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Human neuropathological studies indicate that the pontine nucleus Locus Coeruleus (LC) undergoes significant and early degeneration in Alzheimer's disease. This line of evidence alongside experimental data suggests that the LC functional/structural decay may represent a critical factor for Alzheimer's disease pathophysiological and clinical progression. In the present prospective study, we used Magnetic Resonance Imaging (MRI) with LC-sensitive sequence (LC-MRI) to investigate in vivo the LC involvement in Alzheimer's disease progression, and whether specific LC-MRI features at baseline are associated with prognosis and cognitive performance in amnestic Mild Cognitive Impairment.LC-MRI parameters were measured at baseline by a template-based method on 3.0-T magnetic resonance images in 34 patients with Alzheimer's disease dementia, 73 patients with amnestic Mild Cognitive Impairment, and 53 cognitively intact individuals. A thorough neurological and neuropsychological assessment was performed at baseline and 2.5-year follow-up.In subjects with Mild Cognitive Impairment who converted to dementia (n = 32), the LC intensity and number of LC-related voxels were significantly lower than in cognitively intact individuals, resembling those observed in demented patients. Such a reduction was not detected in Mild Cognitive Impairment individuals, who remained stable at follow-up. In Mild Cognitive Impairment subjects converting to dementia, LC-MRI parameter reduction was maximal in the rostral part of the left nucleus. Structural equation modeling analysis showed that LC-MRI parameters positively correlate with cognitive performance.Our findings highlight a potential role of LC-MRI for predicting clinical progression in Mild Cognitive Impairment and support the key role of LC degeneration in the Alzheimer clinical continuum.

Purpose: The Italian Registry of Contrast Material use in Cardiac Computed Tomography (iRCM-CCT) is a multicenter, multivendor, observational study on the use of contrast media (CM) in patients undergoing cardiac computed tomography (CCT). The aim of iRCM-CCT is to assess image quality and safety profile of intravenous CM compounds. Materials and methods: iRCM-CCT enrolled 1842 consecutive patients undergoing CCT (≥50 per site) at 20 cluster sites with the indication of suspected coronary artery disease. Demographic characteristics, CCT, and CM protocols, clinical indications, safety markers, radiation dose reports, qualitative (ie, poor vascular enhancement) and quantitative (ie, HU attenuation values) image parameters were recorded. A centralized coordinating center collected and assessed all image parameters. Results: The cohort included 891 men and 951 women (age: 63±14 y, body mass index: 26±4 kg/m2) studied with ≥64 detector rows computed tomography scanners and different iodinated intravenous CM protocols and compounds (iodixanol, iopamidol, iohexol, iobitridol, iopromide, and iomeprol). The following vascular attenuation was reported: 504±147 HU in the aorta, 451±146 HU in the right coronary artery, 474±146 HU in the left main, 451±146 HU in the left anterior descending artery, and 441±149 HU in the circumflex artery. In 4% of cases the image quality was not satisfactory due to poor enhancement. The following adverse reactions to CM were recorded: 6 (0.3%) extravasations and 17 (0.9%) reactions (11 mild, 4 moderate, 2 severe). Conclusions: In a multicenter registry on CM use during CCT the prevalence of CM-related adverse reactions was very low. The appropriate use of CM is a major determinant of image quality.

Feasibility assessment and planning of thoracic endovascular aortic repair (TEVAR) require computed tomography (CT)-based analysis of geometric aortic features to identify adequate landing zones (LZs) for endograft deployment. However, no consensus exists on how to take the necessary measurements from CT image data. We trained and applied a fully automated pipeline embedding a convolutional neural network (CNN), which feeds on 3D CT images to automatically segment the thoracic aorta, detects proximal landing zones (PLZs), and quantifies geometric features that are relevant for TEVAR planning. For 465 CT scans, the thoracic aorta and pulmonary arteries were manually segmented; 395 randomly selected scans with the corresponding ground truth segmentations were used to train a CNN with a 3D U-Net architecture. The remaining 70 scans were used for testing. The trained CNN was embedded within computational geometry processing pipeline which provides aortic metrics of interest for TEVAR planning. The resulting metrics included aortic arch centerline radius of curvature, proximal landing zones (PLZs) maximum diameters, angulation, and tortuosity. These parameters were statistically analyzed to compare standard arches vs. arches with a common origin of the innominate and left carotid artery (CILCA). The trained CNN yielded a mean Dice score of 0.95 and was able to generalize to 9 pathological cases of thoracic aortic aneurysm, providing accurate segmentations. CILCA arches were characterized by significantly greater angulation (p = 0.015) and tortuosity (p = 0.048) in PLZ 3 vs. standard arches. For both arch configurations, comparisons among PLZs revealed statistically significant differences in maximum zone diameters (p < 0.0001), angulation (p < 0.0001), and tortuosity (p < 0.0001). Our tool allows clinicians to obtain objective and repeatable PLZs mapping, and a range of automatically derived complex aortic metrics.

