Objective To summarize the clinical, imaging, and etiological characteristics of mycoplasma pneumonia in children. Methods The data of 110 hospitalized children diagnosed with mycoplasma pneumoniae infection in Department of Pediatrics of our hospital from November 2023 to June 2024 were retrospectively analyzed. Results Mycoplasma pneumoniae infection was most common in children aged 6-13 years. The main manifestations were respiratory system (100%), among which cough (98.2%) and fever (78.2%) were the most common. Among them, 2.8% of the patients presented with pertussi-like symptoms, and 7.0% of the patients presented with low-grade fever. Extrapulmonary manifestations were mainly digestive tract (49.1%). Blood routine examination showed that 31.9% of the children had abnormal white blood cell count, including an increase in white blood cell count of 26.4% and a decrease in white blood cell count of 5.5%. Chest imaging showed bronchitis (64.4%) and patchy hyperdensity (35.6%). In this area, mycoplasma pneumoniae was easily co-infected with influenza virus (including influenza A and B), accounting for 30%. All patients were treated with macrolide antibiotics, 67.3% were cured and 32.7% were improved. Conclusion Mycoplasma pneumoniae infection is most common in school-age children, predominantly affecting the respiratory system, extrapulmonary manifestations are primarily observed in the digestive tract. White blood cell counts can either increase or decrease, and chest imaging findings are predominantly bronchitis, Mycoplasma pneumoniae infection is prone to co-occur with influenza virus infection, and no resistance to macrolide antibiotics was detected in this cohort of patients.

Objective To explore the value of Neuromelanin magnetic resonance imaging (NM-MRI) combined with quantitative susceptibility mapping (QSM) in staging and assessment of cognitive function in PD. Methods NM-MRI and QSM scans were conducted on 62 patients with PD diagnosed by the neurology department in our hospital and 22 age and gender matched healthy controls (HC). The contrast-to-noise ratio (CNR) and the magnetic susceptibility (MSV) values of the substantia nigra (SN) were obtained by post-processing software, then comparing the CNR and MSV values among different stages of PD. The diagnostic efficacy of each single and combined parameter for PD in staging and assessment of cognitive function were assessed using subject operating characteristic curves and binary logistic regression analyses. Results The CNR values of SN were lower in PD group than in HC group (P<0.05) and the MSV values of SN were higher in PD group than in HC group (P<0.05), and the differences were statistically significant. Inter-group comparisons of PD revealed that the CNR values of early PD group were higher than those of the middle and advanced PD groups (P<0.05), the MSV values of advanced PD group were higher than those of the early and middle PD groups (P<0.05), and the differences were statistically significant. The CNR values of PD group showed a positive correlation with MoCA scores and MMSE scores, while showing a negative correlation with UPDRS-III scores (P<0.05); the MSV values of PD group showed a negative correlation with MoCA scores and MMSE scores but showed a positive correlation with the UPDRSIII scores (P<0.05). The ROC curve demonstrated that the AUC values for NM-MRI, QSM and combined of NM-MRI and QSM were 0.778, 0.783 and 0.820 in the distinguish of early and middle PD group. The ROC curve demonstrated that the AUC values for NM-MRI, QSM and combined of NM-MRI and QSM were 0.821, 0.787 and 0.830 in assessment of cognitive function. The combination of above two sequences was more effective in distinguishing different stages and assessing cognitive function of PD than any single technique. Conclusion NM-MRI combined with QSM technology has a high diagnostic efficiency in staging and assessment of cognitive function in PD, which can identify early PD patients and provide imaging evidence for PD cognitive assessment.

Lung cancer, being one of the cancers with the highest global incidence and the main reason for cancer deaths, usually exhibits as pulmonary nodules in the early stage. CT represents a crucial imaging examination approach for the assessment of pulmonary nodules. With the advancement of technology, dual-energy CT is widely used in clinical practice. By acquiring images at two different energy spectra, dual-energy CT enables material decomposition, allowing generation of material- and energy-specific images. Existing research has demonstrated that dual-energy CT can be employed not merely for differentiating between benign and malignant pulmonary nodules, predicting pathological types of lung cancer, assessing the degree of tumor differentiation as well as the gene expression, but also for assessing therapy response and prognosis of lung cancer. This article reviews the clinical applications of dual-energy CT material decomposition images in distinguishing between benign and malignant pulmonary nodules, predicting the pathological types of lung cancer, the degree of tumor differentiation, the gene expression of lung cancer, evaluating therapy response and prognosis of lung cancer. It aims to systematically sort out the clinical application progress of dual-energy CT material decomposition images in pulmonary nodules, provide a more scientific and accurate basis for clinical decision-making, and promote the further development of precision medicine for lung cancer.

Objective To validate the feasibility of the deep learning image reconstruction (DLIR) algorithm in coronary computed tomography angiography (CCTA) under low radiation dose and low contrast agent volume conditions. Methods This prospective study included 86 patients with normal BMI who underwent CCTA at the Affiliated BenQ Hospital of Nanjing Medical University from November 2021 to April 2022. The patients were randomly divided into group A and group B. Both groups employed Smart-mA tube current automatic control technology, Auto Gating, Smart Phase and Motion correction algorithm techniques, with a noise index set at 12.2 HU. Iodixanol (350 mgI/mL) was used as the contrast agent. The tube voltage was set to 70 kV, with the contrast agent volume calculated as (body weight ×0.275) mL in group A, and the tube voltage was set to 120 kV, the contrast agent volume was (body weight ×0.55) mL in group B. Group A used the DLIR algorithm for image reconstruction, while group B used the 50% ASIR-V algorithm. The CT values and noise levels of the aortic root, left main, left anterior descending artery, left circumflex artery, and right coronary artery proximal segments were measured and calculated. Objective evaluation parameters, including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and edge rise distance were computed. A double-blind method was used to compare the subjective image quality of the two reconstruction methods. Results Except for no significant differences in CNR of the left main artery and SNR of the left circumflex artery proximal segment (P=0.358, 0.252), the CNR and SNR of all other regions of interest in group A were significantly higher than those in group B (P<0.001). The edge rise distance of the left anterior descending proximal segment in group A was smaller than in group B (P<0.001). Image quality in both groups met diagnostic requirements, but group A demonstrated significantly better subjective image quality than group B (P<0.001). Radiation dose: The effective dose in group A was 0.81±0.40 mSv, compared to 2.84±1.50 mSv in group B, with a statistically significant difference (P<0.001). Contrast agent volume: The volume in group A was 22.11±3.31 mL, while in group B it was 34.40±2.98 mL, with a statistically significant difference (P<0.001). Conclusion The DLIR algorithm can effectively reduce radiation dose and contrast agent volume in CCTA, demonstrating potential for wider application.

The presence of wounds can significantly impact patients' quality of life, as well as their physical and mental well-being, while also posing substantial challenges and burdens to the healthcare system. Ultrasound, as a physical therapy modality, shows promising potential in the field of wound healing. This article offers a concise review of the wound healing process, the biological effects of ultrasound, the mechanisms by which ultrasound promotes wound healing, the key parameters of ultrasound therapy, and its application value across various types of wounds. Additionally, we discuss the research advancements in combining ultrasound with other therapeutic approaches, aiming to provide valuable insights for future studies.

