Minimum Variance Algorithm-Based Correlation Analysis between Body Mass Index and the Malignant Degree of Prostate Cancer Mediated under Ultrasound Images

Yong Wei,Wenhui Qian,Peng Chen,Wenren Zuo,Hongru Zhu,Qingyi Zhu,M Pallikonda Rajasekaran

doi:10.1155/2021/4990942

Abstract

This study was to explore the correlation between the malignant degree of prostate cancer (PCa) and body mass index (BMI) mediated by ultrasound images under multioperator algorithm (MOA) based on minimum variance (MV) algorithm. MOA was established by optimizing the smoothing technique and diagonal loading algorithms of MV, and its quality and processing speed of ultrasound images were compared with other algorithms. Ninety two patients were selected as the subjects investigated, who had transrectal prostate biopsy mediated by ultrasound to be diagnosed as PCa in the hospital. Based on Gleason score and prostate specific antigen (PSA) value, all patients were divided into a high-risk PCa group (a high-risk group) and a non-high-risk PCa group (a non-high-risk group). The proportion of obese patients in the two groups was compared. The logistic regression analysis method was applied to analyze related factors of PCa development, and Pearson correlation was for analyzing the correlation between Gleason score and BMI of patients. The results showed that the number of patients in the high-risk group was greater than that of the non-high-risk group ( P < 0.05), while the proportion of nonobese patients in the non-high-risk group was markedly higher than that of the higher-risk group ( P < 0.01). Both PSA and BMI were obviously correlated with the development of high-risk PCa ( P < 0.05), and there was an extreme positive correlation between BMI and Gleason score (r = 0.661 and P = 0.007). It indicated that MOA was established based on conventional MV, which could increase the ultrasonic image quality and calculation speed. Besides, BMI was a risk factor of high-risk PCa and was positively correlated with malignant degree of PCa, which provided a referable evidence for clinical evaluation of malignant degree of PCa.

Highlights

prostate cancer (PCa) is a common malignant tumor of male reproductive system, and its incidence ranks the second among male malignant tumors [1], which has seriously threatened men’s healthy life at present
The image quality of ultrasound image obtained from multioperator algorithm (MOA) was compared with that of other algorithms. e results showed that the horizontal resolution and image contrast of MOA was relatively stable with continuous increase of M/N value in contrast to other algorithms. us, it suggested that MOA improved the robustness of minimum variance (MV) to increase its stability
Li et al [15] found that men with body mass index (BMI) ≥ 35 kg/m2 had a greatly higher risk of developing PCa than men with BMI < 25 kg/m2, which were similar to the results of the study. e proportion of obese patients with PCa was analyzed to find that the proportion of obese patients increased markedly in contrast to the nonobese patients (P < 0.05)

Summary

Introduction

PCa is a common malignant tumor of male reproductive system, and its incidence ranks the second among male malignant tumors [1], which has seriously threatened men’s healthy life at present. The incidence of PCa in developed countries such as some European countries and America is obviously higher than that of China. Some studies have shown that changes in BMI and blood lipid level are correlated with the emerging of PCa to a certain extent [3]. Some studies have found that the mortality rate of patients with PCa in countries with high dietary fat intake is higher than the rate of countries with low dietary fat intake, indicating that excessive fat intake has a certain influence on the development of cancer [4]. The influence factors for malignant degree of PCa are not clear at present

Results

Discussion

Conclusion