Trial reportJournal of clinical oncology : official journal of the American Society of Clinical Oncology2011
Variability of lung tumor measurements on repeat computed tomography scans taken within 15 minutes.
Trial report in Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 1 of them a synthesis that pooled it.
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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.
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
85 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Twenty Years On: RECIST as a Biomarker of Response in Solid Tumours an EORTC Imaging Group - ESOI Joint Paper.Frontiers in oncology · 2021Pooled it
- Trial
- Total intracranial hemorrhage volume measurement summating all compartments best in traumatic and nontraumatic intracranial bleeding.Brain and behavior · 2024Trial
- Exploring intra- and inter-reader variability in uni-dimensional, bi-dimensional, and volumetric measurements of solid tumors on CT scans reconstructed at different slice intervals.European journal of radiology · 2013Trial
- Impact of the first tumor response at eight weeks on overall survival in metastatic breast cancer patients treated with first-line combination chemotherapy.Medical oncology (Northwood, London, England) · 2013Trial
- Article
- Assessing the reliability of Response Evaluation Criteria In Solid Tumors (RECIST): a systematic review of the factors contributing to inter-observer variability.Insights into imaging · 2026Article
- Evaluation of an artificial intelligence generated Brock score to determine malignancy risk of screen-detected pulmonary nodules.European journal of radiology open · 2026Article
- Impact of reconstruction kernel variability on segmentation consistency in low-dose thoracic CT.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- Cohort-Aware Agents for Individualized Lung Cancer Risk Prediction Using a Retrieval-Augmented Model Selection Framework.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- Deep-Learning Serial CT Prediction of Survival in Immunotherapy-Treated Non-Small Cell Lung Cancer.JAMA network open · 2026Article
- Physician-guided deep learning model for assessing thymic epithelial tumor volume.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- Variability of HCC Tumor Diameter and Density Measurements on Dynamic Contrast-Enhanced Computed Tomography.Tomography (Ann Arbor, Mich.) · 2025Article
- Performance of Lung Cancer Prediction Models for Screening-detected, Incidental, and Biopsied Pulmonary Nodules.Radiology. Artificial intelligence · 2025Article
- A reduction in tumor volume exceeding 65% predicts a good histological response to neoadjuvant chemotherapy in patients with Ewing sarcoma.Skeletal radiology · 2024Article
- Annotated test-retest dataset of lung cancer CT scan images reconstructed at multiple imaging parameters.Scientific data · 2024Article
- Feasibility of an artificial intelligence system for tumor response evaluation.BMC medical imaging · 2024Article
- Imaging diagnostics of pulmonary ground-glass nodules: a narrative review with current status and future directions.Quantitative imaging in medicine and surgery · 2024Review
- New Anticancer Drugs: Reliably Assessing "Value" While Addressing High Prices.Current oncology (Toronto, Ont.) · 2024Article
- Postoperative recurrence detection using individualized circulating tumor DNA in upper tract urothelial carcinoma.Cancer science · 2024Article
25 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
purposeWe use changes in tumor measurements to assess response and progression, both in routine care and as the primary objective of clinical trials. However, the variability of computed tomography (CT) -based tumor measurement has not been comprehensively evaluated. In this study, we assess the variability of lung tumor measurement using repeat CT scans performed within 15 minutes of each other and discuss the implications of this variability in a clinical context. PATIENTS AND
methodsPatients with non-small-cell lung cancer and a target lung lesion ≥ 1 cm consented to undergo two CT scans within a period of minutes. Three experienced radiologists measured the diameter of the target lesion on the two scans in a side-by-side fashion, and differences were compared.
resultsFifty-seven percent of changes exceeded 1 mm in magnitude, and 33% of changes exceeded 2 mm. Median increase and decrease in tumor measurements were +4.3% and -4.2%, respectively, and ranged from 23% shrinkage to 31% growth. Measurement changes were within ± 10% for 84% of measurements, whereas 3% met criteria for progression according to Response Evaluation Criteria in Solid Tumors (RECIST; ≥ 20% increase). Smaller lesions had greater variability of percent measurement change (P = .005).
conclusionApparent changes in tumor diameter exceeding 1 to 2 mm are common on immediate reimaging. Increases and decreases less than 10% can be a result of the inherent variability of reimaging. Caution should be exercised in interpreting the significance of small changes in lesion size in the care of individual patients and in the interpretation of clinical trial results.
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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.