An “electronic nose” detects pancreatic and ovarian cancers by the odors emitted from cells in blood plasma cells.

A study from researchers at the University of Pennsylvania and Penn’s Perelman School of Medicine shows that a new tool uses AI and machine learning to “sniff” vapors emanating from blood samples and thereby distinguish between benign and pancreatic and ovarian cancer cells with up to 95% accuracy. (Penn Medicine News)

Non-invasive test

Blood plasma cells emit volatile organic compounds (VOCs). The tool devised by Penn analyzes the mix of these VOCs using AI and machine learning.

“It’s an early study but the results are very promising,” said A. T. Charlie Johnson, PhD, the Rebecca W. Bushnell Professor of Physics and Astronomy in Penn’s School of Arts & Sciences. “The data shows we can identify these tumors at both advanced and the earliest stages, which is exciting.

“If developed appropriately for the clinical setting, this could potentially be a test that’s done on a standard blood draw that may be part of your annual physical.”

How it works

The researchers were aware from previous studies that VOCs released from tissue and plasma from ovarian cancer patients were distinct from those released from samples of patients with benign tumors.

They therefore trained the AI tool to identify the VOC patterns more associated with cancer cells and those associated with cells from healthy blood samples. Using electronic olfaction, an “e-nose” system equipped with nanosensors was calibrated to detect the composition of VOCs, which all cells emanate.

Test results

Among 93 patients, including 20 patients with ovarian cancer, 20 with benign ovarian tumors and 20 age-matched controls with no cancer, as well as 13 patients with pancreatic cancer, 10 patients with benign pancreatic disease, and 10 controls, the vapor sensors discriminated the VOCs from ovarian cancer with 95% accuracy and pancreatic cancer with 90% accuracy.

The tool also correctly identified all patients (a total of eight) with early-stage cancers.

Furthermore, it could generate a result in 20 minutes or less.

Commercialization on the anvil

The Penn researchers are working with VOC Health and other parties to commercialize the tool for clinical and research uses.

“Initial prototypes of commercial devices able to detect cancer from liquids and vapors will be ready soon and be provided to these Penn researchers to further their work,” said Richard Postrel, CEO and chief innovation officer of VOC Health.

Related Story:  Prostate Cancer Diagnosis Now More Accurate With AI  

Image of ovarian cancer:  Wikimedia Commons