Rule-based semi-automated method to segment black hole multiple sclerosis lesions on post-gadolinium 2D T1-weighted brain images - Scorecard - MDSpire

Rule-based semi-automated method to segment black hole multiple sclerosis lesions on post-gadolinium 2D T1-weighted brain images

  • By

  • Rozemarijn M. Mattiesing

  • Fleur A. Groeneveld

  • Iman Brouwer

  • Ronald A. van Schijndel

  • Frederik Barkhof

  • Henk J. M. M. Mutsaerts

  • Hugo Vrenken

  • May 2, 2026

  • 0 min

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Clinical Scorecard: Automated Segmentation of Black Hole Lesions in Multiple Sclerosis Using a Rule-Based Approach on Post-Gadolinium 2D T1-Weighted Brain MRI

At a Glance

CategoryDetail
Condition
Key Mechanisms
Target PopulationPatients with clinically isolated syndrome and early MS.
Care Setting

Key Highlights

  • Study findings may improve clinical decision-making regarding MS management.

Guideline-Based Recommendations

Diagnosis

    Management

      Monitoring & Follow-up

      • Regular MRI assessments every 6-12 months to evaluate changes in black hole lesions over time.

      Risks

        Patient & Prescribing Data

        Subcutaneous interferon beta-1a was assessed for longitudinal effects on black hole lesions.

        Clinical Best Practices

        • Ensure quality control of MRI input images before analysis.
        • Use consensus decisions among experienced radiologists for complex cases.
        • Provide training for radiologists on the use of automated methods.

        References

        Original Source(s)

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