This review summarized the progress of clinical research on liver disease ultrasound in China in 2024, covering multiple fields, including precise diagnosis of focal liver lesions, prediction of biological characteristics of hepatocellular carcinoma (HCC), evaluation of therapeutic efficacy and prognosis, quantitative diagnosis of metabolic-associated fatty liver disease (MAFLD), and interventional ultrasound treatment. In the field of liver tumor diagnosis, the application scope of the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) has been further expanded, with significant improvement in diagnostic performance. The integration of artificial intelligence and multimodal data has played an important role in predicting the biological characteristics of HCC, enhancing the stability and generalizability of predictions. Ultrasound technology combined with multimodal models has shown significant advantages in evaluating the efficacy and prognosis of liver tumors. Additionally, ultrasound fat quantification techniques have achieved important breakthroughs in the diagnosis of MAFLD, transitioning from single-center to multi-center validation. In interventional ultrasound research, the application of irreversible electroporation and artificial intelligence-assisted navigation systems has significantly improved the precision and safety of interventional treatments. Overall, the research on liver ultrasound in China in 2024 has actively explored the application of artificial intelligence and multimodal data integration, significantly improving the accuracy and efficiency of liver disease diagnosis and treatment evaluation. Significant progress has been made in the directions of multi-center validation and precision medicine, providing new ideas and strategies for clinical practice.

Objective: Based on magnetic resonance imaging of patients with brain metastases, using imaging omics methods to differentiate the primary lesion of brain metastases and determine the specific source of the patient’s brain metastases. Methods: The data of this study were collected from patients with brain metastasis who treated in Liaoning Cancer Hospital from January 2017 to September 2020. Experienced imaging doctors manually delineate the active area of the patient’s brain metastasis tumor, and obtain a 4 mm circular area containing the active area and the surrounding area through computer methods. And 1 967 imaging omics features were extracted from each region of the contrast-enhanced T1-weighted imaging (CE-T1WI) and T2-weighted imaging (T2WI) sequences. After merging the sequences, a three-step feature screening method was performed using U-test, least absolute shrinkage and selection operator (LASSO) logistic regression, and Akaike information criterion (AIC), draw the receive operating characteristic (ROC) curve to calculate the area under curve (AUC) value as an indicator of the classification performance of the discriminative model. Results: A total of 215 patients with brain metastases were identified, including 100 cases of lung origin, 50 cases of breast origin, 50 cases of gastrointestinal origin, and 15 cases of other origin. From each of the two sequences, 1 967 imaging histological features were extracted. Three radiomics models were successfully constructed to differentiate whether brain metastases arose from lung cancer lesions in the RS_Lung model, breast cancer lesions in the RS_breast model and gastrointestinal cancer lesions in the RS_Gastrointestic model, with training set AUC of 0.898, 0.872 and 0.938, sensitivity of 0.908, 0.744 and 0.860, specificity of 0.818, 0.879 and 0.909, respectively. Conclusion: This study achieved good results in the distinguishing task derived from brain metastases using an imaging omics model constructed based on a 4 mm annular region, which has the potential to be a noninvasive preoperative new marker and guide personalized treatment options for patients with brain metastases.

Objective: To explore the potential value of multiparametric magnetic resonance imaging (mpMRI) radiomics combined with machine learning models in predicting sentinel lymph node (SLN) metastasis in breast cancer. Methods: A retrospective analysis of imaging and clinical data from pathologically confirmed breast cancer patients was conducted, and the patients were divided into training and validation groups in a 7∶3 ratio. Radiomics features were extracted from T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and the second phase of dynamic contrast-enhanced MRI (DCE-MRI), including the whole tumor (ROI_Whole) and subregions (ROI_Sub). Multiple machine learning models were constructed by integrating clinical, pathological, and imaging features, and their predictive performance was evaluated using receiver operating characteristic (ROC) curves, decision curve analysis, and calibration curves. Results: This study analyzed 193 breast cancer patients, including 80 SLN-positive and 113 SLN-negative cases. Univariate and multivariate logistic regression analyses were performed on clinical, imaging, and pathological data to identify independent risk factors associated with SLN metastasis. Finally, it is analyzed that，peritumoral edema and lymphovascular invasion (LVI) showed significant differences between SLN-positive and SLN-negative groups (P<0.01), with LVI identified as an independent predictive factor (P<0.05). The MLP model, incorporating radiomics features from T2WI, ADC, ROI-Whole, ROI-Sub, and LVI, demonstrated the best performance, with an AUC of 0.947 in the training set and 0.932 in the validation set. Conclusion: The radiomics model based on breast mpMRI effectively predicts SLN metastasis in breast cancer preoperatively.

Objective: To investigate the value of quantitative parameters of dual-energy computed tomography (DECT) in the differential diagnosis of parotid gland tumors. Methods: The imaging data of patients with parotid gland tumors who attended the Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine from March 2023 to July 2024 were reviewed and analyzed. Virtual non-contrast CT value (VNC), iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number (Z_eff), electron density (Rho), virtual monochromatic CT values of 40-100 keV (interval of 20 keV) and slope of spectral curve (K) of enhanced phase were measured. The differences of quantitative parameters between benign parotid gland tumors and malignant parotid gland tumors, as well as between different pathological types of parotid gland tumors were compared. Univariate and multivariate logistic regression analysis was performed to screen for independent predictors among groups, and receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of quantitative parameters. Results: The DECT images of 72 parotid gland tumors in 71 cases were retrospectively analyzed. There were 58 cases of benign parotid gland tumors, including 33 pleomorphic adenomas in 33 cases, 26 Warthin tumors in 25 cases, and 13 malignant parotid gland tumors. There were no significant differences in any parameters between benign and malignant tumor groups (all P>0.05). Compared with Warthin tumors, pleomorphic adenomas had significantly lower K (0.87±0.50), VNC (27.28 HU±8.03 HU), IC (1.00 mg/mL±0.08 mg/mL), NIC (11.32%±5.64%), Z_eff (7.91±0.31), Rho (33.27±5.99), and virtual monochromatic CT values of 40-100 keV (91.39 HU±36.05 HU, 57.81 HU±17.48 HU, 44.96 HU±10.95 HU, and 39.31 HU±8.50 HU, respectively) (all P<0.05). Among these, Rho was an independent predictor for differentiating between the two, with an AUC of 0.978. VNC (37.17 HU±9.86 HU), Rho (42.89±6.64), and monochromatic CT values of 100 keV (50.34 HU±7.33 HU) in the malignant tumor group were significantly higher than those in the pleomorphic adenoma group (P<0.05). Rho was an independent predictor for differentiating between the two, with an AUC of 0.858. Compared with Warthin tumors, malignant tumors had significantly lower K (1.00±0.58), IC (1.05 mg/mL±0.18 mg/mL), NIC (13.00%±9.98%), Z_eff (7.89±0.34), and monochromatic CT values of 40-100 keV (110.46 HU±39.64 HU, 71.71 HU±17.85 HU, 56.87 HU±10.14 HU, 50.34 HU±7.33 HU, respectively) (all P<0.05). And the monochromatic CT value of 100 keV was an independent predictor for differentiating between the two, with an AUC of 0.852. Conclusion: DECT can provide reliable quantitative indicators for the differentiation of parotid gland tumors, possessing significant clinical application value.

