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Assessing Quality and Adherence to PI-RADSv2.1 Minimum Technical Standards of Prostate MRI in NRG-GU005
Stephanie Alley1,2, Marion Tonneau2, Damien Olivié2
1Polytechnique Montréal, Montréal, Canada.
Background:
Multi-parametric MRI (mpMRI) datasets often vary between sites due to differences in acquisition protocols.
Purpose:
Evaluate adherence of multi-site mpMRI dataset to minimum technical standards (MTS) of PI-RADSv2.1.
Study Type:
Prospective.
Subjects:
Six hundred patients (Age (years): ≤ 49 = 0.8%, 50-59 = 10.7%, 60-69 = 47.0%, ≥ 70 = 41.5%) with intermediate-risk prostate cancer (PCa) imaged across 124 institutions prior to radiotherapy.
Field Strength/Sequence:
3T, 1.5T, and 1.16T, T2-weighted (T2w): fast spin-echo, diffusion-weighted imaging (DWI): single-shot echo-planar imaging, and dynamic contrast-enhanced (DCE): T1-weighted 3D fast spoiled gradient echo.
Assessment:
Scanner vendors included Siemens, GE, Philips, Toshiba, and Hitachi. Degree of adherence to PIRADSv2.1 was determined as the proportion of datasets that met MTS. Mean and standard deviation of parameter values were calculated where applicable. Prostate imaging quality (PI-QUAL)v2 scores were assigned by one of three observers in 491 datasets. Evaluation of DICOM metadata consistency was performed.
Statistical Tests:
Fisher's exact test to assess changes in MTS adherence over time and by field strength; Harrel's C-index to compare MTS adherence to PI-QUAL score. A p value of < 0.001 is considered statistically significant after Bonferroni correction.
Results:
Eighty-two percent of MTS showed greater than 75% adherence. Low adherence was found in the in-plane dimension (frequency-encoding direction) for T2w images (57%, mean = 0.45 ± 0.16 mm) and field of view (FOV) for DW images (62%, mean = 22.67 ± 4.70 cm). Only 50% of datasets used the recommended high b value image to compute the apparent diffusion coefficient map. Adherence improved significantly over time for one T2w and two DWI parameters; the adherence of FOV improved significantly at 3T for T2w and DWI sequences. C-index values for two T2w and two DWI parameters demonstrated a relationship between PI-RADS MTS and PI-QUAL score. Ten percent of anonymized datasets were stripped of some sequence information.
Data Conclusion:
Results show promise for mpMRI standardization in characterization of PCa and identify key parameters that remain variable across datasets and institutions.
Evidence Level:
1.
Technical Efficacy:
Stage 2.
Trial Registration:
ClinicalTrials.gov: NCT03367702.
Insights
Multi-parametric MRI (mpMRI) standardization for prostate cancer (PCa) shows promise, but adherence to PI-RADSv2.1 minimum technical standards (MTS) varies. Key parameters like in-plane dimension and field of view require improvement for consistent imaging quality.
Area of Science:
- Radiology
- Medical Imaging
- Prostate Cancer Diagnosis
Background:
- Multi-parametric MRI (mpMRI) datasets exhibit inter-site variability due to differing acquisition protocols.
- Standardization is crucial for reliable prostate cancer (PCa) characterization using mpMRI.
Purpose of the Study:
- To evaluate the adherence of multi-site mpMRI datasets to the minimum technical standards (MTS) of PI-RADSv2.1.
- Identify specific parameters with low adherence to guide future standardization efforts.
Main Methods:
- Prospective evaluation of 600 intermediate-risk PCa patients across 124 institutions.
- Analysis of mpMRI data including T2-weighted (T2w), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) sequences.
- Assessment of adherence to PI-RADSv2.1 MTS and correlation with Prostate Imaging Quality (PI-QUAL)v2 scores.
Main Results:
- Overall adherence to PI-RADSv2.1 MTS was 82%, with >75% met for most standards.
- Low adherence observed for T2w in-plane dimension (57%) and DWI field of view (62%).
- Only 50% of datasets used recommended high b-value images for ADC map calculation; adherence improved over time and with 3T scanners.
Conclusions:
- Multi-parametric MRI standardization for PCa shows potential for improving diagnostic consistency.
- Specific parameters, including image resolution and ADC map generation, require optimization across institutions.
- Addressing these variability points is key to enhancing the reliability of mpMRI in prostate cancer assessment.
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