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nCLE-guided bronchoscopy for peripheral lung cancer diagnosis: a Randomized Controlled Trial

nCLE-guided bronchoscopy for peripheral lung cancer diagnosis: a Randomized Controlled Trial - Confocal Laser Endomicroscopy Verification (CLEVER)

Status
Recruiting
Phases
Unknown
Study type
Interventional
Source
NL-OMON
Registry ID
NL-OMON53986
Enrollment
45
Registered
2023-05-10
Start date
2023-10-17
Completion date
Unknown
Last updated
2024-11-04

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Peripheral lung cancer

Interventions

Bronchoscopy will be performed as usual, including radial endobronchial ultrasound (r-EBUS) and optionally fluoroscopy, followed by transbronchial needle aspiration (TBNA and (cryo-)biopsies (contro

Sponsors

Academisch Medisch Centrum
Lead Sponsor

Eligibility

Age
18 Years to 99 Years

Inclusion criteria

Inclusion criteria: • >=18 years of age • Suspected malignant peripheral lung lesion with an indication for a bronchoscopic diagnostic work-up • Solid part of the lesion must be >10 mm • Largest dimension of lesion size on CT equal to or less than 30 mm • Bronchus sign on pre-procedural CT or estimated confidence for successful navigation to the nodule resulting in a r-EBUS signal • Ability to understand and willingness to sign a written informed consent

Exclusion criteria

Exclusion criteria: • Inability or non-willingness to provide informed consent • Patients with an endobronchial visible lung tumor on bronchoscopic inspection • Patients in which the target lesion is within reach of the linear EBUS scope • Failure to comply with the study protocol • Patients with known allergy for fluorescein or risk factors for an allergic reaction • Pregnant or breastfeeding women • Patients with hemodynamic instability • Patients with refractory hypoxemia • Patients with a therapeutic anticoagulant that cannot be held for an appropriate interval before the procedure • Patients who are unable to tolerate general anesthesia according to the anesthesiologist • Patient undergoing chemotherapy as several chemotherapies have fluorescent properties at the same wavelength (e.g. doxorubicin) • Inability to follow-up

Design outcomes

Primary

MeasureTime frame
To determine if the addition of nCLE-imaging to conventional bronchoscopic peripheral lung lesion analysis results in an improved diagnostic yield.

Secondary

MeasureTime frame
1. Diagnostic sensitivity for malignancy (defined as the proportion of patients that have malignancy diagnosed by bronchoscopic tissue sampling, relative to the total number of patients with a final diagnosis of malignancy as determined by the reference standard). 2. Procedure duration (from bronchoscope insertion until removal) 3. Amount and proportion of needle repositionings (defined as the selection of a different distal airway for tissue sampling) and needle fine-tuning tuned (defined as moving the needle within the same distal airway) per arm 4. To assess the diagnostic yield for several lesion and procedural characteristics (lesion size, bronchus sign, eccentric vs concentric vs absent radial EBUS image, location) 5. Fluoroscopy time and radiation dose 6. To extend the nCLE image atlas for malignant and benign pathologies 7. To assess the yield of ROSE for a classifying diagnosis 8. To assess the ability of ROSE to provide tool-in-lesion-confirmation (the acquisition of tissue not related to airway/lung parenchyma sampling such as bronchus epithelium/blood contamination including tissue not suitable for a specific diagnosis such as atypical cells) 9. Complication rate (defined as any complication occurring during or directly after the bronchoscopic procedure or any procedure-related complication in the follow-up period). 10. Proportion of patients per arm that need additional diagnostic procedures (CT-guided transthoracic biopsies, surgical diagnostics and/or additional bronchoscopy) after the bronchoscopy during the 6-month follow-up period. 11. Create an algorithm for automated nCLE criteria recognition (for example machine learning)

Countries

Netherlands

Outcome results

None listed

Source: NL-OMON (via WHO ICTRP)