Objective To evaluate the potential of deep learning image reconstruction (DLIR) in improving image quality and reducing radiation dose by comparing the noise power spectrum, task-based transfer function and lesion detection capability. Methods The ACR464 phantom was scanned using GE Revolution APEX CT and eight different noise indices (NI=10, 14, 16, 18, 20, 22, 24, 28) were set. The original data were subjected to image reconstruction using filtered back-projection (FBP), multi-model iterative reconstruction algorithms (ASiR-V) at 40%, ASiR-V at 60%, ASiR-V at 80%, and different levels of deep learning image reconstruction (DLIR-L, DLIR-M, DLIR-H) algorithms. The image quality was evaluated by using imQuest software to calculate the noise power spectrum (NPS), task-based transfer function (TTF), and detection capability index (d') of different reconstruction algorithms. Results Among all the reconstruction algorithms, the NPS peak of DLIR-H was the lowest. With the increase of noise index, both NPS and fav move towards low frequencies. The fav of DLIR-H (0.24-0.27 mm^-1) was only 40% lower than that of ASiR-V (0.26-0.28 mm^-1). The TTF_50% value was not affected by the DLIR level. The TTF_50% value was (37.44±10.85)% and (46.24±15.28)% higher than that of ASiR-V60% and 80%, respectively. The detection ability of both large and small features in deep learning image reconstruction was 40% higher than that of ASiR-V. When comparing the radiation doses with comparable lesions detection capabilities of 40% ASiR-V at NI=10 and DLIR-H, the radiation dose for small features decreased by approximately 76.48%, and that for large features decreased by approximately 72.59%. Conclusion Deep learning image reconstruction can not only reduce noise, improve spatial resolution and lesion detectibility without changing noise texture, but also has more powerful ability to reduce radiation dose than ASiR-V.

Objective To explore the value of a Nomogram model based on CT radiomics with clinical parameters in differentiating non-small cell lung cancer from benign pulmonary lesions. Methods A retrospective study was conducted on 177 patients with benign pulmonary lesions and non-small cell lung cancer, confirmed by pathology, at the First Affiliated Hospital of Bengbu Medical Unversity from December 2020 to December 2023. The cases were randomly divided into a training group and a validation group in an 8:2 ratio. Radiomic features were extracted from contrast-enhanced CT images, and a stepwise dimensionality reduction was performed using the Relief-LASSO algorithm, ultimately selecting five optimal features from a total of 2264 radiomic features. Single and multiple factor Logistic regression was employed to screen independent clinical risk factors. Clinical, radiomics, and Nomogram models were constructed respectively. The performance of the Nomogram model was comprehensively evaluated using multiple metrics, including the area under the ROC curve (AUC), calibration curves, and decision curve analysis. Results The results indicated that the Nomogram model exhibited excellent predictive performance, with AUC values of 0.872 (95% CI: 0.817-0.928) in the training set and 0.788 (95% CI: 0.627-0.948) in the validation set. These values were significantly higher than those of the individual imaging model (0.811, 0.722) and the clinical model (0.797, 0.734). Conclusion The established Nomogram model serves as a non-surgical predictive tool for the differential diagnosis of non-small cell lung cancer and benign pulmonary lesions. Validation demonstrated that the Nomogram model exhibited excellent differentiation and calibration abilities, indicating its clinical utility in the early screening of lung cancer and providing important guidance for clinical decision-making prior to surgery.

Objective To explore the clinical value of a combined model constructed based on ultrasound radiomics features and clinicopathological features in predicting pathological complete response after neoadjuvant chemotherapy (NAC) for breast cancer. Methods Retrospective analysis included 160 breast cancer patients receiving NAC before surgery at the First Affiliated Hospital of Bengbu Medical College from August 2021 to July 2024. By analyzing the ultrasound images, the radiomics features were extracted, and the features with statistical significance were screened out for subsequent modeling. Multivariate Logistic regression analysis and the XGBoost algorithm were used to construct joint models based on ultrasound radiomics features, clinicopathological features, and their combination, respectively, and nomograms were drawn. Model performance for NAC response was evaluated using AUC and decision curve analysis, with calibration curves assessing prediction-actuality agreement in the combined model. Results Estrogen receptor (P=0.006), progesterone receptor (P=0.024), and human epidermal growth factor receptor-2 (P=0.034) emerged as independent predictors of NAC response among clinicopathological features. The integrated model combining these three clinical predictors with radiomics features demonstrated optimal predictive performance, achieving a training-set AUC of 0.863, significantly higher than individual models. Calibration curves confirmed robust agreement between predicted and observed outcomes, while decision curve analysis indicated substantial clinical net benefit. Conclusion The combined model constructed based on the characteristics of ultrasound radiomics and clinicopathological features can effectively predict the efficacy of NAC in breast cancer and provide strong support for clinical decision-making. This model has high predictive accuracy and clinical application value, and is expected to become an important tool for individualized treatment of breast cancer.

