| Literature DB >> 35294599 |
Martin Toby Tan1, Thomas Bernard Lloyd2.
Abstract
Computed tomography (CT) is routinely used to diagnose and evaluate metastatic lesions in oncology. CT alone suffers from lack of sensitivity, especially for skeletal lesions in the bone marrow and lesions that have similar attenuation profiles to surrounding bone. Magnetic resonance imaging and nuclear medicine imaging remain the gold standard in evaluating skeletal lesions. However, compared to CT, these modalities are not as widely available or suitable for all patients. Dual energy computed tomography (DECT) exploits variations in linear attenuation coefficient of materials at different photon energy levels to reconstruct images based on material composition. DECT in musculoskeletal imaging is used in the imaging of crystal arthropathy and detecting subtle fractures, but it is not broadly utilized in evaluating infiltrative skeletal lesions. Malignant skeletal lesions have different tissue and molecular compositions compared to normal bone. DECT may exploit these physical differences to delineate infiltrative skeletal lesions from surrounding bone better than conventional monoenergetic CT. Studies so far have examined the utility of DECT in evaluating skeletal metastases, multiple myeloma lesions, pathologic fractures, and performing image-guided biopsies with promising results. These studies were mostly retrospective analyses and case reports containing small samples sizes. As DECT becomes more widely used clinically and more scientific studies evaluating the performance of DECT are published, DECT may eventually become an important modality in the work-up of infiltrative skeletal lesions. It may even challenge MRI and nuclear medicine because of relatively faster scanning times and ease of access.Entities:
Keywords: Bony metastasis; Dual energy CT; Multiple myeloma; Osseous lesion; Skeletal lesion; Spectral CT
Mesh:
Year: 2022 PMID: 35294599 DOI: 10.1007/s00256-022-04032-6
Source DB: PubMed Journal: Skeletal Radiol ISSN: 0364-2348 Impact factor: 2.128