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Updated: Mar 24, 2026
Modeling Brain Metastases Through Intracranial Injection and Magnetic Resonance Imaging
Published on: June 7, 2020
Brain metastases detection on MR by means of three-dimensional tumor-appearance template matching
Úrsula Pérez-Ramírez1, Estanislao Arana2, David Moratal1
1Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Valencia, Spain.
Purpose:
To develop and evaluate a method for an automatic detection of brain metastases in MR images.
Materials And Methods:
Nineteen patients were scanned using a 1.5 Tesla MR scanner. Two radiologists and a radiation oncologist marked the location of the brain metastases. The training group consisted of eight patients harboring 20 metastases. First, three-dimensional (3D) tumor-appearance templates were cross-correlated with MR brain images to evaluate their similarity, and a correlation threshold was established for metastasis candidates. Afterward, a method to reduce false positive rate (FPR) was applied: each detected object was segmented and its degree of anisotropy (DA) was obtained, removing the elongated structures with a DA above the optimal value from the receiver operating characteristic curve. Finally, the method was statistically validated in two groups: 11 patients with 42 brain metastases and 11 patients without metastases.
Results:
The method led to a sensitivity of 80% and an FPR per slice of 0.023 and 2.75 per patient in the training group. In the first validation group, a sensitivity of 88.10% and an FPR per slice of 0.05 corresponding to 6.91 false positives per patient were obtained. DA implementation decreased 3.5 times FPR compared with templates alone. It improved the radiologist's performance in metastases less than 10 mm from 89-93% to 100%. In the second validation group the FPR was 0.04 per slice and 5.18 per patient.
Conclusion:
This method demonstrates that 3D template matching applying DA technique has high sensitivity and low FPR for detecting brain metastases in MR images. J. Magn. Reson. Imaging 2016;44:642-652.
Insights
This study presents an automated method for detecting brain metastases in MR images using 3D template matching and a degree of anisotropy technique. The approach achieves high sensitivity and low false positive rates, improving diagnostic accuracy.
Area of Science:
- Medical Imaging
- Radiology
- Computational Pathology
Background:
- Brain metastases detection in MR images is crucial for patient management.
- Current detection methods can be time-consuming and prone to errors.
Purpose of the Study:
- To develop and evaluate an automated method for detecting brain metastases in MR images.
- To improve the accuracy and efficiency of brain metastasis detection.
Main Methods:
- Utilized 3D tumor-appearance templates for cross-correlation with MR brain images.
- Implemented a degree of anisotropy (DA) technique to reduce false positive rates by analyzing object shape.
- Validated the method on training and independent patient groups.
Main Results:
- Achieved high sensitivity (80-88.10%) and low false positive rates (FPR) per slice and per patient.
- The DA technique reduced FPR by 3.5 times compared to template matching alone.
- Improved radiologist performance for small metastases (<10mm) to 100%.
Conclusions:
- The developed 3D template matching with DA technique is effective for sensitive and accurate brain metastasis detection in MR images.
- This automated method shows potential to aid radiologists in diagnosing brain metastases.
- Further validation may support its clinical integration.