Objective: To evaluate the diagnostic efficacy of the LR-M criteria in the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) classification system for distinguishing intrahepatic cholangiocarcinoma (ICC) from poorly differentiated hepatocellular carcinoma (HCC). Methods: A retrospective analysis was conducted on pathologically confirmed ICC patients and poorly differentiated HCC patients who underwent CEUS prior to treatment between January 2019 and December 2023. The conventional ultrasound features, CEUS characteristics, and CEUS LI-RADS classifications of the two groups were compared. Lesions were stratified into three subgroups based on maximum diameter: ≤5 cm, 5-10 cm, and >10 cm, and the diagnostic performance of the LR-M category in CEUS LI-RADS was analyzed within these subgroups. CEUS LI-RADS categories were assigned according to CEUS LI-RADS version 2017. Receiver operating characteristic curves were used to assess the diagnostic performance of LR-M. Results: A total of 50 patients with ICC and 50 patients with poorly differentiated HCC were included. Lesions were located in the left liver in 24 (48.0%) ICC patients and 10 (20.0%) poorly differentiated HCC patients (P=0.003). Biliary dilatation or biliary stones were observed in 23 (46.0%) ICC patients and 1 (2.0%) poorly differentiated HCC patient (P<0.001). In the arterial phase, 31 (62.0%) ICC patients and 1 (2.0%) poorly differentiated HCC patient exhibited typical peripheral, irregular rim-like enhancement (P<0.001). Significant washout was observed in 34 (68.0%) ICC patients and 3 (6.0%) poorly differentiated HCC patients in the portal or delayed phase (P<0.001). The mean washout time was 34.45 s for ICC and 74.08 s for poorly differentiated HCC (P<0.001). The overall area under curve (AUC), sensitivity, and specificity of LR-M were 0.730, 94.00%, and 52.00%, respectively. In the ≤5 cm, 5-10 cm, and >10 cm subgroups, the AUC values were 0.746, 0.667, and 0.833, respectively. Conclusion: The LR-M classification demonstrates high sensitivity in identifying ICC, but its specificity requires improvement. The accuracy of LR-M classification significantly increases when the lesion size exceeds 10 cm. The specificity of LR-M for distinguishing ICC from poorly differentiated HCC is significantly improved when the lesion size is ≤5 cm or >10 cm.

Objective: To explore the clinical and imaging features of diffuse high-grade gliomas in the brainstem of children based on multi parameter sequences, so as to improve the comprehensive understanding of the disease. Methods: The clinical and imaging data of pediatric brain stem diffuse high-grade gliomas confirmed by pathology from January 2022 to January 2024 were retrospectively analyzed. Results: A total of 45 children in Xinhua Hospital, Shanghai Jiao Tong University School of Medicine with diffuse high-grade gliomas in the brainstem (19 males and 26 females, aged 6.48±2.34 years) were included in this study. Among them, 4.4% (2/45) had cerebrospinal fluid dissemination, while the rest had localized or nearby infiltration and growth in the brainstem. 45 cases underwent computed tomography (CT) plain scan+ magnetic resonance imaging (MRI) plain scan/enhanced scan+diffusion-weighted imaging (DWI) basic scan, 6 cases underwent CT perfusion imaging (CTP) scan simultaneously, 8 cases underwent magnetic resonance spectroscopy (MRS) scan simultaneously, 7 cases underwent diffusion tensor imaging (DTI) scan simultaneously, and 2 cases underwent susceptibility weighted imaging (SWI) scan simultaneously. All 45 cases had endogenous swelling growth, including 36 cases with uniform swelling growth on both sides and 9 cases with lateral swelling growth (7 cases crossed the midline during the growth process, and 2 cases with diffuse growth on one side of the head and tail); 28.9% (13/45) limited brainstem growth, 2.2% (1/45) limited medullary growth, 68.9% (31/45) grew towards the head and tail (midbrain/thalamus/medulla oblongata, 21/31, 67.7%) and laterally (pons/cerebellum, 10/31, 32.3%), and 26.7% (12/45) progressed to exogeneity (including 11 cases involving the basilar artery, 11/12, 91.7%). The CT plain scan sequence showed low-density thickening shadows in the brainstem area, with a density lower than that of the normal brainstem (P<0.001). CT perfusion sequence scan showed a decrease in cerebral blood flow (CBF) in the tumor area of 83.3% (5/6) of patients (1 case showed a significantly lower than average level in the tumor center area), and 1 case showed an increase. Bilateral cerebral hemisphere perfusion abnormalities, with delayed peak time, mainly around the lateral ventricles. The MRI structural sequence showed that 8.9% (4/45) of the tumor solid components on T1-weighted imaging (T1WI) showed equal signal intensity, 11.1% (5/45) showed low signal intensity, and 80.0% showed mixed signal intensity (36/45). The T2-fluid suppressed inversion recovery (FLAIR) sequence showed slightly high to high signal intensity, and the pattern after T1WI enhancement showed diverse changes. Six cases did not show enhancement, while the rest showed varying degrees of mild to moderate enhancement. 28.2% (11/39) showed local circular enhancement, 38.5% (15/39) showed local nodular enhancement, 10.3% (4/39) showed patchy enhancement, and 23.1% (9/39) showed patchy enhancement. Manifested as gravel like enhancement, 7.7% (3/39) showed mixed mode enhancement, and some patients with unclear T1WI enhancement had better T2-FLAIR enhancement sequence contrast. In the MRI functional sequence, MRS showed varying degrees of increase in Cho peak and decrease in NAA peak, with one case showing a significant inversion of Lac peak; DTI scan showed that the nerve fiber bundles in the lesion area were pushed to the periphery by the tumor, with 5 cases showing partial interruption of the fiber bundles and 1 case only showing compression and pushing of the fiber bundles. Local low signal can be seen on the SWI phase map, indicating intratumoral microbleeds. Conclusion: The conventional CT findings of diffuse high-grade gliomas in the brain stem of children are low-density brain stem thickening, and quantification is helpful for early detection and prevention of missed diagnosis. The growth mainly occurred in the diffuse endogenetic pontine, and most of them infiltrated and grew to other brain regions along the direction of nerve fiber bundles, pushing or destroying the nearby fiber bundles. The enhancement patterns were various, and most of them were scattered mild to moderate enhancement. There may be cystic image signals inside, which may be related to the reduction of necrosis by local perfusion and absorption after microbleeds;

Objective: To explore the clinical application value of the contrast-enhanced ultrasound (CEUS) scoring method in reclassifying Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions. Methods: The data of patients with breast nodules diagnosed by postoperative pathology or puncture biopsy in Shanghai Yangpu District Shidong Hospital and Shanghai Fourth People’s Hospital from May 2021 to April 2024 were retrospectively analyzed. All nodules underwent routine ultrasound examination and were indicated as BI-RADS category 4. Each nodule underwent CEUS and was assigned a score. The BI-RADS classification was adjusted according to the score results, and the diagnostic efficiency before and after adjustment was compared. In addition, breast nodules were divided into 3 groups according to the maximum diameter, and the diagnostic efficacy of CEUS scoring was evaluated for nodules of different sizes. Results: A total of 105 patients with 109 nodules were included, comprising 59 benign nodules and 50 malignant nodules. BI-RADS 4b and above were considered as malignant, and the sensitivity and accuracy of diagnosis combined with CEUS scoring method (94.00% and 92.66%) were significantly higher than those of conventional ultrasound (52.00% and 75.23%, P<0.05). The area under the receiver operating characteristic (ROC) curve after adjustment was 0.95, significantly higher than that of conventional ultrasound (0.76). After integrating the CEUS scoring method, the diagnostic sensitivity significantly improved across all three groups of breast nodules stratified by size (P<0.05). The diagnostic accuracy in all three groups increased to over 90%, with the most notable improvement observed in the ≥2 cm group (65.38% vs 96.15%, P< 0.05). Conclusion: The CEUS scoring method has high diagnostic efficiency and is valuable for the readjustment of BI-RADS category 4 nodules, and has extensive clinical application value.

