Use of Sensor Array Analysis to Detect Ovarian Cancer through Breath, Urine, and Blood: A Case-Control Study.

carbohydrate antigen 125 human epididymis protein 4 ovarian cancer sensor array

Journal

Diagnostics (Basel, Switzerland)
ISSN: 2075-4418
Titre abrégé: Diagnostics (Basel)
Pays: Switzerland
ID NLM: 101658402

Informations de publication

Date de publication:
06 Mar 2024
Historique:
received: 22 01 2024
revised: 26 02 2024
accepted: 27 02 2024
medline: 13 3 2024
pubmed: 13 3 2024
entrez: 13 3 2024
Statut: epublish

Résumé

Ovarian cancer (OC) is the eighth most common cancer in women. Since screening programs do not exist, it is often diagnosed in advanced stages. Today, the detection of OC is based on clinical examination, transvaginal ultrasound (US), and serum biomarker (Carbohydrate Antigen 125 (CA 125) and Human Epididymis Protein 4 (HE4)) dosage, with a sensitivity of 88% and 95%, respectively, and a specificity of 84% for US and 76% for biomarkers. These methods are clearly not enough, and OC in its early stages is often missed. Many scientists have recently focused their attention on volatile organic compounds (VOCs). These are gaseous molecules, found in the breath, that could provide interesting information on several diseases, including solid tumors. To detect VOCs, an electronic nose was invented by a group of researchers. A similar device, the e-tongue, was later created to detect specific molecules in liquids. For the first time in the literature, we investigated the potential use of the electronic nose and the electronic tongue to detect ovarian cancer not just from breath but also from urine, blood, and plasma samples.

Identifiants

pubmed: 38473033
pii: diagnostics14050561
doi: 10.3390/diagnostics14050561
pii:
doi:

Types de publication

Journal Article

Langues

eng

Auteurs

Roberto Angioli (R)

Unit of Gynecology, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 200, 00128 Rome, Italy.

Marco Santonico (M)

Unit of Electronics for Sensor Systems, Department of Science and Technology for Sustainable Development and One Health, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy.

Giorgio Pennazza (G)

Unit of Electronics for Sensor Systems, Department of Engineering, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy.

Roberto Montera (R)

Unit of Gynecology, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 200, 00128 Rome, Italy.

Daniela Luvero (D)

Unit of Gynecology, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 200, 00128 Rome, Italy.

Alessandra Gatti (A)

Unit of Gynecology, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 200, 00128 Rome, Italy.

Alessandro Zompanti (A)

Unit of Electronics for Sensor Systems, Department of Engineering, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy.

Panaiotis Finamore (P)

Unit of Geriatrics, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 200, 00128 Rome, Italy.

Raffaele Antonelli Incalzi (RA)

Unit of Geriatrics, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 200, 00128 Rome, Italy.

Classifications MeSH