Prognostic Significance of Growth Kinetics in Newly Diagnosed Glioblastomas Revealed by Combining Serial Imaging with a Novel Biomathematical Model

Glioblastomas (GBMs) are the most aggressive primary brain tumors characterized by their rapid proliferation and diffuse infiltration of the brain tissue. Survival patterns in patients with GBM have been associated with a number of clinico-pathologic factors, including age and neurological status, yet a significant quantitative link to in vivo growth kinetics of each glioma has remained elusive. Exploiting a recently developed tool for quantifying glioma net proliferation and invasion rates in individual patients using routinely available magnetic resonance images (MRIs), we propose to link these patient-specific kinetic rates of biological aggressiveness to prognostic significance. Using our biologically-based mathematical model for glioma growth and invasion, examination of serial pre-treatment MRIs of 32 GBM patients allowed quantification of these rates for each patient’s tumor. Survival analyses revealed that even when controlling for standard clinical parameters (e.g., age, KPS) these model-defined parameters quantifying biologically aggressiveness (net proliferation and invasion rates) were significantly associated with prognosis. One hypothesis generated was that the ratio of the actual survival time after whatever therapies were employed to the duration of survival predicted (by the model) without any therapy would provide a “Therapeutic Response Index” (TRI) of the overall effectiveness of the therapies. The TRI may provided important information, not otherwise available, as to the effectiveness of the treatments in individual patients. To our knowledge, this is the first report indicating that dynamic insight from routinely obtained pre-treatment imaging may be quantitatively useful in characterizing survival of individual patients with GBM. Such a hybrid tool bridging mathematical modeling and clinical imaging may allow for statifying patients for clinical studies relative to their pretreatment biological aggressiveness

Patient-Specific Metrics of Invasiveness Reveal Significant Prognostic Benefit of Resection in a Predictable Subset of Gliomas

Object Malignant gliomas are incurable, primary brain neoplasms noted for their potential to extensively invade brain parenchyma. Current methods of clinical imaging do not elucidate the full extent of brain invasion, making it difficult to predict which, if any, patients are likely to benefit from gross total resection. Our goal was to apply a mathematical modeling approach to estimate the overall tumor invasiveness on a patient-by-patient basis and determine whether gross total resection would improve survival in patients with relatively less invasive gliomas. Methods In 243 patients presenting with contrast-enhancing gliomas, estimates of the relative invasiveness of each patient's tumor, in terms of the ratio of net proliferation rate of the glioma cells to their net dispersal rate, were derived by applying a patient-specific mathematical model to routine pretreatment MR imaging. The effect of varying degrees of extent of resection on overall survival was assessed for cohorts of patients grouped by tumor invasiveness. Results We demonstrate that patients with more diffuse tumors showed no survival benefit (P = 0.532) from gross total resection over subtotal/biopsy, while those with nodular (less diffuse) tumors showed a significant benefit (P = 0.00142) with a striking median survival benefit of over eight months compared to sub-totally resected tumors in the same cohort (an 80% improvement in survival time for GTR only seen for nodular tumors). Conclusions These results suggest that our patient-specific, model-based estimates of tumor invasiveness have clinical utility in surgical decision making. Quantification of relative invasiveness assessed from routinely obtained pre-operative imaging provides a practical predictor of the benefit of gross total resection

Toward patient-specific, biologically optimized radiation therapy plans for the treatment of glioblastoma.

PURPOSE: To demonstrate a method of generating patient-specific, biologically-guided radiotherapy dose plans and compare them to the standard-of-care protocol. METHODS AND MATERIALS: We integrated a patient-specific biomathematical model of glioma proliferation, invasion and radiotherapy with a multiobjective evolutionary algorithm for intensity-modulated radiation therapy optimization to construct individualized, biologically-guided plans for 11 glioblastoma patients. Patient-individualized, spherically-symmetric simulations of the standard-of-care and optimized plans were compared in terms of several biological metrics. RESULTS: The integrated model generated spatially non-uniform doses that, when compared to the standard-of-care protocol, resulted in a 67% to 93% decrease in equivalent uniform dose to normal tissue, while the therapeutic ratio, the ratio of tumor equivalent uniform dose to that of normal tissue, increased between 50% to 265%. Applying a novel metric of treatment response (Days Gained) to the patient-individualized simulation results predicted that the optimized plans would have a significant impact on delaying tumor progression, with increases from 21% to 105% for 9 of 11 patients. CONCLUSIONS: Patient-individualized simulations using the combination of a biomathematical model with an optimization algorithm for radiation therapy generated biologically-guided doses that decreased normal tissue EUD and increased therapeutic ratio with the potential to improve survival outcomes for treatment of glioblastoma

Phase 1/2 Trials of Temozolomide Motexafin Gadolinium and 60-Gy Fractionated Radiation for Newly Diagnosed Supratentorial Glioblastoma Multiforme: Final Results of RTOG 0513

Purpose The purpose of phase 1 was to determine the maximum tolerated dose (MTD) of motexafin gadolinium (MGd) given concurrently with temozolomide (TMZ) and radiation therapy (RT) in patients with newly diagnosed supratentorial glioblastoma multiforme (GBM). Phase 2 determined whether this combination improved overall survival (OS) and progression-free survival (PFS) in GBM recursive partitioning analysis class III to V patients compared to therapies for recently published historical controls. Methods and Materials Dose escalation in phase 1 progressed through 3 cohorts until 2 of 6 patients experienced dose-limiting toxicity or a dose of 5 mg/kg was reached. Once MTD was established, a 1-sided 1-sample log-rank test at significance level of.1 had 85% power to detect a median survival difference (13.69 vs 18.48 months) with 60 deaths over a 12-month accrual period and an additional 18 months of follow-up. OS and PFS were estimated using the Kaplan-Meier method. Results In phase 1, 24 patients were enrolled. The MTD established was 5 mg/kg, given intravenously 5 days a week for the first 10 RT fractions, then 3 times a week for the duration of RT. The 7 patients enrolled in the third dose level and the 94 enrolled in phase 2 received this dose. Of these 101 patients, 87 were eligible and evaluable. Median survival time was 15.6 months (95% confidence interval [CI]: 12.9-17.6 months), not significantly different from that of the historical control (P=.36). Median PFS was 7.6 months (95% CI: 5.7-9.6 months). One patient (1%) experienced a grade 5 adverse event possibly related to therapy during the concurrent phase, and none experience toxicity during adjuvant TMZ therapy. Conclusions Treatment was well tolerated, but median OS did not reach improvement specified by protocol compared to historical control, indicating that the combination of standard RT with TMZ and MGd did not achieve a significant survival advantage

Dose-volume histogram showing the total dose delivered to normal brain tissue outside of the T1Gd abnormality for optimized and standard-of-care plans for patient 10.

<p>The lines intersect at 62% of the normal tissue volume, demonstrating that only 2% of the normal tissue receives a higher dose from the optimized plan.</p