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PURPOSE: To evaluate the diagnostic efficacy of computed diffusion-weighted imaging (DWI) in pediatric posterior fossa tumors generated using high b-values. METHODS: We retrospectively performed our study on 32 pediatric patients who had undergone brain magnetic resonance imaging for a posterior fossa tumor between January 2016 and January 2022. The DWIs were evaluated for each patient by two blinded radiologists. The computed DWI (cDWI) was mathematically derived using a mono-exponential model from images with b = 0 and 1,000 s/mm2 and high b-values of 1,500, 2,000, 3,000, and 5,000 s/mm2. The posterior fossa tumors were divided into two groups, low grade and high grade, and the tumor/thalamus signal intensity (SI) ratios were compared. The Mann-Whitney U test and receiver operating characteristic (ROC) curves were used to compare the diagnostic performance of the acquired DWI (DWI1000), apparent diffusion coefficient (ADC)1000 maps, and cDWI (cDWI1500, cDWI2000, cDWI3000, and cDWI5000). RESULTS: The comparison of the two tumor groups revealed that the tumor/thalamus SI ratio on the DWI1000 and cDWI (cDWI1500, cDWI2000, cDWI3000, and cDWI5000) was statistically significantly higher in high-grade tumors (P < 0.001). In the ROC curve analysis, higher sensitivity and specificity were detected in the cDWI1500, cDWI2000, cDWI3000, and ADC1000 maps (100%, 90.90%) compared with the DWI1000 (80%, 81.80%). cDWI3000 had the highest area under the curve (AUC) value compared with other parameters (AUC: 0.976). CONCLUSION: cDWI generated using high b-values was successful in differentiating between low-grade and high-grade posterior fossa tumors without increasing imaging time. CLINICAL SIGNIFICANCE: cDWI created using high b-values can provide additional information about tumor grade in pediatric posterior fossa tumors without requiring additional imaging time.

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Purpose To determine whether the unsupervised domain adaptation (UDA) method with generated images improves the performance of a supervised learning (SL) model for prostate cancer (PCa) detection using multisite biparametric (bp) MRI datasets. Materials and Methods This retrospective study included data from 5150 patients (14 191 samples) collected across nine different imaging centers. A novel UDA method using a unified generative model was developed for PCa detection using multisite bpMRI datasets. This method translates diffusion-weighted imaging (DWI) acquisitions, including apparent diffusion coefficient (ADC) and individual diffusion-weighted (DW) images acquired using various b values, to align with the style of images acquired using b values recommended by Prostate Imaging Reporting and Data System (PI-RADS) guidelines. The generated ADC and DW images replace the original images for PCa detection. An independent set of 1692 test cases (2393 samples) was used for evaluation. The area under the receiver operating characteristic curve (AUC) was used as the primary metric, and statistical analysis was performed via bootstrapping. Results For all test cases, the AUC values for baseline SL and UDA methods were 0.73 and 0.79 (P < .001), respectively, for PCa lesions with PI-RADS score of 3 or greater and 0.77 and 0.80 (P < .001) for lesions with PI-RADS scores of 4 or greater. In the 361 test cases under the most unfavorable image acquisition setting, the AUC values for baseline SL and UDA were 0.49 and 0.76 (P < .001) for lesions with PI-RADS scores of 3 or greater and 0.50 and 0.77 (P < .001) for lesions with PI-RADS scores of 4 or greater. Conclusion UDA with generated images improved the performance of SL methods in PCa lesion detection across multisite datasets with various b values, especially for images acquired with significant deviations from the PI-RADS-recommended DWI protocol (eg, with an extremely high b value). Keywords: Prostate Cancer Detection, Multisite, Unsupervised Domain Adaptation, Diffusion-weighted Imaging, b Value Supplemental material is available for this article. © RSNA, 2024.

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The quantitative characterization of rock mass and stress changes induced by mining activities is crucial for structural stability monitoring and disaster early warning. This paper investigates the time-space-intensity distribution of microseismic sources during the pillar-free large-area continuous extraction. Furthermore, it explores a method involving collaborative evolution patterns of the velocity field and spatial b-value to identify stress and structural changes at the panel stope. Results show that anomalous zones in wave velocities and b-values form at the intersections of extraction drifts, strike drifts, cross drifts, and connection roadways influenced by mining activities, as well as in footwall ore-rock contacts, often accompanied by the nucleation of microseismic events. The synergistic use of wave velocity fields and spatial b-value models reveals the relationship between stress migration behavior and stope structure changes due to mining disturbances. The velocity field primarily reflects macroscopic changes in the structure and stress distribution, while spatial b-values further explain stress gradients in specific areas. Additionally, we have advanced the identification of an instability disaster at the connection roadway and cross drift intersection based on increases in wave velocity and abnormal changes in b-value. This paper demonstrates the potential of risk identification using the proposed method, providing insights into predicting geotechnical engineering disasters in complex stress environments.

