than the myocardium were lipomas (278 ± 29 ms), calcifications (621 ± 218 ms), and melanoma (736 ms). All other masses showed T1 values higher than myocardial T1, with T2 consistently >70 ms. T1 and T2 mapping CMR sequences can be useful and represent a new approach for the evaluation of cardiac thrombi and masses.