Multi-detector CT imaging: impact of virtual tube current reduction and sparse sampling on detection of vertebral fractures

Abstract

Purpose To systematically evaluate the effects of virtual tube current reduction and sparse sampling on image quality and vertebral fracture diagnostics in multi-detector computed tomography (MDCT). Materials and methods In routine MDCT scans of 35 patients (80.0% females, 70.6 ± 14.2 years, 65.7% showing vertebral fractures), reduced radiation doses were retrospectively simulated by virtually lowering tube currents and applying sparse sampling, considering 50%, 25%, and 10% of the original tube current and projections, respectively. Two readers evaluated items of image quality and presence of vertebral fractures. Readout between the evaluations in the original images and those with virtually lowered tube currents or sparse sampling were compared. Results A significant difference was revealed between the evaluations of image quality between MDCT with virtually lowered tube current and sparse-sampled MDCT ( p < 0.001). Sparse-sampled data with only 25% of original projections still showed good to very good overall image quality and contrast of vertebrae as well as minimal artifacts. There were no missed fractures in sparse-sampled MDCT with 50% reduction of projections, and clinically acceptable determination of fracture age was possible in MDCT with 75% reduction of projections, in contrast to MDCT with 50% or 75% virtual tube current reduction, respectively. Conclusion Sparse-sampled MDCT provides adequate image quality and diagnostic accuracy for vertebral fracture detection with 50% of original projections in contrast to corresponding MDCT with lowered tube current. Thus, sparse sampling is a promising technique for dose reductions in MDCT that could be introduced in future generations of scanners. Key Points • MDCT with a reduction of projection numbers of 50% still showed high diagnostic accuracy without any missed vertebral fractures. • Clinically acceptable determination of vertebral fracture age was possible in MDCT with a reduction of projection numbers of 75%. • With sparse sampling, higher reductions in radiation exposure can be achieved without compromised image or diagnostic quality in routine MDCT of the spine as compared to MDCT with reduced tube currents. Electronic supplementary material The online version of this article (10.1007/s00330-019-06090-2) contains supplementary material, which is available to authorized users.

Automatic Detection and Classification of Rib Fractures on Thoracic CT Using Convolutional Neural Network: Accuracy and Feasibility

“…However, it is time-consuming and labor-intensive to detect rib fractures in the "24 ribs" on hundreds of thin-slice CT images and missed rib fractures are not uncommon (1,7). Cho et al (1) reported that the rate of missed diagnosis of rib fracture on initial CT images reached 20.7%, significantly higher than those of the thoracic vertebrae or sternum (nearly 100% sensitivity) (8,9), which could lead to poor patient prognosis or adverse medicolegal disputes (10). Therefore, it is necessary to improve the accuracy of clinical diagnosis and reduce the rate of missed diagnoses.…”

Low-dose MDCT: evaluation of the impact of systematic tube current reduction and sparse sampling on the detection of degenerative spine diseases

“…Additionally, images with up to 50% reductions in radiation dose through sparse sampling can be used for finite element (FE)-based predictions of femoral failure load [35]. Sufficient image quality and diagnostic accuracy for detection of vertebral fractures could be achieved with 50% of original projections, while, on the contrary, MDCT with 50% lowered tube currents yielded inferior results [28]. Concerning the degenerative spine, the present study suggests that both sparse sampling and virtual reductions of tube current have potential for dose reduction.…”

“…Initial preprocessing of imaging data used a total-variation method for the projection data to reduce image noise (λ = 0.01, n = 50) [24,25]. By the use of a simulation algorithm based on raw imaging data, we generated MDCT scans with virtually lowered tube currents in a stepwise fashion [26][27][28][29][30][31]. The approach for simulations of LD MDCT has been validated previously [31].…”

“…Sparse sampling was simulated by reading only a reduced amount of projection angles and by deleting the remaining projections in the sinogram [27][28][29]32]. The original imaging was defined as D100P100, and virtual sparse-sampled imaging was generated as if MDCT was performed with only 50% (D100P50), 10% (D100P10), 5% (D100P5), and 3% (D100P3) of the original projection data.…”

Radiation dose reduction for CT-guided intrathecal nusinersen administration in adult patients with spinal muscular atrophy

“…Third, this study achieved lowering of radiation exposure by reductions of tube current in combination with IMR, but did not evaluate other modern approaches to limit radiation exposure, such as sparse sampling. The technique of sparse sampling has shown high potential for even more drastic dose reductions with largely preserved image quality at the spine when compared to decreases in tube current 27,28 ; however, this has not yet been explicitly confirmed for MDCT scanning for planning purposes of neuroradiological interventions. While standard, commercially available MDCT scanners are not yet capable of using sparse sampling, first prototypes have already been constructed successfully 29,30 .…”