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Objective: To compare image quality and diagnostic performance using different b-values for the zooming technique with diffusion-weighted imaging (ZOOMit-DWI) in thyroid nodules. Materials and methods: A total of 51 benign thyroid nodules and 50 thyroid papillary carcinomas were included. ZOOMit-DWI was performed with b-values of 0, 500, 1000, 1500 and 2000 s/mm2. The sharpness was evaluated as subjective index. The signal intensity ratio (SIR), signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) were measured as objective indices. Pairwise comparisons were performed among the different b-value groups using the Friedman test. A receiver operating characteristic curve of the ADC value was used to evaluate diagnostic performance. The DeLong test was used to compare diagnostic effectiveness among the different b-value groups. Results: In both the papillary carcinoma group (P = 0.670) and the benign nodule group (P = 0.185), the sharpness of nodules was similar between b-values of 1000 s/mm2and 1500 s/mm2. In the papillary carcinoma group, the SIRnodule was statistically higher in DWI images with a b-value of 1500 s/mm2than in DWI images with b-values of 500 s/mm2(P = 0.004), 1000 s/mm2(P = 0.002), and 2000 s/mm2(P = 0.003). When the b-values were 1500 s/mm2(P = 0.008) and 2000 s/mm2(P = 0.009), the SIRnodule significantly differed between the papillary carcinoma group and the benign nodule group. When b = 500 s/mm2, the ADC had an AUC of 0.888. When b = 1000 s/mm2, the ADC had an AUC of 0.881. When b = 1500 s/mm2, the ADC had an AUC of 0.896. When b = 2000 s/mm2, the ADC had an AUC of 0.871. The DeLong test showed comparable diagnostic effectiveness among the different b-value groups except for between b-values of 2000 s/mm2and 1500 s/mm2, with a b-value of 2000 s/mm2showing lower effectiveness. Conclusion: This study suggests that 1500 s/mm2may be a suitable b-value to differentiate benign and malignant thyroid nodules in ZOOMit-DWI images, which yielded better image quality.

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PURPOSE: Demonstrate the feasibility and evaluate the performance of single-shot diffusion trace-weighted radial echo planar spectroscopic imaging (Trace DW-REPSI) for quantifying the trace ADC in phantom and in vivo using a 3T clinical scanner. THEORY AND METHODS: Trace DW-REPSI datasets were acquired in 10 phantom and 10 healthy volunteers, with a maximum b-value of 1601 s/mm2 and diffusion time of 10.75 ms. The self-navigation properties of radial acquisitions were used for corrections of shot-to-shot phase and frequency shift fluctuations of the raw data. In vivo trace ADCs of total NAA (tNAA), total creatine (tCr), and total choline (tCho) extrapolated to pure gray and white matter fractions were compared, as well as trace ADCs estimated in voxels within white or gray matter-dominant regions. RESULTS: Trace ADCs in phantom show excellent agreement with reported values, and in vivo ADCs agree well with the expected differences between gray and white matter. For tNAA, tCr, and tCho, the trace ADCs extrapolated to pure gray and white matter ranged from 0.18-0.27 and 0.26-0.38 µm2/ms, respectively. In sets of gray and white matter-dominant voxels, the values ranged from 0.21 to 0.27 and 0.24 to 0.31 µm2/ms, respectively. The overestimated trace ADCs from this sequence can be attributed to the short diffusion time. CONCLUSION: This study presents the first demonstration of the single-shot diffusion trace-weighted spectroscopic imaging sequence using radial echo planar trajectories. The Trace DW-REPSI sequence could provide an estimate of the trace ADC in a much shorter scan time compared to conventional approaches that require three separate measurements.

