Abstract: Objective To develop a model based on clinical data and contrast-enhanced ultrasound (CEUS) and MRI results for predicting biochemical recurrence of prostate cancer (PCa) in the elderly patients confirmed by targeted biopsy. Methods The clinical data of 169 elderly patients who underwent radical prostatectomy from January 2018 to February 2020 in Taizhou Hospital of Traditional Chinese Medicine were analyzed retrospectively. The cases were divided into biochemical recurrence group (n=65) and normal group (n=104) according to the results of 2-4 years of follow-up. PCa biochemical recurrence was defined as two consecutive detection of PSA ≥0.2 ng/mL . General data model, CEUS model, MRI radiomics model and combined model to predict the biochemical recurrence of PCa were established based on the clinical-imaging data of these patients. The predictive effects were compared among the four models. Results Logistic regression analysis showed that the tumor diameter, preoperative PSA concentration, treatment mode, elastography grade, small area high gray level emphasis and run variance were the independent risk factors of biochemical recurrence. In the training set, the combined model based on clinical-imaging parameters showed the highest predictive efficiency of PCa biochemical recurrence than general data model, contrast-enhanced ultrasound model and MRI radiomics model. Conclusions The predictive value of clinical data or imaging data alone for PCa biochemical recurrence is not ideal. The combined model provides an opportunity for clinical screening of biochemical recurrence population and helps to improve the prognosis of PCa.

Key words: prostate cancer, biochemical recurrence, contrast-enhanced ultrasound, magnetic resonance imaging, radiomics, predictive model