Development and validation of an automated methodology to assess perceptual in vivo noise texture in liver CT

Abstract

<b>Purpose</b>: Developing, validating, and evaluating a method for measuring noise texture directly from patient liver CT images (i.e., <i>in vivo</i>). <b>Approach</b>: The method identifies target regions within patient scans that are least likely to have major contribution of patient anatomy, detrends them locally, and measures noise power spectrum (NPS) there using a previously phantom-validated technique targeting perceptual noise-non-anatomical fluctuations in the image that may interfere with the detection of focal lesions. Method development and validation used scanner-specific CT simulations of computational, anthropomorphic phantom (XCAT phantom, three phases of contrast-enhancement) with known ground truth of the NPS. Simulations were based on a clinical scanner (Definition Flash, Siemens) and clinically relevant settings (tube voltage of 120 kV at three dose levels). Images were reconstructed with filtered backprojection (kernel: B31, B41, and B50) and Sinogram Affirmed Iterative Reconstruction (kernel: I31, I41, and I50) using a manufacturer-specific reconstruction software (ReconCT, Siemens). All NPS measurements were made in the liver. Ground-truth NPS were taken as the sum of (1) a measurement in parenchymal regions of anatomy-subtracted (i.e., noise only) scans, and (2) a measurement in the same region of noise-free (pre-noise-insertion) images. To assess <i>in vivo</i> NPS performance, correlation of NPS average frequency ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub><mml:mrow><mml:mi>f</mml:mi></mml:mrow> <mml:mrow><mml:mi>avg</mml:mi></mml:mrow> </mml:msub> </mml:mrow> </mml:math> ), was reported. Sensitivity of accuracy [root-mean-square-error (RMSE)] to number of pixels included in measurement was conducted via bootstrapped pixel-dropout. Sensitivity of NPS to dose and reconstruction kernel was assessed to confirm that ground truth NPS similarities were maintained in patient-specific measurements. <b>Results</b>: Pearson and Spearman correlation coefficients 0.97 and 0.96 for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub><mml:mrow><mml:mi>f</mml:mi></mml:mrow> <mml:mrow><mml:mi>avg</mml:mi></mml:mrow> </mml:msub> </mml:mrow> </mml:math> indicated good correlation. Results suggested accurate NPS measurements (within 5% total RMSE) could be acquired with <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>∼</mml:mo> <mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow> <mml:mrow><mml:mn>6</mml:mn></mml:mrow> </mml:msup> <mml:mtext> </mml:mtext> <mml:mtext>pixels</mml:mtext></mml:mrow> </mml:math> . <b>Conclusions</b>: Relationships of similar NPS due to reconstruction kernel and dose were preserved between gold standard and observed <i>in vivo</i> estimations. The NPS estimation method was further deployed on clinical cases to demonstrate the feasibility of clinical analysis.