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PURPOSE: Multi-Shot (MS) Echo-Planar Imaging (EPI) may improve the in-plane resolution of multi-b-value DWI, yet it also considerably increases the scan time. Here we explored the combination of EPI with Keyhole (EPIK) and a calibrationless reconstruction algorithm for acceleration of multi-b-value MS-DWI. METHODS: We firstly analyzed the impact of nonuniform phase accrual in EPIK on the reconstructed image. Based on insights gained from the analysis, we developed a calibrationless reconstruction algorithm based on a Space-Contrast-Coil Locally Low-Rank Tensor (SCC-LLRT) constraint for reconstruction of EPIK-acquired data. We compared the algorithm with a modified SPatial-Angular Locally Low-Rank (SPA-LLR) algorithm through simulations, phantoms, and in vivo study. We then compared EPIK with uniformly undersampled EPI for accelerating multi-b-value DWI in 6 healthy subjects. RESULTS: Through theoretical derivations, we found that the reconstruction of EPIK with a SENSE-encoding-based algorithm, such as SPA-LLR, may cause additional aliasing artifacts due to the frequency-dependent distortion of the coil sensitivity. Results from simulations, phantoms, and in vivo study verified the theoretical finding by showing that the calibrationless SCC-LLRT algorithm reduced aliasing artifacts compared with SPA-LLR. Finally, EPIK with SCC-LLRT substantially reduced the ghosting artifacts compared with uniform undersampled multi-b-value DWI, decreasing the fitting errors in ADC (0.05 ± 0.01 vs 0.10 ± 0.01, P < 0.001) and IVIM mapping (0.026 ± 0.004 vs 0.06 ± 0.006, P < 0.001). CONCLUSION: The SCC-LLRT algorithm reduced the aliasing artifacts of EPIK by using a calibrationless modeling of the multi-coil data. The dense sampling of k-space center offers EPIK a potential to improve image quality for acceleration of multi-b-value MS-DWI.

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In diffusion magnetic resonance imaging, oscillating gradient spin echo (OGSE) has an extremely short diffusion time if motion probing gradient (MPG) is applied to the waveform. Further, it can detect microstructural specificity. OGSE changes sensitivity to spin displacement velocity based on the MPG phase. The current study aimed to investigate the restricted diffusion characteristics of each OGSE waveform using the capillary phantom with various b-values, frequencies, and MPG phases. We performed OGSE (b-value = 300, 500, 800, 1200, 1600, and 2000 s/mm2) for the sine and cosine waveforms using the capillary phantom (6, 12, 25, 50, and 100 µm and free water) with a 9.4-T experimental magnetic resonance imaging system and a solenoid coil. We evaluated the axial and radial diffusivity (AD, RD) of each structure size. The output current of the MPG was assessed with an oscilloscope and analyzed with the gradient modulation power spectra by fast Fourier transform. In sine, the sidelobe spectrum was enhanced with increasing frequency, and the central spectrum slightly increased. The difference in RD was detected at 6 and 12 µm; however, it did not depend on the structure scale at 50 or 100 µm and free water. In cosine, the diffusion spectrum was enhanced, whereas the central spectrum decreased with increasing frequency. Both AD and RD in cosine had a frequency dependence, and AD and RD increased with a higher frequency regardless of structure size. AD and RD in either sine or cosine had no evident b-value dependence. We evaluated the OGSE-restricted diffusion characteristics. The measurements obtained diffusion information similar to the pulsed gradient spin echo. Hence, the cosine measurements indicated that a higher frequency could capture faster diffusion within the diffusion phenomena.

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This study aims to explore the possibility of detecting indices that could potentially provide warning about the proximity of internal damage to critical levels, beyond which catastrophic fracture is impending. In this direction, advantage was taken of the Cumulative Counts that were recorded during the mechanical loading of specimens made of either plain or fiber-reinforced concrete. The parameter adopted for the analysis was the average rate of change in the Cumulative Counts. Τhe evolution of the specific parameter was considered in the Natural Time Domain, rather than in the conventional time domain. Experimental data from already published three-point bending protocols were used. It was revealed that the specific parameter attains, systematically, a limiting value equal to unity exactly at the instant at which the load reaches its maximum value, which is not identical to the load recorded at the instant of fracture. Similar observations were made for a complementary protocol with uniaxially compressed mortar specimens. The conclusions drawn were supported by the b-values analysis of the respective acoustic data, again in terms of Natural Time. It is, thus, indicated that the evolution of the average rate of change in the Cumulative Counts in the Natural Time Domain provides an index about the proximity of the applied load to a value beyond which the specimen enters into the critical state of impending fracture.

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The northeastern margin of the Tibetan Plateau (NE Tibetan Plateau) exhibits active geological structures and has experienced multiple strong earthquakes, with M ≥ 7, throughout history. Particularly noteworthy is the 1920 M81/2 earthquake in the Haiyuan region that occurred a century ago and is documented as one of the deadliest earthquakes. Consequently, analyzing seismic risks in the northeastern margin of the Tibetan Plateau holds significant importance. The b value, a crucial parameter for seismic activity, plays a pivotal role in seismic hazard analyses. This study calculates the spatial b values in this region based on earthquake catalogs since 1970. The study area encompasses several major active faults, and due to variations in b values across different fault types, traditional grid-search methods may introduce significant errors in calculating the spatial b value within complex fault systems. To address this, we employed the hierarchical space-time point-process (HIST-PPM) method proposed by Ogata. This method avoids partitioning earthquake samples, optimizes parameters using Akaike's Bayesian Information Criterion (ABIC) with entropy maximization, and theoretically allows for a higher spatial resolution and more accurate b value calculations. The results indicate a high spatial heterogeneity in b values within the study area. The northwestern and southeastern regions exhibit higher b values. Along the Haiyuan fault zone, the central rupture zone of the Haiyuan earthquake has relatively higher b values than other regions of this fault zone, which is possibly related to the sufficient release of stress during the main rupture of the Haiyuan earthquake. The b values vary from high in the west to low in the east along the Zhongwei fault. On the West Qinling fault zone, the epicenter of the recent Minxian-Zhangxian earthquake is associated with a low b value. In general, regions with low b values correspond well to areas with moderate-strong seismic events in the past 50 years. The spatial differences in b values may reflect variances in seismic hazards among fault zones and regions within the same fault zone.

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This study conducts an in-depth analysis of the failure behavior of woven GFRP under cyclic loading, leveraging AE sensors for monitoring damage progression. Utilizing destructive testing and AE methods, we observed the GFRP's response to varied stress conditions. Key findings include identifying distinct failure modes of GFRP and the effectiveness of AE sensors in detecting broadband frequency signals indicative of crack initiation and growth. Notably, the Felicity effect was observed in AE signal patterns, marking a significant characteristic of composite materials. This study introduces the Ibe-value, based on statistical parameters, to effectively track crack development from inception to growth. The Ibe-values potential for assessing structural integrity in composite materials is highlighted, with a particular focus on its variation with propagation distance and frequency-dependent attenuation. Our research reveals challenges in measuring different damage modes across frequency ranges and distances. The effectiveness of Ibe-values, combined with the challenges of propagation distance, underscores the need for further investigation. Future research aims to refine assessment metrics and improve crack evaluation methods in composite materials, contributing to the field's advancement.

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Objective:To investigate the clinical effect of high diffusion sensitivity coefficient(high b value)diffusion-weighted imaging(DWI),dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)combined with tumor carbohydrate antigen 125(CA125)in judging the nature of ovarian lesions.Methods:A total of 100 patients with ovarian lesions who were treated in Nantong Haimen People's Hospital from April 2020 to April 2022 were selected for retrospective study.All of them underwent CA125,DWI,DCE-MRI and pathologically qualitative examination.According to the pathological results,58 patients with malignant lesions of ovarian were divided into malignant group and patients with benign lesions of ovarian were divided into benign group.The CA125 levels of the two groups were analyzed and compared,and the results of the receiver operating characteristics(ROC)of different detection methods(DWI with high b value+CA125,DCE-MRI+CA125,DWI with high b value+DCE-MRI+CA125)also were analyzed and compared.Results:The CA125 index of the malignant group was significantly higher than that of the benign group,with a statistically significant difference(t=29.357,P＜0.05),and the CA125 positive rate of the malignant group was significantly better than that of the benign group,with a statistically significant difference(x2=34.456,P＜0.05).The apparent diffusion coefficient(ADC)value[(0.91±0.18)×103mm2/s]of the malignant group was significantly less than that[(33±0.21)×103mm2/s]of the benign group,while the contrast agent volume conversion constant(Ktrans),rate constant(Kep)and the extracellular space volume ratio outside of blood vessels(Ve)of the malignant group were significantly higher than those of the benign group,with significant differences(t=16.863,9.686,10.205,P＜0.05),respectively.The diagnostic accuracy,sensitivity,negative predictive value and positive predictive value of DWI with high b-value+DCE-MRI+CA125 examination method were higher than those of DWI with high b-value + CA125 or DCE-MRI+CA125 examination method in diagnosing malignant ovarian tumors.There were not significant differences in various indicators between DCE-MRI+CA125 examination method and DWI with high b-value +CA125 examination method(P＞0.05).ROC curve analysis showed that the area under curve(AUC)of the DWI with high b-value +DCE-MRI+CA125 examination method was the best(AUC=0.920).Conclusion:The combined examination method of DWI with high b-value + DCE-MRI + CA125 has better overall diagnostic efficiency,which can improve the screening ability of clinical diagnosis for malignant ovarian tumors.It has a certain clinical application value.

