Magnetic Resonance Sequences Research Articles

High-precision MRI of liver and hepatic lesions on gadoxetic acid-enhanced hepatobiliary phase using a deep learning technique.

The purpose of this study was to investigate whether the high-precision magnetic resonance (MR) sequence using modified Fast 3D mode wheel and Precise IQ Engine (PIQE), that was collected in a wheel shape with sequential data filling in the k-space in the phase encode-slice encode plane, is feasible for breath-hold (BH) three-dimensional (3D) T1-weighted imaging of the hepatobiliary phase (HBP) of gadoxetic acid-enhanced MRI in comparison to the compressed sensing (CS) sequence using Advanced Intelligent Clear-IQ Engine (AiCE). This retrospective study included 54 patients with focal hepatic lesions who underwent dynamic contrast-enhanced MRI. Both standard HBP images using CS with AiCE and high-precision HBP images using modified Fast 3D mode wheel and PIQE were obtained. Image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were evaluated using the Wilcoxon signed-rank test. p values of < 0.05 were considered to be statistically significant. Scores for image noise, conspicuity of liver contours and intrahepatic structures, and overall image quality in high-precision HBP imaging using modified Fast 3D mode wheel and PIQE were significantly higher than those in HBP imaging using CS and AiCE (all p < 0.001). There was no significant difference in the presence of artifact and motion-related blurring. There were no significant differences between the sequences in SNR (p = 0.341) or CNR (p = 0.077). The detection rate of focal hepatic lesions was 71.4-85.3% in CS with AiCE, and 82.2-95.8% in modified Fast 3D mode wheel and PIQE. A high-precision MR sequence using a modified Fast 3D mode wheel and PIQE is applicable for the HBP of BH 3D T1-weighted imaging.

A novel non-contrast agent-enhanced 3D whole-heart magnetic resonance sequence for congenital heart disease patients: the REACT Study.

The three-dimensional balanced-steady-state-free-precession (3D bSSFP) whole-heart (WH) technique has long been used to depict cardiac morphology in congenital heart disease (CHD) but is prone to banding artifacts. The Relaxation Enhanced Angiography without Contrast and Triggering (REACT) sequence is an alternative method that is resistant to off-resonance effects. To evaluate cardiac structures and great vessels in CHD patients using 3D WH REACT sequence and compare it to 3D WH bSSFP sequence. This study was approved by the Institutional Review Board. Thirty CHD patients were prospectively enrolled. Contrast-to-noise ratio (CNR), image quality, and cross-sectional area (CSA) were analyzed. Categorical data were compared with a Wilcoxon signed-rank test and normally distributed variables with a t-test. Thirty patients (16 females) participated in this study (median age 17, range 5months to 52years). REACT showed higher CNR in all pulmonary veins (all P<0.05), while 3D bSSFP had higher CNR in the right ventricle (P<0.001) and right pulmonary artery, (P=0.04). Image quality favored 3D bSSFP in the right atrium and ventricle (both P<0.001), main pulmonary artery (P=0.02), and coronary arteries (left: P<0.001, right: P=0.01). REACT outperformed 3D bSSFP for the pulmonary veins (all P<0.05) from image quality perspective. CSA measurements were not significantly different between REACT and 3D bSSFP (all P≥0.05). The REACT method is associated with improved image quality and CNR for pulmonary veins, with CSA measurements concordant with 3D bSSFP in CHD patients, while bSSFP shows better performance for imaging cardiac chambers and coronary arteries.

