Analysis of Breath Volatile Organic Compounds Using Mass Spectrometry

Brief summary public domain (ClinicalTrials.gov)

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.

Detailed description public domain (ClinicalTrials.gov)

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.

Intervention public domain (ClinicalTrials.gov)

Device: Proton Transfer Reaction Mass Spectrometry Analysis. 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.

Arm public domain (ClinicalTrials.gov)

Diagnosed Malignancies (): Participants in this group either have a newly diagnosed, untreated cancer or a pre-existing cancer diagnosis but are not currently receiving anticancer therapy. Participants with a pre-existing diagnosis must not have received any anticancer treatment within the previous month.

Arm public domain (ClinicalTrials.gov)

Healthy Control Group (): Participants in this control group have no current or prior diagnosis of a malignancy.

Primary outcome public domain (ClinicalTrials.gov)

VOC Signature Collection.. The successful collection of breath samples from 1000 cancer patients and 1000 healthy volunteers. Time frame: 2 Years.

Primary outcome public domain (ClinicalTrials.gov)

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 outcome public domain (ClinicalTrials.gov)

Assess The Specificity and Accuracy of ML Analysis In The Test Dataset.. Time frame: 1 year.

Eligibility public domain (ClinicalTrials.gov)

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

Enrollment public domain (ClinicalTrials.gov)

Enrollment: 2000 participants (estimated).