Acquisition models in intraoperative positron surface imaging.

Area of Science:

• Medical Imaging
• Nuclear Medicine
• Surgical Oncology

Background:

• Intraoperative imaging is crucial for identifying residual brain tumors during surgery.
• Positron Surface Imaging (PSI) with [18F]-based radiotracers offers potential for improved detection of tumor resection margins.
• Existing PSI acquisition models lack comparative validation.

Purpose of the Study:

• To comparatively validate different Positron Surface Imaging (PSI) acquisition models for intraoperative brain tumor detection.
• To establish a reference-based validation framework for assessing PSI performance.
• To evaluate models based on efficiency, computational speed, spatial accuracy, and tumor contrast.

Main Methods:

• Investigated performance of multiple PSI acquisition models using defined validation criteria and normalized metrics.
• Developed a reference-based framework for comparative analysis against a basic method.
• Estimated model performance across efficiency, computational speed, spatial accuracy, and tumor contrast.

Main Results:

• Several acquisition models demonstrated superior performance over the basic method, though real-time capabilities were sometimes reduced.
• One model achieved the highest performance, showing excellent efficiency (1-Spe: 0.1, Se: 0.94), spatial accuracy (max Dice: 0.77), and tumor contrast (max T/B: 5.2).
• Reconstruction quality showed minimal improvement beyond a specific sampling rate threshold.

Conclusions:

• The developed validation method effectively compared PSI acquisition models, identifying an optimal model.
• This approach can be extended to 3D datasets for validating future PSI models in intraoperative brain surgery guidance.
• The findings support enhanced intraoperative tumor margin detection and improved patient outcomes.