Mathematical model of perineural tumor spread: a pilot study

Area of Science:

• Oncology
• Medical Imaging
• Mathematical Modeling

Background:

• Perineural spread (PNS) of pelvic cancer along the lumbosacral plexus causes neoplastic lumbosacral plexopathy (nLSP), leading to significant patient morbidity and mortality.
• Diagnosing and treating PNS in recurrent tumors presents a clinical challenge due to its complex nature.

Purpose of the Study:

• To develop and present a mathematical model for predicting the course and extent of perineural tumor spread.
• To adapt existing mathematical models for glioblastoma multiforme (GBM) to model recurrent pelvic tumor spread along the lumbosacral plexus.

Main Methods:

• Created 3D models of perineural tumor spread using MRI scans from two patients with pelvic cancer (prostate and cervical).
• Adapted a mathematical model of GBM to simulate tumor progression along the nerves on an anatomical model.

Main Results:

• Successfully modeled and visualized perineural spread of pelvic cancer in two patients.
• Calculated average tumor growth rates of 60.7 mm/year and 129 mm/year.
• Demonstrated good correlation between the model's predictions and the extent of PNS observed on MRI scans.

Conclusions:

• This is the first mathematical model developed for perineural tumor spread, offering a novel approach to disease progression monitoring.
• The model provides a foundation for future integration of mathematical tools in personalized medicine for cancer treatment response assessment.
• Highlights the need for unified scales, like 'days gained,' for reporting treatment response in the era of individualized medicine.