CMR Mapping: The 4th-Era Revolution in Cardiac Imaging.

Cardiac magnetic resonance (CMR) imaging has witnessed substantial progress with the advent of parametric mapping techniques, most notably T1 and T2 mapping. These advanced techniques provide valuable insights into a wide range of cardiac conditions, including ischemic heart disease, cardiomyopathies, inflammatory cardiomyopathies, heart valve disease, and athlete's heart. Mapping could be the first sign of myocardial injury and oftentimes precedes symptoms, changes in ejection fraction, and irreversible myocardial remodeling. The ability of parametric mapping to offer a quantitative assessment of myocardial tissue properties addresses the limitations of conventional CMR methods, which often rely on qualitative or semiquantitative data. However, challenges persist, especially in terms of standardization and reference value establishment, hindering the wider clinical adoption of parametric mapping. Future developments should prioritize the standardization of techniques to enhance their clinical applicability, ultimately optimizing patient care pathways and outcomes. In this review, we endeavor to provide insights into the potential contributions of CMR mapping techniques in enhancing the diagnostic processes across a range of cardiac conditions.

Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems.

OBJECTIVE: We aimed to evaluate the effectiveness of utilizing artificial intelligence (AI) to quantify the extent of pneumonia from chest CT scans, and to determine its ability to predict clinical deterioration or mortality in patients admitted to the hospital with COVID-19 in comparison to semi-quantitative visual scoring systems. METHODS: A deep-learning algorithm was utilized to quantify the pneumonia burden, while semi-quantitative pneumonia severity scores were estimated through visual means. The primary outcome was clinical deterioration, the composite end point including admission to the intensive care unit, need for invasive mechanical ventilation, or vasopressor therapy, as well as in-hospital death. RESULTS: The final population comprised 743 patients (mean age 65  ±â€¯ 17 years, 55% men), of whom 175 (23.5%) experienced clinical deterioration or death. The area under the receiver operating characteristic curve (AUC) for predicting the primary outcome was significantly higher for AI-assisted quantitative pneumonia burden (0.739, p = 0.021) compared with the visual lobar severity score (0.711, p < 0.001) and visual segmental severity score (0.722, p = 0.042). AI-assisted pneumonia assessment exhibited lower performance when applied for calculation of the lobar severity score (AUC of 0.723, p = 0.021). Time taken for AI-assisted quantification of pneumonia burden was lower (38 ± 10 s) compared to that of visual lobar (328 ± 54 s, p < 0.001) and segmental (698 ± 147 s, p < 0.001) severity scores. CONCLUSION: Utilizing AI-assisted quantification of pneumonia burden from chest CT scans offers a more accurate prediction of clinical deterioration in patients with COVID-19 compared to semi-quantitative severity scores, while requiring only a fraction of the analysis time. ADVANCES IN KNOWLEDGE: Quantitative pneumonia burden assessed using AI demonstrated higher performance for predicting clinical deterioration compared to current semi-quantitative scoring systems. Such an AI system has the potential to be applied for image-based triage of COVID-19 patients in clinical practice.

The use of dedicated long-axis views focused on the left atrium improves the accuracy of left atrial volumes and emptying fraction measured by cardiovascular magnetic resonance.

