The value of coordinated analysis of multimodal atherosclerotic plaque imaging in the assessment of cardiovascular and cerebrovascular events.

Background: Although atherosclerosis (AS) can affect multiple vascular beds, previous studies have focused on the analysis of single-site AS plaques. Objective: The aim of this study is to explore the differences or similarities in the characteristics of atherosclerotic plaque found in the internal carotid artery, cerebral artery, and coronary artery between patients with atherosclerotic cardiovascular disease (ASCVD) and those without events. Methods: Patients aged ≥ 18 years who underwent both high-resolution vessel wall imaging (HR-VWI) and coronary computed tomography angiography (CCTA) were retrospectively collected and categorized into the ASCVD group and the non-event group. The plaques were then categorized into culprit plaques, non-culprit plaques, and non-event plaques. Plaque morphological data such as stenosis, stenosis grades, plaque length (PL), plaque volume (PV), minimal lumen area (MLA), enhancement grade, and plaque composition data such as calcified plaque volume (CPV), fibrotic plaque volume (FPV), fibro-lipid plaque volume (FLPV), lipid plaque volume (LPV), calcified plaque volume ratio (CPR), fibrotic plaque volume ratio (FPR), fibro-lipid plaque ratio (FLPR), lipid plaque volume ratio (LPR), intraplaque hemorrhage volume (IPHV), and intraplaque hemorrhage volume ratio (IPHR)were recorded and analyzed. Results: A total of 44 patients (mean age 66 years, SD 9 years, 28 men) were included. In cervicocephalic plaques, the ASCVD group had more severe stenosis grades (p = 0.030) and demonstrated significant differences in LPV, LPR, and CPV (p = 0.044, 0.030, 0.020) compared with the non-event group. In coronary plaques, the ASCVD group had plaques with greater stenosis (p < 0.001), more severe stenosis grades (p < 0.001), larger volumes (p = 0.001), longer length (p = 0.008), larger FLPV (p = 0.012), larger FPV (p = 0.002), and higher FPR (p = 0.043) compared with the non-event group. There were significant differences observed in stenosis (HR-VWI, CCTA: p < 0.001, p < 0.001), stenosis grades (HR-VWI, CCTA: p < 0.001, p < 0.001), plaque length (HR-VWI, CCTA: p = 0.028, p < 0.001), and plaque volume (HR-VWI, CCTA: p = 0.013, p = 0.018) between the non-event plaque, non-culprit plaque, and culprit plaque. In the image analysis of HR-VWI, there were differences observed between IPHR (p < 0.001), LPR (p = 0.001), FPV (p = 0.011), and CPV (p = 0.015) among the three groups of plaques. FLPV and FPV were significantly different among the three different plaque types from the coronary artery (p = 0.043, p = 0.022). Conclusion: There is a consistent pattern of change in plaque characteristics between the cervicocephalic and coronary arteries in the same patient.

Inflammatory activity evaluation in patients with axial spondyloarthritis using MRI relaxometry and mucosal-associated invariant T cells.

Background: Currently, there is a lack of an objective quantitative measure to comprehensively evaluate the inflammatory activity of axSpA, which poses certain challenges in accurately assessing the disease activity. Objective: To explore the value of combined-parameter models of sacroiliac joints (SIJs) MRI relaxometry and peripheral blood Mucosal-associated invariant T (MAIT) cells in evaluating the inflammatory activity of axial spondyloarthritis (axSpA). Methods: This retrospective clinical study included 88 axSpA patients (median age 31.0 (22.0, 41.8) years, 21.6% females) and 20 controls (median age 28.0 (20.5, 49.5) years, 40.0% females). The axSpA group was classified into active subgroup (n=50) and inactive subgroup (n=38) based on ASDAS-CRP. All participants underwent SIJs MRI examination including T1 and T2* mapping, and peripheral blood flow cytometry analysis of MAIT cells (defined as CD3+Vα7.2+CD161+) and their activation markers (CD69). The T1 and T2* values, as were the percentages of MAIT cells and CD69+MAIT cells were compared between different groups. Combined-parameter models were established using logistic regression, and ROC curves were employed to evaluate the diagnostic efficacy. Results: The T1 values of SIJs and %CD69+MAIT cells in the axSpA group and its subgroup were higher than the control group (p<0.05), while %MAIT cells were lower than the control group (p<0.05). The T1 values and %CD69+MAIT cells correlated positively, while %MAIT cells correlated negatively, with the ASDAS-CRP (r=0.555, 0.524, -0.357, p<0.001). Between the control and axSpA groups, and between the inactive and active subgroups, the combined-parameter model T1 mapping+%CD69+MAIT cells has the best efficacy (AUC=0.959, 0.879, sensibility=88.6, 70%, specificity=95.0, 94.7%, respectively). Conclusion: The combined-parameter model T1 mapping+%CD69+MAIT cells allows a more accurate evaluation of the level of inflammatory activity.

The Role of Nomogram Based on the Combination of Ultrasound Parameters and Clinical Indicators in the Degree of Pathological Remission of Breast Cancer.

Background: The mortality rate of breast cancer (BC) ranks first among female tumors worldwide and presents a trend of younger age, which poses a great threat to women's health and life. Neoadjuvant chemotherapy (NAC) for breast cancer is defined as the first step of treatment for breast cancer patients without distant metastasis before planned surgical treatment or local treatment with surgery and radiotherapy. According to the current NCCN guidelines, patients with different molecular types of BC should receive neoadjuvant chemotherapy (NAC), which can not only achieve tumor downstaging, increase the chance of surgery, and improve the breast-conserving rate. In addition, it can identify new genetic pathways and drugs related to cancer, improve patient survival rate, and make new progress in breast cancer management. Objective: To explore the role of the nomogram established by the combination of ultrasound parameters and clinical indicators in the degree of pathological remission of breast cancer. Methods: A total of 147 breast cancer patients who received neoadjuvant chemotherapy and elective surgery in the Department of Ultrasound, Nantong Cancer Hospital, from May 2014 to August 2021 were retrospectively included. Postoperative pathological remission was divided into two groups according to Miller-Payne classification: no significant remission group (NMHR group, n = 93) and significant remission group (MHR group, n = 54). Clinical characteristics of patients were recorded and collected. The multivariate logistic regression model was used to screen the information features related to the MHR group, and then, a nomogram model was constructed; ROC curve area, consistency index (C-index, CI), calibration curve, and H-L test were used to evaluate the model. And the decision curve is used to compare the net income of the single model and composite model. Results: Among 147 breast cancer patients, 54 (36.7%) had pathological remission. Multivariate logistic regression showed that ER, reduction/disappearance of strong echo halo, Adler classification after NAC, PR + CR, and morphological changes were independent risk factors for pathological remission (P < 0.05). Based on these factors, the nomogram was constructed and verified. The area under the curve (AUC) and CI were 0.966, the sensitivity and specificity were 96.15% and 92.31%, and the positive predictive value (PPV) and negative predictive value (NPV) were 87.72% and 97.15%, respectively. The mean absolute error of the agreement between the predicted value and the real value is 0.026, and the predicted risk is close to the actual risk. In the range of HRT of about 0.0∼0.9, the net benefit of the composite evaluation model is higher than that of the single model. H-L test results showed that χ 2 = 8.430, P=0.393 > 0.05. Conclusion: The nomogram model established by combining the changes of ultrasound parameters and clinical indicators is a practical and convenient prediction model, which has a certain value in predicting the degree of pathological remission after neoadjuvant chemotherapy.