Lymph Node Stations of Pancreas Which Are Identified in Real Color Sectioned Images of a Cadaver With Pancreatic Cancer

BACKGROUND

In pancreatic cancer surgery, anatomical understanding of lymph node metastases is required. Distinguishing lymph nodes in computed tomography or magnetic resonance imaging is challenging for novice doctors and medical students because of their small size and similar color to surrounding tissues. This study aimed to enhance our understanding of the clinical anatomy of lymph node stations relevant to pancreatic cancer using newly sectioned images of a cadaver with true color and high resolution and their three-dimensional (3D) models.

METHODS

An 88-year-old female cadaver who died of pancreatic cancer was serially sectioned. Among the sectioned images of the whole body (0.05 mm-sized pixel, 48 bits color), images of the abdomen were selected, and examined to identify lymph nodes and nearby structures. 34 structures (9 in digestive system; 1 in urinary system; 2 in cardiovascular system; 22 in lymphatic system) were segmented on the sectioned images. Based on the sectioned and segmented images, volume and surface models were produced.

RESULTS

Among the known 28 lymph node stations, 21 stations were identified through location, size, and color of normal and abnormal structures in the sectioned images and 3D models. Two near the splenic artery could not be separated from the cancer tissue, and the remaining five were not clearly identified. In the surface models, the shape and location of lymph node stations could be confirmed with nearby structures.

CONCLUSION

The lymph node stations relevant to pancreatic cancer can be anatomically understood by using the sectioned images and 3D models which contain true color and high resolution.

A Novel Human Brainstem Map Based on True-Color Sectioned Images

BACKGROUND

Existing atlases for the human brainstem were generated from magnetic resonance images or traditional histologically stained slides, but both are insufficient for the identification of detailed brainstem structures at uniform intervals.

METHODS

A total of 319 sectioned images of the brainstem were selected from whole-body axial sectioned images, then coronal and sagittal sectioned images were reconstructed from the horizontal images. The fine and detailed structures were annotated in PowerPoint slides, then the volume model was produced and some white matter fibers were traced using MRIcroGL.

RESULTS

In this study, a novel brainstem atlas based on sectioned images was generated that shows the true color and shape, as well as the accurate location of the nuclei and tracts; it reveals the striking contrast between gray and white matter, as well as fine structures. In total, 212 structures, including nuclei and tracts, were annotated in axial, coronal, and sagittal plane views of sectioned images (48-bit true color; 0.2 mm intervals, 0.06 mm × 0.06 mm pixel size). To verify the accuracy of the annotations, a volume model of the brainstem was constructed for independent observations of the three planes.

CONCLUSION

In this paper, we describe several interesting structures included in the atlas. By depicting the fine structures of the human brainstem in detail, this atlas allows comprehensive understanding of the complicated topographies of the brainstem. As such, it will be of value for neuroanatomy education and research, in addition to enriching the literature on the human brain.

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.

Real-Color Volume Models Made from Real-Color Sectioned Images of Visible Korean

BACKGROUND

Volume models made from magnetic resonance images on computed tomographs can produce horizontal, coronal, sagittal, and oblique planes that are used widely in clinics, although detailed structures cannot be identified. Existing real color volume models are mostly commercial and their production methods have not been released. The aim of this study was to distribute free of charge, real-color volume models produced from sectioned images with the production method.

METHODS

The original voxel size of sectioned images was increased appropriately so that the volume model could be handled by typical personal computers. By using Dicom Browser and MRIcroGL, the sectioned images were processed to become the volume models.

RESULTS

On the MRIcroGL, the resultant volume model with the voxel size of 0.5 × 0.5 × 0.5 mm³ could be displayed and freely rotated. By adjusting variables of the software, desired oblique planes could be produced instantly. With overlay function, a model of segmented structure can be overlapped to the entire volume models. The sectioned images with high quality and the segmentation data of Visible Korean enabled the identification of detailed anatomical structures on the planes.

CONCLUSION

The volume models can be used by medical students and doctors for learning sectional anatomy. Other researchers can utilize the method of this study to produce volume models from their own sectioned images.

New Viewpoint of Surface Anatomy Using the Curved Sectional Planes of a Male Cadaver

BACKGROUND

The curved sectional planes of the human body can provide a new approach of surface anatomy that the classical horizontal, coronal, and sagittal planes cannot do. The purpose of this study was to verify whether the curved sectional planes contribute to the morphological comprehension of anatomical structures.

METHODS

By stacking the sectioned images of a male cadaver, a volume model of the right half body was produced (voxel size 1 mm). The sectioned images with the segmentation data were also used to build another volume model. The volume models were peeled and rotated to be screen captured. The captured images were loaded on user-friendly browsing software that had been made in the laboratory.

RESULTS

The browsing software was downloadable from the authors' homepage (anatomy.co.kr). On the software, the volume model was peeled at 1 mm thicknesses and rotated at 30 degrees. Since the volume models were made from the cadaveric images, actual colors of the structures were displayed in high resolution. Thanks to the segmentation data, the structures on the volume model could be automatically annotated. Using the software, the sternocleidomastoid muscle and the internal jugular vein in the neck region, the cubital fossa in the upper limb region, and the femoral triangle in the lower limb region were observed to be described.

CONCLUSION

For the students learning various medical procedures, the software presents the needed graphic information of the human body. The curved sectional planes are expected to be a tool for disciplinary convergence of the sectional anatomy and surface anatomy.