Quantitation of Tissue Resection Using a Brain Tumor Model and 7-T Magnetic Resonance Imaging Technology.

Area of Science:

• Neurosurgery
• Medical Imaging
• Biomedical Engineering

Background:

• Animal brain tumor models offer risk-free neurosurgical resident training.
• Current Magnetic Resonance Imaging (MRI) technologies lack quantitative assessment of tissue removal in these models.
• This study explores the use of 7-Tesla MRI for quantitative assessment in neurosurgical procedures.

Purpose of the Study:

• To demonstrate the feasibility of using animal brain tumor models with 7-Tesla MRI.
• To quantitatively assess tissue removal, including tumor, gray matter, and white matter, during subpial tumor resection.
• To evaluate the potential of 7-Tesla MRI in improving surgical training and operative procedure assessment.

Main Methods:

• Utilized seven ex vivo calf brain hemispheres for methodology development.
• Employed 7-Tesla MRI segmentation to quantify tissue removal in three brains.
• Created alginate artificial brain tumors in four brains to test quantitative assessment of tumor and normal tissue removal during subpial resection.

Main Results:

• Established a correlation between removed brain tissue weight and volume measured by 7-Tesla MRI.
• Quantified removed tumor, gray matter, and white matter volumes using segmented 7-Tesla MRIs.
• Detected alterations in surrounding gray and white matter post-resection.

Conclusions:

• 7-Tesla MRI combined with animal brain tumor models enhances data granularity in surgical procedures.
• This approach improves the assessment and training of neurosurgical residents.
• The study serves as a proof of concept for advanced quantitative surgical assessment.