Demonstration of magnetic resonance Z-spectral imaging for fatty acid characterization of bone marrow at 3 T.

Magnetic resonance Z-spectral imaging (ZSI) has emerged as a new approach to measure fat fraction (FF). However, its feasibility for fat spectral imaging remains to be elucidated. In this study, a single-slice ZSI sequence dedicated to fat spectral imaging was designed, and its capability for fatty acid characterization was investigated on peanut oil samples, a multiple-vial fat-water phantom with varied oil volumes, and vertebral body marrow in healthy volunteers and osteoporosis patients at 3 T. The peanut oil spectrum was also recorded with a 400-MHz NMR spectrometer. A Gaussian-Lorentzian sum model was used to resolve water and six fat signals of the pure oil sample or four fat signals of the fat-water phantom or vertebral bone marrow from Z spectra. Fat peak amplitudes were normalized to the total peak amplitude of water and all fat signals. Normalized fat peak amplitudes and FF were quantified and compared among vials of the fat-water phantom or between healthy volunteers and osteoporosis patients. An unpaired student's t-test and Pearson's correlation were conducted, with p less than 0.05 considered statistically significant. The results showed that the peanut oil spectra measured with the ZSI technique were in line with respective NMR spectra, with amplitudes of the six fat signal peaks significantly correlated between the two methods (y = x + 0.001, r = 0.996, p < 0.001 under a repetition time of 1.6 s; and y = 1.026x - 0.003, r = 0.996, p < 0.001 under a repetition time of 3.1 s). Moreover, ZSI-measured FF exhibited a significant correlation with prepared oil volumes (y = 0.876x + 1.290, r = 0.996, p < 0.001). The osteoporosis patients showed significantly higher normalized fat peak amplitudes and FF in the L4 vertebral body marrow than the healthy volunteers (all p < 0.01). In summary, the designed ZSI sequence is feasible for fatty acid characterization, and has the potential to facilitate the diagnosis and evaluation of diseases associated with fat alterations at 3 T.

Nucleos(t)ide analogues altered quasispecies composition of hepatitis B virus (HBV)-resistant mutations in serum HBV DNA and serum HBV RNA.

Serum hepatitis B virus (HBV) RNA is a new serological indicator reflecting viral replication with good clinical application prospects. This study aimed to clarify the dynamic changes of serum HBV RNA levels and the quasispecies of HBV RNA virus-like particles in nucleos(t)ide analogues (NAs)-experienced chronic hepatitis B (CHB) patients harboring NAs-resistant mutations and their identifiable effects on NAs resistance. We included CHB patients who were on long-term NAs treatment and with HBV DNA rebound. The longitudinally dynamics of serum HBV RNA levels were quantitatively detected, and the quasispecies differences between serum HBV DNA and serum HBV RNA were compared by high-throughput sequencing. The effect of NAs concentration pressure on altering the resistance mutations quasispecies proportion of HBV DNA and HBV RNA in cell supernatant was analyzed in vitro. A total of 447 serum samples from 36 CHB patients treated with NAs were collected. The median follow-up period was 47 months (about 4 years), and the longest follow-up period was 117 months (about 10 years). Our results showed that HBV RNA could reflect virological breakthrough in 23 (64%, 23/36) patients, and serum HBV RNA rebound earlier than HBV DNA in 12 (52%, 12/23) patients. However, serum HBV RNA remained at a consistently high level and did not fluctuate significantly with the HBV DNA rebound in 6 of 36 patients. In addition, serum HBV RNA was not consistently detectable in 7 of the 36 patients, and their serum HBV RNA was undetectable even after HBV DNA had rebounded. The proportion of drug-resistant mutations in HBV DNA was higher than that of HBV RNA by high-throughput sequencing. The results of in vitro experiments showed that the viral strains with drug-resistant mutation in HBV DNA in cell supernatants gradually become the dominant strains with the increase of NAs concentrations. Serum HBV RNA levels can reflect virological breakthrough in most NAs- treated CHB patients, but there are certain limitations. NAs alter the quasispecies composition of serum HBV DNA and serum HBV RNA, resulting in a higher detection rate of drug-resistant mutations in serum HBV DNA than in serum HBV RNA.