Aims Gamma-glutamyltransferase (GGT) has been recognized as a cardiovascular risk factor, and its highest molecular weight fraction [big GGT (b-GGT)] is found in vulnerable atherosclerotic plaques. We explored the relationship between b-GGT, computed tomography findings, and long-term outcomes in the general population. Methods and results Between May 2010 and October 2011, subjects aged 45–75 years living in a Tuscan city and without known cardiac disease were screened. The primary endpoint was a composite of cardiovascular death or acute coronary syndrome requiring urgent coronary revascularization. Gamma-glutamyltransferase fractions were available in 898 subjects [median age 65 years (25th–75th percentile 55–70), 46% men]. Median plasma GGT was 20 IU (15–29), and b-GGT was 2.28 (1.28–4.17). Coronary artery calcium (CAC) score values were 0 (0–60), and the volume of pro-atherogenic epicardial fat was 155 mL (114–204). In a model including age, sex, low-density lipoprotein (LDL) cholesterol, current or previous smoking status, hypertension, diabetes, obesity, b-GGT independently predicted epicardial fat volume (EFV) (r = 0.162, P < 0.001), but not CAC (P = 0.198). Over a 10.3-year follow-up (9.6–10.8), 27 subjects (3%) experienced the primary endpoint. We evaluated couples of variables including b-GGT and a cardiovascular risk factor, CAC or EFV. Big GGT yielded independent prognostic significance from age, LDL cholesterol, current or previous smoking status, hypertension, diabetes, obesity, but not CAC or EFV. Conversely, GGT predicted the primary endpoint even independently from CAC and EFV. Conclusion Big GGT seemed at least as predictive as the commonly available GGT assay; therefore, the need for b-GGT rather than GGT measurement should be carefully examined.

The concept of vascular age (VA) was proposed to provide patients with an understandable explanation of cardiovascular (CV) risk and to improve the performance of prediction models. The present study compared risk-based VA derived from Framingham Risk Score (FRS) and Systematic Coronary Risk Estimation (SCORE) models with value-based VA derived from the measurement of the common carotid artery (CCA) distensibility coefficient (DC), and it assessed the impact of DC-based VA on risk reclassification. In 528 middle-aged individuals apparently free of CV disease, DC was measured by radiofrequency-based arterial wall tracking that was previously utilised to establish sex- and age-specific reference values in a healthy population. DC-based VA represented the median value (50th percentile) for given sex in the reference population. FRS-based and SCORE-based VA was calculated as recommended. We observed a good agreement between DC-based and FRS-based VA, with a mean difference of 0.46 ± 12.2 years (p = 0.29), while the mean difference between DC-based and SCORE-based VA was higher (3.07 ± 12.7 years, p < 0.0001). When only nondiabetic individuals free of antihypertensive therapy were considered (n = 341), the mean difference dropped to 0.70 ± 12.8 years (p = 0.24). Substitution of chronological age with DC-based VA in FRS and SCORE models led to a reclassification of 28% and 49% of individuals, respectively, to the higher risk category. Our data suggest that the SCORE prediction model, in which diabetes and antihypertensive treatment are not considered, should be used as a screening tool only in healthy individuals. The use of VA derived from CCA distensibility measurements could improve the performance of risk prediction models, even that of the FRS model, as it might integrate risk prediction with additional risk factors participating in vascular ageing, unique to each individual. Prospective studies are needed to validate the role of DC-based VA in risk prediction.

Cardiac computed tomography (CCT) has rapidly evolved, becoming a powerful integrated tool for the evaluation of coronary artery disease (CAD), and being superior to other noninvasive methods due to its high accuracy and ability to simultaneously assess both lumen stenosis and atherosclerotic plaque burden. Furthermore, CCT is regarded as an effective gatekeeper for coronary angiography, and carries independent important prognostic information. In the last decade, the introduction of new functional CCT applications, namely CCT perfusion (CCTP) imaging and CT-derived fractional flow reserve (FFR(CTA)), has opened the door for accurate assessment of the haemodynamic significance of stenoses. These new CCT technologies, thus, share the unique advantage of assessing both myocardial ischemia and patient-specific coronary artery anatomy, providing an integrated anatomical/functional analysis. In the present review, starting from the pathophysiology of myocardial ischemia, we evaluate the existing evidence for functional CCT imaging and its value in relation to alternative, well-established, non-invasive imaging modalities and invasive indices of ischemia (currently the gold-standard). The knowledge of clinical applications, benefits, and limitations of these new CCT technologies will allow efficient and optimal use in clinical practice in the near future.

Aims Cardiac magnetic resonance (CMR) is part of the diagnostic work-up for cardiac amyloidosis (CA). Deep learning (DL) is an application of artificial intelligence that may allow to automatically analyze CMR findings and establish the likelihood of CA. Methods and results 1.5 T CMR was performed in 187 subjects with suspected CA (n = 92, 49% with unexplained left ventricular—LV—hypertrophy; n = 95, 51% with blood dyscrasia and suspected light-chain amyloidosis). Patients were randomly assigned to the training (n = 121, 65%), validation (n = 28, 15%), and testing subgroups (n = 38, 20%). Short axis (SA), 2-chamber (2 C), 4-chamber (4 C) late gadolinium enhancement (LGE) images were evaluated by 3 networks (DL algorithms). The tags “amyloidosis present” or “absent” were attributed when the average probability of CA from the 3 networks was ≥50% or Conclusion A DL approach evaluating LGE acquisitions displayed a similar diagnostic performance for CA to a ML-based approach, which simulates CMR reading by experienced operators.

