"Potentially in the future one can use imaging to directly reveal multiple features of diseases that will make it much easier to carry out personalized medicine, where you are making diagnoses and treatment decisions based exactly on what is happening in a person," said co-senior author Howard Chang, MD, PhD, assistant professor of dermatology at Stanford.
The study's other senior author is Michael Kuo, MD, assistant professor of interventional radiology at University of California, San Diego (UCSD), who said their work will help doctors obtain the molecular details of a specific tumour or disease without having to remove body tissue for a biopsy.
"When we look at noninvasive images, there are lots and lots of different patterns that had no known meaning," said Chang. "We thought that maybe we could come up with a way to systematically connect the gene activity seen with microarrays to imaging patterns, to translate meaning into three different types of languages, from genes to images and then to outcome of the disease process."
Kuo and his radiology colleagues initially defined mutually agreeable terminology for more than 100 features that appeared on scans. As their work progressed, they found they only needed 28 of them to capture maximal information.
What they found is that two very different aspects of cancer - how it looks by imaging and how it behaves on a molecular level - have a strong connection. Out of the 5,000 or more genes that have different activity in cancerous tissue, the researchers could reconstruct 80 percent of gene expression based on looking at standard CT scans the patients had undergone.
"Clearly, we are very far from clinical applications of these tools that we developed," said Eran Segal, PhD, lead author of the study, who is now a computational biologist at the Weizmann Institute of Science in Rehovot, Israel. "But the fact that we saw strong connections between the imaging features and the molecular gene activity data suggests that this could be a promising and fruitful research direction."
MEDICA.de; Source: Stanford University Medical Center