Alexander M. Spence

Hypoxia and glucose metabolism in malignant tumors: evaluation by [18F]fluoromisonidazole and [18F]fluorodeoxyglucose positron emission tomography imaging.

Purpose: The aim of this study is to compare glucose metabolism and hypoxia in four different tumor types using positron emission tomography (PET). 18F-labeled fluorodeoxyglucose (FDG) evaluates energy metabolism, whereas the uptake of 18F-labeled fluoromisonidazole (FMISO) is proportional to tissue hypoxia. Although acute hypoxia results in accelerated glycolysis, cellular metabolism is slowed in chronic hypoxia, prompting us to look for discordance between FMISO and FDG uptake. Experimental Design: Forty-nine patients (26 with head and neck cancer, 11 with soft tissue sarcoma, 7 with breast cancer, and 5 with glioblastoma multiforme) who had both FMISO and FDG PET scans as part of research protocols through February 2003 were included in this study. The maximum standardized uptake value was used to depict FDG uptake, and hypoxic volume and maximum tissue:blood ratio were used to quantify hypoxia. Pixel-by-pixel correlation of radiotracer uptake was performed on coregistered images for each corresponding tumor plane. Results: Hypoxia was detected in all four patient groups. The mean correlation coefficients between FMISO and FDG uptake were 0.62 for head and neck cancer, 0.47 for breast cancer, 0.38 for glioblastoma multiforme, and 0.32 for soft tissue sarcoma. The correlation between the overall tumor maximum standardized uptake value for FDG and hypoxic volume was small (Spearman r = 0.24), with highly significant differences among the different tumor types (P < 0.005). Conclusions: Hypoxia is a general factor affecting glucose metabolism; however, some hypoxic tumors can have modest glucose metabolism, whereas some highly metabolic tumors are not hypoxic, showing discordance in tracer uptake that can be tumor type specific.

Machado disease A hereditary ataxia in Portuguese emigrants to Massachusetts

A KINDRED with a hereditary ataxia and associated abnormalities is reported. In addition, we attempted to determine the mode of genetic transmission. All family members descended from one William Machado, a native of Bretanha on the island of SZo Miguel in the Portuguese Azores. Some of his children emigrated to Massachusetts in the late nineteenth and early twentieth centuries. Most members of the family live in southeastern Massachusetts, many of them in Fall River. We hospitalized G affected members of the family who volunteered for a study in the clinical center of the Peter Bent Brigham Hospital. The investigative protocol included biochemical studies on blood and urine, a pneumoencephalogram (PEG), biopsies of nerve and muscle, and neurophysiological studies. Thirty other available family members were later examined by us. The pedigree (Fig. 1) was formulated from family records, church registries, and relatives. Thirty-five affected family members were not examined, but family records indicated that they had neurological signs. These latter cases could not be clearly classified.

Regional Hypoxia in Glioblastoma Multiforme Quantified with [18F]Fluoromisonidazole Positron Emission Tomography before Radiotherapy: Correlation with Time to Progression and Survival

Purpose: Hypoxia is associated with resistance to radiotherapy and chemotherapy and activates transcription factors that support cell survival and migration. We measured the volume of hypoxic tumor and the maximum level of hypoxia in glioblastoma multiforme before radiotherapy with [18F]fluoromisonidazole positron emission tomography to assess their impact on time to progression (TTP) or survival. Experimental Design: Twenty-two patients were studied before biopsy or between resection and starting radiotherapy. Each had a 20-minute emission scan 2 hours after i.v. injection of 7 mCi of [18F]fluoromisonidazole. Venous blood samples taken during imaging were used to create tissue to blood concentration (T/B) ratios. The volume of tumor with T/B values above 1.2 defined the hypoxic volume (HV). Maximum T/B values (T/Bmax) were determined from the pixel with the highest uptake. Results: Kaplan-Meier plots showed shorter TTP and survival in patients whose tumors contained HVs or tumor T/Bmax ratios greater than the median (P ≤ 0.001). In univariate analyses, greater HV or tumor T/Bmax were associated with shorter TTP or survival (P < 0.002). Multivariate analyses for survival and TTP against the covariates HV (or T/Bmax), magnetic resonance imaging (MRI) T1Gd volume, age, and Karnovsky performance score reached significance only for HV (or T/Bmax; P < 0.03). Conclusions: The volume and intensity of hypoxia in glioblastoma multiforme before radiotherapy are strongly associated with poorer TTP and survival. This type of imaging could be integrated into new treatment strategies to target hypoxia more aggressively in glioblastoma multiforme and could be applied to assess the treatment outcomes.

Enhanced optical imaging of rat gliomas and tumor margins.

