Assessment of Global and Regional Lung Compliance in Pulmonary Fibrosis With Hyperpolarized Gas MRI.

BACKGROUND: Lung compliance, a biomarker of pulmonary fibrosis, is generally measured globally. Hyperpolarized 129Xe gas MRI offers the potential to evaluate lung compliance regionally, allowing for visualization of changes in lung compliance associated with fibrosis. PURPOSE: To assess global and regional lung compliance in a rat model of pulmonary fibrosis using hyperpolarized 129Xe gas MRI. STUDY TYPE: Prospective. ANIMAL MODEL: Twenty Sprague-Dawley male rats with bleomycin-induced fibrosis model (N = 10) and saline-treated controls (N = 10). FIELD STRENGTH/SEQUENCE: 7-T, fast low-angle shot (FLASH) sequence. ASSESSMENT: Lung compliance was determined by fitting lung volumes derived from segmented 129Xe MRI with an iterative selection method, to corresponding airway pressures. Similarly, lung compliance was obtained with computed tomography for cross-validation. Direction-dependencies of lung compliance were characterized by regional lung compliance ratios (R) in different directions. Pulmonary function tests (PFTs) and histological analysis were used to validate the pulmonary fibrosis model and assess its correlation with 129Xe lung compliance. STATISTICAL TESTS: Shapiro-Wilk tests, unpaired and paired t-tests, Mann-Whitney U and Wilcoxon signed-rank tests, and Pearson correlation coefficients. P < 0.05 was considered statistically significant. RESULTS: For the entire lung, the global and regional lung compliance measured with 129Xe gas MRI showed significant differences between the groups, and correlated with the global lung compliance measured using PFTs (global: r = 0.891; regional: r = 0.873). Additionally, for the control group, significant difference was found in mean regional compliance between areas, eg, 0.37 (0.32, 0.39) × 10-4 mL/cm H2O and 0.47 (0.41, 0.56) × 10-4 mL/cm H2O for apical and basal lung, respectively. The apical-basal direction R was 1.12 ± 0.09 and 1.35 ± 0.13 for fibrosis and control groups, respectively, indicating a significant difference. DATA CONCLUSION: Our findings demonstrate the feasibility of using hyperpolarized gas MRI to assess regional lung compliance. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Dynamic evaluation of acute lung injury using hyperpolarized 129 Xe magnetic resonance.

Prognosticating acute lung injury (ALI) is challenging, in part because of a lack of sensitive biomarkers. Hyperpolarized gas magnetic resonance (MR) has unique advantages in pulmonary function measurement and can provide promising biomarkers for the assessment of lung injuries. Herein, we employ hyperpolarized 129 Xe MRI and generate a number of imaging biomarkers to detect the pulmonary physiological and morphological changes during the progression of ALI in an animal model. We find the measured ratio of 129 Xe in red blood cells to interstitial tissue/plasma (RBC/TP) is significantly lower in the ALI group on the second (0.32 ± 0.03, p = 0.004), seventh (0.23 ± 0.03, p < 0.001), and 14th (0.29 ± 0.04, p = 0.001) day after lipopolysaccharide treatment compared with that in the control group (0.41 ± 0.04). In addition, significant differences are also observed for RBC/TP measurements between the second and seventh day (p = 0.001) and between the seventh and 14th day (p = 0.018) in the ALI group after treatment. Besides RBC/TP, significant differences are also observed in the measured exchange time constant (T) on the second (p = 0.038) and seventh day (p = 0.009) and in the measured apparent diffusion coefficient (ADC) and alveolar surface-to-volume ratio (SVR) on the 14th day (ADC: p = 0.009 and SVR: p = 0.019) after treatment in the ALI group compared with that in the control group. These findings indicate that the parameters measured with 129 Xe MR can detect the dynamic changes in pulmonary structure and function in an ALI animal model.

Accelerate gas diffusion-weighted MRI for lung morphometry with deep learning.

