Cardiovascular imaging techniques play a crucial role in the diagnosis, treatment, and prognosis of cardiovascular diseases. In 2024, Chinese scholars achieved remarkable research outcomes in this field, with findings published in various high-level domestic and international journals. By systematically reviewing the guidelines and expert consensuses, technological advancements, clinical studies, and artificial intelligence-related studies published by Chinese scholars in 2024, this review summarizes the key research hotspots and directions, aiming to provide reference and guidance for clinicians in both diagnostic decision-making and clinical research endeavors.
Objective This study aims to explore the predictive value of thrombus histogram features for successful recanalization and reperfusion after mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS), and to assess the clinical applicability of these features in preoperative imaging evaluation. Methods We retrospectively collected clinical and imaging data from 98 patients who underwent MT for AIS. All patients underwent non-contrast cranial CT and CT angiography (CTA), and thrombus histogram features such as mean, standard deviation, skewness, and kurtosis were measured from original images using Image J software. Patients were categorized into the successful recanalization group (n=65) and failed recanalization group (n=33) based on the recanalization status, and the successful reperfusion group (n=70) and failed reperfusion group (n=28) based on the reperfusion status. Differences between groups were compared using t-test, Mann-Whitney U test, Chi-square test, and Fisher’s exact test. Multivariate logistic regression was used to identify independent predictors, and to establish nomogram models. Calibration curves and decision curve analysis were performed to evaluate model stability and clinical utility. Results Compared with the failed recanalization group, successful recanalization group had a shorter onset time and higher thrombus CTA skewness (both P<0.05). Similarly, there were significant differences in onset time and thrombus CTA skewness between the successful and failed reperfusion groups (both P<0.05). Multivariate logistic regression analysis indicated that onset time and thrombus CTA skewness were independent predictors of both recanalization and reperfusion (both P<0.05). Nomogram models were constructed to predict recanalization and reperfusion based on thrombus CTA skewness and onset time. Calibration curves showed good agreement between the predicted and actual values for recanalization and reperfusion (P=0.862 and 0.831, respectively). Decision curve analysis indicated that the nomogram models had good clinical applicability for predicting recanalization and reperfusion. Conclusion The skewness of thrombus histogram features demonstrates potential predictive value for assessing recanalization and reperfusion status following mechanical thrombectomy, serving as a novel reference indicator in preoperative imaging evaluation that facilitates personalized treatment strategies for AIS.
Objective To investigate differences in white matter microstructure between patients with neuropsy-chiatric systemic lupus erythematosus (NPSLE) and those with non-neuropsychiatric SLE (Non-NPSLE) using tract-based spatial statistics (TBSS). Methods A total of 34 NPSLE patients and 32 Non-NPSLE patients were prospectively enrolled, along with 33 healthy controls (HC) during the same period. All participants underwent brain diffusion tensor imaging (DTI). TBSS was used to compare white matter microstructural differences among the three groups. Fractional anisotropy (FA) values were compared using one-way ANOVA, with post hoc analyses conducted for pairwise group comparisons. Partial correlation analyses assessed the relationships between FA values of significantly different clusters and neuropsychological scores or clinical indicators, as well as the correlations between neuropsychological scores and clinical indicators. Results Five clusters showed significant FA differences among the three groups (P<0.05, FWE-corrected). Post hoc analysis revealed that two clusters in both the Non-NPSLE and NPSLE groups had lower FA values than the HC group, and one cluster in the NPSLE group had a lower FA value than the Non-NPSLE group (P<0.05, FWE-corrected), indicating more extensive white matter involvement in NPSLE. FA reductions in SLE patients were primarily located in the corpus callosum and corona radiata. Correlation analysis showed that FA values of the significant clusters in pairwise comparisons were positively correlated with IgM levels (P<0.05). In the NPSLE group, HADS-D scores were negatively correlated with C4 levels (r=-0.354, P=0.047), while in the Non-NPSLE group, MoCA scores were negatively correlated with ESR (r=-0.424, P=0.019). Conclusion NPSLE patients exhibit more extensive white matter microstructural damage compared to Non-NPSLE patients. The FA values of some differential clusters correlate with clinical indicators, suggesting that these changes may serve as important imaging biomarkers for detecting disease activity or neuropsychiatric involvement in SLE.
