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 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.

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.

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 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.

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.

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.

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 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.

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 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 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.

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 whether the use of spectral CT (IQon CT) combined compensation strategy technology can ensure the image quality while limiting the total radiation absorption rate in coronary CT angiography. Methods The clinical data of 80 subjects admitted to Nanjing Gulou Hospital from January 2021 to December 2023 were retrospective reviewed and divided into two groups, with forty subjects in each. Group A: 100 mL of contrast, injection rate of 5.0 mL/s (tube voltage 120 kV, 320 mgI/mL); Group B: 40 mL of contrast, injection rate of 3.5 mL/s, compensation strategy IQon CT scan (tube voltage 70 kV, 270 mgI/mL). The subjective and objective evaluation [contrast to noise ratio (CNR), signal-to-noise ratio (SNR)], the radiation dose [volume dose index (CTDIvoI), product of dose length (DLP), effective dose (ED)] were compared, and contrast iodine absorption coefficient were calculated between the two groups. Results There was no significant difference in the subjective evaluation of the two groups (P>0.05), the subjective quality score of the two groups was 3 points, and the consistency of the two groups was high (P <0.05). CT values, SNR and CNR between the two images were statistically different (P<0.05); CT values in group A were lower than group B, and group B had optimal CT values, CNR and SNR at 40 keV single-energy images. In group B, CTDIvoI decreased 66.7%, DLP decreased 83.8%, and ED decreased 75.6% (P<0.05). The iodine absorption coefficient of group B was 70.1% lower than group A (85.2 g vs 25.4 g). Conclusion The application of IQon CT combined with compensation strategies in coronary CTA has broad prospects, possessing significant clinical value and great potential for promotion.

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 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.

In recent years, traditional ¹⁸F-FDG PET/CT has been widely used in cancer diagnosis. However, it has certain limitations in detecting small metastases and lymph node metastases, as well as imaging specificity. Fibroblast activation protein-α (FAPα) is overexpressed on cancer-associated fibroblasts in approximately 90% of malignant solid tumors. ⁶⁸Ga-labelled radiopharmaceuticals-FAP-inhibitors (FAPI)-have been developed for PET by targeting FAPα, and showed breakthrough diagnostic potential in various tumors. This article reviews the molecular basis and development history of FAPI imaging technology, and reviews the current clinical application status of FAPI imaging in various cancers such as breast cancer, lung cancer, and pancreatic cancer, showing its diagnostic efficacy compared to traditional ¹⁸F-FDG. Finally, it discusses the main challenges FAPI imaging faces in current clinical promotion, aiming to highlight the great potential of FAPI imaging in cancer diagnosis and its future research directions, to promote further improvement of the technology and its widespread application in clinical practice.

Breast cancer is one of the most prevalent malignant tumors in women, and the status of axillary lymph nodes plays a decisive role in clinical staging, treatment decision-making, and prognosis of the tumor. Sentinel lymph node biopsy and axillary lymph node dissection are currently the gold standards for evaluating the status of axillary lymph nodes, but both are invasive procedures with various postoperative complications. Therefore, preoperative non-invasive assessment of axillary lymph nodes status is crucial for clinical treatment decision-making. Radiomics and deep learning techniques predict the biological behavior of tumors by extracting high-throughput radiomics features, characterized by reproducibility, noninvasiveness, and objectivity. They have been widely used in the diagnosis of breast cancer, evaluation of lymph node metastasis, and prognosis assessment. This article summarizes the research progress of radiomics and deep learning techniques based on digital mammography and MRI in predicting axillary lymph node metastasis in breast cancer, aiming to provide new ideas for clinical individualized precision medicine.

Breast cancer is one of the most common cancers worldwide and the leading cause of cancer death in women.In recent years, with the rapid improvement of computer performance, artificial intelligence shines in various fields, and artificial intelligence deep learning with automatic image analysis ability has also attracted more and more attention in the medical field, medical institutions have begun to pay attention to the collection of medical data, especially the accumulation of a large number of medical image data. At present, there are three conventional imaging methods for breast diseases: mammography, breast ultrasound and breast MRI.Artificial intelligence combined with breast imaging offers unprecedented opportunities for the diagnosis and treatment of breast cancer.This paper reviews the combination of artificial intelligence and breast image data in the diagnosis, treatment and prognosis prediction of breast cancer, hoping that artificial intelligence can be more widely and maturely applied to the imaging diagnosis and treatment of breast cancer, so as to provide ideas for promoting the transformation and application of precision medicine for breast cancer from theory to clinical practice by combining artificial intelligence with breast image data.

Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor of the gastrointestinal tract, with complex biological characteristics and varying risk levels, thus early diagnosis and precise risk assessment are crucial for subsequent treatment. Imaging genomics can extract and analyze quantitative imaging features with strong representativeness from different modalities of imaging data, and complete the tasks of diagnosis and prediction by combining machine learning methods with clinical data. Studies have shown that imaging genomics can not only be used for differential diagnosis, risk stratification, and prognosis assessment of GIST, but also show potential in gene mutation status assessment and treatment response prediction. This review discussed the application of imaging genomics in early differential diagnosis, risk grading, gene mutation prediction, and treatment effect evaluation of GIST, and reported its limitations, in order to explore the future development directions.

Breast cancer is the most common malignancy among women, with the highest incidence rate of all female cancers. Radiotherapy is an essential treatment modality for breast cancer, effectively reducing recurrence and mortality rates. However, during radiotherapy, the heart inevitably gets exposed to ionizing radiation, increasing the risk of cardiac toxicity, particularly complications such as ischemic cardiomyopathy. Therefore, effective cardiac protection and minimizing heart radiation exposure are crucial challenges in breast cancer radiotherapy. This review explores four key aspects: the impact of radiotherapy on the heart, cardiac dose constraints, automated segmentation of cardiac regions, and strategies to reduce cardiac dose exposure, in order to implement effective cardiac protection through various technologies to reduce the risk of cardiac complications and improve patients' long-term quality of life.

In recent years, the incidence of differentiated thyroid cancer (DTC) has been increasing significantly. The application of PET/CT in the integration of diagnosis and treatment of DTC has attracted much attention. It provides molecular information by combining anatomical with functional imaging. Fluorodeoxyglucose (¹⁸F-FDG) has been confirmed as a marker of cellular glucose metabolism and is the most widely used PET radiopharmaceutical. In addition to ¹⁸F-FDG, multiple new PET molecular probes are also expected to be applied from basic research to clinical practice for imaging and guiding treatment of DTC. This article reviews the mechanism and research progress of new PET molecular probes, aiming to provide valuable reference for the development and application of new molecular probes in the diagnosis and treatment of DTC.

Liver fibrosis is a degenerative condition of the liver induced by a number of chronic liver disorders that is distinguished by aberrant deposition of hepatic extracellular matrix. Liver fibrosis is reversible in its early stages, thus early detection and proper staging are critical in clinical practice. Hepatic stellate cells, which are the core cells in the formation of hepatic fibrosis, play an important role in its initiation and progression. Molecular imaging approaches for targeting hepatic stellate cells integrate physiological and pathological metabolic molecular information in an accurate and non- invasive manner, allowing for the early and specific identification of liver fibrosis. As a result, the advancement of targeted hepatic stellate cell molecular imaging in the assessment of liver fibrosis serves an important purpose and significance, not only in improving diagnostic accuracy and therapeutic efficacy of liver fibrosis, but also in promoting the development and innovation of related disciplines. In this paper, we will review recent research progress in molecular imaging of targeted hepatic stellate cells in liver fibrosis, as well as summarize the research and application value of different molecular probes against various hepatic stellate cell targets for the diagnosis and staging of early liver fibrosis.

Objective To explore the uptake of tau PET in meningioma by ¹⁸F-PI-2620 PET brain imaging, its correlation with lesion size and calcification, and its potential application. Methods A retrospective analysis was performed on 311 subjects who underwent ¹⁸F-PI-2620 PET brain examinations at our hospital from January 2020 to December 2023. Patients with meningioma diagnosed by final MRI enhancement were screened. The size and maximum standardized uptake value (SUV_max) of the meningioma lesions were measured for all included subjects, and the SUV_max of the lesion to the background (T/N) were obtained using the normal cerebral cortex on the opposite side as the background. Statistical analysis was performed using SPSS 26.0 statistical software, and the correlation between SUV_max, T/N values and lesion size and calcification was compared. Results Eight meningioma patients were included, including 3 males and 5 females, aged at 65-78 (69.8±4.86) years old. There was a statistically significant difference in SUV_max between the meningioma and the background (P<0.05). The T/N in the meningioma group was higher than that of the background (P<0.001). There was no statistically significant difference in SUVmax and T/N ratio between the meningioma calcification group and the non-calcification group (P>0.05). The volume of the lesion was significantly correlated with the T/N ratio of uptake (R=0.89, P<0.01). Conclusion The tau uptake value of ¹⁸F-PI-2620 in meningioma is related to the size of the lesion, but not whether the lesion is calcified.