OBJECTIVES: Multiple b-value gas diffusion-weighted MRI (DW-MRI) enables non-invasive and quantitative assessment of lung morphometry, but its long acquisition time is not well-tolerated by patients. We aimed to accelerate multiple b-value gas DW-MRI for lung morphometry using deep learning. METHODS: A deep cascade of residual dense network (DC-RDN) was developed to reconstruct high-quality DW images from highly undersampled k-space data. Hyperpolarized 129Xe lung ventilation images were acquired from 101 participants and were retrospectively collected to generate synthetic DW-MRI data to train the DC-RDN. Afterwards, the performance of the DC-RDN was evaluated on retrospectively and prospectively undersampled multiple b-value 129Xe MRI datasets. RESULTS: Each slice with size of 64 × 64 × 5 could be reconstructed within 7.2 ms. For the retrospective test data, the DC-RDN showed significant improvement on all quantitative metrics compared with the conventional reconstruction methods (p < 0.05). The apparent diffusion coefficient (ADC) and morphometry parameters were not significantly different between the fully sampled and DC-RDN reconstructed images (p > 0.05). For the prospectively accelerated acquisition, the required breath-holding time was reduced from 17.8 to 4.7 s with an acceleration factor of 4. Meanwhile, the prospectively reconstructed results showed good agreement with the fully sampled images, with a mean difference of -0.72% and -0.74% regarding global mean ADC and mean linear intercept (Lm) values. CONCLUSIONS: DC-RDN is effective in accelerating multiple b-value gas DW-MRI while maintaining accurate estimation of lung microstructural morphometry, facilitating the clinical potential of studying lung diseases with hyperpolarized DW-MRI. KEY POINTS: • The deep cascade of residual dense network allowed fast and high-quality reconstruction of multiple b-value gas diffusion-weighted MRI at an acceleration factor of 4. • The apparent diffusion coefficient and morphometry parameters were not significantly different between the fully sampled images and the reconstructed results (p > 0.05). • The required breath-holding time was reduced from 17.8 to 4.7 s and each slice with size of 64 × 64 × 5 could be reconstructed within 7.2 ms.

Improvement in the signal amplitude and bandwidth of an optical atomic magnetometer via alignment-to-orientation conversion.

We evaluated the alignment-to-orientation conversion (AOC) at the cesium D1 line to improve a nonlinear magneto-optical rotation (NMOR) optical atomic magnetometer's signal amplitude and bandwidth. For the 6 2S1/2 F = 3 → 6 2P1/2 F' = 4 transition, the AOC-related NMOR achieves a 1.7-fold enhancement in signal amplitude compared to the conventional NMOR, benefiting from narrow linewidth and ultraweak power broadening. Therefore, an effective amplitude-to-linewidth ratio is maintained in the high-laser-power region. This method is beneficial for detecting high-frequency magnetic signals in nuclear magnetic resonance and biomagnetism, as the NMOR magnetometer bandwidth increases with laser power.

Quieting an environmental magnetic field without shielding.

We construct an active magnetic compensation device and propose an efficient magnetic compensation method that suppresses a wider range of frequencies and amplitudes of time-varying magnetic fields than conventional methods. This system can compensate for all frequencies in the bandwidth of the sensors used by analyzing and extracting the spectral characteristics of the ambient field. We compensate simultaneously for various types of interference in rotation and achieve a reduction of the 50-Hz power-frequency field noise by 36 dB. Meanwhile, the real-time compensation of the field gradient is also investigated. Due to the effectiveness and extensive applicability of this method, it holds great promise for applications in atomic magnetometers, electron microscopes, and atomic clocks.

Quantitative evaluation of lung injury caused by PM2.5 using hyperpolarized gas magnetic resonance.

PURPOSE: To demonstrate the feasibility of 129 Xe MR in evaluating the pulmonary physiological changes caused by PM2.5 in animal models. METHODS: Six rats were treated with PM2.5 solution (16.2 mg/kg) by intratracheal instillation twice a week for 4 weeks, and another six rats treated with normal saline served as the control cohort. Pulmonary function tests, hyperpolarized 129 Xe multi-b diffusion-weighted imaging, and chemical shift saturation recovery MR spectroscopy were performed on all rats, and the pulmonary structure and functional parameters were obtained from hyperpolarized 129 Xe MR data. Additionally, histological analysis was performed on all rats to evaluate alveolar septal thickness. Statistical analysis of all the obtained parameters was performed using unpaired 2-tailed t tests. RESULTS: Compared with the control group, the measured exchange time constant increased from 11.74 ± 2.39 to 14.00 ± 2.84 ms (P < .05), and the septal wall thickness increased from 6.17 ± 0.48 to 6.74 ± 0.52 µm (P < .05) in the PM2.5 cohort by 129 Xe MR spectroscopy, which correlated well with that obtained using quantitative histology (increased from 5.52 ± 0.32 to 6.20 ± 0.36 µm). Additionally, the mean TP/GAS ratio increased from 0.828 ± 0.115 to 1.019 ± 0.140 in the PM2.5 cohort (P = .021). CONCLUSIONS: Hyperpolarized 129 Xe MR could quantify the changes in gas exchange physiology caused by PM2.5 , indicating that the technique has the potential to be a useful tool for evaluation of pulmonary injury caused by air pollution in the future.

Fast and accurate reconstruction of human lung gas MRI with deep learning.

PURPOSE: To fast and accurately reconstruct human lung gas MRI from highly undersampled k-space using deep learning. METHODS: The scheme was comprised of coarse-to-fine nets (C-net and F-net). Zero-filling images from retrospectively undersampled k-space at an acceleration factor of 4 were used as input for C-net, and then output intermediate results which were fed into F-net. During training, a L2 loss function was adopted in C-net, while a function that united L2 loss with proton prior knowledge was used in F-net. The 871 hyperpolarized 129 Xe pulmonary ventilation images from 72 volunteers were randomly arranged as training (90%) and testing (10%) data. Ventilation defect percentage comparisons were implemented using a paired 2-tailed Student's t-test and correlation analysis. Furthermore, prospective acquisitions were demonstrated in 5 healthy subjects and 5 asymptomatic smokers. RESULTS: Each image with size of 96 × 84 could be reconstructed within 31 ms (mean absolute error was 4.35% and structural similarity was 0.7558). Compared with conventional compressed sensing MRI, the mean absolute error decreased by 17.92%, but the structural similarity increased by 6.33%. For ventilation defect percentage, there were no significant differences between the fully sampled and reconstructed images through the proposed algorithm (P = 0.932), but had significant correlations (r = 0.975; P < 0.001). The prospectively undersampled results validated a good agreement with fully sampled images, with no significant differences in ventilation defect percentage but significantly higher signal-to-noise ratio values. CONCLUSION: The proposed algorithm outperformed classical undersampling methods, paving the way for future use of deep learning in real-time and accurate reconstruction of gas MRI.

Single breath-hold measurement of pulmonary gas exchange and diffusion in humans with hyperpolarized 129 Xe MR.

Pulmonary diseases usually result in changes of the blood-gas exchange function in the early stages. Gas exchange across the respiratory membrane and gas diffusion in the alveoli can be quantified using hyperpolarized 129 Xe MR via chemical shift saturation recovery (CSSR) and diffusion-weighted imaging (DWI), respectively. Generally, CSSR and DWI data have been collected in separate breaths in humans. Unfortunately, the lung inflation level cannot be the exactly same in different breaths, which causes fluctuations in blood-gas exchange and pulmonary microstructure. Here we combine CSSR and DWI obtained with compressed sensing, to evaluate the gas diffusion and exchange function within a single breath-hold in humans. A new parameter, namely the perfusion factor of the respiratory membrane (SVRd/g ), is proposed to evaluate the gas exchange function. Hyperpolarized 129 Xe MR data are compared with pulmonary function tests and computed tomography examinations in healthy young, age-matched control, and chronic obstructive pulmonary disease human cohorts. SVRd/g decreases as the ventilation impairment and emphysema index increase. Our results indicate that the proposed method has the potential to detect the extent of lung parenchyma destruction caused by age and pulmonary diseases, and it would be useful in the early diagnosis of pulmonary diseases in clinical practice.

A Multiscale Fuzzy Metric for Detecting Small Infrared Targets Against Chaotic Cloudy/Sea-Sky Backgrounds.

