BJU international · 2026
ManUSPECTRAL - the Mannheim Urology HyperSPECTRAL Imaging Atlas of 17 Physiological Human Organs.
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Rathenborg Alexander, Klütz Vera, Grützner Paula, Hartung Luisa, Demmel Greta, Bender Christoph Julien, Sellner Jan, Seidlitz Silvia, Haney-Aubert Caelan Max, Fattal Wahid, Clanget Tilmann, Özdemir Berkin, Knoedler Samuel, Salg Gabriel Alexander, Renner Luisa, Carl Nicolas, Yu Cuyler, Leung Charlene, Edelmann Dominic, Schreck Nicholas, Michel Maurice Stephan, Maier-Hein Lena, Kowalewski Karl-Friedrich
Аннотация
OBJECTIVES: To establish a standardised intraoperative hyperspectral imaging (HSI) human organ reference dataset and to characterise spectral signatures across organ classes as a foundation for future computational and clinical applications.
SUBJECTS AND METHODS: Intraoperative assessment of anatomical structures and tissue quality such as perfusion or malignancy remains largely subjective and lacks quantitative, spatially resolved standards. Spectral imaging is a promising technology to address this ambition containing information content far beyond regular red, green, and blue light (RGB) imaging. While HSI is progressively establishing itself in medicine with certified devices, the lack of human organ-specific reference datasets appears to be the key bottleneck for future applications. In this prospective observational study, 1095 hyperspectral recordings spanning a spectral range of 500-1000 nm were acquired during 159 urological procedures. Data were obtained using medically-certified HSI systems and expert-annotations across 17 anatomical organ classes. Median reflectance spectra and derived physiological indices (tissue oxygenation index, near-infrared perfusion index, tissue water index, organ haemoglobin index, tissue haemoglobin index) were analysed, and dimensionality reduction (principal component analysis, t-distributed stochastic neighbour embedding), cosine distance, linear mixed model (LMM) and centred kernel alignment were used to assess spectral differentiability.
RESULTS: Human organs demonstrated distinct and consistent spectral fingerprints. Cosine distance showed very low within-organ distances of 0.001-0.003, indicating high consistency of normalised spectra across subjects (i.e., patients) for the same organs. There were several organ pairs with elevated distances, e.g., bone vs multiple soft tissues with values up to ~0.042 indicating clearer spectral dissimilarity between those pairs. A LMM could quantify the spectral effects of the three influencing factors to be 49.51% for organ, 18.17% for subject and 32.32% for residuals (including repetition) as mean values across the recorded spectrum.
CONCLUSION: The Mannheim Urology hyperSPECTRAL imaging atlas dataset (ManUSPECTRAL) (https://spectralverse-heidelberg.org/) provides the first standardised multi-organ hyperspectral reference dataset for human organs. By demonstrating consistent and separable organ-specific signatures, it establishes a quantitative foundation for future computational modelling and clinical validation studies for intraoperative tissue characterisation in surgery.
SUBJECTS AND METHODS: Intraoperative assessment of anatomical structures and tissue quality such as perfusion or malignancy remains largely subjective and lacks quantitative, spatially resolved standards. Spectral imaging is a promising technology to address this ambition containing information content far beyond regular red, green, and blue light (RGB) imaging. While HSI is progressively establishing itself in medicine with certified devices, the lack of human organ-specific reference datasets appears to be the key bottleneck for future applications. In this prospective observational study, 1095 hyperspectral recordings spanning a spectral range of 500-1000 nm were acquired during 159 urological procedures. Data were obtained using medically-certified HSI systems and expert-annotations across 17 anatomical organ classes. Median reflectance spectra and derived physiological indices (tissue oxygenation index, near-infrared perfusion index, tissue water index, organ haemoglobin index, tissue haemoglobin index) were analysed, and dimensionality reduction (principal component analysis, t-distributed stochastic neighbour embedding), cosine distance, linear mixed model (LMM) and centred kernel alignment were used to assess spectral differentiability.
RESULTS: Human organs demonstrated distinct and consistent spectral fingerprints. Cosine distance showed very low within-organ distances of 0.001-0.003, indicating high consistency of normalised spectra across subjects (i.e., patients) for the same organs. There were several organ pairs with elevated distances, e.g., bone vs multiple soft tissues with values up to ~0.042 indicating clearer spectral dissimilarity between those pairs. A LMM could quantify the spectral effects of the three influencing factors to be 49.51% for organ, 18.17% for subject and 32.32% for residuals (including repetition) as mean values across the recorded spectrum.
CONCLUSION: The Mannheim Urology hyperSPECTRAL imaging atlas dataset (ManUSPECTRAL) (https://spectralverse-heidelberg.org/) provides the first standardised multi-organ hyperspectral reference dataset for human organs. By demonstrating consistent and separable organ-specific signatures, it establishes a quantitative foundation for future computational modelling and clinical validation studies for intraoperative tissue characterisation in surgery.