Size-specific weighted detectability index for computed tomography image characterization.

backgroundTechnological developments in computed tomography (CT) have increased the diversity of acquisition and reconstruction strategies available for clinical imaging. Task-based image quality metrics that account for patient-size variability are needed to characterize reconstructed image performance and support protocol optimization across clinically relevant imaging conditions. PURPOSE: To propose and evaluate a novel size-specific weighted detectability index (SSW-d'), a task-based image performance metric (d') that incorporates lesion contrast weighting and water-equivalent diameter variability for the characterization of CT images acquired at low dose.

methodsFirst, a multi-sized image quality phantom was scanned on two CT systems: one photon-counting CT (PCCT, CT1) and one CT equipped with energy integrating detectors (EICT, CT2). Acquisitions were performed with a volume CT dose index (CTDI

resultsOn CT1, the highest SSW-d' values were 19.3 ± 0.3 and 6.9 ± 0.0, at 120 kV for bone and iodine rods, respectively. On CT2, the highest SSW-d' results were 19.0 ± 0.3 and 4.9 ± 0.0 at Sn100 kV for bone and iodine rods, respectively. The lowest values were at Sn140kV for both rods and CT systems. When encompassing both tasks, the maximum SSW-d' values were 10.05 ± 0.04 and 8.25 ± 0.03, respectively obtained at 120 kV for CT1 and at Sn100 kV for CT2. The results showed that the lowest SSW-d' values were at Sn140 kV for both CT systems. Comparison of acquisition and reconstruction parameters showed that the highest SSW-d' value was obtained using the Br32 kernel (17.6 ± 0.7), approximately twofold higher than that obtained at 6 mGy (8.6 ± 0.3). The lowest SSW-d' value (1.9 ± 0.1) was obtained with FBP, while the highest performance was achieved with QIR-4 reconstruction.

conclusionsA novel metric based on a size-specific weighted detectability index (SSW-d') was developed and evaluated for the characterization of reconstructed CT image performance across a range of patient-equivalent diameters and clinically relevant detection tasks. The proposed SSW-d' consolidates multiple detectability index measurements into a single descriptor that accounts for lesion contrast weighting and patient-size variability. The metric was sensitive to acquisition and reconstruction parameters and proved useful for identifying imaging conditions that maximize task-based performance in ultra-low-dose CT. These findings suggest that SSW-d' may serve as a practical tool for image-quality characterization and protocol optimization across clinically relevant imaging scenarios.