Computers in biology and medicine · 2025
Advancing multispectral optoacoustic tomography (MSOT): Phasor analysis for real-time spectral unmixing.
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Di Giacinto Flavio, Riente Alessia, Mignini Irene, Ainora Maria Elena, Esposto Giorgio, Borriello Raffaele, Zocco Maria Assunta, Minordi Laura Maria, Sala Evis, Scaldaferri Franco, Gasbarrini Antonio, De Spirito Marco, Maulucci Giuseppe
Аннотация
BACKGROUND: Multispectral optoacoustic tomography (MSOT) merges optical and ultrasound imaging to generate high-resolution, molecularly specific images. By capturing ultrasound emissions at multiple wavelengths, MSOT enables real-time visualization of tissue slices or volumes. The technique's specificity relies on chromophores emitting distinct signals across different wavelengths, requiring accurate spectral unmixing. However, existing unmixing methods are computationally demanding and often difficult to evaluate, limiting their applicability in real-time scenarios.
METHOD: We present a phasor-based approach as a fast and intuitive solution for spectral component quantification in MSOT. By projecting multispectral data onto a two-dimensional phasor plane, this method enables direct visualization of spectral components and rapid detection of unexpected signals or artifacts. The approach was validated using optically characterized experimental phantoms with flowing blood, allowing comparison with linear mixing models (LMM). It was then applied to clinical MSOT images from Crohn's disease patients and healthy controls.
RESULTS: The phasor method facilitated the identification of artifacts and spectral anomalies, significantly improving interpretability of MSOT data. It also outperformed conventional unmixing algorithms in terms of processing speed, making it suitable for real-time application. In clinical datasets, the method revealed distinct spectral patterns between Crohn's disease patients and healthy individuals, highlighting its ability to detect changes and differences in biologically complex systems.
CONCLUSIONS: This work establishes the phasor approach as a powerful tool for MSOT spectral unmixing, offering both speed and clarity in data interpretation. Its real-time capability and diagnostic potential support broader clinical adoption of MSOT for noninvasive disease characterization.
METHOD: We present a phasor-based approach as a fast and intuitive solution for spectral component quantification in MSOT. By projecting multispectral data onto a two-dimensional phasor plane, this method enables direct visualization of spectral components and rapid detection of unexpected signals or artifacts. The approach was validated using optically characterized experimental phantoms with flowing blood, allowing comparison with linear mixing models (LMM). It was then applied to clinical MSOT images from Crohn's disease patients and healthy controls.
RESULTS: The phasor method facilitated the identification of artifacts and spectral anomalies, significantly improving interpretability of MSOT data. It also outperformed conventional unmixing algorithms in terms of processing speed, making it suitable for real-time application. In clinical datasets, the method revealed distinct spectral patterns between Crohn's disease patients and healthy individuals, highlighting its ability to detect changes and differences in biologically complex systems.
CONCLUSIONS: This work establishes the phasor approach as a powerful tool for MSOT spectral unmixing, offering both speed and clarity in data interpretation. Its real-time capability and diagnostic potential support broader clinical adoption of MSOT for noninvasive disease characterization.