Objective To explore the feasibility of constructing a machine learning model based on mammography signs and clinical informations to predict the histological grade in the ductal carcinoma in situ. Methods A retrospective analysis were conducted on the mammography signs and clinical informations of 239 patients who had histologically confirmed breast ductal carcinoma in situ (DCIS). Based on pathological results, these patients were categorized into : non-high-grade group (n=109) and high-grade group (n=130). The collected 10 clinical informations and 15 mammography signs were statistically analyzed, and the features with statistical differences were selected to construct three machine learning models, namely eXtreme Gradient Boosting, logistic regression and multinomial naive bayes, with the area under the ROC curve (AUC) was used as the main index to select the optimal mode. Results The AUC values for the training sets of eXtreme Gradient Boosting, logistic regression and multinomial Naive Bayes were 0.790, 0.794, 0.802, and the AUC values of text sets were 0.760, 0.758, 0.774, and the accuracies were 0.760, 0.759, 0.774,the sensitivities were 0.725, 0.825, 0.800, the specificities were 0.625, 0.434, 0.625. Conclusion The histological grade models of ductal carcinoma in situ based on machine learning have better prediction efficiency, and the multinomial naive Bayes has the best prediction efficiency.

Objective To explore diagnostic value of ¹⁸F-FDG PET/CT combined with serum RNA binding motif protein 38 (RBM38) in postoperative recurrence/metastasis of colorectal cancer. Methods A total of 120 patients with colorectal cancer admitted to Hai'an People's Hospital from January 2021 to August 2023 were enrolled. According to presence or absence of postoperative recurrence/metastasis by pathological examination, patients were divided into occurrence group (n=48) and non-occurrence group (n=72). All patients underwent ¹⁸F-FDG PET/CT examination, ¹⁸F-FDG PET/CT parameters [maximum standardized uptake value (SUV_max), metabolic tumor volume (MTV), total lesion glycolysis (TLG)] and level of serum RBM38 were compared between the two groups. The correlation between serum RBM38 and SUV_max, MTV, TLG was analyzed by Pearson analysis. The predictive value of RBM38, SUV_max, MTV, TLG and combined detection in postoperative recurrence/metastasis of colorectal cancer was analyzed by ROC curves. Results RBM38 level in occurrence group was lower than that in non-occurrence group, while SUV_max, MTV and TLG were higher than those in non-occurrence group (P<0.05). Pearson analysis showed that RBM38 level was negatively correlated with SUV_max, MTV, and TLG (r=-0.600, -0.606, -0566, P<0.05). ROC curves analysis showed that area under the curve, sensitivity and specificity of SUV_max, MTV, TLG, RBM38 and combined detection for predicting postoperative recurrence/metastasis of colorectal cancer were 0.732, 0.732, 0.706, 0.737, 0.910; 64.58%, 66.67%, 70.83%, 79.17%, 89.58%; 76.39%, 72.22%, 65.28%, 62.50%, 75.00%, respectively (P<0.05). Conclusion ¹⁸F-FDG PET/CT combined with serum RBM38 has high predictive value in postoperative recurrence/metastasis of colorectal cancer, which is beneficial to improve the accuracy of clinical prediction and diagnosis.

Liver disease has a high morbidity and poor prognosis, and shear wave elastography, a new ultrasound technique for detecting liver disease in recent years, is limited since it ignores the effect of tissue viscosity when determining tissue elasticity. Shear wave dispersion, an innovative non-invasive ultrasound imaging approach, uses the shear waves' dispersion slope to analyze the viscoelastic characteristics of tissues. Because the liver contains viscous and elastic mechanical properties, shear wave dispersion is considered a valuable tool for diagnosing liver disease. This paper reviewed the physical principles of shear wave dispersion and its clinical application in evaluating diffuse and focal liver disease. Additionally, The limitations of shear wave dispersion and its future development prospects were summarized, to provide new ideas for early liver disease diagnosis.

Objective To analyze the imaging features of a group of children's pleuropulmonary blastomas (PPB) and enhance understanding of the disease and reduce misdiagnosis. Methods A retrospective analysis was conducted on the clinical, imaging, and pathological data of 13 children with pathologically confirmed PPB. All 13 cases underwent chest X-ray, CT and enhanced CT, and 2 cases also had MRI examinations. Results Lesions were observed in the right thoracic cavity in 7 cases and the left thoracic cavity in 6 cases, with an average tumor diameter of 7.87±2.48 cm. There were 6 cases of cystic lesions, 5 cases of cystic-solid lesions, and 2 cases of solid lesions. On enhanced CT, the cystic areas of the lesions showed no enhancement, while the solid components of cystic-solid and solid lesions exhibited mild-moderate heterogeneous enhancement. 5 cases were complicated with pleural effusion, 1 with pneumothorax, and 1 with intrapulmonary metastasis. Radiological classification: there were 6 cases of type I, 3 cases of type II, and 4 cases of type III. Pathological classification: there were 6 cases of type I, 5 cases of type II, and 2 cases of type III. Conclusion The radiological manifestations of PPB are correlated with its pathological type, and its diagnosis requires reliance on pathology and immunohistochemistry.

Objective To explore the feasibility and clinical value of low radiation dose scanning combined with deep learning reconstruction (DLIR) algorithm in CT-guided lung puncture biopsy. Methods Patients who underwent CT-guided lung puncture at the Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine from September 2023 to March 2024 were selected, and according to the different scanning protocols, 60 lung puncture biopsy patients were divided into a conventional dose group (group A) and a low-dose group (group B). Group A was 100 kV, with a noise index (NI)=15; Group B had an NI=45; the rest of the scanning parameters were the same. The first and last whole-lung scans in the conventional dose group were scanned with the parameters of group A and B, respectively. They were used to evaluate the image quality improvement potential of the deep learning reconstruction algorithm (DLIR). The first whole-lung scan in group A was reconstructed with filtered back projection (FBP) and weighted 50% adaptive statistical iterative reconstruction-V (50% ASIR-V), and the last whole-lung scan was reconstructed with the three intensities of the deep learning reconstruction algorithm (DLIR-L, DLIR-M, DLIR-H) reconstructed images. The CT and SD values of paraspinal muscles, subcutaneous fat, and aortic vessels were measured, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The baseline characteristics of the patients, the total radiation dose during puncture, the pathological positivity rate, and the complication rate were compared between group A and B. Results The differences in CT values at muscle, subcutaneous fat, and aortic vessels in the reconstructed images under the five different conditions were not statistically significant (P>0.05). The differences in SD, SNR, and CNR values were statistically significant (P<0.05). The two-by-two comparative analyses between the groups showed that there were no statistically significant differences between the DLIR-H images and the 50% ASIR-V images in muscle, fat, and vessel SD and SNR (P>0.05); the differences in CNR values between FBP vs DLIR-H and DLIR-L vs DLIR-H groups were statistically significant (P<0.05). Compared with group A's total radiation dose, group B's total radiation dose was reduced by about 93.6% (P<0.001). The image quality of both groups could meet the needs of clinical puncture, and the differences in baseline characteristics, pathological positivity rate, and complication rate between the two groups were not statistically significant (P>0.05). Conclusion Low-dose CT scanning combined with DLIR reconstruction significantly reduces image noise and improves image quality without compromising the safety of puncture or pathology positivity.

Magnetic resonance technology is safe and radiation-free, and has been widely used in the whole body. Multi-sequence and multi-parameter combined MRI imaging breaks the limitation of single imaging, and can reflect the information of lesion diffusion, perfusion and metabolism through quantitative analysis by DWI, IVIM, DCE-MRI,MRS And other technologies, so as to differentiate and evaluate the benign and malignant of isolated pulmonary nodules from the molecular level. Multi-parameter combined imaging significantly improved the sensitivity and specificity of single imaging, which is superior to single-parameter imaging. Additionally, it demonstrates potential for further analyzing pathological typing of lung cancer. MRI multi-parameter combined imaging is expected to improve the early diagnosis rate and specificity of pulmonary nodules, and provide a more reliable basis for individualized treatment.

