Improvement of image quality applying iterative scatter correction for grid-less skeletal radiography in trauma room setting.

BACKGROUND: Iterative reconstruction is well established for CT. Plain radiography also takes advantage of iterative algorithms to reduce scatter radiation and improve image quality. First applications have been described for bedside chest X-ray. A recent experimental approach also provided proof of principle for skeletal imaging. PURPOSE: To examine clinical applicability of iterative scatter correction for skeletal imaging in the trauma setting. MATERIAL AND METHODS: In this retrospective single-center study, 209 grid-less radiographs were routinely acquired in the trauma room for 12 months, with imaging of the chest (n = 31), knee (n = 111), pelvis (n = 14), shoulder (n = 24), and other regions close to the trunk (n = 29). Radiographs were postprocessed with iterative scatter correction, doubling the number of images. The radiographs were then independently evaluated by three radiologists and three surgeons. A five-step rating scale and visual grading characteristics analysis were used. The area under the VGC curve (AUCVGC) quantified differences in image quality. RESULTS: Images with iterative scatter correction were generally rated significantly better (AUCVGC = 0.59, P < 0.01). This included both radiologists (AUCVGC = 0.61, P < 0.01) and surgeons (AUCVGC = 0.56, P < 0.01). The image-improving effect was significant for all body regions; in detail: chest (AUCVGC = 0.64, P < 0.01), knee (AUCVGC = 0.61, P < 0.01), pelvis (AUCVGC = 0.60, P = 0.01), shoulder (AUCVGC = 0.59, P = 0.02), and others close to the trunk (AUCVGC = 0.59, P < 0.01). CONCLUSION: Iterative scatter correction improves the image quality of grid-less skeletal radiography in the clinical setting for a wide range of body regions. Therefore, iterative scatter correction may be the future method of choice for free exposure imaging when an anti-scatter grid is omitted due to high risk of tube-detector misalignment.

Iterative scatter correction for grid-less skeletal radiography allows improved image quality equal to an antiscatter grid in adjunct with dose reduction: a visual grading study of 20 body donors.

BACKGROUND: Iterative scatter correction (ISC) is a new technique applicable to plain radiography; comparable to iterative reconstruction for computed tomography, it promises dose reduction and image quality improvement. ISC for bedside chest X-rays has been applied and evaluated for some time and has recently been commercially offered for plain skeletal radiography. PURPOSE: To analyze the potential of ISC for plain skeletal radiography with regard to image quality improvement, dose reduction, and replacement for an antiscatter grid. MATERIAL AND METHODS: A total of 385 radiographs with different imaging protocols of the pelvis and cervical spine were acquired from 20 body donors. Radiographs were rated by four radiologists. Ratings were analyzed with visual grading characteristics (VGC) analysis. The area under the VGC curve was used as a measure of difference in image quality. RESULTS: Without ISC, the grid-less images were rated significantly worse than their grid-based counterparts (0.389, P = 0.005); adding ISC made image quality equal (0.498; P = 0.963). In grid-less imaging, reduction of dose by 50% led to significant image quality impairment (0.415, P = 0.001); this was fully counterbalanced when ISC was added (0.512; P = 0.588). CONCLUSION: ISC for plain skeletal radiography has the ability to replace the antiscatter grid without image quality impairment, to improve image quality in grid-less imaging, and to reduce patient radiation dose by 50% without substantial loss in image quality.

Diagnostic value of MRI-based 3D texture analysis for tissue characterisation and discrimination of low-grade chondrosarcoma from enchondroma: a pilot study.

OBJECTIVES: To explore the diagnostic value of MRI-based 3D texture analysis to identify texture features that can be used for discrimination of low-grade chondrosarcoma from enchondroma. METHODS: Eleven patients with low-grade chondrosarcoma and 11 patients with enchondroma were retrospectively evaluated. Texture analysis was performed using mint Lesion: Kurtosis, entropy, skewness, mean of positive pixels (MPP) and uniformity of positive pixel distribution (UPP) were obtained in four MRI sequences and correlated with histopathology. The Mann-Whitney U-test and receiver operating characteristic (ROC) analysis were performed to identify most discriminative texture features. Sensitivity, specificity, accuracy and optimal cut-off values were calculated. RESULTS: Significant differences were found in four of 20 texture parameters with regard to the different MRI sequences (p<0.01). The area under the ROC curve values to discriminate chondrosarcoma from enchondroma were 0.876 and 0.826 for kurtosis and skewness in contrast-enhanced T1 (ceT1w), respectively; in non-contrast T1, values were 0.851 and 0.822 for entropy and UPP, respectively. The highest discriminatory power had kurtosis in ceT1w with a cut-off ≥3.15 to identify low-grade chondrosarcoma (82 % sensitivity, 91 % specificity, accuracy 86 %). CONCLUSION: MRI-based 3D texture analysis might be able to discriminate low-grade chondrosarcoma from enchondroma by a variety of texture parameters. KEY POINTS: • MRI texture analysis may assist in differentiating low-grade chondrosarcoma from enchondroma. • Kurtosis in the contrast-enhanced T1w has the highest power of discrimination. • Tools provide insight into tumour characterisation as a non-invasive imaging biomarker.