研究目的
To investigate and discuss the clinical value of positron emission tomography-computed tomography (PET-CT) combined with ultrasound in detection of primary tumors in patients with malignant ascites (MA).
研究成果
PET-CT combined with ultrasound improves diagnostic efficiency for primary tumors in malignant ascites patients, offering higher sensitivity and accuracy than either method alone, and can be cost-beneficial in the long term despite initial high costs.
研究不足
The study has limitations such as the high cost of PET-CT, potential for false negatives and positives due to factors like tumor size and histologic subtypes, and the complexity of overlapping SUVmax values between benign and malignant cases. Optimization could involve larger sample sizes and integration with other diagnostic methods.
1:Experimental Design and Method Selection:
A clinical study enrolling patients with malignant and benign ascites to compare the diagnostic efficiency of PET-CT, abdominal B-ultrasound, and their combination in detecting primary tumors, using pathological findings as the gold standard. Statistical analysis was performed using SPSS software.
2:Sample Selection and Data Sources:
122 malignant tumor patients (gastric, ovarian, intestinal cancer) with ascites as initial symptom and 48 benign ascites patients were selected based on inclusion and exclusion criteria, with informed consent and ethics approval.
3:List of Experimental Equipment and Materials:
PET-CT scanner (Discovery LS, GE Healthcare), 18F-FDG imaging agent, abdominal B-ultrasound equipment (specific model not mentioned), Statistical Product and Service Solutions (SPSS) 17.0 software.
4:0 software.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: Patients fasted for 6-8 hours, injected with 18F-FDG, rested for 1 hour, then underwent PET-CT and B-ultrasound scans. Images were analyzed by nuclear medicine physicians, and diagnostic parameters were calculated.
5:Data Analysis Methods:
Statistical analysis using SPSS 17.0, including t-tests, chi-square tests, Pearson correlation, and ROC curve analysis to compare sensitivity, specificity, accuracy, etc.
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