Trial reportEuropean radiology2015
Detection and quantification of the solid component in pulmonary subsolid nodules by semiautomatic segmentation.
Trial report in European radiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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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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Who cites it
31 citing papers in PubMed.
- Scientific evidence of commercial artificial intelligence products for pulmonary nodule assessment on CT scans: a systematic review.European radiology · 2026Article
- Image-Based Deep Learning Model for Predicting Lymph Node Metastasis in Lung Adenocarcinoma With CT ≤ 2 cm.Thoracic cancer · 2025Article
- Preoperative markers for identifying CT ≤2 cm solid nodules of lung adenocarcinoma based on image deep learning.Thoracic cancer · 2024Article
- Accuracy of solid portion size measured on multiplanar volume rendering images for assessing invasiveness in lung adenocarcinoma manifesting as subsolid nodules.Quantitative imaging in medicine and surgery · 2024Article
- The value of CT shape quantification in predicting pathological classification of lung adenocarcinoma.BMC cancer · 2024Article
- Generative Adversarial Network (Generative Artificial Intelligence) in Pediatric Radiology: A Systematic Review.Children (Basel, Switzerland) · 2023Review
- CT-based three-dimensional invasiveness analysis of adenocarcinoma presenting as pure ground-glass nodules.Translational cancer research · 2023Article
- Artificial-intelligence-based computed tomography histogram analysis predicting tumor invasiveness of lung adenocarcinomas manifesting as radiological part-solid nodules.Frontiers in oncology · 2023Article
- Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective.Pediatric radiology · 2022Review
- Artificial intelligence-based CT metrics used in predicting clinical outcome of COVID-19 in young and middle-aged adults.Medical physics · 2022Article
- Development and Validation of a Comprehensive Model for Predicting Distant Metastasis of Solid Lung Adenocarcinoma: 3D Radiomics, 2D Radiomics and Clinical Features.Cancer management and research · 2022Article
- A radiomics nomogram for invasiveness prediction in lung adenocarcinoma manifesting as part-solid nodules with solid components smaller than 6 mm.Frontiers in oncology · 2022Article
- Quantitative CT for detecting COVID‑19 pneumonia in suspected cases.BMC infectious diseases · 2021Article
- Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?Thoracic cancer · 2021Article
- Prediction of microvascular invasion of hepatocellular carcinoma: value of volumetric iodine quantification using preoperative dual-energy computed tomography.Cancer imaging : the official publication of the International Cancer Imaging Society · 2020Article
- Optimal Attenuation Threshold for Quantifying CT Pulmonary Vascular Volume Ratio.Korean journal of radiology · 2020Article
- Unravelling complexities of the subsolid pulmonary nodule-detection, characterization, natural history, monitoring and (future) patient management.Journal of thoracic disease · 2019Article
- Quality assurance and quantitative imaging biomarkers in low-dose CT lung cancer screening.The British journal of radiology · 2018Review
- Effect of CT window settings on size measurements of the solid component in subsolid nodules: evaluation of prediction efficacy of the degree of pathological malignancy in lung adenocarcinoma.The British journal of radiology · 2018Article
- Pulmonary subsolid nodules: value of semi-automatic measurement in diagnostic accuracy, diagnostic reproducibility and nodule classification agreement.European radiology · 2018Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo determine whether semiautomatic volumetric software can differentiate part-solid from nonsolid pulmonary nodules and aid quantification of the solid component.
methodsAs per reference standard, 115 nodules were differentiated into nonsolid and part-solid by two radiologists; disagreements were adjudicated by a third radiologist. The diameters of solid components were measured manually. Semiautomatic volumetric measurements were used to identify and quantify a possible solid component, using different Hounsfield unit (HU) thresholds. The measurements were compared with the reference standard and manual measurements.
resultsThe reference standard detected a solid component in 86 nodules. Diagnosis of a solid component by semiautomatic software depended on the threshold chosen. A threshold of -300 HU resulted in the detection of a solid component in 75 nodules with good sensitivity (90%) and specificity (88%). At a threshold of -130 HU, semiautomatic measurements of the diameter of the solid component (mean 2.4 mm, SD 2.7 mm) were comparable to manual measurements at the mediastinal window setting (mean 2.3 mm, SD 2.5 mm [p = 0.63]).
conclusionSemiautomatic segmentation of subsolid nodules could diagnose part-solid nodules and quantify the solid component similar to human observers. Performance depends on the attenuation segmentation thresholds. This method may prove useful in managing subsolid nodules. KEY POINTS: • Semiautomatic segmentation can accurately differentiate nonsolid from part-solid pulmonary nodules • Semiautomatic segmentation can quantify the solid component similar to manual measurements • Semiautomatic segmentation may aid management of subsolid nodules following Fleischner Society recommendations • Performance for the segmentation of subsolid nodules depends on the chosen attenuation thresholds.
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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.