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Diagnostic value of diffusion-weighted MRI as an imaging biomarker for ovarian cancer: A systematic review and
Rosa Alba Pugliesi1, Karim Ben Mansour2, Jonas Apitzsch3
1Section of Radiology, Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Via del Vespro 129, Palermo, 90127, Italy.
Background:
Diffusion-weighted imaging (DWI) is a functional MRI technique reflecting tissue cellularity and water diffusivity and shows promise for evaluating malignant from benign ovarian masses. However, reported diagnostic performance remains inconsistent. This systematic review and meta-analysis aimed to determine the pooled diagnostic accuracy of DWI for ovarian cancer.
Methods:
A comprehensive literature search was conducted in PubMed, Embase, Scopus, Web of Science, Cochrane Library, CINAHL, and Google Scholar from inception to October 2025. Studies reporting sensitivity and specificity of DWI for ovarian cancer were included. Two reviewers independently performed data extraction and quality assessment using the QUADAS-2 tool. Pooled sensitivity, specificity, positive and negative likelihood ratios (PLR, NLR), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristic curve (AUC) were calculated using a random-effects model. Heterogeneity was assessed with the I2 statistic, and subgroup and meta-regression analyses explored potential sources.
Results:
Seventeen studies comprising 1486 patients were included. Pooled sensitivity and specificity were 0.89 (95% CI: 0.86-0.91) and 0.83 (95% CI: 0.80-0.85), respectively. The pooled PLR was 5.38 (95% CI: 3.72-7.77), NLR 0.12 (95% CI: 0.07-0.20), and DOR 50.85 (95% CI: 27.33-94.61). The AUC was 0.93, indicating excellent diagnostic performance. Substantial heterogeneity was observed (I2 > 75%) and was not explained by study design, MRI field strength, or ADC thresholds.
Conclusion:
DWI demonstrates high pooled sensitivity and specificity for differentiating benign from malignant ovarian lesions with substantial heterogeneity across studies. Therefore, DWI should be considered a promising non-invasive, not standalone diagnostic tool.