Objective To investigate the characteristics of altered spontaneous brain activity in patients with sensorineural hearing loss (SNHL) using activation likelihood estimation (ALE) meta-analysis, and to further understand the potential neural mechanisms of brain functional impairment and remodeling in SNHL. Methods A systematic search was conducted up to August 21, 2023, in Web of Science, PubMed, CNKI, Wanfang Med Online, and the Chinese Medical Journal Full-text Database for studies applying regional homogeneity (ReHo) and amplitude of low-frequency fluctuation/fractional ALFF (ALFF/fALFF) analyses to evaluate brain functional changes in SNHL patients. After applying inclusion and exclusion criteria, studies were included in a meta-analysis using the ALE method to identify brain regions with abnormal spontaneous neural activity in SNHL patients. Results A total of 22 articles comprising 29 studies were included, involving 736 cases of SNHL and 487 controls. Among these, 11 studies used ReHo and 18 studies used ALFF/fALFF. A combined analysis of ReHo/ALFF/fALFF without differentiating the side of deafness revealed increased spontaneous brain activity in the left medial dorsal thalamus, and decreased activity in the left superior temporal gyrus, left opercular part of the inferior frontal gyrus, and left dorsolateral prefrontal cortex. Separate ALE analyses for left-sided and right-sided SNHL patients, as well as separate analyses using ReHo or ALFF/fALFF methods, did not identify any significantly altered brain regions. Conclusion The ALE meta-analysis confirms that SNHL patients exhibit abnormal spontaneous activity in multiple brain regions. These findings help elucidate the patterns and characteristics of brain functional damage and remodeling associated with SNHL, providing important evidence for future clinical assessment and treatment planning.
Objective To investigate the relationship between pericoronary fat attenuation index (FAI) and the plaque progression. Methods This retrospective study included 140 inpatients with suspected coronary artery disease (CAD) who underwent consecutive coronary computed tomography angiography (CCTA), with an average age of 56.8 ± 10.5 years old. A total of 348 plaques were identified. Clinical data, as well as baseline and follow-up (at least one year apart) CCTA imaging data, were collected. Characteristics, degree of stenosis, plaque volume (PV), and percentage atheroma volume (PAV) were analyzed. Peri-plaque FAI was measured and analyzed. A multivariate generalized estimating equation was used to adjust for confounding variables, and linear regression models were fitted to analyze the association between the annual change in FAI (ΔFAI/y) and the annual changes in PV (ΔPV/y) and PAV (ΔPAV/y). Results The median interval between the two CCTA scans was 2.3 (1.7, 3.8) years. Quantitative analysis of the two scans revealed significant increases in all components of PV and PAV except for lipid PV and lipid PAV (all P<0.001). After adjusting for China-PAR score, Leiden score, TyG index, antiplatelet therapy, and statin use using generalized estimating equation, ΔPAV/y of total plaques was significantly positively correlated with ΔFAI/y (β=0.156, 95%CI: 0.025-0.287, P=0.019). Specifically, ΔPAV/y of non-calcified plaques (β=0.139, 95%CI: 0.006-0.273, P=0.041) and fibrous plaques (β=0.197, 95%CI: 0.067-0.327, P=0.003) also showed significant positive correlations with ΔFAI/y. Conclusion Changes in FAI are consistent with changes in non-calcified PAV and fibrous PAV. This may help identify potentially high-risk patients with stable coronary artery disease and supports the use of FAI as a valuable tool for evaluating treatment efficacy in coronary artery disease.
