Radiomics approach to distinguish between benign and malignant soft tissue tumors on magnetic resonance imaging
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View abstract on PubMed
Summary
This summary is machine-generated.This study developed a radiomics signature using MRI scans to differentiate between benign and malignant soft tissue neoplasms (STTs). The signature showed high accuracy, aiding in preoperative diagnosis and treatment planning for STTs.
Area Of Science
- Radiology
- Medical Imaging
- Oncology
Background
- Soft tissue neoplasms (STTs) present a diagnostic challenge, often requiring invasive procedures.
- Accurate preoperative differentiation between benign and malignant STTs is crucial for effective treatment planning.
Purpose Of The Study
- To develop a radiomics signature from MRI images for preoperative identification of benign versus malignant STTs.
- To evaluate the diagnostic performance of the developed radiomics signature.
Main Methods
- A cohort of 193 patients with STTs was randomly divided into training (70%) and validation (30%) sets.
- Radiomics features were extracted from T2 and T1-weighted MRI sequences with fat saturation and gadolinium contrast.
- A radiomics signature was constructed using the least absolute shrinkage and selection operator (LASSO) logistic regression model.
Main Results
- A radiomics signature comprising 16 features (5 shape, 11 wavelet) demonstrated favorable predictive efficacy.
- Malignant STTs exhibited significantly higher radiomics scores than benign STTs in both training and validation cohorts.
- The radiomics signature achieved high diagnostic performance with Area Under the Curve (AUC) values of 0.885 (training) and 0.841 (validation).
Conclusions
- A radiomics signature derived from MRI images serves as a reliable imaging biomarker for distinguishing benign from malignant STTs.
- This non-invasive approach can assist clinicians in guiding appropriate treatment strategies for patients with STTs.
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