Artificial intelligence (AI) has been making waves in recent months, but many of it’s various applications are not immediately apparent. In medicine, AI has been used to search medical data and uncover insights to help improve health outcomes and patient experiences. In pain management, there are very promising uses of AI already materializing.
A recent study published in the February 2023 issue of Plastic and Reconstructive Surgery revealed that an automated pattern recognition tool created using AI technology can detect whether surgery will be effective in reducing pain due to nerve compression headaches. According to ASPS Member Surgeons Lisa Gfrerer, MD, PhD, of Weill Cornell Medicine, and William G. Austen, Jr., MD, of Massachusetts General Hospital, patient drawings of headache pain can be useful in identifying patients who are more or less likely to have a good response to headache surgery. The machine learning framework evaluated in their study can automatically interpret pain drawings and appears to be most accurate in predicting patients who will not achieve a good reduction in headache activity after nerve decompression surgery.
What is headache surgery?
Headache surgery is a well-established treatment for selected patients with nerve compression headaches that do not respond to medical treatment. The surgery targets specific trigger sites linked to certain headache patterns. However, predicting the results of headache surgery can be difficult. In a previous study, Drs. Gfrerer and Austen found that asking patients to draw their headache pain can provide valuable information on the likely response to surgery. Patients who have more typical pain patterns for a particular trigger site appear more likely to have good pain reduction after headache surgery.
AI? In this economy?
To simplify the process for less-experienced surgeons, Drs. Gfrerer and Austen and their team used AI technology to develop and validate a machine learning framework capable of interpreting pain drawings to aid in predicting headache surgery outcomes. The study used 131 pain drawings provided by patients before undergoing surgery for nerve compression headaches. The machine learning algorithm outperformed human evaluators in predicting the response to surgery. The algorithm performed best in predicting patients who would have poor responses to surgery, defined as less than 20% improvement in Migraine Headache Index (MIH) score, with an accuracy of 94%.
The algorithm identified three factors as strong predictors of poor surgical outcome: diffuse pain, facial pain, and pain at the vertex of the head. The researchers emphasized the need for further studies using larger datasets and including other important clinical screening variables to improve outcome predictions in headache surgery and to apply the AI algorithm to clinical practice.
The study suggests that AI may be more objective at interpreting atypical pain drawings than surgeons. The platform will allow clinicians with less clinical experience, neurologists, primary care practitioners, and even patients to better understand candidacy for headache surgery and seek evaluation by certified headache surgeons. If you suffer from nerve compression headaches that do not respond to medical treatment, consider seeking evaluation by a certified headache surgeon and ask if AI-assisted pain pattern recognition may be helpful in predicting your potential outcome from surgery.
