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Related Concept Videos

Computed Tomography01:10

Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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Imaging Studies III: Computed Tomography01:27

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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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Related Experiment Video

Updated: Jul 17, 2025

Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos
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Pediatric body composition based on automatic segmentation of computed tomography scans: a pilot study.

Atia Samim1,2, Suzanne Spijkers3, Pim Moeskops4,5

  • 1Department of Radiology and Nuclear Medicine, University Medical Center Utrecht and Wilhelmina Children's Hospital, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands. atiasamim@gmail.com.

Pediatric Radiology
|August 28, 2023
PubMed
Summary

Automatic segmentation accurately quantifies pediatric body composition from CT scans. This study provides normative data on muscle and fat distribution in children, highlighting sex-based differences in development.

Keywords:
Body compositionChildComputed tomographySarcopeniaSkeletal muscleSubcutaneous fatVisceral fat

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Area of Science:

  • Radiology and Imaging
  • Pediatric Health
  • Body Composition Analysis

Background:

  • Childhood body composition influences long-term health.
  • Accurate quantification of pediatric body composition is crucial for early health assessments.

Purpose of the Study:

  • To evaluate automatic segmentation for body composition analysis in pediatric computed tomography (CT) scans.
  • To establish normative data for muscle and fat areas in children aged 1-17 years.

Main Methods:

  • Retrospective analysis of 493 pediatric CT scans (ages 1-17).
  • Automatic segmentation used to measure muscle and fat areas at the L3 vertebral level.
  • Manual segmentation of a subset (52 scans) validated automatic segmentation accuracy.

Main Results:

  • High accuracy (Dice 0.87-0.90) for muscle and subcutaneous fat; lower for visceral fat (0.60).
  • Boys developed more muscle after age 13; girls showed higher fat-to-muscle ratios.
  • Boys exhibited higher visceral-to-subcutaneous fat ratios from a young age.

Conclusions:

  • Automatic segmentation provides accurate pediatric body composition quantification.
  • Normative data reveal distinct muscle and fat distribution patterns in childhood.
  • This method aids in understanding pediatric body composition development.