BACKGROUND: The use of apical views focused on the left atrium (LA) has improved the accuracy of LA volume evaluation by two-dimensional (2D) echocardiography. However, routine cardiovascular magnetic resonance (CMR) evaluation of LA volumes still uses standard 2- and 4-chamber cine images focused on the left ventricle (LV). To investigate the potential of LA-focused CMR cine images, we compared LA maximuml (LAVmax) and minimum (LAVmin) volumes, and emptying fraction (LAEF), calculated on both standard and LA-focused long-axis cine images, with LA volumes and LAEF obtained by short-axis cine stacks covering the LA. LA strain was also calculated and compared between standard and LA-focused images. METHODS: LA volumes and LAEF were obtained from 108 consecutive patients by applying the biplane area-length algorithm to both standard and LA-focused 2- and 4-chamber cine images. Manual segmentation of a short-axis cine stack covering the LA was used as the reference method. In addition, LA strain reservoir (εs), conduit (εe) and booster pump (εa) were calculated using CMR feature-tracking. RESULTS: Compared to the reference method, the standard approach significantly underestimated LA volumes (LAVmax: bias - 13 ml; LOA = + 11, - 37 ml; LAVmax i: bias - 7 ml/m2; LOA = + 7, - 21 ml/m2; LAVmin; bias - 10 ml, LOA: + 9, - 28 ml; LAVmin i: bias - 5 ml/m2, LOA: + 5, - 16 ml/m2), and overestimated LA-EF (bias 5%, LOA: + 23, - 14%). Conversely, LA volumes (LAVmax: bias 0 ml; LOA: + 10, - 10 ml; LAVmax i: bias 0 ml/m2; LOA: + 5, - 6 ml/m2; LAVmin: bias - 2 ml; LOA: + 7, - 10 ml; LAVmin i: bias - 1 ml/m2; LOA: + 3, - 5 ml/m2) and LAEF (bias 2%, LOA: + 11, - 7%) by LA-focused cine images were similar to those measured using the reference method. LA volumes by LA-focused images were obtained faster than using the reference method (1.2 vs 4.5 min, p < 0.001). LA strain (εs: bias 7%, LOA = 25, - 11%; εe: bias 4%, LOA = 15, - 8%; εa: bias 3%, LOA = 14, - 8%) was significantly higher in standard vs. LA-focused images (p < 0.001). CONCLUSION: LA volumes and LAEF measured using dedicated LA-focused long-axis cine images are more accurate than using standard LV-focused cine images. Moreover, LA strain is significantly lower in LA-focused vs. standard images.

Blood pressure variability: methodological aspects, clinical relevance and practical indications for management - a European Society of Hypertension position paper ∗.

Blood pressure is not a static parameter, but rather undergoes continuous fluctuations over time, as a result of the interaction between environmental and behavioural factors on one side and intrinsic cardiovascular regulatory mechanisms on the other side. Increased blood pressure variability (BPV) may indicate an impaired cardiovascular regulation and may represent a cardiovascular risk factor itself, having been associated with increased all-cause and cardiovascular mortality, stroke, coronary artery disease, heart failure, end-stage renal disease, and dementia incidence. Nonetheless, BPV was considered only a research issue in previous hypertension management guidelines, because the available evidence on its clinical relevance presents several gaps and is based on heterogeneous studies with limited standardization of methods for BPV assessment. The aim of this position paper, with contributions from members of the European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability and from a number of international experts, is to summarize the available evidence in the field of BPV assessment methodology and clinical applications and to provide practical indications on how to measure and interpret BPV in research and clinical settings based on currently available data. Pending issues and clinical and methodological recommendations supported by available evidence are also reported. The information provided by this paper should contribute to a better standardization of future studies on BPV, but should also provide clinicians with some indications on how BPV can be managed based on currently available data.

An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar.

BACKGROUND AND OBJECTIVES: Myocardial infarction scar (MIS) assessment by cardiac magnetic resonance provides prognostic information and guides patients' clinical management. However, MIS segmentation is time-consuming and not performed routinely. This study presents a deep-learning-based computational workflow for the segmentation of left ventricular (LV) MIS, for the first time performed on state-of-the-art dark-blood late gadolinium enhancement (DB-LGE) images, and the computation of MIS transmurality and extent. METHODS: DB-LGE short-axis images of consecutive patients with myocardial infarction were acquired at 1.5T in two centres between Jan 1, 2019, and June 1, 2021. Two convolutional neural network (CNN) models based on the U-Net architecture were trained to sequentially segment the LV and MIS, by processing an incoming series of DB-LGE images. A 5-fold cross-validation was performed to assess the performance of the models. Model outputs were compared respectively with manual (LV endo- and epicardial border) and semi-automated (MIS, 4-Standard Deviation technique) ground truth to assess the accuracy of the segmentation. An automated post-processing and reporting tool was developed, computing MIS extent (expressed as relative infarcted mass) and transmurality. RESULTS: The dataset included 1355 DB-LGE short-axis images from 144 patients (MIS in 942 images). High performance (> 0.85) as measured by the Intersection over Union metric was obtained for both the LV and MIS segmentations on the training sets. The performance for both LV and MIS segmentations was 0.83 on the test sets. Compared to the 4-Standard Deviation segmentation technique, our system was five times quicker (<1 min versus 7 ± 3 min), and required minimal user interaction. CONCLUSIONS: Our solution successfully addresses different issues related to automatic MIS segmentation, including accuracy, time-effectiveness, and the automatic generation of a clinical report.

