Carl Saab, director of the Pain Science Technology And Research (STAR) Lab in the Cleveland Clinic Department of Biomedical Engineering (BME, part of the Lerner Research Institute), states his goal very plainly: “I want to transform the landscape of pain management, using innovation and scientific discovery.”
For Saab, the transformation begins with the way we approach the concept of pain. “We don’t have to be passive in dealing with pain,” he says. “We can be active participants. We can shape our pain experience.”
Saab received his bachelor of science degree in public health from the American University of Beirut, Lebanon, where he also got a master’s degree in neuroscience. The field was so new that, at the time (mid-90s), Saab’s was the first such degree at the university.
From the beginning of his career, Saab has been interested in the study of pain, not just as a physical experience, but also as a mental and emotional phenomenon. “I’ve always sought to understand the basis of emotions,” he says. “In that sense, pain is a window to the mind.”
It is also a universal, and very expensive, syndrome. In the United States, more than $600 billion a year is spent on pain management — $100 billion on chronic low back pain alone. Complicating its diagnosis and treatment: pain is also a subjective experience, so what’s painful for one person may only be an inconvenience for another.
“Because pain is so prevalent, it’s a bottleneck for the healthcare system,” Saab notes. “Many resources are tied up in dealing with it. In addition, misdiagnosing pain can make treatment difficult and has contributed to the overprescription and abuse of opioids.”
Before coming to Cleveland Clinic, Saab was director of the Center for Pain and Neural Circuits at Rhode Island Hospital and Brown University, where his research revolved around traffic patterns between networks in the brain and machine learning. Using artificial intelligence (AI) and electroencephalography (EEG), in which electrodes are attached to the scalp (non-invasively) to measure electrical activity in the brain, his lab developed computer algorithms to help phenotype patients with chronic back pain and migraine — work which continues in his position at Cleveland Clinic.
In the Pain STAR lab, electrodes are attached to the scalp
(non-invasively) to measure electrical activity in the brain.
The Cleveland Clinic BME Pain STAR lab has at its heart a collaboration between researchers and clinicians that will lead to translational discovery. Saab and his Cleveland Clinic scientific team (Muhammad Edhi, MD, Ki-Soo Jeong and Jason Leung) are mapping the brain networks that control sensory and emotional states in people —including pain. “The brain is fundamental in mediating the experience of pain,” he notes. “The brain is making up your pain experience — not in the sense of hallucination, but more like actively generating your experience. So we need to understand the mechanisms of the brain as it relates to pain.”
As Saab notes, this is a new approach that will take some time to catch on. One of his goals is to enable clinicians to move beyond the visual analogue scale (the “smiley face” — a frown for pain, a smiley face for no pain) in assessing a patient’s level of pain.
Saab’s research has posited that, through the use of AI, machines could be “taught” to detect and measure pain. At Cleveland Clinic, Saab and his team continue to use AI and EEG to define with crystal clarity the networks that control pain.
In a recent study, Saab created and tested an AI software platform to objectively classify pain based on EEG scans in three groups of subjects: healthy patients, patients with radiculopathy (pinched nerve) and patients with chronic back pain who were scheduled to have a device implanted to relieve pain. The researchers trained the computer algorithm to compare and correctly distinguish patterns among the EEGs of the different subject groups. The AI algorithm not only distinguished between healthy patients and those with pain, it was also able to identify those patients who were due to have surgery.
According to Saab, AI is the new frontier for diagnosing pain. “AI gives you an extra edge when you reach the limits of conventional statistics and human interpretation of complex data. You can capture patterns that aren’t noticeable to the naked eye. AI has the additional advantage of being able to cross over into clinical use, free of bias."
This kind of algorithm can take the guesswork out of diagnosing pain, Saab adds. “With this platform, we can make pain diagnosis an automated procedure — an objective, rather than subjective, process that also mitigates health disparities.” Saab adds that this algorithm could be expanded to assess other conditions, such as depression and anxiety.
The need to get a better handle on pain management, and to reduce the overprescription of opioids, is so critical that the National Institutes of Health (NIH) has established two programs toward that end: the Helping to End Addiction Long-termSM (HEAL) Initiative, a multi-agency endeavor “to speed scientific solutions to stem the national opioid public health crisis,” which is funding projects to better understand and treat pain; and the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative, which calls for “innovative approaches and new paradigms for identifying and understanding brain disorders.”
The BRAIN Initiative also solicited applications related to nociception (the ability to feel pain) and pain in the context of circuit mechanics of the central nervous system. Saab’s lab was awarded a grant from the BRAIN Initiative to elucidate the mechanisms of pain in the spinal cord and brain. The goal is to approach the mechanisms of pain in the nervous system as a “continuum” between the spine and the brain, in order to have a comprehensive understanding of how pain signals are relayed through the spine and processed in the brain.
“Receiving the NIH BRAIN initiative grant was an honor,” Saab says. “These new models and pain circuits in the brain will guide us toward pain diagnostics and more effective non-opioid therapies. The aims in this grant can be summarized as elucidating the mechanisms of pain with unprecedented cellular precision, ultra-fast temporal resolution and high-density neural recordings, simultaneously.”
“Dr. Saab’s work in pain research, especially in the growing field of defining brain networks, is groundbreaking,” notes D. Geoffrey Vince, chair of the Cleveland Clinic Department of Biomedical Engineering. “His grant from the NIH Brain Initiative is confirmation of the value of his team’s efforts. Their work in mapping neural circuits, and sharing that research with our clinicians, will go a long way not only toward helping our patients, but also to making Cleveland Clinic a leader in pain management.”
Saab is confident that Cleveland Clinic can be a pioneer for transferring this scientific knowledge to a clinical setting. “We’ve had a very positive response to our work from Cleveland Clinic physicians,” he says. “When they’re treating a patient who has chronic pain, they want to use innovative tools backed up by rigorous science. We are adding tools to the toolbox. This can have several benefits: reducing opioid dependence, improving patients’ quality of life and, ultimately, lowering healthcare costs. In the process, we will better understand how the brain works and how the physical in our environment is internally represented in our minds.