Objective To investigate the relationship between contrast-enhanced ultrasound (CEUS) Liver imaging reporting and data system (LI-RADS) classification and the degree of pathological differentiation and microvascular invasion (MVI) in hepatocellular carcinoma (HCC) within the context of liver cirrhosis. Methods A retrospective analysis was conducted on 368 HCC patients who underwent liver CEUS at the Department of Ultrasound Medicine, West China Hospital, Sichuan University from June 2021 to December 2022, including 298 males and 70 females, aged 25-85(55.72±10.60) years old. Clinical features, CEUS characteristics, and LI-RADS classification were analyzed and compared in relation to the degree of pathological differentiation of the lesions and MVI. Results According to the Edmondson-Steiner grading system for pathological differentiation, 112 cases were classified as poorly differentiated, 239 as moderately differentiated, and 17 as well-differentiated. Pathological examination revealed 142 MVI-positive cases and 226 MVI-negative cases. The size of HCC lesions was inversely correlated with the degree of differentiation (P<0.001), with MVI-positive lesions being significantly larger than MVI-negative lesions (P<0.001). The proportions of HCC lesions presenting with mild or late washout were 59.8%, 67.4%, and 70.6% for poorly, moderately, well-differentiated lesions, respectively. Similarly, the proportions of lesions classified as LI-RADS 5 were 58.0%, 66.5%, 70.6%, respectively, with both proportions increasing with higher degrees of pathological differentiation. In contrast, the proportions of lesions presenting with early or marked washout were 38.4%, 28.0%, 5.9% for poorly, moderately, and well-differentiated HCC, respectively. The proportions classified as LI-RADS M were 40.2%, 28.9%, 5.9%, respectively, showing a decreasing trend with increasing differentiation. Furthermore, a higher degree of differentiation was associated with a greater proportion of patients without MVI (P<0.001). There were no statistically significant differences observed in CEUS features, including arterial phase enhancement, washout patterns, and LI-RADS classification between MVI-positive and MVI-negative patients (P>0.05). Conclusion In cirrhotic patients, a correlation was identified between the CEUS LI-RADS classification of HCC and the degree of tumor differentiation. Well-differentiated lesions were more frequently categorized as LI-RADS 5, whereas poorly differentiated lesions were predominantly classified as LI-RADS M.

Objective To evaluate the early condylar bone changes in patients with anterior disc displacement of temporomandibular joint by using MRI gray level co-occurrence matrix technique. Methods A total of 60 patients (120 joints) with temporomandibular disorders (TMD) who underwent temporomandibular joint MRI examination in Hainan Hospital of Chinese PLA General Hospital from March 2019 to March 2022 were retrospectively collected. According to the unilateral disc displacement, the patients were divided into normal control (NC), anterior disc displacement with reduction (ADDwR) and anterior disc displacement without reduction (ADDwoR). Condylar gray level co-occurrence matrix analysis was performed on the PDWI sequence of oblique sagittal plane in the closed mouth position. Kruskal-Wallis test and one-way analysis of variance were used to evaluate the difference of texture features between groups, and receiver operating characteristic curve analysis was used to evaluate the diagnostic performance of each parameter. Results The angular second moment and entropy of the texture feature parameters of condylar bone were statistically significant (P<0.001). The Angle second moment of the anterior disc displacement group was higher than that of the normal group, and the entropy was lower than that of the normal group.The contrast,correlation, homogeneity were not statistically significant (P>0.05). ROC curve results showed that the AUC of ASM and entropy in the NC-ADDwoR group and ADDwR-ADDwoR group were both>0.7, suggesting that both texture feature parameters had good diagnostic value. Among them, ASM and entropy had the highest diagnostic efficiency in the NC-ADDwoR group, with the cut off values of 1.50 and 6.49, respectively. The AUC were 0.75 and 0.75, the sensitivity were 54.3% and 51.40%, and the specificity were 90.00% and 94.00%, respectively. Conclusion The texture feature parameters angular second moment and entropy from MRI gray level co-occurrence matrix can quantitatively evaluate the texture feature changes of the condyle bone in TMD patients, providing objective reference for the early diagnosis, treatment and pathogenesis of TMD.

Objective To establish a predictive model by extracting radiomic features from multi-parametric MRI data and combining them with clinical characteristics, and identify the machine learning model with the highest predictive value for triple-negative breast cancer (TNBC). Methods A total of 175 breast cancer patients, including 40 cases of TNBC and 135 cases of non-triple negative breast cancer (NTNBC), were collected and divided into training set (n=123) and validation set (n=52)according to 7:3. Multiparameter predictive models were developed using various machine learning algorithms and combined with clinical features for joint modeling. The predictive performance of different models was assessed using ROC curves. Results In the training and validation sets, Boundary, WHO classification and T2WI signals of lesions were statistically different in TNBC and NTNBC (P<0.05), among the nine models established using rbf_SVM, including Model-T2WI, Model-DWI, Model-DCE_Phase2, Model-DCE_Phase7, Model-T2WI+DWI, Model-DCE_Phase7+T2WI, Model-DCE_Phase7+T2WI+DWI, and Model-DCE_Phase7+T2WI+DWI+Clinic, the radiomics-based predictive model of Model-DCE_Phase7+T2WI+DWI+Clinic demonstrated the highest performance, with areas under the curve (AUC) of 0.992 and 0.936 in the training and validation sets, respectively. Conclusion The radiomics model based on multi-parametric MRI can accurately predict TNBC, contributing to the clinical diagnosis and treatment management of TNBC.

Objective To investigate the clinical significance of susceptibility-weighted imaging (SWI) combined with dual post-labelling delay (PLD) 3D arterial spin labelling (3D-ASL) technique for evaluating patients with acute cerebral infarction and predicting early infarct growth. Methods Thirty-two patients with acute ischaemic cerebral infarction underwent routine MRI, DWI, SWI and 3D-ASL (PLD of 1.5 s and 2.5 s) within 24 h after onset. Among these patients, 21 were re-examined with routine MRI and DWI on day 7 after onset. The following parameters were recorded: NIHSS scores, prominent venous signs (PVS) and scores, DWI infarct size, the bilateral cerebral blood flow (CBF) values (infarct area and mirror area, peri-infarct area and mirror area), rCBF values (CBF value on the affected side/CBF value on the mirror side), ischaemic penumbra area (PLD of 1.5 s and 2.5 s), increase in DWI infarct size between two examinations and 90 d modified Rankin scale (mRS) scores. The patients were divided into PVS positive and PVS negative groups according to the presence of PVS. The differences in imaging parameters among 32 patients were analysed, and Spearman correlation was used to detect the correlation of cerebral infarction growth values with SWI and ASL parameters in 21 patients. Results Significant differences in the first NIHSS score, DWI infarct size, CBF_{1.5 s peri-infarct area}, rCBF_{1.5 s peri-infarct area}, rCBF_{2.5 s peri-infarct area}, CBF_{2.5 s infarct area}, rCBF_{2.5 s infarct area}, PLD 1.5 s and 2.5 s ischaemic penumbra area, difference in PLD 1.5-2.5 s penumbra area and increase in infarct size after 7 d were observed between the PVS positive and negative groups (P<0.05). Specifically, the increase in infarct size was positively correlated with the PVS score, DWI infarct size, and ischaemic penumbra areas (PLD of 1.5 s and 2.5 s) at the first examination (P<0.05) but negatively correlated with the rCBF_{1.5 s infarct area}, rCBF_{1.5 s peri-infarct area}, rCBF_{2.5 s infarct area} and rCBF_{2.5 s peri-infarct area} (P<0.05). Conclusion SWI-based examination of PVS reflects low blood perfusion, large infarct size, large ischaemic penumbra area and high admission severity, demonstrating a certain predictability for the short-term increase in infarct size. Combined with ASL multimodality functional imaging, this approach can provide an accurate assessment of the blood perfusion status in the infarct area and hypoxia in brain tissue, making it crucial for guiding treatment decisions and prognosis in clinical practice.

