Cesare Mantini

Coronary artery calcium score on low-dose computed tomography for lung cancer screening

AIM To evaluate the feasibility of coronary artery calcium score (CACS) on low-dose non-gated chest CT (ngCCT). METHODS Sixty consecutive individuals (30 males; 73 ± 7 years) scheduled for risk stratification by means of unenhanced ECG-triggered cardiac computed tomography (gCCT) underwent additional unenhanced ngCCT. All CT scans were performed on a 64-slice CT scanner (Somatom Sensation 64 Cardiac, Siemens, Germany). CACS was calculated using conventional methods/scores (Volume, Mass, Agatston) as previously described in literature. The CACS value obtained were compared. The Mayo Clinic classification was used to stratify cardiovascular risk based on Agatston CACS. Differences and correlations between the two methods were compared. A P-value < 0.05 was considered significant. RESULTS Mean CACS values were significantly higher for gCCT as compared to ngCCT (Volume: 418 ± 747 vs 332 ± 597; Mass: 89 ± 151 vs 78 ± 141; Agatston: 481 ± 854 vs 428 ± 776; P < 0.05). The correlation between the two values was always very high (Volume: r = 0.95; Mass: r = 0.97; Agatston: r = 0.98). Of the 6 patients with 0 Agatston score on gCCT, 2 (33%) showed an Agatston score > 0 in the ngCCT. Of the 3 patients with 1-10 Agatston score on gCCT, 1 (33%) showed an Agatston score of 0 in the ngCCT. Overall, 23 (38%) patients were reclassified in a different cardiovascular risk category, mostly (18/23; 78%) shifting to a lower risk in the ngCCT. The estimated radiation dose was significantly higher for gCCT (DLP 115.8 ± 50.7 vs 83.8 ± 16.3; Effective dose 1.6 ± 0.7 mSv vs 1.2 ± 0.2 mSv; P < 0.01). CONCLUSION CACS assessment is feasible on ngCCT; the variability of CACS values and the associated re-stratification of patients in cardiovascular risk groups should be taken into account.

Aortic valve bypass surgery in severe aortic valve stenosis: Insights from cardiac and brain magnetic resonance imaging

Objective To investigate and describe the distribution of aortic and cerebral blood flow (CBF) in patients with severe valvular aortic stenosis (AS) before and after aortic valve bypass (AVB) surgery. Methods We enrolled 10 consecutive patients who underwent AVB surgery for severe AS. Cardiovascular magnetic resonance imaging (CMR) and brain magnetic resonance imaging were performed as baseline before surgery and twice after surgery. Quantitative flow measurements were obtained using 1.5‐T magnetic resonance imaging (MRI) scanner phase‐contrast images of the ascending aorta, descending thoracic aorta (3 cm proximally and distally from the conduit‐to‐aorta anastomosis), and ventricular outflow portion of the conduit. The evaluation of CBF was performed using 3.0‐T MRI scanner arterial spin labeling (ASL) through sequences acquired at the gray matter, dorsal default‐mode network, and sensorimotor levels. Results Conduit flow, expressed as the percentage of total antegrade flow through the conduit, was 63.5 ± 8% and 67.8 ± 7% on early and mid‐term postoperative CMR, respectively (P < .05). Retrograde perfusion from the level of the conduit insertion in the descending thoracic aorta toward the aortic arch accounted for 6.9% of total cardiac output and 11% of total conduit flow. We did not observe any significant reduction in left ventricular stroke volume at postoperative evaluation compared with preoperative evaluation (P = .435). No differences were observed between preoperative and postoperative CBF at the gray matter, dorsal default‐mode network, and sensorimotor levels (P = .394). Conclusions After AVB surgery in patients with severe AS, cardiac output is split between the native left ventricular outflow tract and the apico‐aortic bypass, with two‐thirds of the total antegrade flow passing through the latter and one‐third passing through the former. In our experience, CBF assessment confirms that the flow redistribution does not jeopardize cerebral blood supply.

Nonbinary quantification technique accounting for myocardial infarct heterogeneity: Feasibility of applying percent infarct mapping in patients: Nonbinary Infarct Quantification

Binary threshold‐based quantification techniques ignore myocardial infarct (MI) heterogeneity, yielding substantial misquantification of MI.

