PURPOSE: To provide a quantitative assessment of motion and distortion correction of diffusion-weighted images (DWIs) of the breast and to evaluate the effects of registration on the mean apparent diffusion coefficient (mADC). MATERIALS AND METHODS: Eight datasets from four patients with breast cancer and eight datasets from six healthy controls were acquired on a 3T scanner. A 3D affine registration was used to align each set of images and principal component analysis was used to assess the results. Variance in tumor ADC measurements, tumor mADC values, and voxel-wise tumor mADC values were compared before and after registration for each patient. RESULTS: Image registration significantly (P = 0.008) improved image alignment for both groups and significantly (P < 0.001) reduced the variance across individual tumor ADC measurements. While misalignment led to potential under- and overestimation of mADC values for individual voxels, average tumor mADC values did not significantly change (P > 0.09) after registration. CONCLUSION: 3D affine registration improved the alignment of DWIs of the breast and reduced the variance between ADC measurements. Although the reduced variance did not significantly change tumor region-of-interest measures of mADC, it may have a significant impact on voxel-based analyses.
PURPOSE: To provide a quantitative assessment of motion and distortion correction of diffusion-weighted images (DWIs) of the breast and to evaluate the effects of registration on the mean apparent diffusion coefficient (mADC). MATERIALS AND METHODS: Eight datasets from four patients with breast cancer and eight datasets from six healthy controls were acquired on a 3T scanner. A 3D affine registration was used to align each set of images and principal component analysis was used to assess the results. Variance in tumorADC measurements, tumormADC values, and voxel-wise tumormADC values were compared before and after registration for each patient. RESULTS: Image registration significantly (P = 0.008) improved image alignment for both groups and significantly (P < 0.001) reduced the variance across individual tumorADC measurements. While misalignment led to potential under- and overestimation of mADC values for individual voxels, average tumormADC values did not significantly change (P > 0.09) after registration. CONCLUSION: 3D affine registration improved the alignment of DWIs of the breast and reduced the variance between ADC measurements. Although the reduced variance did not significantly change tumor region-of-interest measures of mADC, it may have a significant impact on voxel-based analyses.
Authors: Bing Ma; Charles R Meyer; Martin D Pickles; Thomas L Chenevert; Peyton H Bland; Craig J Galbán; Alnawaz Rehemtulla; Lindsay W Turnbull; Brian D Ross Journal: Inf Process Med Imaging Date: 2009
Authors: Nkiruka C Atuegwu; Xia Li; Lori R Arlinghaus; Richard G Abramson; Jason M Williams; A Bapsi Chakravarthy; Vandana G Abramson; Thomas E Yankeelov Journal: Med Phys Date: 2014-05 Impact factor: 4.071
Authors: Debosmita Biswas; Daniel S Hippe; Yi Wang; Michaela R DelPriore; Mladen Zečević; John R Scheel; Habib Rahbar; Savannah C Partridge Journal: Radiol Imaging Cancer Date: 2022-01
Authors: Xia Li; Lori R Arlinghaus; Gregory D Ayers; A Bapsi Chakravarthy; Richard G Abramson; Vandana G Abramson; Nkiruka Atuegwu; Jaime Farley; Ingrid A Mayer; Mark C Kelley; Ingrid M Meszoely; Julie Means-Powell; Ana M Grau; Melinda Sanders; Sandeep R Bhave; Thomas E Yankeelov Journal: Magn Reson Med Date: 2013-05-09 Impact factor: 4.668
Authors: Jennifer G Whisenant; Justin Romanoff; Habib Rahbar; Averi E Kitsch; Sara M Harvey; Linda Moy; Wendy B DeMartini; Basak E Dogan; Wei T Yang; Lilian C Wang; Bonnie N Joe; Lisa J Wilmes; Nola M Hylton; Karen Y Oh; Luminita A Tudorica; Colleen H Neal; Dariya I Malyarenko; Elizabeth S McDonald; Christopher E Comstock; Thomas E Yankeelov; Thomas L Chenevert; Savannah C Partridge Journal: J Breast Imaging Date: 2020-12-24
Authors: Hossein Ragheb; Neil A Thacker; Jean-Marie Guyader; Stefan Klein; Nandita M deSouza; Alan Jackson Journal: PLoS One Date: 2015-07-23 Impact factor: 3.240