An improved attention module based on nnU-Net for segmenting primary central nervous system lymphoma (PCNSL) in MRI images1.

BACKGROUND: Accurate volumetric segmentation of primary central nervous system lymphoma (PCNSL) is essential for assessing and monitoring the tumor before radiotherapy and the treatment planning. The tedious manual segmentation leads to interindividual and intraindividual differences, while existing automatic segmentation methods cause under-segmentation of PCNSL due to the complex and multifaceted nature of the tumor. OBJECTIVE: To address the challenges of small size, diffused distribution, poor inter-layer continuity on the same axis, and tendency for over-segmentation in brain MRI PCNSL segmentation, we propose an improved attention module based on nnUNet for automated segmentation. METHODS: We collected 114 T1 MRI images of patients in the Huashan Hospital, Shanghai. Then randomly split the total of 114 cases into 5 distinct training and test sets for a 5-fold cross-validation. To efficiently and accurately delineate the PCNSL, we proposed an improved attention module based on nnU-Net with 3D convolutions, batch normalization, and residual attention (res-attention) to learn the tumor region information. Additionally, multi-scale dilated convolution kernels with different dilation rates were integrated to broaden the receptive field. We further used attentional feature fusion with 3D convolutions (AFF3D) to fuse the feature maps generated by multi-scale dilated convolution kernels to reduce under-segmentation. RESULTS: Compared to existing methods, our attention module improves the ability to distinguish diffuse and edge enhanced types of tumors; and the broadened receptive field captures tumor features of various scales and shapes more effectively, achieving a 0.9349 Dice Similarity Coefficient (DSC). CONCLUSIONS: Quantitative results demonstrate the effectiveness of the proposed method in segmenting the PCNSL. To our knowledge, this is the first study to introduce attention modules into deep learning for segmenting PCNSL based on brain magnetic resonance imaging (MRI), promoting the localization of PCNSL before radiotherapy.

Deep learning-accelerated T2WI: image quality, efficiency, and staging performance against BLADE T2WI for gastric cancer.

PURPOSE: The purpose of our study is to investigate image quality, efficiency, and diagnostic performance of a deep learning-accelerated single-shot breath-hold (DLSB) against BLADE for T2-weighted MR imaging (T2WI) for gastric cancer (GC). METHODS: 112 patients with GCs undergoing gastric MRI were prospectively enrolled between Aug 2022 and Dec 2022. Axial DLSB-T2WI and BLADE-T2WI of stomach were scanned with same spatial resolution. Three radiologists independently evaluated the image qualities using a 5-scale Likert scales (IQS) in terms of lesion delineation, gastric wall boundary conspicuity, and overall image quality. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated in measurable lesions. T staging was conducted based on the results of both sequences for GC patients with gastrectomy. Pairwise comparisons between DLSB-T2WI and BLADE-T2WI were performed using the Wilcoxon signed-rank test, paired t-test, and chi-squared test. Kendall's W, Fleiss' Kappa, and intraclass correlation coefficient values were used to determine inter-reader reliability. RESULTS: Against BLADE, DLSB reduced total acquisition time of T2WI from 495 min (mean 4:42 per patient) to 33.6 min (18 s per patient), with better overall image quality that produced 9.43-fold, 8.00-fold, and 18.31-fold IQS upgrading against BALDE, respectively, in three readers. In 69 measurable lesions, DLSB-T2WI had higher mean SNR and higher CNR than BLADE-T2WI. Among 71 patients with gastrectomy, DLSB-T2WI resulted in comparable accuracy to BLADE-T2WI in staging GCs (P > 0.05). CONCLUSIONS: DLSB-T2WI demonstrated shorter acquisition time, better image quality, and comparable staging accuracy, which could be an alternative to BLADE-T2WI for gastric cancer imaging.

Vessel-specific quantification of cerebral venous oxygenation with velocity-encoding preparation and rapid acquisition.

