Reproducibility Of R2 Research Articles

Quantitative MRI: Defining repeatability, reproducibility and accuracy for prostate cancer imaging biomarker development

IntroductionQuantitative MRI (qMRI) parameters have been increasingly used to develop predictive models to accurately monitor treatment response in prostate cancer after radiotherapy. To reliably detect changes in signal due to treatment response, predictive models require qMRI parameters with high repeatability and reproducibility. The purpose of this study was to measure qMRI parameter uncertainties in both commercial and in-house developed phantoms to guide the development of robust predictive models for monitoring treatment response. Materials and methodsADC, T1, and R2* values were acquired across three 3 T scanners with a prostate-specific qMRI protocol using the NIST/ISMRM system phantom, RSNA/NIST diffusion phantom, and an in-house phantom. A B1 field map was acquired to correct for flip angle inhomogeneity in T1 maps. All sequences were repeated in each scan to assess within-session repeatability. Weekly scans were acquired on one scanner for three months with the in-house phantom. Between-session repeatability was measured with test-retest scans 6-months apart on all scanners with all phantoms. Accuracy, defined as percentage deviation from reference value for ADC and T1, was evaluated using the system and diffusion phantoms. Repeatability and reproducibility coefficients of variation (%CV) were calculated for all qMRI parameters on all phantoms. ResultsOverall, repeatability CV of ADC was <2.40%, reproducibility CV was <3.98%, and accuracy ranged between −8.0% to 2.7% across all scanners. Applying B1 correction on T1 measurements significantly improved the repeatability and reproducibility (p<0.05) but increased error in accuracy (p<0.001). Repeatability and reproducibility of R2* was <4.5% and <7.3% respectively in the system phantom across all scanners. ConclusionRepeatability, reproducibility, and accuracy in qMRI parameters from a prostate-specific protocol was estimated using both commercial and in-house phantoms. Results from this work will be used to identify robust qMRI parameters for use in the development of predictive models to longitudinally monitor treatment response for prostate cancer in current and future clinical trials.

Complex confounder-corrected R2* mapping for liver iron quantification with MRI.

MRI-based R2* mapping may enable reliable and rapid quantification of liver iron concentration (LIC). However, the performance and reproducibility of R2* across acquisition protocols remain unknown. Therefore, the objective of this work was to evaluate the performance and reproducibility of complex confounder-corrected R2* across acquisition protocols, at both 1.5T and 3.0T. In this prospective study, 40 patients with suspected iron overload and 10 healthy controls were recruited with IRB approval and informed written consent and imaged at both 1.5T and 3.0T. For each subject, acquisitions included four different R2* mapping protocols at each field strength, and an FDA-approved R2-based method performed at 1.5T as a reference for LIC. R2* maps were reconstructed from the complex data acquisitions including correction for noise effects and fat signal. For each subject, field strength, andR2* acquisition, R2* measurements were performed in each of the nine liver Couinaud segments and the spleen. R2* measurements were compared across protocols and field strength (1.5T and 3.0T), and R2* was calibrated to LIC for each acquisition and field strength. R2* demonstrated high reproducibility across acquisition protocols (p > 0.05 for 96/108 pairwise comparisons across 2 field strengths and 9 liver segments, ICC > 0.91 for each field strength/segment combination) and high predictive ability (AUC > 0.95 for four clinically relevant LIC thresholds). Calibration of R2* to LIC was LIC = - 0.04 + 2.62 × 10-2 R2* at 1.5T and LIC = 0.00 + 1.41 × 10-2 R2* at 3.0T. Complex confounder-corrected R2* mapping enables LIC quantification with high reproducibility across acquisition protocols, at both 1.5T and 3.0T. • Confounder-corrected R2* of the liver provides reproducible R2* across acquisition protocols, including different spatial resolutions, echo times, and slice orientations, at both 1.5T and 3.0T. • For all acquisition protocols, high correlation with R2-based liver iron concentration (LIC) quantification was observed. • The calibration between confounder-corrected R2* and LIC, at both 1.5T and 3.0T, is determined in this study.

Improvement of reproducibility in quantitative susceptibility mapping (QSM) and transverse relaxation rates ( ) after physiological noise correction.

Numerous studies have suggested that quantitative susceptibility mapping (QSM) and transverse relaxation rates ( ) are useful to monitor neurological diseases. For clinical use of QSM and , reproducibility is an important feature. However, respiration-induced local magnetic field variation makes artifacts in gradient echo-based images and reduces the reproducibility of QSM and . To investigate the improvement of reproducibility of QSM and after the correction of respiration-induced field variation, and to assess the effect of varying types of the region of interest (ROI) analysis on reproducibility. Reproducibility study. Ten controls. 3T/multiecho gradient echo sequence. Intrascan reproducibility of QSM and was investigated in ROIs before and after the respiration correction. Reproducibility was obtained by the square of voxel-wise correlation coefficients between scans. A paired t-test was performed for comparison between before and after the respiration correction and between QSM and . Based on the ROI analysis, reproducibility increased after the respiration correction. Reproducibility in the white matter (11.89% increased in QSM and 23.38% in , P = 0.009 and 0.024, respectively) and deep gray matter (5.50% increased in QSM and 13.96% in , P = 0.024 and 0.019, respectively) increased significantly after the respiration correction. Reproducibility of was higher than that of QSM in the whole brain and cortical gray matter, while QSM maps showed higher reproducibility than in the white matter and deep gray matter. Respiration-induced error correction significantly improved reproducibility in QSM and mapping. QSM and mapping showed a different level of reproducibility depending on the types of ROI analysis. 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.