CDC STACKS serves as an archival repository of CDC-published products including scientific findings, journal articles, guidelines, recommendations, or other public health information authored or co-authored by CDC or funded partners.
As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.
i
Multi-site concordance of diffusion weighted imaging quantification for assessing prostate cancer aggressiveness
-
6 2022
-
-
Source: J Magn Reson Imaging. 55(6):1745-1758
[PDF-2.75 MB]
Details:
-
Alternative Title:J Magn Reson Imaging
-
Personal Author:
-
Description:Background:
Diffusion weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease.
Purpose:
To compare 14 site-specific parametric fitting implementations applied to the same dataset of whole mount-pathologically validated DWI to test the hypothesis that cancer differentiation varies with different fitting algorithms.
Study Type:
Prospective
Population:
33 patients prospectively imaged prior to prostatectomy.
Field Strength/Sequence:
3T, field-of-view optimized and constrained undistorted single-shot (FOCUS) DWI sequence.
Assessment:
Datasets, including a noise-free digital reference object (DRO), were distributed to the 14 teams, where locally implemented DWI parameter maps were calculated, including monoexponential apparent diffusion coefficient (MEADC), kurtosis (K), diffusion kurtosis (DK), bi-exponential diffusion (BID), pseudo-diffusion (BID*), and perfusion fraction (F). The resulting parametric maps were centrally analyzed, where differentiation of benign from cancerous tissue was compared between DWI parameters and the fitting algorithms with a receiver operating characteristic area under the curve (ROC AUC).
Statistical Test:
Levene’s test, p<0.05 corrected for multiple comparisons was considered statistically significant.
Results:
The DRO results indicated minimal discordance between sites. Comparison across sites indicated that K, DK, and MEADC had significantly higher prostate cancer detection capability (AUC range = 0.72–0.76, 0.76–0.81, and 0.76–0.80 respectively) as compared to bi-exponential parameters (BID, BID*, F) which had lower AUC and greater between site variation (AUC range = 0.53–0.80, 0.51–0.81, and 0.52–0.80 respectively). Post-processing parameters also affected the resulting AUC, moving from for example, 0.75 to 0.87 for MEADC varying cluster size.
Data Conclusion:
We found that conventional diffusion models had consistent performance at differentiating prostate cancer from benign tissue. Our results also indicated that post-processing decisions on DWI data can affect sensitivity and specificity when applied to radiological-pathological studies in prostate cancer.
-
Subjects:
-
Source:
-
Pubmed ID:34767682
-
Pubmed Central ID:PMC9095769
-
Document Type:
-
Funding:
-
Volume:55
-
Issue:6
-
Collection(s):
-
Main Document Checksum:
-
Download URL:
-
File Type:
