An intrinsically disordered region-mediated confinement state contributes to the dynamics and function of transcription factors.

Transcription factors (TFs) regulate gene expression by binding to specific consensus motifs within the local chromatin context. The mechanisms by which TFs navigate the nuclear environment as they search for binding sites remain unclear. Here, we used single-molecule tracking and machine-learning-based classification to directly measure the nuclear mobility of the glucocorticoid receptor (GR) in live cells. We revealed two distinct and dynamic low-mobility populations. One accounts for specific binding to chromatin, while the other represents a confinement state that requires an intrinsically disordered region (IDR), implicated in liquid-liquid condensate subdomains. Further analysis showed that the dwell times of both subpopulations follow a power-law distribution, consistent with a broad distribution of affinities on the GR cistrome and interactome. Together, our data link IDRs with a confinement state that is functionally distinct from specific chromatin binding and modulates the transcriptional output by increasing the local concentration of TFs at specific sites.

Performance of MR learned pulse sequences for 3D bi-exponential, stretched-exponential, and mono-exponential T2 and T1ρ mapping of knee cartilage.

PURPOSE: To compare the performance of a learned magnetization-prepared gradient echo (L-MPGRE) sequence against a commonly used sequence for 3D T2 and T1ρ mapping of the knee joint, the magnetization-prepared angle-modulated partitioned k-space spoiled gradient echo snapshots (MAPSS), on bi-exponential (BE), stretched-exponential (SE), and mono-exponential (ME) relaxation models. METHODS: We used a combined differentiable and non-differentiable optimization to learn pulse sequence structure and its parameters for 3D T2 and T1ρ mapping of the knee joint using ME, SE, and BE models. The learned pulse sequence framework was used to improve quantitative accuracy and SNR and to reduce filtering effects. We compare the measured multi-compartment values between the two sequences (n = 8), and their repeatability (n = 4) in healthy volunteers (n = 12 total). RESULTS: The voxel-wise median absolute percentage difference (MAPD) between the T2 and T1ρ maps obtained with each sequence was 18.6% and 19.9%, respectively. The T2 and T1ρ repeatability tests showed a MAPD of 18.5% and 19.1% for MAPSS, and 16.8% and 15.5% for L-MPGRE. Bland-Altman region of interest (ROI)-wise analysis shows that bias is small, close to -1.5%, and the coefficient of variation is around 5.5% when comparing ROIs from both sequences. CONCLUSION: The L-MPGRE sequences can be used as a replacement for MAPSS for T2 and T1ρ mapping in the knee cartilage with advantages, achieving similar accuracy and 15% better repeatability in only half of its scan time.

Evidence for biexponential glutamate T2 relaxation in human visual cortex at 3T: A functional MRS study.

Functional magnetic resonance spectroscopy (fMRS) measures dynamic changes in metabolite concentration in response to neural stimulation. The biophysical basis of these changes remains unclear. One hypothesis suggests that an increase or decrease in the glutamate signal detected by fMRS could be due to neurotransmitter movements between cellular compartments with different T2 relaxation times. Previous studies reporting glutamate (Glu) T2 values have generally sampled at echo times (TEs) within the range of 30-450 ms, which is not adequate to observe a component with short T2 (<20 ms). Here, we acquire MRS measurements for Glu, (t) total creatine (tCr) and total N-acetylaspartate (tNAA) from the visual cortex in 14 healthy participants at a range of TE values between 9.3-280 ms during short blocks (64 s) of flickering checkerboards and rest to examine both the short- and long-T2 components of the curve. We fit monoexponential and biexponential Glu, tCr and tNAA T2 relaxation curves for rest and stimulation and use Akaike information criterion to assess best model fit. We also include power calculations for detection of a 2% shift of Glu between compartments for each TE. Using pooled data over all participants at rest, we observed a short Glu T2-component with T2 = 10 ms and volume fraction of 0.35, a short tCr T2-component with T2 = 26 ms and volume fraction of 0.25 and a short tNAA T2-component around 15 ms with volume fraction of 0.34. No statistically significant change in Glu, tCr and tNAA signal during stimulation was detected at any TE. The volume fractions of short-T2 component between rest and active conditions were not statistically different. This study provides evidence for a short T2-component for Glu, tCr and tNAA but no evidence to support the hypothesis of task-related changes in glutamate distribution between short and long T2 compartments.

Bridging the gap between two-stage and joint models: The case of tumor growth inhibition and overall survival models.