Image quality of the non-contrast BOOST cardiac magnetic resonance sequence to visualize the pulmonary veins in patients with atrial fibrillation

Abstract Background In patients with atrial fibrillation (AF), imaging examinations have an important role in planning ablation by imaging the pulmonary veins (PV). The PV anatomy is conventionally assessed before ablation using computer tomography (CT) or 3 dimensional (3D) contrast-enhanced cardiac magnetic resonance (CMR) imaging. The new 3-dimensional, free-breathing BOOST (Bright-blood and black-blOOd phase SensiTive inversion recovery) cardiac magnetic resonance (CMR) sequence is suitable for imaging the left atrium without the addition of contrast agent. Purpose The aim of our study was to investigate the BOOST sequence for the imaging of PVs, and the effect of heart rate and rhythm on image quality. Methods Forty-seven patients underwent and BOOST CMR before ablation, 25 of them had also left atrial CT angiography (CTA). The BOOST sequence was performed using T2 preparation pre-pulse (T2prep) and magnetization transfer preparation (MTC) techniques. The image quality was analyzed using a subjective Likert scale and quantitatively by determining the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Heart rate and rhythm were assessed by 12-lead ECG. Results MTC-BOOST images were suitable for PVs analysis in all cases, whereas the assessment of PVs on T2prep-BOOST images was inadequate in the majority of cases due to artifacts. CTA showed the same PV anatomy as assessed with BOOST CMR. Based on the operating electrophysiologists’ subjective opinion, the quality of the CTA scans was better compared with BOOST sequence. Still, they found the CMR images appropriate for procedural planning in 43 out of 47 cases (91%). SNR and CNR values of the MTC-BOOST bright-blood images were higher if patients had sinus rhythm. We found a significant or nearly significant negative correlation between heart rate and the SNR and CNR values of MTC-BOOST bright-blood images. Conclusions MTC-BOOST images are suitable for visualisation of PVs, producing diagnostic image quality in 100% of cases. In the majority of cases, MTC-BOOST images were appropriate for procedural planning before ablation. Image quality is affected by the patients' heart rate and frequency. Figure 1: MTC BOOST bright blood image of the left atrium and the right pulmonary veins (arrows)

Extracellular vesicles characterization in patients with hypertrophic cardiomyopathy

Abstract Background Hypertrophic cardiomyopathy (HCM) is a genetic disorder, diagnosed according to the presence of phenotypical traits of the myocardium. A specific biomarker which can associate with the severity of HCM is lacking. Extracellular Vesicles (EVs), nanoparticles released by cells into biological fluids, hold promise as accessible diagnostic tools, as their abundance and molecular composition can reflect the severity of cardiac diseases (Rizzuto 2024). We aim at characterising plasma-derived EVs isolated from 28 HCM patients and 18 healthy volunteers (CTR). Methods The whole cohort underwent transthoracic echocardiography, whereas magnetic resonance and exome sequencing was performed on HCM patients. EVs were isolated via ultracentrifugation from plasma of both groups. Quantitative and qualitative assessments of EVs were performed by nanoparticle tracking analysis, transmission electron microscopy, Western blot, targeted (Olink) and untargeted (nLC-MS/MS) proteomics and FACS analysis. Plasma-derived EV subpopulations were characterised according to their cellular origin. Data are expressed as median and interquartile range (25th, 75th). Results Most patients were male (68% HCM and 66% CTR) with a median age of 58 (49-69) years (HCM) and 47 (44-52) (CTR). Among HCM patients, missense mutations in the MYH7 gene were the most identified. The median maximum wall thickness (WTMax) in HCM was 16 mm (15-19) vs 8 mm (7-9) in CTR. The isolated EVs expressed tetraspanins (CD9, CD63 and CD81), Alix and β-integrin and showed an intact phospholipid bilayer of 100 nm in size. EV concentration was reduced in HCM vs CTRL, respectively 2.8*109 EV/ml/cell count (2*109-4*109) and 4.6*10⁹ EV/ml/cell count (3*109-6*109). Among 15 plasma-derived EV subpopulations studied, those released from platelets (CD41a) and activated platelets (CD62P and CD40L) were increased in HCM patients vs CTR by 1.7 fold. Negative associations were found between E/e’, parameter of diastolic function, and cardiomyocyte-derived EVs (r= -0.2658), and between left ventricle ejection fraction and platelet-derived EVs (r=-0.2189); a positive correlation was found between WTMax and EVs derived from activated endothelial cells (r=0.2330). The proteomic analysis of EVs shows an enrichment in proteins related to platelets adhesion and inflammation in HCM patients. Conclusions HCM patients present a peculiar phenotypic pattern of EVs that may associate with diagnostic clinical features of HCM.

