ArticleQuantitative imaging in medicine and surgery2026
Assessment of high-grade pattern in lung invasive nonmucinous adenocarcinoma based on multiparametric features from dual-layer detector spectral computed tomography combined with extracellular volume fraction.
Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The International Association for the Study of Lung Cancer (IASLC) introduced a new grading system for invasive nonmucinous adenocarcinoma (INMA), in which complex glandular, micropapillary, and solid subtypes are classified as high-grade patterns (HGPs). Since a higher proportion of HGP is associated with poorer prognosis, accurate assessment is essential for individualized treatment. The aim of this study was to assess the value of conventional computed tomography (CT) features and spectral CT quantitative parameters, particularly extracellular volume (ECV) fraction, in predicting HGP ≥20% in INMA. Methods: This retrospective study included 317 patients with pathologically confirmed INMA who were categorized into HGP ≥20% and HGP <20% groups. Conventional CT features, including the lobulation sign, spiculation sign, and pleural retraction sign, were assessed. Quantitative spectral CT parameters were measured within the lesion during the arterial phase (AP) and venous phase (VP). These parameters included effective atomic number (Zeff), iodine concentration (IC), normalized iodine concentration (NIC), the slope of the energy spectrum curve [g Hounsfield units (HU)], and CT values within the 40- to 200-keV energy range. The ECV was calculated based on VP data. Intergroup differences were analyzed via the Results: Significant differences were observed between the HGP ≥20% and <20% groups in terms of lobulation, spiculation, ECV, and tumor size (all P values <0.05). Additionally, significant variations (all P values <0.05) were noted in several quantitative parameters, including Zeff Conclusions: The combined model can aid in the prediction of the HGP in INMA. This method involves the use of EVC, allowing for a noninvasive diagnosis of HGP, which is critical for patient care.
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