Lung cancer is the most common cancer and accounts for 1.76 million deaths per year worldwide. Non-small cell lung cancer (NSCLC) comprises 85% of all lung cancers and is typically diagnosed at advanced stages. Due to late detection of the disease, data indicate that 10-20% of these patients die within 1-3 months of diagnosis.
Taking this critical issue into account, Imagene, a precision imaging diagnostic company, has developed an innovative AI-based system that detects cancer biomarkers in real time, with the potential to expedite the administration of treatment significantly.
Imagene’s system uses the ALK and ROS1 genes as cancer biomarkers, which, despite their relatively low prevalence in healthy cells, are common in malignant cells.
A recent Sheba study, published in Modern Pathology Journal, was conducted to assess the efficacy and utility of the new system with an eye to its future deployment at Sheba. During the study, Imagene’s AI technology was compared to conventional pathological cancer detection methods, including immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), and NGS.
To evaluate the platform’s performance, Imagene’s AI technology was compared to conventional methods, such as immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), and next-generation sequencing (NGS). Results indicate that among all 72 study participants, the platform validated the presence of both ALK and ROS1 biomarkers in 100% of applicable cases, and in 100% and 98.6% of respective ALK and ROS1 relevant cases, with only one false-positive ROS1 detection.
The system has also demonstrated a capability to identify a spectrum of alterations, including mutations (e.g., EGFR), fusions, and other structural variants (e.g., NTRK), differential gene expression (e.g., HER2), and cancer signatures (e.g., HRD).
By providing immediate results, Imagene’s AI platform allows much faster treatment for patients, who would usually have to wait days for therapeutic intervention.
“Through ARC, Sheba’s innovation center, Imagene and Sheba have developed a close research collaboration in the field of biomarker detection, aiming to improve the quality of care received by cancer patients and save lives,” said Prof. Iris Barshack, Head of Sheba’s Institute of Pathology. “With the unprecedented accuracy levels indicated in our study, it is clear Imagene’s deep learning algorithms possess the potential to radically streamline cancer diagnosis and targeted therapy. We are committed to continue and expand this collaboration to cover more cancer types and biomarkers.”
Sheba remains committed to fulfilling the promise of AI-based genomic testing, creating new paths for fast and accurate cancer diagnosis that will provide patients with premier, timely care.
