Abstract
This work aimed to explore the accuracy of magnetic resonance imaging (MRI) images based on the convolutional neural network (CNN) algorithm in the diagnosis of prostate cancer patients and tumor risk grading. A total of 89 patients with prostate cancer and benign prostatic hyperplasia diagnosed by MRI examination and pathological examination in hospital were selected as the research objects in this study (they passed the exclusion criteria). The MRI images of these patients were collected in two groups and divided into two groups before and after treatment according to whether the CNN algorithm was used to process them. The number of diagnosed diseases and the number of cases of risk level inferred based on the tumor grading were compared to observe which group was closer to the diagnosis of pathological biopsy. Through comparative analysis, compared with the positive rate of pathological diagnosis (44%), the positive rate after the treatment of the CNN algorithm (42%) was more similar to that before the treatment (34%), and the comparison was statistically marked (P < 0.05). In terms of risk stratification, the grading results after treatment (37 cases) were closer to the results of pathological grading (39 cases) than those before treatment (30 cases), and the comparison was statistically obvious (P < 0.05). In addition, it was obvious that the MRT images would be clearer after treatment through the observation of the MRT images before and after treatment. In conclusion, MRI image segmentation algorithm based on CNN was more accurate in the diagnosis and risk stratification of prostate cancer than routine MRI. According to the evaluation of Dice similarity coefficient (DSC) and Hausdorff I distance (HD), the CNN segmentation method used in this study was more perfect than other segmentation methods.
Highlights
Prostate malignant tumor is the one with the highest incidence among all types of tumors of the male urinary system, ranking 6th in China and around the world [1], and it is most common in middle-aged and elderly men [2]
A total of 89 cases passed the exclusion criteria. e patients were all male and 39–74 years old, with an average age of 49 years. e magnetic resonance imaging (MRI) images of these patients were collected in two groups and enrolled into a pretreatment group and a posttreatment group. e number of research cases in both groups was 89, and the results were compared with the known pathological biopsy results. e process had been approved by the ethics committee of the hospital, and all the research objects included in this study signed the informed consent forms
Routine MRI Imaging Features of Patients with Prostate Cancer and Prostate Hyperplasia. e MRI images of various diseases of the prostate were very similar to the MRI images of prostate cancer, so it was difficult to distinguish between ordinary ultrasound and other examinations. e normal MRI images of the prostate are presented in Figure 4. e shape and size of the prostate in the images were all similar to a flat chestnut. e upper end was wide, the lower end was tapered, and the back of the body was relatively flat. e longitudinal diameter was about 3 cm, the transverse diameter was about 4 cm, and the front and back diameters were about 2 cm
Summary
Prostate malignant tumor (prostate cancer) is the one with the highest incidence among all types of tumors of the male urinary system, ranking 6th in China and around the world [1], and it is most common in middle-aged and elderly men [2]. Whether the diagnosis of this disease is accurate is related to the good or bad prognosis of prostate cancer treatment [5]. At this stage, prostate-specific antigen (PSA) is the primary screening method, but its accuracy is not high. MRI can be used for multidirectional and multiparameter imaging, which can diagnose diseases—to determine the location, Journal of Healthcare Engineering nature of the disease, and the stage of the tumor and to judge the curative effect—to evaluate the effectiveness of the treatment plan [7]. MRI is globally recognized as the preferred method for the early diagnosis and staging of prostate cancer
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