Clinical application of CMR in cardiomyopathies: evolving concepts and techniques : A position paper of myocardial and pericardial diseases and cardiac magnetic resonance working groups of Italian society of cardiology.

Cardiac magnetic resonance (CMR) has become an essential tool for the evaluation of patients affected or at risk of developing cardiomyopathies (CMPs). In fact, CMR not only provides precise data on cardiac volumes, wall thickness, mass and systolic function but it also a non-invasive characterization of myocardial tissue, thus helping the early diagnosis and the precise phenotyping of the different CMPs, which is essential for early and individualized treatment of patients. Furthermore, several CMR characteristics, such as the presence of extensive LGE or abnormal mapping values, are emerging as prognostic markers, therefore helping to define patients' risk. Lastly new experimental CMR techniques are under investigation and might contribute to widen our knowledge in the field of CMPs. In this perspective, CMR appears an essential tool to be systematically applied in the diagnostic and prognostic work-up of CMPs in clinical practice. This review provides a deep overview of clinical applicability of standard and emerging CMR techniques in the management of CMPs.

Myocardial Fibrosis at Cardiac MRI Helps Predict Adverse Clinical Outcome in Patients with Mitral Valve Prolapse.

Background Patients with mitral valve prolapse (MVP) may develop adverse outcomes even in the absence of mitral regurgitation or left ventricular (LV) dysfunction. Purpose To investigate the prognostic value of mitral annulus disjunction (MAD) and myocardial fibrosis at late gadolinium enhancement (LGE) cardiac MRI in patients with MVP without moderate-to-severe mitral regurgitation or LV dysfunction. Materials and Methods In this longitudinal retrospective study, 118 144 cardiac MRI studies were evaluated between October 2007 and June 2020 at 15 European tertiary medical centers. Follow-up was from the date of cardiac MRI examination to June 2020; the minimum and maximum follow-up intervals were 6 months and 156 months, respectively. Patients were excluded if at least one of the following conditions was present: cardiomyopathy, LV ejection fraction less than 40%, ischemic heart disease, congenital heart disease, inflammatory heart disease, moderate or worse mitral regurgitation, participation in competitive sport, or electrocardiogram suggestive of channelopathies. In the remainder, cardiac MRI studies were reanalyzed, and patients were included if they were aged 18 years or older, MVP was diagnosed at cardiac MRI, and clinical information and electrocardiogram monitoring were available within 3 months from cardiac MRI examination. The end point was a composite of adverse outcomes: sustained ventricular tachycardia (VT), sudden cardiac death (SCD), or unexplained syncope. Multivariable Cox regression analysis was performed. Results A total of 474 patients (mean age, 47 years ± 16 [SD]; 244 women) were included. Over a median follow-up of 3.3 years, 18 patients (4%) reached the study end point. LGE presence (hazard ratio, 4.2 [95% CI: 1.5, 11.9]; P = .006) and extent (hazard ratio, 1.2 per 1% increase [95% CI: 1.1, 1.4]; P = .006), but not MAD presence (P = .89), were associated with clinical outcome. LGE presence had incremental prognostic value over MVP severity and sustained VT and aborted SCD at baseline (area under the receiver operating characteristic curve, 0.70 vs 0.62; P = .03). Conclusion In contrast to mitral annulus disjunction, myocardial fibrosis determined according to late gadolinium enhancement at cardiac MRI was associated with adverse outcome in patients with mitral valve prolapse without moderate-to-severe mitral regurgitation or left ventricular dysfunction. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Gerber in this issue.

Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional long short-term memory networks.