Rheumatoid arthritis (RA) is a systemic inflammatory disease that typically presents as polyarthritis but can involve multiple systems and lead to increased morbidity and mortality. Due to its diverse clinical manifestations, the diagnosis of RA remains challenging. PET is increasingly utilized for diagnosing RA, monitoring treatment response, predicting remission, and detecting subclinical complications. This paper summarizes the factors produced by different cells in the synovial membrane of RA joints and analyzes and compares recent research hotspots such as PET/MRI and immune cells in RA. Although PET has shown promise as a tool for assessing and managing RA, more evidence is needed before it can be included in standard clinical management.

Depression is a common mental disorder, but its pathogenesis is intricate and there is still only a partial understanding of its underlying pathophysiology. Studies have shown that metabolic glutamate receptor 5 (mGluR5) plays a key role in the pathophysiology of depression. Depression animal model studies and in vitro radiotracer autoradiography have provided insights into the changes of mGluR5 in depression, but limitations in its translation to the clinic have restricted further understanding of depression. With the continued development of PET and radiotracers, nuclide noninvasive receptor imaging has made it possible to study the availability of mGluR5 for depression in vivo. This review summarised the development of the mGluR5 PET radioligand, provided the results of clinical and preclinical PET in vivo studies supporting the involvement of mGluR5 in the pathophysiological processes of depression, and discussed the potential value of mGluR5 PET imaging in depression.

Lumbar disc herniation(LDH) is a common and frequently-occurring disease in orthopaedics, which can seriously affect patients' physical and mental health, daily life and work. At present, there are many clinical methods to treat LDH, and the vast majority of mild and moderate patients can relieve symptoms or even recover after conservative treatment. Surgical treatment should be selected for failure of conservative treatment or cauda equina syndrome. There are many specific types of surgical treatment, and each therapy has its own characteristics, various treatment methods can be used alone, can also be used in combination, the effect of combined treatment is significantly better than single treatment. In this paper, various literatures on LDH surgical treatment published at home and abroad in recent years were reviewed and summarized, and four aspects of traditional surgery, minimally invasive surgery, interventional surgery and robot-assisted surgery were reviewed, aiming to provide reference for the selection of clinical treatment of LDH.

In the field of Parkinson's disease (PD), sleep disorders are recognized as one of the most common non-motor symptoms, closely related to the development of motor and non-motor symptoms of the disease. Research shows that patients with PD and sleep disorders (such as rapid eye movement sleep behavior disorder) progress faster than those without sleep disorders, and most sleep disorder patients will eventually progress to Parkinson's disease. At present, the relationship between sleep disorders and the pathogenesis of PD has not been fully clarified. Therefore, early detection of abnormal structural and functional changes in patients with PD and sleep disorders is of great value in delaying disease progression and preventing the transformation of sleep disorders into PD. In recent years, with the continuous development of imaging technology and its wide application, many neuroimaging techniques have been widely used in the study of PD patients with non-motor symptoms, such as diffusion tensor imaging, resting-state functional -MRI, neuromelanin sensitive-MRI, SPECT/PET and Transcranial sonography.They play a key role in the study of Parkinson's disease, and they have important value in the early diagnosis, monitoring and clarifying the pathogenesis of the disease. This article reviews the imaging research progress of the above neuroimaging techniques in patients with Parkinson's disease and sleep disorders. To better understand the pathophysiological mechanisms of PD accompanied by sleep disorders, and to guide clinical diagnosis and treatment.

Objective To explore the imaging characteristics of ¹⁸F-FDG PET/CT in patients with dermatomyositis accompanied by malignant tumors, with the aim of enhancing understanding of this disease. Methods A retrospective analysis was conducted on 14 patients diagnosed with dermatomyositis and malignant tumors through pathology, spanning from April 2018 to March 2023. The degree of muscle uptake throughout the body was analyzed by manually delineating regions of interest. Meanwhile, a normal control group (n=14) was established, and the muscle uptake values of the control group were measured. Differences in muscle uptake values between the two groups were then compared. Results Among the 14 patients with dermatomyositis, there were 4 cases of gastric cancer, 3 cases of ovarian cancer, 2 cases of lymphoma, 1 case each of lung cancer, esophageal cancer, nasopharyngeal cancer, and breast cancer, as well as 1 case of poorly differentiated adenocarcinoma of unknown origin. The average muscle uptake value of the patients with dermatomyositis was 3.5±1.8, which was significantly higher than the average value of 1.3±0.1 in the control group, and the difference was statistically significant (P<0.001). Conclusion ¹⁸F-FDG PET/CT imaging not only enables the assessment of disease activity through the diffuse uptake degree of muscles and provide a basis for biopsy of the lesions, but also facilitates the staging and evaluation of accompanying malignant tumors, offering significant imaging reference value for clinicians in further precise diagnosis and treatment.