A KNOWLEDGE-BASED APPROACH TO DECONVOLVE THE WATER COMPONENT IN IN-VIVO PROTON MR SPECTROSCOPY

Objective: The water component dominates in in vivo proton (H-1) spect roscopy. This consists of a prominent central peak with large ''wings, '' and consequently metabolites that lie on the ''wings'' become diffi cult to quantitate. A method has been developed to deconvolve the wate r component in in vivo H-1 spectroscopy, hence highlighting the metabo lite information. Materials and Methods: Spectra were acquired from vo lunteers and patients using 4D chemical shift imaging. The water decon volution procedure employed knowledge-based data processing in the fre quency domain and was fully automated. This involved describing the wa ter component as a coarse function consisting of a ''bulk'' region and ''wing'' areas. Points were identified in the spectrum that fit this description and then linked together to produce the water component. T he latter was smoothed and then subtracted from the original spectra t o produce good water deconvolution. Results: Over 2,000 in vivo H-1 sp ectra have been subjected to this algorithm. The method took similar t o 5 s to execute per spectrum consisting of 2,048 data points. Conclus ion: Knowledge-based data processing has provided a fast, efficient, a nd robust procedure to deconvolve the water component.