Objective: To explore the value of multimodal ultrasound imaging in predicting central lymph node metastasis of papillary carcinoma of the thyroid (PTC). Methods: Patients with PTC confirmed by operation and pathology were selected in The First People’s Hospital of Foshan from March 2022 to February 2024. The patients were examined by conventional ultrasound, shear wave elastography (SWE) and superb microvascular imaging (SMI) before surgery. Conventional ultrasound was used to evaluate lesion maximum diameter, location, shape, internal parenchymal echo, microcalcification, the ratio of longitudinal and transverse diameter, capsule continuity. SWE was used to measure the mean of Young’s modulus (E_mean). SMI was used to measure vascular index (VI). Single-factor and multi-factor logistic regression analysis were used to analyze the risk factors of the central lymph node metastasis in PTC patients. Results: A total of 110 patients included 52 patients with central lymph node metastasis (metastatic group) and 58 patients without central lymph node metastasis (non-metastatic group). There were significant differences in age, maximum diameter, shape, parenchymal echo, microcalcification, capsule continuity, E_mean and VI between the two groups (all P<0.05). Multi-factor logistic regression analysis showed that age, maximum diameter, parenchymal echo and E_mean were the independent risk factors of central lymph node metastasis (all P<0.05). Conclusion: Multimodal ultrasound has a certain value in predicting the central lymph node metastasis of PTC.

The Chinese Anti-Cancer Association Society of Integrative Cardio-oncology, the Ultrasound Branch of the Chinese Medical Association, and the Chinese Society of Echocardiography convened experts formulated the Chinese guideline for the clinical application of noninvasive imaging technology in accessing cancer therapy-related cardiovascular toxicity (2023 edition). The guideline highlighted that cancer therapy-related cardiovascular toxicity (CTR-CVT) has become one of the major threats to the survival of cancer patients. Non-invasive imaging technologies play crucial roles in the risk stratification, early diagnosis, monitoring and follow-up of CTR-CVT. This article provided an interpretation of the non-invasive imaging examination methods and monitoring strategies for common CTR-CVT as proposed in the guideline, offering practical and effective guidance for the clinical management of CTR-CVT.

Objective: To evaluate and compare the diagnostic value of contrast-enhanced ultrasound (CEUS), ultrasound-guided fine-needle aspiration biopsy (US-FNAB), and the combination of the two in the diagnosis of Thyroid Imaging Reporting and Data System (TI-RADS) 4 nodules of the thyroid gland. Methods: Patients with TI-RADS 4 thyroid nodules having clear pathological findings from February 2019 to November 2023 in Tangshan Central Hospital and Tangshan Gongren Hospital were retrospectively analyzed. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of CEUS, US-FNAB, and the combination of the two methods were calculated by using postoperative pathology as a criterion, and the diagnostic efficacy of CEUS, US-FNAB and their combination was compared by drawing the receiver operating characteristic (ROC) curve. Results: In the differential diagnosis of seventy-five patients benign and malignant thyroid TI-RADS 4 nodules, the diagnostic sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of CEUS were 70.7%, 70.6%, 70.6%, 74.4%, and 66.7%, respectively, and of US-FNAB were 75.6%, 79.4%, 77.3%, 81.6% and 73.0%, respectively, and the combination of the two were 97.6%, 58.8%, 80.0%, 74.1%, and 95.2%, respectively. The false-positive rates of CEUS, US-FNAB, and the combination of the two were 29.3%, 24.4%, and 2.4%, respectively. The false-negative rates of CEUS, US-FNAB and the combination of the two were 29.4%, 20.6% and 41.2%, respectively. The AUC of CEUS, US-FNAB and the combination of the two applied diagnostics were 0.707, 0.775, and 0.782, respectively, as derived from plotting the ROC curve. Conclusion: Both CEUS and US-FNAB have a certain value in the differential diagnosis of benign and malignant thyroid TI-RADS 4 nodules, and their diagnostic value can be improved when they are combined, which can be combined when it is difficult to distinguish between benign and malignant in the clinical situation.

Objective: To investigate the feasibility of fusion registration of high-frequency ultrasound (HFUS)-pathology images and predictive value of model for predicting the pathological tissue components in in vitro models based on deep learning (DL) networks. Methods: Sixty in vitro mimetic tumor models containing four different biological tissues and localized particles were prepared. HFUS images and wide slide images (WSI) of the same slide were obtained under physical registration. The obtained images were quality controlled and selected, and the region of interest (ROI) was manually outlined along the edges of the tissues in the WSI and then transferred to HFUS images. The datasets were consisted of original images and corresponding ROIs and were divided into the training set (n=462), validation set (n=34) and testing set (n=38) at the ratio of 13∶1∶1. DL models were developed via transfer learning DeepLabV3, FCN-50 and MobileNetV3 networks. The pixel accuracy (PA), precision, recall and F1-score were used to quantify and compare the performance of each model in the training and testing datasets. The automatically segmented images were output. Results: The DL models based on DeepLabV3, FCN-50 and MobileNetV3 networks had high accuracy and similarity for automatically segmentation of different tissue components in the testing set, and the MobileNetV3 model outperformed others with the PA of 91.4% and F1-score of 87.1%. There was no significant difference between performance of models (all P> 0.05). There were statistically significant differences between the efficiencies of models for predicting different in vitro biological tissue components (all P<0.001), with the best of liver tissue. Conclusion: The constructed ultrasound-pathology fusion models in this study can effectively recognize the in vitro tissue components in ultrasound images and provide the methodological basis for further clinical applications.

In the contemporary medical field, the incidence of cancer is on the rise, and cancer therapy - related cardiovascular toxicity (CTR-CVT) has become a crucial issue that cannot be overlooked, having a significant impact on the prognosis of patients. With the increasing diversification and sophistication of cancer treatment methods, including chemotherapy, radiotherapy, targeted therapy, and immunotherapy, while these offer hope for anti-tumor treatment to patients, they also carry the potential risk of cardiovascular toxicity, affecting treatment effectiveness and patients’ quality of life. Therefore, it is of particular importance to accurately and comprehensively assess CTR-CVT. This article evaluated cardiovascular toxicity from multiple dimensions such as clinical manifestations, electrocardiogram, imaging, and biomarkers, aiming to provide precise and practical assessment strategies for clinical practice. These strategies are intended to balance the efficacy of cancer treatment and cardiac safety, improve patients’ quality of life, optimize long-term outcomes, and enhance patients’ living standards.