Artificial intelligence machine learning-based coronary CT fractional flow reserve (CT-FFRML): Impact of iterative and filtered back projection reconstruction techniques

BACKGROUND The influence of computed tomography (CT) reconstruction algorithms on the performance of machine-learning-based CT-derived fractional flow reserve (CT-FFRML) has not been investigated. CT-FFRML values and processing time of two reconstruction algorithms were compared using an on-site workstation. METHODS CT-FFRML was computed on 40 coronary CT angiography (CCTA) datasets that were reconstructed with both iterative reconstruction in image space (IRIS) and filtered back-projection (FBP) algorithms. CT-FFRML was computed on a per-vessel and per-segment basis as well as distal to lesions with ≥50% stenosis on CCTA. Processing times were recorded. Significant flow-limiting stenosis was defined as invasive FFR and CT-FFRML values ≤ 0.80. Pearsons correlation, Wilcoxon, and McNemar statistical testing were used for data analysis. RESULTS Per-vessel analysis of IRIS and FBP reconstructions demonstrated significantly different CT-FFRML values (p ≤ 0.05). Correlation of CT-FFRML values between algorithms was high for the left main (r = 0.74), left anterior descending (r = 0.76), and right coronary (r = 0.70) arteries. Proximal and middle segments showed a high correlation of CT-FFRML values (r = 0.73 and r = 0.67, p ≤ 0.001, respectively), despite having significantly different averages (p ≤ 0.05). No difference in diagnostic accuracy was observed (both 81.8%, p = 1.000). Of the 40 patients, 10 had invasive FFR results. Per-lesion correlation with invasive FFR values was moderate for IRIS (r = 0.53, p = 0.117) and FBP (r = 0.49, p = 0.142). Processing time was significantly shorter using IRIS (15.9 vs. 19.8 min, p ≤ 0.05). CONCLUSION CT reconstruction algorithms influence CT-FFRML analysis, potentially affecting patient management. Additionally, iterative reconstruction improves CT-FFRML post-processing speed.

Influence of image reconstruction parameters on cardiovascular risk reclassification by Computed Tomography Coronary Artery Calcium Score

OBJECTIVE To investigate the influence of different CT reconstruction parameters on coronary artery calcium scoring (CACS) values and reclassification of predicted cardiovascular (CV) risk. METHODS CACS was evaluated in 113 patients undergoing ECG-gated 64-slice CT. Reference CACS protocol included standard kernel filter (B35f) with slice thickness/increment of 3/1.5 mm, and field-of-view (FOV) of 150-180 mm. Influence of different image reconstruction algorithms (reconstructed slice thickness/increment 2.0/1.0-1.5/0.8-3.0/2.0-3.0/3.0 mm; slice kernel B30f-B45f; FOV 200-250 mm) on Agatston score was assessed by Bland-Altman plots and concordance correlation coefficient (CCC) analysis. Classification of CV risk was based on the Mayo Clinic classification. RESULTS Different CACS reconstruction parameters showed overall good accuracy and precision when compared with reference protocol. Protocols with larger FOV, thinner slices and sharper kernels were associated with significant CV risk reclassification. Use of kernel B45f showed a moderate positive correlation with reference CACS protocol (Agatston CCC = 0.67), and yielded significantly higher CACS values (p < .05). Reconstruction parameters using B30f or B45f kernels, 250 mm FOV, or slice thickness/increment of 2.0/1.0 mm or 1.5/0.8 mm, were associated with significant reclassification of CV risk (p < .05). CONCLUSIONS Kernel, FOV, slice thickness and increment are major determinants of accuracy and precision of CACS measurement. Despite high agreement and overall good correlation of different reconstruction protocols, thinner slices thickness and increment, and sharper kernels were associated with significant upward reclassification of CV risk. Larger FOV determined both upward and downward reclassification of CV risk.

