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Abstract #2451

Using Multimodal MRI Quantitative Metrics as Image Biomarkers to Predict the Tumor Malignant Degree of Prostate Cancer

Ruo di Zhang1,2, Zhiqiang Chen3, and Guangxu Han4
1Clinical medicine school of Ningxia Medical University, Bao ji, China, 2Department of Medical Imaging, Baoji Traditional Chinese Medicine Hospital, Baoji, China, 3Department of Radiology ,the First Hospital Affiliated to Hainan Medical College, Haikou, China, 4GE HealthCare MR Research, Beijing, China

Synopsis

Keywords: Prostate, Cancer, Multimodal MRI, P504s, Prostate cancer

Motivation: Multimodal MRI plays a crucial role in prostate examinations, offering detailed imaging. But The potential of multimodal MRI metrics to predict early prostate cancer diagnosis remains unknown.

Goal(s): To identify a non-invasive and effective examination method that provide reliable reference information for early prostate cancer diagnosis.

Approach: Multimodal MRI data of 107 patients was acquired. The time-signal intensity curves were obtained, and the quantitative image metrics (Tmax, SImax, Rmax and ADC) were correlated with the tumor markers (P504s).

Results: Multimodal MRI quantitative metrics have the potential to serve as imaging indicators for predicting the expression levels of P504s in PCa.

Impact: The ADC value, Tmax(s), SImax% and Rmax% of multimodal MRI are correlated with the expression of P504s . These metrics can serve as imaging biomarkers to predict the proliferation and metabolic ability of PCa.

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Keywords