In a low signal-to-clutter ratio (SCR) small-infrared-target image with chaotic cloudy-/sea-sky background, the target has very similar thermal intensities to the background (e.g., edges of clouds). In such case, how to accurately detect small targets is crucial in infrared search and tracking applications. Conventional methods based on the local difference/mutation potentially result in high miss and/or false alarm rates. Here, we propose an effective method for detecting small infrared targets embedded in complex backgrounds through a multiscale fuzzy metric that measures the certainty of targets in images. Accordingly, the detection task is formulated as a fuzzy measure issue. The presented metric is able to eliminate substantial background clutters and noise. Especially, it significantly improves SCR values of the image. Subsequently, a simple and adaptive threshold is used to segment target. Extensive clipped and real data experiments demonstrate that the proposed algorithm not only works more robustly for different target sizes, SCR values, target and/or background types, but also has better performance regarding detection accuracy, when compared with traditional baseline methods. Moreover, the mathematical proofs are provided for understanding the proposed detection method.

Highly and Adaptively Undersampling Pattern for Pulmonary Hyperpolarized 129Xe Dynamic MRI.

Hyperpolarized (HP) gas (e.g., 3He or 129Xe) dynamic MRI could visualize the lung ventilation process, which provides characteristics regarding lung physiology and pathophysiology. Compressed sensing (CS) is generally used to increase the temporal resolution of such dynamic MRI. Nevertheless, the acceleration factor of CS is constant, which results in difficulties in precisely observing and/or measuring dynamic ventilation process due to bifurcating network structure of the lung. Here, an adaptive strategy is proposed to highly undersample pulmonary HP dynamic k-space data, according to the characteristics of both lung structure and gas motion. After that, a valid reconstruction algorithm is developed to reconstruct dynamic MR images, considering the low-rank, global sparsity, gas-inflow effects, and joint sparsity. Both the simulation and the in vivo results verify that the proposed approach outperforms the state-of-the-art methods both in qualitative and quantitative comparisons. In particular, the proposed method acquires 33 frames within 6.67 s (more than double the temporal resolution of the recently proposed strategy), and achieves high-image quality [the improvements are 29.63%, 3.19%, 2.08%, and 13.03% regarding the mean absolute error (MAE), structural similarity index (SSIM), quality index based on local variance (QILV), and contrast-to-noise ratio (CNR) comparisons]. This provides accurate structural and functional information for early detection of obstructive lung diseases.

Quantitative evaluation of pulmonary gas-exchange function using hyperpolarized 129 Xe CEST MRS and MRI.

Hyperpolarized 129 Xe gas MR has been a powerful tool for evaluating pulmonary structure and function due to the extremely high enhancement in spin polarization, the good solubility in the pulmonary parenchyma, and the excellent chemical sensitivity to its surrounding environment. Generally, the quantitative structural and functional information of the lung are evaluated using hyperpolarized 129 Xe by employing the techniques of chemical shift saturation recovery (CSSR) and xenon polarization transfer contrast (XTC). Hyperpolarized 129 Xe chemical exchange saturation transfer (Hyper-CEST) is another method for quantifying the exchange information of hyperpolarized 129 Xe by using the exchange of xenon signals according to its different chemical shifts, and it has been widely used in biosensor studies in vitro. However, the feasibility of using hyperpolarized 129 Xe CEST to quantify the pulmonary gas exchange function in vivo is still unclear. In this study, the technique of CEST was used to quantitatively evaluate the gas exchange in the lung globally and regionally via hyperpolarized 129 Xe MRS and MRI, respectively. A new parameter, the pulmonary apparent gas exchange time constant (Tapp ), was defined, and it increased from 0.63 s to 0.95 s in chronic obstructive pulmonary disease (COPD) rats (induced by cigarette smoke and lipopolysaccharide exposure) versus the controls with a significant difference (P = 0.001). Additionally, the spatial distribution maps of Tapp in COPD rats' pulmonary parenchyma showed a regionally obvious increase compared with healthy rats. These results indicated that hyperpolarized 129 Xe CEST MR was an effective method for globally and regionally quantifying the pulmonary gas exchange function, which would be helpful in diagnosing lung diseases that are related to gas exchange, such as COPD.

Lung morphometry using hyperpolarized 129 Xe multi-b diffusion MRI with compressed sensing in healthy subjects and patients with COPD.