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This study demonstrates the feasibility and performance of the point-resolved spectroscopy (PRESS)-based, single-shot diffusion trace-weighted sequence in quantifying the trace apparent diffusion coefficient (ADC) in phantom and in vivo using a 3-T MRI/MRS scanner. The single-shot diffusion trace-weighted PRESS sequence was implemented and compared with conventional diffusion-weighted (DW)-PRESS variants using bipolar and unipolar diffusion-sensitizing gradients. Nine phantom datasets were acquired using each sequence, and seven volunteers were scanned in three different brain regions to determine the range and variability of trace ADC values, and to allow a comparison of trace ADCs among the sequences. This sequence results in a comparatively stable range of trace ADC values that are statistically significantly higher than those produced from unipolar and bipolar DW-PRESS sequences. Only total n-acetylaspartate, total creatine, and total choline were reliably estimated in all sequences with Cramér-Rao lower bounds of, at most, 20%. The larger trace ADCs from the single-shot sequences are probably attributable to the shorter diffusion time relative to the other sequences. Overall, this study presents the first demonstration of the single-shot diffusion trace-weighted sequence in a clinical scanner at 3 T. The results show excellent agreement of phantom trace ADCs computed with all sequences, and in vivo ADCs agree well with the expected differences between gray and white matter. The diffusion trace-weighted sequence could provide an estimate of the trace ADC in a shorter scan time (by nearly a factor of 3) compared with conventional DW-PRESS approaches that require three separate orthogonal directions.

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Diffusion MRI (dMRI) explores tissue microstructures by analyzing diffusion-weighted signal decay measured at different b-values. While relatively low b-values are used for most dMRI models, high b-value diffusion-weighted imaging (DWI) techniques have gained interest given that the non-Gaussian water diffusion behavior observed at high b-values can yield potentially valuable information. In this study, we investigated anomalous diffusion behaviors associated with degeneration of spinal cord tissue using a continuous time random walk (CTRW) model for DWI data acquired across an extensive range of ultrahigh b-values. The diffusion data were acquired in situ from the lumbar level of spinal cords of wild-type and age-matched transgenic SOD1G93A mice, a well-established animal model of amyotrophic lateral sclerosis (ALS) featuring progressive degeneration of axonal tracts in this tissue. Based on the diffusion decay behaviors at low and ultrahigh b-values, we applied the CTRW model using various combinations of b-values and compared diffusion metrics calculated from the CTRW model between the experimental groups. We found that diffusion-weighted signal decay curves measured with ultrahigh b-values (up to 858,022 s/mm2 in this study) were well represented by the CTRW model. The anomalous diffusion coefficient obtained from lumbar spinal cords was significantly higher in SOD1G93A mice compared with control mice (14.7 × 10-5 ± 5.54 × 10-5  vs. 7.87 × 10-5 ± 2.48 × 10-5  mm2 /s, p = 0.01). We believe this is the first study to illustrate the efficacy of the CTRW model for analyzing anomalous diffusion regimes at ultrahigh b-values. The CTRW modeling of ultrahigh b-value dMRI can potentially present a novel approach for noninvasively evaluating alterations in spinal cord tissue associated with ALS pathology.