Objective To analyze the imaging features of pediatric diffuse midline glioma H3K27M variant (DMG-A). Methods The data of 22 children with DMG-A admitted to our hospital from February 2019 to October 2023 were retrospectively analyzed. Preoperative CT scan was performed in 12 cases (11 cases simultaneously with MRI). The images were independently read by two experienced pediatric imaging diagnostic doctors with over 10 years of working experience. Observed the lesion location, shape, size, density/signal characteristics of the solid part, signal intensity, restricted diffusion and MRS Manifestations, intratumoral calcification, hemorrhage and necrosis/cystic changes, enhancement features, whether there are blood vessels passing through the tumor, peritumoral edema, adjacent and secondary changes of the tumor, whether there is distant metastasis, and the metastatic site, etc. Results CT examinations were conducted in 10 cases. The brainstem lesions were mostly low/slightly low density shadows (9 cases), followed by equal or slightly high density shadows (1 case each). It is manifested as thickening of the brainstem, mostly centered on the pons, and partially involving the medulla oblongata, midbrain, cerebellar peduncle and cerebellar hemispheres. The thalamic lesion was a mass-like, uneven, slightly high-density shadow (1 case), extending towards the cisterns and the right side of the midbrain. MRI examination was conducted in 21 cases. The brainstem lesions were characterized by significant thickening and enlargement of the brainstem, with the pons being the most prominent. The main signal shadows were low on T1WI and slightly high on T2WI/FLAIR (15 cases). DWI could have diffuse limitation (9 cases), or no diffuse limitation (5 cases), and another case had no DWI examination. The lesions mostly surrounded the basilar artery (14 cases). Thalamic lesions were manifested as an increase in thalamic volume (6 cases), mainly low signal shadows on T1WI (5 cases), followed by isosignal shadows (1 case), and slightly high signal shadows on T2WI/FLAIR. DWI may have diffuse limitation (4 cases) or no limitation (2 cases). It partially affects the cerebellum, midbrain and other parts downward. After enhancement, most cases presented with obvious nodular, flower-shaped and patchy enhancement (13 cases), and could also show mild heterogeneous enhancement and no obvious enhancement (3 cases each). Additionally, 2 cases had no MRI enhancement examination. Nine cases underwent MRS Examination. The main manifestations were elevated Cho and Cr peaks, decreased NAA peak, and elevated Cho+Cr/NAA. Conclusion Although the imaging manifestations of DMG-A in children are varied, they still have certain characteristics. A comprehensive analysis of the age of occurrence, location of onset, whether the diffusion is limited, and the way and extent of intensification is helpful to improve the imaging diagnosis and differential diagnosis of the disease.

Objective To evaluate the clinical, pathological, and imaging characteristics of multiple renal hemangiomas in different renal functions, namely end-stage renal disease (ESRD) and non-ESRD. Methods A retrospective analysis was performed on 1 case of ESRD-related multiple renal hemangioma confirmed by surgery in Shanxi Bethune Hospital (Shanxi Academy of Medical Sciences) on April 2017. Additionally, 23 cases of pathologically confirmed multiple renal hemangiomas patients from 1980 to 2023 were collected from the PubMed database. They were divided into the ESRD group and non-ESRD group according to renal function status. The clinical basic conditions, imaging features, treatment methods, and prognosis of the two groups were analyzed. Results The ESRD group included 19 cases (79.2%) , and the non-ESRD group included 5 cases (20.8%). Males were more common. There were no statistically significant differences between the two groups in terms of age, gender, clinical symptoms, tumor side, location, and concomitant renal epithelial tumors (P0.05). Extramedullary hematopoiesis was only observed in the ESRD group, with a statistically significant difference (P0.05). Except for the 1 case in our hospital, 5 patients were followed up for an average of 16 months, and no signs of tumor recurrence or metastasis were found. Conclusion Multiple renal hemangiomas are rare and mostly occur in the kidneys with ESRD. There were no significant differences in gender, age, clinical features, and imaging manifestations between multiple renal hemangiomas in ESRD and non-ESRD, but there were differences in extramedullary hematopoiesis.