PURPOSE: Non-invasive measurement of cerebral venous oxygenation (Yv) is of critical importance in brain diseases. The present work proposed a fast method to quantify regional Yv map for both large and small veins. METHODS: A new sequence was developed, referred to as TRU-VERA (T2 relaxation under velocity encoding and rapid acquisition, which isolates blood spins from static tissue with velocity-encoding preparation, modulates the T2 weighting of venous signal with T2-preparation and utilizes a bSSFP readout to achieve fast acquisition with high resolution. The sequence was first optimized to achieve best sensitivity for both large and small veins, and then validated with TRUST (T2 relaxation under spin tagging), TRUPC (T2 relaxation under phase contrast), and accelerated TRUPC MRI. Regional difference of Yv was evaluated, and test-retest reproducibility was examined. RESULTS: Optimal Venc was determined to be 3 cm/s, while recovery time and balanced SSFP flip angle within reasonable range had minimal effect on SNR efficiency. Venous T2 measured with TRU-VERA was highly correlated with T2 from TRUST (R2 = 0.90), and a conversion equation was established for further calibration to Yv. TRU-VERA sequences showed consistent Yv estimation with TRUPC (R2 = 0.64) and accelerated TRUPC (R2 = 0.79). Coefficient of variation was 0.84% for large veins and 2.49% for small veins, suggesting an excellent test-retest reproducibility. CONCLUSION: The proposed TRU-VERA sequence is a promising method for vessel-specific oxygenation assessment.

Comprehensive characterization of polyproline tri-helix macrocyclic nanoscaffolds for predictive ligand positioning.

Multivalent ligands hold promise for enhancing avidity and selectivity to simultaneously target multimeric proteins, as well as potentially modulating receptor signaling in pharmaceutical applications. Essential for these manipulations are nanosized scaffolds that precisely control ligand display patterns, which can be achieved by using polyproline oligo-helix macrocyclic nanoscaffolds via selective binding to protein oligomers and cell surface receptors. This work focuses on synthesis and structural characterization of different-sized polyproline tri-helix macrocyclic (PP3M) scaffolds. Through combined analysis of circular dichroism (CD), small- and wide-angle X-ray scattering (SWAXS), electron spin resonance (ESR) spectroscopy, and molecular modeling, a non-coplanar tri-helix loop structure with partially crossover helix ends is elucidated. This structural model aligns well with scanning tunneling microscopy (STM) imaging. The present work enhances the precision of nanoscale organic synthesis, offering prospects for controlled ligand positioning on scaffolds. This advancement paves the way for further applications in nanomedicine through selective protein interaction, manipulation of cell surface receptor functions, and developments of more complex polyproline-based nanostructures.

Echo time optimization for in-vivo measurement of unsaturated lipid resonances using J-difference-edited MRS.

PURPOSE: Measuring lipid composition provides more information than just total lipid content. Hence, the non-invasive measurement of unsaturated lipid protons with both high efficiency and precision is of pressing need. This study was to optimize echo time (TE) for the best resolving of J-difference editing of unsaturated lipid resonances. METHODS: The TE dependence of J-difference-edited (JDE) MRS was verified in the density-matrix simulation, soybean oil phantom, in-vivo experiments of white adipose tissue (WAT), and skeletal muscles using single-voxel MEGA-PRESS sequence at 3T. The peak SNRs and Cramér-Rao lower bounds (CRLBs) acquired at the proposed TE of 45 ms and previously published TE of 70 ms were compared (eight pairs) in WAT, extramyocelluar lipids (EMCLs), and intramyocellular lipids (IMCLs). The lipid composition in skeletal muscles was compared between healthy males (n = 7) and females (n = 7). RESULTS: The optimal TE was suggested as 45 ms. Compared to 70 ms, the mean signal gains at TE of 45 ms were 151% in WAT, 168% in EMCL, 204% in IMCL for allylic resonance, and 52% in EMCL for diallylic resonance. CRLBs were significantly reduced at TE of 45 ms in WAT, EMCL, IMCL for allylic resonance and in EMCL for diallylic resonance. With TE of 45 ms, significant gender differences were found in the lipid composition in EMCL pools, while no difference in IMCL pools. CONCLUSION: The JDE-MRS protocol with TE of 45 ms allows improved quantification of unsaturated lipid resonances in vivo and future lipid metabolism investigations.

3D diffusion MRI with twin navigator-based GRASE and comparison with 2D EPI for tractography in the human brain.

