ArticleQuantitative imaging in medicine and surgery2026
Development and validation of intratumoral and peritumoral CT-based radiomics nomograms for predicting malignancy and invasiveness of pulmonary ground-glass nodules: a retrospective study.
Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Currently, it is still very challenging for radiologists to visually distinguish between benign and malignant ground-glass nodules (GGNs) and predict the degree of invasiveness of GGNs directly from computed tomography (CT) images. Radiomics is a newly emerging technique that can transform digital medical images into numerous quantitative features revealing pathophysiology. The present study aimed to evaluate the predictive value of intratumoral and peritumoral CT-based radiomics and the radiomics nomogram for determining the benign or malignant status of pulmonary GGNs and the invasiveness of malignant GGNs. Methods: A total of 1,372 GGNs from 1,280 patients with preoperative CT scans were included in this retrospective study. Among these, 212 GGNs were diagnosed with inflamed or infected benign lesions, 31 with atypical adenomatous hyperplasia (AAH), 257 with adenocarcinoma in situ (AIS), 559 with minimally invasive adenocarcinoma (MIA), and 313 with invasive adenocarcinoma (IAC). Malignant GGNs were classified according to clinical management strategies, with AAH, AIS, and MIA categorized as non-invasive lesions, and IAC as an invasive lesion. Two types of regions of interest (ROIs) were annotated from the CT images: gross tumor volume (GTV) and peritumoral volume (5 and 10 mm around the tumor, PTV Results: For malignancy predictions, the GTV + PTV Conclusions: The radiomic signatures of both GTV and PTV
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.