Objective To construct a dual-phase integrated enhanced CT radiomics model for predicting PD-L1 expression in non-small cell lung cancer (NSCLC) patients. Methods A retrospective study was conducted on 150 NSCLC patients who were pathologically confirmed at the Affiliated Hospital of Jining Medical University from November 2019 to July 2023. These patients were randomly assigned to a training cohort (105 cases) and a testing cohort (45 cases) at a ratio of 7:3. Radiomics features were extracted from both the arterial and venous phases of CT images. Dimensionality reduction and key feature selection were performed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Eight machine learning algorithms, including logistic regression, were employed to construct radiomics models. The best predictive model was identified through ROC curve analysis, and a dual-phase integrated radiomics model was developed by combining radiomics features from both phases. Univariate and multivariate logistic regression analyses were conducted to evaluate clinical features and to identify independent predictors for constructing a clinical model. A Combine model was then established by integrating radiomics and clinical features. The performance of the models was assessed using ROC curves, and their clinical utility was evaluated using decision curve analysis. Results A total of 1835 radiomics features were extracted from both the arterial and venous phase CT images. After dimensionality reduction and selection, 9 radiomics features were ultimately chosen from each phase. Among the radiomics models, the logistic regression model exhibited higher predictive efficiency and robustness. The dual-phase integrated enhanced CT radiomics model demonstrated superior performance compared to single-phase models. The radiomics-clinical model showed the best discriminative ability, with AUC values of 0.822 in the training cohort and 0.681 in the testing cohort. Decision curve analysis indicated the best clinical effectiveness. Conclusion The diagnostic model combining radiomics and clinical features of NSCLC has a good ability to predict PD-L1 expression and can provide a non-invasive and effective diagnostic method for clinical practice.

Objective To explore the feasibility of applying dual-flow injection technique combined with 70 kV tube voltage scanning in head and neck computed tomography angiography (CTA). Methods A total of 160 patients who underwent head and neck CTA examinations at the Medical Imaging Center of Taihe Hospital in Shiyan City were prospectively collected from July to November 2024 and randomly categorized into three groups (A, B, C): group A (n=60) underwent 70 kV tube voltage scanning with dual-flow injection; group B (n=40) underwent 100 kV tube voltage scanning and dual-flow injection; group C (n=60) underwent 100 kV tube voltage scanning with conventional injection. For each group, the CT values, background noise (SD), contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of the aortic arch, common carotid artery, internal carotid artery, and D2 segment of middle cerebral artery were recorded. Additionally, the computed tomography dose index (CTDI) and dose length product (DLP) values of each patient were recorded; the subjective evaluation was performed by 2 senior physicians using double-blind scoring of all VR images. All data were statistically analyzed. Results group A showed significantly higher CT values in the aortic arch compared to group C (P0.05), while no significant differences were observed in the remaining vessel segments between group A and C (P0.05). In group A, the CT values of the aortic arch, bilateral common carotid arteries, bilateral internal carotid arteries, and bilateral middle cerebral arteries were all above 300 HU, meeting the diagnostic requirements. At the level of the bifurcation of the aortic arch, right common carotid artery, and the beginning of the right middle cerebral artery, the SNR and CNR values of group A were significantly lower than those of group C (P0.05), with no significant differences compared to group B (P0.05). The CTDI, DLP, and Effective dose(ED) values of group A were significantly lower than those of groups B and C, and the differences were statistically significant (P0.05). Specifically, compared to group C, group A showed a 77.41% reduction in CTDI, a 77.37% reduction in DLP, and a 77.78% reduction in ED. Additionally, the iodine contrast dose in group A was reduced by 40% compared to group C. Conclusion In head and neck CTA, the dual-flow injection technique combined with 70 kV low-tube-voltage scanning method can significantly reduce the radiation dose and pure iodine contrast agent usage without affecting the image quality and meeting the diagnostic requirements. The method is feasible in clinical examination.