PURPOSE: To demonstrate the feasibility of compressed sensing (CS) to accelerate the acquisition of hyperpolarized (HP) 129 Xe multi-b diffusion MRI for quantitative assessments of lung microstructural morphometry. METHODS: Six healthy subjects and six chronic obstructive pulmonary disease (COPD) subjects underwent HP 129 Xe multi-b diffusion MRI (b = 0, 10, 20, 30, and 40 s/cm2 ). First, a fully sampled (FS) acquisition of HP 129 Xe multi-b diffusion MRI was conducted in one healthy subject. The acquired FS dataset was retrospectively undersampled in the phase encoding direction, and an optimal twofold undersampled pattern was then obtained by minimizing mean absolute error (MAE) between retrospective CS (rCS) and FS MR images. Next, the FS and CS acquisitions during separate breath holds were performed on five healthy subjects (including the above one). Additionally, the FS and CS synchronous acquisitions during a single breath hold were performed on the sixth healthy subject and one COPD subject. However, only CS acquisitions were conducted in the rest of the five COPD subjects. Finally, all the acquired FS, rCS and CS MR images were used to obtain morphometric parameters, including acinar duct radius (R), acinar lumen radius (r), alveolar sleeve depth (h), mean linear intercept (Lm ), and surface-to-volume ratio (SVR). The Wilcoxon signed-rank test and the Bland-Altman plot were employed to assess the fidelity of the CS reconstruction. Moreover, the t-test was used to demonstrate the effectiveness of the multi-b diffusion MRI with CS in clinical applications. RESULTS: The retrospective results demonstrated that there was no statistically significant difference between rCS and FS measurements using the Wilcoxon signed-rank test (P > 0.05). Good agreement between measurements obtained with the CS and FS acquisitions during separate breath holds was demonstrated in Bland-Altman plots of slice differences. Specifically, the mean biases of the R, r, h, Lm , and SVR between the CS and FS acquisitions were 1.0%, 2.6%, -0.03%, 1.5%, and -5.5%, respectively. Good agreement between measurements with the CS and FS acquisitions was also observed during the single breath-hold experiments. Furthermore, there were significant differences between the morphometric parameters for the healthy and COPD subjects (P < 0.05). CONCLUSIONS: Our study has shown that HP 129 Xe multi-b diffusion MRI with CS could be beneficial in lung microstructural assessments by acquiring less data while maintaining the consistent results with the FS acquisitions.

Considering low-rank, sparse and gas-inflow effects constraints for accelerated pulmonary dynamic hyperpolarized 129Xe MRI.

Dynamic hyperpolarized (HP) 129Xe MRI is able to visualize the process of lung ventilation, which potentially provides unique information about lung physiology and pathophysiology. However, the longitudinal magnetization of HP 129Xe is nonrenewable, making it difficult to achieve high image quality while maintaining high temporal-spatial resolution in the pulmonary dynamic MRI. In this paper, we propose a new accelerated dynamic HP 129Xe MRI scheme incorporating the low-rank, sparse and gas-inflow effects (L + S + G) constraints. According to the gas-inflow effects of HP gas during the lung inspiratory process, a variable-flip-angle (VFA) strategy is designed to compensate for the rapid attenuation of the magnetization. After undersampling k-space data, an effective reconstruction algorithm considering the low-rank, sparse and gas-inflow effects constraints is developed to reconstruct dynamic MR images. In this way, the temporal and spatial resolution of dynamic MR images is improved and the artifacts are lessened. Simulation and in vivo experiments implemented on the phantom and healthy volunteers demonstrate that the proposed method is not only feasible and effective to compensate for the decay of the magnetization, but also has a significant improvement compared with the conventional reconstruction algorithms (P-values are less than 0.05). This confirms the superior performance of the proposed designs and their ability to maintain high quality and temporal-spatial resolution.

Simultaneous assessment of both lung morphometry and gas exchange function within a single breath-hold by hyperpolarized 129 Xe MRI.

