Recognizing the unmet need in the field of breast cancer margin visualization, Perimeter has a randomized, controlled, multi-site, clinical trial to evaluate its next-gen investigational Perimeter B-Series OCT2 with ImgAssist AI against the standard of care when used in breast lumpectomy procedures.
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Perimeter is advancing the development of its proprietary, next-gen “ImgAssist” artificial intelligence technology under the ATLAS AI project, which is made possible, in part, by a $7.4 million grant awarded by the Cancer Prevention and Research Institute of Texas (CPRIT). In addition, the U.S. FDA granted Breakthrough Device Designation for Perimeter B-Series OCT coupled with ImgAssist AI.
Investigator-Initiated Studies (IIS) are research studies initiated and conducted by an investigator who assumes the legal and regulatory responsibilities as the Investigator Sponsor.
Perimeter’s artificial intelligence technology has the potential to be a powerful intraoperative tool for identifying regions of interest to help surgeons make real-time decisions on margin status in the OR. The goal is to determine whether this technology can help lower re-excision rates – potentially setting a new standard for specimen imaging technology during breast conservation surgery.
Dr. Alastair Thompson from Baylor College of Medicine in Houston, TX, enrolls the first clinical study subject into the trial.
Clinical trial expands to include Baylor College of Medicine in Houston, TX, under the direction of Dr. Alastair Thompson, who is Principal Investigator of the study.
Perimeter announces initiation of first clinical trial site at West Cancer Center & Research Institute in Tennessee.
Perimeter receives approval from the U.S. FDA for an Investigational Device Exemption (IDE) to support the launch of the pivotal study. Trial start-up activities get underway at eight sites.
U.S. FDA grants Perimeter’s B-Series OCT Breakthrough Device Designation, a program designed to speed up access to disruptive new technologies.
ImgAssist is trained with more than 400 volumes of images of excised breast tissue and achieves a 0.94 AUC score (or 94% “predictivity”) of how well the algorithm can differentiate between suspicious and non-suspicious breast tissue areas
With the support of a $7.4 million grant from Cancer Prevention and Research Institute of Texas (CPRIT), the ATLAS AI project is launched to collect data from leading cancer centers – including MD Anderson, Baylor College of Medicine and UT Southwestern San Antonio – to train and test the ImgAssist AI algorithm.