Clinical trial · Observational
Evaluation of Contextflow DETECT Lung CT Nodule Detection Software in Chest CT Scans
Evaluation of Computer-Aided Lung Nodule Detection Software in Chest CT Scans With an Assessment of Its Impact on Readers Decision-Making Process
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
contextflow DETECT Lung CT is a Artificial Intelligence (AI)-based computed-aided detection (CADe) system, intended to support radiologists in the detection of lung nodules in chest computed tomography (CT) scans. System is intended to be used as a second-reader, therefore results provided by the software are meant to complement the radiologist's findings and decisions. Proposed study will be multi-reader, multi case (MRMC) retrospective reader study. The goal of the study is to evaluate the influence of CADe on the effectiveness of lung nodule detection. During the study, 10 radiologists will analyze 350 chest CT scans of adult patients, with and without the assistance of CADe. The study will be conducted remotely. CT scans will be uploaded to a web-based image submission and annotation platform, in which every participant of the study will be provided with individual account and assigned task list. The primary objective of the study determine if the diagnostic accuracy of radiologists with CADe assistance is superior to the diagnostic accuracy of radiologists without CADe assistance in localizing the pulmonary nodules with enhanced area under the free-response operating characteristic curve (AUC of FROC). The study will target approximately 350 asymptomatic adult patients, whose CT scans were acquired during routine CT examination. The patient population will include patients with and without lung nodules.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Lung Cancer | Malignant Lung Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Aided read with contextflow DETECT Lung CT | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- Asymptomatic adult patients
- interventionNames
- Device: Aided read with contextflow DETECT Lung CT
Primary outcomes (1)
- measure
- Diagnostic accuracy
- timeFrame
- 20 hours
- description
- The primary objective of the reader study is to determine if the diagnostic accuracy of radiologists with CADe assistance is superior to the diagnostic accuracy of radiologists without CADe assistance in localizing the pulmonary nodules with enhanced area under the free-response operating characteristic curve (AUC of FROC). The true positive rate (or sensitivity) is calculated as the identified positive lesion among the true positive divided by the total number of true positive lesions among all images. The number of false positive findings is collected per image.
Secondary outcomes (2)
- measure
- Disease diagnosis capabilities
- timeFrame
- 20 hours
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 22 Years
Show eligibility criteria text
Inclusion Criteria: * adult asymptomatic patients, who undergo a routine chest CT scan. Exclusion Criteria: * symptomatic patients.
References
Publications (3)
- BACKGROUNDHansell DM, Bankier AA, MacMahon H, McLoud TC, Muller NL, Remy J. Fleischner Society: glossary of terms for thoracic imaging. Radiology. 2008 Mar;246(3):697-722. doi: 10.1148/radiol.2462070712. Epub 2008 Jan 14. PMID 18195376
- BACKGROUNDSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4. PMID 33538338
- BACKGROUNDQian F, Yang W, Chen Q, Zhang X, Han B. Screening for early stage lung cancer and its correlation with lung nodule detection. J Thorac Dis. 2018 Apr;10(Suppl 7):S846-S859. doi: 10.21037/jtd.2017.12.123. PMID 29780631