Fatty Acids Composition of the Sacroiliac Joint in Axial Spondyloarthritis: Analysis Using 3.0 T Chemical Shift-Encoded MRI.

BACKGROUND: Axial spondyloarthritis (axSpA) is a group of inflammatory diseases that may lead to ankylosis of the sacroiliac joint and spine. Fat lesion in the sacroiliac joint is an important feature in diagnosis and disease progression of axSpA. However, whether there is alteration of fatty acids (FAs) composition has not been investigated using MRI. PURPOSE: To investigate bone marrow FA composition of the sacroiliac joint in patients with axSpA compared to controls. STUDY TYPE: Prospective. SUBJECTS: Eighty five participants (mean age, 32.3 ± 6.1 years): 48 axSpA (25 male, 23 female) and 37 non-SpA controls (18 male, 19 female). FIELD STRENGTH/SEQUENCE: 3.0 T/Two multiple gradient-echo chemical shift-encoded (CSE) MRI which differed only in echo times (TEs) were scanned consecutively. ASSESSMENT: Axial multi-echo CSE MRI was performed in the sacroiliac joints in vivo. Regions of interest (ROIs) were manually placed on subchondral bone with and without fat lesion in axSpA patients, and on subchondral bone without fat lesion in controls. FA composition was computed within the ROIs using a nonlinear least square method from literature. STATISTICAL TESTS: Intergroup comparisons were performed using t tests. RESULTS: In axSpA, male patients had significantly higher monounsaturated FA compared to controls in areas with fat lesion in the sacrum (+12%) and in the ilium (+9%), and in areas without fat lesion in the sacrum (+10%). Significantly lower polyunsaturated FAs were found in areas with fat lesion in the sacrum (-10%) and ilium (-11%), and lower saturated FAs were found in areas without fat lesion in the sacrum (-6%). In female, patients with axSpA had significantly higher saturated FAs in areas with fat lesion in the ilium (+7%) in comparison to controls. DATA CONCLUSION: FA composition of the sacroiliac joint alters in patients with axSpA, and it can be detected using CSE MRI based analysis.

Intermediate-weighted MRI with fat suppression (IW-FS): diagnostic performance for bone marrow edema and erosion detection in axial spondyloarthritis.

BACKGROUND: Bone marrow edema (BME) and erosion of the sacroiliac joint are both key lesions for diagnosing axial spondyloarthritis (axSpA) on magnetic resonance imaging (MRI). PURPOSE: To qualitatively and quantitatively compare intermediate-weighted MRI with fat suppression (IW-FS) with T2-weighted short tau inversion recovery (T2-STIR) in assessment of sacroiliac BME and erosion in axSpA. MATERIAL AND METHODS: Patients aged 18-60 years with axSpA were prospectively enrolled. All patients underwent a 3.0-T MRI examination of the sacroiliac joints. Para-coronal IW-FS, T2-STIR, and T1-weighted (T1W) images were acquired. BME and erosion were scored by two readers in consensus on IW-FS and STIR using a modified Spondyloarthritis Research Consortium of Canada (SPARCC) scoring system. Consensus scores on T1WI were used as the reference for erosion. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured for BME. RESULTS: In total, 49 patients (mean age=33.4 ± 7.6 years) were included. More patients were scored as having BME on T2-STIR (36 vs. 29, P = 0.016). SPARCC-BME score on IW-FS was lower than that acquired on T2-STIR (mean, 11.5 vs. 14.7, P = 0.002). SNR and CNR of BME were both lower on IW-FS than on T2-STIR (mean SNR, 118 vs. 218, P < 0.001; mean CNR, 44 vs. 137, P < 0.001). The sensitivity of erosion detection was higher on IW-FS (83%) than on T2-STIR (54%, P = 0.006). CONCLUSION: IW-FS is not sufficient for BME detection using T2-STIR as the reference standard in patients with axSpA. IW-FS has a much higher sensitivity than T2-STIR for erosion detection in the sacroiliac joint.

Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based on contrast-enhanced spectral mammography.

OBJECTIVE: To investigative the performance of intratumoral and peritumoral radiomics based on contrast-enhanced spectral mammography (CESM) to preoperatively predict the effect of the neoadjuvant chemotherapy (NAC) of breast cancers. MATERIALS AND METHODS: A total of 118 patients with breast cancer who underwent preoperative CESM and NAC from July 2017 to June 2020 were retrospectively analyzed, and the patients were grouped into training (n = 81) and test sets (n = 37) according to the CESM examination time. NAC effect for each patient was assessed by pathology. Intratumoral and peritumoral radiomics features were extracted from CESM images, and feature selection was performed through the Mann-Whitney U test and least absolute shrinkage and selection operator regression (LASSO). Five radiomics signatures based on intratumoral regions, 5-mm peritumoral regions, 10-mm peritumoral regions, intratumoral regions + 5-mm peritumoral regions, and intratumoral regions + 10-mm peritumoral regions were calculated through a linear combination of selected features weighted by their respective coefficients. The prediction performance of radiomics signatures was assessed by the area under the receiver operator characteristic (ROC) curve, the precision-recall (P-R) curve, the calibration curve, and decision curve analysis (DCA). RESULTS: Ten radiomics features were selected to establish the radiomics signature of intratumoral regions + 5-mm peritumoral regions, which yielded a maximum AUC of 0.85 (95% CI, 0.72-0.98) in the test set. The calibration curves, P-R curves, and DCA showed favorable predictive performance of the five radiomics signatures. CONCLUSION: The intratumoral and peritumoral radiomics based on CESM exhibited potential for predicting the NAC effect in breast cancer, which could guide treatment decisions. KEY POINTS: • The intratumoral and peritumoral CESM-based radiomics signatures show good performance in predicting the NAC effect in breast cancer.

Combining Magnetic Resonance Diffusion-Weighted Imaging with Prostate-Specific Antigen to Differentiate Between Malignant and Benign Prostate Lesions.

BACKGROUND We aimed to develop a combined model of quantitative parameters derived from 3 different magnetic resonance imaging (MRI) diffusion models and laboratory data related to prostate-specific antigen (PSA) for differentiating between prostate cancer (PCa) and benign lesions. MATERIAL AND METHODS Eighty-four patients pathologically confirmed as having PCa or benign disease were enrolled. All patients underwent multiparametric MRI before biopsy, added intravoxel incoherent motion (IVIM) imaging, and diffusion kurtosis imaging (DKI). The following data were collected: quantitative parameters of diffusion-weighted imaging (DWI), IVIM, and DKI, preoperative total PSA, free/total PSA ratio, and PSA density (PSAD) values. A combined logistic regression model was established by above MRI quantitative parameters and PSA data to diagnose PCa. The Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) was used to assess the lesions for comparison. RESULTS Thirty-two patients had PCa and 52 patients had benign lesions. In multivariate logistic regression analysis, only apparent diffusion coefficient (ADC) and PSAD were significant variables (P<0.05) and were thus retained in the model. The area under curve value of the combined model (0.911) was higher than that of ADC, PSAD, and PI-RADS v2 (0.887, 0.861, and 0.859, respectively) in univariate analysis, but without any statistically significant differences. The combined model generated greater clinical benefit than the independent application of ADC, PSAD, and PI-RADS v2. CONCLUSIONS ADC and PSAD were the 2 most important metrics for distinguishing PCa from benign lesions. The combined model of ADC and PSAD demonstrated satisfactory discrimination and improved clinical net benefit.

Nanomedicine Directs Neuronal Differentiation of Neural Stem Cells via Silencing Long Noncoding RNA for Stroke Therapy.