PURPOSE: 3D pulse sequences enable high-resolution acquisition with a high SNR and ideal slice profiles, which, however, is particularly difficult for diffusion MRI (dMRI) due to the additional phase errors from diffusion encoding. METHODS: We proposed a twin navigator-based 3D diffusion-weighted gradient spin-echo (GRASE) sequence to correct the phase errors between shots and between odd and even spin echoes for human whole-brain acquisition. We then compared the SNR of 3D GRASE and 2D simultaneous multi-slice EPI within the same acquisition time. We further tested the performance of 2D versus 3D acquisition at equivalent SNR on fiber tracking and microstructural mapping, using the diffusion tensor and high-order fiber orientation density-based metrics. RESULTS: The proposed twin navigator approach removed multi-shot phase errors to some extent in the whole brain dMRI, and the 2D navigator performed better than the 1D navigator. Comparisons of SNR between the 2D simultaneous multi-slice EPI and 3D GRASE sequences demonstrated that the SNR of the GRASE sequence was 1.4-1.5-fold higher than the EPI sequence at an equivalent scan time. More importantly, we found a significantly higher fiber cross-section in the cerebrospinal tract, as well as richer subcortical fibers (U-fibers) using the 3D GRASE sequence compared to 2D EPI. CONCLUSION: The twin navigator-based 3D diffusion-weighted-GRASE sequence minimized the multishot phase error and effectively improved the SNR for whole-brain dMRI acquisition. We found differences in fiber tracking and microstructural mapping between 2D and 3D acquisitions, possibly due to the different slice profiles.

Convolutional neural network to predict IDH mutation status in glioma from chemical exchange saturation transfer imaging at 7 Tesla.

Background and goal: Noninvasive prediction of isocitrate dehydrogenase (IDH) mutation status in glioma guides surgical strategies and individualized management. We explored the capability on preoperatively identifying IDH status of combining a convolutional neural network (CNN) and a novel imaging modality, ultra-high field 7.0 Tesla (T) chemical exchange saturation transfer (CEST) imaging. Method: We enrolled 84 glioma patients of different tumor grades in this retrospective study. Amide proton transfer CEST and structural Magnetic Resonance (MR) imaging at 7T were performed preoperatively, and the tumor regions are manually segmented, leading to the "annotation" maps that offers the location and shape information of the tumors. The tumor region slices in CEST and T1 images were further cropped out as samples and combined with the annotation maps, which were inputted to a 2D CNN model for generating IDH predictions. Further comparison analysis to radiomics-based prediction methods was performed to demonstrate the crucial role of CNN for predicting IDH based on CEST and T1 images. Results: A fivefold cross-validation was performed on the 84 patients and 4090 slices. We observed a model based on only CEST achieved accuracy of 74.01% ± 1.15%, and the area under the curve (AUC) of 0.8022 ± 0.0147. When using T1 image only, the prediction performances dropped to accuracy of 72.52% ± 1.12% and AUC of 0.7904 ± 0.0214, which indicates no superiority of CEST over T1. However, when we combined CEST and T1 together with the annotation maps, the performances of the CNN model were further boosted to accuracy of 82.94% ± 1.23% and AUC of 0.8868 ± 0.0055, suggesting the importance of a joint analysis of CEST and T1. Finally, using the same inputs, the CNN-based predictions achieved significantly improved performances above those from radiomics-based predictions (logistic regression and support vector machine) by 10% to 20% in all metrics. Conclusion: 7T CEST and structural MRI jointly offer improved sensitivity and specificity of preoperative non-invasive imaging for the diagnosis of IDH mutation status. As the first study of CNN model on imaging acquired at ultra-high field MR, our results could demonstrate the potential of combining ultra-high-field CEST and CNN for facilitating decision-making in clinical practice. However, due to the limited cases and B1 inhomogeneities, the accuracy of this model will be improved in our further study.

Automatic bundle-specific white matter fiber tracking tool using diffusion tensor imaging data: A pilot trial in the application of language-related glioma resection.