Objective To investigate the association between the pericoronary adipose tissue fat attenuation index (FAI) surrounding culprit plaques in acute coronary syndrome (ACS) and plaque characteristics, and to assess its value in predicting culprit plaques. Methods This retrospective study enrolled 50 patients diagnosed with ACS (ACS group) and 40 asymptomatic individuals with coronary atherosclerosis who underwent coronary computed tomography angiography (CCTA) during the same period (control group). Clinical and imaging data were analyzed. In the ACS group, plaques were classified as culprit or non-culprit plaques. Based on the number of high-risk features, plaques were further categorized as non-high-risk or high-risk. FAI surrounding plaques was measured using predefined default (-190 to -30 HU) and wide (-190 to 20 HU) attenuation thresholds. Student’s t-test, one-way ANOVA, and chi-square test were used to compare FAI values of plaques with different characteristics and degrees of stenosis between and within groups; the plaque characteristics, stenosis severity, and FAI among culprit plaques, non-culprit plaques, and control group plaques; the high-risk features between culprit and non-culprit plaques; and the FAI values between high-risk and non-high-risk plaques. Multivariable logistic regression analysis was performed to identify independent predictors of culprit plaques. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive performance of individual and combined factors for culprit plaques. The DeLong test was used to compare the differences in the area under the curve (AUC) among individual and combined factors. Results The FAI measured with the wide threshold was significantly higher than that measured with the default threshold for culprit plaques, non-culprit plaques, and control group plaques (all P<0.05). Under both thresholds, the FAI of culprit plaques was significantly greater than that of non-culprit plaques and control plaques (all P<0.05). Among the culprit plaques, 64% were classified as high-risk plaques, and these also showed high proportions of mixed plaque morphology, severe stenosis, and occlusion (52%, 76%, and 12%, respectively). In the ACS group, the FAI surrounding calcified plaques was lower than that surrounding non-calcified and mixed plaques (P<0.05). The FAI was significantly higher around plaques causing severe stenosis or occlusion (P<0.05), and higher around high-risk plaques compared to non-high-risk plaques (P<0.05). Multivariable logistic regression analysis indicated that stenosis severity ≥ moderate, higher default threshold FAI, and a greater number of high-risk plaque features were independent predictors of culprit plaques. The combination of default threshold FAI, stenosis severity, and high-risk features yielded the highest predictive performance (AUC=0.981). DeLong test analysis showed that the AUCs of models combining default threshold FAI with other factors were significantly higher than those of any single factor alone (all P<0.05). Conclusion The FAI surrounding ACS plaques can partially reflect plaque inflammation and vulnerability. Combining default threshold FAI with stenosis severity and high-risk features improves diagnostic performance in identifying culprit plaques.
Objective To investigate the predictive value of the minimum distance between left atrial appendage (LAA) and left superior pulmonary vein (LSPV), measured on cardiac computed tomography (CT), for atrial fibrillation (AF) recurrence within 2 years after the first radiofrequency ablation procedure. Methods A retrospective analysis was conducted on the clinical and imaging data of 342 AF patients who underwent cardiac CT, with a median age of 64 (56, 71) years. Based on recurrence status within 2 years, patients were divided into a recurrence group (n=106) and a non-recurrence group (n=236). Differences in clinical and cardiac CT parameters between the two groups were analyzed using the chi-square test or Mann-Whitney U test. Cox regression analysis was used to identify independent predictors of AF recurrence and construct predictive models. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate model performance, and DeLong’s test was used to compare AUC values. Kaplan-Meier analysis was used to assess event-free survival, and the log-rank test was used to compare survival between groups. Results The proportion of patients with an end-diastolic LAA-LSPV distance (LAA-LSPVend-diastolic) <2 mm was significantly higher in the recurrence group than in the non-recurrence group (P<0.05). The recurrence group also had significantly higher end-diastolic and end-systolic volume indices of the left atrium and LAA (LAVImax, LAVImin, LAAVImax, LAAVImin) compared to the non-recurrence group (all P<0.05). Multivariate Cox regression identified (LAA-LSPVend-diastolic) <2 mm, LAAVImax, persistent AF, and NT-proBNP as independent predictors of recurrence. Three predictive models were developed: Model 1: clinical parameters only (persistent AF+NT-proBNP); Model 2: Model 1+LAAVImax; Model 3: Model 2+LAA-LSPVend-diastolic <2 mm. Model 3 had significantly better predictive performance than both Model 1 (Z=2.829, P<0.05) and Model 2 (Z=2.246, P<0.05). Conclusion LAA-LSPVend-diastolic <2 mm is an independent predictor of AF recurrence within 2 years after ablation and provides incremental prognostic value.