Texture Analysis and Prediction of Response to Neoadjuvant Treatment in Patients with Locally Advanced Rectal Cancer

Background: The purpose of this study is to determine the relationship between the texture analysis extracted from preoperative rectal magnetic resonance (MR) studies and the response to neoadjuvant treatment. Materials and Methods: In total, 88 patients with rectal adenocarcinoma who underwent staging MR between 2017 and 2022 were retrospectively enrolled. After the completion of neoadjuvant treatment, they underwent surgical resection. The tumour regression grade (TRG) was collected. Patients with TRG 1–2 were classified as responders, while patients with TRG 3 to 5 were classified as non-responders. A texture analysis was conducted using LIFEx software (v 7.6.0), where T2-weighted MR sequences on oriented axial planes were uploaded, and a region of interest (ROI) was manually drawn on a single slice. Features with a Spearman correlation index &gt; 0.5 have been discarded, and a LASSO feature selection has been applied. Selected features were trained using bootstrapping. Results: According to the TRG classes, 49 patients (55.8%) were considered responders, while 39 (44.2) were non-responders. Two features were associated with the responder class: GLCM_Homogeneity and Discretized Histo Entropy log 2. Regarding GLCM_Homogeneity, the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were 0.779 (95% CIs = 0.771–0.816), 86% (80–90), and 67% (60–71). Regarding Discretized Histo Entropy log 2, we found 0.775 AUC (0.700–0.801), 80% sensitivity (74–83), and 63% specificity (58–69). Combining both radiomics features the radiomics signature diagnostic accuracy increased (AUC = 0.844). Finally, the AUC of 1000 bootstraps were 0.810. Conclusions: Texture analysis can be considered an advanced tool for determining a possible correlation between pre-surgical MR data and the response to neoadjuvant therapy.

Three-Dimensional Magnetic Resonance Imaging in the Musculoskeletal System: Clinical Applications and Opportunities to Improve Imaging Speed and Resolution.

Although conventional 2-dimensional magnetic resonance (MR) sequences have traditionally comprised the foundational imaging strategy for visualization of musculoskeletal anatomy and pathology, the emergence of isotropic volumetric 3-dimensional sequences offers to advance musculoskeletal evaluation with comparatively similar image quality and diagnostic performance, shorter acquisition times, and the added advantages of improved spatial resolution and multiplanar reformation capability. The purpose of this review article is to summarize the available 3-dimensional MR sequences and their role in the management of patients with musculoskeletal disorders, including sports imaging, rheumatologic conditions, peripheral nerve imaging, bone and soft tissue tumor imaging, and whole-body MR imaging.

Magnetic resonance cavitation imaging for the monitoring of ultrasound therapies

Objective.Focused ultrasound (FUS) is a promising non-invasive therapeutic approach that can be used to generate thermal and non-thermal bioeffects. Several non-thermal FUS therapies rely on FUS-induced oscillations of microbubbles (MBs), a phenomenon referred to as cavitation. Cavitation monitoring in real time is essential to ensure both the efficacy and the safety of FUS therapies. This study aims to introduce a new magnetic resonance (MR) method for cavitation monitoring during FUS therapies.Approach.By finely synchronizing the FUS pulse with an accelerated turbo spin-echo MR sequence, the cavitation effect could be quantitatively estimated on the acquired images at 1-Hz refresh rate. The proposed method was assessed in vitro in a water bath. A series of FUS pulses were generated on a silicone tube filled with MBs at different acoustic pressures (0.07-2.07 MPa) and pulse durations (20-2000μs). MR images and passive cavitation detection (PCD) signals were simultaneously acquired for each FUS pulse.Main results.Inertial cavitation was found to induce a quantitatively interpretable signal loss on the MR image. The transition from stable to inertial cavitation was identified on MR cavitation maps with high repeatability. These results were found to be in good agreement with PCD measurements in terms of pressure thresholds between stable and inertial cavitation. MR cavitation imaging was shown to be sensitive to short and even ultrashort FUS pulses, from 2 ms down to 20μs. The presented theoretical model suggests that the signal loss in MR cavitation imaging relies on susceptibility changes related to the diameter of the oscillating MBs.Significance.The proposed MR cavitation imaging method can both locate and characterize cavitation activity. It has therefore the potential to improve the efficacy and safety of FUS therapies, particularly for localized drug delivery applications.

