Registration of Image Modalities for Analyses of Tissue Samples Using 3D Image Modelling.

Area of Science:

• Biomedical imaging
• Computational pathology
• Mass spectrometry imaging

Background:

• Biopsies are crucial for diagnosing diseases using histopathological, molecular, proteomic, and imaging data.
• Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is an advanced technique for molecular imaging of biological tissues.

Purpose of the Study:

• To develop a 3D model of biopsies and whole organs by registering MALDI MSI datasets with histological staining data.
• To establish an automated registration system for cross-process evaluation and 3D model creation.

Main Methods:

• A global, deformable Schatten-q-Norm registration approach was employed for aligning image modalities.
• Connected-component segmentation and principal-axis based linear pre-registration were used for image alignment and background removal.
• 3D reconstruction of histological and MALDI MSI data was performed.

Main Results:

• An automated system for registering multimodal image data (MALDI MSI and histology) was successfully developed.
• The developed system enables the creation of 3D models from diverse tissue imaging datasets.
• The registration accuracy of MALDI MSI with histological data was evaluated using the established system.

Conclusions:

• This multimodal image registration approach facilitates molecular analyses of tissue specimens.
• The developed 3D modeling technique has potential applications in clinical research and diagnosis.
• The study establishes a foundation for integrating imaging and molecular data in pathology.