Noninvasive Atherosclerotic Phenotyping: The Next Frontier into Understanding the Pathobiology of Coronary Artery Disease.

PURPOSE OF REVIEW: Despite recent advances, coronary artery disease remains one of the leading causes of mortality worldwide. Noninvasive imaging allows atherosclerotic phenotyping by measurement of plaque burden, morphology, activity and inflammation, which has the potential to refine patient risk stratification and guide personalized therapy. This review describes the current and emerging roles of advanced noninvasive cardiovascular imaging methods for the assessment of coronary artery disease. RECENT FINDINGS: Cardiac computed tomography enables comprehensive, noninvasive imaging of the coronary vasculature, and is used to assess luminal stenoses, coronary calcifications, and distinct adverse plaque characteristics, helping to identify patients prone to future events. Novel software tools, implementing artificial intelligence solutions, can automatically quantify and characterize atherosclerotic plaque from standard computed tomography datasets. These quantitative imaging biomarkers have been shown to improve patient risk stratification beyond clinical risk scores and current clinical interpretation of cardiac computed tomography. In addition, noninvasive molecular imaging in higher risk patients can be used to assess plaque activity and plaque thrombosis. Noninvasive imaging allows unique insight into the burden, morphology and activity of atherosclerotic coronary plaques. Such phenotyping of atherosclerosis can potentially improve individual patient risk prediction, and in the near future has the potential for clinical implementation.

Monocyte-to-lymphocyte ratio correlates with parathyroid hormone concentration in patients with severe symptomatic aortic stenosis.

PURPOSE: The normal healthy valve is devoid of inflammatory cells, however background of aortic stenosis (AS) may include inflammatory processes. Moreover, the link between hyperparathyroidism and heart failure is postulated. Simple whole blood analysis with indices is a beneficial tool in cardiovascular diseases' assessment. The purpose of the study was to evaluate correlation between parathyroid hormone (PTH) and simple blood parameters in severe AS. MATERIAL AND METHODS: The study included 62 patients with severe AS. Patients with inflammatory or autoimmune co-morbidities were excluded. Blood samples were collected, and clinical and demographic data were analyzed. RESULTS: The final study group comprised 55 patients (31 females, 56.4%; mean age 77.13 (SD 6.76)). In 23 patients (41.8%), PTH concentration was markedly increased. The study group was divided into two subgroups according to the PTH concentration. Patients from both groups did not differ significantly in terms of age and co-morbidities. PTH concentration correlated positively with monocyte-lymphocyte ratio (MLR) (p â€‹= â€‹0.008, Spearman rho 0.356) and platelet-lymphocyte ratio (PLR) (p â€‹= â€‹0.047, Spearman rho 0.269), creatinine level (p â€‹= â€‹0.001, Spearman rho 0.425) and glomerular filtration rate (GFR-MDRD) (p â€‹= â€‹0.009, Spearman rho -0.349). The multivariable logistic regression with backward analysis revealed MLR (p â€‹= â€‹0.029) and GFR (p â€‹= â€‹0.028) as independent significant predictors of abnormal PTH values. The receiver operator characteristics (ROC) curve was performed for the model of MLR and GFR-MDRD (AUC â€‹= â€‹0.777), yielding the sensitivity of 60.9% and specificity of 90.6%. CONCLUSIONS: PTH concentration correlates with monocyte-to-lymphocyte and platelet-to-lymphocyte ratios in calcified AS.

Impact of previous coronary artery revascularization on outcomes in patients undergoing transcatheter aortic valve implantation.