Objective To assess the postnatal outcomes of fetuses diagnosed with large artery dysfunction but ultimately without developing coarctation of the aorta (CoA). Methods A total of 275 cases of prenatal diagnosis of aorto-pulmonary imbalance from January 2019 to March 2023 were extracted from two fetal prenatal ultrasound diagnostic centers of Anhui Provincial Hospital and the First Affiliated Hospital of Anhui Medical University. According to the postpartum follow-up, 93 cases (34%) were diagnosed with CoA as the CoA group. The non-CoA group included 182 patients (66%) without CoA. Another 149 cases of normal pregnancy were selected as the normal group. The prenatal data, postpartum follow-up and fetal survival curves of the three groups were analyzed to explore the possible influencing factors of postpartum outcomes. Results In the non-CoA group, after eliminating the fetuses with combined intracardiac or extracardiac malformations, the prognosis of fetuses with simple aortic disproportion was favorable, and there was no statistically significant difference in the long-term survival rate compared with normal fetuses (P>0.05). The same was true for the CoA group compared with the non-CoA group (P>0.05), with better long-term survival. The combination of intracardiac and extracardiac malformations was an influencing factor for the poor postnatal prognosis of fetuses with aortic disproportion. Compared with the normal group, infants with bicuspid aortic valve had a smaller aortic annulus and a faster blood flow velocity at the aortic valve orifice, and the differences were statistically significant (P<0.05). Conclusion The prognosis of fetuses prenatally diagnosed with large artery disorders is closely related to the combined intracardiac and extracardiac malformations. The prognosis of fetuses with isolated aorta-pulmonary incoordination is good. Long-term follow-up is recommended for infants with congenital bicuspid aortic valves.

Type 1 diabetes mellitus (T1DM)-related cognitive dysfunction and potential brain impairment have attracted increasing attention with the rising incidence of T1DM and the extension of patient life expectancy. Several studies have demonstrated an association between T1DM and cognitive dysfunction. In recent years, the widespread application of MRI technology has provided objective imaging evidence for exploring the neuropathophysiological mechanisms of brain impairment in T1DM. This article reviews the manifestations of cognitive dysfunction, the application of MRI technology in brain impairment, and the underlying pathological mechanism in patients with T1DM. By summarizing previous research, it aims to help clinicians gain a deeper understanding of the relationship between T1DM and cognitive dysfunction, and to provide new perspectives for future research, with the hope of early identification and intervention for cognitive dysfunction in patients with T1DM.

Objective To analyze the impact of using the fixed tube current technique, CARE Dose 4D, and X-CARE technique during head CT examinations on the radiation dose and image quality of the patients, and develop a head CT scanning protocol that can effectively safeguard radio sensitive organs. Methods We prospectively gathered ninety patients for head CT scans at Xuzhou First People's Hospital from May 2023 to Februray 2024 and randomly assigned them to three group, with 30 patients in each group, including the fixed tube current technique (group A), CARE Dose 4D (group B), and the X-CARE technique (group C). The variability of radiation dose in patients across the different groups was analyzed using volume CT dose index (CTDIvol), size-specific dose estimate (SSDE) and radiation dose of eye lens surface comparisons. Two radiologists with rich experience in film reading were used to perform the subjective score of image quality according to the five-point scale by double-blind method, and the differences of image quality among different groups were compared by using the SD, SNR and subjective score of the images. Results The CTDIvol of the A, B and C group were 49.61±0.40, 33.85±3.20 and 32.40±3.11 mGy, respectively, SSDE were 34.26±1.77, 28.08±5.34 and 27.29±5.30 mGy, respectively. The ocular surface doses were 6.76±0.46, 3.41±0.40 and 2.05±0.73 mSv, respectively. Compared with fixed tube current, CARE Dose 4D and X-CARE technology reduced radiation dose CTDIvol by 31.76% and 34.69%, respectively, and SSDE by 36.55% and 38.34%, respectively. SSDE was 10.78% lower than CTDIvol. For image quality, the noise and SNR of the images using CARE Dose 4D and X-CARE techniques were lower than those of the fixed tube current group, but there was no statistically significant difference in subjective scores among the three groups of images (P>0.05). Conclusion X-CARE technology can effectively reduce the radiation dose of head CT scanning while guaranteeing image quality and protecting the sensitive organs in the eyes.

The incidence and mortality of dilated cardiomyopathy have risen significantly in recent years, establishing it as the most common cardiomyopathy and a primary indication for heart transplantation. Accurate assessment of viable and fibrotic myocardium is crucial for guiding treatment strategies, evaluating therapeutic efficacy, and predicting clinical outcomes in dilated cardiomyopathy patients. Cardiac magnetic resonance imaging with late gadolinium enhancement (CMR-LGE) has proven to be a reliable modality for identifying viable myocardium, providing critical guidance for early diagnosis and personalized treatment strategies in dilated cardiomyopathy. This review systematically summarizes the non-invasive imaging features for evaluating myocardial viability and fibrosis, highlights their clinical applications and prognostic value in cardiovascular diseases, and explores future technological advancements in the field. By integrating current research findings and emerging trends, this work aims to advance innovative methodologies and frameworks for improving early diagnosis and precision medicine in cardiac care.

Objective To develop a combined nomogram model based on enhanced CT imaging features and clinical indicators for predicting early recurrence (ER) in untreated intermediate-stage hepatocellular carcinoma (HCC) patients after transcatheter arterial chemoembolization (TACE), and to compare the performance of this model with radiomics and clinical models. Methods In this retrospective, two-center study, 55 HCC patients who underwent enhanced CT before TACE at Affiliated Hefei First People's Hospital from February 2020 to February 2024 were randomly divided into training and validation groups using five-fold cross-validation. Clinical data, CT radiomics data, pathological data, and serum markers collected within one week before TACE were collected and evaluated for all patients. Radiomic features were selected using univariate rank sum tests and Spearman correlation analysis. Radscore was calculated based on the linear product of logistic regression model coefficients and feature values. Significant variables were identified using univariate and multivariate logistic regression, and a nomogram was constructed. The model's performance was assessed using ROC curves and decision curve analysis. Results In both the training and validation groups, the combined nomogram model had AUCs of 0.787 (95% CI: 0.52-1.05) and 0.847 (95% CI: 0.54-1.14), respectively, for predicting early recurrence after TACE. Univariate and multivariate regression analysis indicated that prothrombin time (P<0.05) was an independent serum marker associated with early recurrence after TACE. In both the training and validation groups, the AUC, accuracy, sensitivity, and specificity of the clinical model and the radiomic nomogram model alone were lower than those of the combined clinical-radiomic nomogram model. Decision curve analysis showed that the combined nomogram model had greater net benefit. Conclusion The proposed combined nomogram model has the potential to accurately predict early recurrence in HCC patients after TACE.

