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Multimodal molecular 3D imaging for the tumoral volumetric distribution assessment of folate-based biosensors
Gerardo J Ramírez-Nava1,2, Clara L Santos-Cuevas3, Isaac Chairez4
1Instituto Nacional de Investigaciones Nucleares (ININ), 52750, Ocoyoacac, Estado de México, Mexico.
Abstract:
The aim of this study was to characterize the in vivo volumetric distribution of three folate-based biosensors by different imaging modalities (X-ray, fluorescence, Cerenkov luminescence, and radioisotopic imaging) through the development of a tridimensional image reconstruction algorithm. The preclinical and multimodal Xtreme imaging system, with a Multimodal Animal Rotation System (MARS), was used to acquire bidimensional images, which were processed to obtain the tridimensional reconstruction. Images of mice at different times (biosensor distribution) were simultaneously obtained from the four imaging modalities. The filtered back projection and inverse Radon transformation were used as main image-processing techniques. The algorithm developed in Matlab was able to calculate the volumetric profiles of 99mTc-Folate-Bombesin (radioisotopic image), 177Lu-Folate-Bombesin (Cerenkov image), and FolateRSense™ 680 (fluorescence image) in tumors and kidneys of mice, and no significant differences were detected in the volumetric quantifications among measurement techniques. The imaging tridimensional reconstruction algorithm can be easily extrapolated to different 2D acquisition-type images. This characteristic flexibility of the algorithm developed in this study is a remarkable advantage in comparison to similar reconstruction methods.
Insights
This study developed a 3D image reconstruction algorithm to analyze folate-based biosensor distribution in mice using multiple imaging techniques. The algorithm accurately quantified biosensor volumes, showing no significant differences between methods.
Area of Science:
- Medical Imaging
- Biomedical Engineering
- Molecular Imaging
Background:
- Folate-based biosensors are crucial for targeted imaging.
- Accurate in vivo volumetric quantification is essential for assessing biosensor distribution.
- Multimodal imaging offers complementary information but requires robust data integration.
Purpose of the Study:
- To develop and validate a 3D image reconstruction algorithm for multimodal in vivo biosensor imaging.
- To characterize the volumetric distribution of three distinct folate-based biosensors.
- To compare volumetric quantification across X-ray, fluorescence, Cerenkov luminescence, and radioisotopic imaging modalities.
Main Methods:
- Development of a 3D image reconstruction algorithm using filtered back projection and inverse Radon transformation in MATLAB.
- Acquisition of simultaneous 2D images from four modalities (X-ray, fluorescence, Cerenkov, radioisotopic) using the Xtreme imaging system and MARS.
- Calculation of volumetric profiles for 99mTc-Folate-Bombesin, 177Lu-Folate-Bombesin, and FolateRSense™ 680 in mouse tumors and kidneys.
Main Results:
- The developed algorithm successfully reconstructed 3D volumetric data from multimodal 2D images.
- No significant differences were found in volumetric quantifications between the different imaging techniques.
- The algorithm accurately calculated biosensor distribution in tumors and kidneys.
Conclusions:
- The novel 3D image reconstruction algorithm provides accurate and comparable volumetric quantification of folate-based biosensors across multiple imaging modalities.
- The algorithm's flexibility allows for easy extrapolation to other 2D imaging data, offering a significant advantage.
- This tool enhances the preclinical assessment of targeted biosensors for improved diagnostic and therapeutic strategies.
