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Intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced MRI for predicting parametrial invasion in cervical cancer.
- Source :
-
Abdominal Radiology . Sep2024, Vol. 49 Issue 9, p3232-3240. 9p. - Publication Year :
- 2024
-
Abstract
- Purpose: This study aimed to assess the predictive efficacy of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in parametrial invasion (PMI) in cervical cancer patients. Methods: A total of 83 cervical cancer patients (32 PMI-positive and 51 PMI-negative) retrospectively underwent pretreatment IVIM-DWI and DCE-MRI scans. IVIM-DWI parameters included apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D*), and perfusion fraction (f). DCE-MRI parameters included volume transfer constant (Ktrans), flux rate constant (Kep), and fractional extravascular extracellular space volume (Ve). Logistic regression analyses were conducted to identify independent variables associated with PMI. Receiver operating characteristic curves were generated to assess the predictive performance of significant parameters. Results: Multivariable analysis revealed that the MRI parameters D (odds ratio [OR]: 7.05; 95% CI 1.78–27.88; P = 0.005), D* (OR 6.58; 95% CI 1.49–29.10; P = 0.01), f (OR 5.12; 95% CI 1.23–21.37; P = 0.03), Ktrans (OR 4.60; 95% CI 1.19–17.81; P = 0.03), and Kep (OR 4.90; 95% CI 1.25–19.18; P = 0.02) were independent predictors of PMI in cervical cancer patients. The combined parameter incorporating these parameters demonstrated the highest performance in predicting PMI, yielding an area under the curve of 0.906, sensitivity of 84.4%, and specificity of 86.3%. Conclusion: The proposed combined parameter exhibited favorable performance in identifying PMI in cervical cancer patients. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 2366004X
- Volume :
- 49
- Issue :
- 9
- Database :
- Academic Search Index
- Journal :
- Abdominal Radiology
- Publication Type :
- Academic Journal
- Accession number :
- 179144173
- Full Text :
- https://doi.org/10.1007/s00261-024-04339-z