Purpose: Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in coronavirus disease 2019 (COVID-19) patients but are not part of clinical routine because the required manual segmentation of lung lesions is prohibitively time consuming. We aim to automatically segment ground-glass opacities and high opacities (comprising consolidation and pleural effusion). Approach: We propose a new fully automated deep-learning framework for fast multi-class segmentation of lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional long short-term memory (ConvLSTM) networks. Utilizing the expert annotations, model training was performed using five-fold cross-validation to segment COVID-19 lesions. The performance of the method was evaluated on CT datasets from 197 patients with a positive reverse transcription polymerase chain reaction test result for SARS-CoV-2, 68 unseen test cases, and 695 independent controls. Results: Strong agreement between expert manual and automatic segmentation was obtained for lung lesions with a Dice score of 0.89 ± 0.07 ; excellent correlations of 0.93 and 0.98 for ground-glass opacity (GGO) and high opacity volumes, respectively, were obtained. In the external testing set of 68 patients, we observed a Dice score of 0.89 ± 0.06 as well as excellent correlations of 0.99 and 0.98 for GGO and high opacity volumes, respectively. Computations for a CT scan comprising 120 slices were performed under 3 s on a computer equipped with an NVIDIA TITAN RTX GPU. Diagnostically, the automated quantification of the lung burden % discriminate COVID-19 patients from controls with an area under the receiver operating curve of 0.96 (0.95-0.98). Conclusions: Our method allows for the rapid fully automated quantitative measurement of the pneumonia burden from CT, which can be used to rapidly assess the severity of COVID-19 pneumonia on chest CT.

Intravenous iron therapy improves the hypercapnic ventilatory response and sleep disordered breathing in chronic heart failure.

AIMS: Intravenous iron therapy can improve symptoms in patients with heart failure, anaemia and iron deficiency. The mechanisms underlying such an improvement might involve chemoreflex sensing and nocturnal breathing patterns. METHODS AND RESULTS: Patients with heart failure, reduced left ventricular ejection fraction, anaemia (haemoglobin <13 g/dl in men; <12 g/dl in women) and iron deficiency (ferritin <100 or 100-299 µg/L with transferrin saturation <20%) were 2:1 randomized to patient-tailored intravenous ferric carboxymaltose dose or placebo. Chemoreflex sensitivity cardiorespiratory sleep study, symptom assessment and cardiopulmonary exercise test were performed before and 2 weeks after the last treatment dose. Fifty-eight patients (38 active arm/20 placebo arm) completed the study. Intravenous iron was associated with less severe symptoms, higher haemoglobin (12.5 ± 1.4 vs. 11.7 ± 1.0 mg/dl, p < 0.05) and improved haematinic parameters. Ferric carboxymaltose improved the central hypercapnic ventilatory response (-25.8%, p < 0.05 vs. placebo), without changes in peripheral chemosensitivity. In particular, the central hypercapnic ventilatory responses passed from 4.6 ± 6.5 to 2.9 ± 2.9 L/min/mmHg after ferric carboxymaltose and from 4.4 ± 4.6 to 4.6 ± 3.9 L/min/mmHg after placebo (ptreatment*condition  = 0.046). In patients presenting with sleep-related breathing disorder, apnoea-hypopnoea index was reduced with active treatment as compared to placebo (12 ± 11 vs. 19 ± 13 events/h, p < 0.05). After ferric carboxymaltose, but not after placebo, both peak oxygen uptake (VO2 ) increased (Δ1.1 ± 2.0 ml/kg/min, p < 0.05) and VO2 /workload slope was steeper (Δ0.67 ± 1.7 L/min/W, p < 0.01). CONCLUSIONS: Intravenous ferric carboxymaltose improves the hypercapnic ventilatory response and sleep-related breathing disorders in patients with heart failure, anaemia and iron deficiency. These newly described findings, along with improved oxygen delivery to exercising muscles, likely contribute to the favourable effects of ferric carboxymaltose in anaemic patients with heart failure.

Changes in smell and taste perception related to COVID-19 infection: a case-control study.

The main aim of the present study was to psychophysically evaluate smell and taste functions in hospitalized COVID-19 patients and to compare those results with a group of healthy subjects. Another aim of the study was to assess the relationship of changes in patients' smell and taste functions with a number of clinical parameters, symptoms, and other physiological signs as well as with severity of disease. Olfactory and gustatory functions were tested in 61 hospitalized patients positive for SARS-CoV-2 infection and in a control group of 54 healthy individuals. Overall, we found a significant impairment of olfactory and gustatory functions in COVID-19 patients compared with the control group. Indeed, about 45% of patients self-reported complaints about or loss of either olfactory or gustatory functions. These results were confirmed by psychophysical testing, which showed a significantly reduced performance in terms of intensity perception and identification ability for both taste and smell functions in COVID-19 patients. Furthermore, gustatory and olfactory impairments tended to be more evident in male patients suffering from more severe respiratory failure (i.e., pneumonia with need of respiratory support need during hospitalization).

Effective Study: Development and Application of a Question-Driven, Time-Effective Cardiac Magnetic Resonance Scanning Protocol.

