Analysis of Breath Volatile Organic Compounds Using Mass Spectrometry

N/ANot Yet RecruitingNCT07732686

University of Oklahoma2,000 enrolled

Overview

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.

This study aims to determine whether metabolic changes associated with cancer produce distinct alterations in exhaled breath compared with those of healthy individuals. Breath samples will be analyzed using machine learning techniques to identify volatile organic compound (VOC) patterns and develop diagnostic algorithms capable of detecting multiple types of cancer. The long-term goal is to establish a noninvasive, breath-based screening tool that can facilitate the early detection of various cancers. Additionally, patients and healthy participants who consent to this study may opt in to be contacted in the future to provide additional breath samples.

Study Type

OBSERVATIONAL

Enrollment

2,000

Conditions

Pancreas Cancer Hepatocellular Carcinoma Lung Cancer Ovarian Cancer Breast Cancer Head and Neck Cancer

Interventions

Proton Transfer Reaction Mass Spectrometry AnalysisDEVICE

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.

Eligibility

Sex: ALLMin age: 18 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * 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. * Newly diagnosed cancer and untreated or established diagnosis of cancer. For established cancer patients, no active anti-cancer treatment for more than one month (reasons for no treatment are such as relapse, progression of cancer, refractory, or intolerance to treatment etc.) Exclusion Criteria: * Under the age of 18. * Anticipated inability to complete breath sampling procedure. * Unable to provide informed consent. * Pregnant women * Active respiratory infection symptoms * Recent use of antibiotics * Difficulty in performing coached exhalation * Individuals who are unable to follow the instructions * Cancer patients who are on active treatment for cancer or have received cancer treatment within one month

Outcomes

Primary Outcomes

VOC Signature Collection.

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

Time frame: 2 Years

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

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

Central Contacts

Lead Onco Nurse

CONTACT

405-271-8777 SCC-IIT-Office@ouhsc.edu

Nirmal Choradia, MD