Evaluation of Inflammatory Disease Activity in the Sacroiliac Joints Using Magnetic Resonance Imaging: A Comparative Analysis of Short-Tau Inversion Recovery, Post-Contrast, and Diffusion-Weighted Imaging –Preliminary Study

Introduction: It is essential to detect sacroiliitis earlier to decrease morbidity and unwanted complications such as ankylosing of sacroiliac joints. In recent studies, magnetic resonance imaging (MRI) serves as a key diagnostic tool for identifying sacroiliitis and is now included in the diagnostic criteria. We aim to detect the utility of diffusion-weighted imaging on the MRI in diagnosing sacroiliitis and measure ADC values for the response to treatment in future studies. Materials -methods: There were 39 patients (16 male, 20 female). A 1.5 Tesla MR device with a pelvic coil was used. The sequences were T1 (before and after intravenous contrast administration of gadolinium), T2-weighted fast field echo, short tau inversion recovery (STIR), diffusion-weighted (DW) images, and apparent diffusion coefficient (ADC) mapping. Sacroiliac joints were divided into four quadrants, and two radiologists interpreted all the sequences by giving scores from 0 to 3 depending on bone marrow edema from none to severe. The concordance of scores assigned to STIR, T1-weighted gadolinium-enhanced images, ADC mapping, and diffusion-weighted MR images was evaluated by calculating intraclass correlation coefficients. Results: A statistically significant positive correlation was observed between the activity scores derived from short tau inversion recovery (STIR) and other magnetic resonance (MR) sequences, namely T1-weighted gadolinium-enhanced images, apparent diffusion coefficient (ADC) mapping, and diffusion-weighted MR images. Conclusion: Active bone marrow abnormalities were identified with comparable efficacy using STIR imaging and other MR sequences (T1W-Gad, ADC mapping, DW-MR). In our study, we tried to emphasize the role of the diffusion-weighted images near the other sequences. Diffusion is a fast, easy-applied sequence. After increased experience in the diffusion-weighted images, routine application of this sequence will increase, and even becoming one of the diagnostic criteria will be inevitable. The difference in DWI from the other sequences is that it is measurable. The response to treatment may be followed up by ADC values.

Comparison between the diagnostic utility of three-dimensional fluid attenuated inversion recovery (3D FLAIR) and three dimensional double inversion recovery (3D DIR) magnetic resonance sequences in the assessment of overall load of multiple sclerosis lesions in the brain

BackgroundMultiple sclerosis (MS) is a complex CNS demyelinating disease. Assessment of MS plaques in specific anatomic locations in the brain was challenging to detect by conventional MRI sequences. So, this study aimed to compare the diagnostic accuracy of 3D FLAIR (Fluid attenuation inversion recovery), or 3D DIR (Double inversion recovery) sequences to conventional 2D FLAIR and T2 sequences in detecting MS plaques in different anatomic sites, as well as counting the total lesion burden.MethodsA comparative cross-sectional study enrolled 30 MS patients on the basis of McDonald’s criteria 2017. All participants underwent a brain MRI study including 3D FLAIR or 3D DIR sequences, conventional 2D FLAIR, and T2 sequences.ResultsNo statistically significant difference between the 3D DIR and 3D FLAIR in total lesion (plaque) burden results; however, when each is compared to the conventional ones, both are superior. 3D FLAIR detected the most significant number of plaques in the periventricular region, followed by 2D FLAIR and T2W sequences, with 3D DIR being the least accurate in this region. Meanwhile, 3D DIR was the most precise and can detect a statistically significant number of cortical plaques compared to the 3D FLAIR and the conventional sequences. No statistically significant results on which sequence is best in regard to infratentorial plaque detection.Conclusion3D FLAIR and 3D DIR were superior to 2D FLAIR and T2 sequences in detecting overall lesion burden in MS. Moreover, the 3D DIR sequence was the most precise in the detection of the cortical plaques.