Many clinical trials generate both longitudinal biomarker and time-to-event data. We might be interested in their relationship, as in the case of tumor size and overall survival in oncology drug development. Many well-established methods exist for analyzing such data either sequentially (two-stage models) or simultaneously (joint models). Two-stage modeling (2stgM) has been challenged (i) for not acknowledging that biomarkers are endogenous covariable to the survival submodel and (ii) for not propagating the uncertainty of the longitudinal biomarker submodel to the survival submodel. On the other hand, joint modeling (JM), which properly circumvents both problems, has been criticized for being time-consuming, and difficult to use in practice. In this paper, we explore a third approach, referred to as a novel two-stage modeling (N2stgM). This strategy reduces the model complexity without compromising the parameter estimate accuracy. The three approaches (2stgM, JM, and N2stgM) are formulated, and a Bayesian framework is considered for their implementation. Both real and simulated data were used to analyze the performance of such approaches. In all scenarios, our proposal estimated the parameters approximately as JM but without being computationally expensive, while 2stgM produced biased results.

Lung T2 * mapping using 3D ultrashort TE with tight intervals δTE.

PURPOSE: To develop 3D ultrashort-TE (UTE) sequences with tight TE intervals (δTE), allowing for accurate T 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping of lungs under free breathing. METHODS: We have implemented a four-echo UTE sequence with δTE (< 0.5 ms). A Monte-Carlo simulation was performed to identify an optimal number of echoes that would result in a significant improvement in the accuracy of the T 2 * $$ {\mathrm{T}}_2^{\ast } $$ fit within an acceptable scan time. A validation study was conducted on a phantom with known short T 2 * $$ {\mathrm{T}}_2^{\ast } $$ values (< 5 ms). The scanning protocol included a combination of a standard multi-echo UTE with six echoes (2.2-ms intervals) and a new four-echo UTE (TE < 2 ms) with tight TE intervals δTE. The human imaging was performed at 3 T on 6 adult volunteers. T 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping was performed with mono-exponential and bi-exponential models. RESULTS: The simulation for the proposed 10-echo acquisition predicted over 2-fold improvement in the accuracy of estimating the short T 2 * $$ {\mathrm{T}}_2^{\ast } $$ compared with the regular six-echo acquisition. In the phantom study, the T 2 * $$ {\mathrm{T}}_2^{\ast } $$ was measured up to three times more accurately compared with standard six-echo UTE. In human lungs, T 2 * $$ {\mathrm{T}}_2^{\ast } $$ maps were successfully obtained from 10 echoes, yielding average values T 2 * $$ {\mathrm{T}}_2^{\ast } $$ = 1.62 ± 0.48 ms for mono-exponential and T 2 s * $$ {\mathrm{T}}_{2s}^{\ast } $$ = 1.00 ± 0.53 ms for bi-exponential models. CONCLUSION: A UTE sequence using δTE was implemented and validated on short T 2 * $$ {\mathrm{T}}_2^{\ast } $$ phantoms. The sequence was successfully applied for lung imaging; the bi-exponential signal model fit for human lung imaging may provide valuable insights into the diseased human lungs.

Synthesis, Structural and Fluorescence Investigations of Novel Li2Ba5W3O15:Sm3+ Phosphors for Photonic Device Applications.

In the current study, Sm3+ ions doped Lithium Barium Tungstate (Li2Ba5W3O15) (LBW) phosphors with the ability to emit orange-red light were made using the traditional high-temperature solid-state reaction technique. The structure and phase of the as-synthesized phosphor samples were examined via X-ray diffraction (XRD) patterns. The diffraction peaks of the undoped LBW and Sm3+ ions doped LBW phosphors closely resemble those of the Joint Committee on Powder Diffraction Standards (JCPDS) pattern with card number 01-072-1717. Scanning electron microscopy (SEM) was employed for the analysis of the morphological characteristics of the synthesized phosphor material. Fourier Transform Infrared (FT-IR) spectroscopy was used to study several vibrational and molecular bands present in the host matrix. Using diffuse reflectance spectra (DRS), the optical band gap values (Eg) were evaluated by applying Tauc's method. The photoluminescence (PL) spectra characteristics at λex = 336 nm indicate the emission of dopant ions (Sm3+) in the deep orange-red region corresponding to 4G5/2 → 6H5/2 transition (at 581 nm) with concentration quenching after 2 mol % of Sm3+ ions. Using the PL spectra, the CIE chromaticity coordinates of LBWS2.0 phosphor were estimated and found in the deep visible orange-red area, indicating the potential use of the prepared phosphor material for phosphor-converted white light emitting diodes (w-LEDs) applications. Double exponential behaviour can be seen in the PL decay spectral profiles obtained under λem = 581 nm and λex = 336 nm. The experimental lifetimes (τexp) decrease as the concentration of Sm3+ ions rise. The temperature-dependent PL (TDPL) and activation energy results show that the as-synthesized phosphor has considerably superior thermal stability. The results of the current research contemplate us the applicability of Sm3+ ions doped LBW phosphor for photonic devices such as w-LEDs.

Multiphoton FLIM Analyses of Native and UVA-Modified Synthetic Melanins.

