Amyloid : the international journal of experimental and clinical investigation : the official journal of the International Society of Amyloidosis · 2025
Single-slide detection and typing of AL renal amyloidosis: combining mass spectrometry imaging and digital pathology.
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Bindi Greta, Cazzaniga Giorgio, Alberici Federico, Mescia Federica, Mannino Mauro, Maggioni Alice, Galimberti Stefania, Capitoli Giulia, Fisogni Simona, Magni Fulvio, Pagni Fabio, Smith Andrew, L'Imperio Vincenzo
Аннотация
BACKGROUND: Amyloid typing, particularly in monoclonal gammopathies of renal significance, can be technically challenging. Matrix-Assisted Laser Desorption/Ionisation-Mass Spectrometry Imaging (MALDI-MSI) has been proposed as a non-destructive method to detect and type amyloid deposits on a single tissue slide. This study aims to confirm this capability of MALDI-MSI in renal light chain amyloidosis (AL amyloidosis), irrespective of the fixative utilised, confronting results with other traditional and upcoming methods for amyloid detection.
METHODOLOGY: MALDI-MSI was applied to 15 renal biopsies diagnosed with AL amyloidosis. Results were compared with the routinely utilised methods of amyloid detection and typing, respectively, the pathologist's evaluation and immunofluorescence (IF) and additionally with a computational technique for amyloid detection, SPADA (Streamlined Pipeline for Amyloid Detection through Congo red fluorescence digital Analysis).
RESULTS: MALDI-MSI demonstrated an agreement of 85.0% and 86.4% with SPADA and the pathologist in detecting glomerular deposits. It also showed complementary potential with SPADA, suggesting the possibility of combining all methodologies on a single tissue slide. Furthermore, MALDI-MSI showed a complete agreement with IF in amyloid typing.
CONCLUSION: This study confirmed the capability of MALDI-MSI to detect and type AL amyloidosis, assessing the possibility to integrate an additional computational method for amyloid detection on a single tissue slide.
METHODOLOGY: MALDI-MSI was applied to 15 renal biopsies diagnosed with AL amyloidosis. Results were compared with the routinely utilised methods of amyloid detection and typing, respectively, the pathologist's evaluation and immunofluorescence (IF) and additionally with a computational technique for amyloid detection, SPADA (Streamlined Pipeline for Amyloid Detection through Congo red fluorescence digital Analysis).
RESULTS: MALDI-MSI demonstrated an agreement of 85.0% and 86.4% with SPADA and the pathologist in detecting glomerular deposits. It also showed complementary potential with SPADA, suggesting the possibility of combining all methodologies on a single tissue slide. Furthermore, MALDI-MSI showed a complete agreement with IF in amyloid typing.
CONCLUSION: This study confirmed the capability of MALDI-MSI to detect and type AL amyloidosis, assessing the possibility to integrate an additional computational method for amyloid detection on a single tissue slide.