Diagnosis by Volatile Organic Compounds in Exhaled Breath in Exhaled Breath from Patients with Gastric and Colorectal Cancers.
Jinwook ChungSalima AkterSunhee HanYoonhwa ShinTae Gyu ChoiInsug KangSung Soo KimPublished in: International journal of molecular sciences (2022)
One in three cancer deaths worldwide are caused by gastric and colorectal cancer malignancies. Although the incidence and fatality rates differ significantly from country to country, the rates of these cancers in East Asian nations such as South Korea and Japan have been increasing each year. Above all, the biggest danger of this disease is how challenging it is to recognize in its early stages. Moreover, most patients with these cancers do not present with any disease symptoms before receiving a definitive diagnosis. Currently, volatile organic compounds (VOCs) are being used for the early prediction of several other diseases, and research has been carried out on these applications. Exhaled VOCs from patients possess remarkable potential as novel biomarkers, and their analysis could be transformative in the prevention and early diagnosis of colon and stomach cancers. VOCs have been spotlighted in recent studies due to their ease of use. Diagnosis on the basis of patient VOC analysis takes less time than methods using gas chromatography, and results in the literature demonstrate that it is possible to determine whether a patient has certain diseases by using organic compounds in their breath as indicators. This study describes how VOCs can be used to precisely detect cancers; as more data are accumulated, the accuracy of this method will increase, and it can be applied in more fields.
Keyphrases
- gas chromatography
- case report
- mass spectrometry
- newly diagnosed
- systematic review
- ejection fraction
- childhood cancer
- squamous cell carcinoma
- tandem mass spectrometry
- machine learning
- risk assessment
- papillary thyroid
- radiation therapy
- gas chromatography mass spectrometry
- high resolution
- high resolution mass spectrometry
- big data
- patient reported outcomes