ArticleEuropean radiology2013
Differentiation of malignant and benign pulmonary nodules with first-pass dual-input perfusion CT.
Article in European radiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02316327 (Phase IV/II Open-label Study to Evaluate Prompt Response to Treatment With Cisplatin, Gemcitabine and Bevacizumab in Patients With Non-small Lung Cancer.), which is not on this map. Cited by 25 papers, 2 of them syntheses that pooled it.
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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.
Phase IV/II Open-label Study to Evaluate Prompt Response to Treatment With Cisplatin, Gemcitabine and Bevacizumab in Patients With Non-small Lung Cancer.
Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 56 citations in OpenAlex.
- Safety and efficacy of drug-eluting beads versus conventional bronchial arterial chemoembolization for lung cancer: a systematic review and meta-analysis.Frontiers in oncology · 2026Pooled it
- Diagnostic Performance of Perfusion Computed Tomography for Differentiating Lung Cancer from Benign Lesions: A Meta-Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2019Pooled it
- Differential diagnosis of benign and malignant pulmonary nodules attached to the interlobar pleura.Quantitative imaging in medicine and surgery · 2026Article
- Optimal image-derived input function models for multi-parameter analysis and acceptably reduced acquisition time in [EJNMMI physics · 2025Article
- Differentiation of inflammatory pseudotumors and malignant pulmonary nodules using the time-to-peak in first-pass dual-input volume computed tomography-perfusion.Quantitative imaging in medicine and surgery · 2025Article
- Quantifying lower extremity blood flow using low-dose CT perfusion: validation in a swine model.Radiology advances · 2024Article
- The Role of CT Perfusion in Differentiating Benign Versus Malignant Focal Pulmonary Lesions.Cureus · 2024Article
- High-Temporal-Resolution Kinetic Modeling of Lung Tumors with Dual-Blood Input Function Using Total-Body Dynamic PET.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024Article
- Value of ultrasound guided biopsy combined with XpertWorld journal of clinical cases · 2023Article
- Thoracic Diseases: Technique and Applications of Dual-Energy CT.Diagnostics (Basel, Switzerland) · 2023Review
- A Novel Deep Learning Model to Distinguish Malignant Versus Benign Solid Lung Nodules.Medical science monitor : international medical journal of experimental and clinical research · 2022Article
- Evaluation of the dual vascular supply patterns in ground-glass nodules with a dynamic volume computed tomography.World journal of radiology · 2022Article
- Contrast timing optimization of a two-volume dynamic CT pulmonary perfusion technique.Scientific reports · 2022Article
- CT perfusion imaging can detect residual lung tumor early after radiofrequency ablation: a preliminary animal study on both tumoral and peri-tumoral region assessment.Journal of thoracic disease · 2022Article
- Pulmonary lesions: correlative study of dynamic triple-phase enhanced CT perfusion imaging with tumor angiogenesis and vascular endothelial growth factor expression.BMC medical imaging · 2021Article
- Comparison of Spectral and Perfusion Computed Tomography Imaging in the Differential Diagnosis of Peripheral Lung Cancer and Focal Organizing Pneumonia.Frontiers in oncology · 2021Article
- Article
- Dynamic pulmonary CT perfusion using first-pass analysis technique with only two volume scans: Validation in a swine model.PloS one · 2020Article
- Dual-input tracer kinetic modeling of dynamic contrast-enhanced MRI in thoracic malignancies.Journal of applied clinical medical physics · 2019Article
- Review
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo assess diagnostic performance of dual-input CT perfusion for distinguishing malignant from benign solitary pulmonary nodules (SPNs).
methodsFifty-six consecutive subjects with SPNs underwent contrast-enhanced 320-row multidetector dynamic volume CT. The dual-input maximum slope CT perfusion analysis was employed to calculate the pulmonary flow (PF), bronchial flow (BF), and perfusion index [Formula: see text]. Differences in perfusion parameters between malignant and benign tumours were assessed with histopathological diagnosis as the gold standard. Diagnostic value of the perfusion parameters was calculated using the receiver-operating characteristic (ROC) curve analysis.
resultsAmongst 56 SPNs, statistically significant differences in all three perfusion parameters were revealed between malignant and benign tumours. The PI demonstrated the biggest difference between malignancy and benignancy: 0.30 ± 0.07 vs. 0.51 ± 0.13 , P < 0.001. The area under the PI ROC curve was 0.92, the largest of the three perfusion parameters, producing a sensitivity of 0.95, specificity of 0.83, positive likelihood ratio (+LR) of 5.59, and negative likelihood ratio (-LR) of 0.06 in identifying malignancy.
conclusionsThe PI derived from the dual-input maximum slope CT perfusion analysis is a valuable biomarker for identifying malignancy in SPNs. PI may be potentially useful for lung cancer treatment planning and forecasting the therapeutic effect of radiotherapy treatment. KEY POINTS: • Modern CT equipment offers assessment of vascular parameters of solitary pulmonary nodules (SPNs) • Dual vascular supply was investigated to differentiate malignant from benign SPNs. • Different dual vascular supply patterns were found in malignant and benign SPNs. • The perfusion index is a useful biomarker for differentiate malignancy from benignancy.
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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.