Objective To explore the clinical value of three-dimensional CT bronchial angiography (3D-CTBA) reconstruction based on non-contrast chest CT in guiding surgical approach for anatomical pulmonary segmentectomy of pulmonary nodules. Methods This retrospective study included 20 patients who underwent anatomical pulmonary segmentectomy guided by non-contrast CT(plain scan group) and 3D-CTBA navigation, and 20 patients guided by contrast-enhanced 3D-CTBA(enhanced group). Differences in clinical data (age, sex, body mass index, operative time, intraoperative blood loss, duration of chest drainage, and postoperative hospital stay) and CT imaging parameters [subjective 3D-CTBA image quality score, image accuracy assessment, CT scan cost, nodule diameter, consolidation-to-tumor ratio (CTR), proportion of pure ground-glass nodules (CTR=0), and effective radiation dose] were analyzed using t-tests, Mann-Whitney U tests, Chi-square tests, or Fisher’s exact test. Inter-rater agreement for image quality and anatomical accuracy was assessed using Cohen’s Kappa and Gwet’s AC1. Results There were no statistically significant differences in baseline characteristics between the two groups (all P>0.05). Interobserver agreement for subjective image quality and anatomical accuracy was high (κ≥0.75; AC1≥0.80). No significant differences were observed in subjective image quality scores or anatomical accuracy between the two groups (all P>0.05). The cost of CT examination in the plain scan group was lower than that in the enhanced scan group. The effective radiation dose in the plain scan group was lower than that in the enhanced scan group (P<0.05). No significant differences were found in other objective imaging metrics or surgical outcome measures (all P>0.05). Conclusion 3D-CTBA reconstruction based on non-contrast CT provides comparable intraoperative navigation value to contrast-enhanced 3D-CTBA in anatomical segmentectomy for pulmonary nodules, with the added benefits of lower cost and reduced radiation exposure, making it suitable for broader clinical adoption.
Objective To evaluate the value of models based on clinical and MRI features in predicting HER-2-positive and HER-2-low expression breast cancers. Methods A retrospective analysis was conducted on 213 female patients (mean age 50.8±10.6 years) with surgically and pathologically confirmed mass-forming breast cancer. Based on postoperative pathological results, patients were categorized into HER-2-zero (65 cases), HER-2-low (79 cases), and HER-2-positive (69 cases) groups. Clinical and MRI characteristics were compared among the three HER-2 expression groups using one-way ANOVA and chi-square tests, including estrogen receptor (ER) status, progesterone receptor (PR) status, T stage, clinical stage, maximum lesion diameter, and apparent diffusion coefficient (ADC) values. Multivariate logistic regression was used to identify independent predictive factors for the HER-2-positive and HER-2-low expression subtypes, followed by predictive model construction. Receiver operating characteristic (ROC) analysis was used to assess model performance. Results Significant differences were observed among the HER-2-zero, HER-2-low, and HER-2-positive groups in ER status, PR status, T stage, clinical stage, maximum lesion diameter, and ADC values (all P<0.05). Multivariate analysis demonstrated that clinical stage and ADC value were independent predictors for both HER-2-positive and HER-2-low breast cancer (both P<0.05). The model constructed using clinical stage and ADC demonstrated high predictive efficacy for both HER-2 positive and HER-2-low expressing breast cancers, with areas under the curve (AUC) of 0.899 and 0.861, respectively. Conclusion A model integrating clinical stage and ADC values shows high efficacy for the noninvasive prediction of HER-2-positive and HER-2-low expression breast cancers.
Preoperative prediction of the efficacy of neoadjuvant immunotherapy (NIT) in non-small cell lung cancer (NSCLC) helps identify patients who are likely to benefit, reduce the risk of postoperative recurrence and metastasis, and improve prognosis. Radiomics and deep learning can be used to explore imaging biomarkers for predicting NIT efficacy in NSCLC. Radiomics, through global feature analysis or habitat analysis methods, can effectively quantify the temporal and spatial heterogeneity of tumors, providing a quantitative basis for efficacy prediction. Deep learning, on the other hand, adaptively extracts deep imaging features to evaluate treatment response. This review summarizes recent research progress in radiomics and deep learning technologies for predicting NIT efficacy in NSCLC patients, and discusses the associated technical challenges and corresponding solutions.
Ischemia with non-obstructive coronary artery disease (INOCA) is characterized by coronary microvascular dysfunction and epicardial vasospasm as its core pathological mechanisms, which significantly increase the risk of adverse cardiovascular events. Non-invasive imaging modalities, including cardiac magnetic resonance imaging, myocardial computed tomography perfusion imaging, echocardiography, and positron emission tomography, have demonstrated significant potential in the evaluation of INOCA. Artificial intelligence further enhances the efficiency and accuracy of imaging-based assessments. This article provides a systematic review of the pathophysiological mechanisms underlying INOCA and recent advances in imaging techniques for its evaluation, with a focus on clinical applicability and technological innovation.
Diabetes is a risk factor for coronary heart disease (CHD), and the two conditions often coexist and interact, increasing the risk of cardiovascular events. Multimodal imaging techniques such as coronary artery CTA, cardiac MRI, molecular imaging, intravascular ultrasound, optical coherence tomography, as well as imaging artificial intelligence can comprehensively assess anatomical, functional, and metabolic abnormalities of the coronary arteries and myocardium, assisting in the precise diagnosis and risk stratification of patients with diabetes and CHD. This paper reviews recent imaging research progress in diabetes mellitus complicated with coronary heart disease.
Neoadjuvant chemotherapy (NAC) can not only reduce the stage of breast cancer but also enable some tumor lesions and axillary lymph nodes to achieve pathological complete response (pCR). Accurate preoperative imaging assessment of axillary lymph node status after NAC in breast cancer patients can help avoid excessive surgical intervention and guide the development of individualized treatment plans. This review summarizes recent progress in the use of imaging methods such as ultrasound, MRI, CT, and PET/CT to evaluate axillary lymph node pCR after NAC.
Habitat imaging(HI) can analyze tumor heterogeneity and microenvironmental characteristics and has been increasingly applied in the research, diagnosis, and treatment of common digestive system tumors, including colorectal cancer, gastric cancer, and hepatocellular carcinoma. Currently, HI is used to construct genotypic prediction models, precision staging, and metastasis prediction in colorectal cancer; to quantify immune microenvironment characteristics, evaluate treatment response, and predict prognosis in gastric cancer; and to achieve non-invasive identification of microvascular invasion and recurrence risk stratification in hepatocellular carcinoma. This article introduces the basic principles and technical processes of HI, and reviews its research progress in the above-mentioned digestive system tumors.
Ultrasound technology offers clear visualization of skin tissue structure, echogenicity, and blood flow, while also providing information on tissue stiffness. It enables measurement of lesion depth and facilitates the assessment of recurrence and treatment efficacy. Currently, its applications in the diagnosis and evaluation of non-mass skin diseases involve modalities such as high-frequency ultrasound (HFUS), color Doppler ultrasound, and ultrasound elastography. This review summarizes recent advancements in applying ultrasound technology to non-mass skin conditions, including connective tissue diseases involving the skin, bullous diseases, cellulitis, other inflammatory dermatoses, and pressure injuries.
Early and comprehensive diagnosis and treatment are crucial for improving the prognosis of radioiodine-refractory differentiated thyroid cancer (RAIR-DTC). Radiopharmaceuticals targeting emerging probes, such as Arg-Gly-Asp, somatostatin receptors, prostate-specific membrane antigen, and fibroblast activation protein, can be used for the non-invasive evaluation of the biological characteristics of RAIR-DTC. These probes assist in tumor diagnosis and staging and play an important role in predicting disease progression and formulating treatment strategies. This review summarizes recent advancements in the integrated strategy of radioisotope-based diagnosis and therapy for RAIR-DTC.
Objective To explore the clinical and imaging characteristics of intramural duodenal hematoma (IDH) in children, aiming to provide a basis for early diagnosis and treatment. Methods A retrospective analysis was conducted on the clinical and imaging data of 16 pediatric IDH cases, aged 3 to 10 years. Among the 16 cases, 11 underwent CT scans (10 with contrast enhancement) and 5 underwent MRI scans (4 with contrast enhancement). Results Most of the IDH cases had a history of trauma (10 cases). The lesions were mostly solitary (15 cases), primarily involving the descending and horizontal portions of the duodenum. On non-contrast CT, the lesions appeared as heterogeneous iso- to hyperdense masses, with “melting ice sign” observed in 7 cases and “air cleft sign” in 11 cases. MRI revealed hyperintense signals on T1-weighted imaging (T1WI), hypointense or isointense signals on T2-weighted imaging (T2WI), and mixed hyperintensity on diffusion-weighted imaging (DWI). On contrast-enhanced scans, no enhancement was observed within the lesions, though 6 cases exhibited wall enhancement of the hematoma. Six cases were complicated with intestinal obstruction, and 7 cases showed elevated pancreatic enzymes. Fourteen cases were successfully treated conservatively, 2 cases underwent surgery due to intestinal obstruction, and one case died from multi-organ failure. Conclusion The integration of clinical manifestations with characteristic CT and MRI imaging features is essential for the early diagnosis of pediatric IDH. Imaging follow-up can effectively assess the absorption of the hematoma and the progression of complications.