Cerebral neoplasms like gliomas may cause intracranial pressure increasing, neural tract deviation, infiltration, or destruction in peritumoral areas, leading to neuro-functional deficits. Novel tracking technology, such as DTI, can objectively reveal and visualize three-dimensional white matter trajectories; in combination with intraoperative navigation, it can help achieve maximum resection whilst minimizing neurological deficit. Since the reconstruction of DTI raw data largely relies on the technical engineering and anatomical experience of the operator; it is time-consuming and prone to operator-induced bias. Here, we develop new user-friendly software to automatically segment and reconstruct functionally active areas to facilitate precise surgery. In this pilot trial, we used an in-house developed software (DiffusionGo) specially designed for neurosurgeons, which integrated a reliable diffusion-weighted image (DWI) preprocessing pipeline that embedded several functionalities from software packages of FSL, MRtrix3, and ANTs. The preprocessing pipeline is as follows: 1. DWI denoising, 2. Gibbs-ringing removing, 3. Susceptibility distortion correction (process if opposite polarity data were acquired), 4. Eddy current and motion correction, and 5. Bias correction. Then, this fully automatic multiple assigned criteria algorithms for fiber tracking were used to achieve easy modeling and assist precision surgery. We demonstrated the application with three language-related cases in three different centers, including a left frontal, a left temporal, and a left frontal-temporal glioma, to achieve a favorable surgical outcome with language function preservation or recovery. The DTI tracking result using DiffusionGo showed robust consistency with direct cortical stimulation (DCS) finding. We believe that this fully automatic processing pipeline provides the neurosurgeon with a solution that may reduce time costs and operating errors and improve care quality and surgical procedure quality across different neurosurgical centers.

Numerical fitting of Extrapolated semisolid Magnetization transfer Reference (NEMR) signals: Improved detection of ischemic stroke.

PURPOSE: To propose a novel Numerical fitting method of the Extrapolated semisolid Magnetization transfer Reference (NEMR) signal for quantifying the CEST effect. THEORY AND METHODS: Modified two-pool Bloch-McConnell equations were used to numerically fit the magnetization transfer (MT) and direct water saturation (DS) signals at far off-resonance frequencies, which was subsequently extrapolated into the frequency range of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) pools. Then the subtraction of the fitted two-pool z-spectrum and the experimentally acquired z-spectrum yielded APT# and NOE# signals mostly free of MT and DS contamination. Several strategies were used to accelerate the NEMR fitting. Furthermore, the proposed NEMR method was compared with the conventional extrapolated semisolid magnetization transfer reference (EMR) and magnetization transfer ratio asymmetry (MTRasym ) methods in simulations and stroke patients. RESULTS: The combination of RF downsampling, MT lineshape look-up table, and conversion of MATLAB code to C code accelerated the NEMR fitting by over 2700-fold. Monte-Carlo simulations showed that NEMR had higher accuracy than EMR and eliminated the requirement of the steady-state condition. In ischemic stroke patients, the NEMR maps at 1 µT removed hypointense artifacts seen on EMR and MTRasym images, and better depicted stroke lesions than EMR. For NEMR, NOE# yielded significantly (p < 0.05) stronger signal contrast between stroke and normal tissues than APT# at 1 µT. CONCLUSION: The proposed NEMR method is suitable for arbitrary saturation settings and can remove MT and DS contamination from the CEST signal for improved detection of ischemic stroke.

The Consistence of Dynamic Contrast-Enhanced MRI and Filter-Exchange Imaging in Measuring Water Exchange Across the Blood-Brain Barrier in High-Grade Glioma.

