Machine learning prediction model for gray-level co-occurrence matrix features of synchronous liver metastasis in colorectal cancer.

BACKGROUND: Synchronous liver metastasis (SLM) is a significant contributor to morbidity in colorectal cancer (CRC). There are no effective predictive device integration algorithms to predict adverse SLM events during the diagnosis of CRC. AIM: To explore the risk factors for SLM in CRC and construct a visual prediction model based on gray-level co-occurrence matrix (GLCM) features collected from magnetic resonance imaging (MRI). METHODS: Our study retrospectively enrolled 392 patients with CRC from Yichang Central People's Hospital from January 2015 to May 2023. Patients were randomly divided into a training and validation group (3:7). The clinical parameters and GLCM features extracted from MRI were included as candidate variables. The prediction model was constructed using a generalized linear regression model, random forest model (RFM), and artificial neural network model. Receiver operating characteristic curves and decision curves were used to evaluate the prediction model. RESULTS: Among the 392 patients, 48 had SLM (12.24%). We obtained fourteen GLCM imaging data for variable screening of SLM prediction models. Inverse difference, mean sum, sum entropy, sum variance, sum of squares, energy, and difference variance were listed as candidate variables, and the prediction efficiency (area under the curve) of the subsequent RFM in the training set and internal validation set was 0.917 [95% confidence interval (95%CI): 0.866-0.968] and 0.09 (95%CI: 0.858-0.960), respectively. CONCLUSION: A predictive model combining GLCM image features with machine learning can predict SLM in CRC. This model can assist clinicians in making timely and personalized clinical decisions.

A 5G-based telerobotic ultrasound system provides qualified abdominal ultrasound services for patients on a rural island: a prospective and comparative study of 401 patients.

PURPOSE: To explore the feasibility of a 5G-based telerobotic ultrasound (US) system for providing qualified abdominal US services on a rural island. METHODS: This prospective study involved two medical centers (the tele-radiologist site's hospital and the patient site's hospital) separated by 72 km. Patients underwent 5G-based telerobotic US by tele-radiologists and conventional US by on-site radiologists from September 2020 to March 2021. The clinical feasibility and diagnostic performance of the 5G-based telerobotic abdominal US examination were assessed based on safety, duration, image quality, diagnostic findings, and questionnaires. RESULTS: A total of 401 patients (217 women and 184 men; mean age, 54.96 ± 15.43 years) were enrolled. A total of 90.1% of patients indicated no discomfort with the telerobotic US examination. For the examination duration, telerobotic US took longer than conventional US (12.54 ± 3.20 min vs. 7.23 ± 2.10 min, p = 0.001). For image quality scores, the results of the two methods were similar (4.54 ± 0.63 vs. 4.57 ± 0.61, p = 0.112). No significant differences were found between the two methods in measurements for the aorta, portal vein, gallbladder, kidney (longitudinal diameter), prostate, and uterus; however, telerobotic US underestimated the transverse diameter of the kidney (p < 0.05). A total of 504 positive results, including 31 different diseases, were detected. Among them, 455 cases were identified by the two methods; 17 cases were identified by telerobotic US only; and 32 cases were identified by conventional US only. There was good consistency in the diagnosis of 29 types of disease between the two methods (κ = 0.773-1.000). Furthermore, more than 90% of patients accepted the telerobotic US examination and agreed to pay additional fees in future. CONCLUSION: The 5G-based telerobotic US system can expand access to abdominal US services for patients in rural areas, thereby reducing health care disparities.

Primary splenic angiosarcoma with liver metastasis: A case report and literature review.

Primary splenic angiosarcoma (PSA) is an unusual and highly malignant vascular tumour with a high rate of metastatic. Moreover, the research on prognosis of the disease is poor. The epidemiology, etiology, clinical diagnosis and treatment of the disease remain challenging, because case reports of the disease are few in number. In accordance with other malignant tumors, PSA is very aggressive, and the majority of patients in which this disease is found are at an advanced stage. Almost all patients die within 12 mo of diagnosis irrespective of treatment. We report here a woman who had complained of upper bellyache and anorexia for 10 d. Magnetic resonance imaging showed enlargement of the spleen with multiple heterogeneous masses in the lower pole of the spleen. A hand-assisted laparoscopic splenectomy was performed which allowed histopathologic diagnosis. The patient was diagnosed with PSA and liver metastasis, and succumbed to the disease 35 d after surgery. The literature was finished combined with the clinical features, diagnosis and management of PSA.