Transplantation of neural stem cells (NSCs) is a promising treatment paradigm to replace lost neurons and reconstruct the damaged neural circuit after ischemic stroke. However, most transplanted NSCs often differentiate into astrocytes rather than functional neurons, and the poor neuronal differentiation adversely affects the therapeutic outcome of NSCs and limits their clinical translation for stroke therapy. Herein, a theranostic nanomedicine is developed to codeliver superparamagnetic iron oxide nanoparticles (SPIO) and small interfering RNA/antisense oligonucleotides (siRNA/ASO) against Pnky long noncoding RNA (lncRNA) into NSCs. This nanomedicine not only directs neuronal differentiation of NSCs through silencing the Pnky lncRNA but also allows an in vivo tracking of NSCs with magnetic resonance imaging. The enhanced neuronal differentiation of NSCs significantly improved the structural and functional recovery of the damaged brain after a stroke. The results demonstrate the great potential of the multifunctional nanomedicine targeting lncRNA to enhance stem cell-based therapies for a stroke.

Clinical characteristics and neuroimaging findings of seven patients with Dyke Davidoff Masson syndrome.

BACKGROUND: DDMS is a rare disease diagnosed by clinical and radiological characteristics. But the complexity of radiological and clinical manifestations of DDMS has become a challenge diagnostically. To date, the reported cases with DDMS had highly varied clinical manifestations including seizures, contralateral hemiplegia/hemiparesis, facial asymmetry, mental retardation, etc. In addition to typical clinical findings, some new characteristics have been recently added to the spectrum of DDMS. However, few cases have been reported to be associated with neuropsychiatric symptoms according to the literature. This study aimed to investigate the neuropsychiatric manifestations associated with Dyke-Davidoff-Masson syndrome (DDMS) and related imaging findings. METHODS: This study included 7 patients diagnosed with DDMS between 2014 and 2020. The clinical characteristics, neuropsychiatric manifestations, and radiological results were retrospectively evaluated. RESULTS: Seven patients (five males and two females) with a mean age of 28.0 ± 9.73 (range 15.0-41.0) years were included. Five patients were admitted to the psychiatric unit due to psychological and behavioral disorders. Two patients were referred to the neurology unit mainly due to epilepsy. Six patients had epileptic seizures, 4 had hemiplegia, 3 had mental retardation, 2 patients had external ear deformities, and 2 had facial asymmetry. Neuropsychiatric symptoms were presented in 6 (85.7 %) cases. Cases 2-6 developed affective disorders. Deficits in verbal communication, impairment of social interaction, lack of insight, adulia and hypobulia appeared in cases 1-4. Schizophrenia with apathy, and epileptic schizoid psychosis were observed in cases 4 and 5 respectively. Case 6 had behavioral disorders, hyperactivity, tic disorder, mental retardation, anxiety, catatonic symptoms and suicidal tendency. Case 7 had seizures and mental retardation, and no psychiatric symptoms were presented. Radiological examinations showed unilateral cerebral atrophy, enlarged lateral ventricles, and various compensatory hypertrophy of the skull in all cases. The midline structure has shifted to the affected side in 5(71.4 %) cases. Atrophy of the basal ganglia or brain stem was observed in 4(57.1 %) cases. CONCLUSIONS: The hallmark imaging manifestations of DDMS facilitated the diagnosis in most cases. This study illustrated that a variety of psychoneurotic disorders and ear abnormalities were correlated with DDMS.

An iterative reconstruction method for sparse-projection data for low-dose CT.

Reducing X-ray radiation is beneficial for reducing the risk of cancer in patients. There are two main approaches for achieving this goal namely, one is to reduce the X-ray current, and another is to apply sparse-view protocols to do image scanning and projections. However, these techniques usually lead to degradation of the reconstructed image quality, resulting in excessive noise and severe edge artifacts, which seriously affect the diagnosis result. In order to overcome such limitation, this study proposes and tests an algorithm based on guided kernel filtering. The algorithm combines the characteristics of anisotropic edges between adjacent image voxels, expresses the relevant weights with an exponential function, and adjusts the weights adaptively through local gray gradients to better preserve the image structure while suppressing noise information. Experiments show that the proposed method can effectively suppress noise and preserve the image structure. Comparing with similar algorithms, the proposed algorithm greatly improves the peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and root mean square error (RMSE) of the reconstructed image. The proposed algorithm has the best effect in quantitative analysis, which verifies the effectiveness of the proposed method and good image reconstruction performance. Overall, this study demonstrates that the proposed method can reduce the number of projections required for repeated CT scans and has potential for medical applications in reducing radiation doses.

