Sample size requirements for estimating effective dose from computed tomography using solid-state metal-oxide-semiconductor field-effect transistor dosimetry.
OBJECTIVE
Effective dose (ED) is a widely used metric for comparing ionizing radiation burden between different imaging modalities, scanners, and scan protocols. In computed tomography (CT), ED can be estimated by performing scans on an anthropomorphic phantom in which metal-oxide-semiconductor field-effect transistor (MOSFET) solid-state dosimeters have been placed to enable organ dose measurements. Here a statistical framework is established to determine the sample size (number of scans) needed for estimating ED to a desired precision and confidence, for a particular scanner and scan protocol, subject to practical limitations.


METHODS
The statistical scheme involves solving equations which minimize the sample size required for estimating ED to desired precision and confidence. It is subject to a constrained variation of the estimated ED and solved using the Lagrange multiplier method. The scheme incorporates measurement variation introduced both by MOSFET calibration, and by variation in MOSFET readings between repeated CT scans. Sample size requirements are illustrated on cardiac, chest, and abdomen-pelvis CT scans performed on a 320-row scanner and chest CT performed on a 16-row scanner.


RESULTS
Sample sizes for estimating ED vary considerably between scanners and protocols. Sample size increases as the required precision or confidence is higher and also as the anticipated ED is lower. For example, for a helical chest protocol, for 95% confidence and 5% precision for the ED, 30 measurements are required on the 320-row scanner and 11 on the 16-row scanner when the anticipated ED is 4 mSv; these sample sizes are 5 and 2, respectively, when the anticipated ED is 10 mSv.


CONCLUSIONS
Applying the suggested scheme, it was found that even at modest sample sizes, it is feasible to estimate ED with high precision and a high degree of confidence. As CT technology develops enabling ED to be lowered, more MOSFET measurements are needed to estimate ED with the same precision and confidence.
Department of Medicine, Division of Cardiology, Columbia University Medical Center and New York-Presbyterian Hospital, New York, New York 10032.
Sigal
S
Trattner
Department of Biostatistics, Columbia University Mailman School of Public Health, New York, New York 10032.
Bin
B
Cheng
Center for Radiological Research, Columbia University Medical Center and New York-Presbyterian Hospital, New York, New York 10032.
Radoslaw L
RL
Pieniazek
Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114.
Udo
U
Hoffmann
Department of Medicine, Division of Cardiology, Duke University, Durham, North Carolina 27715.
Pamela S
PS
Douglas
Department of Medicine, Division of Cardiology, Columbia University Medical Center and New York-Presbyterian Hospital, New York, New York and Department of Radiology, Columbia University Medical Center and New York-Presbyterian Hospital, New York, New York.
Andrew J
AJ
Einstein
D006801:Humans; D008670:Metals / Q000737:chemistry*; D010087:Oxides; D019047:Phantoms, Imaging; D011829:Radiation Dosage; D011874:Radiometry / Q000295:instrumentation*; D014057:Tomography, X-Ray Computed / Q000295:instrumentation*; D014173:Transistors, Electronic
D008670:Metals; D010087:Oxides