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Please see the Editorial Comment by Derik L. Davis discussing this article. BACKGROUND. Potential approaches for abbreviated knee MRI, including prospective acceleration with deep learning, have ac...

BACKGROUND: Clinical knee MRI protocols require upwards of 15 minutes of scan time. PURPOSE/HYPOTHESIS: To compare the imaging appearance of knee abnormalities depicted with a 5-minute 3D double-echo in steady-state (DESS) sequence with separate echo images, with that of a routine clinical knee MRI protocol. A secondary goal was to compare the imaging appearance of knee abnormalities depicted with 5-minute DESS paired with a 2-minute coronal proton-density fat-saturated (PDFS) sequence. STUDY TYPE: Prospective. SUBJECTS: Thirty-six consecutive patients (19 male) referred for a routine knee MRI. FIELD STRENGTH/SEQUENCES: DESS and PDFS at 3T. ASSESSMENT: Five musculoskeletal radiologists evaluated all images for the presence of internal knee derangement using DESS, DESS+PDFS, and the conventional imaging protocol, and their associated diagnostic confidence of the reading. STATISTICAL TESTS: Differences in positive and negative percent agreement (PPA and NPA, respectively) and 95% confidence intervals (CIs) for DESS and DESS+PDFS compared with the conventional protocol were calculated and tested using exact McNemar tests. The percentage of observations where DESS or DESS+PDFS had equivalent confidence ratings to DESS+Conv were tested with exact symmetry tests. Interreader agreement was calculated using Krippendorff’s alpha. RESULTS: DESS had a PPA of 90% (88–92% CI) and NPA of 99% (99–99% CI). DESS+PDFS had increased PPA of 99% (95–99% CI) and NPA of 100% (99–100% CI) compared with DESS (both P < 0.001). DESS had equivalent diagnostic confidence to DESS+Conv in 94% of findings, whereas DESS+PDFS had equivalent diagnostic confidence in 99% of findings (both P < 0.001). All readers had moderate concordance for all three protocols (Krippendorff’s alpha 47–48%). DATA CONCLUSION: Both 1) 5-minute 3D-DESS with separated echoes and 2) 5-minute 3D-DESS paired with a 2-minute coronal PDFS sequence depicted knee abnormalities similarly to a routine clinical knee MRI protocol, which may be a promising technique for abbreviated knee MRI.

PURPOSE: To improve the homogeneity and consistency of Apparent Diffusion Coefficient (ADC) estimates in cartilage from the Double-Echo in Steady-State (DESS) sequence by applying SNR-weighted regularization during post-processing. MATERIALS AND METHODS: An estimation method that linearizes ADC estimates from DESS is used in conjunction with a smoothness constraint to suppress noise-induced variation in ADC estimates. Simulations, phantom scans, and in vivo scans are used to demonstrate how the method reduces ADC variability. Conventional Diffusion Weighted Echo Planar Imaging (DW EPI) maps are acquired for comparison of mean and standard deviation of the ADC estimate. RESULTS: Simulations and phantom scans demonstrated that the SNR-weighted regularization can produce homogenous ADC maps at varying levels of SNR, while non-regularized maps only estimate ADC accurately at high SNR levels. The in vivo maps showed that the SNR-weighted regularization produced ADC maps with similar heterogeneity to maps produced with standard DW EPI, but without the distortion of such reference scans. CONCLUSION: A linear approximation of a simplified model of the relationship between DESS signals allows for fast SNR-weighted regularization of ADC maps that reduces estimation error in relatively short T(2) tissue such as cartilage.

Purpose To introduce a simple analytical formula for estimating T 2 from a single Double-Echo in Steady-State (DESS) scan. Methods Extended Phase Graph (EPG) modeling was used to develop a straightforward linear approximation of the relationship between the two DESS signals, enabling accurate T 2 estimation from one DESS scan. Simulations were performed to demonstrate cancellation of different echo pathways to validate this simple model. The resulting analytic formula was compared to previous methods for T 2 estimation using DESS and fast spin-echo scans in agar phantoms and knee cartilage in three volunteers and three patients. The DESS approach allows 3D (256 × 256 × 44) T 2 -mapping with fat suppression in scan times of 3–4 min. Results The simulations demonstrated that the model approximates the true signal very well. If the T 1 is within 20% of the assumed T 1 , the T 2 estimation error was shown to be less than 5% for typical scans. The inherent residual error in the model was demonstrated to be small both due to signal decay and opposing signal contributions. The estimated T 2 from the linear relationship agrees well with reference scans, both for the phantoms and in vivo. The method resulted in less underestimation of T 2 than previous single-scan approaches, with processing times 60 times faster than using a numerical fit. Conclusion A simplified relationship between the two DESS signals allows for rapid 3D T 2 quantification with DESS that is accurate, yet also simple. The simplicity of the method allows for immediate T 2 estimation in cartilage during the MRI examination.