Radiomics in RayPlus: a Web-Based Tool for Texture Analysis in Medical Images.

Radiomics has been shown to have considerable potential and value in quantifying the tumor phenotype and predicting the treatment response. In most scenarios, the commercial and open-source software programs are available for quantitative analysis in medical images to streamline radiomics research. However, at this stage, most of these programs are local applications and require users to have experience in programming and software engineering, which clinicians usually do not have. Therefore, in this article, a web-based tool was proposed to flexibly support radiomics research workflow tasks. Radiomics in RayPlus requires zero installation, is easy to maintain, and accessible anywhere via any PC or MAC with an Internet connection. The system provides functions including multimodality image import and viewing, ROI definition, feature extraction, and data sharing. As a web application, it appears an effective way to multi-institution and multi-department collaborative radiomics research and moreover, its transparency, flexibility, and portability can greatly accelerate the pace of clinical data analysis.

The CT and MRI features of benign calvarium and skull base osteoblastoma.

OBJECTIVE: We retrospectively reviewed the CT and MRI features of patients with benign osteoblastoma in the calvarium and skull base (CSBOB). METHODS: Nine cases of pathologically confirmed benign CSBOB were analysed retrospectively. The patients had undergone CT and/or MRI. Tumour location, size, and imaging features were reviewed and recorded. RESULTS: The patients included four males and five females with a mean age of 27.0 years (age 14-40 years). The tumours were located in the frontal bone in 3 patients, the occipital bone in 3 patients, and in the parietal bone, sphenoid bone, and skull base in 1 patient each. On CT, the tumours measured 5.1 ± 3.3 (1.8-8.4) cm. Seven tumours were shown to have caused expansile bony destruction with an eggshell appearance and varying degrees of calcification or matrix mineralization. Multiple septa were observed in 5 tumours. Intracranial growth was observed in 5 tumours. On MRI, 7 tumours showed heterogeneous hypo- to isointensity on T1WI. Heterogeneous high signal patterns with low signal rims and septa were observed in 6 tumours on T2WI, and 4 showed a fluid-fluid level. On contrast-enhanced imaging, 6 tumours showed peripheral and septal enhancement, and 2 showed the dural tail sign. CONCLUSIONS: Benign CSBOB is a rare tumour characterized by expansile bony destruction, septa, a sclerotic rim and calcification or matrix mineralization on CT and MRI. ADVANCES IN KNOWLEDGE: The findings from this study contribute to a better understanding of benign CSBOB and provide valuable imaging features that can aid in its diagnosis and differentiation from other tumours in the calvarium and skull base.

Fully automated assessment of the future liver remnant in a blood-free setting via CT before major hepatectomy via deep learning.

OBJECTIVES: To develop and validate a deep learning (DL) model for automated segmentation of hepatic and portal veins, and apply the model in blood-free future liver remnant (FLR) assessments via CT before major hepatectomy. METHODS: 3-dimensional 3D U-Net models were developed for the automatic segmentation of hepatic veins and portal veins on contrast-enhanced CT images. A total of 170 patients treated from January 2018 to March 2019 were included. 3D U-Net models were trained and tested under various liver conditions. The Dice similarity coefficient (DSC) and volumetric similarity (VS) were used to evaluate the segmentation accuracy. The use of quantitative volumetry for evaluating resection was compared between blood-filled and blood-free settings and between manual and automated segmentation. RESULTS: The DSC values in the test dataset for hepatic veins and portal veins were 0.66 ± 0.08 (95% CI: (0.65, 0.68)) and 0.67 ± 0.07 (95% CI: (0.66, 0.69)), the VS values were 0.80 ± 0.10 (95% CI: (0.79, 0.84)) and 0.74 ± 0.08 (95% CI: (0.73, 0.76)), respectively No significant differences in FLR, FLR% assessments, or the percentage of major hepatectomy patients were noted between the blood-filled and blood-free settings (p = 0.67, 0.59 and 0.99 for manual methods, p = 0.66, 0.99 and 0.99 for automated methods, respectively) according to the use of manual and automated segmentation methods. CONCLUSION: Fully automated segmentation of hepatic veins and portal veins and FLR assessment via blood-free CT before major hepatectomy are accurate and applicable in clinical cases involving the use of DL. CRITICAL RELEVANCE STATEMENT: Our fully automatic models could segment hepatic veins, portal veins, and future liver remnant in blood-free setting on CT images before major hepatectomy with reliable outcomes. KEY POINTS: Fully automatic segmentation of hepatic veins and portal veins was feasible in clinical practice. Fully automatic volumetry of future liver remnant (FLR)% in a blood-free setting was robust. No significant differences in FLR% assessments were noted between the blood-filled and blood-free settings.

