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UnknownNCT03967652

Cancer Diagnoses From Exhaled Breath With Na-nose

Diagnosing Cancers From Healthy From Human Exhaled Breath With Na-nose

Status
Unknown
Phase
Study type
Observational
Enrollment
10,000 (estimated)
Sponsor
Anhui Medical University · Academic / Other
Sex
All
Age
18 Years – 75 Years
Healthy volunteers
Accepted

Summary

Early diagnoses of malignant tumors are pivotal for improving their prognoses. The Exhaled Breath is made up of oxygen, carbon dioxide, nitrogen, water, inert gases and volatile organic compounds (VOCs). Theoretically, the concentration of VOCs in exhalation produced by metabolism in human body is only about nmol/L-pmol/L, which can significantly increase under certain pathological conditions. A series of studies of VOCs diagnosing solid tumors the investigators had been conducted in the past decade. It was found that VOCs in exhaled breath can not only distinguish different types of tumors, but also can make a clear distinction between different stages. Our long-term collaborator, Professor Hossam Haick (Israel Institute of Technology) has developed a nano sensor array, so called Na-nose, which can detect VOCs of the exhaled breath by binding gases to specific chemiresistors coated with gold nanomaterials. The Na-nose has the advantages of low cost, easy to use, good reproducibility and real-time detection for large scale clinical application. This study was to use large clinical samples to validate the diagnostic efficacy of the newly developed Nano-nose( Sniffphone and Breath Screener) for malignant tumors .

Detailed description

Israel Institute of Technology provides two type of Na-nose. One is Breath Screener used for large-scale sampling and feature VOCs extraction to establish database. The other is called Sniff Phone aim at clinical real-time VOCs detection assisted by software. About 10,000 patients will participate in the subject of Breath Screener in batches. First, 7000 patients will have a definitive diagnosis and exhaled breath collected. Feature VOCs of specific tumors will be extracted from these samples and employed to build predictive model by using discriminant factor analysis (DFA). After the predictive model had been completed, 3000 definitively diagnosed patients will participate in validating the specificity and sensitivity of the prediction model. With the assistance of Breath Screener clinical database and software services, Sniff Phone is more suitable for clinical real-time detection for its small and convenient design characteristics. At last, Breath Screener and Sniff Phone will continue enriching databases and improve diagnosis efficacy in their clinical applications.

Conditions

Interventions

TypeNameDescription
DIAGNOSTIC_TESTNanomaterial-based sensorsChemical sensors based on Monolayer-Capped Metallic Nanoparticles (MCMNPs) can recognize and classify exhaled breath by special recognition algorithm, which achieves the purpose of disease diagnosis.

Timeline

Start date
2019-07-01
Primary completion
2020-12-31
Completion
2022-12-31
First posted
2019-05-30
Last updated
2019-05-31

Source: ClinicalTrials.gov record NCT03967652. Inclusion in this directory is not an endorsement.