Objective: To investigate the value of multiple radiomics models constructed by combining clinical risk factors and multiparametric magnetic resonance imaging (MRI) radiomics features to predict microsatellite instability (MSI) in rectal cancer. Methods: A total of 149 rectal cancer patients were included in the First Affiliated Hospital of Bengbu Medical University from December 2020 to November 2023, including 34 patients with MSI and 115 patients with microsatellite stability (MSS). Based on MRI examination of multiple sequence images, 3D regions of interest were delineated, radiomics features were extracted and dimensionality was reduced to select the best features. Then, five different machine learning algorithms, including logistic regression (LR), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and naive Bayes tree (NBT) were used to construct different imaging radiomics models using the optimal radiomics features. And receiver operating characteristic (ROC) curves were drew to evaluate the diagnostic performance of different models. Results: The RF model showed the most stable performance, and the clinical imaging radiomics joint model nomogram based on clinical independent risk factors and imaging radiomics showed high diagnostic efficiency for MSI in rectal cancer. The area under curve (AUC) of the training group and the validation group were 0.923 and 0.914, respectively, indicating the most significant evaluation of MSI in rectal cancer. Conclusion: Combining different machine learning algorithms, a clinical imaging radiomics nomogram constructed from clinical risk factors and multi-parameter MRI radiomics features can effectively predict the unstable state of preoperative rectal cancer.

Objective: To investigate the predictive value of a scoring model based on conventional ultrasound combined with clinicopathological features for pathologic complete response (pCR) in human epidermal growth factor receptor 2 (HER2) positive breast cancer after neoadjuvant chemotherapy (NAC). Methods: A retrospective analysis was performed in patients who confirmed as HER2 positive breast cancer by ultrasound-guided coarse needle biopsies and followed by eight cycles of NAC from January 2022 to August 2023 in The First Affiliated Hospital of Nanjing Medical University. According to the Miller-Payne grading system, the patients were divided into pathological complete response (pCR) group and non-pathological complete response (non-pCR) group. The differences of clinical and pathological data and ultrasound imaging features between the two groups were analyzed by t test or χ²/Fisher test. Multivariate regression analysis was used to determine the independent predictors of pCR in HER2 positive breast cancer, and a nomogram was established to visualize the predictive efficacy of related factors for pCR. Results: A total of 103 patients were included, 51 in the pCR group and 52 in the non-pCR group. Univariate analysis revealed significant differences between pCR and non-pCR groups regarding tumor molecular classification (χ²=12.266, P<0.001), as well as the ultrasound features including the rate of longest diameter change ΔD₂, ΔD₄, ΔD₆, ΔD₈ (t=-2.760, P=0.007; t=-2.557, P=0.012; t=-4.006, P<0.001; t=-2.872, P=0.005) and volume change rate ΔV₂, ΔV₄, ΔV₆, ΔV₈ (t=-4.167, P<0.001; Z=-3.443, P<0.001; Z=-4.518, P<0.001; Z=-3.708, P<0.001) along with resistance index (RI) measurements in the 4th, the 6th and the 8th cycle (Z=-2.108, P=0.035; Z=-2.386, P=0.017; Z=-3.708, P<0.001). Multivariate analysis showed that tumor molecular type (OR=0.15, 95% CI 0.03-0.64, P=0.005) and tumor volume change rate after the second cycle of NAC ΔV₂ (OR=121.47, 95% CI 4.25-3468.72, P=0.010) were independent predictors of pCR in HER2 positive breast cancer after NAC (P<0.05). The area under the receiver operating characteristic (ROC) curve (AUC) of the nomogram model was 0.82 (95% CI 0.74-0.91), the sensitivity was 85%, and the specificity was 75%. Calibration chart and decision curve analysis (DCA) showed it has good application value in clinical evaluation. Conclusion: The developed nomogram scoring model integrating ultrasound and clinicopathological features demonstrates strong predictive potential for identifying pCR among HER2 positive breast cancer patients post-NAC, thereby offering valuable insights into subsequent treatment decisions.

Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive liver malignancy with a poor prognosis, and early diagnosis is critical for improving patient survival. Conventional ultrasound has limited diagnostic value for ICC, and clinical diagnosis primarily relies on contrast-enhanced computed tomography (CECT) or contrast-enhanced magnetic resonance imaging (CEMRI). Contrast-enhanced ultrasound (CEUS), as a real-time, non-invasive, and convenient imaging technique, has demonstrated significant value in the diagnosis of focal liver lesion (FLL). This article systematically reviewed the current applications of CEUS in the diagnosis of ICC, with a particular focus on the controversies and latest advances in its development. Due to the overlapping imaging features of ICC and hepatocellular carcinoma (HCC) on CEUS, the diagnostic capability of CEUS was once questioned and even removed from the diagnostic tools for HCC in the guidelines of the American Association for the Study of Liver Diseases (AASLD). Subsequently, the academic community has engaged in extensive discussions on the value of CEUS in the differential diagnosis of ICC and HCC. Recent studies have shown that by optimizing the Liver Imaging Reporting and Data System (LI-RADS) criteria, incorporating dynamic quantitative analysis, and leveraging radiomics and artificial intelligence technologies, the accuracy and specificity of CEUS in diagnosing ICC have significantly improved. With the development of more high-quality studies, CEUS is expected to play an increasingly important role in the early diagnosis, classification, and treatment monitoring of ICC.

Objective: To compare the value of ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computer tomography (CT) and ⁶⁸GA-fibroblast activation protein inhibitor (FAPI) PET/CT in the diagnosis of different types of lymphoma. Methods: The clinical, pathological and imaging data of patients with lymphoma who received ¹⁸F-FDG and ⁶⁸Ga-FAPI PET/CT in Fudan University Shanghai Cancer Center within one week from November 2020 to October 2022 were retrospectively analyzed, and the detection rates of the two imaging agents for lesions were compared. At the same time, the differences of maximum standard uptake value (SUV_max), target-to-background ratio (TBR) and target-to-liver ratio (TLR) between the two groups were compared. Results: A total of 197 lymphomas (167 lymph node lesions and 30 extranodal lesions) were detected in 28 patients with pathologically confirmed lymphoma, and 191 lesions (161 lymph node lesions and 30 extranodal lesions) were detected by ¹⁸F-FDG PET/CT. ⁶⁸Ga-FAPI PET/CT detected 98 lesions (including 74 lymph node lesions and 24 extranodal lesions), and the detection rate of ¹⁸F-FDG PET/CT was significantly higher than that of ⁶⁸Ga-FAPI PET/CT. But for gastrointestinal infiltrating lesions, ¹⁸F-FDG PET/CT has a higher false positive rate. In lymphoma patients, SUV_max-FDG > SUV_max-FAPI, TBR-FDG > TBR-FAPI, the difference was statistically significant (14.4 vs 6.5, 13.3 vs 3.4, P<0.05). However, the SUV_max and TBR of Hodgkin’s lymphoma (HL) were 12.3 vs 6.5, 11.6 vs 5.1 (P>0.05) and indolent lymphoma 10.2 vs 10.9, 21.4 vs 5.1 (P>0.05), the difference was not statistically significant. There was no significant difference in TLR between the two examinations in all lymphoma patients (5.2 vs 5.2, P>0.05). Conclusion: The diagnostic value of ¹⁸F-FDG PET/CT for lymphoma is better than ⁶⁸Ga-FAPI PET/CT. But for HL and inert lymphoma, there was no significant difference in metabolic parameters between the two groups, and ⁶⁸Ga-FAPI PET/CT has higher diagnostic accuracy for gastrointestinal infiltration.