BACKGROUND: Water exchange across blood-brain barrier (BBB) (WEXBBB ) is an emerging biomarker of BBB dysfunction with potential applications in many brain diseases. Several MRI methods have been proposed to measure WEXBBB , but evidence remains scarce whether different methods can produce comparable WEXBBB . PURPOSE: To explore whether dynamic contrast-enhanced (DCE)-MRI and vascular water exchange imaging (VEXI) could produce comparable WEXBBB in high-grade glioma (HGG) patients. STUDY TYPE: Prospective cross-sectional. SUBJECTS: 13 HGG patients (58.4 ± 9.4 years, 9 females, 4 WHO III and 9 WHO IV). FIELD STRENGTH/SEQUENCE: A 3 T, spoiled gradient-recalled-echo DCE-MRI and VEXI containing two pulsed-gradient spin-echo blocks separated by a mixing block. ASSESSMENTS: The enhanced tumor and contralateral normal-appearing white matter (cNAWM) volume-of-interests (VOIs) were drew by two neuroradiologists. And whole-brain NAWM and normal-appearing gray matter (NAGM) without tumor-affected regions were segmented by automated segmentation algorithm in FSL. STATISTICAL TESTS: Student's t-test was used to evaluate parameters difference between cNAWM and tumor, NAGM and NAWM, respectively. The correlation between vascular water efflux rate constant (kbo ) from DCE-MRI and apparent exchange rate across BBB (AXRBBB ) from VEXI was evaluated by Pearson correlation. P < 0.05 was considered statistically significant. RESULTS: Compared with cNAWM, both kbo and AXRBBB were significantly reduced in tumor (kbo = 3.50 ± 1.18 sec-1 vs. 1.03 ± 0.75 sec-1 ; AXRBBB = 3.54 ± 1.11 sec-1 vs. 1.94 ± 1.04 sec-1 ). Both kbo and AXRBBB showed significantly higher values in NAWM than NAGM (kbo = 3.50 ± 0.59 sec-1 vs. 2.10 ± 0.56 sec-1 ; AXRBBB = 3.35 ± 0.77 sec-1 vs. 2.07 ± 0.52 sec-1 ). The VOI-averaged kbo and AXRBBB were also linearly correlated in tumor, NAWM, and NAGM (r = 0.59). DATA CONCLUSION: DCE-MRI and VEXI showed comparable and correlated WEXBBB in HGG patients, suggesting that the consistence and reliability of these two MRI methods in measuring WEXBBB . EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 1.

Lateralization of temporal lobe epileptic foci with automated chemical exchange saturation transfer measurements at 3 Tesla.

BACKGROUND: Magnetic Resonance Imaging (MRI) is an indispensable tool for the diagnosis of temporal lobe epilepsy (TLE). However, about 30% of TLE patients show no lesion on structural MRI (sMRI-negative), posing a significant challenge for presurgical evaluation. This study aimed to investigate whether chemical exchange saturation transfer (CEST) MRI at 3 Tesla can lateralize the epileptic focus of TLE and study the metabolic contributors to the CEST signal measured. METHODS: Forty TLE subjects (16 males and 24 females) were included in this study. An automated data analysis pipeline was established, including segmentation of the hippocampus and amygdala (HA), calculation of four CEST metrics and quantitative relaxation times (T1 and T2), and construction of prediction models by logistic regression. Furthermore, a modified two-stage Bloch-McConnell fitting method was developed to investigate the molecular imaging mechanism of 3 T CEST in identifying epileptic foci of TLE. FINDINGS: The mean CEST ratio (CESTR) metric within 2.25-3.25 ppm in the HA was the most powerful index in predicting seizure laterality, with an area under the receiver-operating characteristic curve (AUC) of 0.84. And, the combination of T2 and CESTR further increased the AUC to 0.92. Amine and guanidinium moieties were the two leading contributors to the CEST contrast between the epileptogenic HA and the normal HA. INTERPRETATION: CEST at 3 Tesla is a powerful modality that can predict seizure laterality with high accuracy. This study can potentially facilitate the clinical translation of CEST MRI in identifying the epileptic foci of TLE or other localization-related epilepsies. FUNDING: National Natural Science Foundation of China, Science Technology Department of Zhejiang Province, and Zhejiang University.

Vascular-water-exchange MRI (VEXI) enables the detection of subtle AXR alterations in Alzheimer's disease without MRI contrast agent, which may relate to BBB integrity.