During the measurement of hyperpolarized 129 Xe magnetic resonance imaging (MRI), the diffusion-weighted imaging (DWI) technique provides valuable information for the assessment of lung morphometry at the alveolar level, whereas the chemical shift saturation recovery (CSSR) technique can evaluate the gas exchange function of the lungs. To date, the two techniques have only been performed during separate breaths. However, the request for multiple breaths increases the cost and scanning time, limiting clinical application. Moreover, acquisition during separate breath-holds will increase the measurement error, because of the inconsistent physiological status of the lungs. Here, we present a new method, referred to as diffusion-weighted chemical shift saturation recovery (DWCSSR), in order to perform both DWI and CSSR within a single breath-hold. Compared with sequential single-breath schemes (namely the 'CSSR + DWI' scheme and the 'DWI + CSSR' scheme), the DWCSSR scheme is able to significantly shorten the breath-hold time, as well as to obtain high signal-to-noise ratio (SNR) signals in both DWI and CSSR data. This scheme enables comprehensive information on lung morphometry and function to be obtained within a single breath-hold. In vivo experimental results demonstrate that DWCSSR has great potential for the evaluation and diagnosis of pulmonary diseases.

Detection of smoke-induced pulmonary lesions by hyperpolarized 129 Xe diffusion kurtosis imaging in rat models.

PURPOSE: To demonstrate that hyperpolarized (HP) xenon diffusion kurtosis imaging (DKI) is able to detect smoke-induced pulmonary lesions in rat models. METHODS: Multi-b DKI with hyperpolarized xenon was used for the first time in five smoke-exposed rats and five healthy rats. Additionally, DKI with b values of up to 80 s/cm2 were used in two healthy rats to probe the critical b value (a limit beyond which the DKI cannot describe the non-Gaussian diffusion). RESULTS: The mean apparent diffusion coefficient (Dapp ) and diffusion kurtosis (Kapp ) extracted by the DKI model revealed significant changes in the smoke-exposed rats compared with those in the control group (P = 0.027 and 0.039, respectively), exhibiting strong correlations with mean linear intercept (Lm ) from the histology. Although the maximum b value was increased to 80 s/cm2 , the DKI could still describe the non-Gaussian diffusion (R2 > 0.97). CONCLUSION: DKI with hyperpolarized xenon exhibited sensitivity in the detection of pulmonary lesions induced by smoke, including moderate emphysema and small airway diseases. The critical b value was rarely exceeded in DKI of the lungs due to the limited gradient strength of the MRI scanner used in our study. Magn Reson Med 78:1891-1899, 2016. © 2016 International Society for Magnetic Resonance in Medicine.

Mammogram Enhancement Using Intuitionistic Fuzzy Sets.

OBJECTIVE: Conventional mammogram enhancement methods use transform-domain filtering, which possibly produce some artifacts or not well highlight all local details in images. This paper presents a new enhancement method based on intuitionistic fuzzy sets. METHODS: The presented algorithm initially separates a mammogram via a global threshold and then fuzzifies the image utilizing the intuitionistic fuzzy membership function that adopts restricted equivalence functions. After that, the presented scheme hyperbolizes membership degrees of foreground and background areas, defuzzifies the fuzzy plane, and achieves a filtered image via normalization. Finally, an enhanced mammogram is obtained by fusing the original image with filtered one. These implementations can be processed in parallel. RESULTS: This algorithm can improve the contrast and visual quality of regions of interest. CONCLUSION: Real data experiments demonstrate that our method has better performance regarding the improvement of contrast and visual quality of abnormalities in mammograms (such as masses and/or microcalcifications), compared with classical baseline methods. SIGNIFICANCE: This algorithm has potential for understanding and determining abnormalities.

Detection of the mild emphysema by quantification of lung respiratory airways with hyperpolarized xenon diffusion MRI.

PURPOSE: To demonstrate the feasibility to quantify the lung respiratory airway in vivo with hyperpolarized xenon diffusion magnetic resonance imaging (MRI), which is able to detect mild emphysema in the rat model. MATERIALS AND METHODS: The lung respiratory airways were quantified in vivo using hyperpolarized xenon diffusion MRI (7T) with eight b values (5, 10, 15, 20, 25, 30, 35, 40 s/cm2 ) in five control rats and five mild emphysematous rats, which were induced by elastase. The morphological results from histology were acquired and used for comparison. RESULTS: The parameters DL (longitudinal diffusion coefficient), r (internal radius), h (alveolar sleeve depth), Lm (mean linear intercept), and S/V (surface area to lung volume ratio) derived from the hyperpolarized xenon diffusion MRI in the emphysematous group showed significant differences from those in the control group (P < 0.05). Additionally, these parameters correlated well with the Lm obtained by the traditional histological sections (Pearson's correlation coefficients >0.8). CONCLUSION: The lung respiratory airways can be quantified by hyperpolarized xenon diffusion MRI, showing the potential for mild emphysema diagnosis. Also, the study suggested that the hyperpolarized xenon DL is more sensitive than DT (transverse diffusion coefficient) to detect mild emphysema. LEVEL OF EVIDENCE: 1 J. Magn. Reson. Imaging 2017;45:879-888.

