Pre-TAVI aortic annulus sizing: comparison between manual and semi-automated new generation software measurements in operators with different experience.

OBJECTIVES: Aim of the study is to compare manual and semi-automatic measurements for aortic annulus assessment among different operators. METHODS: Eighty patients who underwent TAVI were retrospectively enrolled. The measurements manually performed by an experienced reader for aortic annulus (minimum and maximum diameters, perimeter, area), annulus-to-coronary ostia distance and time needed for the whole evaluation, were collected. The same operator (observer 1) and two less experienced readers (observer 2 and 3, with >5 years and 1 year of experience, respectively) assessed the same measurements using a semi-automatic software. Differences between manual and semi-automatic measurements, reading time and suggested valves size derived by CT were compared. RESULTS: Very good correlations were found between manual and software-aided measurements for aortic annulus area and perimeter in comparison with standard measurements for the three readers (ICC range 0.81-0.98). Good correlations were found for the distance with coronary ostia(0.75-0.79). The same area-derived prosthesis size for manual and semi-automatic measurements was selected in 96% of cases for observer 1; very good correlations were also found for observer 2 and 3 (ICC = 0.89 and 0.88, respectively). Using semi-automatic measurements, the mean time needed for CT images was significantly lower for observers 1 and 2 (1.50 and 1.72versus 3.14 min), respectively. CONCLUSIONS: Pre-TAVI CT using semi-automatic software allows accurate and reproducible measurements, reducing reconstruction time up to 50% and is reliable even for operators with different experience. ADVANCES IN KNOWLEDGE: The use of semi-automatic dedicated software for CT in TAVI planning is reliable even for operators without long time experience and allows accurate and reproducible measurements improving pre-TAVI workflow.

Changing Paradigms in the Diagnosis of Ischemic Heart Disease by Multimodality Imaging.

Coronary artery disease (CAD) represents the most common cardiovascular disease, with high morbidity and mortality. Historically patients with chest pain of suspected coronary origin have been assessed with functional tests, capable to detect haemodynamic consequences of coronary obstructions through depiction of electrocardiographic changes, myocardial perfusion defects or regional wall motion abnormalities under stress condition. Stress echocardiography (SE), single-photon emission computed tomography (SPECT), positron emission tomography (PET) and cardiovascular magnetic resonance (CMR) represent the functional techniques currently available, and technical developments contributed to increased diagnostic performance of these techniques. More recently, cardiac computed tomography angiography (cCTA) has been developed as a non-invasive anatomical test for a direct visualisation of coronary vessels and detailed description of atherosclerotic burden. Cardiovascular imaging techniques have dramatically enhanced our knowledge regarding physiological aspects and myocardial implications of CAD. Recently, after the publication of important trials, international guidelines recognised these changes, updating indications and level of recommendations. This review aims to summarise current standards with main novelties and specific limitations, and a diagnostic algorithm for up-to-date clinical management is also proposed.

Feasibility of late gadolinium enhancement (LGE) in ischemic cardiomyopathy using 2D-multisegment LGE combined with artificial intelligence reconstruction deep learning noise reduction algorithm.