Objective To evaluate the diagnostic efficacy and predictive value of CT imaging features in identifying gastrointestinal stromal tumors (GIST) with high Ki-67 proliferation index expression. Methods In this retrospective study, we analyzed clinical and imaging data from 638 pathologically confirmed GIST cases at Sir Run Run Shaw Hospital, Zhejiang University School of Medicine from January 2016 to December 2023. Patients were stratified into low-Ki-67 (n=539) and high-Ki-67 (n=99) groups based on postoperative immunohistochemical results. Potential associations between CT characteristics and Ki-67 status were initially screened through univariate analysis, followed by multivariate logistic regression to identify independent predictors. A composite predictive model was subsequently developed and evaluated using ROC curve analysis, with particular attention to the area under the curve (AUC), sensitivity, and specificity. Results Univariate analysis demonstrated significant correlations between high Ki-67 expression and multiple CT features including: tumor size, irregular shape, cystic changes, necrosis, surface ulceration, intratumoral hemorrhage, heterogeneous enhancement, and intratumoral neovascularization (P0.05). Multivariate logistic regression analysis established tumor size, surface ulceration, and intratumoral hemorrhage as independent predictive factors. The combined model incorporating these three features achieved an AUC of 0.750 (95% CI: 0.696-0.804), with sensitivity and specificity of 81.32% and 59.68%, respectively. Conclusion The combined evaluation of tumor size, surface ulceration, and intratumoral hemorrhage on CT imaging serves as an effective predictor of elevated Ki-67 expression in GIST patients. This imaging-based triage approach enables reliable identification of high Ki-67 cases.

Objective To compare the differences in image quality between adaptive statistical iterative reconstruction (ASiR) and model-based iterative reconstruction (MBIR) techniques in routine-dose abdominal thin-slice CT scanning. Methods Twenty patients admitted to the Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine from June to September 2024 who underwent CT scanning of the upper abdomen were selected to undergo conventional dose CT scanning of the abdomen using a GE Discovery CT 750HD, and the images were reconstructed with filtered back-projection reconstruction (FBP) and iterative reconstruction techniques after data acquisition,respectively, and the thickness of the reconstructed layer was set at 0.625 mm.The images were analysed and evaluated for parallel quality with the help of a post-processing platform. The images were analysed with the help of a post-processing platform for parallel quality evaluation,focusing on measuring and comparing the noise value (SD), contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of the liver, spleen and muscle in each reconstruction mode. The reconstructed images were subjectively judged by two senior radiologists in a double-blind manner. Results Focusing on the liver,the liver noise of FBP, 40% ASiR and VEO3.0-NR40 reconstructed images were 23.45±3.34, 16.93±2.53, 5.72±1.02, respectively, and the noise of the 40% ASiR and VEO3.0-NR40 reconstructed images were reduced by 27.8% and 75.6%, respectively, compared with that of FBP (P0.001); CNR of the liver in the 3 groups of images was 9.25±1.86, 12.54±2.52, 32.83±4.61, and SNR was 3.82±0.77, 5.13±0.95, 13.48±2.34, respectively. The CNR of the reconstructed images with 40% ASiR and VEO3.0-NR40 increased by 35.6% and 255.0% respectively compared with the FBP group, and the SNR increased by 34.3% and 252.9% respectively (P0.001). The subjective scores of the images in the 3 groups were 2.90±0.31, 3.77±0.43, 4.83±0.38, respectively. Conclusion At equivalent doses, 40% ASiR and VEO 3.0-NR40 effectively reduce noise in abdominal CT images, thereby enhancing image quality,outperforming the conventional FBP reconstruction algorithm. Among these, the VEO3.0-NR40 reconstruction algorithm demonstrated exceptional performance, significantly optimizing image details and reducing noise interference.

Objective To explore the application value of ¹⁸F-NaF PET/CT imaging technology in the assessment of carotid plaque vulnerability and risk stratification in diabetic patients. Methods A total of 59 diabetic patients (102 plaques) and 51 non-diabetic patients (83 plaques) with carotid atherosclerosis from Inner Mongolia Autonomous Region People's Hospital from January 2022 to December 2024 were included as the case group and the control group, respectively. The case group was stratified into high-risk (n=36), medium-risk (n=35), and stable groups (n=31) using the Triangle stratification model. The maximum standardized uptake value (SUV_max), mean standardized uptake value (SUV_mean), and target-to-background ratio (TBR) of the plaques were detected by PET/CT, and the differences among the groups and their correlations with risk stratification were compared. Results The SUV_max, SUV_mean, and TBR in the case group were higher than those in the control group (P0.05), and they showed a gradient increasing trend with the increase of risk stratification (P0.05). SUV_max, SUV_mean, and TBR were positively correlated with the risk stratification of diabetes (P0.05). Conclusion ¹⁸F-NaF PET/CT can effectively evaluate the vulnerability of carotid plaques in diabetic patients, and the degree is positively correlated with risk stratification, suggesting that early intervention should be strengthened for high-risk patients to prevent acute vascular events.