Background Long scanning times impede cardiac magnetic resonance (CMR) clinical uptake. A "one-size-fits-all" shortened, focused protocol (eg, only function and late-gadolinium enhancement) reduces scanning time and costs, but provides less information. We developed 2 question-driven CMR and stress-CMR protocols, including tailored advanced tissue characterization, and tested their effectiveness in reducing scanning time while retaining the diagnostic performances of standard protocols. Methods and Results Eighty three consecutive patients with cardiomyopathy or ischemic heart disease underwent the tailored CMR. Each scan consisted of standard cines, late-gadolinium enhancement imaging, native T1-mapping, and extracellular volume. Fat/edema modules, right ventricle cine, and in-line quantitative perfusion mapping were performed as clinically required. Workflow was optimized to avoid gaps. Time target was <30 minutes for a CMR and <35 minutes for a stress-CMR. CMR was considered impactful when its results drove changes in diagnosis or management. Advanced tissue characterization was considered impactful when it changed the confidence level in the diagnosis. The quality of the images was assessed. A control group of 137 patients was identified among scans performed before February 2020. Compared with standard protocols, the average scan duration dropped by >30% (CMR: from 42±8 to 28±6 minutes; stress-CMR: from 50±10 to 34±6 minutes, both P<0.0001). Independent on the protocol, CMR was impactful in ≈60% cases, and advanced tissue characterization was impactful in >45% of cases. Quality grading was similar between the 2 protocols. Tailored protocols did not require additional staff. Conclusions Tailored CMR and stress-CMR protocols including advanced tissue characterization are accurate and time-effective for cardiomyopathies and ischemic heart disease.

Automated left atrial volume measurement by two-dimensional speckle-tracking echocardiography: feasibility, accuracy, and reproducibility.

AIMS: A byproduct of left atrial (LA) strain analysis is the automated measurement of LA maximal volume (LAVmax), which may decrease the time of echocardiography reporting, and increase the reproducibility of the LAVmax measurement. However, the automated measurement of LAVmax by two-dimensional speckle-tracking analysis (2DSTE) has never been validated. Accordingly, we sought to (i) assess the feasibility of automated LAVmax measurement by 2DSTE; (ii) compare the automated LAVmax by 2DSTE with conventional two-dimensional (2DE) biplane and three-dimensional echocardiography (3DE) measurements; and (iii) evaluate the accuracy and reproducibility of the three echocardiography techniques. METHODS AND RESULTS: LAVmax (34-197 mL) were obtained from 198/210 (feasibility 94%) consecutive patients (median age 67 years, 126 men) by 2DSTE, 2DE, and 3DE. 2DE and 2DSTE measurements resulted in similar LAVmax values [bias = 1.5 mL, limits of agreement (LOA) ± 7.5 mL], and slightly underestimated 3DE LAVmax (biases = -5 mL, LOA ± 17 mL and -6 mL, LOA ± 16 mL, respectively). LAVmax by 2DSTE and 2DE were strongly correlated to those obtained by cardiac magnetic resonance (CMR) (r = 0.946 and r = 0.935, respectively; P < 0.001). However, LAVmax obtained by 2DSTE (bias = -9.5 mL, LOA ± 16 mL) and 2DE (bias = -8 mL, LOA ± 17 mL) were significantly smaller than those measured by CMR. Conversely, 3DE LAVmax were similar to CMR (bias = -2 mL, LOA ± 10 mL). Excellent intra- and inter-observer intraclass correlations were found for 3DE (0.995 and 0.995), 2DE (0.990 and 0.988), and 2DSTE (0.990 and 0.989). CONCLUSION: Automated LAVmax measurement by 2DSTE is highly feasible, highly reproducible, and provided similar values to conventional 2DE calculations in consecutive patients with a wide range of LAVmax.

Recent advances in multimodality imaging of the tricuspid valve.