Background Cardiovascular magnetic resonance (CMR) is part of the diagnostic work-up for cardiac amyloidosis (CA). Deep learning (DL) is an application of artificial intelligence that may allow to automatically analyze CMR findings and establish the likelihood of CA. Methods 1.5 T CMR was performed in 206 subjects with suspected CA (n = 100, 49% with unexplained left ventricular (LV) hypertrophy; n = 106, 51% with blood dyscrasia and suspected light-chain amyloidosis). Patients were randomly assigned to the training (n = 134, 65%), validation (n = 30, 15%), and testing subgroups (n = 42, 20%). Short axis, 2-chamber, 4-chamber late gadolinium enhancement (LGE) images were evaluated by 3 networks (DL algorithms). The tags “amyloidosis present” or “absent” were attributed when the average probability of CA from the 3 networks was ≥ 50% or Results The DL strategy displayed good diagnostic accuracy (88%), with an area under the curve (AUC) of 0.982. The precision (positive predictive value), recall score (sensitivity), and F1 score (a measure of test accuracy) were 83%, 95%, and 89% respectively. A ML algorithm considering all CMR features had a similar diagnostic yield to DL strategy (AUC 0.952 vs. 0.982; p = 0.39). Conclusions A DL approach evaluating LGE acquisitions displayed a similar diagnostic performance for CA to a ML-based approach, which simulates CMR reading by experienced operators.

BACKGROUND: Carotid artery disease is highly prevalent and a main cause of ischemic stroke and vascular dementia. There is a paucity of information on predictors of serious vascular events. Besides percentage diameter stenosis, international guidelines also recommend the evaluation of qualitative characteristics of carotid artery disease as a guide to treatment, but with no agreement on which qualitative features to assess. This inadequate knowledge leads to a poor ability to identify patients at risk, dispersion of medical resources, and unproven use of expensive and resource-consuming techniques, such as magnetic resonance imaging, positron emission tomography, and computed tomography.OBJECTIVES: The Carotid Artery Multimodality imaging Prognostic (CAMP) study will: prospectively determine the best predictors of silent and overt ischemic stroke and vascular dementia in patients with asymptomatic subcritical carotid artery disease by identifying the noninvasive diagnostic features of the 'vulnerable carotid plaque'; assess whether 'smart' use of low-cost diagnostic methods such as ultrasound-based evaluations may yield at least the same level of prospective information as more expensive techniques.STUDY DESIGN: We will compare the prognostic/predictive value of all proposed techniques with regard to silent or clinically manifest ischemic stroke and vascular dementia. The study will include ≥300 patients with asymptomatic, unilateral, intermediate degree (40-60% diameter) common or internal carotid artery stenosis detected at carotid ultrasound, with a 2-year follow-up. The study design has been registered on Clinicaltrial.gov on December 17, 2020 (ID number NCT04679727).

Aims Doppler ultrasound (DUS), CT angiography (CTA), and contrast-enhanced MR angiography (CEMRA) are all recommended techniques to evaluate the significance of carotid artery stenosis, although they may give discordant results. Plaque ulcerations may be present, but their role is still controversial. We aimed at assessing the concordance and level of agreement, as well as the prevalence of characteristics related to plaque ulceration and association to patients’ characteristics among different imaging diagnostic techniques. Methods and results Sixty-one patients with unilateral asymptomatic carotid artery stenosis (40–60% detected by DUS), enrolled in the ongoing CAMP study were prospectively evaluated with CEMRA and CTA. The level of agreement was calculated by the weighed kappa test. Plaque ulceration was defined as an intimal defect larger than 1 mm in width or 2 mm in depth, detected by CTA and/or CEMRA. Concordance rate was 71% for DUS–CTA, 51% for DUS–CEMRA, and 66% for CTA–CEMRA. Concordance among all noninvasive techniques was only 45%. Compared with DUS, the stenosis was downgraded by CTA in 17% and by CEMRA in 32% of cases. There was a moderate agreement between DUS–CTA {weighed kappa 0.49 [95% confidence interval (CI): 0.31–0.67]}, while agreement between DUS–CEMRA and CTA–CEMRA was fair [weighed kappa 0.15 (95% CI: −0.01–0.31) and 0.38 (95% CI: 0.14–0.62), respectively]. An ulcerated plaque was present in 39% of patients at CTA and/or CEMRA; compared with patients with non-ulcerated plaques, those with an ulcerated plaque had higher levels of C-reactive protein (CRP), and a trend to higher levels of high sensitivity cardiac troponin (cTn) T (Table), whereas the degree of stenosis was similar. Conclusions CTA and CEMRA tend to report a lower degree of stenosis compared with DUS. Concordance and level of agreement was higher for DUS and CTA. Plaque ulceration is common and is associated with a significant higher level of systemic inflammation, as detected by CRP and, possibly, cTn.

