- Email: [email protected]
Nonlinear spatial normalization of SPECT images with SPM'99
NeuroImage
11, Number
5,2000,
Part 2 of 2 Parts 10
E al@
METHODS
Nonlinear spatial normalization E. A. Stamatakis*,
- ACQUISITION
of SPECT images with SPM’99
J.T.L. Wilson*, D.J. Wyperf-
*Department of Psychology, University of Stirling, Stirling, Scotland iDepartment of Clinical Physics, Institute of Neurological Sciences, Southern General Hospital, Glasgow, Scotland Introduction 99mTc-Exametazime (HMPAO) SPECT is used to assess blood flow abnormality in a variety of psychiatric and neurological disorders. Prior to image analysis, SPECT images are spatially normalized to each other or to a standardized atlas in order to allow correspondence of homologous anatomical regions between images and reporting of the results to a reference space such as the Talairach and Toumoux atlas (1). In previous experiments we established that with SPECT images, linear alignment offers satisfactory results in most cases (2). The aim here was to determine, by utilising the latest version of Statistical Parametric Mapping (3) SPM’99, whether nonlinear alignment or warping could be beneficial or detrimental to images containing lesions. Warping is used in image registration to distort the shape of images in order to accomplish a more exact correspondence between them by taking into account head shape. Artificial lesions were created in order to test images with known and controllable characteristics. Methods Artificial lesions were introduced on the average of 32 spatially normalized control images obtained using an SME 810 Novo (Strichman Medical Equipment) scanner. The lesions were constructed with NIH Image 1.61 by reducing the mean intensity (by 25%, 50% and 75%) of a spherical volume. They had diameters of 5, 10, 15,20, 2.5, 30, 35,40,45 and 50 voxels and each image contained only one lesion. The pitch, roll and yaw of all experimental images were adjusted by 0.1 radians. Following this the images were aligned to a SPECT template on a Sun ULTRA1 workstation, with the use of 12 parameter affine transformation in addition to 2x2x2,3x3x3,4x4x4,5x5x5,6x6x6, and 7x7x7 basis functions. The effect of nonlinear warping was examined in relation to the size (volume change) and shape (form factor change) of the lesion. The use of highly nonlinear models was expected to produce distorted lesions. The sum of squared differences between the template and each aligned image was also obtained in order to measure quality of image alignment. The smaller the sum of squared differences the better the alignment. Results Figure 1. The effect of nonlinear alignment The overall picture for volume measurement is that larger lesions suffer greater with SPM’99 on the volume of lesions with volume reduction as a result of increasing nonlinearity (Fig. 1). The greatest 10 and 30 voxels diameter at mean intensities decrease in volume, 65.86%, was noted for a lesion of 20 voxels diameter (2% of of 25%. 50% and 75% below normal. total brain volume) at 75% below normal intensity when aligned with 7x7x7 basis functions. Shape factor measurements varied from 1 for a circle to 0.87 in the worst deformation case for a lesion of 20 voxels diameter (2% of total brain volume) and mean intensity 75% lower than normal aligned with 6x6x6 basis functions. Overall there is a significant improvement over results previously obtained with SPM’96 (2). From the interpretation of the sum of squared differences results. it appears that when using SPM’99 lesions up to 15 voxels diameter can be aligned with any number of basis functions. Conclusions If the results for volume change, shape factor and the sum of square differences are considered, it is concluded that the use of I2 parameter linear affine alignment and up to 2x2x2 basis functions is the best choice for avoiding compromising anatomical integrit! when aligning SPECT images that contain lesions. References I. Tailarach, .I., Tournoux, P., 1988. Coplanar stereotaxic atlas of the human brain. New York: Thieme Medicai. 2. Stamatakis, E.A., Wilson, J.T.L., Wyper, D.J., 1999. Effect of non-linear registration on cerebral lesions. Medical Image Understanding and Analysis, Oxford 19-20 July 1999. 3. Friston, K.J., 1994. Statistical parametric mapping. Functional Neuroimaging (R.W. Thatcher. M.Hallet. T.Zeffiro. E.R. John and M. Huerta, Eds.), pp. 79-93. Academic Press, New York.
