Carotid Artery Disease in the Era of Biomarkers: A Pilot Study

The intima-media thickness (IMT) and its irregularities or ulcerations in the common carotid artery (CCA) are useful tools as sentinel biomarkers for the integrity of the cardiovascular system. Total homocysteine and lipoprotein levels are the most commonly used elements in cardiovascular risk stratification. Duplex ultrasound (DUS), associated with serum biomarkers, can be used simply to assess the degree of atherosclerotic disease and cardiovascular risk. This study highlights the role of different kinds of biomarkers, showing their usefulness and potentiality in multi-district atherosclerotic patients, especially for early diagnosis and therapy effectiveness monitoring. A retrospective analysis performed from September 2021 to August 2022, of patients with carotid artery disease, was performed. A total of 341 patients with a mean age of 53.8 years were included in the study. The outcomes showed an increased risk of stroke in patients with significative carotid artery disease, nonresponsive to therapy, monitored through a series of serum biomarkers (homocysteine, C-reactive protein, and oxidized LDL). In this reported experience, the systematic use of DUS in association with the multiple biomarkers approach was effective for the early identification of patients at higher risk of disease progression or inefficient therapy

Malignant carotid body tumors: What we know, what we do, and what we need to achieve. A systematic review of the literature

: Malignant carotid body tumors (MCBT) are rare and diagnosed after detection of nodal or distant metastases. This systematic review (SR) focuses on MCBT initially approached by surgery. Preferred Reporting Items for SR and Meta-Analysis (MA) guided the articles search from 2000 to 2023 on PubMed, Scopus, and Web of Science. Among 3548 papers, 132 (337 patients) were considered for SR; of these, 20 (158 patients) for MA. Malignancy rate was 7.3%, succinate dehydrogenase (SDH) mutation 17%, age at diagnosis between 4th and 6th decades, with a higher prevalence of females. MCBTs were mostly Shamblin III, with nodal and distant metastasis in 79.7% and 44.7%, respectively. Malignancy should be suspected if CBT >4 cm, Shamblin III, painful or otherwise symptomatic, at the extremes of age, bilateral, with multifocal disease, and SDHx mutations. Levels II-III clearance should be performed to exclude nodal metastases and adjuvant treatments considered on a case-by-case basis

Acute heart failure in patients with acute aortic syndrome: Pathophysiology and clinical-prognostic implications

Aims Although acute heart failure (AHF) is a potential complication of acute aortic syndromes (AAS), its clinical details and management implications have been scarcely evaluated. This study aimed to assess prevalence, pathophysiological mechanisms, impact on treatment, and in-hospital mortality of AHF in AAS. Methods and results Data were collected from a prospective AAS registry (398 patients diagnosed between 2000 and 2013). Patients with AHF were identified by the presence of dyspnoea as the presentation symptom or radiological signs of pulmonary congestion or cardiogenic shock, including patients with cardiac tamponade (CT). AHF frequency was 28% (Stanford type A 32% vs. type B 20%, P = 0.01). Four mechanisms leading to AHF were identified, alone or in combination: CT (26%), aortic regurgitation (25%), myocardial ischaemia (17%), and hypertensive crisis (10%). In type A patients, aortic regurgitation and CT were the most frequent mechanisms, whereas myocardial ischaemia and hypertensive crisis were the most frequent in type B patients. Although no difference was noted for diagnostic times, AHF at presentation led to a longer surgical delay in type A AAS. In-hospital mortality was higher in patients with AHF compared with those without (34% vs. 17%, P < 0.001). After multivariable analysis, AHF was associated with increased risk of in-hospital death (adjusted odds ratio 1.97, 95% confidence interval 1.14-3.36, P = 0.014). Conclusion AHF occurs in more than a quarter of patients with AAS of both type A and type B, is due to a variety of pathophysiological mechanisms, and is associated with increased surgical delay and in-hospital mortality. © 2015 The Authors European Journal of Heart Failure © 2015 European Society of Cardiology

The elusive link between aortic wall histology and echocardiographic anatomy in bicuspid aortic valve: implications for prophylactic surgery

OBJECTIVE: Prediction of aortic dissection or rupture is extremely difficult in patients with bicuspid aortic valve. We aimed to identify clinical and echocardiography predictors of histological abnormalities of the aortic wall in patients with bicuspid aortic valve undergoing aortic surgery. METHODS: We assessed the histology of the aortic wall and clinical and echocardiography variables in a cohort of patients with bicuspid aortic valve (n = 127) and a wide spectrum of valvar disease who underwent replacement of the ascending aorta (with or without aortic valve surgery). Histology was classified using a 5-grade system developed by Larson and Edward. RESULTS: Histological alterations of the aortic wall were absent/mild (grade 0-1) in 77 patients (61%) and moderate/severe (grade 2-3) in 50 (39%). Patients with moderate/severe histological alterations were younger (47 ± 17 vs 53 ± 16; p = 0.042). Eighteen patients out of 48 (38%) with an ascending aorta diameter ≤ 4.5 cm had grade 2-3 aortic wall disease as did 8 out of 18 (44%) with a diameter ≤ 4 cm. Nineteen out of 46 (41%) patients with a maximal ascending aortic area/height ratio < 10 cm(2) m(-1) had moderate/severe histological alterations. Multivariate logistic regression analysis showed that the indexed diameter of the aortic annulus was significantly associated with grade 2-3 aortic wall disease (odds ratio (OR): 12.22, 95% confidence interval (CI): 1.65-90.38, p = 0.014). CONCLUSIONS: A high proportion of patients with bicuspid aortic valve and mild to moderate aortic dilatation have severe histological abnormalities of the aortic wall that are not predictable by clinical and echocardiographic findings. These observations suggest that risk stratification for aortic dissection or rupture in patients with bicuspid aortic valve is so far quite suboptimal and future investigations are warranted