Adaptive Intuitionistic Fuzzy Enhancement of Brain Tumor MR Images.

Image enhancement techniques are able to improve the contrast and visual quality of magnetic resonance (MR) images. However, conventional methods cannot make up some deficiencies encountered by respective brain tumor MR imaging modes. In this paper, we propose an adaptive intuitionistic fuzzy sets-based scheme, called as AIFE, which takes information provided from different MR acquisitions and tries to enhance the normal and abnormal structural regions of the brain while displaying the enhanced results as a single image. The AIFE scheme firstly separates an input image into several sub images, then divides each sub image into object and background areas. After that, different novel fuzzification, hyperbolization and defuzzification operations are implemented on each object/background area, and finally an enhanced result is achieved via nonlinear fusion operators. The fuzzy implementations can be processed in parallel. Real data experiments demonstrate that the AIFE scheme is not only effectively useful to have information from images acquired with different MR sequences fused in a single image, but also has better enhancement performance when compared to conventional baseline algorithms. This indicates that the proposed AIFE scheme has potential for improving the detection and diagnosis of brain tumors.

Fast Determination of Flip Angle and T1 in Hyperpolarized Gas MRI During a Single Breath-Hold.

MRI of hyperpolarized media, such as (129)Xe and (3)He, shows great potential for clinical applications. The optimal use of the available spin polarization requires accurate flip angle calibrations and T1 measurements. Traditional flip angle calibration methods are time-consuming and suffer from polarization losses during T1 relaxation. In this paper, we propose a method to simultaneously calibrate flip angles and measure T1 in vivo during a breath-hold time of less than 4 seconds. We demonstrate the accuracy, robustness and repeatability of this method and contrast it with traditional methods. By measuring the T1 of hyperpolarized gas, the oxygen pressure in vivo can be calibrated during the same breath hold. The results of the calibration have been applied in variable flip angle (VFA) scheme to obtain a stable steady-state transverse magnetization. Coupled with this method, the ultra-short TE (UTE) and constant VFA (CVFA) schemes are expected to give rise to new applications of hyperpolarized media.

Oxygen-dependent hyperpolarized (129) Xe brain MR.

Hyperpolarized (HP) (129) Xe MR offers unique advantages for brain functional imaging (fMRI) because of its extremely high sensitivity to different chemical environments and the total absence of background noise in biological tissues. However, its advancement and applications are currently plagued by issues of signal strength. Generally, xenon atoms found in the brain after inhalation are transferred from the lung via the bloodstream. The longitudinal relaxation time (T1 ) of HP (129) Xe is inversely proportional to the pulmonary oxygen concentration in the lung because oxygen molecules are paramagnetic. However, the T1 of (129) Xe is proportional to the pulmonary oxygen concentration in the blood, because the higher pulmonary oxygen concentration will result in a higher concentration of diamagnetic oxyhemoglobin. Accordingly, there should be an optimal pulmonary oxygen concentration for a given quantity of HP (129) Xe in the brain. In this study, the relationship between pulmonary oxygen concentration and HP (129) Xe signal in the brain was analyzed using a theoretical model and measured through in vivo experiments. The results from the theoretical model and experiments in rats are found to be in good agreement with each other. The optimal pulmonary oxygen concentration predicted by the theoretical model was 21%, and the in vivo experiments confirmed the presence of such an optimal ratio by reporting measurements between 25% and 35%. These findings are helpful for improving the (129) Xe signal in the brain and make the most of the limited spin polarization available for brain experiments. Copyright © 2016 John Wiley & Sons, Ltd.