Randomized Metabolic Response Monitoring Trial in Patients With Suspected Recurrence of Glioblastoma F-DOPA PET/CT
Randomized Metabolic Response Monitoring Trial in Patients With Suspected Recurrence of Glioblastoma F-DOPA PET/CT
It was previously shown that 18F-DOPA PET imaging results in intended management changes in 41% of brain tumor patients. However, its impact on patient outcome defined as survival, costs, and/or quality of life has not been demonstrated. Regulatory agencies require randomized trials to determine the impact of PET on patient management and outcome. In this study we hypothesize that the addition of 18F-DOPA PET will improve patient outcome by more accurately identifying presence or absence of tumor recurrence than conventional imaging.
Malignant gliomas are aggressive primary brain tumors that almost always lead to rapid patient deterioration and death. Timely diagnosis of recurrent disease as well as accurate monitoring of therapeutic responses is critically important in glioblastoma patients.
Despite introduction of new treatment approaches patient prognosis is poor with less than half of the patients being progression-free during the first 6 months after diagnosis of disease recurrence (6-month-progression-free survival rates of 46%).
The current diagnostic standard of care for diagnosing and monitoring brain tumors is contrast-enhanced, multi-planar magnetic resonance imaging (MRI). However, the ability of MRI for early detection of disease recurrence or progression is limited. Moreover, determination of treatment responses is difficult since benign tissue changes after radiation and/or chemotherapy can have the appearance of tumor recurrence or progression on MRI. Positron emission tomography (PET) is an established imaging technique that utilizes small amounts of radioactivity attached to very minimal amounts of substances (tracers) that are injected via a hand or arm vein. These substances can track certain features of cancers that can be visualized by using the PET/CT scanner. For instance, a number of different PET-tracers have been used to study brain tumor metabolism and to detect primary or recurrent tumors. These include tracers of glucose (18F-FDG) and amino acid metabolism (e.g. 18F-DOPA). Metabolic imaging of brain tumors with amino acid analogues has advantages over 18F-FDG. Since FDG assess glucose metabolism and the normal brain consumes a lot of glucose it can be difficult to detect tumors against high glucose use of normal brain tissue. 18FDOPA has been successfully used clinically for many years. The advantage of 18F-DOPA is that normal brain tissue consumes very little 18F-DOPA. Thus, tumors can be seen easily against a low background activity.
18F-DOPA PET imaging detects brain tumors with a very high accuracy and 18F-DOPA imaging affects the management of 40% of patients. However, its impact on patient outcome defined as survival, costs, and/or quality of life has not been demonstrated.
Randomized trials are needed to evaluate the impact of PET on patient management and outcome. We will determine this by randomizing patients with suspected recurrence of glioblastoma into those who are managed using conventional diagnostic imaging versus those who will receive conventional imaging plus 18F-DOPA PET. Randomization is like flipping a coin. Patients will have a 50% chance to undergo standard imaging or standard imaging combined with 18F-DOPA PET.
Approximately 25-40% of the patients with suspected tumor recurrence will have pseudo-progression on MRI (i.e. the images suggest that there is tumor recurrence when there is in fact no recurrence). These patients will have correctly negative 18F-DOPA PET scans. In these patient initiation of treatment can be postponed. In contrast, patients with positive 18F-DOPA PET scans will undergo some kind of treatment at the discretion of the treating physician (radiation therapy, chemotherapy or surgery). We will find out whether the management and treatment change that is based on 18FDOPA PET affects the survival of patients and affects the costs of caring for the patients.
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Exclusion Criteria: