Cancer presents a significant global public health challenge, impacting human health on a broad scale. In recent years, the rapid advancement of big data-based bioinformatics has unveiled crucial potential in precision oncology through various omics research methods. The advent of radiomics has notably expanded the application scope of medical imaging in the field. However, due to the multi-level and multifactorial nature of tumor initiation and progression, a single omics information remains insufficient to meet the demands for advancing precision oncology strategies. Multi-omics research has become an emerging trend. The research paradigm integrating radiomics with other omics offers a novel perspective for personalized decision-making in oncology. Nevertheless, there persists a need to introduce more integrated new technologies and theories to expedite the progress of this field.
Objective To evaluate the role of contrastenhanced CT (CECT) scanning in the diagnosis and treatment planning of some rare liver tumors. MethodsWe retrospectively reviewed the CECT imaging features of 10 cases with rare tumors of the liver proved by surgical pathology in 8 cases or by liver biopsy in 2 cases, with correlation of relevant clinical manifestations, laboratory results and surgical findings. ResultsThree cases were histopathologically proved to be benign, and 7 cases were malignant. On CT images, the liver lesions were mixed cysticsolid in 5 cases, totally solid in the other 5. Eight cases demonstrated heterogeneous enhancement, while 2 cases of liver lymphoma had no enhancement. The anatomic relationship of tumors to intrahepatic vasculature, the compression and infiltration of neighboring abdominal structures were accurately delineated by CT as compared with findings at operation. Clinical manifestations and laboratory findings were not useful for the qualitative diagnosis of rare liver tumors, except for hepatocellular carcinoma. ConclusionCECT is very useful for the detection of rare liver tumors and the fine depiction of local extent of these tumors. When correlated with clinical and laboratory information, it helps to differentiate rare liver tumors from hepatocellular carcinoma. But its role in the characterization of rare liver tumors is limited.
ObjectiveTo investigate the CT and MR imaging features and distribution characteristics of lymphatic nodal involvement in patients with gallbladder carcinoma. MethodsThirtyseven histopathologically proven cases of gallbladder carcinoma with regional lymphatic nodal enlargement in upper abdomen were included into the study. The lymph nodal short diameter of equal to or larger than 10 mm was used as the criteria for positive lymphadenopathy. Thirtyone cases underwent contrastenhanced spiral CT scanning, 6 cases had MR imaging studies. CT and MR images were jointly evaluated by three radiologists with especial attention to the size and location of enlarged lymph nodes in upper abdomen.ResultsThe enlarged lymph nodes were observed in four anatomic locations in the upper abdominal region. ①The retroportal and retropancreatic group in which lymph nodes were located along the cystic duct and common bile duct, in the portocaval space and behind the pancreatic head. ②The celiac group in which enlarged nodes distributed along the common hepatic artery and surrounded the celiac trunk. ③The mesenteric group in which lymph nodes assembled at the mesenteric root and around the superior mesenteric vessels. ④The abdominal aorta group in which lymph nodes scattered at the left side of abdominal aorta and in the aortocaval space at the level of the left renal vein. The spiral CT visualization rates for the above 4 groups of lymphadenopathy were 89.1%(33/37), 78.3%(29/37), 29.8%(11/37) and 51.3%(19/37) respectively.ConclusionCT and MR can clearly depict the four location sites of lymphadenopathy in patients with gallbladder carcinoma, which closely reflects the three major lymphatic spreading pathways of gallbladder carcinoma, namely, the cholecystoretropancreatic, cholecystoceliac and cholecystomesenteric routes.
ObjectiveTo explore the value of a radiomics model based on ultrasound imaging in predicting the HER-2 status of breast cancer prior to surgery.MethodsA total of 230 patients with invasive breast cancer were retrospectively analyzed, all the patients underwent preoperative breast ultrasound examination. According to the order of examination time, the patients were categorized into training group (n=115) and validation group (n=115). Image J software was used to manually delineate the lesion area in the ultrasound image along the tumor boundary. Pyradiomics was used to extract 1 820 features from each lesion area, and three statistical methods were used to screen features. A logistic regression model was used to construct ultrasound imaging radiomics model. The receive operating characteristic curve (ROC), calibration curve and decision curve were used to evaluate the performance and value of ultrasound imaging radiomics model in predicting HER-2 status.ResultsNine key image features were identified to construct ultrasound imaging radiomics model. The area of under the ROC curve of the model in the training group and the validation group were 0.82 (95%CI 0.74 to 0.90) and 0.81 (95%CI 0.72 to 0.89), respectively. The calibration curve showed that the model had a good calibration in both the training and validation groups.ConclusionsUltrasound-based imaging radiomics model is of significant value in predicting the HER-2 status of breast cancer prior to surgery.