To better understand the impact of solar light exposure on human skin, the chemical characterization of native melanins and their structural photo-modifications is of central interest. As the methods used today are invasive, we investigated the possibility of using multiphoton fluorescence lifetime (FLIM) imaging, along with phasor and bi-exponential fitting analyses, as a non-invasive alternative method for the chemical analysis of native and UVA-exposed melanins. We demonstrated that multiphoton FLIM allows the discrimination between native DHI, DHICA, Dopa eumelanins, pheomelanin, and mixed eu-/pheo-melanin polymers. We exposed melanin samples to high UVA doses to maximize their structural modifications. The UVA-induced oxidative, photo-degradation, and crosslinking changes were evidenced via an increase in fluorescence lifetimes along with a decrease in their relative contributions. Moreover, we introduced a new phasor parameter of a relative fraction of a UVA-modified species and provided evidence for its sensitivity in assessing the UVA effects. Globally, the fluorescence lifetime properties were modulated in a melanin-dependent and UVA dose-dependent manner, with the strongest modifications being observed for DHICA eumelanin and the weakest for pheomelanin. Multiphoton FLIM phasor and bi-exponential analyses hold promising perspectives for in vivo human skin mixed melanins characterization under UVA or other sunlight exposure conditions.

Application of Simultaneous 18 F-FDG PET With Monoexponential, Biexponential, and Stretched Exponential Model-Based Diffusion-Weighted MR Imaging in Assessing the Proliferation Status of Lung Adenocarcinoma.

BACKGROUND: Ki-67 proliferation index (PI) is important for providing information on tumor behavior, treatment response, and prognosis. Integrated positron emission tomography/magnetic resonance (PET/MR) may have the potential to assess Ki-67 PI in patients with lung adenocarcinoma. PURPOSE: To explore the value of simultaneous 18 F-fluorodeoxyglucose (18 F-FDG) PET/MR-derived parameters in assessing the proliferation status of lung adenocarcinoma and to determine the best combination of parameters. STUDY TYPE: Prospective. POPULATION: Seventy-eight patients with lung adenocarcinoma and with Ki-67 PI. FIELD STRENGTH/SEQUENCE: 3.0 T, simultaneous PET/MRI including diffusion-weighted imaging (DWI) and 18 F-FDG PET. ASSESSMENT: DWI-derived parameters, namely, apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), diffusion heterogeneity index (α), and distributed diffusion coefficient (DDC); and PET-derived parameters, namely, maximum standardized uptake value (SUVmax ), metabolic tumor volume (MTV), and total lesion glycolytic volume (TLG), were calculated and compared between the high (>25%) and low (≤25%) Ki-67 PI groups. The correlations between PET-derived parameters and DWI-derived parameters were analyzed. STATISTICAL TESTS: Student's t-test, Mann-Whitney U test, chi-square test, and receiver operating characteristic (ROC) curves. A P-value <0.05 was considered statistically significant. RESULTS: The SUVmax , MTV, TLG, ADC, D, and DDC values were significantly different between the high (N = 35) and low Ki-67 PI groups (N = 43). D, SUVmax , and MTV independently predicted the Ki-67 PI status. The combination of D, SUVmax , and MTV had the largest area under the ROC curve (AUC = 0.900), which was significantly larger than the AUC alone of DDC (AUC = 0.725), SUVmax (AUC = 0.815), MTV (AUC = 0.774), or TLG (AUC = 0.783). The perfusion fraction did not correlate with SUVmax , MTV, or TLG (r = -0.03, -0.11, and -0.04, respectively; P = 0.786, 0.348, and 0.733). DATA CONCLUSION: The combination of D, SUVmax , and MTV may predict Ki-67 PI status. No correlation was observed between perfusion parameters and metabolic parameters. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Volumetric multicomponent T1ρ relaxation mapping of the human liver under free breathing at 3T.

PURPOSE: To develop a 3D sequence for T1ρ relaxation mapping using radial volumetric encoding (3D-T1ρ -RAVE) and to evaluate the multi relaxation components in the liver of healthy controls and chronic liver disease (CLD) patients. METHODS: Fat saturation and T1ρ preparation modules were followed by a train of gradient-echo acquisitions and T1 restoration delay. The series of T1ρ -weighted images were fitted using mono-exponential, bi-exponential, and stretched-exponential models. The repeatability and reproducibility of the proposed technique were evaluated on National Institute of Standards and Technology phantom by calculating the coefficient of variation between test-retest scans on the same scanner and between two different 3T scanners, respectively. Mann-Whitney U-test was performed to assess differences in T1ρ components among patients (n = 3) and a control group (n = 10). RESULTS: The phantom study showed an error of 8.9% and 11.5% in mono T2 relaxation time measurement relative to the reference on 2 different scanners. The coefficient of variation for test-retest scans performed on the same scanner was 5.7% and 2.4% for scans performed on 2 scanners. The comparison between healthy controls and CLD patients showed a significant difference (P < .05) in mono relaxation time (P = .002), stretched-exponential relaxation parameter (P = .04). The Akaike information criteria C criterion showed 2.53 ± 0.9% (2.3 ± 0.3% for CLD) of the voxels are bi-exponential while in 65.3 ± 5.8% (81.2 ± 0.06% for CLD) of the liver voxels, the stretched-exponential model was preferred. CONCLUSION: The 3D-T1ρ -RAVE sequence allows volumetric, multicomponent T1ρ assessment of the liver during free breathing and can distinguish between healthy volunteers and CLD patients.

Bio-SCOPE: fast biexponential T1ρ mapping of the brain using signal-compensated low-rank plus sparse matrix decomposition.

PURPOSE: To develop and evaluate a fast imaging method based on signal-compensated low-rank plus sparse matrix decomposition to accelerate data acquisition for biexponential brain T1ρ mapping (Bio-SCOPE). METHODS: Two novel strategies were proposed to improve reconstruction performance. A variable-rate undersampling scheme was used with a varied acceleration factor for each k-space along the spin-lock time direction, and a modified nonlinear thresholding scheme combined with a feature descriptor was used for Bio-SCOPE reconstruction. In vivo brain T1ρ mappings were acquired from 4 volunteers. The fully sampled k-space data acquired from 3 volunteers were retrospectively undersampled by net acceleration rates (R) of 4.6 and 6.1. Reference values were obtained from the fully sampled data. The agreement between the accelerated T1ρ measurements and reference values was assessed with Bland-Altman analyses. Prospectively undersampled data with R = 4.6 and R = 6.1 were acquired from 1 volunteer. RESULTS: T1ρ -weighted images were successfully reconstructed using Bio-SCOPE for R = 4.6 and 6.1 with signal-to-noise ratio variations <1 dB and normalized root mean square errors <4%. Accelerated and reference T1ρ measurements were in good agreement for R = 4.6 (T1ρs : 18.6651 ± 1.7786 ms; T1ρl : 88.9603 ± 1.7331 ms) and R = 6.1 (T1ρs : 17.8403 ± 3.3302 ms; T1ρl : 88.0275 ± 4.9606 ms) in the Bland-Altman analyses. T1ρ parameter maps from prospectively undersampled data also show reasonable image quality using the Bio-SCOPE method. CONCLUSION: Bio-SCOPE achieves a high net acceleration rate for biexponential T1ρ mapping and improves reconstruction quality by using a variable-rate undersampling data acquisition scheme and a modified soft-thresholding algorithm in image reconstruction.

Modeling the diffusion-weighted imaging signal for breast lesions in the b = 200 to 3000 s/mm2 range: quality of fit and classification accuracy for different representations.

PURPOSE: To evaluate different non-Gaussian representations for the diffusion-weighted imaging (DWI) signal in the b-value range 200 to 3000 s/mm2 in benign and malignant breast lesions. METHODS: Forty-three patients diagnosed with benign (n = 18) or malignant (n = 25) tumors of the breast underwent DWI (b-values 200, 600, 1200, 1800, 2400, and 3000 s/mm2 ). Six different representations were fit to the average signal from regions of interest (ROIs) at different b-value ranges. Quality of fit was assessed by the corrected Akaike information criterion (AICc), and the Friedman test was used for assessing representation ranks. The area under the curve (AUC) of receiver operating characteristic curves were used to evaluate the power of derived parameters to differentiate between malignant and benign lesions. The lesion ROI was divided in central and peripheral parts to assess potential effect of heterogeneity. Sensitivity to noise-floor correction was also evaluated. RESULTS: The Padé exponent was ranked as the best based on AICc, whereas 3 models (kurtosis, fractional, and biexponential) achieved the highest AUC = 0.99 for lesion differentiation. The monoexponential model at bmax = 600 s/mm2 already provides AUC = 0.96, with considerably shorter acquisition time and simpler analysis. Significant differences between central and peripheral parts of lesions were found in malignant lesions. The mono- and biexponential models were most stable against varying degrees of noise-floor correction. CONCLUSION: Non-Gaussian representations are required for fitting of the DWI curve at high b-values in breast lesions. However, the added clinical value from the high b-value data for differentiation of benign and malignant lesions is not clear.

Blood-brain barrier permeability measurement by biexponentially modeling whole-brain arterial spin labeling data with multiple T2 -weightings.

