Abstract
Objective It aimed to explore the diagnostic efficacy of multimodal ultrasound images based on mask region with convolutional neural network (M-RCNN) segmentation algorithm for small liver cancer and analyze the expression of zeste gene enhancer homolog 2 (EZH2) and p57 (P57 Kip2) genes in cancer cells. Methods A total of 100 patients suspected of small liver cancer were randomly divided into Doppler group (color Doppler ultrasound examination), contrast group (contrast ultrasound examination), elastic group (ultrasound elastography examination), and multimodal group (combined examination of the three methods), with 25 patients in each group. Images were processed by the M-RCNN segmentation algorithm. The results of the pathological biopsy were used to evaluate the diagnostic efficacy of the four methods. The liver tissues were then extracted and divided into observation group 1 (lesion tissue specimen), observation group 2 (liver tissue around cancer lesion), and control group (normal liver tissue), and the expression activities of EZH2 and p57 genes in the three groups were analyzed. Results The accuracy of M-RCNN (97.23%) and average precision (AP) (71.90%) were higher than other methods (P < 0.05). Sensitivity (88.87%), specific degree of consistency (90.91%), accuracy (89.47%), and consistence (0.68) of the multimodal group were better than the other three groups (P < 0.05). Low and medium differentiated cancer tissues had an irregular shape, unclear boundary, uneven internal echo, unchanged/enhanced posterior echo, blood flow level 1∼2, elastic score 4∼5, and enhancement mode fast in and fast out. The positive expression rate of EZH2 in observation group 1 (75.95%) was higher than that in the other two groups, the positive expression rate of p57 in observation group 1 (80.79%) was lower than that in the other two groups, and the positive expression rate of p57 in the highly differentiated cancer foci (80.79%) was significantly lower than that in the middle and low differentiated cancer foci (P < 0.05). Conclusions M-RCNN segmentation algorithm had a better segmentation effect. Multimodal ultrasound had a good effect on the benign and malignant diagnosis of small liver cancer and had a high clinical application value. The high expression of EZH2 and the decreased expression of p57 can promote the occurrence of small hepatocellular carcinoma, and the deficiency of the P57 gene was related to the low differentiation of cancer cells.
Highlights
Liver cancer, one of the most common malignant tumors in clinical practice, has a high incidence and mortality, which poses a great threat to people’s life and health [1, 2]
Studies have found that enhancer of zeste homolog 2 (EZH2) has high expression activity in a variety of cancer diseases with high incidence, such as breast cancer, stomach cancer, bladder cancer, and prostate cancer [5–8]. e p57 gene, known as the p57 Kip2 gene, belongs to CDK inhibitors (CKIs), which can reduce the activity of cyclin-dependent kinase (CDK), so as to achieve the purpose of inhibiting the proliferation of cancer cells [9, 10]
Three ultrasound methods were combined for diagnosis. e ultrasound images of patients in the four groups were processed by the mask region with convolutional neural network (M-RCNN) segmentation algorithm. en, the results of pathological tissue biopsy were used as the gold standard to evaluate the diagnostic efficacy of the four methods. is study had been approved by the relevant medical ethics committee
Summary
One of the most common malignant tumors in clinical practice, has a high incidence and mortality, which poses a great threat to people’s life and health [1, 2]. During the occurrence of liver cancer, the expressions of enhancer of zeste homolog 2 (EZH2) [3] and p57 gene [4] of flies would change to some extent. EZH2 is an important member of the poly comb group gene family. Studies have found that EZH2 has high expression activity in a variety of cancer diseases with high incidence, such as breast cancer, stomach cancer, bladder cancer, and prostate cancer [5–8]. The expression activity of the two genes has a certain influence on the development of cancer foci. Erefore, early detection and early treatment of small liver cancer are very necessary to reduce mortality If timely discovery and effective treatment can be obtained, the prognosis is relatively good, with a high surgical resection rate and a 5-year postoperative survival rate [11, 12]. erefore, early detection and early treatment of small liver cancer are very necessary to reduce mortality
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