BACKGROUND: Despite the low spatial resolution of 2D-multisegment late gadolinium enhancement (2D-MSLGE) sequences, it may be useful in uncooperative patients instead of standard 2D single segmented inversion recovery gradient echo late gadolinium enhancement sequences (2D-SSLGE). The aim of the study is to assess the feasibility and comparison of 2D-MSLGE reconstructed with artificial intelligence reconstruction deep learning noise reduction (NR) algorithm compared to standard 2D-SSLGE in consecutive patients with ischemic cardiomyopathy (ICM). METHODS: Fifty-seven patients with known ICM referred for a clinically indicated CMR were enrolled in this study. 2D-MSLGE were reconstructed using a growing level of NR (0%,25%,50%,75%and 100%). Subjective image quality, signal to noise ratio (SNR) and contrast to noise ratio (CNR) were evaluated in each dataset and compared to standard 2D-SSLGE. Moreover, diagnostic accuracy, LGE mass and scan time were compared between 2D-MSLGE with NR and 2D-SSLGE. RESULTS: The application of NR reconstruction ≥50% to 2D-MSLGE provided better subjective image quality, CNR and SNR compared to 2D-SSLGE (p < 0.01). The best compromise in terms of subjective and objective image quality was observed for values of 2D-MSLGE 75%, while no differences were found in terms of LGE quantification between 2D-MSLGE versus 2D-SSLGE, regardless the NR applied. The sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 2D-MSLGE NR 75% were 87.77%,96.27%,96.13%,88.16% and 94.22%, respectively. Time of acquisition of 2D-MSLGE was significantly shorter compared to 2D-SSLGE (p < 0.01). CONCLUSION: When compared to standard 2D-SSLGE, the application of NR reconstruction to 2D-MSLGE provides superior image quality with similar diagnostic accuracy.

Quantitative Evaluation of COVID-19 Pneumonia Lung Extension by Specific Software and Correlation with Patient Clinical Outcome.

Lung infection named as COVID-19 is an infectious disease caused by the most recently discovered coronavirus 2 (SARS-CoV-2). CT (computed tomography) has been shown to have good sensitivity in comparison with RT-PCR, particularly in early stages. However, CT findings appear to not always be related to a certain clinical severity. The aim of this study is to evaluate a correlation between the percentage of lung parenchyma volume involved with COVID-19 infection (compared to the total lung volume) at baseline diagnosis and correlated to the patient's clinical course (need for ventilator assistance and or death). All patients with suspected COVID-19 lung disease referred to our imaging department for Chest CT from 24 February to 6 April 2020were included in the study. Specific CT features were assessed including the amount of high attenuation areas (HAA) related to lung infection. HAA, defined as the percentage of lung parenchyma above a predefined threshold of -650 (HAA%, HAA/total lung volume), was automatically calculated using a dedicated segmentation software. Lung volumes and CT findings were correlated with patient's clinical course. Logistic regressions were performed to assess the predictive value of clinical, inflammatory and CT parameters for the defined outcome. In the overall population we found an average infected lung volume of 31.4 ± 26.3% while in the subgroup of patients who needed ventilator assistance and who died as well as the patients who died without receiving ventilator assistance the volume of infected lung was significantly higher 41.4 ± 28.5 and 72.7 ± 36.2 (p < 0.001). In logistic regression analysis best predictors for ventilation and death were the presence of air bronchogram (p = 0.006), crazy paving (p = 0.007), peripheral distribution (p < 0.001), age (p = 0.002), fever at admission (p = 0.007), dyspnea (p = 0.002) and cardiovascular comorbidities (p < 0.001). In multivariable analysis, quantitative CT parameters and features added incremental predictive value beyond a model with only clinical parameters (area under the curve, 0.78 vs. 0.74, p = 0.02). Our study demonstrates that quantitative evaluation of lung volume involved by COVID-19 pneumonia helps to predict patient's clinical course.

Role of CMR Mapping Techniques in Cardiac Hypertrophic Phenotype.