INTRODUCTION: The tricuspid valve (TV) and the right heart chambers are complex three-dimensional structures that are difficult to assess using tomographic imaging techniques. The progressive aging of the general population and the advancements in treating left-sided heart diseases by transcatheter procedures have contributed to the tricuspid regurgitation (TR) becoming a major public health problem associated with progression to refractory heart failure and poor outcome. Recent advances in multimodality cardiac imaging allow a better understanding of the pathophysiology of TR that may translate in better management of patients. AREAS COVERED: Three-dimensional echocardiography, cardiac magnetic resonance, and computed tomography provide complementary information to i. assess the TV complex; ii. identify the etiology and the mechanisms of TR; iii. evaluate its severity and hemodynamic consequences; iv. explore the remodeling of the right heart chambers; and v. properly plan, guide, and monitor the transcatheter interventions aimed to reduce the severity of TR. EXPERT OPINION: We need thorough understanding of both the TV and the right heart chamber geometry and function to understand the pathophysiology of TR. The integrated use of multimodality cardiac imaging is pivotal to assess patients with TR and to identify tailored and timely treatment of TR in properly selected patients.

Age matters: differences in exercise-induced cardiovascular remodelling in young and middle aged healthy sedentary individuals.

AIMS: Remodelling of the cardiovascular system (including heart and vasculature) is a dynamic process influenced by multiple physiological and pathological factors. We sought to understand whether remodelling in response to a stimulus, exercise training, altered with healthy ageing. METHODS: A total of 237 untrained healthy male and female subjects volunteering for their first time marathon were recruited. At baseline and after 6 months of unsupervised training, race completers underwent tests including 1.5T cardiac magnetic resonance, brachial and non-invasive central blood pressure assessment. For analysis, runners were divided by age into under or over 35 years (U35, O35). RESULTS: Injury and completion rates were similar among the groups; 138 runners (U35: n = 71, women 49%; O35: n = 67, women 51%) completed the race. On average, U35 were faster by 37 minutes (12%). Training induced a small increase in left ventricular mass in both groups (3 g/m2, P < 0.001), but U35 also increased ventricular cavity sizes (left ventricular end-diastolic volume (EDV)i +3%; left ventricular end-systolic volume (ESV)i +8%; right ventricular end-diastolic volume (EDV)i +4%; right ventricular end-systolic volume (ESV)i +5%; P < 0.01 for all). Systemic aortic compliance fell in the whole sample by 7% (P = 0.020) and, especially in O35, also systemic vascular resistance (-4% in the whole sample, P = 0.04) and blood pressure (systolic/diastolic, whole sample: brachial -4/-3 mmHg, central -4/-2 mmHg, all P < 0.001; O35: brachial -6/-3 mmHg, central -6/-4 mmHg, all P < 0.001). CONCLUSION: Medium-term, unsupervised physical training in healthy sedentary individuals induces measurable remodelling of both heart and vasculature. This amount is age dependent, with predominant cardiac remodelling when younger and predominantly vascular remodelling when older.

Home blood pressure monitoring: methodology, clinical relevance and practical application: a 2021 position paper by the Working Group on Blood Pressure Monitoring and Cardiovascular Variability of the European Society of Hypertension.

The present paper provides an update of previous recommendations on Home Blood Pressure Monitoring from the European Society of Hypertension (ESH) Working Group on Blood Pressure Monitoring and Cardiovascular Variability sequentially published in years 2000, 2008 and 2010. This update has taken into account new evidence in this field, including a recent statement by the American Heart association, as well as technological developments, which have occurred over the past 20 years. The present document has been developed by the same ESH Working Group with inputs from an international team of experts, and has been endorsed by the ESH.

May Measurement Month 2019: an analysis of blood pressure screening results from Italy.

Cardiovascular (CV) diseases are burdened by high mortality and morbidity, being responsible for half of the deaths in Europe. Although hypertension is recognized as the most important CV risk factor, hypertension awareness, and blood pressure (BP) control are still unsatisfactory. In 2017 and 2018, respectively >10 000 and >5000 individuals took part in the May Measurement Month (MMM) campaign in Italy, of whom 30.6% and 26.3% were found to have high BP, respectively. To raise public awareness on the importance of hypertension and to collect BP data on a nation-wide scale in Italy. In the frame of the MMM campaign, an opportunistic cross-sectional survey of volunteers aged ≥18 years was carried out in May 2019. BP measurement, the definition of hypertension, and statistical analysis followed the standard MMM protocol. Screening was conducted in multiple sites by health personnel. Among the 10 182 people screened (females: 52.3%, mean age 58 ± 16years) mean BP was 127/78 mmHg, and 3171 (31.1%) participants had arterial hypertension, of whom 62.1% were aware of being hypertensive. Diabetes, body mass index >25 kg/m2 were associated with higher BP and previous myocardial infarction with lower BP. For the third consecutive year we collected a nation-wide snapshot of BP control in a large sample of individuals. The high participation, with some yearly fluctuations likely due to the limitations of the sampling technique, confirms the power of this kind of health campaign in reaching a significant number of people to raise awareness on health topics.

