A strategy to optimize CT pediatric dose with a visual discrimination model

Daniel Gutierrez; François Gudinchet; Leonor T. Alamo-Maestre; François O. Bochud; Francis R. Verdun

doi:10.1117/12.769419

6 March 2008 A strategy to optimize CT pediatric dose with a visual discrimination model

Daniel Gutierrez, François Gudinchet, Leonor T. Alamo-Maestre, François O. Bochud, Francis R. Verdun

Proceedings Volume 6917, Medical Imaging 2008: Image Perception, Observer Performance, and Technology Assessment; 69171B (2008) https://doi.org/10.1117/12.769419
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Technological developments of computed tomography (CT) have led to a drastic increase of its clinical utilization, creating concerns about patient exposure. To better control dose to patients, we propose a methodology to find an objective compromise between dose and image quality by means of a visual discrimination model. A GE LightSpeed-Ultra scanner was used to perform the acquisitions. A QRM 3D low contrast resolution phantom (QRM - Germany) was scanned using CTDI_vol values in the range of 1.7 to 103 mGy. Raw data obtained with the highest CTDI_vol were afterwards processed to simulate dose reductions by white noise addition. Noise realism of the simulations was verified by comparing normalized noise power spectra aspect and amplitudes (NNPS) and standard deviation measurements. Patient images were acquired using the Diagnostic Reference Levels (DRL) proposed in Switzerland. Noise reduction was then simulated, as for the QRM phantom, to obtain five different CTDI_vol levels, down to 3.0 mGy. Image quality of phantom images was assessed with the Sarnoff JNDmetrix visual discrimination model and compared to an assessment made by means of the ROC methodology, taken as a reference. For patient images a similar approach was taken but using as reference the Visual Grading Analysis (VGA) method. A relationship between Sarnoff JNDmetrix and ROC results was established for low contrast detection in phantom images, demonstrating that the Sarnoff JNDmetrix can be used for qualification of images with highly correlated noise. Patient image qualification showed a threshold of conspicuity loss only for children over 35 kg.

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Daniel Gutierrez, François Gudinchet, Leonor T. Alamo-Maestre, François O. Bochud, and Francis R. Verdun "A strategy to optimize CT pediatric dose with a visual discrimination model", Proc. SPIE 6917, Medical Imaging 2008: Image Perception, Observer Performance, and Technology Assessment, 69171B (6 March 2008); https://doi.org/10.1117/12.769419

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KEYWORDS

Visualization

Visual process modeling

Computed tomography

Chest

Image analysis

Image quality

Visual analytics

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