Introduction In patients (pts) undergoing cardiac surgery for primary mitral regurgitation (PMR), coronary angiography (CA) is always scheduled shortly before surgery to rule out significant coronary artery disease (CAD), despite this population is often young and with relatively low risk for CAD. Computed Tomography Coronary Angiography (CTCA) could be an alternative approach to evaluate coronary arteries, at least ruling out significant CAD in selected pts, due to its high negative predictive value. Purpose A safer, more appropriate and efficient clinical and diagnostic pathway for patients undergoing cardiac surgery for PMR by stratifying patients prior cardiac surgery according to pretest probability score (PTP) and therefore shifting imaging of epicardial coronary arteries from invasive to noninvasive in specific patients subsets. Methods A retrospective analysis (Jan 2014–Dec 2020) was carried out through the extraction of 7343 electronic medical records of pts who underwent cardiac valve surgery. In 1556 pts with PMR (1195 with no-CAD and 361 with CAD) a PTP was retrospectively calculated according to Genders, 2012, to stratify their risk of CAD. A Decision oriented Health Technology Assessment (DoHTA) and a cost analysis were also performed to support the analysis results. A survey was distributed to a team of experts with a multidisciplinary background to analyze the most significant evaluation areas (Economic Aspects, Clinical Effectiveness, Safety, Innovation) and the sub-criteria related to them. Following the Core Model Eunethta as a guideline, a Rapid Report HTA has been drawn up to identify the best solution. Results Patients characteristics are listed in Picture 1. Pts with normal coronary arteries showed a PTP low-to intermediate while pts with high PTP had CAD and therefore had a real pretest need for a CA (average 11 percent ± 9 in noCAD group vs 20 percent ± 14 in the CAD group). In two thirds of PMR population coronary angiography could have been avoided according to a PTP score The cost analysis results were significantly lower in CTCA (1,315.00 EUR vs 180.00 EUR, CA vs CTCA respectively), The Decision Oriented HTA conducted by a multidisciplinary team showed a relevant preference for the new pathway (Picture 2) with a score of 70.23 percent of preference among the Team. Conclusions This new pathway, already proposed for selected pts in ESC guidelines on valve diseases (class IIA, LOE C) could be always adopted in PMR pts with low-to intermediate PTP score undergoing cardiac surgery. It could improve workflow efficiency and reduce LOS, and last but not least, avoid an invasive test, reduce radiation exposure and AKI risk in in a relatively young population The DoHTA provided a more effective and efficient support to the decision-making process. Funding Acknowledgement Type of funding sources: None. Picture 1. Patients characteristics (noCAD-CAD)Picture 2. HTA Score CTCA vs CA

Key Points Question What are the patient perceptions and knowledge about ionizing radiation used for medical imaging? Findings In this survey study among 2866 patients undergoing radiological examinations in Italian hospitals, a substantial proportion of respondents perceived their medical radiation knowledge as inadequate and had misconceptions about basic aspects of radiation protection. Better knowledge was associated with receiving such information from medical staff and having a higher educational level. Meaning These findings suggest that interventions to improve patients’ knowledge about radiation protection risks would be beneficial, with communication from medical staff potentially playing a determinant role., Importance Although imaging has become a standard tool of modern medicine, its widespread use has been paralleled by an increasing cumulative radiation dose to patients despite technological advancements and campaigns calling for better awareness and minimization of unnecessary exposures. Objective To assess patients’ knowledge about medical radiation and related risks. Design, Setting, and Participants A survey study of hospitals in Italy was conducted; all patients in waiting rooms for medical imaging procedures before undergoing imaging examinations at 16 teaching and nonteaching hospitals were approached to take the survey. The survey was performed from June 1, 2019, to May 31, 2020. Main Outcomes and Measures Survey respondents’ basic knowledge of ionizing radiation levels and health risks, earlier imaging tests performed, and information and communication about radiation protection issues. Results Among 3039 patients invited to participate, the response rate was 94.3% (n = 2866). Participants included 1531 women (53.4%); mean (SD) age was 44.9 (17.3) years. Of the 2866 participants, 1529 (53.3%) were aware of the existence of natural sources of ionizing radiation. Mammography (1101 [38.4%]) and magnetic resonance imaging (1231 [43.0%]) were categorized as radiation-based imaging modalities. More than half of the 2866 patients (1579 [55.1%]; P = .03) did not know that chest computed tomography delivers a larger dose of radiation than chest radiography, and only 1499 (52.3%) knew that radiation can be emitted after nuclear medicine examinations (P = .004). A total of 667 patients (23.3%) believed that radiation risks were unrelated to age, 1273 (44.4%) deemed their knowledge about radiation risks inadequate, and 2305 (80.4%) preferred to be informed about radiation risks by medical staff. A better knowledge of radiation issues was associated with receiving information from health care professionals (odds ratio [OR], 1.71; 95% CI, 1.43-2.03; P, This survey study examines patients’ knowledge of radiation used in imaging procedures.