Blood-brain barrier (BBB) permeability assessment remains of ongoing interest in clinical practice and research. Transitions between intravascular (IV) and extravascular (EV) gray matter (GM) compartments may provide information regarding the microstructural status of the BBB. Due to different transverse relaxation times (T2 ) of water protons in vessels and GM, it is possible to determine the compartment in which these protons are located. This work presents and investigates the feasibility of a simplified analytical approach for compartmentalizing the proportions of magnetically marked water protons into IV and EV GM components by biexponentially modeling T2 -weighted arterial spin labeling (ASL) data. Numerous model assumptions were used to stabilize the fit and achieve in vivo applicability. Particularly, transverse relaxation times of IV and EV water protons were determined from the analysis of two supporting T2 -weighted ASL measurements, utilizing a monoexponential signal model. This stabilized a two-parameter biexponential fit of ASL data with T2 preparation (PLD = 0.9/1.2/1.5/1.8 s, TET2Prep = 0/30/40/60/80/120/160 ms), which thereby robustly provided estimates of the IV and EV compartment fractions. Experiments were conducted with three healthy volunteers in a 3 T scanner. Averaged over all subjects, the labeled water protons inherit T2,IV = 200 ± 18 ms initially and adapt T2,EV = 91 ± 2 ms with a longer retention time in cerebral structures. Accordingly, the EVlocated ASL signal fraction rises with increasing PLD from 0.31 ± 0.11 at the shortest PLD of 0.9 s to 0.73 ± 0.02 at the longest PLD of 1.8s. These results indicate a transition of the water protons from IV to EV space. The findings support the potential of biexponential modeling for compartmentalizing ASL spin fractions between IV and EV space. The novel integration of monoexponential parameter estimates stabilizes the two-compartment model fit, suggesting that this technique is suitable for robustly estimating the BBB permeability in vivo.

Stromal Collagen Content in Breast Tumors Correlates With In Vivo Diffusion-Weighted Imaging: A Comparison of Multi b-Value DWI With Histologic Specimen From Benign and Malignant Breast Lesions.

BACKGROUND: Increased deposition and reorientation of stromal collagen fibers are associated with breast cancer progression and invasiveness. Diffusion-weighted imaging (DWI) may be sensitive to the collagen fiber organization in the stroma and could provide important biomarkers for breast cancer characterization. PURPOSE: To understand how collagen fibers influence water diffusion in vivo and evaluate the relationship between collagen content and the apparent diffusion coefficient (ADC) and the signal fractions of the biexponential model using a high b-value scheme. STUDY TYPE: Prospective. SUBJECTS/SPECIMENS: Forty-five patients with benign (n = 8), malignant (n = 36), and ductal carcinoma in situ (n = 1) breast tumors. Lesions and normal fibroglandular tissue (n = 9) were analyzed using sections of formalin-fixed, paraffin-embedded tissue stained with hematoxylin, erythrosine, and saffron. FIELD STRENGTH/SEQUENCE: MRI (3T) protocols: Protocol I: Twice-refocused spin-echo echo-planar imaging with: echo time (TE) 85 msec; repetition time (TR) 9300/11600 msec; matrix 90 × 90 × 60; voxel size 2 × 2 × 2.5 mm3 ; b-values: 0 and 700 s/mm2 . Protocol II: Stejskal-Tanner spin-echo echo-planar imaging with: TE: 88 msec; TR: 10600/11800 msec, matrix 90 × 90 × 60; voxel size 2 × 2 × 2.5 mm3 ; b-values [0, 200, 600, 1200, 1800, 2400, 3000] s/mm2 . ASSESSMENT: Area fractions of cellular and collagen content in histologic sections were quantified using whole-slide image analysis and compared with the corresponding DWI parameters. STATISTICAL TESTS: Correlations were assessed using Pearson's r. Univariate analysis of group median values was done using the Mann-Whitney U-test. RESULTS: Collagen content correlated with the fast signal fraction (r = 0.67, P < 0.001) and ADC (r = 0.58, P < 0.001) and was lower (P < 0.05) in malignant lesions than benign and normal tissues. Cellular content correlated inversely with the fast signal fraction (r = -0.67, P < 0.001) and ADC (r = -0.61, P < 0.001) and was different (P < 0.05) between malignant, benign, and normal tissues. DATA CONCLUSION: Our findings suggest stromal collagen content increases diffusivity observed by MRI and is associated with higher ADC and fast signal fraction of the biexponential model. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2020;51:1868-1878.

Differentiation of high-grade from low-grade diffuse gliomas using diffusion-weighted imaging: a comparative study of mono-, bi-, and stretched-exponential diffusion models.