Objective: To evaluate the size and internal changes of bone metastases in breast cancer by spectral computed tomography (CT) images, to explore the predictive value of these multiple parameters for progression-free survival (PFS), and to overcome the limitations of conventional CT and existing criteria in the evaluation of bone metastases. Methods: The clinical and imaging data of patients with breast cancer with bone metastasis who were treated in Fudan University Shanghai Cancer Center from June 2019 to December 2022 were retrospectively analyzed. All patients underwent two contrast-enhanced spectral CT examinations, and the size indexes of bone metastases were recorded on the venous stage images: long diameter, short diameter, sum of long diameter and short diameter, and area of interest. Internal indicators of bone metastasis were CT value of conventional image (bone window) (CTv), CT value of single-level image (CT_{40 keV}, CT_{80 keV}, CT_{120 keV}), CT value of calcium suppression image (CT_CaSupp30, CT_CaSupp50, CT_CaSupp70, CT_CaSupp90). Each index of all the bone metastatic target lesions measured in the patient was summed respectively, and the change rate and monthly change rate of each index were calculated. The independent risk factors of PFS were determined by univariate and multifactor Cox proportional risk regression analysis combined with stepwise regression method. Cox proportional hazard regression model was used to construct the model, and the area under the time-dependent receiver operating characteristic curve (AUC) was used to evaluate its predictive performance. DeLong test compared AUC. The threshold was determined by X-tile method and divided into high and low risk groups according to the threshold. Kaplan-Meier (KM) survival curve and log-rank test were used to analyze the difference in prognosis between groups. Results: A total of 30 patients with breast cancer with bone metastases were included. The monthly rate of change of the sum of length and diameter of bone metastases and the monthly rate of change of CT_CaSupp70 are effective predictors of PFS in breast cancer patients with bone metastases. PFS was significantly prolonged in patients with the monthly change rate of the sum of length and diameter < 0.39% and the monthly change rate of CT_CaSupp70>-9.75%. The AUC of 1-year PFS predicted by the sum of long and short diameters model, CT_CaSupp70 model, combined model and response criteria of bone metastases at MD Anderson Cancer Center (MDA criteria) were 0.751, 0.702, 0.827 and 0.600, respectively. The predictive performance of the combined model was significantly better than that of the MDA standard (P=0.003). The PFS of high risk group were significantly lower than those of low risk group (P<0.05). There was no significant difference in PFS survival curve under MDA (P=0.091). Conclusion: The monthly rate of change in the sum of long and short diameters of bone metastases and the monthly rate of change in CT_CaSupp70 are effective predictive indicators for the prognosis of breast cancer patients with bone metastasis, and their combined application can enhance predictive performance.

Objective: To explore the application value of contrast-enhanced ultrasound in the diagnosis of Xp11.2 translocation /TFE3 gene fusion associated renal carcinoma (Xp11.2 translocation renal carcinoma). Methods: Patients with Xp11.2 translocation renal carcinoma confirmed by pathological examination were retrospectively enrolled as XP group between January 2021 and May 2023, while patients with clear cell renal cell carcinoma (ccRCC) during the same period were enrolled as ccRCC group. All patients underwent scans of routine ultrasound and contrast-enhanced ultrasound. The ultrasonographic findings in the two groups were compared. The diagnostic value of contrast-enhanced ultrasound in Xp11.2 translocation /TFE3 gene fusion-associated renal carcinoma was analyzed. Results: A total of 28 patients were included in the XP group and 40 in the ccRCC group. The age in XP group was younger than that in ccRCC group, and proportion of males was lower than that in ccRCC group (χ²=5.419; χ²=7.502, P<0.05). Routine ultrasound showed that there were significant differences in boundary and calcification between XP group and ccRCC group (P<0.05). Contrast-enhanced ultrasound showed that there were significant differences in perfusion mode and peak enhancement mode between XP group and ccRCC group (P<0.05). The time to peak (TTP) and begin to fade (BTF) in XP group were shorter than those in ccRCC group (P<0.05). There was no significant difference in arrival time (AT) between the two groups (P>0.05). Receiver operating characteristic (ROC) curve showed that AUC of TTP combined with BTF in the diagnosis of Xp11.2 translocation renal carcinoma was 0.855, greater than that of single index (0.773, 0.744; Z=2.202; Z=2.141, P<0.05). Binary logistic analysis showed that calcification, peak low enhancement or isoenhancement, TTP≤21.15 s, BTF≤25.31 s were all independent risk factors for the diagnosis of Xp11.2 translocative renal carcinoma by contrast ultrasound (P<0.05). Conclusion: Quantitative parameters of contrast-enhanced ultrasound have good differential diagnosis effect and clinical application value in Xp11.2 translocation renal carcinoma.

Objective: To explore the ultrasound imaging evaluation of breast cancer microcalcifications under the expression status of different SOX gene family transcription factors. Methods: The study selected breast cancer patients diagnosed through pathological examination in Xingtai Central Hospital from January 2020 to October 2023. All patients underwent surgical treatment. Breast cancer tissue was obtained from the tumor site, along with adjacent normal tissue at least 5 cm away from the cancerous tissue. The collected tissues were immediately preserved in liquid nitrogen at -196℃ for subsequent research. Preoperative ultrasound examinations, including routine ultrasound, shear wave elastography, and contrast-enhanced ultrasound were performed. Postoperative pathological histological testing was conducted to detect SOX4 expression, and the relationship between ultrasonographic microcalcifications and SOX4 protein expression was analyzed. Results: In 215 patients, the proportion of high SOX4 expression in breast cancer tissue was 86.05%, significantly higher than that in adjacent normal tissue, which was 48.84% (χ²=67.783, P=0.000). Breast cancer microcalcifications were closely associated with clinical pathological features such as tumor differentiation and lymph node metastasis (P<0.05). High SOX4 expression in breast cancer was closely correlated with microcalcifications, Alder blood flow grading, peripheral radial enhancement, and the rim sign (P<0.05). Logistic regression analysis showed that microcalcifications (OR=1.839, 95% CI 1.538-2.198), peripheral radial enhancement (OR=1.795, 95% CI 1.089-2.959), and rim sign (OR=1.496, 95% CI 1.007-2.223) were risk factors for high SOX4 expression in breast cancer (P<0.05). Conclusion: SOX4 is implicated as a pivotal contributor to the pathogenesis and progression of breast cancer. The manifestation of microcalcifications in ultrasound imaging exhibits a significant correlation with tumor differentiation and lymph node metastasis, underscoring microcalcification as a prognostic marker for elevated SOX4 expression. Clinically, the identification of microcalcification patterns serves as a predictive tool for the expression of SOX4 transcription factors, which is anticipated to augment the precision of early diagnostic modalities and inform the development of targeted therapeutic strategies in breast cancer management.

Breast cancer is highly heterogeneous at the molecular level, and molecular classification of breast cancer is very important for treatment selection and prognosis assessment. As a non-invasive and convenient diagnostic method, ultrasound plays an important role in breast cancer screening and diagnosis. By analyzing ultrasound image features and artificial intelligence modeling, medical personnel are expected to achieve non-invasive and accurate diagnosis of breast cancer molecular subtypes. This article reviewed the progress of ultrasonography in determining molecular typing of breast cancer.