OBJECTIVES Arterial stiffness as pulse wave velocity (PWV) predicts cardiovascular events independently of blood pressure (BP). PWV does not distinguish between stiffness in systole and diastole. This cross-sectional study aimed to test the hypothesis that viscous and elastic carotid wall properties differ between systole and diastole, distinguishing effects of ageing, hypertension and T2 diabetes (T2DM). METHODS We examined carotid visco-elasticity in 307 people (180 men), with hypertension alone (n = 69), combined hypertension/T2DM (H-T2DM, n = 99), normotensive (N-T2DM, n = 25) and healthy controls (n = 114). Diameter (D)/pressure (P) waveforms were measured at right /left common carotid arteries, respectively. Local carotid PWV and distensibility in systole and diastole were evaluated by the D2P-loop method, and wall viscosity from hysteresis, the area (HA) within the P--D loop, as a dynamic measure of systolic loading and diastolic unloading. RESULTS Controls' hysteresis fell quadratically with age (R2 = 0.23, P

The normal and pathological anatomy of the heart and coronary arteries are nowadays widely developed topics and constitute a fundamental part of the cultural background of the radiologist. The introduction of cardiac ECG-gated synchronized CT scanners with an ever-increasing number of detectors and with increasingly high structural characteristics (increase in temporal resolution, increase in contrast resolution with dual-source, dual energy scanners) allows the virtual measurement of anatomical in vivo structures complying with heart rate with submillimetric precision permitting to clearly depict the normal anatomy and follow the pathologic temporal evolution. Accordingly to these considerations, cardiac computed tomography angiography (CCTA) asserts itself as a gold standard method for the anatomical evaluation of the heart and permits to evaluate, verify, measure and characterize structural pathological alterations of both congenital and acquired degenerative diseases. Accordingly, CCTA is increasingly used as a prognostic model capable of modifying the outcome of diseased patients in planning interventions and in the post-surgical/interventional follow-up. The profound knowledge of cardiac anatomy and function through highly detailed CCTA analysis is required to perform an efficient and optimal use in real-world clinical practice.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic management is limited by great uncertainty, for both health systems and citizens. Facing this information gap requires a paradigm shift from traditional approaches to healthcare to the participatory model of improving health. This work describes the design and function of the Doing Risk sElf-assessment and Social health Support for COVID (Dress-COV) system. It aims to establish a lasting link between the user and the tool, thus, enabling modeling of the data to assess individual risk of infection, or developing complications, to improve the individual&rsquo, s self-empowerment. The system uses bot technology of the Telegram application. The risk assessment includes the collection of user responses and the modeling of data by machine learning models, with increasing appropriateness based on the number of users who join the system. The main results reflect: (a) the individual&rsquo, s compliance with the tool, (b) the security and versatility of the architecture, (c) support and promotion of self-management of behavior to accommodate surveillance system delays, (d) the potential to support territorial health providers, e.g., the daily efforts of general practitioners (during this pandemic, as well as in their routine practices). These results are unique to Dress-COV and distinguish our system from classical surveillance applications.

Background Cardiac magnetic resonance (CMR) is an important diagnostic technique for cardiac amyloidosis (CA). A deep learning (DL) approach to define the likelihood of CA based on automated interpretation of CMR images has never been attempted so far. Methods 187 subjects underwent standard 1.5 T CMR examination (GE-Healthcare, Milwaukee, USA) as part of a diagnostic workup for either unexplained left ventricular hypertrophy or blood dyscrasia with suspected light-chain (AL) amyloidosis. Patients were randomly assigned to 3 subgroups, which were used for training (n=121, 65%), internal validation (n=28, 15%), and model testing (n=38, 20%). LGE images in different orientations (short-axis, 2- and 4-chambers) were selected as the most informative CMR features. A deep convolutional neural network was trained to classify CMR examinations as “amyloidosis” (probability ≥50%) or “no amyloidosis” (probability Results CA was diagnosed in 101 subjects (54%; 45 AL, 56 transthyretin amyloidosis). A model including 2C, 4C and SA LGE images was created. In the test cohort, it allowed to diagnose CA with good diagnostic accuracy (84.2%), and an area under the curve (AUC) of 0.96 (Figure). The precision (positive predictive value), recall score (sensitivity), and F1 score (a measure of test accuracy) were 0.78, 0.94, and 0.86, respectively. An ML algorithm considering all available parameters (LV volumes and function, LGE presence and pattern, early darkening, pericardial and pleural effusion, etc.) displayed a similar diagnostic performance than the DL method (AUC 0.93 vs. 0.96; p=0.45). Conclusions The deep learning technique allowed to create an accurate diagnostic tool for CA based on LGE patterns, which could be easily converted into an online platform for automated image analysis. Funding Acknowledgement Type of funding source: None

Background Non-contrast-enhanced cardiac computed tomography (CT) may provide two measures that are emerging as independent predictors of cardiovascular events: coronary calcium score (CCS) and the volume of epicardial fat, a metabolically and immunologically active tissue surrounding the coronary arteries. The quantification of epicardial fat volume (EFV) is not routinely performed in clinical practice for the long time required for image reconstruction and the intra- and inter-observer variability. Purpose We evaluated if artificial intelligence (AI) might prove a valuable tool to interpret the CT data-set, and to better understand the relative prognostic value of CCS and EFV compared to “traditional” cardiovascular risk factors. Methods The Montignoso HEart and Lung Project is a community-based study carried out in a small town of Northern Tuscany (Italy). Starting from 2009, asymptomatic individuals from the general population underwent a baseline screening including a non-contrast cardiac CT, and were followed-up. For the present study, CCS and EFV were automatically measured from CT scans through a deep learning (DL) strategy based on convolutional neural networks. Because of the low incidence of the primary endpoint (myocardial infarction [MI]), the observed cardiac events were predicted with a random forest model built using a subsampling approach. Results Study participants (n=1528; 48% males, age 40 to 77 years) experienced 47 MI events (3%) over 5.5±1.5 years. CCS and EFV independently predicted this endpoint (p values Conclusions The tools of AI allow to perform an automated analysis of non-contrast-enhanced CT scans, with rapid and accurate measurement of CCS and EFV through a DL approach. In asymptomatic individuals from the general population, these features are more predictive of non-fatal MI than other variables related to the cardiovascular risk, as we can be demonstrated through an application of AI. Figure 1 Funding Acknowledgement Type of funding source: None

