Iodine quantification in limited angle tomography.
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| Title: | Iodine quantification in limited angle tomography. |
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| Authors: | Michielsen, Koen1 (AUTHOR), Rodríguez‐Ruiz, Alejandro1 (AUTHOR), Reiser, Ingrid2 (AUTHOR), Nagy, James G.3 (AUTHOR), Sechopoulos, Ioannis1,4 (AUTHOR) ioannis.sechopoulos@radboudumc.nl |
| Source: | Medical Physics. Oct2020, Vol. 47 Issue 10, p4906-4916. 11p. |
| Subjects: | Digital mammography, Magnetic resonance mammography, Convolutional neural networks, Breast, Tomosynthesis, Iodine, Tomography |
| Abstract: | Purpose: To develop and test the feasibility of a two‐pass iterative reconstruction algorithm with material decomposition designed to obtain quantitative iodine measurements in digital breast tomosynthesis. Methods: Contrast‐enhanced mammography has shown promise as a cost‐effective alternative to magnetic resonance imaging for imaging breast cancer, especially in dense breasts. However, one limitation is the poor quantification of iodine contrast since the true three‐dimensional lesion shape cannot be inferred from the two‐dimensional (2D) projection. Use of limited angle tomography can potentially overcome this limitation by segmenting the iodine map generated by the first‐pass reconstruction using a convolutional neural network, and using this segmentation to restrict the iodine distribution in the second pass of the reconstruction. To evaluate the performance of the algorithms, a set of 2D digital breast phantoms containing targets with varying iodine concentration was used. In each breast phantom, a single simulated lesion with a random size (4 to 8 mm) was placed in a random location within each phantom, with the iodine distribution defined as either homogeneous or rim‐enhanced and blood iodine concentration set between 1.4 and 5.6 mg/mL. Limited angle projection data of these phantoms were simulated for wide and narrow angle geometries, and the proposed reconstruction and segmentation algorithms were applied. Results: The median Dice similarity coefficient of the segmented masks was 0.975 for the wide angle data and 0.926 for the narrow angle data. Using these segmentations during the second reconstruction pass resulted in an improvement in the concentration estimates (mean estimated‐to‐true concentration ratio, before and after second pass: 48% to 73% for wide angle; 30% to 73% for narrow angle), and a reduction in the coefficient of variation of the estimates (55% to 27% for wide angle; 54% to 35% for narrow angle). Conclusion: We demonstrate that the proposed two‐pass reconstruction can potentially improve accuracy and precision of iodine quantification in contrast‐enhanced tomosynthesis. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Purpose: To develop and test the feasibility of a two‐pass iterative reconstruction algorithm with material decomposition designed to obtain quantitative iodine measurements in digital breast tomosynthesis. Methods: Contrast‐enhanced mammography has shown promise as a cost‐effective alternative to magnetic resonance imaging for imaging breast cancer, especially in dense breasts. However, one limitation is the poor quantification of iodine contrast since the true three‐dimensional lesion shape cannot be inferred from the two‐dimensional (2D) projection. Use of limited angle tomography can potentially overcome this limitation by segmenting the iodine map generated by the first‐pass reconstruction using a convolutional neural network, and using this segmentation to restrict the iodine distribution in the second pass of the reconstruction. To evaluate the performance of the algorithms, a set of 2D digital breast phantoms containing targets with varying iodine concentration was used. In each breast phantom, a single simulated lesion with a random size (4 to 8 mm) was placed in a random location within each phantom, with the iodine distribution defined as either homogeneous or rim‐enhanced and blood iodine concentration set between 1.4 and 5.6 mg/mL. Limited angle projection data of these phantoms were simulated for wide and narrow angle geometries, and the proposed reconstruction and segmentation algorithms were applied. Results: The median Dice similarity coefficient of the segmented masks was 0.975 for the wide angle data and 0.926 for the narrow angle data. Using these segmentations during the second reconstruction pass resulted in an improvement in the concentration estimates (mean estimated‐to‐true concentration ratio, before and after second pass: 48% to 73% for wide angle; 30% to 73% for narrow angle), and a reduction in the coefficient of variation of the estimates (55% to 27% for wide angle; 54% to 35% for narrow angle). Conclusion: We demonstrate that the proposed two‐pass reconstruction can potentially improve accuracy and precision of iodine quantification in contrast‐enhanced tomosynthesis. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 00942405 |
| DOI: | 10.1002/mp.14400 |