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Diffusion-weighted double-echo steady-state (dwDESS) MRI with bipolar diffusion gradients is a promising candidate to obtain diffusion weighted images (DWI) free of geometric distortions and with low motion sensitivity. However, a wider clinical application of dwDESS is currently hindered as no method is reported to explicitly calculate the effective b-value of the obtained DWI from the diffusion-gradients applied in the sequence. To this end, a previously described signal model was adapted for dwDESS with bipolar diffusion gradients, which allows to estimate an effective b-value, dubbed b'. Evaluation in phantom examinations was performed on a clinical 1.5 T MR system. Experimental results were compared with theoretical predictions, including the apparent diffusion coefficient (ADC) based on b-values from a standard EPI-DWI sequence and ADC' based on the effective b' from the dwDESS sequence. The adapted signal model was able to describe the experimental results, and the obtained values of ADC' were in line with conventional ADC measurements.

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BACKGROUND AND STUDY OBJECTIVES: A higher b-value Diffusion-weighted imaging (DWI) would improve the contrast between cancerous and noncancerous tissue. Apparent diffusion coefficient (ADC)-histogram analysis is a method that can provide statistical data and quantitative information on tumor heterogeneity. This study aimed to compare two high b-values (1000 and 2000 sec/mm2) DWI in tumor detection and diagnostic performance in identifying early-stage tumor rectal cancer. PATIENTS AND METHODS: This blinded and blinded retrospective study involved 56 patients with rectal cancer and 45 patients. Two radiologists evaluated the qualitative detection parameters and quantitative parameters of the ADC evaluated histogram and compared them between two DWI sequences (b-value for 1000 sec/mm2 and 2000 sec/mm2). The characteristic curves were used to assess diagnostic administration for the ADC histogram in discriminating early-stage tumors. RESULTS: The b-value for 2000 sec/mm2 DWI significantly improved AUCs, sensitivity, specificity, and precision and decreased false-positive rate for detection compared to the b-value for 1000 sec/mm2 (p < 0.05). The mean and fifth percentile ADC value for stage I using the b-value for 1000 sec/mm2 DWI was significantly higher than stage ≥ II (p = 0.036II and 0.016 respectively), as the well as fifth, 10th, mean ADC of the fifth, 10th, and 25th ADC percentile at b-value for 2000 sec/mm2 (p = 0.031, 0.014, 0.035 and 0.025 respectively). The AUCs of the fifth percentile ADC at b-value for 2000 sec/mm2 DWI in both readers in differentiating the stage Ⅰ tumor were the highest (0.732 and 0.751). CONCLUSION: The b-value for 2000 sec/mm2 DWI could improve the accurate detection of rectal cancer. The fifth percentile ADC at b-value for 2000 sec/mm2 sec/mm2 DWI was more useful for discriminating early stage than the b-value for 1000 sec/mm2 DWI.

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In this paper, an approach to perform leak state detection and size identification for industrial fluid pipelines with an acoustic emission (AE) activity intensity index curve (AIIC), using b-value and a random forest (RF), is proposed. Initially, the b-value was calculated from pre-processed AE data, which was then utilized to construct AIICs. The AIIC presents a robust description of AE intensity, especially for detecting the leaking state, even with the complication of the multi-source problem of AE events (AEEs), in which there are other sources, rather than just leaking, contributing to the AE activity. In addition, it shows the capability to not just discriminate between normal and leaking states, but also to distinguish different leak sizes. To calculate the probability of a state change from normal condition to leakage, a changepoint detection method, using a Bayesian ensemble, was utilized. After the leak is detected, size identification is performed by feeding the AIIC to the RF. The experimental results were compared with two cutting-edge methods under different scenarios with various pressure levels and leak sizes, and the proposed method outperformed both the earlier algorithms in terms of accuracy.