Background Athletic pubalgia (AP), a frequent problem among professional roller hockey players (PRHPs), consists of lower abdominal and groin pain, without the presence of true hernia. Aims We assessed cetylated fatty acids (CFAs) in association with conservative therapy for treatment of AP in PRHPs. Methods Ultrasound examination was performed before and after treatment. Strength tests were performed and AP-related pain was measured during the treatment period. Findings Nine of 10 enrolled PRHPs completed a 12-week treatment with CFAs in association with conservative therapy, consisting of manual therapy, diathermy or ultrasonography. Initial ultrasound examination showed AP signs in 7 (70%) of 10 PRHPs. After 12 weeks of therapy, these signs could only be detected by ultrasound in 2 (22.2%) of 9 PRHPs. An increase in muscle strength (already after first week of treatment) and a reduction of AP-related pain were also observed during the treatment. Conclusion The association of CFA treatment with a conservative rehabilitation therapy improves muscle strength and pain and may accelerate recovery from AP., Musculoskeletal system; Medical imaging; Clinical research; Health profession; Diagnostics; Athletic pubalgia; Cetlyated fatty acids; Physical therapy; Sports hernia; Strength test; Ultrasound.

ObjectivesThe pericardial fat represents a powerful (promising) index which has been seen to correlate with several cardiovascular events. We propose a novel approach to automatically measure it from CT scans and we seek to explore how it is distributed in a study population.MethodsWe studied a population of 1528 patients where 47 (3%) showed a cardiac event. The fat segmentation model was based on a deep neural network to identify the heart and from it, the pericardial fat was extract by threshold. Statistical analysis was finally computed to stratify the population according the quantity of pericardial fat.ResultsThe high segmentation quality was reported with a Dice index (92.5%) and a Pearson coefficient (0.990, p3/m2, p=0.005) with a AUC of 63,44% for discrimination of cardiac event.ConclusionsThe proposed approach reached accurate and fast performance for the evaluation of the pericardial fat making it reliable for a population analysis.

Background and Aims. Atherosclerosis is an inflammatory disease with long-lasting activation of innate immunity and monocytes are the main blood cellular effectors. We aimed to investigate monocyte phenotype (subset fraction and marker expression) at different stages of coronary atherosclerosis in stable coronary artery disease (CAD) patients. Methods. 73 patients with chronic coronary syndrome were evaluated by CT coronary angiography (CTCA) and classified by maximal diameter stenosis of major vessels into three groups of CAD severity: CAD1 (no CAD/minimal CAD, n°=30), CAD2 (non-obstructive CAD, n°=21), and CAD3 (obstructive CAD, n°=22). Flow cytometry for CD14, CD16, and CCR2 was used to quantify Mon1, Mon2, and Mon3 subsets. Expression of CD14, CD16, CD18, CD11b, HLA-DR, CD163, CCR2, CCR5, CX3CR1, and CXCR4 was also measured. Adhesion molecules and cytokines were quantified by ELISA. Results. Total cell count and fraction of Mon2 were higher in CAD2 and CAD3 compared to CAD1. By multivariate regression analysis, Mon2 cell fraction and Mon2 expression of CX3CR1, CD18, and CD16 showed a statistically significant and independent increase, parallel to stenosis severity, from CAD1 to CAD2 and CAD3 groups. A similar trend was also present for CX3CR1 and HLA-DR expressions on total monocyte population. A less calcified plaque composition was associated to a higher Mon2 expression of CD16 and higher TNF-α levels. IL-10 levels were lower at greater stenosis severity, while the IFN-γ/IL-10 ratio, a marker of a systemic pro-inflammatory imbalance, was directly correlated to stenosis degree and number of noncalcified plaques. Conclusions. The results of this study suggest that a specific pattern of inflammation-correlated monocyte marker expression is associated to higher stenosis severity and less calcified lesions in stable CAD. The clinical trial Identifier is NCT04448691.