Objective To develop a diagnostic prediction model for coronary artery disease (CAD) based on ^99mTc-methoxyisobutylisonitrile (MIBI) gated myocardial perfusion imaging (GMPI) and clinical features, and to perform internal validation to assess its utility in predicting the risk of CAD. Methods A retrospective analysis was conducted to collect GMPI parameters and clinical characteristics of 116 patients suspected of having CAD who underwent ^99mTc-MIBI SPECT/CT gated myocardial resting perfusion imaging at Zhujiang Hospital of Southern Medical University from January 2023 to November 2023. Among the patients, 77 were male and 39 were female, with an age range of 23-93 (62.66±12.22) years old. Predictive factors for CAD were identified using stepwise regression and multivariate logistic regression analysis, and a diagnostic prediction model was constructed and presented in the form of a nomogram. The predictive performance of the model was evaluated by calculating the area under the ROC curve (AUC). Internal validation was performed using k-fold cross-validation. The calibration and clinical utility of the model were assessed through calibration curves, decision curve analysis (DCA), and clinical impact curves. Results Stepwise regression analysis identified left ventricular end-diastolic volume, peak filling rate, histogram skewness, and histogram kurtosis among the GMPI parameters as effective diagnostic predictors of CAD. Incorporating clinical characteristics (gender, smoking history, cardiac troponin, hypertension), a predictive model was constructed with an AUC of 0.731 (95%CI: 0.636-0.825), specificity of 0.735, and sensitivity of 0.642. The average AUC from k-fold cross-validation was 0.699. Calibration curves demonstrated good calibration of the CAD diagnostic prediction model, while decision curve analysis and clinical impact curves indicated its high clinical utility. Conclusion The diagnostic prediction model based on ^99mTc-MIBI GMPI parameters and clinical characteristics (gender, smoker, cardiac troponin, hypertension) demonstrates good performance in assessing patients with CAD, offering potential for developing more personalized diagnostic strategies for CAD.

Objective To investigate the diagnostic value of spectral CT quantitative enhancement parameters arterial enhancement fraction (AEF) and extracellular volume (ECV) in the differential diagnosis of renal cell carcinoma and renal angiomyolipoma. Methods The spectral base data of 54 patients with renal cell carcinoma and renal angiomyolipoma who underwent three-phase enhanced spectral CT in the Department of Radiology, Hainan Hospital of General Hospital of Chinese PLA from January 2021 to May 2024 were analyzed. The arterial enhancement fraction (AEF) map and extracellular volume (ECV) map were generated, the AEF and ECV values of tumor and contralateral normal renal cortex were measured respectively. The independent sample t test and Mann-Whitney U test were applied for inter-group comparisons, and ROC curve was used to evaluate the diagnostic efficacy. Results The AEF and ECV values of RCC were presented significantly more highly than those of RAML (P_AEF<0.0001, P_ECV<0.0001). There was no significant difference in AEF value between RCC and contralateral normal kidney cortex(P=0.406). The ECV value of RCC was significantly lower than that of contralateral normal kidney cortex (P<0.0001). The AEF and ECV values of RAML were lower than those of contralateral normal kidney cortex (P_AEF<0.0001, P_ECV<0.0001). The area under the ROC curve of AEF and ECV in the diagnosis of RCC was 0.566 and 0.992. The sensitivity and specificity of AEF were 37.1% and 85.2%. The sensitivity and specificity of ECV were 96.3% and 100%. The area under the ROC curve of AEF and ECV in the diagnosis of RAML was 0.818 and 1.000. The sensitivity and specificity of AEF were 77.8% and 88.9%. The sensitivity and specificity of ECV were both 100%. Conclusion Spectral CT quantitative enhancement parameters AEF and ECV can not only detect renal cell carcinoma and renal angiomyolipoma, but also have high diagnostic value for the identification of them.

Objective To compare the clinical efficacy of ultrasound-guided puncture and aspiration combined with vacuum cupping and vacuum sealing drainage (VSD) in the treatment of fistula stage plasma cell mastitis (PCM). Methods Sixty cases of PCM in fistula stage at Inner Mongolia Autonomous Region People's Hospital from January 2021 to January 2024 were collected and randomized into 30 cases each in the intervention group and VSD group, according to the presence or absence of broken skin surface was categorized into ulcerated and non-ulcerated type. In the intervention group, ultrasound-guided puncture and aspiration and hedging, vacuum cupping and negative pressure suction were performed. A negative pressure drainage device was placed after fistula resection in the VSD group. The clinical efficacy of the two treatment protocols were compared. Results The differences between the intervention group and the VSD group in terms of total effective rate of treatment, short-term recurrence rate, and preoperative and postoperative VAS scores were not statistically significant (P>0.05).The initial maximum diameter of the lesion, postoperative scar area, and wound healing time were smaller in the intervention group than in the VSD group; the degree of pain relief, breast shape integrity, and patient satisfaction were better than in the VSD group, and the treatment time was longer than in the VSD group, and the difference was statistically significant (P<0.05). Conclusion There is no significant difference in clinical efficacy between ultrasound-guided puncture and fluid extraction combined with vacuum cupping and VSD, and patient satisfaction is higher, it can be an effective treatment option for fistula stage PCM patients with fertility requirements or who value the integrity of the breast shape.

Objective To investigate the impact of obesity on left ventricular geometry and myocardial mechanics in elderly hypertensive patients using speckle tracking combined with conventional echocardiography. Methods We enrolled 152 elderly patients with primary hypertension from Shanxi Bethune Hospital between January and December 2023. Participants were categorized based on their BMI into normal weight group (n=62), overweight group (n=50), and obesity group (n=40), with an additional 50 healthy controls. Echocardiography was performed to assess conventional and global longitudinal strain (GLS) parameters. We analyzed the differences in echocardiographic parameters and the prevalence of left ventricular geometric configurations across the groups. Results GLS progressively decreased from control group to normal weight group, overweight group and obese group. Left ventricular mass index (LVMI) gradually increased from control group, normal weight group, overweight group and obese group (P<0.05). The prevalence of eccentric hypertrophy was higher in overweight and obesity groups compared to the control and normal weight groups; The prevalence of concentric hypertrophy increased gradually from the control group to the normal weight group, overweight group and obese group (all P<0.05). Correlation analysis revealed that GLS was negatively correlated with age, systolic blood pressure (SBP), BMI and duration of hypertension; LVMI was positively correlated with age, SBP and BMI (P<0.05). Multi-factor linear regression analysis identified that SBP and BMI are the factors of GLS; BMI is an independent risk factor for elevated LVMI. Conclusion Obesity exerts a synergistic effect on left ventricular systolic and diastolic dysfunction and left ventricular hypertrophy in hypertensive patients. BMI is an independent risk factor for left ventricular systolic dysfunction and left ventricular hypertrophy, with the obese condition being more likely to induce left ventricular hypertrophy, which with increased cardiovascular risk and poorer prognosis. Early detection and intervention of altered left ventricular geometry in these patients can aid in reducing the occurrence of cardiovascular diseases among hypertensive and obese individuals.

Breast cancer is one of the most common malignant tumors in women worldwide, and its early diagnosis and treatment are crucial to improve the prognosis of patients. Ultrasound radiomics technology can extract a large number of quantitative features from ultrasound images, and use advanced image processing and data analysis techniques to assist clinical diagnosis, treatment decision-making and prognosis evaluation. In recent years, with the rise of the field of peritumoral radiomics, it provides a new perspective for evaluating tumor microenvironment, predicting tumor invasion and metastasis potential, guiding treatment options and prognosis evaluation. This article reviews the overview of peritumoral radiomics and ultrasound peritumoral radiomics in identifying benign and malignant breast tumors, predicting molecular staging of breast cancer, pathological diagnosis, lymph node status, efficacy of neoadjuvant chemotherapy, and prognostic assessment, with the aim of providing guidance for precise diagnostic and therapeutic practice of breast tumors.