Optimal Magnetic Resonance Sequence for Assessment of Central Cartilage Tumor Scalloping

Abstract Background Magnetic resonance imaging (MRI) is key in evaluating central cartilage tumors. The BACTIP (Birmingham Atypical Cartilaginous Tumour Imaging Protocol) protocol assesses central cartilage tumor risk based on the tumor size and degree of endosteal scalloping on MRI. It provides a management protocol for assessment, follow-up, or referral of central cartilage tumors. Objective Our study compared four MRI sequences: T1-weighted (T1-w), fluid sensitive (Short Tau Inversion Recovery (STIR)- weighted, STIR-w), and grayscale inversions (T1-w GSI and short tau inversion recovery [STIR] GSI) to see how reliably endosteal scalloping was detected. Materials and Methods Two senior consultant musculoskeletal radiologists with experience reviewed randomly selected 60 representative central cartilage tumor cases with varying degree of endosteal scalloping to reflect a spectrum of BACTIP pathologies. The endosteal scalloping was graded as per the definition of BACTIP A, B, and C. They agreed on a consensus BACTIP grade for each of the 240 key images (60 cases × 4 sequences), which was considered the final “consensus” BACTIP grade. These 240 images were then randomized into a test set and given to two fellowship-trained consultant musculoskeletal radiologists for analysis. They assigned a BACTIP grade to each of the 240 selected images while being blinded to the final “consensus” BACTIP grade. The training set was further subdivided into three groups based on the MR image quality (good quality, average quality, and poor quality) to ascertain if the quality of the acquired images influenced intraobserver and interobserver agreements on the BACTIP grading. The two observers were blinded to the grade assigned to the image quality. Results Linearly weighted kappa analysis was performed to measure the agreement between the BACTIP grading answers by two observers and the “consensus” BACTIP grading answers, as well as the BACTIP grading agreement between the two observers themselves.The analysis revealed that T1-w and STIR-w sequences demonstrated more consistent and higher agreement across different image qualities. However, the T1-w GSI and STIR-w GSI sequences exhibited lower agreement, particularly for poor-quality images. T1-w imaging demonstrated substantial agreement between BACTIP gradings for poor-quality images, suggesting potential resilience of T1-w sequence in challenging imaging conditions. Conclusion T1-w imaging is the best sequence for BACTIP grading of endosteal scalloping, followed by fluid-sensitive STIR sequences.

Cardiac magnetic resonance imaging in the evaluation and management of mitral valve prolapse - a comprehensive review.

