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Decreased, renormalized, or increased values of the calculated apparent diffusion coefficient (ADC) are observed in stroke models. A quantitative description of corresponding tissue states using ADC values may be extended to include true relaxation times. A histogram‐based segmentation is well suited for characterizing tissues according to specific parameter combinations irrespective of the heterogeneity found for human healthy and ischemic brain tissues. In a new approach, navigated diffusion‐weighted images and ADC maps were incorporated into voxel‐based parameter sets of relaxation times (T1, T2), and T1‐ or T2‐weighted images, followed by a supervised histogram‐based analysis. Healthy tissues were segmented by incorporating T1 relaxation into the data set, ischemic regions by combining T2‐ or diffusion‐weighted images with ADC maps. Mean values of healthy and pathologic tissues were determined, spatial distributions of the parameter vectors were visualized using color‐encoded overlays. One to six days after stroke, ischemic regions exhibited reduced relative mean ADC values. Magn Reson Med 43:52–61, 2000. © 2000 Wiley‐Liss, Inc.

T2-selective proton imaging at 10 MHz is based on a Carr-Purcell-Meiboom-Gill pulse sequence with at least 36 echoes and 2 tau greater than or equal to 6 ms employing the projection reconstruction technique. The transverse magnetization decay of the volume elements is multiexponential composed of up to three monoexponential T2 components. The T2 values are arranged in T2 histograms which are slice specific. T2 windows are defined in the T2 histogram and used for imaging and for selecting T2 values which are assigned to proton classes and tissues. Tissue characterization is based on the visualization of differences in T2 behavior. The T2 values are transformed into 256 gray levels or, by use of a red-green-blue lookup table, into a rainbow code. Two display techniques have been developed and implemented in the RWTH Aachen Magnetic Resonance Software System (RAMSES): (i) for nonselective T2 imaging with secondary T2 selection and encoding of molecular classes on the basis of T2 values; (ii) for T2-selective imaging by employing combined primary and secondary T2 selection and encoding particular tissues and variations therein. The tissues can be identified by selecting different classes of molecules, like water, lipids, and proteins, when shifting the primary T2 window on the T2 axis of the T2 histogram.

The authors surveyed existing standard codes for units of measures, such as ISO 2955, ANSI X3.50, and Health Level 7's ISO+. Because these standards specify only the character representation of units, the authors developed a semantic model for units based on dimensional analysis. Through this model, conversion between units and calculations with dimensioned quantities become as simple as calculating with numbers. All atomic symbols for prefixes and units are defined in one small table. Huge permutated conversion tables are not required. This method is also simple enough to be widely implementable in today's information systems. To promote the application of the method the authors provide an open-source implementation of this method in JAVA. All existing code standards for units, however, are incomplete for practical use and require substantial changes to correct their many ambiguities. The authors therefore developed a code for units that is much more complete and free from ambiguities.