Objective To analyze the clinical characteristics of ovarian tumors during pregnancy and explore the diagnostic value of MRI examination in patients with ovarian tumors during pregnancy. Methods This retrospective study analyzed MRI findings and clinical data from 67 pregnant patients diagnosed with ovarian tumors during pregnancy confirmed by postoperative histopathology. Results A total of 82 ovarian tumors were identified in 67 patients, with 15 cases exhibiting bilateral involvement. Tumor diameters ranged from 2.0-34.7(9.3±4.9) cm. Histopathological subtypes included: 11 mature cystic teratomas, 11 mucinous cystadenomas, 10 serous cystadenomas, 9 endometriotic cysts, 7 luteinized cysts, 6 corpus luteum cysts, 3 simple cysts, 4 borderline tumors, 3 high-grade serous carcinomas, 1 sex cord-stromal tumor, 1 dysgerminoma, and 1 metastatic tumor. MRI demonstrated a diagnostic accuracy of 91.5%, with 7 cases misdiagnosed. Most ovarian tumors appeared as cystic or cystic-solid masses. Benign tumors predominantly presented as cystic lesions, whereas borderline and malignant tumors tended to show solid components. No statistically significant differences were observed between benign, borderline, and malignant tumor groups regarding tumor size, presence of pedicle torsion, or elevation of tumor markers (P0.05). In terms of clinical management and outcomes: 7 patients underwent pregnancy termination during the first trimester due to absence of fetal heart tones or lower abdominal pain; 22 patients with benign tumors underwent surgery during the second trimester, primarily via laparoscopy, due to abdominal pain or large tumor size; 30 patients with benign or borderline tumors were monitored via ultrasound and underwent tumor resection during term cesarean section. Among 6 patients with malignant tumors, 1 terminated the pregnancy due to fetal chromosomal abnormalities, 2 experienced preterm delivery following fetal lung maturation and subsequently underwent radical surgery, and 3 underwent fertility-sparing surgery during the second trimester. Overall, maternal and fetal outcomes were favorable. Conclusion Ovarian tumors during pregnancy are predominantly benign and asymptomatic. MRI is a valuable tool for the qualitative assessment of these tumors, supporting accurate diagnosis and informed clinical decision-making.

Objective To investigate the application value of cardiac magnetic resonance imaging with late gadolinium enhancement (CMR-LGE) in the diagnosis of dilated cardiomyopathy (DCM), and to compare the diagnostic results of CMR-LGE with those of echocardiogram (UCG). Methods A retrospective study was conducted on 36 patients diagnosed with DCM upon discharge from Anhui Second Provincial Hospital from January 2023 to March 2025. All patients underwent both CMR-LGE (observation group) and UCG (control group) examinations. Within the observation group, 29 patients were CMR-LGE positive for DCM (observation subgroup 1), and 7 were CMR-LGE negative (observation subgroup 2). Within the control group, 20 patients were UCG positive for DCM (control subgroup 1), and 16 were UCG negative (control subgroup 2). Differences in diagnostic results, CMR-derived parameters, and clinical specificity parameters were analyzed between the groups. Results CMR-LGE confirmed the diagnosis in 29 cases, which was significantly higher than the 20 cases diagnosed by UCG (P=0.014). In observation subgroup 1 (CMR-LGE positive), the left ventricular end-diastolic volume index, left ventricular end-systolic volume index, and myocardial mass index were significantly higher than those in observation subgroup 2 (CMR-LGE negative). Conversely, body surface area, left ventricular ejection fraction, and stroke volume index were significantly lower in observation subgroup 1 compared to observation subgroup 2 (P0.05). ROC curve analysis demonstrated that SVI had the highest diagnostic efficacy for DCM, with an AUC of 0.990. Conclusion CMR-LGE demonstrates higher sensitivity in diagnosing DCM compared to UCG. Its quantitative parameters provide valuable reference for clinical diagnosis and treatment.