Introduction: Coexistence of coronary artery disease (CAD) in patients with severe aortic stenosis (AS) referred for transcatheter aortic valve implantation (TAVI) raises questions regarding the safety and efficacy of TAVI in this subset of patients. Aim: To evaluate the impact of previous coronary revascularization in terms of percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) on clinical outcomes after TAVI. Material and methods: A total of 507 consecutive patients who underwent TAVI were divided into: non-revascularization (NR), post-PCI and post-CABG groups. The endpoints were established according to VARC-2 definitions. Results: Patients with previous coronary revascularization (36.7% of the population) were younger, more often male and their EuroSCORE II risk evaluation was significantly higher (NR 7.9% vs. post-PCI 8.0% vs. post-CABG 20.5%, p < 0.0001). Patients after PCI or CABG prior to TAVI had similar 30-day all-cause mortality rates as those without coronary revascularization at baseline (NR vs. post-PCI vs. post-CABG: 8.1% vs. 5.5% vs. 6.8%, respectively; p = 0.6). There were no differences in 12-month all-cause mortality rates between groups (NR vs. post-PCI vs. post-CABG: 15.3% vs. 14.2% vs. 16.9%, respectively; log-rank p = 0.67). In the Cox proportional-hazards regression model, acute kidney injury stage 2-3 (HR = 3.7, 95% CI: 2.14-6.33; p < 0.001) and post-TAVI stroke (HR = 3.5, 95% CI: 1.57-7.8; p = 0.002) were independently correlated with 1-year mortality. Conclusions: TAVI seems to be a safe and effective procedure for the treatment of severe AS in patients with previous coronary revascularization.

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.

Influence of cusp morphology and sex on quantitative valve composition in severe aortic stenosis.

AIMS: Aortic stenosis is characterized by fibrosis and calcification of the valve, with a higher proportion of fibrosis observed in women. Stenotic bicuspid aortic valves progress more rapidly than tricuspid valves, which may also influence the relative composition of the valve. We aimed to investigate the influence of cusp morphology on quantitative aortic valve composition quantified from contrast-enhanced computed tomography angiography in severe aortic stenosis. METHODS AND RESULTS: Patients undergoing transcatheter aortic valve implantation with bicuspid and tricuspid valves were propensity matched 1:1 by age, sex, and comorbidities. Computed tomography angiograms were analysed using semi-automated software to quantify the fibrotic and calcific scores (volume/valve annular area) and the fibro-calcific ratio (fibrotic score/calcific score). The study population (n = 140) was elderly (76 ± 10 years, 62% male) and had a peak aortic jet velocity of 4.1 ± 0.7 m/s. Compared with those with tricuspid valves (n = 70), patients with bicuspid valves (n = 70) had higher fibrotic scores [204 (interquartile range 118-267) vs. 144 (99-208) mm3/cm2, P = 0.006] with similar calcific scores (P = 0.614). Women had greater fibrotic scores than men in bicuspid [224 (181-307) vs. 169 (109-247) mm3/cm2, P = 0.042] but not tricuspid valves (P = 0.232). Men had greater calcific scores than women in both bicuspid [203 (124-355) vs. 130 (70-182) mm3/cm2, P = 0.008] and tricuspid [177 (136-249) vs. 100 (62-150) mm3/cm2, P = 0.004] valves. Among both valve types, women had a greater fibro-calcific ratio compared with men [tricuspid 1.86 (0.94-2.56) vs. 0.86 (0.54-1.24), P = 0.001 and bicuspid 1.78 (1.21-2.90) vs. 0.74 (0.44-1.53), P = 0.001]. CONCLUSIONS: In severe aortic stenosis, bicuspid valves have proportionately more fibrosis than tricuspid valves, especially in women.

Advanced Cardiac Imaging in the Assessment of Aortic Stenosis.

Aortic stenosis is the most common form of valve disease in the Western world and a major healthcare burden. Although echocardiography remains the central modality for the diagnosis and assessment of aortic stenosis, recently, advanced cardiac imaging with cardiovascular magnetic resonance, computed tomography, and positron emission tomography have provided invaluable pathological insights that may guide the personalized management of the disease. In this review, we discuss applications of these novel non-invasive imaging modalities for establishing the diagnosis, monitoring disease progression, and eventually planning the invasive treatment of aortic stenosis.

Valve-in-valve transcatheter transfemoral mitral valve implantation (ViV-TMVI): Characteristics and early results from nationwide registry.

