Lymph Node Stations of Pancreas Which Are Identified in Real Color Sectioned Images of a Cadaver With Pancreatic Cancer.
J Korean Med Sci
; 38(46): e392, 2023 Nov 27.
Article
in En
| MEDLINE
| ID: mdl-38013647
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.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Pancreatic Neoplasms
/
Imaging, Three-Dimensional
Limits:
Aged80
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Female
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Humans
Language:
En
Journal:
J Korean Med Sci
Journal subject:
MEDICINA
Year:
2023
Document type:
Article
Country of publication: