Resection-inspired histopathological diagnosis of cerebral cavernous malformations using quantitative multiphoton...

Area of Science:

• Neuroscience
• Medical Imaging
• Pathology

Background:

• Cerebral cavernous malformations (CCM) often cause drug-resistant epilepsy due to recurring microhemorrhages.
• Current surgical resection relies on subjective visual identification of CCM lesions and hemosiderin rims.
• Precise resection is crucial for effective seizure control in CCM-associated epilepsy.

Purpose of the Study:

• To introduce quantitative multiphoton microscopy (qMPM) as a histopathology-level diagnostic tool for CCM.
• To assist neurosurgeons in achieving precise resection of CCM lesions and surrounding tissue.
• To enhance intraoperative and postoperative diagnosis of CCM-related epilepsy.

Main Methods:

• qMPM was used to image 35 tissue specimens from 12 patients with CCM-related epilepsy.
• Label-free, multi-channel imaging captured spectral characteristics of CCM tissues.
• Custom algorithms were developed for vascular pattern classification, hemorrhage visualization, and virtual staining (CCM-stainGAN).

Main Results:

• qMPM successfully imaged malformed vasculature and hemosiderin deposits in CCM lesions.
• A vascular pattern classifier achieved 0.97 area under the ROC curve; hemorrhage regions were mapped quantitatively.
• CCM-stainGAN demonstrated 98.8% accuracy in diagnosing CCM histopathological features via virtual staining.

Conclusions:

• qMPM provides high-resolution, quantitative assessment for definitive CCM histopathological diagnosis.
• The technology offers decision support for precise surgical resection guidance in CCM-associated epilepsy.
• This work advances optical diagnostic instruments and applications for epilepsy management.