Identifying Benign Prostatic Hyperplasia Stages by Measuring the Length of the Proximal Prostatic Urethra: An Operator-Error-Free Early-Screening Ultrasonography Method With a Uniquely-Calibrated Standardized Plane

Abstract

Recently, it has become a main consensus that early diagnosis of benign prostatic hyperplasia (BPH) is meaningful in delaying disease progression. Although ultrasound has been well recognized as the most useful early screening technique, the lack of a standard observation plane makes it difficult to determine the BPH stages in a way that is operator-independent and satisfies clinical expectations. Strong enthusiasm has fueled intense research on ultrasound coupled with artificial intelligence (AI) for automated or semiautomated classification of different clinical diseases. Therefore, it is crucial to formulate standard planes for ultrasound imaging with the implementation of AI to evaluate BPH. This study was a preliminary examination of AI-assisted ultrasound in the prostate disease diagnostic classification task, which aimed to define and assess the clinical value of the length of the proximal prostatic urethra (Lppu), detected via transrectal ultrasound within the uniquely calibrated standardized plane, in 643 patients suffering from BPH between January 2015 and December 2016. International Prostate Symptom Score (IPSS), quality of life (QoL) and PSA levels were also recorded. The mean (standard deviation) of Lppu was 28.54 mm (9.19 mm), and there were significant differences in the mean Lppu among men who were over 50 yrs old. Lppu was colinear with IPSS, voiding-IPSS, storage-IPSS and QoL with individual r values of 0.13, 0.09, 0.04, and 0.03, respectively (P<0.001). Compared with the traditional ultrasound screening indicator represented by transitional zone index (TZI), the main advantage of measuring Lppu is that it is reasonable in terms of the pathophysiological characteristics of BPH, it is operator-error-free, it is based on the uniquelycalibrated observation plane, and it is effective in guiding personalized management of BPH, especially among men with severe LUTS but small prostates. Furthermore, this screening method is economical and improves the cost-efficiency of public health. After systematic evaluation, Lppu is believed to be an excellent quantitative measurement parameter and early screening tool for evaluating LUTS/BPH and BPH stages.INDEX TERMS Transrectal ultrasound, benign prostatic hyperplasia, the length of the proximal prostatic urethra, early screening, ultrasound diagnostic criteria.

Current Applications of Artificial Intelligence in Benign Prostatic Hyperplasia

“…There have been attempts to standardize this with the help of AI to fulfill clinical expectations. 11 With the increasing use of predictive models that combine in a nonlinear manner, several predictors have also been established to differentiate BPH from prostate cancer (PCa). 11,12 Along with understanding the usefulness of predicting clinical outcomes before performing minimally invasive therapeutic surgeries in BPH, there is also a growing trend of AI aiding the surgeon to make better-informed decisions.…”

“…11 With the increasing use of predictive models that combine in a nonlinear manner, several predictors have also been established to differentiate BPH from prostate cancer (PCa). 11,12 Along with understanding the usefulness of predicting clinical outcomes before performing minimally invasive therapeutic surgeries in BPH, there is also a growing trend of AI aiding the surgeon to make better-informed decisions. 13 Therefore, there is increasing uptake of utilizing AI in screening, symptom analysis, investigation, and management of BPH like other urological pathologies.…”