Non-ischemic cardiomyopathies represent a heterogeneous group of myocardial diseases potentially leading to heart failure, life-threatening arrhythmias, and eventually death. Myocardial dysfunction is associated with different underlying pathological processes, ultimately inducing changes in morphological appearance. Thus, classification based on presenting morphological phenotypes has been proposed, i.e., dilated, hypertrophic, restrictive, and right ventricular cardiomyopathies. In light of the key diagnostic and prognostic role of morphological and functional features, cardiovascular imaging has emerged as key element in the clinical workflow of suspected cardiomyopathies, and above all, cardiovascular magnetic resonance (CMR) represents the ideal technique to be used: thanks to its physical principles, besides optimal spatial and temporal resolutions, incomparable contrast resolution allows to assess myocardial tissue abnormalities in detail. Traditionally, weighted images and late enhancement images after gadolinium-based contrast agent administration have been used to perform tissue characterization, but in the last decade quantitative assessment of pre-contrast longitudinal relaxation time (native T1), post-contrast longitudinal relaxation time (post-contrast T1) and transversal relaxation time (T2), all displayed with dedicated pixel-wise color-coded maps (mapping), has contributed to give precious knowledge insight, with positive influence of diagnostic accuracy and prognosis assessment, mostly in the setting of the hypertrophic phenotype. This review aims to describe the available evidence of the role of mapping techniques in the assessment of hypertrophic phenotype, and to suggest their integration in the routine CMR evaluation of newly diagnosed cardiomyopathies with increased wall thickness.

Submillisievert CT angiography for carotid arteries using wide array CT scanner and latest iterative reconstruction algorithm in comparison with previous generations technologies: Feasibility and diagnostic accuracy.

OBJECTIVES: To assess evaluability and diagnostic accuracy of a low dose CT angiography (CTA) protocol for carotid arteries using latest Iterative Reconstruction (IR) algorithm in comparison with standard 100 kVp protocol using previous generation CT and IR. MATERIALS AND METHODS: 105 patients, referred for CTA of the carotid arteries were prospectively enrolled in our study and underwent CTA with 80 kVp and latest IR algorithm (group 1). Data were retrospectively compared with 100 consecutive patients with similar examination indications that had previously undergone CTA of carotid arteries with a standard 100 kVp protocol and a first generation IR algorithm (group 2). Image quality was evaluated with a 4-point Likert-scale. For each exam CT number, image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) at level of common carotid artery (CCA), internal carotid artery (ICA) and at level of Circle of Willis and Effective Dose (ED) were evaluated. 62 Group 1 patients underwent a clinically indicated DSA and results were compared with CTA. RESULTS: No exams reported as not diagnostic. The overall mean CT number value of all arterial segments was above 450 HU in both groups. Significant lower noise, and higher SNR and CNR values were found in group 1 in comparison with group 2 despite the use of 80 kVp. In 62-group 1 patients studied by DSA, CTA showed in a segment-based analysis a sensitivity, negative predictive value and accuracy of 100%, 100% and 99% respectively. Mean ED in group 1 was 0.54 ±â€¯0.1 mSv with a dose reduction up to 86%. CONCLUSIONS: CTA for carotid arteries using latest IR algorithm allows to perform exams with submillisievert radiation exposure maintaining good image quality, overall evaluability and diagnostic accuracy.

Overall evaluability of low dose protocol for computed tomography angiography of thoracic aorta using 80 kV and iterative reconstruction algorithm using different concentration contrast media.

INTRODUCTION: Multidetector Computed Tomography Angiography (MDCTA) is presently the imaging modality of choice for aortic disease. However, the effective radiation dose and the risk related to the use of contrast agents associated with MDCTA is an issue of concern. Aim of this study was to assess image quality of a low dose ECG-gated MDCTA of thoracic aorta using different concentration contrast media without tailored injection protocol. METHODS: Two-hundred patients were randomised into four different scan protocols: Group A (Iodixanol 320 and 80 Kvp tube voltage), Group B (Iodixanol 320 and 100 Kvp tube voltage), Group C (Iomeprol 400 and 80 Kvp tube voltage) and Group D (Iomeprol 400 and 100 Kvp tube voltage). Image quality, noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and effective dose (ED) were compared among groups. RESULTS: No significant differences in image noise, SNR and CNR between groups with the same tube voltage. Significant differences in SNR and CNR were found among groups with 80 kV versus groups using 100 kV but without differences in terms of image quality. ED was significantly lower in groups with 80 kV. CONCLUSIONS: Multidetector Computed Tomography Angiography protocols using 80 kV and low concentration contrast media are feasible without need of tailored injection protocols.