TY - JOUR
T1 - Harmonization of Quantitative Parenchymal Enhancement in T1 -Weighted Breast MRI
AU - van der Velden, Bas H M
AU - van Rijssel, Michael J
AU - Lena, Beatrice
AU - Philippens, Marielle E P
AU - Loo, Claudette E
AU - Ragusi, Max A A
AU - Elias, Sjoerd G
AU - Sutton, Elizabeth J
AU - Morris, Elizabeth A
AU - Bartels, Lambertus W
AU - Gilhuijs, Kenneth G A
N1 - Funding Information:
Contract grant sponsor: the Dutch Cancer Society (KWF); Contract grant number: 10755.
Publisher Copyright:
© 2020 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/11
Y1 - 2020/11
N2 - Background: Differences in imaging parameters influence computer-extracted parenchymal enhancement measures from breast MRI. Purpose: To investigate the effect of differences in dynamic contrast-enhanced MRI acquisition parameter settings on quantitative parenchymal enhancement of the breast, and to evaluate harmonization of contrast-enhancement values with respect to flip angle and repetition time. Study Type: Retrospective. Phantom/Populations: We modeled parenchymal enhancement using simulations, a phantom, and two cohorts (N = 398 and N = 302) from independent cancer centers. Sequence Field/Strength: 1.5T dynamic contrast-enhanced T
1-weighted spoiled gradient echo MRI. Vendors: Philips, Siemens, General Electric Medical Systems. Assessment: We assessed harmonization of parenchymal enhancement in simulations and phantom by varying the MR parameters that influence the amount of T
1-weighting: flip angle (8°–25°) and repetition time (4–12 msec). We calculated the median and interquartile range (IQR) of the enhancement values before and after harmonization. In vivo, we assessed overlap of quantitative parenchymal enhancement in the cohorts before and after harmonization using kernel density estimations. Cohort 1 was scanned with flip angle 20° and repetition time 8 msec; cohort 2 with flip angle 10° and repetition time 6 msec. Statistical Tests: Paired Wilcoxon signed-rank-test of bootstrapped kernel density estimations. Results: Before harmonization, simulated enhancement values had a median (IQR) of 0.46 (0.34–0.49). After harmonization, the IQR was reduced: median (IQR): 0.44 (0.44–0.45). In the phantom, the IQR also decreased, median (IQR): 0.96 (0.59–1.22) before harmonization, 0.96 (0.91–1.02) after harmonization. Harmonization yielded significantly (P < 0.001) better overlap in parenchymal enhancement between the cohorts: median (IQR) was 0.46 (0.37–0.58) for cohort 1 vs. 0.37 (0.30–0.44) for cohort 2 before harmonization (57% overlap); and 0.35 (0.28–0.43) vs.0.37 (0.30–0.44) after harmonization (85% overlap). Data Conclusion: The proposed practical harmonization method enables an accurate comparison between patients scanned with differences in imaging parameters. Level of Evidence: 3. Technical Efficacy Stage: 4.
AB - Background: Differences in imaging parameters influence computer-extracted parenchymal enhancement measures from breast MRI. Purpose: To investigate the effect of differences in dynamic contrast-enhanced MRI acquisition parameter settings on quantitative parenchymal enhancement of the breast, and to evaluate harmonization of contrast-enhancement values with respect to flip angle and repetition time. Study Type: Retrospective. Phantom/Populations: We modeled parenchymal enhancement using simulations, a phantom, and two cohorts (N = 398 and N = 302) from independent cancer centers. Sequence Field/Strength: 1.5T dynamic contrast-enhanced T
1-weighted spoiled gradient echo MRI. Vendors: Philips, Siemens, General Electric Medical Systems. Assessment: We assessed harmonization of parenchymal enhancement in simulations and phantom by varying the MR parameters that influence the amount of T
1-weighting: flip angle (8°–25°) and repetition time (4–12 msec). We calculated the median and interquartile range (IQR) of the enhancement values before and after harmonization. In vivo, we assessed overlap of quantitative parenchymal enhancement in the cohorts before and after harmonization using kernel density estimations. Cohort 1 was scanned with flip angle 20° and repetition time 8 msec; cohort 2 with flip angle 10° and repetition time 6 msec. Statistical Tests: Paired Wilcoxon signed-rank-test of bootstrapped kernel density estimations. Results: Before harmonization, simulated enhancement values had a median (IQR) of 0.46 (0.34–0.49). After harmonization, the IQR was reduced: median (IQR): 0.44 (0.44–0.45). In the phantom, the IQR also decreased, median (IQR): 0.96 (0.59–1.22) before harmonization, 0.96 (0.91–1.02) after harmonization. Harmonization yielded significantly (P < 0.001) better overlap in parenchymal enhancement between the cohorts: median (IQR) was 0.46 (0.37–0.58) for cohort 1 vs. 0.37 (0.30–0.44) for cohort 2 before harmonization (57% overlap); and 0.35 (0.28–0.43) vs.0.37 (0.30–0.44) after harmonization (85% overlap). Data Conclusion: The proposed practical harmonization method enables an accurate comparison between patients scanned with differences in imaging parameters. Level of Evidence: 3. Technical Efficacy Stage: 4.
UR - http://www.scopus.com/inward/record.url?scp=85085871598&partnerID=8YFLogxK
U2 - 10.1002/jmri.27244
DO - 10.1002/jmri.27244
M3 - Article
C2 - 32491246
SN - 1053-1807
VL - 52
SP - 1374
EP - 1382
JO - Journal of Magnetic Resonance Imaging
JF - Journal of Magnetic Resonance Imaging
IS - 5
ER -