Metabolic imaging of patients with intracranial tumors: H-1 MR spectroscopic imaging and PET

Article Abstract:

Volume-selective hydrogen-1 magnetic resonance (H-1 MR) spectroscopy is a noninvasive technique used to diagnose and evaluate brain tumors and other diseases. It can measure levels of a number of biochemical compounds that are indicators of tumor growth or metabolism. It does this by measuring the inherently different magnetic properties unique to each compound. Problems arise from the fact that levels of these compounds can vary greatly in tumors, even within a tumor itself, making localization difficult. Volume selection techniques have been developed that enable multiple H-1 MR spectra in a single session and increased localization. This study compared the distribution of lactate (a product of glucose metabolism) and other compounds (metabolites) in the brain as detected by H-1 MR, with findings from positron emission tomography (PET), which can show glucose uptake. Glucose uptake and metabolism data can be used to indicate the presence of tumor activity. These techniques were performed on three patients with histories of brain tumors. MR showed high choline, low N-acetyl aspartate (NAA), and high lactate signal intensities in the tumor region, but with wide variations across the tumor. Lactate was found in all three patients. In one patient, there were undetectable levels of lactate within the tumor but high levels surrounding it; in the second patient, high levels of lactate were found in the solid portion of the tumor. In the third patient, both H-1 MR and PET were performed on the same day. High levels of lactate were found in the cranial part of the tumor with MR, and PET found correspondingly high levels of glucose-uptake. These results indicate that tumor metabolism can be measured as well as variations of metabolism within a tumor by means of H-1 MR. This increased sensitivity could help better characterize and treat brain tumors. (Consumer Summary produced by Reliance Medical Information, Inc.)

Measurement, Magnetic resonance imaging, Tumors, PET imaging, Positron emission tomography, Brain tumors, Brain chemistry

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Benign and malignant adrenal masses: CT distinction with attenuation coefficients, size, and observer analysis

Article Abstract:

Computed tomography (CT) is a scanning X-ray technique in which images are generated by a computer that detect and characterize masses in the adrenal glands. Determination of whether the masses are malignant (cancerous) or benign (not cancerous) is very important for treatment and prognosis, but this is difficult based on clinical information alone. It has been suggested that mass size and shape as seen by CT can help determine the type, but this has not been found to be highly accurate. Another study suggested that attenuation values could be used to differentiate the type of mass. These values are based on the loss of energy through tissue when CT scans are focused on the mass in question; this is measured in Hounsfield units (HU). The usefulness wa evaluated of CT attenuation values, size, and subjective observer interpretation in identifying benign and malignant adrenal masses. CT data from 66 adrenal masses in 55 patients was evaluated. The results showed that 38 of the 66 masses were benign and 28 were malignant. Average attenuation value for the malignant type was 28.9 HU and for the benign it was -2.2 HU, a significant difference. Benign masses averaged 2.1 centimeters (cm) in diameter and malignant masses averaged 3.9 cm in diameter. These results showed that CT attenuation values were more accurate than mass size in predicting the type of tumor. It is concluded that masses with values of less than 0 HU are associated with benign tumors. Patients with tumors with values between 0 and 10 HU probably do not have a malignancy; these patients should be closely followed-up. CT attenuation may be useful in deciding which masses require biopsy and which do not. (Consumer Summary produced by Reliance Medical Information, Inc.)

Usage, CT imaging, CAT scans, Cancer, Cancer diagnosis, Endocrine gland tumors

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