Objective To evaluate the impact of hyperthyroidism on myocardial mechanics in hypertensive patients using two-dimensional speckle tracking imaging (2D-STI). Methods A retrospective analysis was conducted on 75 hypertensive patients who visited our hospital from April to December 2023. They were divided into two groups based on the presence of comorbid hyperthyroidism: hypertension-only group (n=38) and the hypertension with hyperthyroidism group (n=37). Additionally, 32 healthy volunteers were selected as the control group. All participants underwent 2D-STI to measure left ventricular global longitudinal strain across three myocardial layers: GLS-endo, GLS-mid and GLS-epi.Strain parameters were compared among groups. Results The longitudinal strain in each layer of the hypertension with hyperthyroidism group was significantly lower than that in the hypertension-only group and the control group (-18.29±2.40 vs -19.68±2.10 vs -22.60±2.38, -16.60±2.55 vs -18.01±2.12 vs -22.09±2.72, -15.60±2.33 vs -16.78±2.28 vs -20.54±1.42, P<0.05). Notably, the reduction in GLS-endo was more pronounced than that in GLS-mid and GLS-epi (-18.29±2.40 vs -16.60±2.55 vs -15.60±2.33, P<0.05). Conclusion This study utilized two-dimensional speckle tracking imaging to stratify and quantify myocardial strain parameters,revealing a transmural gradient injury from the endocardial layer through the myocardial layer to the epicardial layer in the left ventricle of hypertensive patients with hyperthyroidism. These findings provide sensitive imaging evidence for the early identification of subclinical cardiac dysfunction and suggest that clinicians should pay special attention to hypertensive patients with concurrent hyperthyroidism.

Objective To evaluate the impact of hyperthyroidism on myocardial mechanics in hypertensive patients using two-dimensional speckle tracking imaging (2D-STI). Methods A retrospective analysis was conducted on 75 hypertensive patients who visited our hospital from April to December 2023. They were divided into two groups based on the presence of comorbid hyperthyroidism: hypertension-only group (n=38) and the hypertension with hyperthyroidism group (n=37). Additionally, 32 healthy volunteers were selected as the control group. All participants underwent 2D-STI to measure left ventricular global longitudinal strain across three myocardial layers: GLS-endo, GLS-mid and GLS-epi.Strain parameters were compared among groups. Results The longitudinal strain in each layer of the hypertension with hyperthyroidism group was significantly lower than that in the hypertension-only group and the control group (-18.29±2.40 vs -19.68±2.10 vs -22.60±2.38, -16.60±2.55 vs -18.01±2.12 vs -22.09±2.72, -15.60±2.33 vs -16.78±2.28 vs -20.54±1.42, P0.05). Notably, the reduction in GLS-endo was more pronounced than that in GLS-mid and GLS-epi (-18.29±2.40 vs -16.60±2.55 vs -15.60±2.33, P0.05). Conclusion This study utilized two-dimensional speckle tracking imaging to stratify and quantify myocardial strain parameters,revealing a transmural gradient injury from the endocardial layer through the myocardial layer to the epicardial layer in the left ventricle of hypertensive patients with hyperthyroidism. These findings provide sensitive imaging evidence for the early identification of subclinical cardiac dysfunction and suggest that clinicians should pay special attention to hypertensive patients with concurrent hyperthyroidism.

Objective To investigate the diagnostic efficacy of preoperative MRI features combined with serum inflammatory factors in predicting the pathological grading of breast invasive ductal carcinoma. Methods A retrospective analysis was conducted on 127 patients diagnosed with breast invasive ductal carcinoma at Yancheng First People's Hospital from December 2021 to March 2024. Based on pathological grading, the cohort was stratified into a low-grade group (n=76) and a high-grade group (n=51). Patients underwent preoperative MRI and blood routine examinations. Clinical indicators including age, lymphocyte, monocyte, neutrophil and platelet counts were collected, and derived indicators neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR) and systemic immune-inflammation index (SII) were calculated. Radiological features included maximum tumor diameter, tumor morphology, location, quadrant, parenchymal enhancement characteristics, MRI-reported axillary lymph node status, time-signal intensity curve type, and BI-RADS classification. The differences in clinical and radiological features between the two groups were compared, and Spearman correlation were used to analyze the correlation between clinical-radiological features and pathological grading of breast cancer. Results There were statistically significant differences in NLR, SII, maximum tumor diameter and BI-RADS classification between the low and high grade groups(P0.05), and all of them were positively correlated with pathological grading(P0.05). Among them, SII had the highest diagnostic efficacy in predicting the pathological grading of breast cancer, with an AUC of 0.663. The diagnostic efficacy was improved by combining the four features, with an AUC of 0.750. Conclusion The combination of MRI features and serum inflammatory factors has clinical value in predicting the pathological grading of breast cancer.

