Monographic Research·Application of New Ultrasound Technology in Urinary System Diseases
Building a diagnosis and prediction model for prostate cancer based on multimodal data
Shen Dengwen, Lan Sirong, Li Xiong, Chen Nanhui, Zhang Tianhui, Jiang Huiming
Published 2023-08-20
Cite as J Chin Physician, 2023, 25(8): 1139-1143. DOI: 10.3760/cma.j.cn431274-20230622-00893
Abstract
ObjectiveTo explore the diagnostic value of clinical, multi-parameter magnetic resonance imaging (MP-MRI) combined with transrectal ultrasound elasticity data for prostate cancer.
MethodsA retrospective analysis was conducted on patient data from November 2021 to March 2023 when transrectal prostate two-dimensional ultrasound, real-time strain elastography of the prostate, MP-MRI examination of the prostate, and prostate biopsy were performed simultaneously at the Meizhou People′s Hospital. We collected patient age, height, weight, free serum prostate specific antigen (fPSA), total prostate specific antigen (tPSA), fPSA/tPSA, MRI prostate imaging report and data system (PI-RADS) scores, and ultrasound elasticity values. Four predictive models for prostate cancer diagnosis were constructed using multivariate logistic regression for comparison, and the optimal model was selected to construct a column chart. The diagnostic performance of different models was evaluated using receiver operating characteristic (ROC) curves, and the diagnostic performance of column charts was evaluated using calibration curves.
ResultsThis study included a total of 117 patients with 117 prostate lesions, 47 benign prostate lesions, and 70 prostate cancer lesions. There were statistically significant differences in age, fPSA, tPSA, fPSA/tPSA, PI-RADS scores, and ultrasound elasticity values between benign and malignant lesions patients (all P<0.01). The area under the curve (AUC) of the clinical model (age+ tPSA+ fPSA+ fPSA/tPSA), MRI model (PI-RADS score), ultrasound elastic model, and clinical+ MRI+ ultrasound elastic combined model for diagnosing prostate cancer were 0.86, 0.86, 0.92, and 0.98, respectively.
ConclusionsCompared with a single diagnostic model, the combination of age, tPSA, fPSA/tPSA, PI-RADS scores, and ultrasound elasticity value model can improve the diagnostic rate of prostate cancer.
Key words:
Prostatic neoplasms; Elasticity imaging techniques; Multiparametric magnetic resonance imaging; Models, statistical
Contributor Information
Shen Dengwen
Department of Ultrasound, Meizhou People′s Hospital, Meizhou 514031, China
Lan Sirong
Department of Ultrasound, Meizhou People′s Hospital, Meizhou 514031, China
Li Xiong
Department of Ultrasound, Meizhou People′s Hospital, Meizhou 514031, China
Chen Nanhui
Department of Urology, Meizhou People′s Hospital, Meizhou 514031, China
Zhang Tianhui
Department of Radiology, Meizhou People′s Hospital, Meizhou 514031, China
Jiang Huiming
Department of Urology, Meizhou People′s Hospital, Meizhou 514031, China