s527
11, Number
5,2000,
Part 2 of 2 Parts 10
E al@
METHODS
Nonlinear spatial normalization E. A. Stamatakis*,
- ACQUISITION
of SPECT images with SPM’99
J.T.L. Wilson*, D.J. Wyperf-
*Department of Psychology, University of Stirling, Stirling, Scotland iDepartment of Clinical Physics, Institute of Neurological Sciences, Southern General Hospital, Glasgow, Scotland Introduction 99mTc-Exametazime (HMPAO) SPECT is used to assess blood flow abnormality in a variety of psychiatric and neurological disorders. Prior to image analysis, SPECT images are spatially normalized to each other or to a standardized atlas in order to allow correspondence of homologous anatomical regions between images and reporting of the results to a reference space such as the Talairach and Toumoux atlas (1). In previous experiments we established that with SPECT images, linear alignment offers satisfactory results in most cases (2). The aim here was to determine, by utilising the latest version of Statistical Parametric Mapping (3) SPM’99, whether nonlinear alignment or warping could be beneficial or detrimental to images containing lesions. Warping is used in image registration to distort the shape of images in order to accomplish a more exact correspondence between them by taking into account head shape. Artificial lesions were created in order to test images with known and controllable characteristics. Methods Artificial lesions were introduced on the average of 32 spatially normalized control images obtained using an SME 810 Novo (Strichman Medical Equipment) scanner. The lesions were constructed with NIH Image 1.61 by reducing the mean intensity (by 25%, 50% and 75%) of a spherical volume. They had diameters of 5, 10, 15,20, 2.5, 30, 35,40,45 and 50 voxels and each image contained only one lesion. The pitch, roll and yaw of all experimental images were adjusted by 0.1 radians. Following this the images were aligned to a SPECT template on a Sun ULTRA1 workstation, with the use of 12 parameter affine transformation in addition to 2x2x2,3x3x3,4x4x4,5x5x5,6x6x6, and 7x7x7 basis functions. The effect of nonlinear warping was examined in relation to the size (volume change) and shape (form factor change) of the lesion. The use of highly nonlinear models was expected to produce distorted lesions. The sum of squared differences between the template and each aligned image was also obtained in order to measure quality of image alignment. The smaller the sum of squared differences the better the alignment. Results Figure 1. The effect of nonlinear alignment The overall picture for volume measurement is that larger lesions suffer greater with SPM’99 on the volume of lesions with volume reduction as a result of increasing nonlinearity (Fig. 1). The greatest 10 and 30 voxels diameter at mean intensities decrease in volume, 65.86%, was noted for a lesion of 20 voxels diameter (2% of of 25%. 50% and 75% below normal. total brain volume) at 75% below normal intensity when aligned with 7x7x7 basis functions. Shape factor measurements varied from 1 for a circle to 0.87 in the worst deformation case for a lesion of 20 voxels diameter (2% of total brain volume) and mean intensity 75% lower than normal aligned with 6x6x6 basis functions. Overall there is a significant improvement over results previously obtained with SPM’96 (2). From the interpretation of the sum of squared differences results. it appears that when using SPM’99 lesions up to 15 voxels diameter can be aligned with any number of basis functions. Conclusions If the results for volume change, shape factor and the sum of square differences are considered, it is concluded that the use of I2 parameter linear affine alignment and up to 2x2x2 basis functions is the best choice for avoiding compromising anatomical integrit! when aligning SPECT images that contain lesions. References I. Tailarach, .I., Tournoux, P., 1988. Coplanar stereotaxic atlas of the human brain. New York: Thieme Medicai. 2. Stamatakis, E.A., Wilson, J.T.L., Wyper, D.J., 1999. Effect of non-linear registration on cerebral lesions. Medical Image Understanding and Analysis, Oxford 19-20 July 1999. 3. Friston, K.J., 1994. Statistical parametric mapping. Functional Neuroimaging (R.W. Thatcher. M.Hallet. T.Zeffiro. E.R. John and M. Huerta, Eds.), pp. 79-93. Academic Press, New York.
s527