Objective To determine the difference in CT values and image quality of abdominal CT images reconstructed by filtered back-projection (FBP), hybrid iterative reconstruction (IR), and deep learning... Show moreObjective To determine the difference in CT values and image quality of abdominal CT images reconstructed by filtered back-projection (FBP), hybrid iterative reconstruction (IR), and deep learning reconstruction (DLR). Methods PubMed and Embase were systematically searched for articles regarding CT densitometry in the abdomen and the image reconstruction techniques FBP, hybrid IR, and DLR. Mean differences in CT values between reconstruction techniques were analyzed. A comparison between signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of FBP, hybrid IR, and DLR was made. A comparison of diagnostic confidence between hybrid IR and DLR was made. Results Sixteen articles were included, six being suitable for meta-analysis. In the liver, the mean difference between hybrid IR and DLR was - 0.633 HU (p = 0.483, SD +/- 0.902 HU). In the spleen, the mean difference between hybrid IR and DLR was - 0.099 HU (p = 0.925, SD +/- 1.061 HU). In the pancreas, the mean difference between hybrid IR and DLR was - 1.372 HU (p = 0.353, SD +/- 1.476 HU). In 14 articles, CNR was described. In all cases, DLR showed a significantly higher CNR. In 9 articles, SNR was described. In all cases but one, DLR showed a significantly higher SNR. In all cases, DLR showed a significantly higher diagnostic confidence. Conclusions There were no significant differences in CT values reconstructed by FBP, hybrid IR, and DLR in abdominal organs. This shows that these reconstruction techniques are consistent in reconstructing CT values. DLR images showed a significantly higher SNR and CNR, compared to FBP and hybrid IR. Show less
Gorris, M.; Hoogenboom, S.A.; Wallace, M.B.; Hooft, J.E. van 2020
Novel artificial intelligence techniques are emerging in all fields of healthcare, including gastroenterology. The aim of this review is to give an overview of artificial intelligence applications... Show moreNovel artificial intelligence techniques are emerging in all fields of healthcare, including gastroenterology. The aim of this review is to give an overview of artificial intelligence applications in the management of pancreatic diseases. We performed a systematic literature search in PubMed and Medline up to May 2020 to identify relevant articles. Our results showed that the development of machine-learning based applications is rapidly evolving in the management of pancreatic diseases, guiding precision medicine in clinical, endoscopic and radiologic settings. Before implementation into clinical practice, further research should focus on the external validation of novel techniques, clarifying the accuracy and robustness of these models. Show less
Serial measurements of coronary plaque volume have been used to evaluate drug efficacy in atherosclerotic progression. However, the usefulness of computed tomography for this purpose is unknown. We... Show moreSerial measurements of coronary plaque volume have been used to evaluate drug efficacy in atherosclerotic progression. However, the usefulness of computed tomography for this purpose is unknown. We investigated whether the change in total plaque volume on coronary computed tomographic angiography is associated with the change in segment plaque volume on intravascular ultrasound.We prospectively enrolled 11 consecutive patients (mean age, 56.3 +/- 5 yr; 6 men) who were to undergo serial invasive coronary angiographic examinations with use of grayscale intravascular ultrasound and coronary computed tomography, performed <180 days apart at baseline and from 1 to 2 years later. Subjects underwent 186 serial measurements of total plaque volume on coronary computed tomography and 22 of segmental plaque volume on intravascular ultrasound. We used semiautomated software to examine percentage relationships and changes between total plaque and segmental plaque volumes.No significant correlations were found between percentages of total coronary and segment coronary plaque volume, nor between normalized coronary plaque volume. However, in the per-patient analysis, there were strong correlations between the imaging methods for changes in total coronary and segment coronary plaque volume (r=0.62; P=0.04), as well as normalized plaque volume (r=0.82; P=0.002).Per-patient change in plaque volume on coronary computed tomography is significantly associated with that on intravascular ultrasound. Computed tomographic angiography may be safer and more widely available than intravascular ultrasound for evaluating atherosclerotic progression in coronary arteries. Larger studies are warranted. Show less