Blood-brain barrier (BBB) impairment is an important pathophysiological process in Alzheimer's disease (AD) and a potential biomarker for early diagnosis of AD. However, most current neuroimaging methods assessing BBB function need the injection of exogenous contrast agents (or tracers), which limits the application of these methods in a large population. In this study, we aim to explore the feasibility of vascular water exchange MRI (VEXI), a diffusion-MRI-based method proposed to assess the BBB permeability to water molecules without using a contrast agent, in the detection of the BBB breakdown in AD. We tested VEXI on a 3T MRI scanner on three groups: AD patients (AD group), mild cognitive impairment (MCI) patients due to AD (MCI group), and the age-matched normal cognition subjects (NC group). Interestingly, we find that the apparent water exchange across the BBB (AXRBBB) measured by VEXI shows higher values in MCI compared with NC, and this higher AXRBBB happens specifically in the hippocampus. This increase in AXRBBB value gets larger and extends to more brain regions (medial orbital frontal cortex and thalamus) from MCI group to the AD group. Furthermore, we find that the AXRBBB values of these three regions is correlated significantly with the impairment of respective cognitive domains independent of age, sex and education. These results suggest VEXI is a promising method to assess the BBB breakdown in AD.

Transmembrane water-efflux rate measured by magnetic resonance imaging as a biomarker of the expression of aquaporin-4 in gliomas.

The water-selective channel protein aquaporin-4 (AQP4) contributes to the migration and proliferation of gliomas, and to their resistance to therapy. Here we show, in glioma cell cultures, in subcutaneous and orthotopic gliomas in rats, and in glioma tumours in patients, that transmembrane water-efflux rate is a sensitive biomarker of AQP4 expression and can be measured via conventional dynamic-contrast-enhanced magnetic resonance imaging. Water-efflux rates correlated with stages of glioma proliferation as well as with changes in the heterogeneity of intra-tumoural and inter-tumoural AQP4 in rodent and human gliomas following treatment with temozolomide and with the AQP4 inhibitor TGN020. Regions with low water-efflux rates contained higher fractions of stem-like slow-cycling cells and therapy-resistant cells, suggesting that maps of water-efflux rates could be used to identify gliomas that are resistant to therapies.

Inversion-Recovery-Prepared Oscillating Gradient Sequence Improves Diffusion-Time Dependency Measurements in the Human Brain.

BACKGROUND: Oscillating gradient diffusion MRI (dMRI) enables measurements at a short diffusion-time (td ), but it is challenging for clinical systems. Particularly, the low b-value and low resolution may give rise to cerebrospinal fluid (CSF) contamination. PURPOSE: To assess the effect of CSF partial volume on td -dMRI measurements and efficacy of inversion-recovery (IR) prepared oscillating and pulsed gradient dMRI sequence to improve td -dMRI measurements in the human brain. STUDY TYPE: Prospective. SUBJECTS: Ten normal volunteers and six glioma patients. FIELD STRENGTH/SEQUENCE: A 3 T; three-dimensional (3D) IR-prepared oscillating gradient-prepared gradient spin-echo (GRASE) and two-dimensional (2D) IR-prepared oscillating gradient echo-planar imaging (EPI) sequences. ASSESSMENT: We assessed the td -dependent patterns of apparent diffusion coefficient (ADC) in several gray and white matter structures, including the hippocampal subfields (head, body, and tail), cortical gray matter, thalamus, and posterior white matter in normal volunteers. Pulsed gradient (0 Hz) and oscillating gradients at frequencies of 20 Hz, 40 Hz, and 60 Hz dMRI were acquired with GRASE and EPI sequences with or without the IR module. We also tested the td -dependency patterns in glioma patients using the EPI sequence with or without the IR module. STATISTICAL TESTS: The differences in ADC across the different td s were compared by one-way ANOVA followed by post hoc pairwise t-tests with Bonferroni correction. RESULTS: In the healthy subjects, brain regions that were possibly contaminated by CSF signals, such as the hippocampus (head, body, and tail) and cortical gray matter, td -dependent ADC changes were only significant with the IR-prepared 2D and 3D sequences but not with the non-IR sequences. In brain glioblastomas patients, significantly higher td -dependence was observed in the tumor region with the IR module than that without IR (slope = 0.0196 µm2 /msec2 vs. 0.0034 µm2 /msec2 ). CONCLUSION: The IR-prepared sequence effectively suppressed the CSF partial volume effect and significantly improved the td -dependent measurements in the human brain. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Saturation-prolongated and inhomogeneity-mitigated chemical exchange saturation transfer imaging with parallel transmission.

