From patient-specific mathematical neuro-oncology to precision medicine

A. L. Baldock, R. C. Rockne, A. D. Boone, M. L. Neal, A. Hawkins-Daarud, D. M. Corwin, C. A. Bridge, L. A. Guyman, A. D. Trister, M. M. Mrugala, J. K. Rockhill, K. R. Swanson

Research output: Contribution to journalReview articlepeer-review

52 Scopus citations


Gliomas are notoriously aggressive, malignant brain tumors that have variable response to treatment. These patients often have poor prognosis, informed primarily by histopathology. Mathematical neuro-oncology (MNO) is a young and burgeoning field that leverages mathematical models to predict and quantify response to therapies. These mathematical models can form the basis of modern "precision medicine" approaches to tailor therapy in a patient-specific manner. Patient-specific models (PSMs) can be used to overcome imaging limitations, improve prognostic predictions, stratify patients, and assess treatment response in silico. The information gleaned from such models can aid in the construction and efficacy of clinical trials and treatment protocols, accelerating the pace of clinical research in the war on cancer. This review focuses on the growing translation of PSM to clinical neuro-oncology. It will also provide a forward-looking view on a new era of patient-specific MNO.

Original languageEnglish (US)
Article numberArticle 00062
JournalFrontiers in Oncology
Volume3 APR
StatePublished - Jan 1 2013


  • Clinical modeling
  • Glioma
  • Individualized health care
  • Mathematical modeling
  • Patient-specific
  • Personalized medicine

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


Dive into the research topics of 'From patient-specific mathematical neuro-oncology to precision medicine'. Together they form a unique fingerprint.

Cite this