Quantitative Research Data
Description
The study hypothesized that quantitative MRI parameters, specifically Ktrans and ADC can non-invasively differentiate osteosarcoma histologic subtypes by reflecting underlying differences in vascular permeability and tumor cellularity. Multiparametric MRI data were collected from 43 patients using 3T DWI and DCE-MRI protocols. The data demonstrated that K^trans and ADC significantly varied across subtypes, with chondroblastic osteosarcoma showing higher Ktrans compared to osteoblastic forms, suggesting greater microvascular permeability within the chondroid stroma. These findings indicate that perfusion and diffusion metrics can serve as imaging biomarkers of osteosarcoma heterogeneity. Clinically, the results highlight the role of radiology as a quantitative diagnostic tool in precision oncology, enhancing subtype differentiation, guiding treatment monitoring, and potentially reducing dependence on invasive biopsy. The dataset enables replication of this workflow for validation or radiomics-based prognostic modeling in future studies.
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The data were obtained retrospectively from 43 patients with histologically confirmed osteosarcoma who underwent MRI at RSUD Dr. Soetomo Hospital, Surabaya. MRI acquisition included diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI using a 3T Siemens Magnetom scanner. ADC maps were generated using mono-exponential fitting, and DCE-MRI parameters (Ktrans, Kep, Ve) were calculated using Tofts pharmacokinetic modeling via Syngo.via software (Siemens Healthcare). Statistical analysis was performed using SPSS version 26, employing the Kruskal–Wallis test and ROC curve analysis. All procedures adhered to ethical approval No. 1908/LOE/301.4.2/II/2025, and patient data were anonymized prior to analysis.
Institutions
- Universitas Airlangga Fakultas Kedokteran