Vitamin D and COVID-19 severity and related mortality: a prospective study in Italy.

BACKGROUND: Vitamin D deficiency has been suggested to favor a poorer outcome of Coronavirus disease-19 (COVID-19). We aimed to assess if 25-hydroxyvitamin-D (25OHD) levels are associated with interleukin 6 (IL-6) levels and with disease severity and mortality in COVID-19. METHODS: We prospectively studied 103 in-patients admitted to a Northern-Italian hospital (age 66.1 ± 14.1 years, 70 males) for severely-symptomatic COVID-19. Fifty-two subjects with SARS-CoV-2 infection but mild COVID-19 symptoms (mildly-symptomatic COVID-19 patients) and 206 subjects without SARS-CoV-2 infection were controls. We measured 25OHD and IL-6 levels at admission and focused on respiratory outcome during hospitalization. RESULTS: Severely-symptomatic COVID-19 patients had lower 25OHD levels (18.2 ± 11.4 ng/mL) than mildly-symptomatic COVID-19 patients and non-SARS-CoV-2-infected controls (30.3 ± 8.5 ng/mL and 25.4 ± 9.4 ng/mL, respectively, p < 0.0001 for both comparisons). 25OHD and IL-6 levels were respectively lower and higher in severely-symptomatic COVID-19 patients admitted to intensive care Unit [(ICU), 14.4 ± 8.6 ng/mL and 43.0 (19.0-56.0) pg/mL, respectively], than in those not requiring ICU admission [22.4 ± 1.4 ng/mL, p = 0.0001 and 16.0 (8.0-32.0) pg/mL, p = 0.0002, respectively]. Similar differences were found when comparing COVID-19 patients who died in hospital [13.2 ± 6.4 ng/mL and 45.0 (28.0-99.0) pg/mL] with survivors [19.3 ± 12.0 ng/mL, p = 0.035 and 21.0 (10.5-45.9) pg/mL, p = 0.018, respectively). 25OHD levels inversely correlated with: i) IL-6 levels (ρ - 0.284, p = 0.004); ii) the subsequent need of the ICU admission [relative risk, RR 0.99, 95% confidence interval (95%CI) 0.98-1.00, p = 0.011] regardless of age, gender, presence of at least 1 comorbidity among obesity, diabetes, arterial hypertension, creatinine, IL-6 and lactate dehydrogenase levels, neutrophil cells, lymphocytes and platelets count; iii) mortality (RR 0.97, 95%CI, 0.95-0.99, p = 0.011) regardless of age, gender, presence of diabetes, IL-6 and C-reactive protein and lactate dehydrogenase levels, neutrophil cells, lymphocytes and platelets count. CONCLUSION: In our COVID-19 patients, low 25OHD levels were inversely correlated with high IL-6 levels and were independent predictors of COVID-19 severity and mortality.

Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional LSTM networks.

Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in Coronavirus disease 2019 (COVID-19) patients, but are not part of the clinical routine since required manual segmentation of lung lesions is prohibitively time-consuming. We propose a new fully automated deep learning framework for quantification and differentiation between lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional Long Short-Term Memory (LSTM) networks. Utilizing the expert annotations, model training was performed using 5-fold cross-validation to segment ground-glass opacity and high opacity (including consolidation and pleural effusion). The performance of the method was evaluated on CT data sets from 197 patients with positive reverse transcription polymerase chain reaction test result for SARS-CoV-2. Strong agreement between expert manual and automatic segmentation was obtained for lung lesions with a Dice score coefficient of 0.876 ± 0.005; excellent correlations of 0.978 and 0.981 for ground-glass opacity and high opacity volumes. In the external validation set of 67 patients, there was dice score coefficient of 0.767 ± 0.009 as well as excellent correlations of 0.989 and 0.996 for ground-glass opacity and high opacity volumes. Computations for a CT scan comprising 120 slices were performed under 2 seconds on a personal computer equipped with NVIDIA Titan RTX graphics processing unit. Therefore, our deep learning-based method allows rapid fully-automated quantitative measurement of pneumonia burden from CT and may generate the big data with an accuracy similar to the expert readers.