Utilizing 3D printing technology to merge MRI with histology: A protocol for brain sectioning

Nicholas J. Luciano, Pascal Sati, Govind Nair, Joseph R. Guy, Seung Kwon Ha, Martina Absinta, Wen Yang Chiang, Emily C. Leibovitch, Steven Jacobson, Afonso C. Silva, Daniel S. Reich

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume three-dimensionally. While MRI is an extremely sensitive tool for detecting tissue abnormalities, association of signal changes with an underlying pathological process is usually not straightforward. In the central nervous system, for example, inflammation, demyelination, axonal damage, gliosis, and neuronal death may all induce similar findings on MRI. As such, interpretation of MRI scans depends on the context, and radiological-histopathological correlation is therefore of the utmost importance. Unfortunately, traditional pathological sectioning of brain tissue is often imprecise and inconsistent, thus complicating the comparison between histology sections and MRI. This article presents novel methodology for accurately sectioning primate brain tissues and thus allowing precise matching between histology and MRI. The detailed protocol described in this article will assist investigators in applying this method, which relies on the creation of 3D printed brain slicers. Slightly modified, it can be easily implemented for brains of other species, including humans.

Original languageEnglish (US)
Article numbere54780
JournalJournal of Visualized Experiments
Issue number118
StatePublished - Dec 6 2016


  • 3D printing
  • Brain
  • Histology
  • Human
  • Issue 118
  • MRI
  • Marmoset
  • Neuroscience

ASJC Scopus subject areas

  • General Neuroscience
  • General Chemical Engineering
  • General Biochemistry, Genetics and Molecular Biology
  • General Immunology and Microbiology


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