Evidence map›Paper›PMID 36595045›Full record

ArticleJournal of cancer research and clinical oncology2023

Dual-layer spectral detector CT (SDCT) can improve the detection of mixed ground-glass lung nodules.

Zhenghua Zhang, Fang Yin, Shaolei Kang, Xiaoyu Tuo, Xiaodi Zhang, Dan Han

Abstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
  6. Quantitative parameters of HRCT target scan to predict the risk of lung adenocarcinoma based on the detection of lung ground-glass nodules.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
    Article
  7. Article
  8. Predictive value of spectral dual-detector computed tomography forQuantitative imaging in medicine and surgery · 2024
    Article
  9. Article
  10. Article
4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Zhenghua ZhangMedical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Fang YinMedical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Shaolei KangMedical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Xiaoyu TuoPathology Department, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Xiaodi ZhangPhilips Healthcare, Chengdu, China.
Dan HanMedical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, China. kmhandan@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMixed ground-glass lung nodules are a high-risk factor for lung adenocarcinoma. This study aimed to analyze the value of SDCT electron density imaging in the detection of mixed ground-glass lung nodules (GGNs).

method150 patients with GGNs confirmed by chest SDCT and surgical pathology were retrospectively analyzed. GGNs were screened by two senior radiologists by the double-blind method based on conventional CT and SDCT electron density images. Average CT values and electron density (ED) values of GGNs were measured for all, solid and ground-glass.

resultThirty pGGN cases determined by conventional CT were found to be mGGN on electron density images, including 23 in the invasive adenocarcinoma group (detection rate of 35.38%), which was significantly higher than that of the PGL group (14.89%, P < 0.05). In electron density images, average CT values and ED values in the PGL and invasive adenocarcinoma groups with pGGNs were no difference. The average CT value and ED value were significantly higher in the mGGN invasive adenocarcinoma group compared with the PGL group (P < 0.05). Meanwhile, ROC curve analysis of average CT value and ED value revealed AUC values for mGGN infiltration of 0.759 and 0.752.

conclusionSDCT can improve GGN visualization and increase the detection rate of mGGN compared with conventional CT. Attention should be paid to invasive adenocarcinoma for lung GGNs detected as mGGNs with high average CT value or ED value.

Indexed as

AdenocarcinomaLung NeoplasmsPrecancerous ConditionsDouble-Blind MethodHumansLungNeoplasm InvasivenessRetrospective StudiesTomography, X-Ray ComputedAdenocarcinomaComputed tomographyLung cancerPulmonary nodule

Identifiers

PMID36595045
PMCPMC9808726

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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.