Description

Prostate cancer is one of the most common malignancies among men worldwide, and accurate diagnosis is crucial for treatment planning and outcome prediction. Conventional multiparametric MRI (mpMRI) has become an important tool in prostate cancer (PCa) diagnosis; however, its diagnostic performance remains suboptimal, e.g., for differentiating clinically significant from insignificant disease. Time-dependent diffusion MRI (TDDMRI) is an advanced technique that probes water diffusion over different diffusion times, thereby providing sensitivity to tissue microstructural features such as cell size, cellularity, and transmembrane water exchange. These parameters may serve as novel imaging biomarkers for PCa and could improve diagnostic accuracy beyond what is currently achievable with standard MRI techniques.

This is a multi-center diagnostic cohort study with prospective enrollment of suspected PCa participants, along with pathology data. The study is designed to evaluate the clinical utility of TDDMRI for PCa detection, with a focus on developing and validating MR microstructural imaging markers and establish a robust diagnostic model that is generalizable to most clinical settings.

Study Procedures Participants with clinical suspicion of prostate cancer will undergo standardized MRI examinations that include both conventional mpMRI and TDDMRI sequences. Imaging protocols will be harmonized across participating centers to ensure reproducibility of microstructural parameter estimation. Quantitative markers such as cellularity, cell size, and diffusivity metrics will be derived from TDDMRI data.

Histopathological confirmation through prostate biopsy or prostatectomy will be obtained in a subset of participants who provide informed consent. For these cases, imaging-derived microstructural parameters will be directly compared with histological measures. For participants without available pathology, imaging data will still be retained and analyzed for exploratory purposes and for cross-center reproducibility assessments.

Quality Assurance and Data Management

To guarantee data integrity and cross-site consistency, a centralized data management platform will be implemented. Key measures include:

• Predefined imaging protocols and on-site training to minimize variability across centers.
• Automated and manual data validation checks for completeness, range, and logical consistency.
• Periodic source data verification against original imaging files and pathology reports.
• Maintenance of a data dictionary with standardized definitions for all imaging and clinical variables.
• Regular quality control audits and feedback loops to ensure adherence to protocol.

Statistical and Analytical Plan The primary analysis will assess the diagnostic performance of TDDMRI-derived microstructural parameters, with histopathology as the gold standard. Diagnostic metrics including sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) will be calculated and directly compared with routine mpMRI metrics and PI-RADS scores.

Secondary analyses will evaluate:

• The correlation between TDDMRI biomarkers and Gleason score or tumor cellularity.
• Cross-center reproducibility and robustness of derived biomarkers.
• Subgroup analyses by tumor location, stage, and patient characteristics.
• Exploratory development of diagnostic thresholds or decision rules based on microstructural parameters.

Sample Size and Missing Data The study is planned as a six-center collaborative effort, with an expected 2000 participants. This target sample size accounts for inter-center variability and allows for \~10-15% attrition or unusable imaging. The final dataset is anticipated to include approximately 40% participants with prostate cancer and 60% without, enabling precise estimation of sensitivity and specificity with narrow confidence intervals.

Missing data will be handled according to predefined rules. Incomplete or degraded imaging datasets will be documented and, where possible, analyzed using available sequences.

Overall Aim The overall aim of this study is to validate TDDMRI as a clinically applicable imaging tool and to establish reproducible microstructural imaging markers that can inform prostate cancer diagnosis across diverse clinical settings. By integrating multi-center imaging data with large-scale histopathological validation, this study seeks to advance precision imaging in prostate cancer and provide evidence for the adoption of TDDMRI in routine clinical practice.