Health TrialsbyHealthPanel

Analysis of Breath Volatile Organic Compounds Using Mass Spectrometry

ConditionsPancreas CancerHepatocellular CarcinomaLung CancerOvarian CancerBreast CancerHead and Neck CancerColon CancerBladder CancerOther Cancer
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorUniversity of Oklahoma

About this trial

The purpose of this clinical trial is to evaluate whether volatile organic compound (VOC) signatures detected in the breath of patients with cancer can serve as a potential screening tool for the early detection of cancer.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

Age ≥ 18 at the time of consent. Male and female patients to be tested.

Capable of understanding written and/or spoken English language.

Able to provide informed consent.

Cancer of any type.

Disqualifiers

Under the age of 18.

Anticipated inability to complete breath sampling procedure.

Unable to provide informed consent.

Pregnant women

Trial population

Patients diagnosed with malignancies and healthy individuals who meet the inclusion criteria.

Trial design

Design model

Cohort

Time perspective

Prospective

Treatments tested in this trial

  • Proton Transfer Reaction Mass Spectrometry Analysis

    Device

    This is a noninvasive intervention. Participants will be asked to provide a breath sample using a disposable mouthpiece equipped with a saliva/moisture trap and a non-rebreathing valve. Breath samples will be collected through normal, steady exhalation. The entire breath collection process is expected to take no more than 30 minutes to complete.

Treatment groups

2,000 Participants
are divided into 2 treatment groups
Group A: Diagnosed Malignancies1 intervention
Group B: Healthy Control Group1 intervention

Trial outcomes

Primary outcomes

1

VOC Signature Collection.

The successful collection of breath samples from 1000 cancer patients and 1000 healthy volunteers.

Time frame
2 Years
2

Assess the sensitivity of Machine Learning (ML) Algorithm In The Test Dataset.

Using the training dataset, qualitative output generated by the PTR-MS instrument will be analyzed using machine learning methods to identify volatile organic compound (VOC) patterns associated with different cancer types, including pancreatic, esophageal, hepatocellular carcinoma, lung, and ovarian cancers. The trained machine learning model will be tested using the dataset.

Time frame
1 Years

Secondary outcomes

1

Assess The Specificity and Accuracy of ML Analysis In The Test Dataset.

To determine the specificity, and overall diagnostic accuracy of the machine learning (ML) algorithm for detecting pancreatic, esophageal, hepatocellular carcinoma, lung, and ovarian cancers within the test dataset.

Time frame
1 year

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

University of Oklahoma

Lead sponsor

Source ClinicalTrials.gov

This trial is not recruiting at the moment. You can still explore other options: