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As the genome is organized into a three-dimensional structure in intracellular space, epigenomic information also has a complex spatial arrangement. However, most epigenetic studies describe locations of methylation marks, chromatin accessibility regions, and histone modifications in the horizontal dimension. Proper spatial epigenomic information has rarely been obtained. In this study, we designed spatial chromatin accessibility sequencing (SCA-seq) to resolve the genome conformation by simultaneously capturing the epigenetic information in single-molecular resolution. Using SCA-seq, we simultaneously disclosed spatial interaction of chromatin accessibility (e.g. enhancer-promoter contacts), CpG island methylation, and spatial insulating functions of the CCCTC-binding factor. We demonstrate that SCA-seq paves the way to explore the mechanism of epigenetic interactions and extends our knowledge in 3D packaging of DNA in the nucleus.

Numerous natural antioxidants have been developed into agents for neurodegenerative diseases (NDs) treatment. Rosmarinic acid (RA), an excellent antioxidant, exhibits neuroprotective activity, but its anti-NDs efficacy still reminds puzzled. Here, Caenorhabditis elegans models were employed to systematically reveal RA-mediated mechanisms in delaying NDs from diverse facets, including oxidative stress, the homeostasis of neural and protein, and mitochondrial disorders. Firstly, RA significantly inhibited reactive oxygen species accumulation, reduced peroxide malonaldehyde production, and strengthened the antioxidant defense system via increasing superoxide dismutase activity. Besides, RA activated Notch and Wnt signaling to promote neurohomeostasis, reduce neuronal loss, and ameliorated polyglutamine and ɑ-synuclein-mediated dyskinesia in NDs models. Further, RA enhanced proteostasis by activating insulin/insulin-like growth factor 1 signaling, mitogen activated protein kinases and heat-shock factor 1 pathways. More importantly, molecular docking results revealed that RA specifically bound huntington protein and ɑ-synuclein to prevent toxic protein aggregation, which was consistent with the data that RA diminished polyglutamine and ɑ-synuclein aggregates in nematodes. Finally, RA ameliorated mitochondrial dysfunction including increasing adenosine triphosphate and mitochondrial membrane potential levels and rescuing mitochondrial membrane proteins’ expressions and mitochondrial structural abnormalities via regulating mitochondrial dynamics genes and improving the mitochondrial kinetic homeostasis. Thus, this study systematically revealed the RA-mediated neuroprotective mechanism and promoted RA as a promising nutritional intervention strategy to prevent NDs.

Epigenetic modifications of histones are associated with development and pathogenesis of disease. Existing approaches cannot provide insights into long-range interactions and represent the average chromatin state. Here we describe BIND&MODIFY, a method using long-read sequencing for profiling histone modifications and transcription factors on individual DNA fibers. We use recombinant fused protein A-M.EcoGII to tether methyltransferase M.EcoGII to protein binding sites to label neighboring regions by methylation. Aggregated BIND&MODIFY signal matches bulk ChIP-seq and CUT&TAG. BIND&MODIFY can simultaneously measure histone modification status, transcription factor binding, and CpG 5mC methylation at single-molecule resolution and also quantifies correlation between local and distal elements. Epigenetic modifications of histones are associated with development and pathogenesis of disease. Existing approaches cannot provide insights into long-range interactions and represent the average chromatin state. Here we describe BIND&MODIFY, a method using long-read sequencing for profiling histone modifications and transcription factors on individual DNA fibers. We use recombinant fused protein A-M.EcoGII to tether methyltransferase M.EcoGII to protein binding sites to label neighboring regions by methylation. Aggregated BIND&MODIFY signal matches bulk ChIP-seq and CUT&TAG. BIND&MODIFY can simultaneously measure histone modification status, transcription factor binding, and CpG 5mC methylation at single-molecule resolution and also quantifies correlation between local and distal elements.

Knee osteoarthritis is a prevalent disease worldwide. The automatic segmentation of knee tissues in magnetic resonance (MR) images has important clinical utility in assessing knee osteoarthritis. Deep learning- based methods show great potential in this application, but they often require a large amount of labeled training data, which is challenging and expensive to acquire. Unsupervised domain adaptation that transfers the learned knowledge from a source labeled dataset to a target unlabeled dataset can be used to address this problem. However, in medical scenarios, domain adaption techniques are often limited by access to the source data due to concerns about patient privacy. In this work, we proposed a novel and effective source-free unsupervised domain adaptation method for knee joint multi-tissue segmentation that does not require a source dataset. The proposed framework is split into two stages. In the first stage, matching batch normalization statistics guides the first segmentation network to realize model adaptation and is combined with augmented entropy minimization to obtain pseudo segmentation labels for the target MR images. The pseudo labels generated by the first segmentation network are then refined using a voting strategy to supervise the training of the models in the second stage. In the second stage, uncertainty-aware cross pseudo supervision is used to further boost the performance of the desired segmentation network, which comprises an encoder and a primary decoder. Our experiments demonstrated that the proposed method outperforms the current state-of-the-art source-free unsupervised domain adaptation techniques for segmenting knee tissues in MR images. Our study also demonstrated that the proposed approach is effective in reverse-directional adaptation.

As the genome has a three-dimensional structure in intracellular space, epigenomic information also has a complex spatial arrangement. However, the majority of epigenetic studies describe locations of methylation marks, chromatin accessibility regions, and histone modifications in the linear dimension. Proper spatial epigenomic information has rarely been obtained. In this study, we designed spatial chromatin accessibility sequencing (SCA-seq) to reveal the three-dimensional map of chromatin accessibility and simultaneously capture the genome conformation. Using SCA-seq, we simultaneously disclosed spatial regulation of chromatin accessibility (e.g. enhancer-promoter contacts), CpG island methylation and spatial insulating functions of the CCCTC-binding factor. We demonstrate that SCA-seq paves the way to explore epigenomic information in the three-dimensional space and extends our knowledge in next-generation genome architecture.

Background Magnetic resonance (MR) quantitative T1ρ imaging has been increasingly used to detect the early stages of osteoarthritis. The small volume and curved surface of articular cartilage necessitate imaging with high in-plane resolution and thin slices for accurate T1ρ measurement. Compared with 2D T1ρ mapping, 3D T1ρ mapping is free from artifacts caused by slice cross-talk and has a thinner slice thickness and full volume coverage. However, this technique needs to acquire multiple T1ρ-weighted images with different spin-lock times, which results in a very long scan duration. It is highly expected that the scan time can be reduced in 3D T1ρ mapping without compromising the T1ρ quantification accuracy and precision. Methods To accelerate the acquisition of 3D T1ρ mapping without compromising the T1ρ quantification accuracy and precision, a signal-compensated robust tensor principal component analysis method was proposed in this paper. The 3D T1ρ-weighted images compensated at different spin-lock times were decomposed as a low-rank high-order tensor plus a sparse component. Poisson-disk random undersampling patterns were applied to k-space data in the phase- and partition-encoding directions in both retrospective and prospective experiments. Five volunteers were involved in this study. The fully sampled k-space data acquired from 3 volunteers were retrospectively undersampled at R=5.2, 7.7, and 9.7, respectively. Reference values were obtained from the fully sampled data. Prospectively undersampled data for R=5 and R=7 were acquired from 2 volunteers. Bland-Altman analyses were used to assess the agreement between the accelerated and reference T1ρ measurements. The reconstruction performance was evaluated using the normalized root mean square error and the median of the normalized absolute deviation (MNAD) of the reconstructed T1ρ-weighted images and the corresponding T1ρ maps. Results T1ρ parameter maps were successfully estimated from T1ρ-weighted images reconstructed using the proposed method for all accelerations. The accelerated T1ρ measurements and reference values were in good agreement for R=5.2 (T1ρ: 40.4±1.4 ms), R=7.7 (T1ρ: 40.4±2.1 ms), and R=9.7 (T1ρ: 40.9±2.2 ms) in the Bland-Altman analyses. The T1ρ parameter maps reconstructed from the prospectively undersampled data also showed promising image quality using the proposed method. Conclusions The proposed method achieves the 3D T1ρ mapping of in vivo knee cartilage in eight minutes using a signal-compensated robust tensor principal component analysis method in image reconstruction.

The prolonged mei-yu/baiu system with anomalous precipitation in the year 2020 has swollen many rivers and lakes, caused flash flooding, urban flooding and landslides, and consistently wreaked havoc across large swathes of China, particularly in the Yangtze River basin. Significant precipitation and flooding anomalies have already been seen in magnitude and extension so far this year, which have been exerting much higher pressure on emergency responses in flood control and mitigation than in other years, even though a rainy season with multiple ongoing serious flood events in different provinces is not that uncommon in China. Instead of delving into the causes of the uniqueness of this year’s extreme precipitation-flooding situation, which certainly warrants in-depth exploration, in this article we provide a short view toward a more general hydrometeorological solution to this annual nationwide problem. A "glocal" (global to local) hydrometeorological solution for floods (GHS-F) is considered to be critical for better preparedness, mitigation, and management of different types of significant precipitation-caused flooding, which happen extensively almost every year in many countries such as China, India and the United States. Such a GHS-F model is necessary from both scientific and operational perspectives, with the strength in providing spatially consistent flood definitions and spatially distributed flood risk classification considering the heterogeneity in vulnerability and resilience across the entire domain. Priorities in the development of such a GHS-F are suggested, emphasizing the user’s requirements and needs according to practical experiences with various flood response agencies.

Two-dimensional (2D) fast spin echo (FSE) techniques play a central role in the clinical magnetic resonance imaging (MRI) of knee joints. Moreover, three-dimensional (3D) FSE provides high-isotropic-resolution magnetic resonance (MR) images of knee joints, but it has a reduced signal-to-noise ratio compared to 2D FSE. Deep-learning denoising methods are a promising approach for denoising MR images, but they are often trained using synthetic noise due to challenges in obtaining true noise distributions for MR images. In this study, inherent true noise information from 2-NEX acquisition was used to develop a deep-learning model based on residual learning of convolutional neural network (CNN), and this model was used to suppress the noise in 3D FSE MR images of knee joints. The proposed CNN used two-step residual learning over parallel transporting and residual blocks and was designed to comprehensively learn real noise features from 2-NEX training data. The results of an ablation study validated the network design. The new method achieved improved denoising performance of 3D FSE knee MR images compared with current state-of-the-art methods, based on the peak signal-to-noise ratio and structural similarity index measure. The improved image quality after denoising using the new method was verified by radiological evaluation. A deep CNN using the inherent spatial-varying noise information in 2-NEX acquisitions was developed. This method showed promise for clinical MRI assessments of the knee, and has potential applications for the assessment of other anatomical structures., 6 figures, abstract accepted by Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting

The majority of circular RNAs (circRNAs) spliced from coding genes contain open reading frames (ORFs) and thus, have protein coding potential. However, it remains unknown what regulates the biogenesis of these ORF-containing circRNAs, whether they are actually translated into proteins and what functions they play in specific physiological contexts. Here, we report that a large number of circRNAs are synthesized with increasing abundance when late pachytene spermatocytes develop into round and then elongating spermatids during murine spermatogenesis. For a subset of circRNAs, the back splicing appears to occur mostly at m6A-enriched sites, which are usually located around the start and stop codons in linear mRNAs. Consequently, approximately a half of these male germ cell circRNAs contain large ORFs with m6A-modified start codons in their junctions, features that have been recently shown to be associated with protein-coding potential. Hundreds of peptides encoded by the junction sequences of these circRNAs were detected using liquid chromatography coupled with mass spectrometry, suggesting that these circRNAs can indeed be translated into proteins in both developing (spermatocytes and spermatids) and mature (spermatozoa) male germ cells. The present study discovered not only a novel role of m6A in the biogenesis of coding circRNAs, but also a potential mechanism to ensure stable and long-lasting protein production in the absence of linear mRNAs, i.e., through production of circRNAs containing large ORFs and m6A-modified start codons in junction sequences.

Conventional approaches to studying 5mC marks in single cells or samples with picogram input DNA amounts usually suffer from low genome coverage due to DNA degradation. Many methods have been developed to optimize the library construction efficiency for bisulfite-treated DNA. However, most of these approaches ignored the amplification bias of bisulfite-treated DNA, which leads to shallow genome coverage. In this study, we developed the T7-assisted enzymatic methyl-sequencing method (TEAM-seq), which adopts enzymatic conversion to minimize DNA degradation and T7 polymerase-assisted unbiased amplification. We demonstrate that TEAM-seq delivered, to the best of our knowledge, the highest reported coverage(70% for 100pg, 35% for 20pg) of single cell genomes in whole-genome 5mC sequencing.

Here we describe a powerful method, BIND&MODIFY, for probing histone modifications and transcription factors at single molecular level. Our approach used the recombinant fused protein A-M.EcoGII, which tethers the methyltransferase M.EcoGII to the protein binding sites and locally labels the neighboring DNA regions via artificial methylations. This method could reveal ingle-molecule heterogenous histone modification status and CpG methylation at the same time, and could enable quantify the correlation between the distal elements. Further applications based on this method's concept could be applied to probe multiple protein binding events on the same single molecular DNA. The method proposed herein may soon become an essential tool for third-generation sequencing in the future.

Background: IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide. Circulating immune complexes form that are prone to deposition in the mesangium, where they trigger glomerular inflammation. A growing body of evidence suggests that dysregulated expression of microRNAs in IgAN may play a significant role in establishing the disease phenotype. Methods: We generated single miR-23b-3p(miR-23b) knockout mice using CRISPR-Cas9. Results: In humans, miR-23b levels are downregulated in kidney biopsies and sera of patients with IgAN, and serum miR-23b levels are negatively correlated with serum IgA1 levels. We show that miR-23b-/- mice develop an IgAN-like phenotype of mesangial IgA and C3 deposition associated with development of albuminuria, hypertension, an elevated serum creatinine, and dysregulated mucosal IgA synthesis. Dysregulation of IgA production is likely mediated by the loss of miR-23b mediated suppression of activation-induced cytidine deaminase in mucosal B cells. In addition, we show that loss of miR-23b increases the susceptibility of the kidney to progressive fibrosis through loss of regulation of expression of gremlin 2 and IgA accumulation through downregulation of the transferrin receptor. Conclusions: Our findings suggest an indispensable role for miR-23b in kidney disease, and in particular, IgAN. miR-23b may in the future offer a novel therapeutic target for the treatment of IgAN.

$T_{1\rho}$ mapping is a promising quantitative MRI technique for the non-invasive assessment of tissue properties. Learning-based approaches can map $T_{1\rho}$ from a reduced number of $T_{1\rho}$ weighted images, but requires significant amounts of high quality training data. Moreover, existing methods do not provide the confidence level of the $T_{1\rho}$ estimation. To address these problems, we proposed a self-supervised learning neural network that learns a $T_{1\rho}$ mapping using the relaxation constraint in the learning process. Epistemic uncertainty and aleatoric uncertainty are modelled for the $T_{1\rho}$ quantification network to provide a Bayesian confidence estimation of the $T_{1\rho}$ mapping. The uncertainty estimation can also regularize the model to prevent it from learning imperfect data. We conducted experiments on $T_{1\rho}$ data collected from 52 patients with non-alcoholic fatty liver disease. The results showed that our method outperformed the existing methods for $T_{1\rho}$ quantification of the liver using as few as two $T_{1\rho}$-weighted images. Our uncertainty estimation provided a feasible way of modelling the confidence of the self-supervised learning based $T_{1\rho}$ estimation, which is consistent with the reality in liver $T_{1\rho}$ imaging., Comment: Provisionally accepted by Physics in Medicine and Biology

The epigenetic modifications of histones are essential markers related to the development and pathogenesis of diseases, including human cancers. Mapping histone modification has emerged as the widely used tool for studying epigenetic regulation. However, existing approaches are limited by fragmentation and short-read sequencing represent the average chromatin status in samples and cannot provide information about the long-range chromatin states. We leveraged the advantage of long read sequencing to develop a method “BIND&MODIFY” for profiling the histone modification of individual DNA fibers. Our approach is based on the recombinant fused protein A-M.EcoGII, which tethers the methyltransferase M.EcoGII to the protein binding sites and locally labels the neighboring DNA regions through artificial methylations. We demonstrated that the aggregated BIND&MODIFY signal matches the bulk-level ChIP-seq and CUT&TAG, verify the single-molecule heterogenous histone modification status, and quantify the correlation between distal elements. This method could be an essential tool in future third-generation sequencing ages.

Purpose CEST is commonly used to probe the effects of chemical exchange. Although R1ρ asymmetry quantification has also been described as a promising option for detecting the effects of chemical exchanges, the existing acquisition approaches are highly susceptible to B1 RF and B0 field inhomogeneities. To address this problem, we report a new R1ρ asymmetry imaging approach, AC-iTIP, which is based on the previously reported techniques of irradiation with toggling inversion preparation (iTIP) and adiabatic continuous wave constant amplitude spin-lock RF pulses (ACCSL). We also derived the optimal spin-lock RF pulse B1 amplitude that yielded the greatest R1ρ asymmetry. Methods Bloch-McConnell simulations were used to verify the analytical formula derived for the optimal spin-lock RF pulse B1 amplitude. The performance of the AC-iTIP approach was compared to that of the iTIP approach based on hard RF pulses and the R1ρ -spectrum acquired using adiabatic RF pulses with the conventional fitting method. Comparisons were performed using Bloch-McConnell simulations, phantom, and in vivo experiments at 3.0T. Results The analytical prediction of the optimal B1 was validated. Compared to the other 2 approaches, the AC-iTIP approach was more robust under the influences of B1 RF and B0 field inhomogeneities. A linear relationship was observed between the measured R1ρ asymmetry and the metabolite concentration. Conclusion The AC-iTIP approach could probe the chemical exchange effect more robustly than the existing R1ρ asymmetry acquisition approaches. Therefore, AC-iTIP is a promising technique for metabolite imaging based on the chemical exchange effect.

It is valuable to achieve domain adaptation to transfer the learned knowledge from the source labeled CT dataset to the target unlabeled MR dataset for abdominal multi-organ segmentation. Meanwhile, it is highly desirable to avoid high annotation cost of target dataset and protect privacy of source dataset. Therefore, we propose an effective source-free unsupervised domain adaptation method for cross-modality abdominal multi-organ segmentation without accessing the source dataset. The process of the proposed framework includes two stages. At the first stage, the feature map statistics-guided model adaptation combining with entropy minimization is developed to help the top segmentation network to achieve reliable segmentations on the target images. The pseudo-labels outputted from the top segmentation network is used to guide the style compensation network to generate source-like images. The pseudo-labels outputted from the middle segmentation network is used to supervise the learning of the desired model (the bottom segmentation network). At the second stage, the circular learning and the pixel-adaptive mask refinement are used to further improve the performance of the desired model. With this approach, we achieve satisfactory performance on the abdominal multi-organ segmentation, outperforming recent state-of-the-art domain adaptation methods. The proposed approach can also be easily extended to the situation when there exists target annotation data. With only one labeled MR volume, the performance is improved to close to supervised learning. Furthermore, the proposed approach is proved to be effective in source-free unsupervised domain adaptation in reverse direction.

Background Although extrachromosomal DNA (ecDNA) has been intensively studied for several decades, the mechanisms underlying its tumorigenic effects have been revealed only recently. In most conventional sequencing studies, the high-throughput short-read sequencing largely ignores the epigenetic status of most ecDNA regions except for the junctional areas. Methods Here, we developed a method of sequencing enzyme-accessible chromatin in circular DNA (CCDA-seq) based on the use of methylase to label open chromatin without fragmentation and exonuclease to enrich ecDNA sequencing depth, followed by long-read nanopore sequencing. Results Using CCDA-seq, we observed significantly different patterns in nucleosome/regulator binding to ecDNA at a single-molecule resolution. Conclusions These results deepen the understanding of ecDNA regulatory mechanisms.

BACKGROUND AND PURPOSE: T1ρ imaging is a new quantitative MR imaging pulse sequence with the potential to discriminate between malignant and benign tissue. In this study, we evaluated the capability of T1ρ imaging to characterize tissue by applying T1ρ imaging to malignant and benign tissue in the nasopharynx and to normal tissue in the head and neck. MATERIALS AND METHODS: Participants with undifferentiated nasopharyngeal carcinoma and benign hyperplasia of the nasopharynx prospectively underwent T1ρ imaging. T1ρ measurements obtained from the histogram analysis for nasopharyngeal carcinoma in 43 participants were compared with those for benign hyperplasia and for normal tissue (brain, muscle, and parotid glands) in 41 participants using the Mann-Whitney U test. The area under the curve of significant T1ρ measurements was calculated and compared using receiver operating characteristic analysis and the Delong test, respectively. A P

Liver segmentation on images acquired using computed tomography (CT) and magnetic resonance imaging (MRI) plays an important role in clinical management of liver diseases. Compared to MRI, CT images of liver are more abundant and readily available. However, MRI can provide richer quantitative information of the liver compared to CT. Thus, it is desirable to achieve unsupervised domain adaptation for transferring the learned knowledge from the source domain containing labeled CT images to the target domain containing unlabeled MR images. In this work, we report a novel unsupervised domain adaptation framework for cross-modality liver segmentation via joint adversarial learning and self-learning. We propose joint semantic-aware and shape-entropy-aware adversarial learning with post-situ identification manner to implicitly align the distribution of task-related features extracted from the target domain with those from the source domain. In proposed framework, a network is trained with the above two adversarial losses in an unsupervised manner, and then a mean completer of pseudo-label generation is employed to produce pseudo-labels to train the next network (desired model). Additionally, semantic-aware adversarial learning and two self-learning methods, including pixel-adaptive mask refinement and student-to-partner learning, are proposed to train the desired model. To improve the robustness of the desired model, a low-signal augmentation function is proposed to transform MRI images as the input of the desired model to handle hard samples. Using the public data sets, our experiments demonstrated the proposed unsupervised domain adaptation framework reached four supervised learning methods with a Dice score 0.912 plus or minus 0.037 (mean plus or minus standard deviation).

BACKGROUND: Magnetic resonance (MR) quantitative T(1ρ) imaging has been increasingly used to detect the early stages of osteoarthritis. The small volume and curved surface of articular cartilage necessitate imaging with high in-plane resolution and thin slices for accurate T(1ρ) measurement. Compared with 2D T(1ρ) mapping, 3D T(1ρ) mapping is free from artifacts caused by slice cross-talk and has a thinner slice thickness and full volume coverage. However, this technique needs to acquire multiple T(1ρ)-weighted images with different spin-lock times, which results in a very long scan duration. It is highly expected that the scan time can be reduced in 3D T(1ρ) mapping without compromising the T(1ρ) quantification accuracy and precision. METHODS: To accelerate the acquisition of 3D T(1ρ) mapping without compromising the T(1ρ) quantification accuracy and precision, a signal-compensated robust tensor principal component analysis method was proposed in this paper. The 3D T(1ρ)-weighted images compensated at different spin-lock times were decomposed as a low-rank high-order tensor plus a sparse component. Poisson-disk random undersampling patterns were applied to k-space data in the phase- and partition-encoding directions in both retrospective and prospective experiments. Five volunteers were involved in this study. The fully sampled k-space data acquired from 3 volunteers were retrospectively undersampled at R=5.2, 7.7, and 9.7, respectively. Reference values were obtained from the fully sampled data. Prospectively undersampled data for R=5 and R=7 were acquired from 2 volunteers. Bland-Altman analyses were used to assess the agreement between the accelerated and reference T(1ρ) measurements. The reconstruction performance was evaluated using the normalized root mean square error and the median of the normalized absolute deviation (MNAD) of the reconstructed T(1ρ)-weighted images and the corresponding T(1ρ) maps. RESULTS: T(1ρ) parameter maps were successfully estimated from T(1ρ)-weighted images reconstructed using the proposed method for all accelerations. The accelerated T(1ρ) measurements and reference values were in good agreement for R=5.2 (T(1ρ): 40.4±1.4 ms), R=7.7 (T(1ρ): 40.4±2.1 ms), and R=9.7 (T(1ρ): 40.9±2.2 ms) in the Bland-Altman analyses. The T(1ρ) parameter maps reconstructed from the prospectively undersampled data also showed promising image quality using the proposed method. CONCLUSIONS: The proposed method achieves the 3D T(1ρ) mapping of in vivo knee cartilage in eight minutes using a signal-compensated robust tensor principal component analysis method in image reconstruction.

Background Intravoxel incoherent motion (IVIM) tissue parameters depend on the threshold b-value. Purpose To explore how threshold b-value impacts PF ( f), Dslow ( D), and Dfast ( D*) values and their performance for liver fibrosis detection. Material and Methods Fifteen healthy volunteers and 33 hepatitis B patients were included. With a 1.5-T magnetic resonance (MR) scanner and respiration gating, IVIM data were acquired with ten b-values of 10, 20, 40, 60, 80, 100, 150, 200, 400, and 800 s/mm2. Signal measurement was performed on the right liver. Segmented-unconstrained analysis was used to compute IVIM parameters and six threshold b-values in the range of 40–200 s/mm2 were compared. PF, Dslow, and Dfast values were placed along the x-axis, y-axis, and z-axis, and a plane was defined to separate volunteers from patients. Results Higher threshold b-values were associated with higher PF measurement; while lower threshold b-values led to higher Dslow and Dfast measurements. The dependence of PF, Dslow, and Dfast on threshold b-value differed between healthy livers and fibrotic livers; with the healthy livers showing a higher dependence. Threshold b-value = 60 s/mm2 showed the largest mean distance between healthy liver datapoints vs. fibrotic liver datapoints, and a classification and regression tree showed that a combination of PF (PF slow (Dslow –3 mm2/s), and Dfast (Dfast –3 mm2/s) differentiated healthy individuals and all individual fibrotic livers with an area under the curve of logistic regression (AUC) of 1. Conclusion For segmented-unconstrained analysis, the selection of threshold b-value = 60 s/mm2 improves IVIM differentiation between healthy livers and fibrotic livers.

Liver T1rho has been proposed as an imaging biomarker for liver fibrosis (1-5). In the recent study of Xie et al. (6,7), 18 healthy subjects, 18 patients with fatty liver, and 18 patients with liver fibrosis had T1rho MR imaging performed. The diagnosis of liver fibrosis was based on serologic evidence of hepatitis B or C virus infection and liver stiffness criteria by ultrasonic elastography. Mean liver T1rho values in fibrotic group (52.6±6.8 ms) were significantly higher than those of healthy subjects (44.9±2.8 ms, P et al. ’s paper) (7). Since there was no histologic diagnosis of liver fibrosis for the patients, it is possible that these four cases actually did not have fibrosis; however, it is more likely that these patients did have liver fibrosis, but their liver T1rho was not measured higher than healthy subjects’ liver.

The majority of circular RNAs (circRNAs) spliced from coding genes contain open reading frames (ORFs) and thus, have protein coding potential. However, it remains unknown what regulates the biogenesis of these ORF-containing circRNAs, whether they are actually translated into proteins and what functions they play in specific physiological contexts. Here, we report that a large number of circRNAs are synthesized with increasing abundance when late pachytene spermatocytes develop into round and then elongating spermatids during murine spermatogenesis. For a subset of circRNAs, the back splicing appears to occur mostly at m(6)A-enriched sites, which are usually located around the start and stop codons in linear mRNAs. Consequently, approximately a half of these male germ cell circRNAs contain large ORFs with m(6)A-modified start codons in their junctions, features that have been recently shown to be associated with protein-coding potential. Hundreds of peptides encoded by the junction sequences of these circRNAs were detected using liquid chromatography coupled with mass spectrometry, suggesting that these circRNAs can indeed be translated into proteins in both developing (spermatocytes and spermatids) and mature (spermatozoa) male germ cells. The present study discovered not only a novel role of m(6)A in the biogenesis of coding circRNAs, but also a potential mechanism to ensure stable and long-lasting protein production in the absence of linear mRNAs, i.e., through production of circRNAs containing large ORFs and m(6)A-modified start codons in junction sequences.

PURPOSE: CEST is commonly used to probe the effects of chemical exchange. Although R1rho asymmetry quantification has also been described as a promising option for detecting the effects of chemical exchanges, the existing acquisition approaches are highly susceptible to B1 RF and B0 field inhomogeneities. To address this problem, we report a new R1rho asymmetry imaging approach, AC-iTIP, which is based on the previously reported techniques of irradiation with toggling inversion preparation (iTIP) and adiabatic continuous wave constant amplitude spin-lock RF pulses (ACCSL). We also derived the optimal spin-lock RF pulse B1 amplitude that yielded the greatest R1rho asymmetry. METHODS: Bloch-McConnell simulations were used to verify the analytical formula derived for the optimal spin-lock RF pulse B1 amplitude. The performance of the AC-iTIP approach was compared to that of the iTIP approach based on hard RF pulses and the R1rho-spectrum acquired using adiabatic RF pulses with the conventional fitting method. Comparisons were performed using Bloch-McConnell simulations, phantom, and in vivo experiments at 3.0T. RESULTS: The analytical prediction of the optimal B1 was validated. Compared to the other two approaches, the AC-iTIP approach was more robust under the influences of B1 RF and B0 field inhomogeneities. A linear relationship was observed between the measured R1rho asymmetry and the metabolite concentration. CONCLUSION: The AC-iTIP approach could probe the chemical exchange effect more robustly than the existing R1rho asymmetry acquisition approaches. Therefore, AC-iTIP is a promising technique for metabolite imaging based on the chemical exchange effect.

Purpose To develop and clinically evaluate a pediatric knee magnetic resonance imaging (MRI) technique based on volumetric fast spin-echo (3DFSE) and compare its diagnostic performance, image quality, and imaging time to that of a conventional 2D protocol. Materials and Methods A 3DFSE sequence was modified and combined with a compressed sensing-based reconstruction resolving multiple image contrasts, a technique termed T2 Shuffling (T2Sh). With Institutional Review Board (IRB) approval, 28 consecutive children referred for 3T knee MRI prospectively underwent a standard clinical knee protocol followed by T2Sh. T2Sh performance was assessed by two readers blinded to diagnostic reports. Interpretive discrepancies were resolved by medical record chart review and consensus between the readers and an orthopedic surgeon. Image quality was evaluated by rating anatomic delineation, with 95% confidence interval. A Wilcoxon rank-sum test assessed the null hypothesis that T2Sh structure delineation compared to conventional 2D is unchanged. Intraclass correlation coefficients were calculated for interobserver agreement. Imaging time of the conventional protocol and T2Sh was compared. Results There was 81% and 87% concordance between T2Sh reports and diagnostic reports, respectively, for each reader. Upon consensus review, T2Sh had 93% sensitivity and 100% specificity compared to clinical reports for detection of clinically relevant findings. The 95% confidence interval of diagnostic or better rating was 95–100%, with 34–80% interobserver agreement. There was no significant difference in structure delineation between T2Sh and 2D, except for the retinaculum (P < 0.05), where 2D was preferred. Typical imaging time for T2Sh and the conventional exam was 7 and 13 minutes, respectively. Conclusion A single-sequence pediatric knee exam is feasible with T2Sh, providing multiplanar, reformattable 4D images. Level of Evidence 2 J. Magn. Reson. Imaging 2016;00:000–000.

Background: To explore black blood T1rho (T1ρ) liver imaging and investigate the earliest stage when biliary duct ligation (BDL) induced liver fibrosis can be diagnosed. Methods: MR was performed at 3 Tesla. A T1ρ prepared 2D fast spin echo (FSE) sequence with acquisition of four spin lock times (TSLs: 1, 10, 30, and 50 msec) and spin-lock frequency of 500 Hz was applied. Inherent black blood effect of FSE and double inversion recovery (DIR) achieved blood signal suppression, and 3 axial sections per liver were obtained. Male Sprague-Dawley rats were scanned at baseline (n=32), and on day-3 (n=13), day-5 (n=11), day-7 (n=10), day-10 (n=4) respectively after BDL. Hematoxylin-eosin (HE) and picrosirius red staining liver histology was obtained at these time points. Results: The physiological liver parenchyma T1ρ was 38.38±1.53 msec (range, 36.05–41.53 msec). Liver T1ρ value elevated progressively after BDL. On day-10 after BDL all experimental animals can be separated from normal liver based on T1ρ measurement with lowest value being 42.82 msec. Day-7 and day-10 liver resembled METAVIR stage-F1/F2 fibrosis, and fibrous area counted for 0.22%±0.13% and 0.38%±0.44% of liver parenchyma area, respectively. Conclusions: This study provides the first proof-of-principle that T1ρ might diagnose early stage liver fibrosis.

Background: Liver fibrosis is a key feature in most chronic liver diseases. T1rho magnetic resonance imaging is a potentially important technique for noninvasive diagnosis, severity grading, and therapy monitoring of liver fibrosis. However, it remains challenging to perform robust T1rho quantification of liver on human subjects. One major reason is that the presence of rich blood signal in liver can cause artificially high T1rho measurement and makes T1rho quantification susceptible to motion. Methods: A pulse sequence based on single shot fast/turbo spin echo (SSFSE/SSTSE) acquisition, with theoretical analysis and simulation based on the extended phase graph (EPG) algorithm, was presented for breath-hold single slice quantitative T1rho imaging of liver with suppression of blood signal. The pulse sequence was evaluated in human subjects at 3.0 T with 500 Hz spinlock frequency and time-of-spinlock (TSL) 0, 10, 30 and 50 ms. Results: Human scan demonstrated that the entire T1rho data sets with four spinlock time can be acquired within a single breath-hold of 10 seconds with black blood effect. T1rho quantification with suppression of blood signal results in significantly reduced T1rho value of liver compared to the results without blood suppression. Conclusions: A signal-to-noise ratio (SNR) efficient pulse sequence was reported for T1rho quantification of liver. The black blood effect, together with a short breath-hold, mitigates the risk of quantification errors as would occur in the conventional methods.

Purpose A new acquisition and reconstruction method called T2 Shuffling is presented for volumetric fast spin-echo (three-dimensional [3D] FSE) imaging. T2 Shuffling reduces blurring and recovers many images at multiple T2 contrasts from a single acquisition at clinically feasible scan times (6-7 min). Theory and methods The parallel imaging forward model is modified to account for temporal signal relaxation during the echo train. Scan efficiency is improved by acquiring data during the transient signal decay and by increasing echo train lengths without loss in signal-to-noise ratio (SNR). By (1) randomly shuffling the phase encode view ordering, (2) constraining the temporal signal evolution to a low-dimensional subspace, and (3) promoting spatio-temporal correlations through locally low rank regularization, a time series of virtual echo time images is recovered from a single scan. A convex formulation is presented that is robust to partial voluming and radiofrequency field inhomogeneity. Results Retrospective undersampling and in vivo scans confirm the increase in sharpness afforded by T2 Shuffling. Multiple image contrasts are recovered and used to highlight pathology in pediatric patients. A proof-of-principle method is integrated into a clinical musculoskeletal imaging workflow. Conclusion The proposed T2 Shuffling method improves the diagnostic utility of 3D FSE by reducing blurring and producing multiple image contrasts from a single scan. Magn Reson Med 77:180-195, 2017. © 2016 Wiley Periodicals, Inc.

Purpose To evaluate the utility of amide proton transfer (APT) imaging in the characterization of head and neck tumors. Materials and Methods This retrospective study of APT imaging included 117 patients with 70 nasopharyngeal undifferentiated carcinomas (NUCs), 26 squamous cell carcinomas (SCCs), eight non-Hodgkin lymphomas (NHLs), and 13 benign salivary gland tumors (BSGTs). Normal tissues were examined in 25 patients. The APT means of malignant tumors, normal tissues, and benign tumors were calculated and compared with the Student t test and analysis of variance. The added value of the mean APT to the mean apparent diffusion coefficient (ADC) for differentiating malignant and benign tumors was evaluated by using receiver operating characteristic analysis and integrated discrimination index. Results The mean APT of malignant tumors (2.40% ± 0.97 [standard deviation]) was significantly higher than that of brain tissue (1.13% ± 0.43), muscle tissue (0.23% ± 0.73), and benign tumors (1.32% ± 1.20) (P < .001). There were no differences between malignant groups (NUC, 2.37% ± 0.90; SCC, 2.41% ± 1.16; NHL, 2.65% ± 0.89; P = .45 to P = .86). The mean ADC of malignant tumors ([0.85 ± 0.17] × 10-3 mm2/sec) was significantly lower than that of benign tumors ([1.46 ± 0.47] × 10-3 mm2/sec) (P = .001). Adding APT to ADC increased the area under the curve from 0.87 to 0.96, with an integrated discrimination index of 7.6% (P = .13). Conclusion These preliminary data demonstrate differences in amide proton transfer (APT) mean of malignant tumors, normal tissues, and benign tumors, although APT mean could not be used to differentiate between malignant tumor groups. APT imaging has the potential to be of added value to apparent diffusion coefficient in differentiating malignant from benign tumors.

To understand women's and men's physiological ranges of liver T1rho relaxation time measured with a single breathhold black blood sequence, this healthy volunteer study was conducted in 62 women (mean age, 38.9 y; range, 18-75 y) and 34 men (mean age, 44.7 y; range, 24-80 y). Approval from the institutional ethics committee was obtained. Magnetic resonance imaging was performed with a 3.0T scanner with six spin-lock times of 0, 10, 20, 25, 35, and 50 ms and a single breathhold of 12 s per slice acquisition. Six slices were acquired for each examination. The results demonstrated that the female liver T1rho value ranged between 35.07 and 51.97 ms and showed an age-dependent decrease, with younger women having a higher measurement. The male liver T1rho value ranged between 34.94 and 43.39 ms, with no evidential age dependence. Postmenopausal women had similar liver T1rho values as men. For women, there was a trend that the liver T1rho value could be 4% to 5% lower during the menstrual phase than during the nonmenstrual phase. For both women and men, no evidential association was seen between body mass index and liver T1rho.

PurposeUsing a single breathhold black blood sequence, the current study aims to understand the physiological ranges of liver T1rho relaxation for women and men.Materials and MethodsThis volunteer study was conducted with institutional ethics committee approval, and included 62 females (age mean: 38.9 years; range: 18-75 years) and 34 males (age mean: 44.7 years, range: 24-80 years). MRI was conducted with a 3.0 T scanner, with six spin-lock times of 0, 10, 20, 25, 35, 50msec and a single breathhold of 12 seconds. Six slices were acquired for each examination.ResultsFemale liver T1rho value ranged between 35.07 to 51.97ms, showed an age-dependent decrease with younger women had a higher measurement. Male Liver T1rho values ranged between 34.94 to 43.39 ms, and there was no evidential age-dependence. For females, there was a trend that liver T1rho value could be 4%-5% lower during menstrual phase than nonmenstrual phase. For both females and males, no evidential association was seen between body mass index and liver T1rho.ConclusionLiver T1rho physiological value for males have relatively narrow distribution, while physiological value for females have wider distribution, and decreases with age.Key points1. Liver T1rho shows an age-dependency in women, with young women showing higher measurement. This age-dependency of liver T1rho measurement is not evidential in men. Post-menopausal women have similar liver T1rho value as men.2. Women at menstrual phase may have slight lower liver T1rho measurement.3. No association was noted between body mass index and liver T1rho4. When blood signal suppression sequence is used, in a population of 62 healthy women and 34 healthy men, the highest measured liver T1rho was 52 msec for young women, 44.7 msec for post-menopausal women, and 43.4 msec for men.

PurposeTo explore how the selection of threshold b-value impacts Intravoxel Incoherent Motion (IVIM) diffusion parameters of PF (f), Dslow (D),and Dfast (D*) values and their performance for liver fibrosis detection.Materials and MethodsFifteen healthy volunteers and 33 hepatitis-b patients were included. With a 1.5 T MR scanner and respiration gating, IVIM data was acquired with 10 b-values of 10,20,40,60,80,100,150, 200, 400, and 800 s/mm2. Signal measurement was performed on right liver. Segmented-unconstrained analysis was used to compute IVIM parameters, and six threshold b-values between 40 and 200 s/mm2 were compared. PF, Dslow, and Dfast values were placed along the x-axis, y-axis, and z-axis, and a plane was defined to separate volunteers from patients.ResultsHigher threshold b-values were associated with higher PF measurement; while lower threshold b-values led to higher Dslow and Dfast measurements. The dependence of PF, Dslow, and Dfast on threshold b-value differed between healthy livers and fibrotic livers; with the healthy livers showing a higher dependence. Threshold b-value=60 s/mm2 showed the largest mean distance between healthy liver datapoints vs. fibrotic liver datapoints in 3-dimensional space.ConclusionFor segmented-unconstrained analysis, the selection of threshold b-value=60 s/mm2 improves IVIM diffusion differentiation between healthy livers and fibrotic livers.

This study investigated a combined use of intravoxel incoherent motion (IVIM) parameters, Dslow ( D), PF ( f), and Dfast ( D*), for liver fibrosis evaluation. Sixteen healthy volunteers (F0) and 33 hepatitis-b patients (stage F1 = 15, stage F2-4 = 18) were included. With a 1.5 T MR scanner and respiration gating, IVIM diffusion-weighted imaging was acquired using a single-shot echo-planar imaging sequence with 10 b values of 10, 20, 40, 60, 80, 100, 150, 200, 400, and 800 s/mm2. Signal measurement was performed on right liver parenchyma. With a three-dimensional tool, Dslow, PF, and Dfast values were placed along the x axis, y axis, and z axis, and a plane was defined to separate healthy volunteers from patients. The three-dimensional tool demonstrated that healthy volunteers and all patients with liver fibrosis could be separated. Classification and regression tree showed that a combination of PF (PF < 12.55%), Dslow (Dslow < 1.152 × 10-3 mm2/s), and Dfast (Dfast < 13.36 × 10-3 mm2/s) could differentiate healthy subjects and all fibrotic livers (F1-4) with an area under the curve of logistic regression (AUC) of 0.986. The AUC for differentiation of healthy livers versus F2-4 livers was 1. PF offered the best diagnostic value, followed by Dslow; however, all three parameters of PF, Dslow, and Dfast contributed to liver fibrosis detection.

Background and purposeCerebral edema associated with brain tumors is an important source of morbidity. Its type depends largely on the capillary ultra-structures of the histopathologic subtype of underlying brain tumor. The purpose of our study was to differentiate vasogenic edema associated with brain metastases and infiltrative edema related to diffuse gliomas using quantitative 3D T1 rho (T1ρ) imaging.Materials and methodsPreoperative MR examination including whole brain 3D T1ρ imaging was performed in 23 patients with newly diagnosed brain tumors (9 with metastasis, 8 with lower grade glioma, LGG, 6 with glioblastoma, GBM). Mean T1ρ values were measured in regions of peritumoral non-enhancing T2 signal hyperintensity, excluding both enhancing and necrotic or cystic component, and normal-appearing white matter.ResultsMean T1ρ values were significantly elevated in the vasogenic edema surrounding intracranial metastases when compared to the infiltrative edema associated with either LGG or GBM (p=0.02 and

This study investigated a combined use of IVIM parameters Dslow (D), PF (f) and Dfast (D*) for liver fibrosis evaluation. 16 healthy volunteers (F0) and 33 hepatitis-b patients (stage F1= 15, stage F2-4 = 18) were included. With a 1.5-T MR scanner and respiration-gating, IVIM diffusion weighted imaging was acquired using a single-shot echo-planar imaging sequence with ten b-values of 10, 20, 40, 60, 80, 100, 150, 200, 400, and 800 s/mm2. Signal measurement was performed on right liver parenchyma. With a 3-dimensional tool, Dslow, PF, and Dfast values were placed along the x-axis, y-axis, and z-axis, and a plane was defined to separate healthy volunteers from patients. 3-dimensional tool demonstrated healthy volunteers and all patients with liver fibrosis could be separated. Classification and Regression Tree showed a combination of PF (PF < 12.55%), Dslow (Dslow < 1.152 ×10−3 mm2/s) and Dfast (Dfast −3 mm2/s) could differentiate healthy subjects and all fibrotic livers (F1-F4) with an area under the curve of logistic regression (AUC) of 0.986. The AUC for differentiation of healthy livers vs. F2-4 livers was 1. PF offered the best diagnostic value, followed by Dslow; however, all three parameters of PF, Dslow, and Dfast contributed to liver fibrosis detection.

A comprehensive literature review was performed on liver intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) technique and its applications. Heterogeneous data have been reported. IVIM parameters are magnetic field strength dependent to a mild extent. A lower Dslow (D) value at 3 T than at 1.5 T and higher perfusion fraction (PF) value at 3 T than at 1.5 T were noted. An increased number of b values are associated with increased IVIM parameter measurement accuracy. With the current status of art, IVIM technique is not yet capable of detecting early stage liver fibrosis and diagnosing liver fibrosis grades, nor can it differentiate liver tumors. Though IVIM parameters show promise for tumor treatment monitoring, till now how PF and Dfast (D*) add diagnostic value to Dslow or apparent diffusion coefficient (ADC) remains unclear. This paper shows the state-of-art IVIM MR technique is still not able to offer reliable measurement for liver. More works on the measurement robustness are warranted as they are essential to justify follow-up clinical studies on patients.

Osteoarthritis (OA) IS A degenerative joint disease that affects articular cartilage, subchondral bone, and other tissues predominantly in the hand, knee, and hip (1). Approximately 20 million people in the United States live with OA, and this number is expected to increase due to an aging population and increasing rates of obesity (2,3). Conventional MRI provides a noninvasive assessment of soft-tissue morphology and allows for detection of cartilage defects that are characteristic of OA (4). However, these morphological changes are preceded by degradation of the cartilage ultrastructure, including breakdown of the collagen matrix and loss of supporting proteoglycans (5). Detection of early osteoarthritic changes requires more advanced MR sequences that are sensitive to biochemical changes in cartilage (6,7). Spin-spin or T2 relaxation time mapping is one such technique that has successfully been used to track early osteoarthritic changes in patients (8–12). The biochemical information captured by T2 relaxation is still under investigation. In articular cartilage, T2 relaxation times increase with increases in free water content and mobility (13). A healthy, highly structured collagen matrix immobilizes water and keeps it bound to supporting macromolecules. This system breaks down with early OA, and T2 relaxation time is thus believed to provide an indirect assessment of collagen content and orientation. Other evidence suggests that T2 relaxation times increase with decreases in proteoglycan content within the matrix (14). Most importantly for OA research, T2 relaxation times generally increase with biochemical degradation of cartilage. This phenomenon makes T2 relaxation time mapping an effective tool for tracking changes over time within and between patient and control populations. For this reason it has been selected for use in large-scale clinical studies such as the Osteoarthritis Initiative (OAI) (15). Compared with other quantitative imaging techniques, T2 relaxation time mapping presents its own advantages and disadvantages. The primary advantage of T2 relaxation time mapping is that it can be performed without the use of intravenous contrast agents or ionizing radiation, unlike other quantitative imaging sequences such as dGEMRIC (delayed gadolinium-enhanced MRI of cartilage) and CT (computed tomography) arthrography. The primary disadvantage associated with T2 relaxation time mapping is its susceptibility to the magic angle effect, in which T2 values may be artificially elevated in certain regions based upon the orientation of cartilage in relation to the main magnetic field (16). Regions susceptible to this effect, particularly along curved surfaces such as the femoral head and condyles, are assumed to have some influence from magic angle. However, the magic angle effect should not impact results tracking changes over time or between study populations, so long as subjects are positioned consistently within the magnet. While T2 relaxation time is meant to be an objective measure, several factors have been shown to influence T2 quantitation. Significant differences in T2 quantitation have been observed based on the selection of MR scanner (17), radiofrequency coil (18), and postprocessing fitting method (19). An additional potential source of variation in T2 quantitation is the MR pulse sequence used (20). As with all other external factors affecting T2 quantitation, the impact of pulse sequence selection must be understood for researchers and clinicians to interpret and compare results between studies. Several MR pulse sequences have been developed for T2 relaxation time quantitation. The most fundamental of these are stimulated echo acquisition mode (STEAM) spectroscopy (21) and single echo spin echo (SE). These sequences suffer from low signal-to-noise ratio (SNR) and long scan times, respectively, that prevent their use for clinical examination of cartilage ultrastructure. More advanced 2D approaches overcome these drawbacks and include multi-echo SE (MESE) and fast SE (FSE). 3D approaches are also currently available for T2 relaxation time mapping. A magnetization-prepared angle-modulated partitioned k-space spoiled gradient echo sequence (3D-MAPSS) uses a nonselective T2 magnetization preparation followed by a 3D spoiled gradient echo (SPGR) acquisition (22). Additionally, a 3D FSE sequence with variable refocusing flip angle schedules (3D vfl-FSE) uses a T2 magnetization preparation followed by a pseudo steady-state 3D FSE acquisition (23). In addition to sequences that rely on acquiring multiple echo times to fit T2 relaxation to an exponential decay, a 3D double-echo steady state (DESS) sequence has been modified for T2 relaxation time quantitation, and is known as qDESS (24,25). Analysis of the variation in T2 quantitation between all these sequences can provide a stronger basis for interpreting quantitative outcomes and can eventually allow for comparison of absolute and relative relaxation time differences across studies that use different pulse sequences for T2 relaxation time mapping. To date, variation in quantitative outcome from T2 relaxation time mapping sequences has received limited attention, but previous reports suggest this variation is not trivial. The selection of a multi-slice versus a single-slice sequence has been shown to impact cartilage T2 relaxation times by an average of 6–9% (26). Additionally, T2 relaxation times have been shown to vary up to 42% between MESE and FSE sequences in agar phantoms (27). In vivo studies of cartilage have been limited to analysis of patellar cartilage in the axial plane, and differences of up to 48% between FSE and SE sequences have been reported (28,29). More recently, an average difference of 15% has been reported between 3D-MAPSS and SE within patellar cartilage (20). An analysis of sequence-dependent variation within femoral and tibial cartilage is lacking. Previous reports use axial imaging and are therefore limited to analysis of patellar cartilage. Additionally, studies have compared only a few pulse sequences at a time, so a singular analysis of many sequences is lacking. The aim of the present study is to assess the differences in T2 relaxation time quantitation between an array of MR pulse sequences in agar phantoms and in vivo patellar, femoral, and tibial articular cartilage and to compare these results with a SE reference standard.

Purpose To optimize acquisition parameters for three-dimensional fast spin-echo (3D FSE) imaging of the knee.