Evidence map›Paper›PMID 42816867›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2026

Quantitative PCCT spectral parameters for noninvasive prediction of EGFR status and its subtypes in lung adenocarcinoma.

Jiazhong Ren, Yong Huang, Linfeng Li, Yuqin Jin, Yong Yin

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Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 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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5 · Who and what money

Authors and funding

5 authors.

Jiazhong RenDepartment of Medical Imaging, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No. 440 Jiyan Road, Huaiyin District, Jinan, Shandong Province, China.
Yong HuangDepartment of Medical Imaging, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No. 440 Jiyan Road, Huaiyin District, Jinan, Shandong Province, China.
Linfeng LiSiemens Healthineers Digital Technology (Shanghai) Co., Ltd., CT Collaboration, Siemens Healthineers Digital Technology (Shanghai) Co., Ltd., Shanghai, China.
Yuqin Jin *Department of Medical Imaging, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No. 440 Jiyan Road, Huaiyin District, Jinan, Shandong Province, China. jinyq@sd-cancer.com.
Yong Yin *Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences, No. 440 Jiyan Road, Huaiyin District, Jinan, Shandong Province, China. yinyong@sd-cancer.com.

Funding

National Natural Science Foundation of China Grant Nos. 12275162 and 12575365
6 · The paper itself

Abstract

objectiveTo investigate the non-invasive predictive value of quantitative spectral parameters from photon-counting computed tomography (PCCT) for epidermal growth factor receptor (EGFR) mutation status and its predominant subtypes (19Del and L858R) in patients with lung adenocarcinoma.

methodsA total of 72 patients with pathologically confirmed lung adenocarcinoma who underwent pretreatment PCCT were retrospectively enrolled. Arterial and venous CT attenuation values at 40 keV, 70 keV, and 100 keV (A/V-40 keV, A/V-70 keV, A/V-100 keV) were measured on virtual monoenergetic images, while arterial/venous iodine concentration (IC) and dual-energy index (DEI) of lesions were measured on iodine maps and spectral post-processing (SPP) images, respectively. Normalized iodine concentration (NIC) and spectral curve slope (λHU) were further calculated. Receiver operating characteristic (ROC) curve analysis and binary logistic regression were performed to evaluate the predictive performance and independent predictive value of PCCT parameters for discriminating EGFR-mutant vs. wild-type tumors, as well as 19Del vs. L858R subtypes.

resultsOf 72 patients, 37 (51.4%) harbored EGFR mutations, which correlated with female sex, never-smoking, reduced NSE, and lower monocyte count. The EGFR-mutant group showed significantly higher A-70 keV, A-100 keV, A-DEI, V-40 keV, V-70 keV, V-100 keV, V-λHU and V-DEI (all P < 0.05). Logistic regression identified female sex (P = 0.019, OR = 5.714, 95% CI: 1.336-24.442) and A-100 keV (P = 0.044, OR = 0.543, 95% CI: 0.300-0.983) as independent predictors. ROC analysis with bootstrap validation yielded: clinical model AUC 0.767 (optimism-corrected 0.762); PCCT model AUC 0.713 (optimism-corrected 0.707); combined model AUC 0.771 (optimism-corrected 0.768) (all P < 0.001). Between 19Del (n = 15) and L858R (n = 17) subgroups, A-40 keV and A-DEI showed significant discriminative performance in ROC analysis, with AUCs of 0.694 and 0.704 (optimism-corrected AUCs: 0.688 and 0.697, respectively).

conclusionsQuantitative PCCT spectral parameters enable non-invasive prediction of EGFR mutation status and preliminary differentiation between 19Del and L858R subtypes in lung adenocarcinoma, though subtype-related findings require validation in larger cohorts. Female sex and A-100 keV are independent predictive factors. The combined model yielded a numerically higher AUC without statistically significant superiority, and PCCT parameters may provide auxiliary imaging evidence to inform individualized targeted therapy decisions in lung adenocarcinoma.

Indexed as

AdenocarcinomaAdenocarcinoma of LungLung NeoplasmsTomography, X-Ray ComputedAgedErbB ReceptorsFemaleHumansMaleMiddle AgedMutationPredictive Value of TestsRetrospective StudiesROC CurveEGFR protein, humanErbB ReceptorsEGFRLung adenocarcinomaPhoton-counting computed tomographySpectral parameters

Identifiers

PMID42816867
PMCPMC13625330

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.