BACKGROUND: Valve-in-valve transcatheter transfemoral mitral valve implantation (ViV-TMVI) is an emerging treatment alternative to reoperation in high surgical risk patients with a failed mitral bioprostheses. AIM: To describe characteristics and evaluate 30-day outcomes of ViV-TMVI in the Polish population. METHODS: Nationwide registry was initiated to collect data of all patients with failed mitral bioprosthesis undergoing ViV-TMVI in Poland. This study presents 30-days clinical and echocardiographic follow-up. RESULTS: Overall, 27 ViV-TMVI were performed in 8 centers until May 2022 (85% since 2020). Mean (standard deviation [SD]) age was 73 (11.6) years with the median (interquartile range [IQR]) STS score of 5.3% (4.3%-14.3%). Mean (SD) time between surgical implantation and ViV-TMVI was 8.2 (3.2) years. Failed Hancock II (29%) and Perimount Magna (22%) were most frequently treated. Mechanisms of failure were equally often pure mitral regurgitation or stenosis (both 37%) with mixed etiology in 26%. Balloon-expandable Sapien 3/Ultra were used in all but 1 patient. Technical success was 96.3% (1 patient required additional prosthesis). Mean (SD) transvalvular mitral gradient reached 6.7 (2.2) mm Hg and mitral valve area was 1.8 (0.4) cm². None of the patients had moderate or severe mitral regurgitation with only 14.8% graded as mild. In 92.6% device success (2 patients had mean gradient ≥10 mm Hg) and in 85.6% procedural success was present. There were no deaths, cerebrovascular events or need for mitral valve surgery during 30-day follow-up. CONCLUSIONS: In short-term observation ViV-TMVI is safe and effective alternative for patients with failed mitral bioprosthesis at high surgical risk of re-operation. Longer observations on larger sample are warranted.

Relationship between impaired myocardial blood flow by positron emission tomography and low-attenuation plaque burden and pericoronary adipose tissue attenuation from coronary computed tomography: From the prospective PACIFIC trial.

BACKGROUND: Positron emission tomography (PET) is the clinical gold standard for quantifying myocardial blood flow (MBF). Pericoronary adipose tissue (PCAT) attenuation may detect vascular inflammation indirectly. We examined the relationship between MBF by PET and plaque burden and PCAT on coronary CT angiography (CCTA). METHODS: This post hoc analysis of the PACIFIC trial included 208 patients with suspected coronary artery disease (CAD) who underwent [15O]H2O PET and CCTA. Low-attenuation plaque (LAP, < 30HU), non-calcified plaque (NCP), and PCAT attenuation were measured by CCTA. RESULTS: In 582 vessels, 211 (36.3%) had impaired per-vessel hyperemic MBF (≤ 2.30 mL/min/g). In multivariable analysis, LAP burden was independently and consistently associated with impaired hyperemic MBF (P = 0.016); over NCP burden (P = 0.997). Addition of LAP burden improved predictive performance for impaired hyperemic MBF from a model with CAD severity and calcified plaque burden (P < 0.001). There was no correlation between PCAT attenuation and hyperemic MBF (r = - 0.11), and PCAT attenuation was not associated with impaired hyperemic MBF in univariable or multivariable analysis of all vessels (P > 0.1). CONCLUSION: In patients with stable CAD, LAP burden was independently associated with impaired hyperemic MBF and a stronger predictor of impaired hyperemic MBF than NCP burden. There was no association between PCAT attenuation and hyperemic MBF.

Sex differences in computed tomography angiography-derived coronary plaque burden in relation to invasive fractional flow reserve.

