Richard A Baheza1, E Brian Welch2, Daniel F Gochberg3, Melinda Sanders4, Sara Harvey5, John C Gore6, Thomas E Yankeelov7. 1. Department of Biomedical Engineering and Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee 37232-2310. 2. Institute of Imaging Science and Departments of Radiology and Radiological Sciences and Biomedical Engineering, Vanderbilt University, Nashville, Tennessee 37232-2310. 3. Institute of Imaging Science and Departments of Radiology and Radiological Sciences, and Physics and Astronomy, Vanderbilt University, Nashville, Tennessee 37232-2310. 4. Department of Pathology, Vanderbilt University, Nashville, Tennessee 37232-2310. 5. Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee 37232-2310. 6. Institute of Imaging Science and Departments of Biomedical Engineering, Radiology and Radiological Sciences, Physics and Astronomy, and Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232-2310. 7. Institute of Imaging Science and Departments of Radiology and Radiological Sciences, Biomedical Engineering, Physics and Astronomy, and Cancer Biology, Vanderbilt University, Nashville, Tennessee 37232-2310.
Abstract
PURPOSE: To develop and evaluate a new method for detecting calcium deposits using their characteristic magnetic susceptibility effects on magnetic resonance (MR) images at high fields and demonstrate its potential in practice for detecting breast microcalcifications. METHODS: Characteristic dipole signatures of calcium deposits were detected in magnetic resonance phase images by computing the cross-correlation between the acquired data and a library of templates containing simulated phase patterns of spherical deposits. The influence of signal-to-noise ratio and various other MR parameters on the results were assessed using simulations and validated experimentally. The method was tested experimentally for detection of calcium fragments within gel phantoms and calcium-like inhomogeneities within chicken tissue at 7 T with optimized MR acquisition parameters. The method was also evaluated for detection of simulated microcalcifications, modeled from biopsy samples of malignant breast cancer, inserted in silico into breast magnetic resonance imaging (MRIs) of healthy subjects at 7 T. For both assessments of calcium fragments in phantoms and biopsy-based simulated microcalcifications in breast MRIs, receiver operator characteristic curve analyses were performed to determine the cross-correlation index cutoff, for achieving optimal sensitivity and specificity, and the area under the curve (AUC), for measuring the method's performance. RESULTS: The method detected calcium fragments with sizes of 0.14-0.79 mm, 1 mm calcium-like deposits, and simulated microcalcifications with sizes of 0.4-1.0 mm in images with voxel sizes between (0.2 mm)(3) and (0.6 mm)(3). In images acquired at 7 T with voxel sizes of (0.2 mm)(3)-(0.4 mm)(3), calcium fragments (size 0.3-0.4 mm) were detected with a sensitivity, specificity, and AUC of 78%-90%, 51%-68%, and 0.77%-0.88%, respectively. In images acquired with a human 7 T scanner, acquisition times below 12 min, and voxel sizes of (0.4 mm)(3)-(0.6 mm)(3), simulated microcalcifications with sizes of 0.6-1.0 mm were detected with a sensitivity, specificity, and AUC of 75%-87%, 54%-87%, and 0.76%-0.90%, respectively. However, different microcalcification shapes were indistinguishable. CONCLUSIONS: The new method is promising for detecting relatively large microcalcifications (i.e., 0.6-0.9 mm) within the breast at 7 T in reasonable times. Detection of smaller deposits at high field may be possible with higher spatial resolution, but such images require relatively long scan times. Although mammography can detect and distinguish the shape of smaller microcalcifications with superior sensitivity and specificity, this alternative method does not expose tissue to ionizing radiation, is not affected by breast density, and can be combined with other MRI methods (e.g., dynamic contrast-enhanced MRI and diffusion weighted MRI), to potentially improve diagnostic performance.
PURPOSE: To develop and evaluate a new method for detecting calcium deposits using their characteristic magnetic susceptibility effects on magnetic resonance (MR) images at high fields and demonstrate its potential in practice for detecting breast microcalcifications. METHODS: Characteristic dipole signatures of calcium deposits were detected in magnetic resonance phase images by computing the cross-correlation between the acquired data and a library of templates containing simulated phase patterns of spherical deposits. The influence of signal-to-noise ratio and various other MR parameters on the results were assessed using simulations and validated experimentally. The method was tested experimentally for detection of calcium fragments within gel phantoms and calcium-like inhomogeneities within chicken tissue at 7 T with optimized MR acquisition parameters. The method was also evaluated for detection of simulated microcalcifications, modeled from biopsy samples of malignant breast cancer, inserted in silico into breast magnetic resonance imaging (MRIs) of healthy subjects at 7 T. For both assessments of calcium fragments in phantoms and biopsy-based simulated microcalcifications in breast MRIs, receiver operator characteristic curve analyses were performed to determine the cross-correlation index cutoff, for achieving optimal sensitivity and specificity, and the area under the curve (AUC), for measuring the method's performance. RESULTS: The method detected calcium fragments with sizes of 0.14-0.79 mm, 1 mm calcium-like deposits, and simulated microcalcifications with sizes of 0.4-1.0 mm in images with voxel sizes between (0.2 mm)(3) and (0.6 mm)(3). In images acquired at 7 T with voxel sizes of (0.2 mm)(3)-(0.4 mm)(3), calcium fragments (size 0.3-0.4 mm) were detected with a sensitivity, specificity, and AUC of 78%-90%, 51%-68%, and 0.77%-0.88%, respectively. In images acquired with a human 7 T scanner, acquisition times below 12 min, and voxel sizes of (0.4 mm)(3)-(0.6 mm)(3), simulated microcalcifications with sizes of 0.6-1.0 mm were detected with a sensitivity, specificity, and AUC of 75%-87%, 54%-87%, and 0.76%-0.90%, respectively. However, different microcalcification shapes were indistinguishable. CONCLUSIONS: The new method is promising for detecting relatively large microcalcifications (i.e., 0.6-0.9 mm) within the breast at 7 T in reasonable times. Detection of smaller deposits at high field may be possible with higher spatial resolution, but such images require relatively long scan times. Although mammography can detect and distinguish the shape of smaller microcalcifications with superior sensitivity and specificity, this alternative method does not expose tissue to ionizing radiation, is not affected by breast density, and can be combined with other MRI methods (e.g., dynamic contrast-enhanced MRI and diffusion weighted MRI), to potentially improve diagnostic performance.
Authors: Dennis W J Klomp; Bart L van de Bank; Alexander Raaijmakers; Mies A Korteweg; Cecilia Possanzini; Vincent O Boer; Cornelius A T van de Berg; Maurice A A J van de Bosch; Peter R Luijten Journal: NMR Biomed Date: 2011-03-24 Impact factor: 4.044
Authors: R D Rosenberg; W C Hunt; M R Williamson; F D Gilliland; P W Wiest; C A Kelsey; C R Key; M N Linver Journal: Radiology Date: 1998-11 Impact factor: 11.105
Authors: Blerim Mujaj; Andrés M Arias Lorza; Arna van Engelen; Marleen de Bruijne; Oscar H Franco; Aad van der Lugt; Meike W Vernooij; Daniel Bos Journal: J Cardiovasc Magn Reson Date: 2017-03-06 Impact factor: 5.364