Chemical exchange saturation transfer (CEST) imaging benefits from a longer saturation duration and a higher saturation duty cycle. Dielectric shading effects occur when the radiofrequency (RF) wavelength approaches the object size. Here, we proposed a simultaneous parallel transmission-based CEST (pTx-CEST) sequence to prolongate the saturation duration at a 100% duty cycle and improve the RF saturation homogeneity in CEST imaging. The simultaneous pTx-CEST sequence was implemented by switching the CEST saturation module from the non-pTx to pTx mode, using the pTx functionality with both transmit channels being driven simultaneously (instead of time-interleaved). The optimization of amplitude ratio and phase difference settings between RF channels for best B1 homogeneity was performed in phantoms of two different sizes mimicking the human brain and abdomen. The optimal amplitude and phase settings generating the best B1 homogeneity in the phantoms were used in pTx-CEST scans of the human study. The comparison of the maximum achievable saturation duration between the non-pTx-CEST and pTx-CEST sequences was performed in a protein phantom, healthy volunteers, and a metastatic brain tumor patient. The optimal amplitude ratio and phase difference setting between transmit channels manifested circular and elliptical polarization in the head-sized and abdomen-sized phantoms. In the brain, the maximum saturation durations achieved at a 100% duty cycle using the simultaneous pTx-CEST sequence were prolonged to 2240, 3220, and 4200 ms compared with 980 ms using the non-pTx-CEST sequence at repetition times of 3, 4, and 5 s, respectively. The longer saturation duration helped improve the image contrast between the tumor and the normal tissue in the patient. The optimized elliptical polarization mode saturation pulses yielded improved uniformity of CEST signals acquired from the human abdomen. The proposed simultaneous pTx-CEST sequence enabled essentially arbitrarily long saturation duration at a 100% duty cycle and helped reduce the dielectric shading effects with the optimized RF setting.

Correction: Lai et al. Sensitivity Enhancement of Group Refractive Index Biosensor through Ring-Down Interferograms of Microring Resonator. Micromachines 2022, 13, 922.

In the original publication [...].

Sensitivity Enhancement of Group Refractive Index Biosensor through Ring-Down Interferograms of Microring Resonator.

In recent years, silicon-on-insulator substrates have been utilized for high-speed and low-power electronic components. Because of the high refractive index contrast of the silicon wire, its photonic device footprint can be significantly reduced. Moreover, the silicon photonic process is compatible with a complementary metal-oxide-semiconductor fabrication, which will benefit the high-density optoelectronic integrated circuits development. Researchers have recently proposed using the microring resonator (MRR) for label-free biosensing applications. The high-quality factor caused by the substantial electric field enhancement within the ring makes the MRR a good candidate for biomolecule detection under low analyte concentration conditions. This paper proposes an MRR chip to be a biosensor on the silicon platform through the relative displacement between the spatial ring-down interferograms at various cladding layers. The higher-order ring-down of the spatial interference wave packet will enhance the biosensing sensitivity after optimizing the coupling, MRR length, and the optical source bandwidth at the fixed optical waveguide loss. Finally, a typical sensitivity of 642,000 nm per refractive index unit is demonstrated under 0.1 µW minimum optical power detection for an MRR with a 100 µm radius. Higher sensitivity can be executed by a narrow bandwidth and lower silicon wire propagation loss.

Multiparametric magnetic resonance imaging for differentiating active from inactive thyroid-associated ophthalmopathy: Added value from magnetization transfer imaging.