Objective To explore the predictive value of head CT combined with platelet-to-lymphocyte ratio (PLR) and D-dimer (D-D) for rehabilitation effects of Brunnstrom stage-based functional training in stroke patients during convalescence. Methods A total of 126 stroke patients in convalescence who received Brunnstrom stage-based functional training in Zhejiang Rehabilitation Hospital from January 2023 to December 2024 were selected. After one month of treatment, the Fugl-Meyer Assessment (FMA) was used to evaluate rehabilitation effects, and patients were divided into the good effect group and the poor effect group. Head CT findings, PLR, and D-D level before rehabilitation training were compared between the two groups. The ROC curve was used to evaluate the predictive value of head CT combined with PLR and D-D for rehabilitation effects of Brunnstrom stage-based functional training in stroke patients during convalescence. Results Among the 126 stroke patients in convalescence, 79 (62.70%) showed good rehabilitation effects, with a FMA score of 49.91±1.02. 47 (37.30%) showed poor rehabilitation effects, with a FMA score of 43.57±1.13. The proportion of abnormal head CT findings, PLR, and D-D level in the poor effect group were higher than those in the good effect group (P0.05). Multivariate logistic regression analysis revealed that head CT findings, PLR, and D-D were independent factors influencing rehabilitation effects of Brunnstrom stage-based functional training in stroke patients during convalescence (P0.05). ROC curve analysis showed that the optimal cutoff values of PLR and D-D for predicting rehabilitation effects of Brunnstrom stage-based functional training in stroke patients during convalescence were 150.09 and 208.85 ng/mL, respectively. The AUC and specificity of combination of head CT, PLR and D-D for predicting rehabilitation effects of Brunnstrom stage-based functional training in stroke patients during convalescence were 0.822 and 89.87%, which were higher than those of any single indicator (P0.05). Conclusion Head CT findings, PLR, and D-D level are independent factors influencing rehabilitation effects of Brunnstrom stage-based functional training in stroke patients during convalescence. In addition, combined use of head CT, PLR and D-D can enhance the prediction of rehabilitation effects of Brunnstrom stage-based functional training in stroke patients during convalescence.

Objective To construct a machine learning model using multimodal MRI radiomics features and clinical characteristics to predict lymph node metastasis in rectal cancer patients. Methods A retrospective analysis was conducted on clinical data and MRI images of 223 rectal cancer patients treated at Shunde Hospital of Southern Medical University from May 2018 to May 2023. Tumor regions were delineated using 3D Slicer software, and radiomics features were extracted using PyRadiomics software. Univariate logistic regression and LASSO regression were used to screen features, and clinical, radiomics, and clinico-radiomics models were constructed and evaluated in the training cohort (n=157) and validation cohort (n=66) to evaluate their predictive performance for lymph node metastasis. Results In the training cohort, the AUC values for the clinical, radiomics, and clinico-radiomics models were 0.668, 0.725, and 0.771, respectively. The radiomics model and clinico-radiomics model demonstrated good predictive performance in the validation cohort, with the radiomics model achieving an AUC of 0.780. Conclusion Machine learning models based on MRI radiomics and clinical features can effectively predict lymph node metastasis in rectal cancer. Radiomics features provide high predictive value, while clinical features offer limited predictive value.

Objective To elucidate the molecular pathogenic mechanism by analyzing the clinical phenotype and genetic mutations in a family with trichothiohepatoenteric syndrome (THNS) from Guangxi, China, and to provide a basis for genetic counseling for the family. Methods Clinical phenotype analysis was performed on the patient at the Guangxi Maternal and Child Health Hospital. Peripheral blood was collected and sent to Beijing Quanpu Medical Laboratory for DNA extraction and exome sequencing to screen for genetic mutations. Family analysis was performed, and peripheral blood samples were collected from family members. Sanger sequencing verification was performed at Sangon Biotech. The following functional experiments were conducted in the Medical Genetics Laboratory of Southern Medical University: Using the pEGFP-C1 vector and restriction enzymes EcoRI and BamHI, wild-type plasmids containing CCDC47 and mutant plasmids containing the CCDC47 c.634CT (p.Arg212*) variant were constructed. The constructed plasmids were transfected into HEK293T cells using the lipofection method. Quantitative real-time PCR and Western blotting were used to analyze mRNA and protein expression of the mutant CCDC47 gene. Immunofluorescence was employed to investigate the changes in the subcellular localization of the mutant protein, and the I-TASSER tool were used to predict alterations in the protein's tertiary structure. Results A homozygous mutation (c.634CT, p.Arg212*) in exon 5 of the CCDC47 gene was identified in the proband, Both parents and two elder sisters were heterozygous carriers of this mutation. Compared to the wild-type, the mutant CCDC47 protein showed no significant difference in subcellular localization but exhibited markedly reduced mRNA and protein expression, along with significant structural changes in its three-dimensional conformation. Conclusion This study reports a novel CCDC47 mutation (c.634CT, p.Arg212*) causing THNS, likely due to the substantial structural alteration and decreased expression of the mutant protein. The findings expand the mutational spectrum of the CCDC47 gene and provide critical insights for the early diagnosis of THNS and genetic counseling for the affected family.

