PurposeLow contrast (LC) detectability is a common test criterion for diagnostic radiologic quality control (QC) programs. Automation of this test is desirable in order to reduce human variability and to speed up analysis. However, automation is challenging due to the complexity of the human visual perception system and the ability to create algorithms that mimic this response. This paper describes the development and testing of an automated LC detection algorithm for use in the analysis of magnetic resonance (MR) images of the American College of Radiology (ACR) QC phantom.MethodsThe detection algorithm includes fuzzy logic decision processes and various edge detection methods to quantify LC detectability. Algorithm performance was first evaluated using a single LC phantom MR image with the addition of incremental zero mean Gaussian noise resulting in a total of 200 images. A c‐statistic was calculated to determine the role of CNR to indicate when the algorithm would detect ten spokes. To evaluate inter‐rater agreement between experienced observers and the algorithm, a blinded observer study was performed on 196 LC phantom images acquired from nine clinical MR scanners. The nine scanners included two MR manufacturers and two field strengths (1.5 T, 3.0 T). Inter‐rater and algorithm‐rater agreement was quantified using Krippendorff's alpha.ResultsFor the Gaussian noise added data, CNR ranged from 0.519 to 11.7 with CNR being considered an excellent discriminator of algorithm performance (c‐statistic = 0.9777). Reviewer scoring of the clinical phantom data resulted in an inter‐rater agreement of 0.673 with the agreement between observers and algorithm equal to 0.652, both of which indicate significant agreement.ConclusionsThis study demonstrates that the detection of LC test patterns for MR imaging QC programs can be successfully developed and that their response can model the human visual detection system of expert MR QC readers.
Regional assessment of in vivo myocardial stiffness using 3D magnetic resonance elastography in a porcine model of myocardial infarction
PurposeTo evaluate if cardiac magnetic resonance elastography (MRE) can measure increased stiffness in patients with cardiac amyloidosis. Myocardial tissue stiffness plays an important role in cardiac function. A noninvasive quantitative imaging technique capable of measuring myocardial stiffness could aid in disease diagnosis, therapy monitoring, and disease prognostic strategies. We recently developed a high‐frequency cardiac MRE technique capable of making noninvasive stiffness measurements.Materials and MethodsIn all, 16 volunteers and 22 patients with cardiac amyloidosis were enrolled in this study after Institutional Review Board approval and obtaining formal written consent. All subjects were imaged head‐first in the supine position in a 1.5T closed‐bore MR imager. 3D MRE was performed using 5 mm isotropic resolution oblique short‐axis slices and a vibration frequency of 140 Hz to obtain global quantitativein vivoleft ventricular stiffness measurements. The median stiffness was compared between the two cohorts. An octahedral shear strain signal‐to‐noise ratio (OSS‐SNR) threshold of 1.17 was used to exclude exams with insufficient motion amplitude.ResultsFive volunteers and six patients had to be excluded from the study because they fell below the 1.17 OSS‐SNR threshold. The myocardial stiffness of cardiac amyloid patients (median: 11.4 kPa, min: 9.2, max: 15.7) was significantly higher (P = 0.0008) than normal controls (median: 8.2 kPa, min: 7.2, max: 11.8).ConclusionThis study demonstrates the feasibility of 3D high‐frequency cardiac MRE as a contrast‐agent‐free diagnostic imaging technique for cardiac amyloidosis.Level of Evidence:2Technical Efficacy:Stage 2J. Magn. Reson. Imaging 2017;46:1361–1367.
Quantitative assessment of lung stiffness in patients with interstitial lung disease using MR elastography
PurposeTo investigate the use of magnetic resonance elastography (MRE) in the quantitative assessment of pulmonary fibrosis by comparing quantitative shear stiffness measurements of lung parenchyma in patients diagnosed with fibrotic interstitial lung disease (ILD) and healthy controls.Materials and MethodsA 1.5T spin‐echo, echo planar imaging MRE (SE‐EPI MRE) pulse sequence was utilized to assess absolute lung shear stiffness in 15 patients with diagnosed ILD and in 11 healthy controls. Data were collected at residual volume (RV) and total lung capacity (TLC). Spirometry data were obtained immediately prior to scanning. To test for statistical significance between RV and TLC shear stiffness estimates a two‐sample t‐test was performed. To assess variability within individual subject shear stiffness estimates, the intraclass correlation coefficient (ICC) and Krippendorff's alpha were calculated.ResultsPatients with ILD exhibited an average (±1 standard deviation) shear stiffness of 2.74 (±0.896) kPa at TLC and 1.32 (±0.300) kPa at RV. The corresponding values for healthy individuals were 1.33 (±0.195) kPa and 0.849 (±0.250) kPa, respectively. The difference in shear stiffness between RV and TLC was statistically significant (P < 0.001). At TLC, the ICC and alpha values were 0.909 and 0.887, respectively. At RV, the ICC and alpha values were 0.852 and 0.862, respectively.ConclusionIn subjects with known fibrotic interstitial lung disease, parenchymal shear stiffness is increased when compared to normal controls at both RV and TLC, with TLC demonstrating the most significant difference. MRE‐derived parenchymal shear stiffness is a promising new noninvasive imaging‐based biomarker of interstitial lung disease.Level of Evidence: 1Technical Efficacy: Stage 2J. MAGN. RESON. IMAGING 2017;46:365–374
Quantitative 3D magnetic resonance elastography: Comparison with dynamic mechanical analysis