ArticleWorld journal of surgical oncology2025
Non-invasive identification of KRAS mutation in rectal cancer using hybrid intravoxel incoherent motion and diffusion kurtosis model.
Article in World journal of surgical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Identification of KRAS mutation in rectal cancer based on a 2.5D deep learning model.Frontiers in oncology · 2026Article
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10 authors.
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Abstract
background and purposeSarcoma Viral Oncogene Homologue (KRAS) mutation status is a crucial biomarker in rectal cancer as KRAS mutations confer resistance to anti-EGFR targeted therapies and influence chemotherapy selection, affecting treatment decisions and prognosis. This study evaluates the efficacy of the hybrid intravoxel incoherent motion and diffusion kurtosis imaging (IVIM-DKI) model for non-invasive KRAS mutation identification in rectal cancer.
methodsThis prospective study included 73 patients with rectal cancer who underwent MRI scans using an IVIM-DKI sequence. KRAS mutation status was determined through histopathological analysis. The parameters derived from the hybrid IVIM-DKI model, including the apparent diffusion coefficient (ADC), true diffusion coefficient (D), diffusion kurtosis (K), perfusion fraction (f), and pseudo-diffusion coefficient (D*), were compared between the KRAS mutation group and wild-type group. The diagnostic performance was evaluated using the receiver operating characteristic (ROC) curve. The hybrid IVIM-DKI parameters and their association with clinicopathological features were also explored.
resultsSignificant differences were observed between the KRAS mutation and wild-type groups for ADC, D, and K values (p < 0.05). The K value derived from the IVIM-DKI model demonstrated the highest area under the ROC curve (AUC = 0.779) in characterizing KRAS mutation status, with a sensitivity of 88.1% and specificity of 70.3%. The ADC value also showed moderate diagnostic performance (AUC = 0.702). Specific IVIM-DKI parameters, such as f and K, were associated with various clinicopathological features, suggesting their potential as imaging biomarkers.
conclusionThe hybrid IVIM-DKI model, particularly the diffusion kurtosis parameter, shows promise as a non-invasive imaging biomarker for KRAS mutation identification in rectal cancer. This approach may facilitate early detection of anti-EGFR therapy resistance, potentially guiding personalized treatment strategies and contributing to enhanced clinical outcomes.
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