14 research outputs found
Noise-reducing algorithms do not necessarily provide superior dose optimisation for hepatic lesion detection with multidetector CT
Objective: To compare the doseoptimisation potential of a smoothing filtered backprojection (FBP) and a hybrid FBP/iterative algorithm to that of a standard FBP algorithm at three slice thicknesses for hepatic lesion detection with multidetector CT. Methods: A liver phantom containing a 9.5-mm opacity with a density of 10HU below background was scanned at 125, 100, 75, 50 and 25mAs. Data were reconstructed with standard FBP (B), smoothing FBP (A) and hybrid FBP/iterative (iDose4) algorithms at 5-, 3- and 1-mm collimation. 10 observers marked opacities using a four-point confidence scale. Jackknife alternative freeresponse receiver operating characteristic figure of merit (FOM), sensitivity and noise were calculated. Results: Compared with the 125-mAs/5-mm setting for each algorithm, significant reductions in FOM (p,0.05) and sensitivity (p,0.05) were found for all three algorithms for all exposures at 1-mm thickness and for all slice thicknesses at 25mAs, with the exception of the 25-mAs/5-mm setting for the B algorithm. Sensitivity was also significantly reduced for all exposures at 3-mm thickness for the A algorithm (p,0.05). Noise for the A and iDose4 algorithms was approximately 13% and 21% lower, respectively, than for the B algorithm. Conclusion: Superior performance for hepatic lesion detection was not shown with either a smoothing FBP algorithm or a hybrid FBP/iterative algorithm compared with a standard FBP technique, even though noise reduction with thinner slices was demonstrated with the alternative approaches. Advances in knowledge: Reductions in image noise with non-standard CT algorithms do not necessarily translate to an improvement in low-contrast object detection
Exposure (mAs) optimisation of a multi-detector CT protocol for hepatic lesion detection : are thinner slices better?
Introduction The purpose of this work was to determine the exposure-optimised slice thickness for hepatic lesion detection with CT. Methods A phantom containing spheres (diameter 9.5, 4.8 and 2.4 mm) with CT density 10 HU below the background (50 HU) was scanned at 125, 100, 75 and 50 mAs. Data were reconstructed at 5-, 3- and 1-mm slice thicknesses. Noise, contrast-to-noise ratio (CNR), area under the curve (AUC) as calculated using receiver operating characteristic analysis and sensitivity representing lesion detection were calculated and compared. Results Compared with the 125 mAs/5 mm slice thickness setting, significant reductions in AUC were found for 75 mAs (P < 0.01) and 50 mAs (P < 0.05) at 1- and 3-mm thicknesses, respectively; sensitivity for the 9.5-mm sphere was significantly reduced for 75 (P < 0.05) and 50 mAs (P < 0.01) at 1-mm thickness; sensitivity for the 4.8-mm sphere was significantly lower for 100, 75 and 50 mAs at all three slice thicknesses (P < 0.05). The 2.4-mm sphere was rarely detected. At each slice thickness, noise at 100, 75 and 50 mAs exposures was approximately 10, 30 and 50% higher, respectively, than that at 125 mAs exposure. CNRs decreased in an irregular manner with reductions in exposure and slice thickness. Conclusion This study demonstrated no advantage to using slices below 5 mm thickness, and consequently thinner slices are not necessarily better
Optimization of computed tomography protocols : limitations of a methodology employing a phantom with location-known opacities
This study aimed to determine if phantom-based methodologies for optimization of hepatic lesion detection with computed tomography (CT) require randomization of lesion placement and inclusion of normal images. A phantom containing fixed opacities of varying size (diameters, 2.4, 4.8, and 9.5 mm) was scanned at various exposure and slice thickness settings. Two image sets were compared: All images in the first image set contained opacities with known location; the second image set contained images with opacities in random locations. Following Institutional Review Board approval, nine experienced observers scored opacity visualization using a 4-point confidence scale. Comparisons between image sets were performed using Spearman, Kappa, and Wilcoxon techniques. Observer scores demonstrated strong correlation between both approaches when all opacity sizes were combined (r = 0.92, p < 0.0001), for the 9.5 mm opacity (r = 0.96, p < 0.0001) and for the 2.4 mm opacity (r = 0.64, p < 0.05). There was no significant correlation for the 4.8 mm opacity. A significantly higher sensitivity score for the known compared with the unknown location was found for the 9.5 mm opacity and 4.8 mm opacity for a single slice thickness and exposure condition (p < 0.05). Phantom-based optimization of CT hepatic examinations requires randomized lesion location when investigating challenging conditions; however, a standard phantom with fixed lesion location is suitable for the optimization of routine liver protocols. The development of more sophisticated phantoms or methods than those currently available is indicated for the optimization of CT protocols for diagnostic tasks involving the detection of subtle change