Brain dissection photogrammetry: a tool for studying human white matter connections integrating ex vivo and in vivo multimodal datasets

Understanding the architecture of the white matter of the human brain is central to neuroscience and clinics. Despite major advances in tractography and white matter dissection, integrating these complementary techniques remains a longstanding challenge. Here, we introduce BraDiPho (Brain Dissection Photogrammetry), an open-access resource of high-resolution, fully textured 3D digital models of layer-by-layer white matter microdissection. The models are registered to their radiological space, allowing direct alignment of dissection and neuroimaging data. BraDiPho includes eight hemispheres, enriched with sample tractography bundles, anatomical annotations, and cortical atlases, establishing a unified framework for multimodal analyses. Four case studies demonstrate how BraDiPho supports anatomically grounded investigations, moving beyond classical side-by-side comparisons toward accurate integration of ex vivo dissection and in vivo tractography. All data, tools, and scripts are openly available, enabling customized research and educational applications. BraDiPho offers a framework to support multimodal investigations of human brain connectivity in both research and educational contexts.

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Publication Details

Journal
Nature Communications
Published
2025-11-06
DOI
https://doi.org/10.1038/s41467-025-64788-y
Citations
2
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.72

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article

Brain dissection photogrammetry: a tool for studying human white matter connections integrating ex vivo and in vivo multimodal datasets

Alessandro De Benedictis, Luciano Annicchiarico, François Rheault, Luca Zigiotto et al.
2 citations
Nature Communications
Advanced Neuroimaging Techniques and Applications
2.72
article

Brain dissection photogrammetry: a tool for studying human white matter connections integrating ex vivo and in vivo multimodal datasets

Alessandro De Benedictis, Luciano Annicchiarico, François Rheault, Luca Zigiotto, Umberto Rozzanigo, Paolo Avesani, Laura Vavassori, Erica Nocerino, Mattia Barbareschi, Laurent Petit, Silvio Sarubbo, Francesco Corsini
article en
2 citations

Abstract

Understanding the architecture of the white matter of the human brain is central to neuroscience and clinics. Despite major advances in tractography and white matter dissection, integrating these complementary techniques remains a longstanding challenge. Here, we introduce BraDiPho (Brain Dissection Photogrammetry), an open-access resource of high-resolution, fully textured 3D digital models of layer-by-layer white matter microdissection. The models are registered to their radiological space, allowing direct alignment of dissection and neuroimaging data. BraDiPho includes eight hemispheres, enriched with sample tractography bundles, anatomical annotations, and cortical atlases, establishing a unified framework for multimodal analyses. Four case studies demonstrate how BraDiPho supports anatomically grounded investigations, moving beyond classical side-by-side comparisons toward accurate integration of ex vivo dissection and in vivo tractography. All data, tools, and scripts are openly available, enabling customized research and educational applications. BraDiPho offers a framework to support multimodal investigations of human brain connectivity in both research and educational contexts.

Nature CommunicationsVol. 16(1)
Centre National de la Recherche Scientifique (FR), Université de Sherbrooke (CA), Université de Bordeaux (FR), University of Sassari (IT), University of Trento (IT), Fondazione Bruno Kessler (IT), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Provincia Autonoma di Trento (IT), Bambino Gesù Children's Hospital (IT), Istituti di Ricovero e Cura a Carattere Scientifico (IT)
Université de Sherbrooke, Centre National de la Recherche Scientifique
Openalex Percentile: Top 8%
Advanced Neuroimaging Techniques and Applications
2.72
DOIOpen Access PDFOpenAlex
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