NJ Health System Leverages AI, Robotics for Early Lung Cancer Diagnosis

New Jersey-based AtlantiCare is deploying pre-operative artificial intelligence (AI) assessment tools and robotic bronchoscopy techniques to support early lung cancer diagnosis and treatment.

The health system will leverage the Optellum Virtual Nodule Clinic within its early lung cancer diagnosis program at the Heart & Lung and Cancer Care institutes at AtlantiCare Regional Medical Center (ARMC), the press release states. The platform is designed to help clinicians identify and track patients at risk for lung cancer, enabling care teams to biopsy concerning lesions, begin treatments earlier, and improve patient outcomes.

The Interventional Pulmonology team at AtlantiCare's Lung Nodule Clinic will use the tool to identify and follow up on patients with lung nodules incidentally detected during chest CT scans ordered for other reasons, such as a cardiac event or emergency department visit. The tool also allows the team to prioritize high-risk patients who may need close surveillance.

"Early-stage lung cancer symptoms are often vague or mimic those of other illnesses," explained Amit Borah, MD, who leads the interventional pulmonology team, in the press release. "Through this technology, we are detecting suspicious nodules at earlier stages than ever, which is so critical to saving lives."

The platform will be integrated into the Lung Nodule Clinic’s clinical workflow, automatically alerting AtlantiCare's interventional pulmonology team if it detects a nodule through a CT scan performed at ARMC.

"This could be any patient whose scan shows the lungs or a portion of the lungs,” Borah stated. “We follow up with the patient and the patient's primary care and other providers. We then determine whether the individual can benefit from robotic bronchoscopy to biopsy and/or treat the nodule at its earliest stages – before cancer spreads or a nodule becomes cancerous."

If the platform’s insights lead clinicians to decide that a follow-up intervention such as bronchoscopy is appropriate, AtlantiCare plans to leverage Ethicon's MONARCH robotic bronchoscopy platform. The press release indicates that this platform can help clinicians identify patients with the smallest and hardest-to-reach tumors. Once these patients and tumors are identified, care teams can deploy the robotic bronchoscope to reach and biopsy the regions highlighted using Optellum’s AI.

"We have already identified suspicious tumors in individuals who have no known risk of lung cancer through this technology," said Borah. "It will enhance the life-saving progress we've experienced since offering robotic bronchoscopy to our patients."

Recently, other AI-based technologies for lung cancer risk stratification have also shown promise.

Last month, researchers showcased how a deep-learning (DL) model can predict lung cancer risk using chest radiographs and EMR data.

These insights have the potential to help identify individuals who could benefit from lung cancer screening, including those missed by Medicare screening eligibility criteria. The researchers noted that over 50 percent of lung cancers occur in those that are ineligible for screening per CMS criteria, such as female patients or members of minority racial groups, which may perpetuate health disparities.

To combat this, the researchers developed and validated a tool designed to identify high-risk individuals who smoke cigarettes for lung cancer screening CT based on readily available EMR data: age, sex, current cigarette smoking status, and a chest radiograph image.

The model achieved high performance at identifying patients at high risk for lung cancer, including those missed by Medicare lung cancer screening eligibility criteria, indicating that the model can help identify patients who may benefit from CT-based lung cancer screening.