Intrahepatic cholangiocarcinoma (ICC), the second most common primary malignant liver tumor accounting for 10%~20% of cases, presents significant diagnostic challenges and poor prognosis. The insidious clinical presentation and imaging heterogeneity of ICC often lead to late-stage diagnosis, resulting in missed opportunities for curative surgery. While conventional imaging modalities like computed tomography (CT) and magnetic resonance imaging (MRI) excel in lesion detection and metastasis evaluation, they also demonstrate some limitations. Contrast-enhanced ultrasound (CEUS) has become an effective imaging method for the diagnosis of ICC due to its characteristics of real-time dynamic observation, radiation-free nature, high spatiotemporal resolution, and repeatability. Typical CEUS features of ICC include rim arterial phase hyperenhancement (APHE) or non-rim APHE followed by early washout (within 60 s) in the portal phase and marked washout (“black hole sign”) in the delayed phase. In contrast, hepatocellular carcinoma (HCC) typically demonstrates non-rim APHE with iso-enhancement in the portal phase and mild delayed phase washout, where differences in washout timing and degree serve as key discriminators. The CEUS Liver Imaging Reporting and Data System (LI-RADS) version 2017 categorizes lesions with rim APHE, early washout, or marked washout as LR-M (indicative of non-HCC malignancies), effectively reducing ICC misdiagnosis as HCC. The novel Kupffer cell-specific contrast agent perfluorobutane extends imaging duration significantly. Its Kupffer-phase defect demonstrates 100% sensitivity for ICC, offering new perspectives for lesion detection in cirrhotic livers. CEUS and CT/MRI exhibit complementary diagnostic value for ICC, with multimodal integration improving diagnostic accuracy and providing reliable solutions for complex cases. Current challenges for CEUS LI-RADS include refining LR-M classification to better distinguish HCC from ICC, particularly through adjustments in diagnostic thresholds for different hepatic backgrounds (cirrhotic vs non-cirrhotic) and tumor sizes. The clinical potential of Kupffer phase in perfluorobutane CEUS requires larger validation studies, along with investigations into the correlation between washout timing and hepatic background characteristics.

T1 mapping technology is a quantitative magnetic resonance imaging technique. With the development of this technology, methods for achieving T1 mapping have continually evolved, from traditional T1 mapping techniques to synthetic magnetic resonance imaging that can obtain multiple parameters in once scan. Each method has its own advantages and disadvantages. At present, this technology is widely used in the research of tumor lesions in various regions, including head and neck, chest, breast, liver, cervix, and rectum. This article primarily provided a review of the application of T1 mapping technology in the diagnosis, differential diagnosis, and prognosis evaluation of tumor lesions across different organ systems.

Objective: To compare the diagnostic value of qualitative and quantitative parameters of sound touch elastography (STE) and strain elastography (SE) in differentiating benign and malignant Breast Imaging Reporting and Data System (BI-RADS) 4 breast lesions, and to explore the correlation between the parameters and the expression of human epidermal growth factor receptor 2 (HER2) in BI-RADS 4 breast malignant lesions. Methods: The clinicopathological data of patients with BI-RADS 4 breast lesions diagnosed by ultrasound examination in The First Hospital of Shanxi Medical University were selected. The quantitative and qualitative parameters of STE and SE were obtained: STE maximum elasticity (E_max), STE qualitative score, SE strain ratio (SR) and SE qualitative score. To compare the value of two ultrasonic elastography parameters in differentiating benign and malignant BI-RADS 4 breast lesions and their correlation with HER2 expression in BI-RADS 4 breast malignant lesions. Results: A total of 106 patients with 106 lesions were included. The difference of E_max, STE score, SR and SE score between benign and malignant lesions of BI-RADS 4 breast was statistically significant (P<0.05). Compared with the pathological results, the difference of E_max, STE score, SR and SE score in the diagnosis of benign and malignant BI-RADS 4 breast lesions according to the cut-off value was statistically significant (P<0.05). The diagnostic efficacy of E_max, STE score and SR was generally consistent with that of the gold standard (Kappa=0.436, 0.420, 0.502), and the diagnostic efficacy of SE score was more consistent with that of the gold standard (Kappa=0.626). The area under the receiver operating characteristic (ROC) curve (AUC) of SE score (AUC=0.883) was higher than that of E_max (AUC=0.743), STE score (AUC=0.756) and SR (AUC=0.783) diagnosis, with the greatest diagnostic efficiency, and the difference was statistically significant (P<0.05). In BI-RADS 4 breast malignant lesions, the difference of E_max and SE scores between HER2 positive expression and negative expression was statistically significant (P<0.05). E_max and SE scores were positively correlated with HER2 positive expression (r=0.458, 0.356). The best cut-off value of E_max and SE score in the diagnosis of HER2 positive expression was 123.75 kPa and 4 points, the sensitivity was 81.2% and 62.5%, the specificity was 60.5% and 68.4%, and the AUC was 0.766 and 0.689. Conclusion: The diagnostic efficacy of SE score was higher when STE and SE techniques were used to identify BI-RADS 4 breast lesions. E_max and SE scores were positively correlated with HER2 positive expression. E_max and SE score are of great value in identifying HER2 positive expression in BI-RADS 4 breast malignant lesions.

The application of immune checkpoint inhibitors (ICI) in cancer treatment is on the rise, conferring substantial survival benefits to patients. Nevertheless, the development of life-threatening myocarditis induced by ICI has emerged as a novel challenge in clinical practice. Multimodality imaging, due to their non-invasive and low-risk profile, play an important role in the evaluation of ICI-associated myocarditis. This article reviewed the advancements of multimodality imaging for the assessment of ICI-associated myocarditis.

Objective: To assess the injuries of left ventricular function in breast cancer patients following anthracycline-based chemotherapy using ultrasonic vector flow mapping (VFM) combined with layer-specific two-dimensional speckle tracking imaging (LS2D-STI). Methods: A retrospective analysis was conducted on breast cancer patients who underwent chemotherapy with the TEC regimen (docetaxel 75 mg/m², epirubicin 90 mg/m², and cyclophosphamide 500 mg/m²) for the injuries of left ventricular function in Sichuan Provincial People’s Hospital from January to June 2017. A self-controlled study design was employed, with transthoracic echocardiography (TTE) performed before chemotherapy and at 48 h after each chemotherapy cycle, for a total of seven assessments (denoted as T0, T1, T2, T3, T4, T5, and T6) for parameters of intra-ventricular hemodynamic and transmural strain. Conventional echocardiographic parameters were collected, along with myocardial layer-specific global longitudinal strain, including endocardial global longitudinal strain (GLSendo), mid-myocardial global longitudinal strain (GLSmid), and epicardial global longitudinal strain (GLSepi). Additionally, left intra-ventricular hemodynamic parameters were measured, including global energy loss (EL), comprising early diastolic energy loss (EDC_EL), late diastolic energy loss (LDC_EL), isovolumic contraction energy loss (IVC_EL), and rapid ejection period energy loss (REP_EL). Left ventricular global circulation intensity (CIR) was also analyzed, including early diastolic circulation (EDC_CIR), late diastolic circulation (LDC_CIR), isovolumic contraction circulation (IVC_CIR), and rapid ejection period circulation (REP_CIR). The collected data were analyzed to assess changes in left ventricular function over the course of chemotherapy. Results: ① There were no significant differences in left ventricular ejection fraction (LVEF) between T1-T6 and T0 (P>0.05). The mitral inflow early diastolic peak velocity to mitral annular early diastolic peak velocity ratio (E/e’) gradually increased from T1 onward, with statistically significant differences observed (T0: 5.64 to T6: 8.76, P<0.05). ② There were no significant differences in GLSendo, GLSmid, or GLSepi at any time point compared to baseline (P>0.05). However, these parameters showed a trend of initially increasing and then decreasing, with strains at T6 being lower than baseline values. ③ EL showed an overall downward trend, while CIR exhibited an upward trend. Specifically, LDC_EL at T2-T6 was significantly lower than T0, whereas LDC_CIR at T2, T4, and T6 was higher than T0. EDC_EL and IVC_EL were significantly lower at T5 and T6, and REP_EL at T5 and T6 was significantly lower than baseline (P<0.05). Changes in LDC-phase parameters occurred earlier than those in other phases. EL and CIR changes occurred later than changes in E/e’. Conclusion: Ultrasonic VFM and LS2D-STI contribute to comprehensive assessment of cardiotoxicity in breast cancer patients undergoing anthracycline-based chemotherapy. Among these, the combination of E/e’ with EL and CIR may have more significant clinical value in evaluating changes in left ventricular diastolic function.

