Computed tomography texture analysis of carotid plaque as predictor of unfavorable outcome after carotid artery stenting: A preliminary study

Novel biomarkers are advocated to manage carotid plaques. Therefore, we aimed to test the association between textural features of carotid plaque at computed tomography angiography (CTA) and unfavorable outcome after carotid artery stenting (CAS). Between January 2010 and January 2021, were selected 172 patients (median age, 77 years; 112/172, 65% men) who underwent CAS with CTA of the supra-aortic vessels performed within prior 6 months. Standard descriptors of the density histogram were derived by open-source software automated analysis obtained by CTA plaque segmentation. Multiple logistic regression analysis, receiver operating characteristic (ROC) curve analysis and the area under the ROC (AUC) were used to identify potential prognostic variables and to assess the model performance for predicting unfavorable outcome (periprocedural death or myocardial infarction and any ipsilateral acute neurological event). Unfavorable outcome occurred in 17/172 (10%) patients (median age, 79 years; 12/17, 70% men). Kurtosis was an independent predictor of unfavorable outcome (odds ratio, 0.79; confidence interval, 0.65–0.97; p = 0.029). The predictive model for unfavorable outcome including CTA textural features outperformed the model without textural features (AUC 0.789 vs 0.695, p = 0.004). In patients with stenotic carotid plaque, kurtosis derived by CTA density histogram analysis is an independent predictor of unfavorable outcome after CAS

Auditory-Perceptual Speech Features in Children With Down Syndrome.

Speech disorders occur commonly in individuals with Down syndrome (DS), although data regarding the auditory-perceptual speech features are limited. This descriptive study assessed 47 perceptual speech features during connected speech samples in 26 children with DS. The most severely affected speech features were: naturalness, imprecise consonants, hyponasality, speech rate, inappropriate silences, irregular vowels, prolonged intervals, overall loudness level, pitch level, aberrant oropharyngeal resonance, hoarse voice, reduced stress, and prolonged phonemes. These findings suggest that speech disorders in DS are due to distributed impairments involving voice, speech sound production, fluency, resonance, and prosody. These data contribute to the development of a profile of impairments in speakers with DS to guide future research and inform clinical assessment and treatment

Auditory-perceptual speech features in children with down syndrome

Speech disorders occur commonly in individuals with Down syndrome (DS), although data regarding the auditory-perceptual speech features are limited. This descriptive study assessed 47 perceptual speech features during connected speech samples in 26 children with DS. The most severely affected speech features were: naturalness, imprecise consonants, hyponasality, speech rate, inappropriate silences, irregular vowels, prolonged intervals, overall loudness level, pitch level, aberrant oropharyngeal resonance, hoarse voice, reduced stress, and prolonged phonemes. These findings suggest that speech disorders in DS are due to distributed impairments involving voice, speech sound production, fluency, resonance, and prosody. These data contribute to the development of a profile of impairments in speakers with DS to guide future research and inform clinical assessment and treatment

Quantitative CT at Follow-Up of COVID-19 Pneumonia: Relationship with Pulmonary Function Tests

Background: The role of quantitative chest computed tomography (CT) is controversial in the follow-up of patients with COVID-19 pneumonia. The aim of this study was to test during the follow-up of COVID-19 pneumonia the association between pulmonary function tests (PFTs) and quantitative parameters extrapolated from follow-up (FU) CT scans performed at least 6 months after COVID-19 onset. Methods: The study included patients older than 18 years old, admitted to the emergency department of our institution between 29 February 2020 and 31 December 2020, with a diagnosis of COVID-19 pneumonia, who underwent chest CT at admission and FU CT at least 6 months later; PFTs were performed within 6 months of FU CT. At FU CT, quantitative parameters of well-aerated lung and pneumonia extent were identified both visually and by software using CT density thresholds. The association between PFTs and quantitative parameters was tested by the calculation of the Spearman’s coefficient of rank correlation (rho). Results: The study included 40 patients (38% females; median age 63 years old, IQR, 56–71 years old). A significant correlation was identified between low attenuation areas% (%LAAs) <950 Hounsfield units (HU) and both forced expiratory volume in 1s/forced vital capacity (FEV1/FVC) ratio (rho −0.410, 95% CIs −0.639–−0.112, p = 0.008) and %DLCO (rho −0.426, 95% CIs −0.678–−0.084, p = 0.017). The remaining quantitative parameters failed to demonstrate a significant association with PFTs (p > 0.05). Conclusions: At follow-up, CT scans performed at least 6 months after COVID-19 pneumonia onset showed %LAAs that were inversely associated with %DLCO and could be considered a marker of irreversible lung damage

Qualitative and quantitative chest CT parameters as predictors of specific mortality in COVID-19 patients

Purpose: To test the association between death and both qualitative and quantitative CT parameters obtained visually and by software in coronavirus disease (COVID-19) early outbreak. Methods: The study analyzed retrospectively patients underwent chest CT at hospital admission for COVID-19 pneumonia suspicion, between February 21 and March 6, 2020. CT was performed in case of hypoxemia or moderate-to-severe dyspnea. CT scans were analyzed for quantitative and qualitative features obtained visually and by software. Cox proportional hazards regression analysis examined the association between variables and overall survival (OS). Three models were built for stratification of mortality risk: clinical, clinical/visual CT evaluation, and clinical/software-based CT assessment. AUC for each model was used to assess performance in predicting death. Results: The study included 248 patients (70% males, median age 68 years). Death occurred in 78/248 (32%) patients. Visual pneumonia extent > 40% (HR 2.15, 95% CI 1.2–3.85, P = 0.01), %high attenuation area – 700 HU > 35% (HR 2.17, 95% CI 1.2–3.94, P = 0.01), exudative consolidations (HR 2.85–2.93, 95% CI 1.61–5.05/1.66–5.16, P < 0.001), visual CAC score > 1 (HR 2.76–3.32, 95% CI 1.4–5.45/1.71–6.46, P < 0.01/P < 0.001), and CT classified as COVID-19 and other disease (HR 1.92–2.03, 95% CI 1.01–3.67/1.06–3.9, P = 0.04/P = 0.03) were significantly associated with shorter OS. Models including CT parameters (AUC 0.911–0.913, 95% CI 0.873–0.95/0.875–0.952) were better predictors of death as compared to clinical model (AUC 0.869, 95% CI 0.816–0.922; P = 0.04 for both models). Conclusions: In COVID-19 patients, qualitative and quantitative chest CT parameters obtained visually or by software are predictors of mortality. Predictive models including CT metrics were better predictors of death in comparison to clinical model