Correlation between model observers in uniform background and human observers in patient liver background for a low-contrast detection task in CT

Abstract

Channelized Hotelling observer (CHO) has demonstrated strong correlation with human observer (HO) in both single-slice viewing mode and multi-slice viewing mode in low-contrast detection tasks with uniform background. However, it remains unknown if the simplest single-slice CHO in uniform background can be used to predict human observer performance in more realistic tasks that involve patient anatomical background and multi-slice viewing mode. In this study, we aim to investigate the correlation between CHO in a uniform water background and human observer performance at a multi-slice viewing mode on patient liver background for a low-contrast lesion detection task. The human observer study was performed on CT images from 7 abdominal CT exams. A noise insertion tool was employed to synthesize CT scans at two additional dose levels. A validated lesion insertion tool was used to numerically insert metastatic liver lesions of various sizes and contrasts into both phantom and patient images. We selected 12 conditions out of 72 possible experimental conditions to evaluate the correlation at various radiation doses, lesion sizes, lesion contrasts and reconstruction algorithms. CHO with both single and multi-slice viewing modes were strongly correlated with HO. The corresponding Pearson's correlation coefficient was 0.982 (with 95% confidence interval (CI) [0.936, 0.995]) and 0.989 (with 95% CI of [0.960, 0.997]) in multi-slice and single-slice viewing modes, respectively. Therefore, this study demonstrated the potential to use the simplest single-slice CHO to assess image quality for more realistic clinically relevant CT detection tasks.

Keywords: Channelized Hotelling observer; Computed tomography (CT); Model observer; Multi-slice viewing; Observer study.

Figure 1

Examples of the extracted VOIs from CT images of water phantom and patients, respectively. Lesion size was 9 mm, and lesion contrast was 15 HU. The display window was 400 HU/40 HU (W/L).

Figure 2

AUC of MS-MO (a) and SS-MO (b) with different values of α. The weighting factor α for internal noise was determined by comparing the AUC values of MO to HO at the selected calibration condition.

Figure 3

GUI for human reading study

Figure 4

Comparison between MS-MO performance and the averaged HO performance in experimental conditions with different lesion sizes and reconstruction algorithms. Lesion contrast was fixed at 15 HU and dose level was FD. CT images were reconstructed with WFBP (a) and IR (b), respectively.

Figure 5

Comparison between SS-MO performance and the averaged HO performance in experimental conditions with different lesion sizes and reconstruction algorithms. Lesion contrast was fixed at 15 HU and dose level was FD. CT images were reconstructed with WFBP (a) and IR (b), respectively.