Objective To explore the effects of tenofovir (TAF) on portal hypertension, plasma endothelin-1 (ET-1) and the incidence of cirrhosis-derived complications, for patients with hepatitis B-related cirrhosis who had previously been treated with lamivudine (LAM) combined with adefovir dipivoxil (ADV). Methods A total of 100 patients were enrolled into the group of "switching from LAM+ADV to TAF" and were treated with TAF and underwent a follow-up for 24 months in Zhongshan Chen Xinghai Hospital of Integrated Traditional Chinese and Western Medicine from January 2021 to January 2023. The liver function, alpha-fetoprotein (AFP) and viral index, portal vena-related parameters, abdominal ultrasound, renal function, ET-1, and liver cirrhosis-derived complications were observed and compared at the following 5 time points: before enrollment (T1), at the end of the 6^th month (T2), at the end of the 12^th month (T3), at the end of the 18^th month (T4), and at the end of the 24^th month (T5), respectively. Results TAF was found to significantly down-regulate the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), glutamyl transpeptides (GGT), total bilirubin (TBIL), hepatitis B surface antigen (HBsAg), and hepatitis B virus DNA (HBV-DNA) in patients with posthepatitis B-related cirrhosis. The levels of serum albumin (ALB) was significantly increased after TAF treatment (P<0.05). There were significant differences in portal vein diameter, portal vein pressure, portal vein thrombosis, fatty liver, and splenomegalgia among the time span from T1 to T5, after TAF treatment (P<0.05). There were no significant differences in blood urea, creatinine or uric acid after TAF treatment when compared with pre-treatment (P>0.05). However, changes of ET-1 from T1 to T5 were significantly different (P=0.012), as well as the incidence of gastrointestinal bleeding (P=0.042). Correlation analysis showed that ET-1 was significantly positively correlated with portal vein diameter, portal vein pressure, portal vein thrombosis, and the incidence of gastrointestinal bleeding (P<0.05). Conclusion Switching from (LAM+ADV) to TAF can significantly down-regulate the levels of ET-1 and improve liver function and thus reduce viral loads in patients with posthepatitis B cirrhosis, and improve portal hypertension and its complications, presenting better indexes in the 24^th month than those of 12^th month, and TAF did not present significant side effects on renal function.

Objective To develop a fusion model that integrates multiparametric magnetic resonance imaging (mpMRI)-based radiomics features with clinical and pathological variables for predicting lymph-vascular space invasion (LVSI) in patients with endometrial cancer. Methods This retrospective study included 96 patients with pathologically confirmed endometrial cancer treated at Northwest Women's and Children's Hospital from January 2015 to June 2024. Axial T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) sequences were used to manually delineate both tumor lesions and corresponding uterine body regions. radiomics features were extracted from the delineated regions. clinical and pathological variables were screened using univariate analysis and significant predictors were integrated with imaging features to construct a fusion model. model performance was evaluated using leave-one-out cross-validation. Results The AUC for DWI-based radiomics models reached 0.84 for tumor lesions and 0.87 for the uterine body, while the T2WI-based models yielded AUCs of 0.82 and 0.84, respectively. multivariate logistic regression identified age, CA199 and Ki67 expression as independent predictors of LVSI (P<0.05), with the combined clinical-pathological model achieving an AUC of 0.834. The final fusion model, incorporating both radiomics and clinical-pathological features, achieved an AUC of 0.920, demonstrating superior predictive performance compared to single-modality models. Conclusion The integration of mpMRI-derived radiomics with key clinical and pathological factors significantly enhances the predictive accuracy for LVSI in endometrial cancer. this fusion approach may provide valuable support for accurate preoperative staging and the development of individualized treatment strategies.

Objective To compare the diagnostic value of ¹⁸F-FDG PET/CT versus conventional imaging methods in patients with postoperative peritoneal metastasis of ovarian cancer based on elevated CA125 levels. Methods This study retrospectively analyzed 87 postoperative patients diagnosed with ovarian cancer at the Affiliated Hospital of Xinjiang Medical University from January 2022 to December 2023. The diagnostic performance of four imaging modalities were investigated: ¹⁸F-FDG PET/CT, transabdominal ultrasound (TAUS), transvaginal ultrasound (TVUS), contrast-enhanced computed tomography (CECT) or MRI, in detecting peritoneal metastasis in patients with elevated postoperative CA125 levels exceeding 35 U/mL. The parameters compared include sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for each diagnostic method in the context of postoperative peritoneal metastasis in ovarian cancer patients. Results The sensitivities of ¹⁸F-FDG PET/CT, TAUS, TVUS, CECT or MRI for diagnosing postoperative peritoneal metastasis in ovarian cancer patients were 96.67%, 37.70%, 56.67%, 79.37%, respectively; specificities were 85.19%, 88.46%, 92.59%, 54.17%, respectively; accuracies were 93.10%, 52.87%, 67.82%, 72.41%, respectively; positive predictive values were 93.54%, 88.46%, 94.44%, 81.97%, respectively; negative predictive values were 92.00%, 37.70%, 49.02%, 50.00%, respectively. Conclusion The accuracy of ¹⁸F-FDG PET/CT in diagnosing peritoneal metastasis or recurrence in patients with elevated CA125 levels following ovarian cancer surgery is high, enabling the early detection of peritoneal metastatic lesions.

Vascular dementia (VaD) is the second most common type of dementia, characterized primarily by impairments in attention, information processing, and executive function. Accurate differential diagnosis and early intervention remain challenging. MRI with its non-invasive and reproducible features, plays a crucial role in the diagnosis and monitoring of VaD. Structural MRI can identify white matter hyperintensities, gray matter atrophy, ventricular enlargement, and perivascular space changes. Resting-state functional MRI reveals alterations in local brain activity and functional connectivity in VaD patients. Diffusion tensor imaging quantitatively assesses white matter tract abnormalities, while arterial spin labeling enables non-invasive measurement of cerebral perfusion. Additionally, magnetic resonance spectroscopy detects concentrations of brain metabolites. The integration of multimodal MRI analyses further enhances the diagnostic and monitoring potential of MRI for VaD. This review summarizes recent advancements in multimodal MRI applications for the diagnosis of VaD, providing new strategies for early diagnosis, differential diagnosis, disease monitoring, and intervention.

Objective To explore the relationship between CT fat attenuation index (FAI) of pericoronary adipose tissue (PCAT) and coronary atherosclerosis, plaque properties. Methods A total of 138 patients undergoing coronary CT angiography (CTA) in the hospital from January 2022 to December 2024 were retrospectively analyzed. FAI value of PCAT in all patients was measured to analyze its relationship with coronary atherosclerosis and plaque properties. Results There were 206 lesions in all the 138 patients. FAI value of PCAT has certain relationship with coronary stenosis and plaque properties. FAI value in plaques with mild, moderate and severe coronary stenosis was greater than that with slight stenosis, and which was gradually decreased in non-calcification plaques, mixed plaques and calcification plaques (P<0.05). The results of multiple linear regression analysis showed that FAI value was positively correlated with plaque properties (P<0.05). Conclusion FAI value of PCAT has certain correlation with coronary atherosclerosis and plaque properties. Measuring FAI value around plaques with high risk of unstable inflammation is beneficial to clinically evaluate the risk of coronary heart disease.

