Improvement of Low-Contrast Detectability in Low-Dose Hepatic Multidetector Computed Tomography Using a Novel Adaptive Filter: Evaluation With a Computer-Simulated Liver Including Tumors

Purpose:The purpose of this study was to investigate how much radiation dose can be reduced without loss of low-contrast detectability with a newly developed adaptive noise reduction filter in hepatic multidetector computed tomography (MDCT) scans by using a computer-simulated liver phantom. Materials and Methods:Simulated CT images, including liver and intrahepatic tumors, were mathematically constructed using a computer workstation to evaluate low-contrast detectability by the observer performance test. Milliampere second for construction of simulated images were 60, 80, 100, and 120 mAs (low dose) and 160 mAs (standard dose) at 120 kVp. Images with 60, 80, 100, and 120 mAs were postprocessed with the adaptive noise reduction filter. A total of 432 images were prepared and receiver operating characteristic (ROC) analysis was performed by 5 radiologists. The detectability of simulated tumor by radiologists was estimated with the area under the ROC curves (Az values). In addition, we visually evaluated CT images of 15 patients with chronic liver damage for graininess of the liver parenchyma, sharpness of the liver contour, conspicuity and marginal sharpness of the liver tumors, and overall image quality. Results:The mean Az value at 0.777 (60 mAs), 0.828 (80 mAs), and 0.844 (100 mAs) without filter was significantly lower than that of 160 mAs without filter (P < 0.001, 60 mAs; P = 0.010, 80 mAs; P = 0.040, 100 mAs). There was no statistical difference between the mean Az value at 80 mAs with and 160 mAs without the adaptive noise reduction filter (P = 0.220) and 100 mAs with and 160 mAs without the adaptive noise reduction filter (P = 0.979). In the visual evaluation of patient livers, there was no statistical difference in the graininess and sharpness of the liver, the conspicuity and marginal sharpness of the tumor, and the overall image quality between standard-dose and filtered low-dose images (Wilcoxon signed rank test, P > 0.05). Conclusion:The radiation dose can be reduced by 50% without loss of nodule detectability by applying the adaptive noise reduction filter to simulated and patient liver images obtained at MDCT.

[1]  Jiang Hsieh,et al.  Computer-simulated radiation dose reduction for abdominal multidetector CT of pediatric patients. , 2002, AJR. American journal of roentgenology.

[2]  J. Paul,et al.  Low-kilovoltage multi-detector row chest CT in adults: feasibility and effect on image quality and iodine dose. , 2004, Radiology.

[3]  Francis R Verdun,et al.  Detection of low-contrast objects: experimental comparison of single- and multi-detector row CT with a phantom. , 2002, Radiology.

[4]  H Hu,et al.  Helical CT reconstruction with longitudinal filtration. , 1998, Medical physics.

[5]  T. Murakami,et al.  Hypervascular hepatocellular carcinoma: detection with double arterial phase multi-detector row helical CT. , 2001, Radiology.

[6]  M Takahashi,et al.  Small hepatocellular carcinoma in patients with chronic liver damage: prospective comparison of detection with dynamic MR imaging and helical CT of the whole liver. , 1996, Radiology.

[7]  James H Thrall,et al.  Multi-detector row CT: radiation dose characteristics. , 2003, Radiology.

[8]  G Allan Johnson,et al.  Optimization of eight-element multi-detector row helical CT technology for evaluation of the abdomen. , 2003, Radiology.

[9]  N. Obuchowski.  Receiver operating characteristic curves and their use in radiology. , 2003, Radiology.

[10]  Thomas L Toth,et al.  Low-dose CT of the abdomen: evaluation of image improvement with use of noise reduction filters pilot study. , 2003, Radiology.

[11]  W. Foley,et al.  Multiphase hepatic CT with a multirow detector CT scanner. , 2000, AJR. American journal of roentgenology.

[12]  D. DeLong,et al.  Helical CT for nephrolithiasis and ureterolithiasis: comparison of conventional and reduced radiation-dose techniques. , 2003, Radiology.

[13]  Takamichi Murakami,et al.  Small hypervascular hepatocellular carcinoma revealed by double arterial phase CT performed with single breath-hold scanning and automatic bolus tracking. , 2002, AJR. American journal of roentgenology.

[14]  S. Saini.  Multi-detector row CT: principles and practice for abdominal applications. , 2004, Radiology.

[15]  Marc Kachelrieß,et al.  Improvement of image quality of multislice spiral CT scans of the head and neck region using a raw data-based multidimensional adaptive filtering (MAF) technique , 2004, European Radiology.

[16]  James H Thrall,et al.  Clinical comparison of standard-dose and 50% reduced-dose abdominal CT: effect on image quality. , 2002, AJR. American journal of roentgenology.

[17]  W. Kalender,et al.  Generalized multi-dimensional adaptive filtering for conventional and spiral single-slice, multi-slice, and cone-beam CT. , 2001, Medical physics.

[18]  Walter Hruby,et al.  Diagnostic performance of liquid crystal and cathode-ray-tube monitors in brain computed tomography , 2003, European Radiology.

[19]  R. Morin,et al.  Effect of Acquisition Technique on Radiation Dose and Image Quality in Multidetector Row Computed Tomography Coronary Angiography With Submillimeter Collimation , 2005, Investigative radiology.

[20]  M D Harpen.  A computer simulation of wavelet noise reduction in computed tomography. , 1999, Medical physics.

[21]  Carl-Fredrik Westin,et al.  Affine adaptive filtering of CT data , 2000, Medical Image Anal..

[22]  Karl Stierstorfer,et al.  Multi-detector row CT systems and image-reconstruction techniques. , 2005, Radiology.

[23]  E. Nickoloff,et al.  Influence of phantom diameter, kVp and scan mode upon computed tomography dose index. , 2003, Medical physics.

[24]  G. Stevenson,et al.  Low-dose nonenhanced helical CT of renal colic: assessment of ureteric stone detection and measurement of effective dose equivalent. , 2000, Radiology.