Multi-Parametric Spectral Detector CT for the Assessment of Focal Liver Lesions: Evaluation of Readers’ Diagnostic Confidence and Economic Effects
Year: 2026
Type: article
Abstract: Background/Objectives: Characterization of small liver lesions on computed tomography (CT) remains challenging. This study evaluated whether spectral detector CT (SDCT) improves subjective diagnostic confidence in the characterization of focal hypoperfused liver lesions using additional spectral information and assessed its potential economic impact. Methods: In this IRB-approved retrospective study, 100 patients with 229 focal hypoperfused liver lesions who underwent SDCT were included. Images were evaluated in three consecutive reading sessions using (1) conventional polychromatic images (conv), (2) conventional plus monoenergetic images at 40, 50, and 60 keV (monoE), and (3) a multiparametric SDCT approach (mSDCT) combining conventional and spectral reconstructions, including iodine density (ID) and effective atomic number (Zeff) images. Lesions were characterized, and subjective diagnostic confidence was rated on a 5-point scale. Diagnostic performance was compared, and potential economic savings were estimated. Results: mSDCT yielded the highest diagnostic confidence in 130 lesions, compared with 36 lesions for conventional CT. Diagnostic confidence increased significantly from conventional CT through monoE to mSDCT (median scores: 3, 4, 4, 4, and 5 for conventional CT, 40-, 50-, and 60-keV monoE, and mSDCT, respectively; all p < 0.001). For lesions ≤ 10 mm, sensitivity was comparable between conventional CT and mSDCT, whereas mSDCT significantly improved specificity (85.0% vs. 97.9%) and diagnostic accuracy (86.4% vs. 96.7%; p < 0.001). Conclusion: Multiparametric SDCT significantly improves radiologists’ diagnostic confidence in characterizing focal hypoperfused liver lesions, particularly lesions ≤10 mm in oncologic patients. Increased diagnostic confidence may reduce the need for additional imaging or biopsy, potentially enabling faster and less costly diagnostic workups.
Source: Diagnostics
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W7225829777
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