ArticleEuropean radiology2021
CT severity indices derived from low monoenergetic images at dual-energy CT may improve prediction of outcome in acute pancreatitis.
Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 13 citations in OpenAlex.
- Correlation of CT-Derived Quantitative Image Features and Inflammatory Laboratory Markers with Length of Hospital Stay in Patients with Pyelonephritis.Diagnostics (Basel, Switzerland) · 2026Article
- The clinical applications of dual-layer spectral detector CT in digestive system diseases.European radiology · 2025Review
- Feasibility of using software-aided selection of virtual monoenergetic level for optimal image quality of acute necrotising pancreatitis based on dual-energy computed tomography: a preliminary study.BMC medical imaging · 2023Article
- How Effective are Metal Nanotherapeutic Platforms Against Bacterial Infections? A Comprehensive Review of Literature.International journal of nanomedicine · 2023Review
- Diagnostic performance of dual-energy CT in nonspecific terminal ileitis.Japanese journal of radiology · 2022Article
- Non-linear correlation between amylase day 2 to day 1 ratio and incidence of severe acute pancreatitis.Frontiers in cellular and infection microbiology · 2022Article
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7 authors at 1 institution in 1 country.
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Abstract
objectivesTo determine whether imaging features and severity indices using low monoenergetic DECT images improve diagnostic conspicuity and outcome prediction in acute pancreatitis compared to conventional images.
methodsA retrospective study of patients with clinical and radiographic signs of acute pancreatitis who underwent 50 contrast-enhanced CT exams conducted on a single-source DECT was performed. Representative conventional and 50 keV-monoenergetic images were randomized and presented to four abdominal radiologists to determine preferred imaging for detecting fat stranding and parenchymal inflammation. Contrast and signal-to-noise ratios were constructed for necrotic, hypoattenuated, inflamed, and healthy parenchyma. These parameters and the CT severity index (CTSI) were compared between conventional and low monoenergetic images using paired t tests and correlated to clinical outcome.
resultsAlthough preference for conventional images was noted for subtle peri-pancreatic fat stranding (169/200 (85%) reads), there was clear preference for low monoenergetic images among all readers for pancreatic inflammation evaluation (188/200 (94%) reads). Moreover, identification of small, hypoattenuating inflammatory foci on monoenergetic images alone in 13/50 (26%) cases resulted in upstaged CTSI from mild to moderate in 7/50 (14%), associated with longer hospitalization (16 ± 17 days vs. 5 ± 2 days; p < 0.05), ICU admission, and drainage. Quantitatively, a twofold difference between normal and inflamed parenchyma attenuation was identified for monoenergetic (44.8 ± 27.6) vs. conventional (25.1 ± 14.7) images (p < 0.05). Significant increases were seen in the monoenergetic SNR and CNR compared to the conventional images (p < 0.05).
conclusionsDECT low monoenergetic images afford better tissue assessment and demarcation of inflamed pancreatic parenchyma. Additionally, they provide improved characterization of the extent parenchymal necrosis, enabling better classification that may better predict severe clinical outcomes. KEY POINTS: • DECT low monoenergetic images afford better tissue assessment and demarcation of inflamed pancreatic parenchyma and provide improved characterization of the extent parenchymal necrosis. • Qualitatively, low monoenergetic images were preferred over conventional DECT images for the evaluation of pancreatic inflammation; and quantitatively, there is a twofold difference between normal and inflamed parenchyma attenuation, SNR, and CNR between monoenergetic vs. conventional images. • Monoenergetic imaging identified additional small, hypoattenuating inflammatory foci in 26% resulting in an upstaged CT severity index in 14% associated with longer hospitalization, ICU admission, and drainage, thereby enabling better classification and better prediction of severe clinical outcomes.
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