BACKGROUND: Distinct sex-related differences exist in coronary artery plaque burden and distribution. We aimed to explore sex differences in quantitative plaque burden by coronary CT angiography (CCTA) in relation to ischemia by invasive fractional flow reserve (FFR). METHODS: This post-hoc analysis of the PACIFIC trial included 581 vessels in 203 patients (mean age 58.1 â€‹± â€‹8.7 years, 63.5% male) who underwent CCTA and per-vessel invasive FFR. Quantitative assessment of total, calcified, non-calcified, and low-density non-calcified plaque burden were performed using semiautomated software. Significant ischemia was defined as invasive FFR ≤0.8. RESULTS: The per-vessel frequency of ischemia was higher in men than women (33.5% vs. 7.5%, p â€‹< â€‹0.001). Women had a smaller burden of all plaque subtypes (all p â€‹< â€‹0.01). There was no sex difference on total, calcified, or non-calcified plaque burdens in vessels with ischemia; only low-density non-calcified plaque burden was significantly lower in women (beta: -0.183, p â€‹= â€‹0.035). The burdens of all plaque subtypes were independently associated with ischemia in both men and women (For total plaque burden (5% increase): Men, OR: 1.15, 95%CI: 1.06-1.24, p â€‹= â€‹0.001; Women, OR: 1.96, 95%CI: 1.11-3.46, p â€‹= â€‹0.02). No significant interaction existed between sex and total plaque burden for predicting ischemia (interaction p â€‹= â€‹0.108). The addition of quantitative plaque burdens to stenosis severity and adverse plaque characteristics improved the discrimination of ischemia in both men and women. CONCLUSIONS: In symptomatic patients with suspected CAD, women have a lower CCTA-derived burden of all plaque subtypes compared to men. Quantitative plaque burden provides independent and incremental predictive value for ischemia, irrespective of sex.

Increased Plasma Concentrations of Extracellular Vesicles Are Associated with Pro-Inflammatory and Pro-Thrombotic Characteristics of Left and Right Ventricle Mechanical Support Devices.

Mechanical circulatory support (MCS) allows for functional left and right heart ventricle replacement. MCS induces a systemic inflammatory reaction and prothrombotic state leading to an increased risk of thrombus formation. The extracellular vesicles (EVs) are nanoparticles released from active/injured cells characterized by prothrombotic properties. Simple inflammatory parameters from whole blood count analysis have established a clinical role in everyday practice to describe immune-inflammatory activation. We hypothesized that increased plasma concentrations of EVs might be associated with the proinflammatory and pro-thrombotic characteristics of left ventricle assist device (LVAD) and right ventricle assist device (RVAD) devices. We presented a pilot study showing the concentration of peripheral blood serum, right and left ventricle mechanical assist device extracellular concentration in relation to thrombotic complication in patients treated with a biventricular pulsatile assist device (BIVAD). The observation was based on 12 replacements of pulsatile pumps during 175 days of observation. The proinflammatory characteristics of LVAD were noted. The proinflammatory and procoagulant activation by RVAD was observed. The results may provide possible explanations for the worse results of right-sided mechanical supports observed in clinical practice.

Machine learning for prediction of all-cause mortality after transcatheter aortic valve implantation.

AIMS: Prediction of adverse events in mid-term follow-up after transcatheter aortic valve implantation (TAVI) is challenging. We sought to develop and validate a machine learning model for prediction of 1-year all-cause mortality in patients who underwent TAVI and were discharged following the index procedure. METHODS AND RESULTS: The model was developed on data of patients who underwent TAVI at a high-volume centre between January 2013 and March 2019. Machine learning by extreme gradient boosting was trained and tested with repeated 10-fold hold-out testing using 34 pre- and 25 peri-procedural clinical variables. External validation was performed on unseen data from two other independent high-volume TAVI centres. Six hundred four patients (43% men, 81 ± 5 years old, EuroSCORE II 4.8 [3.0-6.3]%) in the derivation and 823 patients (46% men, 82 ± 5 years old, EuroSCORE II 4.7 [2.9-6.0]%) in the validation cohort underwent TAVI and were discharged home following the index procedure. Over the 12 months of follow-up, 68 (11%) and 95 (12%) subjects died in the derivation and validation cohorts, respectively. In external validation, the machine learning model had an area under the receiver-operator curve of 0.82 (0.78-0.87) for prediction of 1-year all-cause mortality following hospital discharge after TAVI, which was superior to pre- and peri-procedural clinical variables including age 0.52 (0.46-0.59) and the EuroSCORE II 0.57 (0.51-0.64), P < 0.001 for a difference. CONCLUSION: Machine learning based on readily available clinical data allows accurate prediction of 1-year all-cause mortality following a successful TAVI.

