In hepatic CT imaging, the lesion enhancement after the injection of contrast media is of quantitative
interest. However, the precision of this quantitative measurement may be dependent on the imaging
techniques such as dose and reconstruction algorithm. To determine the impact of different techniques,
we scanned an iodinated liver phantom with acquisition protocols of different dose levels, and
reconstructed images with different algorithms (FBP and MBIR) and slice thicknesses. The contrast of
lesions was quantified from the images, and its precision was calculated for each protocol separately.
Results showed that precision was improved by increasing dose, increasing slice thickness, and using
MBIR reconstruction. When using MBIR instead of FBP, the same precision can be achieved at 50% less
dose. To our knowledge, this is the first investigation of the quantification precision in hepatic CT
imaging using iterative reconstructions.
Current lung nodule size assessment methods typically rely on one-dimensional estimation of lesions. While
new 3D volume assessment techniques using MSCT scan data have enabled improved estimation of lesion
size, the effect of acquisition and reconstruction parameters on accuracy and precision of such estimation has
not been adequately investigated. To characterize such dependencies, we scanned an anthropomorphic
thoracic phantom containing synthetic nodules with different protocols, including various acquisition and
reconstruction parameters. We also scanned the phantom repeatedly with the same protocol to investigate
repeatability. The nodule's volume was estimated by a clinical lung analysis software package, LungVCAR.
Accuracy (bias) and precision (variance) of the volume assessment were calculated across the nodules and
compared between protocols via Generalized Estimating Equation analysis. Results suggest a strong
dependence of accuracy and precision on dose level but little dependence on reconstruction thickness, thus
providing possible guidelines for protocol optimization for quantitative tasks.
Radiation-dose awareness and optimization in CT can greatly benefit from a dosereporting
system that provides radiation dose and cancer risk estimates specific to each
patient and each CT examination. Recently, we reported a method for estimating patientspecific
dose from pediatric chest CT. The purpose of this study is to extend that effort to
patient-specific risk estimation and to a population of pediatric CT patients. Our study
included thirty pediatric CT patients (16 males and 14 females; 0-16 years old), for whom
full-body computer models were recently created based on the patients' clinical CT data.
Using a validated Monte Carlo program, organ dose received by the thirty patients from a
chest scan protocol (LightSpeed VCT, 120 kVp, 1.375 pitch, 40-mm collimation,
pediatric body scan field-of-view) was simulated and used to estimate patient-specific
effective dose. Risks of cancer incidence were calculated for radiosensitive organs using
gender-, age-, and tissue-specific risk coefficients and were used to derive patientspecific
effective risk. The thirty patients had normalized effective dose of 3.7-10.4 mSv/100 mAs and normalized effective risk of 0.5-5.8 cases/1000 exposed persons/100 mAs. Normalized lung dose and risk of lung cancer correlated strongly with average chest diameter (correlation coefficient: r = -0.98 to -0.99). Normalized effective risk also correlated strongly with average chest diameter (r = -0.97 to -0.98). These strong correlations can be used to estimate
patient-specific dose and risk prior to or after an imaging study to potentially guide healthcare providers in justifying CT examinations and to guide individualized protocol design and optimization.
KEYWORDS: Data modeling, Intestine, Computed tomography, Computer simulations, Tissues, Kidney, Monte Carlo methods, Image segmentation, 3D modeling, Chest
The purpose of this study is to develop a method for estimating patient-specific dose from
abdomen-pelvis CT examinations and to investigate dose variation across patients in the
same weight group. Our study consisted of seven pediatric patients in the same
weight/protocol group, for whom full-body computer models were previously created
based on the patients' CT data obtained for clinical indications. Organ and effective dose
of these patients from an abdomen-pelvis scan protocol (LightSpeed VCT scanner,
120-kVp, 85-90 mA, 0.4-s gantry rotation period, 1.375-pitch, 40-mm beam collimation, and
small body scan field-of-view) was calculated using a Monte Carlo program previously
developed and validated for the same CT system. The seven patients had effective dose
of 2.4-2.8 mSv, corresponding to normalized effective dose of
6.6-8.3 mSv/100mAs
(coefficient of variation: 7.6%). Dose variations across the patients were small for large
organs in the scan coverage (mean: 6.6%; range: 4.9%-9.2%), larger for small organs in
the scan coverage (mean: 10.3%; range: 1.4%-15.6%), and the largest for organs partially
or completely outside the scan coverage (mean: 14.8%; range:
5.7%-27.7%). Normalized
effective dose correlated strongly with body weight (correlation coefficient: r = -0.94).
Normalized dose to the kidney and the adrenal gland correlated strongly with mid-liver
equivalent diameter (kidney: r = -0.97; adrenal glands:
r = -0.98). Normalized dose to the
small intestine correlated strongly with mid-intestine equivalent diameter (r = -0.97).
These strong correlations suggest that patient-specific dose may be estimated for any
other child in the same size group who undergoes the abdomen-pelvis scan.
The purpose of this study is to evaluate the effect of reduced tube current, as a surrogate
for radiation dose, on lung nodule detection in pediatric chest multi-detector CT (MDCT).
Normal chest MDCT images of 13 patients aged 1 to 7 years old were used as templates
for this study. The original tube currents were between 70 mA and 180 mA. Using
proprietary noise addition software, noise was added to the images to create 13 cases at
the lowest common mA (i.e. 70 mA), 13 cases at 35 mA (50% reduction), and 13 cases at
17.5 mA (75% reduction). Three copies of each case were made for a total of 117 series
for simulated nodule insertion. A technique for three-dimensional simulation of small
lung nodules was developed, validated through an observer study, and used to add
nodules to the series. Care was taken to ensure that each of three lung zones (upper,
middle, lower) contained 0 or 1 nodule. The series were randomized and the presence of
a nodule in each lung zone was rated independently and blindly by three pediatric
radiologists on a continuous scale between 0 (definitely absent) and 100 (definitely
present). Receiver operating characteristic analysis of the data showed no general
significant difference in diagnostic accuracy between the reduced mA values and 70 mA,
suggesting a potential for dose reduction with preserved diagnostic quality. To our
knowledge, this study is the first controlled, systematic, and task-specific assessment of
the influence of dose reduction in pediatric chest CT.
In recent years, there has been a desire to reduce CT radiation dose to children because of their susceptibility and
prolonged risk for cancer induction. Concerns arise, however, as to the impact of dose reduction on image quality and
thus potentially on diagnostic accuracy. To study the dose and image quality relationship, we are developing a
simulation code to calculate organ dose in pediatric CT patients. To benchmark this code, a cylindrical phantom was
built to represent a pediatric torso, which allows measurements of dose distributions from its center to its periphery.
Dose distributions for axial CT scans were measured on a 64-slice multidetector CT (MDCT) scanner (GE Healthcare,
Chalfont St. Giles, UK). The same measurements were simulated using a Monte Carlo code (PENELOPE, Universitat de
Barcelona) with the applicable CT geometry including bowtie filter. The deviations between simulated and measured
dose values were generally within 5%. To our knowledge, this work is one of the first attempts to compare measured
radial dose distributions on a cylindrical phantom with Monte Carlo simulated results. It provides a simple and effective
method for benchmarking organ dose simulation codes and demonstrates the potential of Monte Carlo simulation for
investigating the relationship between dose and image quality for pediatric CT patients.
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