Advanced Sectioned Images of a Cadaver Head with Voxel Size of 0.04 mm

Background The sectioned images of a cadaver head made from the Visible Korean project have been used for research and educational purposes. However, the image resolution is insufficient to observe detailed structures suitable for experts. In this study, advanced sectioned images with higher resolution were produced for the identification of more detailed structures. Methods The head of a donated female cadaver was scanned for 3 Tesla magnetic resonance images and diffusion tensor images (DTIs). After the head was frozen, the head was sectioned serially at 0.04-mm intervals and photographed repeatedly using a digital camera. Results On the resulting 4,000 sectioned images (intervals and pixel size, 0.04 mm3; color depth, 48 bits color; a file size, 288 Mbytes), minute brain structures, which can be observed not on previous sectioned images but on microscopic slides, were observed. The voxel size of this study (0.04 mm3) was very minute compared to our previous study (0.1 mm3; resolution, 4,368 × 2,912) and Visible Human Project of the USA (0.33 mm3; resolution, 2,048 × 2,048). Furthermore, the sectioned images were combined with tractography of the DTIs to elucidate the white matter with high resolution and the actual color of the tissue. Conclusion The sectioned images will be used for diverse research, including the applications for the cross sectional anatomy and three-dimensional models for virtual experiments.

[1]  Christopher Rorden,et al.  The first step for neuroimaging data analysis: DICOM to NIfTI conversion , 2016, Journal of Neuroscience Methods.

[2]  D. Ryugo,et al.  A modified Golgi staining protocol for use in the human brain stem and cerebellum , 2006, Journal of Neuroscience Methods.

[3]  J. Seo,et al.  A Review of Three-Dimensional Printing Technology for Medical Applications , 2019, Journal of the Korean Society of Radiology.

[4]  Joshua H. Park,et al.  Numerical evaluation of image homogeneity, signal‐to‐noise ratio, and specific absorption rate for human brain imaging at 1.5, 3, 7, 10.5, and 14T in an 8‐channel transmit/receive array , 2015, Journal of magnetic resonance imaging : JMRI.

[5]  Paul Brown,et al.  Virtual Dissection Table Including the Visible Korean Images, Complemented by Free Software of the Same Data , 2015 .

[6]  Min Suk Chung,et al.  Accessible and Informative Sectioned Images, Color‐Coded Images, and Surface Models of the Ear , 2013, Anatomical record.

[7]  Jin Seo Park,et al.  Real-Color Volume Models Made from Real-Color Sectioned Images of Visible Korean , 2019, Journal of Korean medical science.

[8]  Jin Seo Park,et al.  Software for browsing sectioned images of a dog body and generating a 3D model. , 2016, Anatomical record.

[9]  PhD Jean C. Tamraz MD,et al.  Atlas of Regional Anatomy of the Brain Using MRI , 2000, Springer Berlin Heidelberg.

[10]  Goran Štrkalj,et al.  The application of 3D printing in anatomy education , 2015, Medical education online.

[11]  Min Suk Chung,et al.  Improved Software to Browse the Serial Medical Images for Learning , 2017, Journal of Korean medical science.

[12]  Jin Seo Park,et al.  Ten Triangles around Cavernous Sinus for Surgical Approach, Described by Schematic Diagram and Three Dimensional Models with the Sectioned Images , 2016, Journal of Korean medical science.

[13]  E. Jones.  Stereotactic Atlas of the Human Thalamus and Basal Ganglia, A. Morel. Informa Healthcare, New York (2007), Price: US$ 229.95 , 2008 .

[14]  Rhys Gethin Thomas,et al.  Augmented Reality for Anatomical Education , 2010, Journal of visual communication in medicine.

[15]  P. Kaufman,et al.  Loss of neurons in magnocellular and parvocellular layers of the lateral geniculate nucleus in glaucoma. , 2000, Archives of ophthalmology.

[16]  K. Baer,et al.  Immunohistochemical staining of post-mortem adult human brain sections , 2006, Nature Protocols.

[17]  Chan Hyeong Kim,et al.  A polygon-surface reference Korean male phantom (PSRK-Man) and its direct implementation in Geant4 Monte Carlo simulation , 2011, Physics in medicine and biology.

[18]  Z. Cho.  Review of Recent Advancement of Ultra High Field Magnetic Resonance Imaging: from Anatomy to Tractography , 2016 .

[19]  Katrin Amunts,et al.  White matter fiber tracts of the human brain: Three-dimensional mapping at microscopic resolution, topography and intersubject variability , 2006, NeuroImage.

[20]  A. Treves,et al.  Taxonomic Separation of Hippocampal Networks: Principal Cell Populations and Adult Neurogenesis , 2016, Front. Neuroanat..

[21]  Dong-Hwan Har,et al.  Sectioned Images of the Cadaver Head Including the Brain and Correspondences With Ultrahigh Field 7.0 T MRIs , 2009, Proceedings of the IEEE.

[22]  Min Suk Chung,et al.  Accessible and Informative Sectioned Images and Surface Models of a Cadaver Head , 2012, The Journal of craniofacial surgery.

[23]  Dong-Hwan Har,et al.  A Proposal of New Reference System for the Standard Axial, Sagittal, Coronal Planes of Brain Based on the Serially-Sectioned Images , 2009, Journal of Korean medical science.

[24]  Antonio A. F. De Salles,et al.  7.0 Tesla MRI Brain Atlas: In vivo atlas with cryomacrotome correlation , 2010, Surgical Neurology International.

[25]  Min Suk Chung,et al.  Whole Courses of the Oculomotor, Trochlear, and Abducens Nerves, Identified in Sectioned Images and Surface Models , 2015, Anatomical record.

[26]  K. Amunts,et al.  Cytoarchitectonic mapping of the human brain cerebellar nuclei in stereotaxic space and delineation of their co-activation patterns , 2015, Front. Neuroanat..

[27]  Min Suk Chung,et al.  Browsing Software of the Head Sectioned Images for the Android Mobile Device , 2017 .

[28]  Cheong Youn,et al.  Software de Navegación para el Dispositivo Móvil Android de Imágenes Seccionadas de Cabeza , 2017 .

[29]  K. A. Jellinger.  7.0 Tesla MRI Brain Atlas. In Vivo Atlas with Cryomacrotome Correlation , 2010 .

[30]  Niels Kuster,et al.  Functionalized Anatomical Models for Computational Life Sciences , 2018, Front. Physiol..

[31]  K. Niemann,et al.  The Morel Stereotactic Atlas of the Human Thalamus: Atlas-to-MR Registration of Internally Consistent Canonical Model , 2000, NeuroImage.

[32]  Hyun-ju Lim,et al.  Accuracy of Model-Based Iterative Reconstruction for CT Volumetry of Part-Solid Nodules and Solid Nodules in Comparison with Filtered Back Projection and Hybrid Iterative Reconstruction at Various Dose Settings: An Anthropomorphic Chest Phantom Study , 2019, Korean journal of radiology.

[33]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.