During the therapeutic management of malignant neoplasms, for instance, during radiotherapy (RT) and chemotherapeutic regimens, treatment-associated cardiotoxicity may ensue, which is typically challenging to be detected and diagnosed at an early stage. Nuclear medicine molecular imaging is capable of directly revealing physiological and pathological processes at the cellular or molecular level, enabling the visualization of cardiotoxicity associated with the treatment of malignant tumors.This article provided a comprehensive review on the diagnostic significance of nuclear medicine molecular imaging in terms of cardiotoxicity associated with malignant neoplasm treatment from multiple perspectives, including myocardial metabolism, inflammation, neural injury, and fibrosis. The aim is to further elucidate its pathophysiological evolution and enhance the early-stage diagnostic proficiency.

Objective: To investigate the diagnostic value of contrast-enhanced ultrasound (CEUS) guided fine-needle aspiration biopsy (FNAB) for papillary thyroid carcinoma of the thyroid (PTC) with a diameter of ≥10 mm. Methods: The data of patients with PTC (≥10 mm in diameter) confirmed by postoperative pathology from May 2020 to August 2023 in Minhang Hospital of Fudan University were reviewed and analyzed. All nodules were first examined by CEUS. After the CEUS, conventional ultrasound-guided FNAB (US-FNAB) was performed to the two-dimensional ultrasound image of the largest diameter of the nodule. Two tissue smears (labeled A₁ and A₂) were used as conventional puncture group. For the same nodule, CEUS images of the same nodule were observed, and the perfused area of the nodule was selected for target puncture, and 2 aspirated cell tissue smears (labeled B₁ and B₂) as the target puncture group. With the postoperative pathological findings as the gold standard, the diagnostic value of CEUS, US-FNAB and CEUS-FNAB for PTC was analyzed using the consistency Kappa test. Results: A total of 149 patients (155 nodes) were included in this study. The sensitivity, specificity and accuracy of CEUS in diagnosing 155 PTCs were 87.1%, 68.6% and 83.2%, respectively; the sensitivity, specificity and accuracy of US-FNAB were 92.9%, 78.0% and 85.6%; and the sensitivity, specificity and accuracy of CEUS-FNAB were 98.1%, 79.6% and 94.9%, respectively. With the postoperative pathology results as the gold standard, Kappa consistency test was performed between the CEUS results and the postoperative pathology results, with Kappa=0.393 (Kappa<0.4), poor consistency, and statistically significant difference (P<0.01); the Kappa value of the US-FNAB results=0.574 (0.75>Kappa≥0.4), the consistency was fair, and the difference was statistically significant (P<0.01); Kappa value of CEUS-FNAB results=0.773 (Kappa>0.75), consistency was good, and the difference was statistically significant (P<0.01). Conclusion: CEUS technology is helpful to detect suspicious lesions of thyroid cancer, and CEUS-FNAB can improve the accuracy of puncture and lesion detection rate, which is of great significance for the diagnosis of PTC.

Objective: To evaluate the protective effects of astragaloside Ⅳ (AS-Ⅳ) against epirubicin (Epb)-induced cardiac injury in rats using speckle tracking imaging. Methods: Thirty-two SD rats were randomly assigned to four groups (n=8 per group): normal control, Epb model, low-dose AS-Ⅳ, and high-dose AS-Ⅳ. Transthoracic echocardiography (TTE) was performed at baseline and at 2, 4, and 6 weeks post-treatment to assess left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS). At week 6, serum levels of CK-MB, LDH, and IL-17 were measured, and heart tissues were collected for Masson staining to evaluate myocardial fibrosis. Results: LVEF showed no significant changes across groups or over time (P>0.05). GLS, however, was significantly influenced by both factors [F group (3, 21)=11.014 2, P<0.000 1] and time [F time (3, 21)=7.215 4, P=0.001 7], with a near-significant interaction effect [F interaction (9, 63)=1.876 1, P=0.072 0]. Serum CK-MB and LDH levels showed no significant differences among groups (P>0.05). IL-17 levels were significantly elevated in the Epb model group compared to the control group, while both AS-Ⅳ treatment groups exhibited significantly reduced levels compared to the Epb model group (P<0.05). The heart weight index did not differ significantly among groups, but myocardial fibrosis area showed significant variations, worsening progressively from control to high-dose AS-Ⅳ, low-dose AS-Ⅳ and Epb model groups（P<0.000 1）. Conclusion: AS-Ⅳ may attenuate myocardial fibrosis and reduce inflammation in Epb-induced myocardial damage. GLS proved to be a more sensitive and accurate indicator than LVEF for detecting subclinical myocardial injury.

Objective: To identify risk factors for central lymph node metastasis (CLNM) in papillary carcinoma of the thyroid (PTC) and establish a prediction model to guide surgical decision-making for PTC patients. Methods: A retrospective analysis was conducted on the clinical features, ultrasonic characteristics, and genetic information of 1 125 PTC patients who underwent thyroidectomy in Nanjing Drum Tower Hospital. The independent risk factors of CLNM were screened by univariate and multivariate logistic regression analysis, and a nomogram model was established based on these factors. The calibration accuracy, accuracy, and clinical utility of the prediction model were evaluated using corrected curves, receiver operating characteristic (ROC) curves, and decision curves. Subsequently, the data of 483 PTC patients who underwent thyroidectomy in Nanjing University Affiliated Jinling Hospital were collected for external validation of the model. Results: Among the 1 125 PTC patients, univariate regression analysis showed significant differences between CLNM positive and negative groups in terms of gender, age, thyroglobulin levels and ultrasonic characteristics of the lesion (maximum diameter, aspect ratio, edge, and microcalcification) (P<0.05). Multivariate logistic regression confirmed gender, age, and ultrasonic characteristics of the lesions (maximum diameter, edge, and microcalcification) as independent risk factors of CLNM. Based on these independent risk factors,a nomogram was Constructed. The area under the ROC curve (AUC) of the model was 0.768 (95% CI 0.741-0.796) in the training set and 0.822 (95% CI 0.784-0.859) in the validation set. Conclusion: The established model has good prediction and generalization abilities and is expected to assist clinicians in making individualized surgical plans for PTC patients.

Objective: To explore the performance of high-frequency ultrasound after manipulation under anesthesia (MUA) of knee joint. Methods: The clinical and ultrasound imaging data of 35 patients who underwent MUA of knee joint in Shanghai Fengcheng hospital from January 2021 to June 2022 were retrospectively analyzed. The ultrasound parameters of each patient included joint effusion, synovium, quadriceps tendon and patellar ligament echo and thickness before and after the MUA. Results: After 2 weeks of MUA, 37.1% of the patients had signs of synovitis, and 20.0% of the patients had joint effusion. Echo reduction was observed in all the quadriceps tendon and patellar ligament, and the thickness were increased with an average of 23.2% and 18.3%, respectively. Macro-calcification was found in 28.6% of the quadriceps tendon and patellar ligaments, and a hypoechoic defect on the patellar ligament was found in 8.6% of the patients. All these parameters were improved after 12 weeks of MUA. Conclusion: Ultrasound provides morphological changes of the knee joint after MUA, which is helpful to guide the clinical decision of further treatment.

