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A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
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Artificial Intelligence Algorithm-Based MRI for Differentiation Diagnosis of Prostate Cancer
Rui Luo1, Qingxiang Zeng2, Huashan Chen1
1Department of Radiology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Sciences, Xiangyang, 441021 Hubei, China.
Computational and Mathematical Methods in Medicine
|July 8, 2022
Summary
Magnetic resonance imaging (MRI) with the RLRE algorithm and dynamic contrast enhancement (DCE) sequences effectively differentiate prostate cancer (PCa) from benign prostatic hyperplasia (BPH), offering improved diagnostic accuracy and clinical value.
Area of Science:
- Medical Imaging
- Oncology
- Radiology
Background:
- Prostate cancer (PCa) and benign prostatic hyperplasia (BPH) require distinct treatments, necessitating accurate differential diagnosis.
- Magnetic resonance imaging (MRI) is a key tool for evaluating suspected PCa.
- Existing MRI methods require enhancement for better differentiation between PCa and BPH.
Purpose of the Study:
- To evaluate the effectiveness of the RLRE algorithm in improving MRI image quality for PCa/BPH differentiation.
- To compare the diagnostic performance of different MRI sequences in distinguishing PCa from BPH.
- To establish a more effective MRI-based examination method for clinical differential diagnosis.
Main Methods:
- Utilized the weighted low-rank matrix restoration algorithm (RLRE) for MRI image processing.
- Compared RLRE with other algorithms (RL, BM3D) under varying noise levels, assessing peak signal-to-noise ratio (PSNR) and structural similarity (SSIM).
- Evaluated diagnostic performance (sensitivity, specificity, accuracy, consistency) of dynamic contrast enhancement (DCE) and plain scan MRI sequences against pathological results in 150 patients.
Main Results:
- The RLRE algorithm demonstrated superior performance in maintaining PSNR and SSIM compared to RL and BM3D algorithms, especially under increased Gaussian noise (P < 0.05).
- The dynamic contrast enhancement (DCE) sequence achieved higher sensitivity (97.08%), specificity (92.31%), accuracy (96.67%), and consistency (0.678) than the plain scan (86.13%, 69.23%, 84.67%, 0.469, respectively).
- Pathological examination confirmed PCa in 137 patients and BPH in 13 patients, serving as the gold standard for comparison.
Conclusions:
- The RLRE algorithm enhances MRI image resolution and display quality.
- Dynamic contrast enhancement (DCE) MRI sequences provide superior differentiation between prostate cancer and benign prostatic hyperplasia.
- The combination of RLRE and DCE holds significant clinical value and warrants widespread adoption for improved PCa/BPH diagnosis.
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