Application of Spinal Subtraction and Bone Background Fusion CTA in the Accurate Diagnosis and Evaluation of Spinal Vascular Malformations.

BACKGROUND AND PURPOSE: Accurate pretreatment diagnosis and assessment of spinal vascular malformations using spinal CTA are crucial for patient prognosis, but the postprocessing reconstruction may not be able to fully depict the lesions due to the complexity inherent in spinal anatomy. Our purpose was to explore the application value of the spinal subtraction and bone background fusion CTA (SSBBF-CTA) technique in precisely depicting and localizing spinal vascular malformation lesions. MATERIALS AND METHODS: In this retrospective study, patients (between November 2017 and November 2022) with symptoms similar to those of spinal vascular malformations were divided into diseased (group A) and nondiseased (group B) groups. All patients underwent spinal CTA using Siemens dual-source CT. Multiplanar reconstruction; routine bone subtraction, and SSBBF-CTA images were obtained using the snygo.via and ADW4.6 postprocessing reconstruction workstations. Multiple observers researched the following 3 aspects: 1) preliminary screening capability using original images with multiplanar reconstruction CTA, 2) the accuracy and stability of the SSBBF-CTA postprocessing technique, and 3) diagnostic evaluation of spinal vascular malformations using the 3 types of postprocessing images. Diagnostic performance was analyzed using receiver operating characteristic analysis, while reader or image differences were analyzed using the Wilcoxon signed-rank test or the Kruskal-Wallis rank sum test. RESULTS: Forty-nine patients (groups A and B: 22 and 27 patients; mean ages, 44.0 [SD, 14.3] years and 44.6 [SD,15.2] years; 13 and 16 men) were evaluated. Junior physicians showed lower diagnostic accuracy and sensitivity using multiplanar reconstruction CTA (85.7% and 77.3%) than senior physicians (93.9% and 90.9%, 98% and 95.5%). Short-term trained juniors achieved SSBBF-CTA image accuracy similar to that of experienced physicians (P > .05). In terms of the visualization and localization of spinal vascular malformation lesions (nidus/fistula, feeding artery, and drainage vein), both multiplanar reconstruction and SSBBF-CTA outperformed routine bone subtraction CTA (P = .000). Compared with multiplanar reconstruction, SSBBF-CTA allowed less experienced physicians to achieve superior diagnostic capabilities (comparable with those of experienced radiologists) more rapidly (P < .05). CONCLUSIONS: The SSBBF-CTA technique exhibited excellent reproducibility and enabled accurate pretreatment diagnosis and assessment of spinal vascular malformations with high diagnostic efficiency, particularly for junior radiologists.

A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detection.