Prognostic value of pulmonary blood volume by first-pass contrast-enhanced CMR in heart failure outpatients: the PROVE-HF study

Aims Pulmonary blood volume (PBV) is a novel clinical application of cardiovascular magnetic resonance (CMR) imaging for the quantitative grading of haemodynamic congestion. In this study, we aimed to assess the prognostic value of PBV in a cohort of outpatients with chronic heart failure (HF). Methods and results One hundred and twelve consecutive patients (91 men, 67 ± 12 years) and 53 age- and sex-matched healthy controls underwent echocardiography and contrast-enhanced CMR. PBV was calculated as the product of stroke volume and the number of cardiac cycles for an intravenous bolus of gadolinium contrast to pass through the pulmonary circulation determined by first-pass perfusion imaging. Compared with healthy controls, HF outpatients showed significantly higher PBV index (PBVI, 308 ± 92 vs. 373 ± 175, mL/m2, P = 0.012) and pulmonary transit time (6.8 ± 1.8 vs. 9.5 ± 4 s, P ≤0.001). During a median follow-up of 26 ± 17 months, 27 patients (24%) reached the composite end point of cardiovascular death, HF hospitalization, or sustained ventricular arrhythmias/appropriate implantable cardioverter-defibrillator intervention. Using a cut-off point of PBVI >492 mL/m2, corresponding to two standard deviations above the mean of healthy controls, event-free survival was significantly lower in patients with higher PBVI (P < 0.001). At multivariable-adjusted Cox regression analysis, PBVI was an independent predictor of the composite cardiovascular end point (per 10% increase hazard ratio 1.31, 95% confidence interval: 1.02-1.69, P = 0.03). Conclusions PBVI is a novel application of perfusion CMR potentially useful to quantitatively determine haemodynamic congestion as a surrogate marker of left ventricular diastolic dysfunction. PBVI might prove to be helpful in stratifying the prognosis of asymptomatic or mildly symptomatic patients with left ventricular dysfunction.

The multi-modality cardiac imaging approach to cardiac sarcoidosis

BACKGROUND Sarcoidosis is a multisystem granulomatous disease with a neglected but high prevalence of life-threatening cardiac involvement. DISCUSSION The clinical presentation of Cardiac Sarcoidosis (CS) depends upon the location and extent of the granulomatous inflammation, with left ventricular free wall the most common location followed by interventricular septum. The lack of a diagnostic gold standard and the unpredictable risk of sudden cardiac death pose serious challenges for the validation of accurate and effective screening test and the management of the disease. In the last few years advanced cardiac imaging modalities such as Cardiac Magnetic Resonance (CMR) and Positron Emission Tomography (PET) have significantly improved our knowledge and understanding of CS, and have also contributed in risk stratification, assessment of inflammatory activity and therapeutic monitoring of the disease. CONCLUSION In this review, we will discuss the state of the art in the diagnosis of CS focusing on the role and importance of multi-modality cardiac imaging.

Uncommon Isolated Unilocular Myocardial Cyst in a Dog-Friendly Young Female Patient — Multimodality Imaging —

0.0–0.50 mg/dL); white blood cells (WBC), 18.83×103/μL (normal, 4.00–10.00×103/μL); neutrophils, 8.02×103/μL (normal, 2.80–5.25×103/μL); eosinophils, 0.47×103/μL (normal, 0.07–0.42×103/μL); and Echinococcus IgG antibodies, A 25-year-old woman was admitted to the emergency department with chest pain, dyspnea and fever (38.5°C). At admission, cardiac troponin I was <0.015 ng/mL; C-reactive protein, 5.54 mg/dL (normal,

Unexplained Cardiac Arrest After Near Drowning in a Young Experienced Swimmer: Insight from Cardiovascular Magnetic Resonance Imaging

Cardiac magnetic resonance imaging (cMRI) is a well-established noninvasive imaging modality in clinical cardiology. Its ability to provide tissue characterization make it well suited for the study of patients with cardiac diseases. We describe a multi-modality imaging evaluation of a 45-year-old man who experienced a near drowning event during swimming. We underline the unique capability of tissue characterization provided by cMRI, which allowed detection of subtle, clinically unrecognizable myocardial damage for understanding the causes of sudden cardiac arrest and also showed the small damages caused by cardiopulmonary resuscitation.

Quantitative computed tomography analysis in the assessment of coronary artery disease

Coronary artery disease (CAD) is one of the leading causes of death in developed countries. Recent literature confirmed multi detector computed tomography (MDCT) as a noninvasive imaging technique able to rule out and rule in CAD with a very high accuracy compared with Conventional Coronary Angiography (CCA). However the plaque burden and stenosis severity on MDCT is usually visually assessed with sequent inherent limitations. Recent technologies have permitted a real quantitative assessment of CAD.