We investigated the effect of nonlinear alignment on SPECT images with lesions. Linear alignment produces reliable results but the introduction of nonlinear methods can improve matching by accounting for global brain shape. We examined the hypothesis that nonlinear alignment can introduce unwanted image distortions when lesions are present. We set out to quantify possible distortions by constructing artificial lesions in order to obtain images with controllable characteristics. We examined the use of basis functions (in SPM96 and SPM99) and other nonlinear models (in AIR3.08) designed to achieve optimum alignment between image and template. We found that the use of models with high degrees of nonlinearity will result in unwanted deformations and that the safest way to align images with lesions is to use 12-point linear affine transformations. Masking was examined as a remedy to distortions caused by nonlinear methodologies and produced significantly improved results. (C) 2001 Academic Press.