Apr 11, 2012
Phantoms assess CT dose to obese patients
The prevalence of overweight and obese individuals is increasing markedly, and the associated health risks mean that this group represents a growing fraction of patients entering radiology clinics. CT imaging of larger patients, however, requires protocol changes to maintain image quality, which impacts the radiation dose to the patient.
In general, the necessary protocol changes result in obese patients facing a greater radiation risk than normal-weight patients undergoing CT scans. Despite this fact, quantitative data describing the relationship between obesity and patient organ dose are not available, and existing tools for CT dose estimates are based on computational phantoms of normal weight.
"A recent survey suggests that nearly 60% of adult Americans are clinically overweight or obese. We realized that there were no computational phantoms for such an important segment of the patients who frequent radiology and radiation oncology clinics," explained lead author Aiping Ding, a member of the Rensselaer Radiation Measurement and Dosimetry Group (RRMDG) at Rensselaer Polytechnic Institute (Troy, NY). "As a result, inaccurate models for these patients have to be used when radiation dose is calculated."
To fill this gap, Ding and colleagues have created a series of computational phantoms representing overweight and obese patients, and used these to examine the effect of obesity on radiation dose from CT exams (Phys. Med. Biol. 57 2441).
The Rensselaer team derived the new phantoms by modifying existing RPI-Adult Male and RPI-Adult Female phantoms, which comprise more than 100 deformable organs defined using mesh geometry. Specified amounts of subcutaneous (under the skin) and visceral (surrounding the abdominal organs) adipose tissues were included to simulate increased BMI.
The end result was five male and five female phantoms with BMI ranging from 23.5 to 46.4 kg/m2, representing normal weight, overweight, obese level-I, obese level-II and morbidly obese. The phantoms were voxelized and defined in the Monte Carlo N-Particle Extended (MCNPX) code for organ dose calculations.
To study the effects of increased subcutaneous and visceral adipose tissues on radiation dose, the researchers simulated CT scans for all phantoms using a multi-detector CT model. Simulations considered tube potentials from 80–140 kVp and the results were normalized by a tube current-time of 100 mAs.
MCNPX dose calculations revealed that, compared to the normal weight phantom, radiation doses to superficial organs decreased slightly for the higher-BMI phantoms. For example, breast dose reduced by up to 24% in female phantoms. Organs deep within the body, however, are highly shielded by the extra adipose tissue, and the dose to these organs decreased significantly. For the colon, for example, dose reductions ranged from 9–57% in male phantoms and from 18–59% in female phantoms, as BMI increased from overweight to morbidly obese.
While using constant tube potential and current-time values eases comparisons, this is not a clinically realistic scenario. To maintain diagnostic image quality, the increased X-ray photon attenuation seen in overweight patients must be compensated for by increasing the tube current and/or potential.
For example, tube potential is often increased to 140 kVp for CT scans of morbidly obese patients. In this study, increasing the potential from 120 to 140 kVp increased the organ doses by as much as 56% for organs within the scan field and 62% for those out of the scan field. The researchers note that this dose increase has less impact upon deep organs, which already receive lower dose in the larger phantoms.
Another way to improve image quality is to increase the tube current, for example by doubling the mAs for obese patients. The researchers found that doubling the tube current (at a constant 120 kVp) increased the effective dose (relative to the normal weight phantom) by 57%, 42% and 23% for obese-I, obese-II and morbidly-obese phantoms, respectively.
The results of this study can be used to help optimize CT scanning procedures for larger patients. "We hope that these data will be integrated with data for normal size adults and children to form a comprehensive database using a software package called VirtualDose. This is being developed for CT dose reporting and is expected to enter clinical testing this summer," said X George Xu, the senior corresponding author of the study. "Dose information can be used to analyse trends in a clinic and study how to optimize image quality for different patients. Clinics that are interested in testing this VirtualDose software can contact us directly."
• Xu is a co-founder of the Consortium of Computational Human Phantoms (CCHP). CCHP published the Handbook of Anatomical Models for Radiation Dosimetry in 2009, involving 64 authors from 13 countries. Last summer, the group organized the Third International Workshop on Computational Phantoms for Radiation Protection, Imaging and Radiotherapy in Beijing, China.
• Related articles in PMB
Extension of RPI-adult male and female computational phantoms to obese patients and a Monte Carlo study of the effect on CT imaging dose
Aiping Ding et al Phys. Med. Biol. 57 2441
Standing adult human phantoms based on 10th, 50th and 90th mass and height percentiles of male and female Caucasian populations
V F Cassola et al Phys. Med. Biol. 56 3749
Deformable adult human phantoms for radiation protection dosimetry: anthropometric data representing size distributions of adult worker populations and software algorithms
Yong Hum Na et al Phys. Med. Biol. 55 3789
RPI-AM and RPI-AF, a pair of mesh-based, size-adjustable adult male and female computational phantoms using ICRP-89 parameters and their calculations for organ doses from monoenergetic photon beams
Juying Zhang et al Phys. Med. Biol. 54 5885
A boundary-representation method for designing whole-body radiation dosimetry models: pregnant females at the ends of three gestational periods—RPI-P3, -P6 and -P9
X George Xu et al Phys. Med. Biol. 52 7023
About the author
Tami Freeman is editor of medicalphysicsweb.