Examples of marginal resolution of NMR relaxation peaks using UPEN and diagnostics

The multiexponential inversion program UPEN by the authors [J. Magn. Reson. 1998; 132, 65-77; Ibid. 2000;147:273-85] employs negative feedback to a re gularization penalty to implement variable smoothing when both sharp and br oad features appear on a single distribution of relaxation times. This allo ws a good fit to relaxation data that correspond to a sum of decaying expon entials plus random noise, but it usually does not give a good fit to data that are distorted by systematic errors from instrument problems, which can cause erroneous "resolution" or erroneous non-resolution of peaks. UPEN pr ovides a series of diagnostic parameters to help identify such data problem s that can lead to interpretation errors, and, in particular, to warn when a close call on the resolution or non-resolution of nearby peaks might be q uestionable. Examples are given from a series of T-2 data sets from desicca ted bone samples, with examples where the presence of two peaks is required by good data, examples where the presence of two peaks is negated by good data, and examples where the resolution or non-resolution of peaks cannot b e trusted because of instrumental distortions revealed by UPEN diagnostic p arameters. It is suggested that processing relaxation data with UPEN in nea rly real time could permit retaking data while a sample is still available if the diagnostic parameters show instrumental problems. (C) 2001 Elsevier Science Inc. All rights reserved.