Image noise and dose performance across a clinical population: Patient size adaptation as a metric of CT performance

Purpose Modern CT systems adjust X‐ray flux accommodating for patient size to achieve certain image noise values. The effectiveness of this adaptation is an important aspect of CT performance and should ideally be characterized in the context of real patient cases. The objective of this study was to characterize CT performance with a new metric that includes image noise and radiation dose across a clinical patient population. Materials and methods The study included 1526 examinations performed by three CT scanners (one GE Healthcare Discovery CT750HD, one GE Healthcare Lightspeed VCT, and one Siemens SOMATOM definition Flash) used for two routine clinical protocols (abdominopelvic with contrast and chest without contrast). An institutional monitoring system recorded all the data involved in the study. The dose–patient size and noise–patient size dependencies were linearized by considering a first‐order approximation of analytical models that describe the relationship between ionization dose and patient size, as well as image noise and patient size. A 3D‐fit was performed for each protocol and each scanner with a planar function, and the root mean square error (RMSE) values were estimated as a metric of CT adaptability across the patient population. Results The data show different scanner dependencies in terms of adaptability: the RMSE values for the three scanners are between 0.0385 HU1/2 and 0.0215 HU1/2. Conclusion A theoretical relationship between image noise, CTDIvol, and patient size was determined based on real patient data. This relationship may be interpreted as a new metric related to the scanners’ adaptability concerning image quality and radiation dose across a patient population. This method could be implemented to investigate the adaptability related to other image quality indexes and radiation dose in a clinical population.

[1]  J. Boone,et al.  Size-Specific Dose Estimates (SSDE) in Pediatric and Adult Body CT Examinations , 2011 .

[2]  P. Christian,et al.  Quantitative PET/CT Scanner Performance Characterization Based Upon the Society of Nuclear Medicine and Molecular Imaging Clinical Trials Network Oncology Clinical Simulator Phantom , 2015, The Journal of Nuclear Medicine.

[3]  W A Kalender,et al.  Dose reduction in CT by anatomically adapted tube current modulation. II. Phantom measurements. , 1999, Medical physics.

[4]  Ting-Yim Lee,et al.  Impact of new technologies on dose reduction in CT. , 2010, European journal of radiology.

[5]  M. Kalra,et al.  Techniques and applications of automatic tube current modulation for CT. , 2004, Radiology.

[6]  John M Boone,et al.  Monte Carlo evaluation of CTD(infinity) in infinitely long cylinders of water, polyethylene and PMMA with diameters from 10 mm to 500 mm. , 2008, Medical physics.

[7]  Ehsan Samei,et al.  Automated Technique to Measure Noise in Clinical CT Examinations. , 2015, AJR. American journal of roentgenology.

[8]  Nicholas Keat,et al.  CT scanner automatic exposure control systems , 2005 .

[9]  伊沢 正実,et al.  Recommendations of the International Commission on Radiological Protection , 1961 .

[10]  D. Larson,et al.  System for verifiable CT radiation dose optimization based on image quality. part II. process control system. , 2013, Radiology.

[11]  W A Kalender,et al.  Dose reduction in CT by anatomically adapted tube current modulation. I. Simulation studies. , 1999, Medical physics.

[12]  Marilyn J Goske,et al.  System for verifiable CT radiation dose optimization based on image quality. part I. Optimization model. , 2013, Radiology.

[13]  Rochester,et al.  Use of Water Equivalent Diameter for Calculating Patient Size and Size-Specific Dose Estimates (SSDE) in CT: The Report of AAPM Task Group 220. , 2014, AAPM report.

[14]  Jack Valentin,et al.  The 2007 Recommendations of the International Commission on Radiological Protection. ICRP publication 103. , 2007, Annals of the ICRP.

[15]  Ehsan Samei,et al.  Automated size-specific CT dose monitoring program: assessing variability in CT dose. , 2012, Medical physics.

[16]  Ehsan Samei,et al.  Comparison of patient size-based methods for estimating quantum noise in CT images of the lung. , 2009, Medical physics.

[17]  E. W. Morris No , 1923, The Hospital and health review.