Improvements in the clinical utility of calculated T2 images of the human brain.
Magnetic Resonance Imaging (MRI) affords a considerable improvement in image contrast over other methods by virtue of the intrinsic NMR parameters spin density, T1, and T2. However, the clinical utility of routine quantification of these parameters is currently unknown. Calculated T2 images might afford additional disease specific information provided the calculation algorithm generates accurate T2 values. In this study, calculated T2 images of a MnCl2 phantom (spanning a T2 range of interest of 45.7 ms to 346.6 ms at 6 MHz) were generated utilizing a variety of calculation algorithms based upon a data set of 32 sequential spin-echo (SE) images. In general, when utilizing only the earliest sequential SE after the 90 degree pulse for the T2 calculation, the greater the number of SE used in the calculation algorithm, regardless of how they were averaged, the more accurate and less noisy was the calculated image. When only limited numbers of SE were used in the calculation algorithm, accuracy and noise varied with the choice of TE suggesting that there may be optimal timings for TE for a particular T2 range of interest. Forty-two calculated T2 head images of normal subjects, based upon data sets of 16 sequential SE, were evaluated for the T2 values of normal brain. These were compared to T2 images calculated via 7 different algorithms based upon 16 SE data sets from two patients with CNS pathology. An optimal algorithm was identified in which 16 SE Carr-Purcell-Meiboom-Gill (CPMG) were averaged into two images for the T2 calculation. With this algorithm, calculated images could be generated efficiently which were accurate and relatively noise free. The availability of such images maximized whatever disease specificity, and thus clinical utility, T2 information affords.
D001921:Brain / Q000033:anatomy & histology*; D001927:Brain Diseases / Q000175:diagnosis; D002544:Cerebral Infarction / Q000175:diagnosis; D006801:Humans; D009682:Magnetic Resonance Spectroscopy / Q000379:methods; D009103:Multiple Sclerosis / Q000175:diagnosis