Objective: To investigate the value of contrast-enhanced ultrasound (CEUS) in percutaneous intrahepatic cholangiocarcinoma (ICC) biopsy. Methods: Patients with ultrasonically suspected ICC who underwent ultrasound-guided percutaneous liver biopsy were included in this study. Patients performed CEUS before biopsy were enrolled in the CEUS group. Cases were enrolled into control group without CEUS examination. The differences of ultrasound image characteristics, biopsy success rate and complications between the two groups were compared, and the application value of CEUS in percutaneous ICC biopsy was analyzed. Results: A total of 141 patients were included, including 94 in the CEUS group and 47 in the control group. The rate of internal lesion necrosis in CEUS group was 22.3% (21/94), higher than that in control group of 4.3% (2/47), the difference was statistically significant (P=0.006). The success rate of puncture biopsy in CEUS group was 94.7% (89/94), higher than that in control group of 83.0% (39/47), and the difference was statistically significant (P=0.032). Especially for 3-5 cm lesions, the biopsy success rate in CEUS group was significantly higher than that in control group (95.5% vs 58.3%, P=0.014). The incidence of complications in the two groups was 2.1% (2/94) and 2.1% (1/47), respectively, and no serious complications occurred, with no significant statistical difference (P=1.000). Conclusion: CEUS examination before percutaneous ICC biopsy was safe and effective, could effectively evaluate the internal structure of the lesion, distinguish the active tumor tissue from the necrotic area, and could significantly improve the success rate of puncture biopsy.

Objective: To investigate the efficiency of preoperative contrast-enhanced ultrasound (CEUS) combined with clinical and pathological features in predicting early recurrence (ER) after surgical resection of hepatocellular carcinoma (HCC). Methods: Patients who underwent initial surgical resection of HCC in the First Affiliated Hospital with Nanjing Medical University from October 2019 to November 2021 were retrospectively analyzed. All patients received preoperative routine ultrasound and CEUS, and were pathologically diagnosed with HCC after surgery. They were divided into ER group and non-ER group according to whether the recurrence occurred within two years after operation. Univariate analysis was used to compare the differences in clinical data, conventional ultrasound characteristics, CEUS parameters, and pathologic features among the different subgroups. Independent risk factors were selected by multivariate logistic regression. Subsequently, the dataset was randomly divided into training and validation sets in a 7∶3 ratio to develop a combined CEUS-clinic-pathology risk prediction model. The predictive efficacy of the model was quantified using the area under curve (AUC) of receiver operating characteristic (ROC) curve. Finally, the risk prediction model was transformed into a nomogram model and its application value was verified. Results: A total of 136 patients were included. The univariate analysis showed that alpha fetoprotein level, capsule, wash-out time, wash-out phase, differentiation grade, microvascular invasion (MVI), liver cirrhosis were significantly different between the two groups (all P<0.05), with the wash-out time, and MVI was the independent risk of ER in patients after surgical resection of HCC. The AUC of training set and validation set were 0.858 and 0.903, with the sensitivity of 94.1%, specificity of 57.1%, Youden index of 0.878 in validation set. The nomogram prediction model showed good calibration in internal validation. Conclusion: The combined model is useful to monitor the risk of ER in high-risk population after surgical resection of HCC, so that timely intervention can be made to improve patient prognosis.

Objective: To explore the predictive value of artificial intelligence (AI) software in identifying benign and malignant lung nodules and predicting the pathological types of lung nodules. Methods: Patients with lung nodules confirmed by pathological examination were collected, who underwent high-risk lung nodule screening at the Minhang Branch of Affiliated to Fudan University Cancer Hospital from September 2020 to August 2024. AI software was used to analyze the benignity and malignancy and pathological types of pulmonary nodules, and consistency with pathological results was tested. The diagnostic performance of the AI software was evaluated through the area under the receiver operating characteristic (ROC) curve. Results: A total of 62 patients with pulmonary nodules were included in the study, including 4 cases of inflammatory nodules, 4 cases of carcinoma in situ, 2 cases of atypical adenomatous hyperplasia, 16 cases of microinvasive adenocarcinoma, 32 cases of invasive adenocarcinoma, and 4 cases of squamous cell carcinoma. The sensitivity, specificity, and accuracy of the pulmonary nodule software in diagnosing the benignity and malignancy of pulmonary nodules were 98.28%, 75.00%, and 96.80%, respectively. The area under the ROC curve for diagnosing benign and malignant pulmonary nodules by AI analysis was 0.866. The consistency between the AI software’s predictions of pulmonary nodule pathological types and the pathological results was tested, with a Kappa value of 0.859. Conclusion: AI software based on computed tomography (CT) target scanning can effectively distinguish between benign and malignant lung nodules during lung cancer screening. It provides a reference for predicting the pathological types of lung nodules and is valuable for optimizing clinical surgical procedures and enabling precise management of patients with pulmonary nodules.

Objective: To assess the feasibility and accuracy of a deep learning model based on two-dimensional ultrasound images for preoperative prediction of lymphovascular invasion (LVI) in breast cancer, and compare its results with traditional interpretations by ultrasound physicians, providing novel imaging insights to support personalized treatment decisions and precision medicine. Methods: A retrospective analysis was conducted on patients diagnosed with breast cancer through postoperative pathology, who underwent breast surgery in Sixth People’s Hospital Affiliated to Medical College of Shanghai Jiao Tong University between January 2020 and December 2023. Standardized grayscale ultrasound images of lesions were processed, and features were extracted using a convolutional neural network (CNN)-based deep learning model to predict LVI. The model’s performance was evaluated using accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). Comparisons were made with the diagnostic performance of ultrasound physicians with varying levels of experience, and the impact of the deep learning model on improving physician diagnostics was analyzed. Results: A total of 232 patients were included, with a total of 232 lesions. The dataset was divided into a training set (185 cases) and a validation set (47 cases) in an 8∶2 ratio. Among the 232 patients, 102 cases (43.97%) were confirmed to have LVI by postoperative pathology. The deep learning model (support vector machine) achieved AUCs of 0.917 (95% CI 0.877-0.956) and 0.863 (95% CI 0.750-0.975) in the training and validation sets, respectively. For the validation set, the accuracy, sensitivity, and specificity were 83.0%, 85.7%, and 80.8%, respectively. In comparison, ultrasound physicians with 5-10 years and 10-15 years of experience achieved AUCs of 0.623 and 0.709, respectively, which were significantly lower than the deep learning model (P<0.05). When assisted by the deep learning model, the AUC for the physician with 10-15 years of experience increased to 0.914, with corresponding improvements in accuracy (91.5%), sensitivity (90.5%), and specificity (92.3%). Conclusion: The deep learning model based on two-dimensional ultrasound images demonstrated superior accuracy and reliability in the preoperative prediction of LVI in breast cancer. It significantly outperformed traditional diagnostic approaches by ultrasound physicians and showed potential as a clinical auxiliary tool to improve the precision of preoperative assessments of LVI, supporting personalized patient treatment planning.