Carotid Artery Disease in the Era of Biomarkers: A Pilot Study

The intima-media thickness (IMT) and its irregularities or ulcerations in the common carotid artery (CCA) are useful tools as sentinel biomarkers for the integrity of the cardiovascular system. Total homocysteine and lipoprotein levels are the most commonly used elements in cardiovascular risk stratification. Duplex ultrasound (DUS), associated with serum biomarkers, can be used simply to assess the degree of atherosclerotic disease and cardiovascular risk. This study highlights the role of different kinds of biomarkers, showing their usefulness and potentiality in multi-district atherosclerotic patients, especially for early diagnosis and therapy effectiveness monitoring. A retrospective analysis performed from September 2021 to August 2022, of patients with carotid artery disease, was performed. A total of 341 patients with a mean age of 53.8 years were included in the study. The outcomes showed an increased risk of stroke in patients with significative carotid artery disease, nonresponsive to therapy, monitored through a series of serum biomarkers (homocysteine, C-reactive protein, and oxidized LDL). In this reported experience, the systematic use of DUS in association with the multiple biomarkers approach was effective for the early identification of patients at higher risk of disease progression or inefficient therapy

Malignant carotid body tumors : What we know, what we do, and what we need to achieve. A systematic review of the literature

Malignant carotid body tumors (MCBT) are rare and diagnosed after detection of nodal or distant metastases. This systematic review (SR) focuses on MCBT initially approached by surgery. Preferred Reporting Items for SR and Meta-Analysis (MA) guided the articles search from 2000 to 2023 on PubMed, Scopus, and Web of Science. Among 3548 papers, 132 (337 patients) were considered for SR; of these, 20 (158 patients) for MA. Malignancy rate was 7.3%, succinate dehydrogenase (SDH) mutation 17%, age at diagnosis between 4th and 6th decades, with a higher prevalence of females. MCBTs were mostly Shamblin III, with nodal and distant metastasis in 79.7% and 44.7%, respectively. Malignancy should be suspected if CBT >4 cm, Shamblin III, painful or otherwise symptomatic, at the extremes of age, bilateral, with multifocal disease, and SDHx mutations. Levels II-III clearance should be performed to exclude nodal metastases and adjuvant treatments considered on a case-by-case basis.Peer reviewe

Vacuolar Proton-Translocating ATPase May Take Part in the Drug Resistance Phenotype of Glioma Stem Cells

The vacuolar proton-translocating ATPase (V-ATPase) is a transmembrane multi-protein complex fundamental in maintaining a normal intracellular pH. In the tumoral contest, its role is crucial since the metabolism underlying carcinogenesis is mainly based on anaerobic glycolytic reactions. Moreover, neoplastic cells use the V-ATPase to extrude chemotherapy drugs into the extra-cellular compartment as a drug resistance mechanism. In glioblastoma (GBM), the most malignant and incurable primary brain tumor, the expression of this pump is upregulated, making it a new possible therapeutic target. In this work, the bafilomycin A1-induced inhibition of V-ATPase in patient-derived glioma stem cell (GSC) lines was evaluated together with temozolomide, the first-line therapy against GBM. In contrast with previous published data, the proposed treatment did not overcome resistance to the standard therapy. In addition, our data showed that nanomolar dosages of bafilomycin A1 led to the blockage of the autophagy process and cellular necrosis, making the drug unusable in models which are more complex. Nevertheless, the increased expression of V-ATPase following bafilomycin A1 suggests a critical role of the proton pump in GBM stem components, encouraging the search for novel strategies to limit its activity in order to circumvent resistance to conventional therapy

A Deep Learning Model for Preoperative Differentiation of Glioblastoma, Brain Metastasis, and Primary Central Nervous System Lymphoma: An External Validation Study

(1) Background: Neuroimaging differentiation of glioblastoma, primary central nervous system lymphoma (PCNSL) and solitary brain metastasis (BM) represents a diagnostic and therapeutic challenge in neurosurgical practice, expanding the burden of care and exposing patients to additional risks related to further invasive procedures and treatment delays. In addition, atypical cases and overlapping features have not been entirely addressed by modern diagnostic research. The aim of this study was to validate a previously designed and internally validated ResNet101 deep learning model to differentiate glioblastomas, PCNSLs and BMs. (2) Methods: We enrolled 126 patients (glioblastoma: n = 64; PCNSL: n = 27; BM: n = 35) with preoperative T1Gd-MRI scans and histopathological confirmation. Each lesion was segmented, and all regions of interest were exported in a DICOM dataset. A pre-trained ResNet101 deep neural network model implemented in a previous work on 121 patients was externally validated on the current cohort to differentiate glioblastomas, PCNSLs and BMs on T1Gd-MRI scans. (3) Results: The model achieved optimal classification performance in distinguishing PCNSLs (AUC: 0.73; 95%CI: 0.62–0.85), glioblastomas (AUC: 0.78; 95%CI: 0.71–0.87) and moderate to low ability in differentiating BMs (AUC: 0.63; 95%CI: 0.52–0.76). The performance of expert neuro-radiologists on conventional plus advanced MR imaging, assessed by retrospectively reviewing the diagnostic reports of the selected cohort of patients, was found superior in accuracy for BMs (89.69%) and not inferior for PCNSL (82.90%) and glioblastomas (84.09%). (4) Conclusions: We investigated whether the previously published deep learning model was generalizable to an external population recruited at a different institution—this validation confirmed the consistency of the model and laid the groundwork for future clinical applications in brain tumour classification. This artificial intelligence-based model might represent a valuable educational resource and, if largely replicated on prospective data, help physicians differentiate glioblastomas, PCNSL and solitary BMs, especially in settings with limited resources