Adaptive statistical iterative reconstruction for computed tomography of the spine

IntroductionThe utility of evaluating a sagittal view of CT of the spine is well-known. In many clinical cases, the sagittal view includes noise generated from surrounding objects and may degrade the image quality. Iterative reconstruction (IR) techniques are useful for noise reduction; however, they can reduce spatial resolution. The aim of this study was to evaluate the effectiveness of the adaptive statistical iterative reconstruction (ASiR) for generating sagittal CT images of the spine when compared to filtered back projection (FBP). MethodsThe image quality of clinical images from 25 patients were subjectively assessed. Three radiologists rated spatial resolution, image noise, and overall image quality using a five-point scale. For objective assessment, z-direction modulation transfer function (z-MTF) was measured using a custom-made phantom. Additionally, z-axis noise power spectrum (z-NPS) was measured using a water phantom. An improved adaptive statistical iterative reconstruction algorithm called ASiR-V was used in this study. Blending levels were 50%, and 100% (ASiR-V50, ASiR-V100, respectively). ResultsFor subjective assessments, images using ASiR-V100 were determined to have the best overall image quality, despite having received the worst score in the assessment of spatial resolution. For objective assessments, the image using ASiR-V50 and ASiR-V100 curves were slightly degraded in terms of low contrast z-MTF when compared to FBP. ConclusionASiR-V was effective to improve the image quality when compared with FBP when reviewing sagittal reformats of the spine. Implications for practiceThis study suggests that high resolution is not the only thing that is key when reviewing sagittal CT spinal reformats. Such images should be provided as part of routine CT spine protocols, where available.