PURPOSE: To investigate the feasibility of using magnetization transfer (MT) magnetic resonance imaging for evaluating patients with thyroid-associated ophthalmopathy (TAO), and determine its added value for differentiating active from inactive TAO and predicting clinical activity score (CAS), compared with conventional fat-saturated T2-weighted and diffusion-weighted imaging. METHODS: Orbital MT, fat-saturated T2-weighted, and diffusion-weighted imaging of 60 prospectively enrolled consecutive patients with TAO was analyzed. Simplified histogram parameters (mean, max, min) of magnetization transfer ratio (MTR), signal intensity ratio (SIR), and apparent diffusion coefficient (ADC) at extraocular muscles were calculated for each orbit and compared between the active and inactive groups. RESULTS: Intraclass correlation coefficients of MTRs and SIRs were similar (0.802-0.963 vs 0.812-0.974, respectively), followed by those of ADCs (0.714-0.855). Patients with active TAO showed significantly lower MTRs and higher SIRs and ADCs than those with inactive TAO (P < 0.05). MTRmean achieved the highest area under the curve (AUC) of 0.868 for differentiating active from inactive group, followed by SIRmax (AUC, 0.836). MTRmean also demonstrated a higher and negative correlation with CAS (r = -0.614, P < 0.001) than MTRmax and MTRmin (r = -0.495, P < 0.001; r = -0.243, P = 0.007; respectively). Support vector machine-based analysis revealed that uniting MTRs could prosper concurrently added performance for disease activity differentiation and CAS prediction, compared with merely combining SIRs and ADCs (AUC, 0.933 vs 0.901; r = 0.703 vs. 0.673). CONCLUSIONS: MT imaging could potentially be used as a noninvasive method for differentiating the activity of TAO and predicting CAS, thereby offering added value to conventional SIR and ADC.

Moyamoya disease: A human model for chronic hypoperfusion and intervention in Alzheimer's disease.

Introduction: Chronic cerebral hypoperfusion has been considered the etiology for sporadic Alzheimer's disease (AD). However, no valid clinical evidence exists due to the similar risk factors between cerebrovascular disease and AD. Methods: We used moyamoya disease (MMD) as a model of chronic hypoperfusion and cognitive impairment, without other etiology interference. Results: Based on the previous reports and preliminary findings, we hypothesized that chronic cerebral hypoperfusion could be an independent upstream crucial variable, resulting in AD, and induce pathological hallmarks such as amyloid beta peptide and hyperphosphorylated tau accumulation. Discussion: Timely intervention with revascularisation would help reverse the brain damage with AD hallmarks and lead to cognitive improvement.

Time-Dependent Diffusion MRI for Quantitative Microstructural Mapping of Prostate Cancer.

Background Recently developed time-dependent diffusion MRI has potential in characterizing cellular tissue microstructures; however, its value in imaging prostate cancer (PCa) remains unknown. Purpose To investigate the feasibility of time-dependent diffusion MRI-based microstructural mapping for noninvasively characterizing cellular properties of PCa and for discriminating between clinically significant PCa and clinically insignificant disease. Materials and Methods Men with a clinical suspicion of PCa were enrolled prospectively between October 2019 and August 2020. Time-dependent diffusion MRI data were acquired with pulsed and oscillating gradient diffusion MRI sequences at an equivalent diffusion time of 7.5-30 msec on a 3.0-T scanner. Time-dependent diffusion MRI-based microstructural parameters, including cell diameter, intracellular volume fraction, cellularity, and diffusivities, were estimated with a two-compartment model. These were compared for different International Society of Urological Pathology grade groups (GGs), and their performance in discriminating clinically significant PCa (GG >1) from clinically insignificant disease (benign and GG 1) was determined with a linear discriminant analysis. The fitted microstructural parameters were validated by means of correlation with histopathologic measurements. Results In the 48 enrolled men, the time-dependent diffusion MRI measurements showed that higher GG was correlated with higher intracellular volume fraction and higher cellularity (intracellular volume fraction = 0.22, 0.36, 0.34, 0.37, and 0.40 in GGs 1-5, respectively; P < .001 at one-way analysis of variance), while lower cell diameter was found at higher GGs (diameter = 23.4, 18.3, 19.2, 17.9, and 18.5 µm in GGs 1-5, respectively; P = .002). Among all measurements derived from time-dependent diffusion MRI, cellularity achieved the highest diagnostic performance, with an accuracy of 92% (44 of 48 participants) and area under the receiver operating characteristic curve of 0.96 (95% CI: 0.87, 0.99) in discriminating clinically significant PCa from clinically insignificant disease. Microstructural mapping was supported by positive correlations between time-dependent diffusion MRI-based and pathologic examination-based intracellular volume fraction (r = 0.83; P < .001). Conclusion Time-dependent diffusion MRI-based microstructural mapping correlates with pathologic findings and demonstrates promise for characterizing prostate cancer. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Chatterjee and Oto in this issue.