Other optical techniques frequently fail to provide images that are clear enough for doctors to differentiate between the two types. The study’s researchers were from Massachusetts General Hospital (MGH; Boston, MA, USA), Brigham and Women’s Hospital (Boston, MA, USA), and Brandeis University (Waltham, MA, USA), and led by Nicusor Iftimia, PhD, from Physical Sciences, Inc. (Andover, MA, USA).

To evaluate the diagnostic potential of OCT imaging, researchers used the technique to examine surgically removed pancreatic tissue samples from patients with cystic lesions. By identifying unique features of the high-risk cysts that appeared in the OCT scans, the team developed a set of visual criteria to differentiate between high and low risk cysts. They then tested the criteria by comparing OCT diagnoses to those obtained by examining thin slices of the pancreatic tissue under a microscope. Their results, described in the August 2011, issue of the Optical Society’s (OSA) open-access journal Biomedical Optics Express, demonstrated that OCT allowed clinicians to effective differentiate between low-risk and high-risk cysts with a success rate close to that achieved by microscope-assisted examinations of slices of the same samples.

Future studies by the research team will focus on improving imaging resolution to additionally differentiate between solid lesions and autoimmune pancreatitis, and test this technology in vivo. They recently received US Food and Drug Administration (FDA) approval for assessing this technology in human patients by using an OCT probe small enough to be inserted into the pancreas through a biopsy needle, which will be guided into suspect masses in the pancreas by endoscopic ultrasound imaging. A pilot clinical study is planned to start within the next couple of months. If in vivo data will prove effective differentiation between the two types of cysts, a study in a larger number of patients will be planned, contingent on the US National Institute of Health (NIH; Bethesda, MD, USA) funding and FDA approval.

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