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PURPOSE: Accurate preoperative radiological staging of adult-type diffuse glioma is crucial for effective prognostic stratification and selection of appropriate therapeutic interventions. The purpose of this study was to compare the effectiveness of apparent diffusion coefficient (ADC) maps generated from ultrahigh b-value diffusion-weighted imaging (DWI) for molecular grading with that for histological grading of adult-type diffuse glioma, and to evaluate the correlation between these ADC maps and molecular and histological biomarkers. METHODS: This study retrospectively enrolled forty adult-type diffuse glioma patients, diagnosed using the 2021 WHO classification criteria. Preoperative imaging data, including multiple b-value DWI and conventional magnetic resonance imaging, were collected. Tumors were graded using both histological and molecular criteria. Histogram analysis was conducted to generate 14 parameters for each tumor. Receiver operating characteristic curves and the area under the curve (AUC) were used to evaluate tumor grading and molecular status differentiation. Analysis of histological biomarkers was performed by calculating the Pearson and Spearman correlation coefficients of continuous and hierarchical variables, respectively. RESULTS: The intensity-related parameters for molecular grading were found to be superior to those for histological grading for the identification of WHO grade 4 (WHO4) adult-type diffuse glioma. The AUC of both grading systems increased with increasing b-values, with ADC8000-based histogram parameters showing the best results (molecular grading, square root: AUC = 0.897; histological grading, median: AUC = 0.737). The intensity-related parameters could also differentiate molecular WHO4 gliomas from histologically lower-grade gliomas (ADC8000-based square root: AUC = 0.919), and different ADC8000-based kurtosis was observed between molecular and histological WHO4 gliomas (AUC = 0.833). Significant correlations between the Ki-67 index and molecular status prediction for IDH, CDKN2A, and EGFR were also demonstrated. CONCLUSION: The histogram parameters derived from high b-value ADC maps were found to be more effective for differentiating molecular grades of WHO4 adult-type diffuse glioma than for differentiating histological grades.

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Three-component intravoxel incoherent motion (3C-IVIM) imaging with spectral analysis provides a proxy for interstitial fluid (ISF) (e.g., in perivascular spaces (PVS), granting a potential marker for altered cerebral clearance. When 3C-IVIM images are acquired with three orthogonal diffusion-sensitizing directions, these are often averaged into the Trace image. This may result in loss of valuable direction-specific information, particularly in PVS-rich regions (basal ganglia (BG) and centrum semiovale (CSO)). This study assessed the dependence of individual diffusion-sensitizing directions to the ISF fraction in PVS-rich regions. Additionally, we explored the value of diffusion direction-specific information on ISF characteristics in distinguishing thirty-one patients with cognitive impairment (CI) (Alzheimer's disease (n = 15) or Mild Cognitive Impairment (n = 16)) from thirty cognitively healthy elderly controls (CON). Multi-b-value diffusion-weighted images were acquired in three orthogonal directions (L-R (left-right), A-P (anterior-posterior) and S-I (superior-inferior)) at 3 T. Voxel-based spectral analysis using non-negative least squares was conducted to independently analyze the L-R, A-P, S-I, and Trace images. 3C-IVIM measures were first compared between diffusion-sensitizing directions and the Trace within the BG using repeated measures ANOVA. Subsequently, the 3C-IVIM measures were compared per direction between the CI and CSO group in the BG and CSO with multivariable linear regression. Our results show that the ISF fraction significantly differs between all diffusion-sensitizing directions and Trace in the BG, with the highest ISF fraction detected using S-I. Solely using S-I, a higher ISF fraction was identified in CI compared to CON in the BG (p = .020) and CSO (p = .046). Thereby, this study found that the measured ISF fraction depends on the acquired diffusion-sensitizing direction, where S-I is most sensitive to detect ISF and differences between CI and CON. The Trace approach is not always sensitive enough to ISF characteristics. Solely acquiring S-I may offer an alternative to reduce scanning time.

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Diffusion tensor imaging (DTI) in animal models are essential for translational neuroscience studies. A critical step in animal studies is the use of anesthetics. Understanding the influence of specific anesthesia regimes on DTI-derived parameters, such as fractional anisotropy (FA) and mean diffusivity (MD), is imperative when comparing results between animal studies using different anesthetics. Here, the quantification of FA and MD under different anesthetic regimes, alpha-chloralose and isoflurane, is discussed. We also used a range of b-values to determine whether the anesthetic effect was b-value dependent. The first group of rats (n = 6) was anesthetized with alpha-chloralose (80 mg/kg), whereas the second group of rats (n = 7) was anesthetized with isoflurane (1.5%). DTI was performed with b-values of 500, 1500, and 1500s/mm2, and the MD and FA were assessed individually. Anesthesia-specific differences in MD were apparent, as manifested by the higher estimated MD under isoflurane anesthesia than that under alpha-chloralose anesthesia (P < 0.001). MD values increased with decreasing b-value in all regions studied, and the degree of increase when rats were anesthetized with isoflurane was more pronounced than that associated with alpha-chloralose (P < 0.05). FA quantitation was also influenced by anesthesia regimens to varying extents, depending on the brain regions and b-values. In conclusion, both scanning parameters and the anesthesia regimens significantly impacted the quantification of DTI indices.

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