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We present our initial experience in using single modality fluoromisonidazole (FMISO) PET/MR imaging to noninvasively evaluate the biological effects induced by bevacizumab therapy in a patient treated for recurrent high grade glioma. In this index patient

BackgroundIn Parkinson disease (PD), the benefit of levodopa therapy becomes less marked over time, perhaps because degeneration of nigrostrial neurons causes progressive loss of aromatic l-amino acid decarboxylase (AADC), the enzyme that converts levodopa into dopamine. In a primate model of PD, intrastriatal infusion of an adeno-associated viral type 2 vector containing the human AADC gene (AAV-hAADC) results in robust response to low-dose levodopa without the side effects associated with higher doses. These data prompted a clinical trial.MethodsPatients with moderately advanced PD received bilateral intraputaminal infusion of AAV-hAADC vector. Low-dose and high-dose cohorts (5 patients in each) were studied using standardized clinical rating scales at baseline and 6 months. PET scans using the AADC tracer [(18)F]fluoro-L-m-tyrosine (FMT) were performed as a measure of gene expression.ResultsThe gene therapy was well tolerated, but 1 symptomatic and 2 asymptomatic intracranial hemorrhages followed the operative procedure. Total and motor rating scales improved in both cohorts. Motor diaries also showed increased on-time and reduced off-time without increased "on" time dyskinesia. At 6 months, FMT PET showed a 30% increase of putaminal uptake in the low-dose cohort and a 75% increase in the high-dose cohort.ConclusionThis study provides class IV evidence that bilateral intrastriatal infusion of adeno-associated viral type 2 vector containing the human AADC gene improves mean scores on the Unified Parkinson's Disease Rating Scale by approximately 30% in the on and off states, but the surgical procedure may be associated with an increased risk of intracranial hemorrhage and self-limited headache.

In 1990, 215 patients with operable breast cancer were entered into a prospective study of the prognostic significance of five biochemical markers and 15 other factors (pathological/chronological/patient). After a median follow-up of 6.6 years, there were 77 recurrences and 77 deaths (59 breast cancer-related). By univariate analysis, patient outcome related significantly to 13 factors. By multivariate analysis, the most important of nine independent factors were: number of nodes involved, steroid receptors (for oestrogen or progestogen), age, clinical or pathological tumour size and grade. Receptors and grade exerted their influence only in the first 3 years. Progestogen receptors (immunohistochemical) and oestrogen receptors (biochemical) were of similar prognostic significance. The two receptors were correlated (r=+0.50, P=0.001) and displaced each other from the analytical model but some evidence for the additivity of their prognostic values was seen when their levels were discordant.

Using our recently reported whole body PET imaging technique, we performed whole body PET studies of the skeletal system with [18F]fluoride ion in 19 patients with a range of malignant and benign skeletal conditions and in 19 normal male volunteers. The technique produces two-dimensional projection images of the entire skeletal system ("a PET bone scan"), in addition to coronal, sagittal, and axial tomographic images of the skeletal system. The tomographic images had a 13% higher lesion detection sensitivity than the projection images. Whole body PET skeletal imaging with [18F]fluoride ion is technically feasible, provides images of excellent quality, and may be coupled with more quantitatively precise kinetic PET [18F]fluoride ion studies (over limited regions of the body) when numerical estimates of skeletal [18F]fluoride ion uptake are desired. The method is potentially useful in clinical applications where the high resolution and numerical precision of PET are of particular value (e.g., in accurately defining the anatomic location and extent of lesions and in assessing changes in bone metabolism on serial studies).

A method to determine the binding of epidermal growth factor (EGF) to the particulate fraction of the cell has been established and evaluated using rat liver, human placenta, and tumours of human breast and brain. Little EGF receptor (EGFR) activity was detected in normal or benign tumour tissues except for meningioma (positive in 95% samples), but EGFR were present in 43% of 131 breast tumours and 75% of 55 primary cerebral tumours. Despite the strong inverse correlation between EGFR activity and oestrogen receptors in breast tumours and a tendency for high levels of EGFR activity to be associated with glioblastoma multiforme, analysis showed that EGFR was of little prognostic significance in patients with tumours of either breast or brain.

Whole-body positron emission tomography (PET) has recently emerged as an important imaging tool for cancer detection and staging. Initial applications of the technique have been primarily qualitative. One of the major reasons is the limits imposed by kinetically undersampled data over the whole body, as opposed to the standard method of continuous dynamic sampling in one body location. In this paper, a new estimation method using weighted nonlinear least squares (WNLS) for the first bed position and Bayesian regression (BR) for subsequent positions is proposed. A general criterion for designing optimal sampling schedules which maximizes the measurement information with multiple bed positions is developed. The overall approach is illustrated with the problem of estimating the metabolic rate of glucose (MRGLu) in tumors at different axial positions (image bed positions) in the body by using computer simulations and patient data. The results show that estimates of MRGLu using sparse data and the optimized Bayesian approach are comparable with those obtained by standard methods and fully sampled data. This study demonstrates the potential of the technique described for quantification where several bed positions have to be used to image all the regions of interest (ROI).

The use of Bayesian regression for improving the estimation of cerebral oxygen utilization rate (CMRO) was investigated. Based on plasma time-activity curves of (15)O oxygen and (15)O water that were obtained previously in a normal subject, realistic tissue time-activity curves of (15)O radioactivity in gray and white matter as obtained in dynamic PET (positron emission tomography) (15)O oxygen studies were computer-simulated for various noise conditions and blood flow variations. Bayesian regression and regular least-square regressions were applied to estimate CMRO from the kinetics. The accuracy and precision of the estimates were evaluated. The improvement in precision was as high as 50% for gray matter of 1 cm (3) size in a study of 0.5 million counts/slice over 3 min. Similar improvement was achieved for white matter in 1-million-count studies. The amount of improvement is larger for higher noise cases.