Objective To explore the diagnostic value of multi-slice spiral CT (MSCT) combined with platelet parameters [platelet count (PLT), mean platelet volume (MPV)] on different pathological types of acute appendicitis (AA). Methods A total of 135 AA patients who were treated in the hospital from January 2022 to December 2024 were retrospectively selected and divided into simple AA group (n=25), suppurative AA group (n=100) and gangrenous AA group (n=10) according to the pathological results. All patients received preoperative MSCT examination, PLT detection and MPV detection after admission. The imaging differences and diagnostic value of MSCT combined with PLT and MPV on different pathological types of AA were analyzed. Results There were no significant differences in MSCT signs such as fecal impaction, cecal end wall thickening and local lymph node enlargement among different pathological types of AA (P0.05). The appendix diameter and appendix wall thickness in the gangrenous AA group were successively higher than those in the suppurative AA group and the simple AA group (P0.05). Compared with the suppurative AA group and the simple AA group, the proportion of pneumatosis outside the appendix wall was higher in the gangrenous AA group, and compared with the simple AA group, the proportion of effusion around the appendix was higher in the suppurative AA group and the gangrenous AA group (P0.05). The PLT in the suppurative AA group and the gangrenous AA group was higher while the MPV was lower compared to the simple AA group (P0.05). The areas under the curves of MSCT sign fitting model, platelet parameter fitting model and combined fitting model in the diagnosis of different pathological types of AA were 0.860 (95% CI 0.766-0.954), 0.817 (95% CI 0.699-0.935) and 0.920 (95% CI 0.848-0.992) respectively. Conclusion AA has typical MSCT signs, such as enlarged appendix diameter and appendix wall thickness, pneumatosis outside the appendix wall, and effusion around the appendix. In addition, MSCT signs combined with PLT and MPV can provide a comprehensive judgment regimen for differentiating different pathological types of AA.

With the acceleration of global population aging, sarcopenia has developed into a significant public health problem that seriously affects the health and quality of life of the elderly. The refined application of MRI provides a new perspective to reveal the microscopic pathological changes in the muscle. Advanced MRI techniques, including Dixon imaging, DTI, T2-mapping, and MRS, enable the quantitative assessment of critical parameters such as intramuscular fat infiltration, fibrosis, and energy metabolism. These methodologies provide a robust theoretical foundation for the early diagnosis, mechanistic analysis, and intervention strategies for sarcopenia. Moreover, sleep and physical activity serve as fundamental pillars for skeletal muscle recovery, repair and growth, promoting anabolic hormone secretion, optimizing protein synthesis conditions, inhibiting catabolic processes, and reducing inflammation. Consequently, by elucidating the intrinsic relationship between sleep, physical activity, and muscle health, and integrating MRI as a non-invasive and quantitative assessment tool for muscle mass, composition and structural changes, this paper establishes a rigorous scientific basis for the early detection, risk stratification, and personalized management of sarcopenia.

Vascular cognitive impairment (VCI) is a clinical syndrome characterized by cognitive impairment in at least one domain, caused by cerebrovascular lesions and their risk factors, with an increasing incidence among middle-aged and elderly populations. In recent years, advancements in MRI have provided new methods for the study of VCI. Among these, diffusion tensor imaging, which is currently the only non-invasive technique that allows visualization of the arrangement of white matter fiber tracts in living brains, has unique advantages in VCI research. This article will review the concept of diffusion tensor imaging and its various applications in VCI, including white matter lesions, diagnosis and classification, risk factor identification, and prevention and treatment, while also discussing its limitations and prospects for future development. This aims to provide new insights for the clinical diagnosis and pathological research of neurological diseases.