Evidence map›Paper›PMID 29862031›Full record

ArticleBMJ open respiratory research2018

Image enhancement technology in bronchoscopy: a prospective multicentre study in lung cancer.

Erik H F M van der Heijden, Piero Candoli, Igor Vasilev, Alessandro Messi, Javier Pérez Pallarés, Piotr Yablonskii, Anna van der Vorm, Olga C J Schuurbiers, Wouter Hoefsloot

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in BMJ open respiratory research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02285426 (A Multicenter Study Evaluating the Diagnostic Value for Vascular Abnormalities of High Definition Bronchoscopy When Combined With I-scan Imaging Technology Compared to High Defintion Bronchoscopy Alone), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.5field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

NCT02285426 completednot on this map

A Multicenter Study Evaluating the Diagnostic Value for Vascular Abnormalities of High Definition Bronchoscopy When Combined With I-scan Imaging Technology Compared to High Defintion Bronchoscopy Alone

TypeobservationalSponsorRadboud University Medical CenterRan2014 to 2017Enrolled134ConditionsLungcancerArmsPentax EB-1990i HD-bronchoscope guided biopsy
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Automatic lesion detection for narrow-band imaging bronchoscopy.Journal of medical imaging (Bellingham, Wash.) · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 4 countries.

Erik H F M van der HeijdenDepartment of Pulmonary Diseases (614), Radboud University Medical Center, Nijmegen, The Netherlands.ORCID 0000-0003-3596-518X
Piero CandoliOspedale Umberto I, Viale Dante Alighieri, Ravenna, Italy.
Igor VasilevCenter of Thoracic Surgery, St-Petersburg Research Institute of TB and Thoracic Surgery, St Petersburg, Russia.
Alessandro MessiOspedale Umberto I, Viale Dante Alighieri, Ravenna, Italy.
Javier Pérez PallarésHospital General Universitario Santa Lucia, Cartagena, Spain.
Piotr YablonskiiCenter of Thoracic Surgery, St-Petersburg Research Institute of TB and Thoracic Surgery, St Petersburg, Russia.
Anna van der VormDepartment of Pulmonary Diseases (614), Radboud University Medical Center, Nijmegen, The Netherlands.
Olga C J SchuurbiersDepartment of Pulmonary Diseases (614), Radboud University Medical Center, Nijmegen, The Netherlands.
Wouter HoefslootDepartment of Pulmonary Diseases (614), Radboud University Medical Center, Nijmegen, The Netherlands.
Radboud University Nijmegen · NLOspedali Riuniti Umberto I · ITTampa Bay Research Institute · USSanta Lucía University General Hospital · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPatients with lung cancer may present with additional lesions in the central airways. Earlier studies have shown a relationship between vessel diameter, pattern and grade of malignancy. High-definition (HD+) bronchoscopy with image enhancement techniques (i-scan) detected more vascular abnormalities but correlation with pathology has not yet been established.

methodsIn this investigator-initiated, randomised, controlled, crossover, multicentre study in patients with suspected lung cancer, a HD+ bronchoscopy was performed with i-scan1 and i-scan2 settings in random order. Biopsies, visual grade and vascular pattern classification were obtained by endoscopists and blinded evaluation.

resultsIn 107 patients, vascular patterns were classified in 48 tumours. Abrupt-ending vessels were predominantly found in squamous cell carcinoma but overall correlation between vessel pattern and histology was not significant (p=0.339). Additional lesions were detected in 35 patients (33%) with a correlation between vessel pattern and high-grade (pre-)invasive lesions (p<0.001). In 8.4% of the patients, relevant second lesions were detected which determined treatment and staging in 3% of all patients. Interobserver agreement was excellent for visual grading of the airway epithelium, but low for classifying vascular patterns. No significant detection rate difference was found by blinded and unblinded evaluation.

conclusionHD+ bronchoscopy with i-scan image enhancement readily detects additional lesions. In one-third of all the patients, additional lesions were detected. Their vascular pattern correlates to pathology outcome, but the interobserver correlation for vascular pattern classification is low. These lesions were relevant in 8.4% and affected treatment and work-up in 3% of the cases. TRIAL REGISTRATION NUMBER: NCT02285426; Results.

Indexed as

bronchoscopyhistology/cytologyimaging/ct MRI etclung cancernon-small cell lung cancer

Identifiers

PMID29862031
PMCPMC5976136
OpenAlexW2805001268

What OpenQuestion holds

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LicenceCC BY-NC
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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.