Task-based image quality procedures in CT that substitute a human observer with a model observer usually use single-slice images with uniform backgrounds from homogeneous phantoms. However, anatomical structures and inhomogeneities in organs generate noise that can affect the detection performance of human observers. The purpose of this work was to assess the impact of background type, uniform or liver, and the viewing modality, single- or multislice, on the detection performance of human and model observers. We collected abdominal CT scans from patients and homogeneous phantom scans in which we digitally inserted low-contrast signals that mimicked a liver lesion. We ran a rating experiment with the two background conditions with three signal sizes and three human observers presenting images in two reading modalities: single- and multislice. In addition, channelized Hotelling observers (CHO) for single- and multislice detection were implemented and evaluated according to their degree of correlation with the human observer performance. For human observers, there was a small but significant improvement in performance with multislice compared to the single-slice viewing mode. Our data did not reveal a significant difference between uniform and anatomical backgrounds. Model observers demonstrated a good correlation with human observers for both viewing modalities. Human observers have very similar performances in both multi- and single-slice viewing mode. It is therefore preferable to use single-slice CHO as this model is computationally more tractable than multislice CHO. However, using images from a homogeneous phantom can result in overestimating image quality as CHO performance tends to be higher in uniform than anatomical backgrounds, while human observers have similar detection performances.
Purpose: We aimed to determine the in-vitro diagnostic performance of multi-energy spectral photon-counting CT (SPCCT) in crystal-related arthropathies. Methods: Four crystal types (monosodium urate, MSU; calcium pyrophosphate, CPP; octacalcium phosphate, OCP; and calcium hydroxyapatite, CHA) were synthesized and blended with agar at the following concentrations: 240, 88, 46, and 72 mg/mL, respectively. Crystal suspensions were scanned on a pre-clinical SPCCT system at 80 kVp using the following four energy thresholds: 20, 30, 40, and 50 keV. Differences in linear attenuation coefficients between the various crystal suspensions were compared using the receiver operating characteristic (ROC) paradigm. Areas under the ROC curves (AUC), sensitivities, specificities, and diagnostic accuracies were calculated. Crystal differentiation was considered successful if AUC>0.95. Results: For each paired comparison of crystal suspensions, AUCs were significantly higher in the first energy range (20-30 keV). In the first energy range, MSU was confidently differentiated from CPP (sensitivity, 0.978; specificity, 0.990; accuracy, 0.984) and CHA (sensitivity, 0.957; specificity, 0.970; accuracy, 0.964), while only moderately distinguished from OCP (sensitivity, 0.663; specificity, 0.714; accuracy, 0.688). CPP was confidently differentiated from OCP (sensitivity, 0.950; specificity, 0.954; accuracy, 0.952), while only moderately from CHA (sensitivity, 0.564; specificity, 0.885; accuracy, 0.727). OCP was accurately differentiated from CHA (sensitivity, 0.898; specificity, 0.917; accuracy, 0.907). Conclusions: Multi-energy SPCCT can accurately differentiate MSU from CPP and CHA, CPP from OCP, and OCP from CHA in vitro. The distinction between MSU and OCP, and CPP and CHA is more challenging.
Image quality assessment is crucial for the optimization of computed tomography (CT) protocols. Human and mathematical model observers are increasingly used for the detection of low contrast signal in abdominal CT, but are frequently limited to the use of a single image slice. Another limitation is that most of them only consider the detection of a signal embedded in a uniform background phantom. The purpose of this paper was to test if human observer performance is significantly different in CT images read in single or multiple slice modes and if these differences are the same for anatomical and uniform clinical images. We investigated detection performance and scrolling trends of human observers of a simulated liver lesion embedded in anatomical and uniform CT backgrounds. Results show that observers don’t take significantly benefit of additional information provided in multi-slice reading mode. Regarding the background, performances are moderately higher for uniform than for anatomical images. Our results suggest that for low contrast detection in abdominal CT, the use of multi-slice model observers would probably only add a marginal benefit. On the other hand, the quality of a CT image is more accurately estimated with clinical anatomical backgrounds.
Major technological advances in CT enable the acquisition of high quality images while minimizing patient exposure. The goal of this study was to objectively compare two generations of iterative reconstruction (IR) algorithms for the detection of low contrast structures. An abdominal phantom (QRM, Germany), containing 8, 6 and 5mm-diameter spheres (with a nominal contrast of 20HU) was scanned using our standard clinical noise index settings on a GE CT: “Discovery 750 HD”. Two additional rings (2.5 and 5 cm) were also added to the phantom. Images were reconstructed using FBP, ASIR-50%, and VEO (full statistical Model Based Iterative Reconstruction, MBIR). The reconstructed slice thickness was 2.5 mm except 0.625 mm for VEO reconstructions. NPS was calculated to highlight the potential noise reduction of each IR algorithm. To assess LCD (low Contrast Detectability), a Channelized Hotelling Observer (CHO) with 10 DDoG channels was used with the area under the curve (AUC) as a figure of merit. Spheres contrast was also measured. ASIR-50% allowed a noise reduction by a factor two when compared to FBP without an improvement of the LCD. VEO allowed an additional noise reduction with a thinner slice thickness compared to ASIR-50% but with a major improvement of the LCD especially for the large-sized phantom and small lesions. Contrast decreased up to 10% with the phantom size increase for FBP and ASIR-50% and remained constant with VEO. VEO is particularly interesting for LCD when dealing with large patients and small lesion sizes and when the detection task is difficult.