Objective To explore the clinical value of MRI in identifying high-risk factors for placenta accreta and postpartum hemorrhage in patients with complete placenta previa. Methods A total of 50 patients with complete placenta previa admitted to the First Affiliated Hospital of Bengbu Medical University from November 2020 to October 2024 were selected as the study subjects. Based on pathological results, the patients were divided into a placenta accreta group (n=41) and a non-placenta accreta group (n=9). According to the occurrence of postpartum hemorrhage, the patients were further divided into a postpartum hemorrhage group (n=42) and a non-postpartum hemorrhage group (n=8). The relationship between MRI features and the occurrence of placenta accreta and postpartum hemorrhage in patients with complete placenta previa was analyzed. The Kappa consistency test was used to evaluate the diagnostic efficacy of prenatal MRI. Multivariate logistic regression analysis was performed to assess MRI features as independent risk factors for postpartum hemorrhage. Results Prenatal MRI findings showed good consistency with pathological results (Kappa=0.675). Comparisons between the placenta accreta group and the non-placenta accreta group, as well as between the postpartum hemorrhage group and the non-postpartum hemorrhage group, revealed statistically significant differences in six out of seven MRI features (P<0.05), except for the sign of thickened and irregular bladder wall. Multivariate logistic regression analysis indicated that the T2WI low-signal band and placental thickness in the lower uterine segment were independent risk factors for postpartum hemorrhage (P<0.05). Conclusion Prenatal MRI demonstrates high consistency with pathological results in diagnosing placenta accreta. The T2WI low-signal band and placental thickness in the lower uterine segment are independent risk factors for predicting postpartum hemorrhage, providing valuable predictive insights for clinical diagnosis and treatment.

Objective To investigate the prenatal ultrasonographic features, magnetic resonance imaging (MRI) characteristics, and postnatal follow-up evaluation of fetal ovarian cysts. Methods A retrospective analysis was conducted on cases of suspected fetal ovarian cysts detected by prenatal ultrasound. Parameters including gestational age, cyst location, size, internal echogenicity, and MRI signal characteristics were systematically analyzed. Based on outcomes, cases were categorized into vanishing and non-vanishing groups. The non-vanishing group underwent surgical intervention and was further subdivided into torsion and non-torsion subgroups. Comparative analyses were performed on cyst echogenicity, dimensional changes, and positional variations across subgroups. Results Among 164 initially identified ovarian cysts, 33 cases were lost to follow-up and one case underwent pregnancy termination, resulting in 130 cases for final analysis. The vanishing group (n=102, 78.5%) demonstrated significantly higher proportions of simple cysts (88/102, 86.3%) and positional stability (100/102, 98.0%) compared to the non-vanishing group (P<0.05). Among 28 surgically managed non-vanishing cases, torsion occurred in 12 cases (42.9%), all presenting as complex cysts. The torsion subgroup exhibited 100% complex cyst morphology (12/12) compared to 25% (4/16) in non-torsion cases (P<0.05). The difference between the changes in size and location of cysts in the two groups was not statistically significant (P>0.05). Median cyst volumes significantly differed between torsion 18.7 (12.8, 61.1) cm³ and non-torsion groups 69.7 (49.9, 149.2) cm³, (P<0.05). Conclusion Surveillance of fetal ovarian cysts should prioritize complex morphology and monitor dimensional/positional changes. Combined ultrasound-MRI evaluation is recommended for persistent complex cysts to facilitate early detection of adnexal torsion and optimize torsional prognosis.

Chronic low back pain ranks among the most prevalent forms of chronic pain in clinical settings and constitutes one of the major causes resulting in global disability or diminished productivity, ultimately imposing substantial economic and social burdens on patients and their families. The common treatment methods of chronic low back pain include medications, physiotherapy, traditional Chinese acupuncture, etc., but there is no objective evaluation methods and unified standard for the treatment effect of chronic low back pain. Functional magnetic resonance imaging analysis is frequently employed in the diagnosis and efficacy assessment of functional nervous system diseases and chronic pain. This article undertakes a review of the recent functional magnetic resonance imaging studies on acupuncture treatment for chronic low back pain with the aim of providing an objective efficacy evaluation basis for acupuncture treatment of chronic low back pain and also proffering possible research directions for subsequent studies.

Objective To explore the application value of energy spectrum CT monochromatic imaging combined with metal artifact removal algorithm in reducing metal artifacts after intracranial aneurysm coil embolization. Methods The original data of 48 patients who needed spectral head and neck CT examination after intracranial aneurysm embolization were collected in Hunan University Of Medicine General Hospital from June 2023 to August 2024. The 40-140 keV monochromatic image, 140 kVp mixed-energy image and 40-140 keV combined with metal artifact reduction algorithm were reconstructed from the original data respectively. In terms of objective analysis, the brain tissue regions affected by artifacts were selected as the experimental group, and brain tissue regions unaffected by artifacts were selected as the control group; CT values and standard deviations were measured, and artifact indices and signal-to-noise ratios were calculated for the regions; In terms of subjective analysis, two diagnostic doctors used the Likert 5-point scale to subjectively score the severity of metal artifacts and the clarity of surrounding tissues. Results The artifact index decreases gradually and the signal-to-noise ratio increases gradually as the single energy level increases. The artifact index of the single-energy combined metal artifact removal algorithm group was lower than that of the single-energy group under the same keV condition, and the difference was statistically significant (P<0.05). The signal-to-noise ratio of the single-energy combined metal artifact removal algorithm group was higher than that of the single-energy group under the same keV condition, and the difference was statistically significant (P<0.05). The signal-to-noise ratio of the single-energy combined metal artifact removal algorithm group reached the highest and stabilized, while the artifact index reached the lowest and stabilized at energy levels 100-140 keV. In terms of subjective evaluation, the subjective scores of the single-energy combined metal artifact removal algorithm group are higher at the same keV, and the differences are statistically significant (P<0.05). Conclusion Spectral CT monochromatic imaging combined with metal artifact removal algorithm effectively reduces metal artifacts after intracranial aneurysm embolization, optimizes blood vessel display, and improves image quality.

Objective To develop and validate an MRI radiomics nomogram model for the accurate preoperative prediction of lymph node metastasis in patients with cervical squamous cell carcinoma. Methods The clinical, pathological and imaging data from patients diagnosed with cervical squamous cell carcinoma at the First Affiliated Hospital of Bengbu Medical College from December 2018 to November 2021 were retrospectively collected. All patients were randomly allocated into a training cohort (n=151) and a validation cohort (n=65) following a 7:3 ratio. Within the training cohort, sagittal T2WI, T1WI and transverse diffusion-weighted images were selected. Regions of interest were delineated at the margins of the largest lesions to extract imaging features. The LASSO algorithm was employed to construct the radiomics score. Multivariate logistic regression analysis identified FIGO stage, squamous cell carcinoma associated antigen levels, and lymph node short-axis diameter as independent risk factors. An MRI radiomics nomogram model was developed by integrating radiomics scores with clinical parameters, and this nomogram model was validated using an independent validation cohort. The area under the curve (AUC) was utilized to assess the predictive performance of the model. Calibration curves and decision curves were employed to evaluate the clinical utility of the nomogram model. Results The nomogram model incorporating clinical parameters and radiomics scores (AUC=0.912) demonstrated superior diagnostic efficacy compared to the clinical feature model (AUC=0.872) and the radiomics model alone (AUC=0.777). Conclusion The integration of MRI radiomics with clinical parameters into a nomogram model represents a simple, effective, and reliable approach for predicting lymph node metastasis in cervical squamous cell carcinoma.

