Multi-Site Concordance of Diffusion-Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness.
J Magn Reson Imaging
; 55(6): 1745-1758, 2022 06.
Article
em En
| MEDLINE
| ID: mdl-34767682
ABSTRACT
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 Thirty-three patients prospectively imaged prior to prostatectomy. FIELD STRENGTH/SEQUENCE 3 T, field-of-view optimized and constrained undistorted single-shot 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 mono-exponential 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. DATACONCLUSION:
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. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY Stage 3.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Próstata
/
Imagem de Difusão por Ressonância Magnética
Tipo de estudo:
Diagnostic_studies
/
Observational_studies
/
Prognostic_studies
Limite:
Humans
/
Male
Idioma:
En
Revista:
J Magn Reson Imaging
Assunto da revista:
DIAGNOSTICO POR IMAGEM
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Estados Unidos