ObjectiveAbout 10 million people in Europe suffer from mitral valve incompetence. Majority of these entity is mitral valve prolapse in developed countries. Endoscopic mitral valve surgery is a relatively new procedure and preparation in the right intercostal space are crucial for success completion of the procedure. We aimed to explore clinical variables and chest X-rays in order to build most performant model that can predict the right intercostal space for thoracotomy.MethodsOverall 234 patients underwent fully endoscopic mitral valve surgery. All patients had preoperative two projection radiography. Intercostal space for right thoracotomy was decided by expert cardiac surgeons taking in consideration the height, weight, chest radiography, anatomical position of skin incision, nipple position and the sex. In order to predict the right intercostal space we have used clinical data and we have collected all radiographies and feed it to deep neural network algorithm. We have spitted the whole data-set into two subsets: training and testing data-sets. We have used clinical data and build an algorithm (Random Forest) in order to have reference model.ResultsThe best-performing classifier was GoogLeNet neural network (now on we will reffera as Deep Learning) and had an AUC of 0.956. Algorithm based on clinical data (Random Forest) had AUC of 0.529 using only chest x-rays. The deep leaning algorithm predicted correctly in all cases the correct intercostal space on the training datasest except two ladies (96.08% ; with sensitivity of 97.06% and specificity 94.12 %, where the Random Forest was capable to predict right intercostal space in 60.78% cases with sensitivity of 93.33% and specificity 14.29 % (only clinical data).ConclusionArtificial intelligence can be helpful to program the minimally invasive cardiac operation, for right intercostal space selection for thoracotomy, especially in non optimal thoraxes (example, obese short ladies). It learned from the standard imaging (thorax x-ray) which is easy, do routinely to every patient.

Aortic aneurysms result from degeneration and abnormal production of elastin and collagen. Besides medical therapy, management includes periodical imaging to identify the best moment for surgery. Nowadays, the alternative to traditional surgical techniques is represented by a hybrid approach in which debranching is followed by positioning of an endograft. We describe a case of a patient with multiple atherosclerotic aneurysms and a penetrating ulcer of the aortic arch treated with a hybrid approach.

Cluster of microcalcifications can be an early sign of breast cancer. In this paper we propose a novel approach based on convolutional neural networks for the detection and segmentation of microcalcification clusters. In this work we used 283 mammograms to train and validate our model, obtaining an accuracy of 98.22% in the detection of preliminary suspect regions and of 97.47% in the segmentation task. Our results show how deep learning could be an effective tool to effectively support radiologists during mammograms examination., Comment: 13 pages, 7 figures

Aims Percutaneous left atrial appendage occlusion (LAAO) with the Amplatzer Cardiac Plug (ACP) emerged as a valid alternative in patients with a formal contraindication to oral anticoagulant therapy. Transoesophageal echocardiography (TEE), cardiac computed tomography angiography (CCTA), intracardiac echocardiography (ICE), and conventional cardiac angiography (CCA) are used to evaluate LAA diameters. The aim of our study was to compare pre- and intraprocedural imaging techniques in determining the correct selection of the device size, with a retrospective evaluation of the results obtained at post-procedural CCTA follow-up. Methods and results Between September 2009 and July 2013, 66 consecutive patients underwent to LAAO with the ACP at our institution. Preoperative LAA evaluation was realized with TEE, CCTA, ICE, and CCA. Fifty-eight (58) patients underwent to post-procedural CCTA to confirm the LAA complete exclusion, the number and extent of the residual leaks, and the positioning of the device. LAA diameters measured by CCTA correlate with the diameters obtained with CCA and ICE, but they are sized slightly larger than the others. TEE has a lower correlation with every other imaging method and a likely tendency to underestimate. The distribution of the leaks and the positioning of the device in post-procedural CCTA show no substantial differences between the devices used greater or equal to the one selected with CCTA in terms of LAA exclusion. Conclusion The sizing of the device decided using CCTA in the phase of maximum LAA expansion reduces the risk of high-flow leaks and device malposition due to undersizing.

Coronary artery calcium (CAC) is a significant marker of atherosclerosis and cardiovascular events. In this work we present a system for the automatic quantification of calcium score in ECG-triggered non-contrast enhanced cardiac computed tomography (CT) images. The proposed system uses a supervised deep learning algorithm, i.e. convolutional neural network (CNN) for the segmentation and classification of candidate lesions as coronary or not, previously extracted in the region of the heart using a cardiac atlas. We trained our network with 45 CT volumes; 18 volumes were used to validate the model and 56 to test it. Individual lesions were detected with a sensitivity of 91.24%, a specificity of 95.37% and a positive predicted value (PPV) of 90.5%; comparing calcium score obtained by the system and calcium score manually evaluated by an expert operator, a Pearson coefficient of 0.983 was obtained. A high agreement (Cohen's k = 0.879) between manual and automatic risk prediction was also observed. These results demonstrated that convolutional neural networks can be effectively applied for the automatic segmentation and classification of coronary calcifications.

Significant underexpansion or distortion of valved stents may be associated with altered leaflet function, leading to increased transprosthetic gradients and, possibly, early structural degeneration. We investigated the relationship between a computed tomography measure of the degree of oversizing and the early hemodynamic and clinical outcomes in patients undergoing aortic valve replacement with the Perceval sutureless aortic valve (LivaNova, Saluggia, Italy).The degree of oversizing of the implanted prosthesis was calculated as the ratio between the patients' aortic annulus cross-sectional area and the ex vivo cross-sectional area of the implanted prosthesis in 151 Perceval patients who underwent preoperative cardiac computed tomography. This value was then entered in a multivariate analysis to ascertain its role as a predictor of increased postoperative gradient.The operative mortality was 1.3%. Procedural success, defined as having a normally functioning valve in the proper anatomical location, was achieved in 150 patients (99.3%). The mean transprosthetic gradient was 13.4 ± 5.0 mm Hg, and 23 patients (15.2%) showed a gradient of 20 mm Hg or more at discharge or at the 1-month follow-up. The degree of oversizing of the implanted prosthesis was the most important predictor of increased postoperative gradient (odds ratio, 1.264; 95% confidence interval, 1.147 to 1.394; p0.0001). Interestingly, other relevant factors (patients' body surface area, prosthesis size) were not associated with increased gradients.Our study demonstrates that excessive oversizing should be avoided in Perceval patients and suggests that a different sizing algorithm, possibly based on cardiac computed tomography, should be developed. Further studies are needed to optimize the sizing strategy for the Perceval sutureless valve.