Accuratedetection and segmentation of brain tumors is critical for medical diagnosis. However, current supervised learning methods require extensively annotated images and the state-of-the-art generative models used in unsupervised methods often have limitations in covering the whole data distribution. In this paper, we propose a novel framework Two-Stage Generative Model (TSGM) that combines Cycle Generative Adversarial Network (CycleGAN) and Variance Exploding stochastic differential equation using joint probability (VE-JP) to improve brain tumor detection and segmentation. The CycleGAN is trained on unpaired data to generate abnormal images from healthy images as data prior. Then VE-JP is implemented to reconstruct healthy images using synthetic paired abnormal images as a guide, which alters only pathological regions but not regions of healthy. Notably, our method directly learned the joint probability distribution for conditional generation. The residual between input and reconstructed images suggests the abnormalities and a thresholding method is subsequently applied to obtain segmentation results. Furthermore, the multimodal results are weighted with different weights to improve the segmentation accuracy further. We validated our method on three datasets, and compared with other unsupervised methods for anomaly detection and segmentation. The DSC score of 0.8590 in BraTs2020 dataset, 0.6226 in ITCS dataset and 0.7403 in In-house dataset show that our method achieves better segmentation performance and has better generalization.

Fast and robust pulsed chemical exchange saturation transfer (CEST) MRI using a quasi-steady-state (QUASS) algorithm at 3 T.

Chemical exchange saturation transfer (CEST) has emerged as a powerful technique to image dilute labile protons. However, its measurement depends on the RF saturation duration (Tsat) and relaxation delay (Trec). Although the recently developed quasi-steady-state (QUASS) solution can reconstruct equilibrium CEST effects under continuous-wave RF saturation, it does not apply to pulsed-CEST MRI on clinical scanners with restricted hardware or specific absorption rate limits. This study proposed a QUASS algorithm for pulsed-CEST MRI and evaluated its performance in muscle CEST measurement. An approximated expression of a steady-state pulsed-CEST signal was incorporated in the off-resonance spin-lock model, from which the QUASS pulsed-CEST effect was derived. Numerical simulation, creatine phantom, and healthy volunteer scans were conducted at 3 T. The CEST effect was quantified with asymmetry analysis in the simulation and phantom experiments. CEST effects of creatine, amide proton transfer, phosphocreatine, and combined magnetization transfer and nuclear Overhauser effects were isolated from a multi-pool Lorentzian model in muscles. Apparent and QUASS CEST measurements were compared under different Tsat/Trec and duty cycles. Paired Student's t-test was employed with P < 0.05 as statistically significant. The simulation, phantom, and human studies showed the strong impact of Tsat/Trec on apparent CEST measurements, which were significantly smaller than the corresponding QUASS CEST measures, especially under short Tsat/Trec times. In comparison, the QUASS algorithm mitigates such impact and enables accurate CEST measurements under short Tsat/Trec times. In conclusion, the QUASS algorithm can accelerate robust pulsed-CEST MRI, promising the efficient detection and evaluation of muscle diseases in clinical settings.

A novel automatic segmentation method directly based on magnetic resonance imaging K-space data for auxiliary diagnosis of glioma.

Background: The use of segmentation architectures in medical imaging, particularly for glioma diagnosis, marks a significant advancement in the field. Traditional methods often rely on post-processed images; however, key details can be lost during the fast Fourier transformation (FFT) process. Given the limitations of these techniques, there is a growing interest in exploring more direct approaches. The adaption of segmentation architectures originally designed for road extraction for medical imaging represents an innovative step in this direction. By employing K-space data as the modal input, this method completely eliminates the information loss inherent in FFT, thereby potentially enhancing the precision and effectiveness of glioma diagnosis. Methods: In the study, a novel architecture based on a deep-residual U-net was developed to accomplish the challenging task of automatically segmenting brain tumors from K-space data. Brain tumors from K-space data with different under-sampling rates were also segmented to verify the clinical application of our method. Results: Compared to the benchmarks set in the 2018 Brain Tumor Segmentation (BraTS) Challenge, our proposed architecture had superior performance, achieving Dice scores of 0.8573, 0.8789, and 0.7765 for the whole tumor (WT), tumor core (TC), and enhanced tumor (ET) regions, respectively. The corresponding Hausdorff distances were 2.5649, 1.6146, and 2.7187 for the WT, TC, and ET regions, respectively. Notably, compared to traditional image-based approaches, the architecture also exhibited an improvement of approximately 10% in segmentation accuracy on the K-space data at different under-sampling rates. Conclusions: These results show the superiority of our method compared to previous methods. The direct performance of lesion segmentation based on K-space data eliminates the time-consuming and tedious image reconstruction process, thus enabling the segmentation task to be accomplished more efficiently.

Correction: MnO2/Ce6 microbubble-mediated hypoxia modulation for enhancing sono-photodynamic therapy against triple negative breast cancer.

Correction for 'MnO2/Ce6 microbubble-mediated hypoxia modulation for enhancing sono-photodynamic therapy against triple negative breast cancer' by Ping Li et al., Biomater. Sci., 2024, https://doi.org/10.1039/d3bm00931a.

MnO2/Ce6 microbubble-mediated hypoxia modulation for enhancing sono-photodynamic therapy against triple negative breast cancer.

Sono-photodynamic therapy (SPDT) has emerged as a promising treatment modality for triple negative breast cancer (TNBC). However, the hypoxic tumor microenvironment hinders the application of SPDT. Herein, in this study, a multifunctional platform (MnO2/Ce6@MBs) was designed to address this issue. A sono-photosensitizer (Ce6) and a hypoxia modulator (MnO2) were loaded into microbubbles and precisely released within tumor tissues under ultrasound irradiation. MnO2in situ reacted with the excess H2O2 and H+ and produced O2 within the TNBC tumor, which alleviated hypoxia and augmented SPDT by increasing ROS generation. Meanwhile, the reaction product Mn2+ was able to achieve T1-weighted MRI for enhanced tumor imaging. Additionally, Ce6 and microbubbles served as a fluorescence imaging contrast agent and a contrast-enhanced ultrasound imaging agent, respectively. In in vivo anti-tumor studies, under the FL/US/MR imaging guidance, MnO2/Ce6@MBs combined with SPDT significantly reversed tumor hypoxia and inhibited tumor growth in 4T1-tumor bearing mice. This work presents a theragnostic system for reversing tumor hypoxia and enhancing TNBC treatment.

HLA-DQA1 expression is associated with prognosis and predictable with radiomics in breast cancer.

BACKGROUND: High HLA-DQA1 expression is associated with a better prognosis in many cancers. However, the association between HLA-DQA1 expression and prognosis of breast cancer and the noninvasive assessment of HLA-DQA1 expression are still unclear. This study aimed to reveal the association and investigate the potential of radiomics to predict HLA-DQA1 expression in breast cancer. METHODS: In this retrospective study, transcriptome sequencing data, medical imaging data, clinical and follow-up data were downloaded from the TCIA ( https://www.cancerimagingarchive.net/ ) and TCGA ( https://portal.gdc.cancer.gov/ ) databases. The clinical characteristic differences between the high HLA-DQA1 expression group (HHD group) and the low HLA-DQA1 expression group were explored. Gene set enrichment analysis, Kaplan‒Meier survival analysis and Cox regression were performed. Then, 107 dynamic contrast-enhanced magnetic resonance imaging features were extracted, including size, shape and texture. Using recursive feature elimination and gradient boosting machine, a radiomics model was established to predict HLA-DQA1 expression. Receiver operating characteristic (ROC) curves, precision-recall curves, calibration curves, and decision curves were used for model evaluation. RESULTS: The HHD group had better survival outcomes. The differentially expressed genes in the HHD group were significantly enriched in oxidative phosphorylation (OXPHOS) and estrogen response early and late signalling pathways. The radiomic score (RS) output from the model was associated with HLA-DQA1 expression. The area under the ROC curves (95% CI), accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the radiomic model were 0.866 (0.775-0.956), 0.825, 0.939, 0.7, 0.775, and 0.913 in the training set and 0.780 (0.629-0.931), 0.659, 0.81, 0.5, 0.63, and 0.714 in the validation set, respectively, showing a good prediction effect. CONCLUSIONS: High HLA-DQA1 expression is associated with a better prognosis in breast cancer. Quantitative radiomics as a noninvasive imaging biomarker has potential value for predicting HLA-DQA1 expression.