ArticleDiagnostics (Basel, Switzerland)2022
Dual-Energy CT, Virtual Non-Calcium Bone Marrow Imaging of the Spine: An AI-Assisted, Volumetric Evaluation of a Reference Cohort with 500 CT Scans.
Article in Diagnostics (Basel, Switzerland), 2022. 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, 5 citations in OpenAlex.
- Understanding Photon-Counting CT: Physics, Detector Technology, and Image Reconstructions.Sensors (Basel, Switzerland) · 2026Review
- Challenging bone biopsies: what radiologists needs to know.Skeletal radiology · 2026Review
- Impact of calcium suppression imaging on hand and wrist fracture detection in spectral CT: a comparison with X-ray and CT.Skeletal radiology · 2026Article
- Advantages of integrating artificial intelligence and spectral CT for lung nodule classification and prognostic judgment: a narrative review.Journal of thoracic disease · 2025Review
- Evaluation of virtual non-contrast detector-based spectral CT images in comparison to true unenhanced images in 20 rabbits.Frontiers in veterinary science · 2025Article
- Dual-Energy CT in Cardiothoracic Imaging: Current Developments.Diagnostics (Basel, Switzerland) · 2023Review
- Physiological iodine uptake of the spine's bone marrow in dual-energy computed tomography - using artificial intelligence to define reference values based on 678 CT examinations of 189 individuals.Frontiers in endocrinology · 2023Article
- Pretreatment computed tomography L1 attenuation values: Easy reaching predicting factor for radiation-related bone insufficiency fractures in females treated for advanced cervical cancer (prospective study).Women's health (London, England)Article
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Virtual non-calcium (VNCa) images from dual-energy computed tomography (DECT) have shown high potential to diagnose bone marrow disease of the spine, which is frequently disguised by dense trabecular bone on conventional CT. In this study, we aimed to define reference values for VNCa bone marrow images of the spine in a large-scale cohort of healthy individuals. DECT was performed after resection of a malignant skin tumor without evidence of metastatic disease. Image analysis was fully automated and did not require specific user interaction. The thoracolumbar spine was segmented by a pretrained convolutional neuronal network. Volumetric VNCa data of the spine's bone marrow space were processed using the maximum, medium, and low calcium suppression indices. Histograms of VNCa attenuation were created for each exam and suppression setting. We included 500 exams of 168 individuals (88 female, patient age 61.0 ± 15.9). A total of 8298 vertebrae were segmented. The attenuation histograms' overlap of two consecutive exams, as a measure for intraindividual consistency, yielded a median of 0.93 (IQR: 0.88-0.96). As our main result, we provide the age- and sex-specific bone marrow attenuation profiles of a large-scale cohort of individuals with healthy trabecular bone structure as a reference for future studies. We conclude that artificial-intelligence-supported, fully automated volumetric assessment is an intraindividually robust method to image the spine's bone marrow using VNCa data from DECT.
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