Evidence map›Paper›PMID 39456114›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2024

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.

Yuting Wu, Jingxu Li, Li Ding, Jianbin Huang, Mingwang Chen, Xiaomei Li, Xiang Qin, Lisheng Huang, Zhao Chen, Yikai Xu and 1 more

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Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. [Research progress on predicting radiation pneumonia based on four-dimensional computed tomography ventilation imaging in lung cancer radiotherapy].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025
    Review
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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Yuting Wu *Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Jingxu Li *Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Li DingDepartment of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Jianbin HuangDepartment of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Mingwang ChenDepartment of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Xiaomei LiDepartment of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Xiang QinDepartment of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Lisheng HuangDepartment of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Zhao ChenDepartment of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Yikai XuDepartment of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China. yikaixu917@gmail.com.
Chenggong YanDepartment of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China. ycgycg007@gmail.com.

Funding

National Natural Science Foundation of China 82271987
6 · The paper itself

Abstract

backgroundTo 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).

methodsBetween 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.

resultsThis 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.

conclusionsThe 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.

Indexed as

Carcinoma, Non-Small-Cell LungKi-67 AntigenLung NeoplasmsAgedBiomarkers, TumorDiagnosis, DifferentialFemaleHumansMaleMiddle AgedProspective StudiesROC CurveThyroid Nuclear Factor 1Tomography, X-Ray ComputedBiomarkers, TumorKi-67 AntigenNKX2-1 protein, humanThyroid Nuclear Factor 1Dual-energy CTNon-small cell lung cancerQuantitative analysisThyroid transcription factor 1

Identifiers

PMID39456114
PMCPMC11515807

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