Objective To develop and validate a 3D convolutional neural network (3D-CNN)-based CT-assisted diagnostic model for tuberculosis (TB) activity grading, aiming to improve diagnostic efficiency and accuracy. The model incorporates Grad-CAM visualization technology to provide interpretability analysis of its decision-making process. Methods Retrospective data were collected from 300 patients who underwent non-contrast chest CT scans at Jining Public Health Medical Center from January 2020 to December 2024. According to the Diagnostic Criteria for Pulmonary Tuberculosis (WS 288-2017) and comprehensive clinical evaluation (including sputum culture, pathological results, anti-TB treatment response, and follow-up imaging dynamics), patients were stratified into three groups, with 100 cases in each group: normal lung group, active TB group, inactive TB group. The 3D-CNN model was employed to extract spatial features from CT images, with model parameters optimized through cross-validation. Model performance was systematically evaluated. The Grad-CAM algorithm generated heatmaps to identify critical regions of model attention, with results validated against clinical diagnostic standards. Results The model achieved 95.00% of classification accuracy, 95.30% of sensitivity, and 95.60% of specificity on the test set. Grad-CAM visualizations demonstrated high spatial concordance between model-identified regions and expert-annotated lesion areas. Conclusion The 3D-CNN-based CT-assisted diagnostic model shows high performance in TB activity grading and may serve as an effective clinical decision-support tool. The integration of Grad-CAM enhances model transparency and credibility.

Objective To investigate the predictors for differential diagnosis of benign and malignant thyroid nodules and construct quantitative model based on ultrasound imaging features to provide more reference for clinical diagnosis and treatment plan formulation. Methods A total of 375 patients for 453 nodules with C-TIRADS 3-5 grade thyroid nodules who received surgical treatment in our hospital from January 2022 to December 2023 were retrospectively included and were divided into benign group and malignant group according to the characteristics of nodules identified by histomatological examination. Univariate and multivariate analysis of predictive factors for differential diagnosis of benign and malignant thyroid nodules. A quantitative prediction model based on ultrasound imaging features was constructed and prediction efficiency was analyzed. Results Among the 453 thyroid nodules, 257 nodules were diagnosed as malignant and 196 were benign based on pathological examination, with a malignant detection rate of 56.73%. The results of univariate analysis showed that the maximum diameter of the lesion, the texture of the lesion echo, the type of lesion echo, the structure of the lesion, the location of the lesion, the local strong echo of the lesion, the edge of the lesion, the thickness of the lesion halo, the echo characteristics behind the lesion, and the lesion elasticity score may all be related to the differential diagnosis of benign and malignant thyroid nodules (P<0.05). The results of multivariate analysis confirmed that lesion echo, local strong echo, lesion edge, posterior echo characteristics, lesion elasticity score and lesion acoustic halo thickness were all independent predictive factors for the differential diagnosis of benign and malignant thyroid nodules (P<0.05). The area under the ROC curve is 0.741, 0.639, 0.747, 0.544, 0.605, 0.796, the predictive model constructed by combining the above factors had an area under the ROC curve of 0.952, a sensitivity of 91.05%, a specificity of 88.78%, and a Yoden index of 79.83%. Conclusion Various ultrasound imaging indexes, including lesion echoes, localized strong echoes of the lesion, lesion margins, posterior echogenic features of the lesion, elasticity score of the lesion, and thickness of the acoustic halo of the lesion, can guide the differential diagnosis of benign and malignant thyroid nodules, and the quantitative model constructed by using the above six imaging features has a higher reliability and accuracy in the prediction of the nature of thyroid nodules, which can provide assistance in clinical prevention and treatment of thyroid cancer.

Myocardial wall motion dysfunction represents a pivotal early pathophysiological mechanism underlying the structural and functional deterioration observed in various cardiovascular diseases, and it is strongly correlated with patient prognosis. Gated myocardial perfusion imaging is a cornerstone non-invasive imaging modality for evaluating myocardial ischemia and viability in patients with cardiovascular disorders. Utilizing advanced post-processing software, gated myocardial perfusion imaging enables the quantification of both global and regional left ventricular functional parameters. Recent advancements have significantly enhanced myocardial wall motion assessment. These include dedicated cardiac SPECT technology, optimized acquisition protocols, sophisticated image reconstruction algorithms, and the integration of artificial intelligence. This review examines the application value and research progress of gated myocardial perfusion imaging in cardiovascular diseases. It focuses on early diagnosis, risk stratification, and prognostic evaluation, particularly in ischemic heart disease. Additionally, the review critically analyzes the current limitations of G-MPI. It also explores future directions to provide novel insights for precise diagnosis and therapeutic management of cardiovascular diseases.

Objective To analyze the risk factors for intracranial aneurysm (IA) rupture based on morphological parameters from computed tomography angiography (CTA), clinical characteristics of patients, and hematological inflammatory indicators. Methods A retrospective analysis was conducted on 176 IA patients treated at the Second Affiliated Hospital of Bengbu Medical University from November 2022 to September 2024. Based on the presence or absence of subarachnoid hemorrhage, patients were categorized into an unruptured group (n=72) and a ruptured group (n=104). Clinical data, hematological inflammatory indicators, and CTA-derived aneurysmal morphological parameters were compared between the two groups. Univariate and multivariate logistic regression analyses were employed to identify risk factors for IA rupture. Additionally, ROC curves and area under the curve (AUC) analyses were performed to evaluate the diagnostic efficacy of these risk factors. Results Irregular morphology (OR=3.079, 95%CI: 1.030-9.200, P=0.044), presence of daughter sacs (OR=3.271, 95% CI: 1.109-9.650, P=0.032), elevated size ratio (OR=2.117, 95%CI: 1.074-4.170, P=0.030), increased aspect ratio (OR=7.189, 95%CI: 1.242-41.619, P=0.028), and elevated systemic inflammatory response index (OR=1.500, 95%CI: 1.242-1.810, P<0.001) were identified as independent risk factors for IA rupture, with AUC values of 0.77, 0.75, 0.67, 0.75 and 0.93, respectively. Conclusion Analysis based on CTA morphological parameters combined with clinical factors and blood inflammation indicators reveals that IAs with irregular morphology, presence of daughter sacs, high size ratio, high aspect ratio, and elevated systemic inflammatory response index are all high-risk factors for aneurysm rupture. These factors hold immense importance in accurately predicting the risk of aneurysm rupture.

Objective To analyze the value of imaging data, clinical-laboratory data model and fusion model in predicting prognosis of patients with spontaneous intracerebral hemorrhage. Methods A total of 363 patients diagnosed with spontaneous cerebral hemorrhage by head CT in Lu'an People's Hospital from September 2021 to March 2023 were retrospectively collected. The functional recovery of patients 6 months after discharge was evaluated using the modified Rankin scale. According to the results, the patients were divided into two groups: the good outcome (n=175) and the poor outcome (n=188). Clinical data such as age and gender, neutrophil and lymphocyte counts and their percentages, D-dimer, and hematoma image data outlined and extracted from the first head CT scan on admission were recorded. Multiple logistic regression method was used to construct clinical-laboratory data model, image data model and fusion model, respectively. Results Clinical and laboratory data of statistical significance between the two groups included GCS score, number and percentage of neutrophils, and percentage of lymphocytes (P<0.001). Imaging data included ventricle presence or absence of hematoma, hematoma sphericity, surface area, and feret diameter (P<0.001). The AUC of clinical-laboratory data model, image data model and fusion model were 0.82(95% CI: 0.78-0.86), 0.80(95% CI: 0.75-0.84) and 0.86(95% CI: 0.82-0.89). Delong test showed that the performance of fusion model was significantly different from that of single clinical-laboratory data model and imaging data model (P<0.05). Conclusion The fusion model of imaging data combined with clinical and laboratory data has significant value in predicting the prognosis of spontaneous intracerebral hemorrhage.