A Retrospectively Study: Diagnosis of Pathological Types of Malignant Lung Tumors by Dual-layer Detector Spectral Computed Tomography

Background To explore the value of dual-energy computed tomography (DECT) in differentiating pathological subtypes and the expression of immunohistochemical markers Ki-67 and thyroid transcription factor 1 (TTF-1) in patients with non-small cell lung cancer (NSCLC). Methods Between July 2022 and May 2024, patients suspected of lung cancer who underwent two-phase contrast-enhanced DECT were prospectively recruited. Whole-tumor volumetric and conventional spectral analysis were utilized to measure DECT parameters in the arterial and venous phase. The DECT parameters model, clinical-CT radiological features model, and combined prediction model were developed to discriminate pathological subtypes and predict Ki-67 or TTF-1 expression. Multivariate logistic regression analysis was used to identify independent predictors. The diagnostic efficacy was assessed by the area under the receiver operating characteristic curve (AUC) and compared using DeLong’s test. Results This study included 119 patients (92 males and 27 females; mean age, 63.0 ± 9.4 years) who was diagnosed with NSCLC. When applying the DECT parameters model to differentiate between adenocarcinoma and squamous cell carcinoma, ROC curve analysis indicated superior diagnostic performance for conventional spectral analysis over volumetric spectral analysis (AUC, 0.801 vs. 0.709). Volumetric spectral analysis exhibited higher diagnostic efficacy in predicting immunohistochemical markers compared to conventional spectral analysis (both P < 0.05). For Ki-67 and TTF-1 expression, the combined prediction model demonstrated optimal diagnostic performance with AUC of 0.943 and 0.967, respectively. Conclusions The combined predictive model based on volumetric quantitative analysis in DECT offers valuable information to discriminate immunohistochemical expression status, facilitating clinical decision-making for patients with NSCLC.

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Clinical value of dual energy CT combined with CEA and CY21-1 in predicting EGFR gene mutation in lung adenocarcinoma

Song

Wang

Zhu

et al. 2022

Preprint

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Objective To evaluate the value of dual-energy CT combined with carcinoembryonic antigen (CEA)and soluble cytokeratin 19 fragment(CY21-1) in predicting epidermal growth factor receptor(EGFR) mutations of patients with advanced lung adenocarcinoma.Methods General informations,quantitative parameters of dual-energy computed tomography (DECT),CEA,CY21-1 and EGFR datas were collected of 90 patients between October 2019 and April 2022,the quantitative parameters include iodine concentration(IC),normalized iodine concentration(NIC) and slope of the curve(k) in venous phase. According to whether there was EGFR gene mutation or not,it was divided into mutation group and wild group.To compare the difference of clinical data and DECT parameters,logistic regression model was established to in the two groups Evaluation of model prediction efficiency by receiver operating characteristic(ROC) curve.Results Among all cases,55 cases were EGFR gene mutations mostly in female and non-smokers.IC,NIC,k in venous phase（VP） and CEA in mutation group were higher than another group,but CY21-1 is opposite.The area under ROC curve of IC(VP),k(VP),CEA and CY21-1 were 0.703,0.642,0.725,0.609,respectively.DECT parameters combinded to establish regression model 1,and then combinded CEA and CY21-1 to establish model 2, the area under curve(AUC) is 0.807, Model 2 was higher to model 1 and other single factors.There was no significant difference in age and NIC(VP)(P>0.05).Conclusion EGFR gene mutations tend to occur in women and non-smokers, IC,k in venous phase and CEA and CY21-1 can effectively predict EGFR gene mutation to some extent.

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A Retrospectively Study: Diagnosis of Pathological Types of Malignant Lung Tumors by Dual-layer Detector Spectral Computed Tomography

Cited by 3 publications

References 17 publications

Role of iodine density value on dual-energy CT for detection of high tumor cell proportion region in lung cancer during CT-guided transthoracic biopsy

Role of iodine density value on dual-energy CT for detection of high tumor cell proportion region in lung cancer during CT-guided transthoracic biopsy

Differentiation of pathological subtypes and Ki-67 and TTF-1 expression by dual-energy CT (DECT) volumetric quantitative analysis in non-small cell lung cancer

Clinical value of dual energy CT combined with CEA and CY21-1 in predicting EGFR gene mutation in lung adenocarcinoma

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