Mathematical model of perineural tumor spread: a pilot study

• Published in: Acta neurochirurgica Vol. 160; no. 3; pp. 655 - 661
• Main Authors: Jacobs, Joshua J., Capek, Stepan, Spinner, Robert J., Swanson, Kristin R.
• Format: Journal Article
• Language: English
• Published: Vienna Springer Vienna 01.03.2018; Springer Nature B.V
• Subjects: Brain cancer; Cancer; Cervical cancer; Cervix; Glioblastoma; Interventional Radiology; Invasiveness; Magnetic resonance imaging; Mathematical models; Medicine; Medicine & Public Health; Minimally Invasive Surgery; Morbidity; Nerves; Neurology; Neuroradiology; Neurosurgery; NMR; Nuclear magnetic resonance; Original Article - Neurosurgical Techniques; Patients; Prostate cancer; Surgical Orthopedics; Tumors; Lumbosacral plexopathy; Pelvic cancer; Treatment response; Mathematical model; Perineural spread
• ISSN: 0001-6268; 0942-0940; 0942-0940
• DOI: 10.1007/s00701-017-3423-6

Background Perineural spread (PNS) of pelvic cancer along the lumbosacral plexus is an emerging explanation for neoplastic lumbosacral plexopathy (nLSP) and an underestimated source of patient morbidity and mortality. Despite the increased incidence of PNS, these patients are often times a clinical conundrum—to diagnose and to treat. Building on previous results in modeling glioblastoma multiforme (GBM), we present a mathematical model for predicting the course and extent of the PNS of recurrent tumors. Methods We created three-dimensional models of perineurally spreading tumor along the lumbosacral plexus from consecutive magnetic resonance imaging scans of two patients (one each with prostate cancer and cervical cancer). We adapted and applied a previously reported mathematical model of GBM to progression of tumor growth along the nerves on an anatomical model obtained from a healthy subject. Results We were able to successfully model and visualize perineurally spreading pelvic cancer in two patients; average growth rates were 60.7 mm/year for subject 1 and 129 mm/year for subject 2. The model correlated well with extent of PNS on MRI scans at given time points. Conclusions This is the first attempt to model perineural tumor spread and we believe that it provides a glimpse into the future of disease progression monitoring. Every tumor and every patient are different, and the possibility to report treatment response using a unified scale—as “days gained”—will be a necessity in the era of individualized medicine. We hope our work will serve as a springboard for future connections between mathematics and medicine.