PURPOSE: To develop a proof-of-concept convolutional neural network (CNN) to synthesize T2 maps in right lateral femoral condyle articular cartilage from anatomic MR images by using a conditional generative adversarial network (cGAN). MATERIALS AND METHODS: In this retrospective study, anatomic images (from turbo spin-echo and double-echo in steady-state scans) of the right knee of 4621 patients included in the 2004–2006 Osteoarthritis Initiative were used as input to a cGAN-based CNN, and a predicted CNN T2 was generated as output. These patients included men and women of all ethnicities, aged 45–79 years, with or at high risk for knee osteoarthritis incidence or progression who were recruited at four separate centers in the United States. These data were split into 3703 (80%) for training, 462 (10%) for validation, and 456 (10%) for testing. Linear regression analysis was performed between the multiecho spin-echo (MESE) and CNN T2 in the test dataset. A more detailed analysis was performed in 30 randomly selected patients by means of evaluation by two musculoskeletal radiologists and quantification of cartilage subregions. Radiologist assessments were compared by using two-sided t tests. RESULTS: The readers were moderately accurate in distinguishing CNN T2 from MESE T2, with one reader having random-chance categorization. CNN T2 values were correlated to the MESE values in the subregions of 30 patients and in the bulk analysis of all patients, with best-fit line slopes between 0.55 and 0.83. CONCLUSION: With use of a neural network–based cGAN approach, it is feasible to synthesize T2 maps in femoral cartilage from anatomic MRI sequences, giving good agreement with MESE scans. See also commentary by Yi and Fritz in this issue. Keywords: Cartilage Imaging, Knee, Experimental Investigations, Quantification, Vision, Application Domain, Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms © RSNA, 2021

Purpose To develop a radial, double-echo steady-state (DESS) sequence with ultra-short echo-time (UTE) capabilities for T2 measurement of short-T2 tissues along with simultaneous rapid, signal-to-noise ratio (SNR)-efficient, and high-isotropic-resolution morphological knee imaging. Methods THe 3D radial UTE readouts were incorporated into DESS, termed UTEDESS. Multiple-echo-time UTEDESS was used for performing T2 relaxometry for short-T2 tendons, ligaments, and menisci; and for Dixon water-fat imaging. In vivo T2 estimate repeatability and SNR efficiency for UTEDESS and Cartesian DESS were compared. The impact of coil combination methods on short-T2 measurements was evaluated by means of simulations. UTEDESS T2 measurements were compared with T2 measurements from Cartesian DESS, multi-echo spin-echo (MESE), and fast spin-echo (FSE). Results UTEDESS produced isotropic resolution images with high SNR efficiency in all short-T2 tissues. Simulations and experiments demonstrated that sum-of-squares coil combinations overestimated short-T2 measurements. UTEDESS measurements of meniscal T2 were comparable to DESS, MESE, and FSE measurements while the tendon and ligament measurements were less biased than those from Cartesian DESS. Average UTEDESS T2 repeatability variation was under 10% in all tissues. Conclusion The T2 measurements of short-T2 tissues and high-resolution morphological imaging provided by UTEDESS makes it promising for studying the whole knee, both in routine clinical examinations and longitudinal studies. Magn Reson Med 78:2136–2148, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

This work presents an analytical relationship between gradient-spoiled and RF-spoiled steady-state signals. The two echoes acquired in double-echo in steady-state scans are shown to lie on a line in the signal plane, where the two axes represent the amplitudes of each echo. The location along the line depends on the amount of spoiling and the diffusivity. The line terminates in a point corresponding to an RF-spoiled signal. In addition to the main contribution of demonstrating this signal relationship, we also include the secondary contribution of preliminary results from an example application of the relationship, in the form of a heuristic denoising method when both types of scans are performed. This is investigated in simulations, phantom scans, and in vivo scans. For the signal model, the main topic of this study, simulations confirmed its accuracy and explored its dependency on signal parameters and image noise. For the secondary topic of its preliminary application to reduce noise, simulations demonstrated the denoising method giving a reduction in noise-induced standard deviation of about 30%. The relative effect of the method on the signals is shown to depend on the slope of the described line, which is demonstrated to be zero at the Ernst angle. The phantom scans show a similar effect as the simulations. In vivo scans showed a slightly lower average improvement of about 28%.

Purpose Slice encoding for metal artifact correction acquires a three-dimensional image of each excited slice with view-angle tilting to reduce slice and readout direction artifacts respectively, but requires additional imaging time. The purpose of this study was to provide a technique for faster imaging around metallic implants by undersampling k-space. Methods Assuming that areas of slice distortion are localized, hexagonal sampling can reduce imaging time by 50% compared with conventional scans. This work demonstrates this technique by comparisons of fully sampled images with undersampled images, either from simulations from fully acquired data or from data actually undersampled during acquisition, in patients and phantoms. Hexagonal sampling is also shown to be compatible with parallel imaging and partial Fourier acquisitions. Image quality was evaluated using a structural similarity (SSIM) index. Results Images acquired with hexagonal undersampling had no visible difference in artifact suppression from fully sampled images. The SSIM index indicated high similarity to fully sampled images in all cases. Conclusion The study demonstrates the ability to reduce scan time by undersampling without compromising image quality. Magn Reson Med 73:662–668, 2015. © 2014 Wiley Periodicals, Inc.