Current intraoperative methods used to maximize the extent of tumor removal are limited to intraoperative biopsies, ultrasound, and stereotactic volumetric resections. A new technique involving the optical imaging of an intravenously injected dye has the potential to localize tumors and their margins with a high degree of accuracy. In a rat glioma model, enhanced optical imaging was performed and indocyanine green was used as the contrast-enhancing agent. In all 22 animals, the peak optical change in the tumor was greater than in the ipsilateral brain around the tumor and the contralateral normal hemisphere. The clearance of the dye was significantly delayed to a greater extent in the tumor than in the brain around the tumor and the normal brain. After attempts were made at complete microscopic resection, enhanced optical imaging of the tumor margins and the histological samples demonstrated a specificity of 93% and a sensitivity of 89.5%. Enhanced optical imaging was capable of outlining the tumor even when the imaging was done through the cranium. The optical imaging of rat gliomas with a contrast-enhancing dye is able to differentiate between normal brain and tumor tissue both at the cortical surface and at the tumor margins. The application of these studies in an intraoperative clinical setting may allow for the more accurate determination of tumor margins and may increase the extent of tumor removal.

Predicting the efficacy of radiotherapy in individual glioblastoma patients in vivo: a mathematical modeling approach

Glioblastoma multiforme (GBM) is the most malignant form of primary brain tumors known as gliomas. They proliferate and invade extensively and yield short life expectancies despite aggressive treatment. Response to treatment is usually measured in terms of the survival of groups of patients treated similarly, but this statistical approach misses the subgroups that may have responded to or may have been injured by treatment. Such statistics offer scant reassurance to individual patients who have suffered through these treatments. Furthermore, current imaging-based treatment response metrics in individual patients ignore patient-specific differences in tumor growth kinetics, which have been shown to vary widely across patients even within the same histological diagnosis and, unfortunately, these metrics have shown only minimal success in predicting patient outcome. We consider nine newly diagnosed GBM patients receiving diagnostic biopsy followed by standard-of-care external beam radiation therapy (XRT). We present and apply a patient-specific, biologically based mathematical model for glioma growth that quantifies response to XRT in individual patients in vivo. The mathematical model uses net rates of proliferation and migration of malignant tumor cells to characterize the tumors growth and invasion along with the linear-quadratic model for the response to radiation therapy. Using only routinely available pre-treatment MRIs to inform the patient-specific bio-mathematical model simulations, we find that radiation response in these patients, quantified by both clinical and model-generated measures, could have been predicted prior to treatment with high accuracy. Specifically, we find that the net proliferation rate is correlated with the radiation response parameter (r = 0.89, p = 0.0007), resulting in a predictive relationship that is tested with a leave-one-out cross-validation technique. This relationship predicts the tumor size post-therapy to within inter-observer tumor volume uncertainty. The results of this study suggest that a mathematical model can create a virtual in silico tumor with the same growth kinetics as a particular patient and can not only predict treatment response in individual patients in vivo but also provide a basis for evaluation of response in each patient to any given therapy.

Quantitative metrics of net proliferation and invasion link biological aggressiveness assessed by MRI with hypoxia assessed by FMISO-PET in newly diagnosed glioblastomas.

Glioblastoma multiforme (GBM) are aggressive and uniformly fatal primary brain tumors characterized by their diffuse invasion of the normal-appearing parenchyma peripheral to the clinical imaging abnormality. Hypoxia, a hallmark of aggressive tumor behavior often noted in GBMs, has been associated with resistance to therapy, poorer survival, and more malignant tumor phenotypes. Based on the existence of a set of novel imaging techniques and modeling tools, our objective was to assess a hypothesized quantitative link between tumor growth kinetics [assessed via mathematical models and routine magnetic resonance imaging (MRI)] and the hypoxic burden of the tumor [assessed via positron emission tomography (PET) imaging]. Our biomathematical model for glioma kinetics describes the spatial and temporal evolution of a glioma in terms of concentration of malignant tumor cells. This model has already been proven useful as a novel tool to dynamically quantify the net rates of proliferation (rho) and invasion (D) of the glioma cells in individual patients. Estimates of these kinetic rates can be calculated from routinely available pretreatment MRI in vivo. Eleven adults with GBM were imaged preoperatively with (18)F-fluoromisonidazole (FMISO)-PET and serial gadolinium-enhanced T1- and T2-weighted MRIs to allow the estimation of patient-specific net rates of proliferation (rho) and invasion (D). Hypoxic volumes were quantified from each FMISO-PET scan following standard techniques. To control for tumor size variability, two measures of hypoxic burden were considered: relative hypoxia (RH), defined as the ratio of the hypoxic volume to the T2-defined tumor volume, and the mean intensity on FMISO-PET scaled to the blood activity of the tracer (mean T/B). Pearson correlations between RH and the net rate of cell proliferation (rho) reached significance (P < 0.04). Moreover, highly significant positive correlations were found between biological aggressiveness ratio (rho/D) and both RH (P < 0.00003) and the mean T/B (P < 0.0007).