Cluster of microcalcifications can be an early sign of breast cancer. In this paper we present a deep convolutional neural network for microcalcification detection and compare its results to a classical approach. In this work we used 238 mammograms to train and validate our neural network to recognize which pixels in a mammogram correspond to a calcification; we tested the results on 52 images and obtained an accuracy of 83.7% against only 58% of the classical approach. Our results show how deep learning could be an effective tool to use for microcalcification detection and segmentation, outdoing classical approaches.

We read with interest the manuscript by Lee et al. [(1)][1], which reports statin use impact on coronary plaque features. Statins increase coronary artery calcification, reducing local inflammation, changing phenotypic plaque composition, and lowering the high-risk plaques, as also observed in

Aims Hybrid imaging provides a non-invasive assessment of coronary anatomy and myocardial perfusion. We sought to evaluate the added clinical value of hybrid imaging in a multi-centre multi-vendor setting. Methods and results Fourteen centres enrolled 252 patients with stable angina and intermediate (20-90%) pre-test likelihood of coronary artery disease (CAD) who underwent myocardial perfusion scintigraphy (MPS), CT coronary angiography (CTCA), and quantitative coronary angiography (QCA) with fractional flow reserve (FFR). Hybrid MPS/CTCA images were obtained by 3D image fusion. Blinded core-lab analyses were performed for CTCA, MPS, QCA and hybrid datasets. Hemodynamically significant CAD was ruled-in non-invasively in the presence of a matched finding (myocardial perfusion defect colocalized with stenosed coronary artery) and ruled-out with normal findings (both CTCA and MPS normal). Overall prevalence of significant CAD on QCA (.70% stenosis or 30-70% with FFR≤0.80) was 37%. Of 1004 pathological myocardial segments on MPS, 246 (25%) were reclassified from their standard coronary distribution to another territory by hybrid imaging. In this respect, in 45/252 (18%) patients, hybrid imaging reassigned an entire perfusion defect to another coronary territory, changing the final diagnosis in 42% of the cases. Hybrid imaging allowed non-invasive CAD rule-out in 41%, and rule-in in 24% of patients, with a negative and positive predictive value of 88% and 87%, respectively. Conclusion In patients at intermediate risk of CAD, hybrid imaging allows non-invasive co-localization of myocardial perfusion defects and subtending coronary arteries, impacting clinical decision-making in almost one every five subjects. -------------------------------------------------------------------------------------------------------------------------------

Coronary-to-bronchial artery fistulae are the most common found in adulthood and have often been associated with bronchiectasis and other abnormalities of pulmonary parenchyma. In this study we describe an unusual case in which circumflex coronary artery-to-left bronchial artery fistula was associated with the presence of extensive aneurysmatic dilatation of thoracic arteries.

The aim of this study is to determine the 99th upper-reference limit (URL) for cardiac troponin T (cTnT) in Italian apparently healthy subjects.The reference population was selected from 5 cities: Bolzano (n=290), Milano (CAMELIA-Study, n=287), Montignoso (MEHLP-Study, n=306), Pisa (n=182), and Reggio Calabria (MAREA-Study, n=535). Subjects having cardiac/systemic acute/chronic diseases were excluded. Participants to MEHLP project underwent cardiac imaging investigation. High-sensitive cTnT was measured with Cobas-e411 (Roche Diagnostics).We enrolled 1600 healthy subjects [54.6% males; age range 10-90years; mean (SD): 36.4 (21.2) years], including 34.6% aged20years, 54.5% between 20 and 64years, and 10.9% over 65years. In the youngest the 99th URL was 10.9ng/L in males and 6.8ng/L in females; in adults 23.2ng/L and 10.2ng/L; and in elderly 36.8ng/L and 28.6ng/L. After the exclusion of outliers the 99th URL values were significantly decreased (P0.05) in particular those of the oldest (13.8ng/L and 14ng/L). MEHLP participants were divided in healthy and asymptomatic, according to known cardiovascular risk factors (HDL, LDL, glucose, C-reactive protein): the 99th URL of cTnT values of these subgroups was significantly different (19.5 vs. 22.7, P0.05).99th URL of cTnT values was strongly affected by age, gender, selection of subjects and the statistical evaluation of outliers.

A 66-year-old man, who had a 20-year-old history of mechanical mitral valve replacement for rheumatic valve disease and concomitant epicardial monopolar lead implantation for symptomatic bradycardic atrial fibrillation, was diagnosed with significant increase in pacing threshold. Therefore, a novel endocardial ventricular lead …