PURPOSE: Diffusion-weighted imaging (DWI) plays an important role in the preoperative assessment of gliomas; however, the diagnostic performance of histogram-derived parameters from mono-, bi-, and stretched-exponential DWI models in the grading of gliomas has not been fully investigated. Therefore, we compared these models' ability to differentiate between high-grade and low-grade gliomas. METHODS: This retrospective study included 22 patients with diffuse gliomas (age, 23-74 years; 12 males; 11 high-grade and 11 low-grade gliomas) who underwent preoperative 3 T-magnetic resonance imaging from October 2014 to August 2019. The apparent diffusion coefficient was calculated from the mono-exponential model. Using 13 b-values, the true-diffusion coefficient, pseudo-diffusion coefficient, and perfusion fraction were obtained from the bi-exponential model, and the distributed-diffusion coefficient and heterogeneity index were obtained from the stretched-exponential model. Region-of-interests were drawn on each imaging parameter map for subsequent histogram analyses. RESULTS: The skewness of the apparent diffusion, true-diffusion, and distributed-diffusion coefficients was significantly higher in high-grade than in low-grade gliomas (0.67 ± 0.67 vs. - 0.18 ± 0.63, 0.68 ± 0.74 vs. - 0.08 ± 0.66, 0.63 ± 0.72 vs. - 0.15 ± 0.73; P = 0.0066, 0.0192, and 0.0128, respectively). The 10th percentile of the heterogeneity index was significantly lower (0.77 ± 0.08 vs. 0.88 ± 0.04; P = 0.0004), and the 90th percentile of the perfusion fraction was significantly higher (12.64 ± 3.44 vs. 7.14 ± 1.70%: P < 0.0001), in high-grade than in low-grade gliomas. The combination of the 10th percentile of the true-diffusion coefficient and 90th percentile of the perfusion fraction showed the best area under the receiver operating characteristic curve (0.96). CONCLUSION: The bi-exponential model exhibited the best diagnostic performance for differentiating high-grade from low-grade gliomas.

Compressed sensing acceleration of biexponential 3D-T1ρ relaxation mapping of knee cartilage.

PURPOSE: Use compressed sensing (CS) for 3D biexponential spin-lattice relaxation time in the rotating frame (T1ρ ) mapping of knee cartilage, reducing the total scan time and maintaining the quality of estimated biexponential T1ρ parameters (short and long relaxation times and corresponding fractions) comparable to fully sampled scans. METHODS: Fully sampled 3D-T1ρ -weighted data sets were retrospectively undersampled by factors 2-10. CS reconstruction using 12 different sparsifying transforms were compared for biexponential T1ρ -mapping of knee cartilage, including temporal and spatial wavelets and finite differences, dictionary from principal component analysis (PCA), k-means singular value decomposition (K-SVD), exponential decay models, and also low rank and low rank plus sparse models. Synthetic phantom (N = 6) and in vivo human knee cartilage data sets (N = 7) were included in the experiments. Spatial filtering before biexponential T1ρ parameter estimation was also tested. RESULTS: Most CS methods performed satisfactorily for an acceleration factor (AF) of 2, with relative median normalized absolute deviation (MNAD) around 10%. Some sparsifying transforms, such as low rank with spatial finite difference (L + S SFD), spatiotemporal finite difference (STFD), and exponential dictionaries (EXP) significantly improved this performance, reaching MNAD below 15% with AF up to 10, when spatial filtering was used. CONCLUSION: Accelerating biexponential 3D-T1ρ mapping of knee cartilage with CS is feasible. The best results were obtained by STFD, EXP, and L + S SFD regularizers combined with spatial prefiltering. These 3 CS methods performed satisfactorily on synthetic phantom as well as in vivo knee cartilage for AFs up to 10, with median error below 15%.

Orientation dependence and decay characteristics of T2 * relaxation in the human meniscus studied with 7 Tesla MR microscopy and compared to histology.

PURPOSE: To evaluate: (1) the feasibility of MR microscopy T2 * mapping by performing a zonal analysis of spatially matched T2 * maps and histological images using microscopic in-plane pixel resolution; (2) the orientational dependence of T2 * relaxation of the meniscus; and (3) the T2 * decay characteristics of the meniscus by statistically evaluating the quality of mono- and biexponential model. METHODS: Ultrahigh resolution T2 * mapping was performed with ultrashort echo time using a 7 Tesla MR microscopy system. Measurement of one meniscus was performed at three orientations to the main magnetic field (0, 55, and 90°). Histological assessment was performed with picrosirius red staining and polarized light microscopy. Quality of mono- and biexponential model fitting was tested using Akaike Information Criteria and F-test. RESULTS: (1) The outer laminar layer, connective tissue fibers from the joint capsule, and the highly organized tendon-like structures were identified using ultra-highly resolved MRI. (2) Highly organized structures of the meniscus showed considerable changes in T2 * values with orientation. (3) No significant biexponential decay was found on a voxel-by-voxel-based evaluation. On a region-of-interest-averaged basis, significant biexponential decay was found for the tendon-like region in a fiber-to-field angle of 0°. CONCLUSION: The MR microscopy approach used in this study allows the identification of meniscus substructures and to quantify T2 * with a voxel resolution approximately 100 times higher than previously reported. T2 * decay showed a strong fiber-to-field angle dependence reflecting the anisotropic properties of the meniscal collagen fibers. No clear biexponential decay behavior was found for the meniscus substructures.

Comparison of tri-exponential decay versus bi-exponential decay and full fitting versus segmented fitting for modeling liver intravoxel incoherent motion diffusion MRI.

OBJECTIVES: To determine whether bi- or tri-exponential models, and full or segmented fittings, better fit the intravoxel incoherent motion (IVIM) imaging signal of healthy livers. METHODS: Diffusion-weighted images were acquired with a 3 T scanner using a respiratory-triggered echo-planar sequence and 16 b-values (0-800 s/mm2 ). Eighteen healthy volunteers had their livers scanned twice in the same session, and then once in another session. Liver parenchyma region-of-interest-based measurements were processed with bi-exponential and tri-exponential models, with both full fitting and segmented fitting (threshold b-value = 200 s/mm2 ). RESULTS: With the signal of all scans averaged, bi-exponential model full fitting showed Dslow  = 1.14 × 10-3  mm2 /s, Dfast  = 193.6 × 10-3  mm2 /s, and perfusion fraction (PF) = 16.9%, and segmented fitting showed Dslow  = 0.98 × 10-3  mm2 /s, Dfast  = 42.2 × 10-3  mm2 /s, and PF = 23.3%. IVIM parameters derived from the tri-exponential model were similar for full fitting and segmented fitting, with slow (D'slow  = 0.98 × 10-3  mm2 /s; F'slow  = 76.4 or 76.6%), fast (D'fast  = 15.1 or 15.4 × 10-3  mm2 /s; F'fast  = 11.8 or 11.7%) and very fast (D'Vfast  = 445.0 or 448.8 × 10-3  mm2 /s; F'Vfast  = 11.8 or 11.7%) diffusion compartments. The tri-exponential model provided an overall better fit than the bi-exponential model. For the bi-exponential model, full fitting provided a better fit at very low and low b-values compared with segmented fitting, with the latter tending to underestimate Dfast ; however, the segmented method demonstrated lower error in signal prediction for high b-values. Compared with full fitting, tri-exponential segmented fitting offered better scan-rescan reproducibility. CONCLUSION: For healthy liver, tri-exponential modeling is preferred to bi-exponential modeling. For the bi-exponential model, segmented fitting underestimates Dfast , but offers a more accurate estimation of Dslow .

3D-T1ρ prepared zero echo time-based PETRA sequence for in vivo biexponential relaxation mapping of semisolid short-T2 tissues at 3 T.

BACKGROUND: In addition to the articular cartilage, osteoarthritis (OA) affects several other tissues such as tendons, ligaments, and subchondral bone. T1ρ relaxation study of these short T2 tissues may provide a more comprehensive evaluation of OA. PURPOSE: To develop a 3D spin-lattice relaxation in the rotating frame (T1ρ ) prepared zero echo time (ZTE)-based pointwise encoding time reduction with radial acquisition (3D-T1ρ -PETRA) sequence for relaxation mapping of semisolid short-T2 tissues on a clinical 3 T scanner. STUDY TYPE: Prospective. POPULATION: Phantom, two bovine whole knee joint and Achilles tendon specimens, 10 healthy volunteers with no known inflammation, trauma or pain in the knee or ankle. FIELD STRENGTH/SEQUENCE: A customized PETRA sequence to acquire fat-suppressed 3D T1ρ -weighted images tissues with semisolid short T2 / T2* relaxation times in the knee and ankle joints at 3 T. ASSESSMENT: Mono- and biexponential T1ρ relaxation components were assessed in the patellar tendon (PT), anterior cruciate ligament (ACL), posterior cruciate ligament (PCL), and Achilles tendon (AT). STATISTICAL TESTS: Kruskal-Wallis with post-hoc Dunn's test for multiple pairwise comparisons. RESULTS: Phantom and ex vivo studies showed the feasibility of T1ρ relaxation mapping using the proposed 3D-T1ρ -PETRA sequence. The in vivo study demonstrated an averaged mono-T1ρ relaxation of (median [IQR]) 15.9 [14.5] msec, 23.6 [9.4] msec, 17.4 [7.4] msec, and 5.8 [10.2] msec in the PT, ACL, PCL, and AT, respectively. The bicomponent analysis showed the short and long components (with their relative fractions) of 0.65 [1.0] msec (46.9 [15.3]%) and 37.3 [18.4] msec (53.1 [15.3]%) for PT, 1.7 [2.1] msec (42.5 [12.5]%) and 43.7 [17.8] msec (57.5 [12.5]%) for ACL, and 1.2 [1.9] msec (42.6 [14.0]%) and 27.7 [14.7] msec (57.3 [14.0]%) for PCL and 0.4 [0.02] msec (58.8 [13.3]%/) and 31.3 [10.8] msec (41.2 [13.3]%) for AT. Statistically significant (P ≤ 0.05) differences were observed in the mono- and biexponential relaxation between several regions. DATA CONCLUSION: The 3D-T1ρ -PETRA sequence allows volumetric, isotropic (0.78 × 0.78 × 0.78 mm), biexponential T1ρ assessment with corresponding fractions of the tissues with semisolid short T2 / T2* . LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;50:1207-1218.

Biexponential T1ρ relaxation mapping of human knee menisci.

BACKGROUND: Measuring T1ρ in the knee menisci can potentially be used as noninvasive biomarkers in detecting early-stage osteoarthritis (OA). PURPOSE: To demonstrate the feasibility of biexponential T1ρ relaxation mapping of human knee menisci. STUDY TYPE: Prospective. POPULATION: Eight healthy volunteers with no known inflammation, trauma, or pain in the knee and three symptomatic subjects with early knee OA. FIELD STRENGTH/SEQUENCE: Customized Turbo-FLASH sequence to acquire 3D-T1ρ -weighted images on a 3 T MRI scanner. ASSESSMENT: T1ρ relaxation values were assessed in 11 meniscal regions of interest (ROIs) using monoexponential and biexponential models. STATISTICAL TESTS: Nonparametric rank-sum tests, Kruskal-Wallis test, and coefficient of variation. RESULTS: The mean monoexponential T1ρ relaxation in the lateral menisci were 28.05 ± 4.2 msec and 37.06 ± 10.64 msec for healthy subjects and early knee OA patients, respectively, while the short and long components were 8.07 ± 0.5 msec and 72.35 ± 3.2 msec for healthy subjects and 2.63 ± 2.99 msec and 55.27 ± 24.76 msec for early knee OA patients, respectively. The mean monoexponential T1ρ relaxation in the medial menisci were 34.30 ± 3.8 msec and 37.26 ± 11.38 msec for healthy and OA patients, respectively, while the short and long components were 7.76 ± 0.7 msec and 72.19 ± 4.2 msec for healthy subjects and 3.06 ± 3.24 msec and 55.27 ± 24.59 msec for OA patients, respectively. Statistically significant (P ≤ 0.05) differences were observed in the monoexponential relaxation between some of the ROIs. The T1ρ,short was significantly lower (P = 0.02) in the patients than controls. The rmsCV% ranges were 1.51-16.6%, 3.59-14.3%, and 4.91-15.6% for T1ρ -mono, T1ρ -short, and T1ρ -long, respectively. DATA CONCLUSION: Our results showed that in all ROIs, T1ρ relaxation times of outer zones (red zones) were less than inner zones (white zones). Monoexponential T1ρ was increased in medial, lateral, and body menisci of early OA while the biexponential numbers were decreased in early OA patients. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2019;50:824-835.

Biexponential R2* relaxometry for estimation of liver iron concentration in children: A better fit for high liver iron states.

BACKGROUND: R2* relaxometry's capacity to calculate liver iron concentration (LIC) is limited in patients with severe overload. Hemosiderin increases in these patients, which exhibits a non-monoexponential decay that renders a failed R2* analysis. PURPOSE/HYPOTHESIS: To evaluate a biexponential R2* relaxometry model in children with different ranges of iron overload. STUDY TYPE: Retrospective. POPULATION: In all, 181 children with different conditions associated with iron overload. FIELD STRENGTH/SEQUENCE: 1.5T, T2 *-weighted gradient echo sequence. ASSESSMENT: Bi- and monoexponential R2* relaxometry were measured in the liver using two regions of interest (ROIs) using a nonproprietary software: one encompassing the whole liver parenchyma (ROI-1) and the other only the periphery (ROI-2). These were drawn by a single trained observer. The residuals for each fitting model were estimated. A ratio between the residuals of the mono- and biexponential models was calculated to identify the best fitting model. Patients with 1) residual ratio ≥1.5 and 2) R2*fast ≥R2*slow were considered as having a predominant biexponential behavior. STATISTICAL TESTS: Nonparametric tests, Bland-Altman plots, linear correlation, intraclass correlation coefficient. Patients were divided according to their LIC into stable (n = 23), mild (n = 58), moderate (n = 61), and severe (n = 39). RESULTS: The biexponential model was more suitable for patients with severe iron overload when compared with the other three LIC categories (P < 0.001) for both ROIs. For ROI-1, 37 subjects met criteria for a predominant biexponential behavior. The slow component (5.7%) had a lower fraction than the fast component (94.2%). For ROI-2, 22 subjects met criteria for a predominant biexponential behavior. The slow component (4.7%) had a lower fraction than the fast component (95.2%). The intraobserver variability between both ROIs was excellent. DATA CONCLUSION: The biexponential R2* relaxometry model is more suitable in children with severe iron overload. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1191-1198.