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.

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.

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 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 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 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 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 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.

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.