Evidence map›Paper›PMID 42295586›Full record

ArticleLa Radiologia medica2026

Spectral CT-based intratumoral and peritumoral radiomics for predicting invasiveness of ground-glass nodules in lung adenocarcinoma.

Daoyu Yang, Shaolei Kang, Xunran Zhao, Xiaojie Xie, Fajin Lv, Guochen Li, Jian Liu, Zhiquan Han, Xiaoxuan Zhang, Xianchun Zeng

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in La Radiologia medica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Daoyu Yang *Medical College, Guizhou University, Guiyang, Guizhou, China.
Shaolei Kang *Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Xunran ZhaoDepartment of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Xiaojie XieDepartment of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Fajin LvDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Guochen LiMedical College, Guizhou University, Guiyang, Guizhou, China.
Jian LiuDepartment of Nuclear Medicine, Guizhou Provincial People's Hospital, Guiyang, , Guizhou, China.
Zhiquan HanDepartment of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Xiaoxuan ZhangMedical College, Guizhou University, Guiyang, Guizhou, China.
Xianchun ZengDepartment of Nuclear Medicine, Guizhou Provincial People's Hospital, Guiyang, , Guizhou, China. zengxianchun04@foxmail.com.ORCID http://orcid.org/0000-0003-0857-3834

Funding

Guizhou hundred levels of personnel training program project QKHPTRC-GCC [2023] 083National Natural Science Foundation of China 82460344
6 · The paper itself

Abstract

objectivesTo evaluate the potential of spectral detector computed tomography (SDCT) combined with intratumoral and peritumoral radiomics for noninvasive characterization of lung adenocarcinomas (LUAD) presenting as ground-glass nodules (GGNs).

methodsThis retrospective multicenter study included patients from two centers. In Center 1, 241 patients with GGNs (adenocarcinoma in situ [AIS], n = 42; minimally invasive adenocarcinoma [MIA], n = 138; invasive adenocarcinoma [IAC], n = 61) were randomly split into training and test sets (7:3). Center 2 served as an external validation cohort including 87 patients (AIS, n = 35; MIA, n = 27; IAC, n = 25). All patients underwent unenhanced dual-layer SDCT examinations. Radiomics features were extracted from intratumoral and peritumoral regions (1-5 mm) based on SDCT-derived conventional polychromatic images (CPI), effective atomic number (Z

resultsAmong all peritumoral models, the 2 mm peritumoral multiparameter fusion model showed the best performance, with macro-average AUCs of 0.795 and 0.768 in the internal and external validation sets, respectively. Combining intratumoral and peritumoral multiparameter models further improved performance, achieving internal AUCs of 0.814, 0.863, and 0.988 and external AUCs of 0.898, 0.774, and 0.812 for AIS, MIA, and IAC, respectively.

conclusionsThe combination of intratumoral and peritumoral multiparametric radiomics derived from SDCT may enhance the noninvasive differentiation of LUAD presenting as GGNs, potentially serving as a valuable tool for supporting clinical decision-making.

Indexed as

Adenocarcinoma of LungLung NeoplasmsRadiomicsTomography, X-Ray ComputedAgedFemaleHumansMaleMiddle AgedNeoplasm InvasivenessPredictive Value of TestsRetrospective StudiesGround-glass nodulesLung adenocarcinomaMachine learningRadiomicsSpectral detector CT

Identifiers

PMID42295586

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.