Nationwide experience with transcarotid transcatheter aortic valve implantation: Insights from the POL-CAROTID registry.

BACKGROUND: The carotid artery is an alternative access route for transcatheter aortic valve implantation (TAVI), especially useful in patients unsuitable for traditional access routes including transfemoral (TF), subclavian, transapical, and aortic. AIMS: To investigate the feasibility and safety of transcarotid (TC) access for TAVI in comparison to the TF approach in a multicenter setting. METHODS: A total of 41 patients, treated between December 2014 and December 2018, were retrospectively reported to the Polish Registry of Common Carotid Artery Access for TAVI (POL-CAROTID). The median follow-up time was 619 (365-944) days, and Valve Academic Research Consortium-2 (VARC-2) definitions were applied. Clinical outcomes were compared with 41 propensity-matched TF-TAVI patients. RESULTS: The mean (standard deviation [SD]) patients' age was 78.0 (7.2) years, and 29 patients (70.7%) were men. Prohibitive iliofemoral anatomy and/or obesity (46.3%) and/or the presence of a stent graft in the abdominal aorta (31.7%) were the most common indications for TC-TAVI. Device success for TC-TAVI was comparable with the matched TF-TAVI group (90.2% vs. 95.3%, respectively, P = 0.396), and no periprocedural mortality was observed. Moreover, early safety was similar between the two groups (92.7% vs. 95.3%, respectively, log-rank P = 0.658) with only 1 case of non-disabling stroke during the first month after TC-TAVI. Consequently, no cerebrovascular events were observed in the mid-term, and the clinical efficacy of TC-TAVI corresponded well with TF-TAVI (90.2% vs. 92.7%, respectively, log-rank P = 0.716). A total of 4 (9.8%) deaths were noted in the TC-TAVI cohort in comparison to 3 (7.3%) in the TF-TAVI group. CONCLUSIONS: The results of the study indicated that the first cohort of Polish patients with implantations of second-generation transcarotid transcatheter heart valves had a similar prognosis to TF-TAVI with regard to safety and feasibility. TC access may be considered an optimal alternative for patients in whom the TF approach is precluded.

Radiomorphological signs and clinical severity of SARS-CoV-2 lineage B.1.1.7.

Objective: We aimed to assess the differences in the severity and chest-CT radiomorphological signs of SARS-CoV-2 B.1.1.7 and non-B.1.1.7 variants. Methods: We collected clinical data of consecutive patients with laboratory-confirmed COVID-19 and chest-CT imaging who were admitted to the Emergency Department between September 1- November 13, 2020 (non-B.1.1.7 cases) and March 1-March 18, 2021 (B.1.1.7 cases). We also examined the differences in the severity and radiomorphological features associated with COVID-19 pneumonia. Total pneumonia burden (%), mean attenuation of ground-glass opacities and consolidation were quantified using deep-learning research software. Results: The final population comprised 500 B.1.1.7 and 500 non-B.1.1.7 cases. Patients with B.1.1.7 infection were younger (58.5 ± 15.6 vs 64.8 ± 17.3; p < .001) and had less comorbidities. Total pneumonia burden was higher in the B.1.1.7 patient group (16.1% [interquartile range (IQR):6.0-34.2%] vs 6.6% [IQR:1.2-18.3%]; p < .001). In the age-specific analysis, in patients <60 years B.1.1.7 pneumonia had increased consolidation burden (0.1% [IQR:0.0-0.7%] vs 0.1% [IQR:0.0-0.2%]; p < .001), and severe COVID-19 was more prevalent (11.5% vs 4.9%; p = .032). Mortality rate was similar in all age groups. Conclusion: Despite B.1.1.7 patients were younger and had fewer comorbidities, they experienced more severe disease than non-B.1.1.7 patients, however, the risk of death was the same between the two groups. Advances in knowledge: Our study provides data on deep-learning based quantitative lung lesion burden and clinical outcomes of patients infected by B.1.1.7 VOC. Our findings might serve as a model for later investigations, as new variants are emerging across the globe.

Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve-Defined Ischemia and Impaired Myocardial Blood Flow.

