Velocity of Radial Expansion of Contrast-enhancing Gliomas and the Effectiveness of Radiotherapy in Individual Patients: a Proof of Principle

Quantifying the roles of cell motility and cell proliferation in a circular barrier assay

“…From a practical point of view, given that estimates of cell diffusivity in the literature can vary over one or two orders of magnitude [2,3,19,38], our observed variation is relatively small. Nonetheless, we do observe a consistent density-dependent mechanism for which there are several plausible explanations such as the possibility that cells produce a chemical signal (or signals) enhancing migration, or the possibility that cells modify the substrate as they migrate.…”

Gene therapy enhances chemotherapy tolerance and efficacy in glioblastoma patients

“…To characterize the treatment benefits achieved with O 6 BG added to the TMZ regimen, we applied a precision medicine, biomathematical model to compare the treatment strategy employed in study patients with standard care regimens in patients treated at our institution (12,13,(16)(17)(18)(19)(20). We show that model-predicted, untreated tumor growth was deflected by a greater degree in study patients compared with matched control patients, at lower cumulative TMZ doses when administered with O 6 BG.…”

“…For these analyses, values of ρ and D were calculated for purposes of matching tumor growth characteristics between case and control patients, and velocity was used to simulate untreated tumor growth (13). As previously reported (16), the parameters were tuned by fitting two serial, pretreatment MRI scans (one obtained at the time of symptom presentation and the other at the time of surgery) obtained on 1.5T and 3.0T Philips machines with routine clinical MR pulse sequences; slice thickness in the axial plane varied from 1 mm to 6 mm. Tumor volumes observed on pretreatment gadoliniumenhanced MRIs were computed using a semiautomated intensity threshold-based segmentation software developed by MATLAB (version 7.13.0.564 [R2011b]; The MathWorks, Inc.).…”

“…Using the model, patient-tuned parameters ρ and D define the profile of the leading edge of the tumor and the speed (velocity V) at which it would be expected to grow untreated (16,18,19,23,24) or treated (20). For these analyses, values of ρ and D were calculated for purposes of matching tumor growth characteristics between case and control patients, and velocity was used to simulate untreated tumor growth (13).…”

“…Biomathematical modeling studies were performed in the laboratory of Kristin Swanson (Northwestern University, Evanston, Illinois, USA). The model used is a biologically based, patient-specific mathematical model for quantifying the growth of gliomas through the estimation of patientcalibrated net rates of proliferation (ρ) and invasion (D) of tumor cells, referred to as the proliferation-invasion (PI) model (12,13,(16)(17)(18)(19)(20)(22)(23)(24)(25), which has previously been shown to generate accurate predictions of GBM growth in untreated (19,21,24) and treated contexts (20). The model was applied to predict the growth of the tumor, if left untreated, holding rate parameters constant.…”