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Correlation of IVIM/DKI Parameters with Hypoxia Biomarkers in Fibrosarcoma Murine Models: Direct Control of MRI and
Zhiqing Duan1, Juan Tao2, Wenyu Liu1
1Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, Liaoning Province, China (Z.D., W.L., Y.L., S.F., Y.Y., X.L., X.D., Y.S., S.W.).
Rationale And Objectives:
To investigate whether intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters correlate with hypoxia biomarkers, namely hypoxia inducible factor-1ɑ (HIF-1ɑ), carbonic anhydrase IX (CAIX), and pimonidazole (PIMO), in fibrosarcoma (FS) murine models.
Materials And Methods:
A model of 30 FS nude mice was established. All mice underwent magnetic resonance imaging (MRI) scans after which the IVIM (standard apparent diffusion coefficient [standard ADC], pure diffusion coefficient [D], pseudo-diffusion coefficient [D*], and perfusion fraction [f]) and DKI parameters (mean diffusion [MD], mean kurtosis [MK]) were obtained. Based on an MRI-pathology controlled method, correlations between each MRI parameter and hypoxia biomarkers were assessed by Pearson or Spearman tests. An independent sample t-test or Wilcoxon's rank sum test, and receiver operating characteristic curves were used to identify whether MRI parameters could differentiate between high and low expressions of hypoxia biomarkers.
Results:
The IVIM/DKI parameters showed varying degrees of correlation with HIF-1α, CAIX, and PIMO expression. Among them, the D, f, and MK values could confirm HIF-1α expression, while D, f, and MK values could assess CAIX expression. Finally, standard D and MK values could evaluate PIMO expression levels.
Conclusion:
IVIM and DKI parameters can be used to reflect hypoxic biomarkers of FS and have the potential to detect tumor hypoxia.
Insights
Intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters correlate with tumor hypoxia biomarkers in fibrosarcoma models. These advanced MRI techniques show potential for detecting and assessing tumor hypoxia.
Area of Science:
- Radiology and Medical Imaging
- Oncology
- Biomarker Discovery
Background:
- Tumor hypoxia is a critical factor influencing cancer progression and treatment resistance.
- Accurate non-invasive methods to assess tumor hypoxia are essential for effective fibrosarcoma management.
- Intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) are advanced MRI techniques offering insights into tissue microstructure and microperfusion.
Purpose of the Study:
- To investigate the correlation between IVIM and DKI MRI parameters and key hypoxia biomarkers in a fibrosarcoma murine model.
- To determine if these advanced MRI parameters can non-invasively reflect the expression levels of hypoxia-inducible factor-1α (HIF-1α), carbonic anhydrase IX (CAIX), and pimonidazole (PIMO).
- To assess the potential of IVIM and DKI parameters in detecting and evaluating tumor hypoxia.
Main Methods:
- Establishment of a fibrosarcoma (FS) nude mouse model (n=30).
- Acquisition of magnetic resonance imaging (MRI) data, including IVIM (standard ADC, D, D*, f) and DKI (MD, MK) parameters.
- Correlation analysis (Pearson/Spearman) between MRI parameters and hypoxia biomarkers (HIF-1α, CAIX, PIMO) using MRI-pathology correlation.
- Receiver operating characteristic (ROC) curve analysis to evaluate the ability of MRI parameters to differentiate between high and low biomarker expressions.
Main Results:
- IVIM and DKI parameters demonstrated varying degrees of correlation with HIF-1α, CAIX, and PIMO expression.
- Specific parameters, including D, f, and MK, showed significant correlations and could assess HIF-1α and CAIX expression.
- Standard D and MK values were found to be effective in evaluating PIMO expression levels.
Conclusions:
- IVIM and DKI parameters are capable of reflecting tumor hypoxia biomarkers in fibrosarcoma.
- These advanced MRI techniques hold significant potential for the non-invasive detection and assessment of tumor hypoxia.
- The findings support the use of IVIM and DKI as valuable tools in preclinical fibrosarcoma research and potentially in clinical settings.
