ArticleKorean journal of radiology2021
Virtual Monochromatic Image Quality from Dual-Layer Dual-Energy Computed Tomography for Detecting Brain Tumors.
Article in Korean journal of radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 15 citations in OpenAlex.
- Practical applications of photon-counting CT in oncology: an organ-based pictorial review.Insights into imaging · 2026Article
- Feasibility of electron density map derived from unenhanced dual-energy CT for detecting peritonsillar abscess.Neuroradiology · 2026Article
- Diagnostic value of dual-energy CT virtual monochromatic imaging for supraspinatus tendon injuries: a comparison with standard CT and MRI.European radiology · 2025Article
- Multi-parameter spectral computed tomography for the prognosis evaluation of prostate cancer bone metastasis: a retrospective study.Quantitative imaging in medicine and surgery · 2025Article
- Italian radiologists and dual-energy CT: a state of the art from a shared document by the computed tomography subspecialty section of the Italian society of radiology.La Radiologia medica · 2025Article
- Application of virtual monochromatic images in bone mineral density measurements: a phantom study.Scientific reports · 2025Article
- Dual-layer spectral computed tomography aortography using a seventy-five-percent-reduced iodine dose protocol and multiparameter spectral imaging: comparison with conventional computed tomography imaging.Quantitative imaging in medicine and surgery · 2023Article
- Diagnostic performance of dual-energy CT in nonspecific terminal ileitis.Japanese journal of radiology · 2022Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo evaluate the usefulness of virtual monochromatic images (VMIs) obtained using dual-layer dual-energy CT (DL-DECT) for evaluating brain tumors. MATERIALS AND
methodsThis retrospective study included 32 patients with brain tumors who had undergone non-contrast head CT using DL-DECT. Among them, 15 had glioblastoma (GBM), 7 had malignant lymphoma, 5 had high-grade glioma other than GBM, 3 had low-grade glioma, and 2 had metastatic tumors. Conventional polychromatic images and VMIs (40-200 keV at 10 keV intervals) were generated. We compared CT attenuation, image noise, contrast, and contrast-to-noise ratio (CNR) between tumor and white matter (WM) or grey matter (GM) between VMIs showing the highest CNR (optimized VMI) and conventional CT images using the paired t test. Two radiologists subjectively assessed the contrast, margin, noise, artifact, and diagnostic confidence of optimized VMIs and conventional images on a 4-point scale.
resultsThe image noise of VMIs at all energy levels tested was significantly lower than that of conventional CT images (
conclusionIn head CT for patients with brain tumors, compared with conventional CT images, 40 keV VMIs from DL-DECT yielded superior tumor contrast and diagnostic confidence, especially for brain tumors located in the WM.
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