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

Glioblastomas are the most aggressive primary brain tumors, characterized by their rapid proliferation and diffuse infiltration of the brain tissue. Survival patterns in patients with glioblastoma have been associated with a number of clinicopathologic factors including age and neurologic 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 (MRI), 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 pretreatment MRIs of 32 glioblastoma patients allowed quantification of these rates for each patients tumor. Survival analyses revealed that even when controlling for standard clinical parameters (e.g., age and Karnofsky performance status), these model-defined parameters quantifying biological 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 used 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 provide important information, not otherwise available, about the effectiveness of the treatments in individual patients. To our knowledge, this is the first report indicating that dynamic insight from routinely obtained pretreatment imaging may be quantitatively useful in characterizing the survival of individual patients with glioblastoma. Such a hybrid tool bridging mathematical modeling and clinical imaging may allow for stratifying patients for clinical studies relative to their pretreatment biological aggressiveness.

Tumor-Specific Positron Emission Tomography Imaging in Patients: [18F] Fluorodeoxyglucose and Beyond

Biochemical and molecular imaging of cancer using positron emission tomography (PET) plays an increasing role in the care of cancer patients. Most clinical work to date uses the glucose analogue [18F]fluorodeoxyglucose (FDG) to detect accelerated and aberrant glycolysis present in most tumors. Although clinical FDG PET has been used largely to detect and localize cancer, more detailed studies have yielded biological insights and showed the utility of FDG as a prognostic marker and as a tool for therapeutic response evaluation. As cancer therapy becomes more targeted and individualized, it is likely that PET radiopharmaceuticals other than FDG, aimed at more specific aspects of cancer biology, will also play a role in guiding cancer therapy. Clinical trials designed to test and validate new PET agents will need to incorporate rigorous quantitative image analysis and adapt to the evolving use of imaging as a biomarker and will need to incorporate cancer outcomes, such as survival into study design.

Complementary but Distinct Roles for MRI and 18F-Fluoromisonidazole PET in the Assessment of Human Glioblastomas

Glioblastoma multiforme is a primary brain tumor known for its rapid proliferation, diffuse invasion, and prominent neovasculature and necrosis. This study explores the in vivo link between these characteristics and hypoxia by comparing the relative spatial geometry of developing vasculature inferred from gadolinium-enhanced T1-weighted MRI (T1Gd), edematous tumor extent revealed on T2-weighted MRI (T2), and hypoxia assessed by 18F-fluoromisonidazole PET (18F-FMISO). Given the role of hypoxia in upregulating angiogenic factors, we hypothesized that the distribution of hypoxia seen on 18F-FMISO is correlated spatially and quantitatively with the amount of leaky neovasculature seen on T1Gd. Methods: A total of 24 patients with glioblastoma underwent T1Gd, T2, and 18F-FMISO—11 studies preceded surgical resection or biopsy, 7 followed surgery and preceded radiation therapy, and 11 followed radiation therapy. Abnormal regions seen on the MRI scan were segmented, including the necrotic center (T0), the region of abnormal blood–brain barrier associated with disrupted vasculature (T1Gd), and infiltrating tumor cells and edema (T2). The 18F-FMISO images were scaled to the blood 18F-FMISO activity to create tumor-to-blood ratio (T/B) images. The hypoxic volume (HV) was defined as the region with T/Bs greater than 1.2, and the maximum T/B (T/Bmax) was determined by the voxel with the greatest T/B value. Results: The HV generally occupied a region straddling the outer edge of the T1Gd abnormality and into the T2. A significant correlation between HV and the volume of the T1Gd abnormality that relied on the existence of a large outlier was observed. However, there was consistent correlation between surface areas of all MRI-defined regions and the surface area of the HV. The T/Bmax, typically located within the T1Gd region, was independent of the MRI-defined tumor size. Univariate survival analysis found the most significant predictors of survival to be HV, surface area of HV, surface area of T1Gd, and T/Bmax. Conclusion: Hypoxia may drive the peripheral growth of glioblastomas. This conclusion supports the spatial link between the volumes and surface areas of the hypoxic and MRI regions; the magnitude of hypoxia, T/Bmax, remains independent of size.

Hypoxia imaging-directed radiation treatment planning

Increasing evidence supports the role of the tumor microenvironment in modulating cancer behavior. Tissue hypoxia, an important and common condition affecting the tumor microenvironment, is well established as a resistance factor in radiotherapy. Increasing evidence points to the ability of hypoxia to induce the expression of gene products, which confer aggressive tumor behavior and promote broad resistance to therapy. These factors suggest that determining the presence or absence of tumor hypoxia is important in planning cancer therapy. Recent advances in PET hypoxia imaging, conformal radiotherapy, and imaging-directed radiotherapy treatment planning now make it possible to perform hypoxia-directed radiotherapy. We review the biological aspects of tumor hypoxia and PET imaging approaches for measuring tumor hypoxia, along with methods for conformal radiotherapy and image-guided treatment, all of which provide the underpinnings for hypoxia-directed therapy. As a case example, we review emerging data on PET imaging of hypoxia to direct radiotherapy.