BACKGROUND: A pathophysiological interplay exists between plaque morphology and coronary physiology. Machine learning (ML) is increasingly being applied to coronary computed tomography angiography (CCTA) for cardiovascular risk stratification. We sought to assess the performance of a ML score integrating CCTA-based quantitative plaque features for predicting vessel-specific ischemia by invasive fractional flow reserve (FFR) and impaired myocardial blood flow (MBF) by positron emission tomography (PET). METHODS: This post-hoc analysis of the PACIFIC trial (Prospective Comparison of Cardiac Positron Emission Tomography/Computed Tomography [CT]' Single Photon Emission Computed Tomography/CT Perfusion Imaging and CT Coronary Angiography with Invasive Coronary Angiography) included 208 patients with suspected coronary artery disease who prospectively underwent CCTA' [15O]H2O PET, and invasive FFR. Plaque quantification from CCTA was performed using semiautomated software. An ML algorithm trained on the prospective NXT trial (484 vessels) was used to develop a ML score for the prediction of ischemia (FFR≤0.80), which was then evaluated in 581 vessels from the PACIFIC trial. Thereafter, the ML score was applied for predicting impaired hyperemic MBF (≤2.30 mL/min per g) from corresponding PET scans. The performance of the ML score was compared with CCTA reads and noninvasive FFR derived from CCTA (FFRCT). RESULTS: One hundred thirty-nine (23.9%) vessels had FFR-defined ischemia, and 195 (33.6%) vessels had impaired hyperemic MBF. For the prediction of FFR-defined ischemia, the ML score yielded an area under the receiver-operating characteristic curve of 0.92, which was significantly higher than that of visual stenosis grade (0.84; P<0.001) and comparable with that of FFRCT (0.93; P=0.34). Quantitative percent diameter stenosis and low-density noncalcified plaque volume had the greatest ML feature importance for predicting FFR-defined ischemia. When applied for impaired MBF prediction, the ML score exhibited an area under the receiver-operating characteristic curve of 0.80; significantly higher than visual stenosis grade (area under the receiver-operating characteristic curve 0.74; P=0.02) and comparable with FFRCT (area under the receiver-operating characteristic curve 0.77; P=0.16). CONCLUSIONS: An externally validated ML score integrating CCTA-based quantitative plaque features accurately predicts FFR-defined ischemia and impaired MBF by PET, performing superiorly to standard CCTA stenosis evaluation and comparably to FFRCT.

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.

Neutrophil-to-lymphocyte ratio as a predictor of inflammatory response in patients with acute kidney injury after transcatheter aortic valve implantation.

BACKGROUND: Persistent inflammatory response after transcatheter aortic valve implantation (TAVI) is one of the possible causes of early and mid-term postprocedural adverse events. OBJECTIVES: To establish the predictive role of whole blood parameters on inflammatory response characteristics within a 1-year follow-up. MATERIAL AND METHODS: The study group comprised 163 consecutive patients (52.1% females), mean age 78.6 (±6.6) years (± standard deviation (SD)) who underwent TAVI and completed 1-year follow-up on-site examinations. Patients were retrospectively divided into acute kidney injury (AKI) and non-AKI subgroups. Clinical and laboratory data were collected. In-hospital and follow-up outcomes were assessed. RESULTS: The clinical and procedural details did not show significant differences between AKI and non-AKI groups. Neutrophil-to-lymphocyte ratio (NLR) decreased from baseline to measurement after 1 year with a statistically significant decline in the whole study population and non-AKI subgroup (both p = 0.005). The baseline NLR cutoff value of 4.2 for the non-AKI group ((area under the curve (AUC) = 0.718, p < 0.0001; sensitivity 46.27%, specificity 92.31%) and of 3.8 for the AKI group (AUC = 0.673, p = 0.0174; sensitivity 59.25%, specificity 84%) had prognostic properties for persistent NLR elevation. CONCLUSIONS: The NLR decreases after TAVI, and this phenomenon is more evident in patients without AKI. Furthermore, baseline NLR cutoff values may be considered predictors of persistence of inflammatory response.