Mitral valve prolapse is a common valve disorder that usually has a benign prognosis unless there is significant regurgitation or LV impairment. However, a subset of patients are at an increased risk of ventricular arrhythmias and sudden cardiac death, which has led to the recognition of "arrhythmic mitral valve prolapse" as a clinical entity. Emerging risk factors include mitral annular disjunction and myocardial fibrosis. While echocardiography remains the primary method of evaluation, cardiac magnetic resonance has become crucial in managing this condition. Cine magnetic resonance sequences provide accurate characterization of prolapse and annular disjunction, assessment of ventricular volumes and function, identification of early dysfunction and remodeling, and quantitative assessment of mitral regurgitation when integrated with flow imaging. However, the unique strength of magnetic resonance lies in its ability to identify tissue changes. T1 mapping sequences identify diffuse fibrosis, in turn related to early ventricular dysfunction and remodeling. Late gadolinium enhancement sequences detect replacement fibrosis, an independent risk factor for ventricular arrhythmias and sudden cardiac death. There are consensus documents and reviews on the use of cardiac magnetic resonance specifically in arrhythmic mitral valve prolapse. However, in this article, we propose an algorithm for the broader use of cardiac magnetic resonance in managing this condition in various scenarios. Future advancements may involve implementing techniques for tissue characterization and flow analysis, such as 4D flow imaging, to identify patients with ventricular dysfunction and remodeling, increased arrhythmic risk, and more accurate grading of mitral regurgitation, ultimately benefiting patient selection for surgical therapy.

Synthetic CT generation based on multi-sequence MR using CycleGAN for head and neck MRI-only planning.

The purpose of this study is to investigate the influence of different magnetic resonance (MR) sequences on the accuracy of generating computed tomography (sCT) images for nasopharyngeal carcinoma based on CycleGAN. In this study, 143 patients' head and neck MR sequence (T1, T2, T1C, and T1DIXONC) and CT imaging data were acquired. The generator and discriminator of CycleGAN are improved to achieve the purpose of balance confrontation, and a cyclic consistent structure control domain is proposed in terms of loss function. Four different single-sequence MR images and one multi-sequence MR image were used to evaluate the accuracy of sCT. During the model testing phase, five testing scenarios were employed to further assess the mean absolute error, peak signal-to-noise ratio, structural similarity index, and root mean square error between the actual CT images and the sCT images generated by different models. T1 sequence-based sCT achieved better results in single-sequence MR-based sCT. Multi-sequence MR-based sCT achieved better results with T1 sequence-based sCT in terms of evaluation metrics. For metrological evaluation, the global gamma passage rate of sCT based on sequence MR was greater than 95% at 3%/3mm, except for sCT based on T2 sequence MR. We developed a CycleGAN method to synthesize CT using different MR sequences, this method shows encouraging potential for dosimetric evaluation.

Importance of T1-Mapping Sequence in Patients with Hypertrophic Cardiomyopathy without Foci of Non-Ischemic Myocardial Injury in Late Gadolinium Enhancement Sequence.

The aim of this study was to assess the importance of T1-mapping sequences in the diagnosis of hypertrophic cardiomyopathy (HCM) in patients without foci of non-ischemic myocardial injury in classic cardiac magnetic resonance (CMR) sequences. Two groups were compared: 28 patients with HCM, without any foci of myocardial injury in the late gadolinium enhancement (LGE) sequence (HCM group), and 28 patients without cardiomyopathy (CON group). Classic CMR sequences and T1-mapping sequences were performed. The following parameters were assessed: T1 time of the whole left ventricular myocardium, T1 time of myocardium in the basal, middle and apical layers of the left ventricle, and T1 time in individual segments of the left ventricular myocardium. Myocardial extracellular volume (ECV) was assessed similarly. ECV was significantly higher in the HCM group than in the CON group, for the whole left ventricular myocardium, for the basal and apical layers of the left ventricle, and for segments 1-3, 8, and 13-16 of the left ventricle. Regression analysis showed that a higher left-ventricular mass index (LVMI), a higher body mass index and older age are factors independently associated with a higher ECV of the whole myocardium but only in the group with LVMI ≥ 131.84 g/m2. In patients with HCM without foci of non-ischemic myocardial injury, higher ECV values of the left ventricular myocardium are observed.

Deep learning automatic semantic segmentation of glioblastoma multiforme regions on multimodal magnetic resonance images.

In patients having naïve glioblastoma multiforme (GBM), this study aims to assess the efficacy of Deep Learning algorithms in automating the segmentation of brain magnetic resonance (MR) images to accurately determine 3D masks for 4 distinct regions: enhanced tumor, peritumoral edema, non-enhanced/necrotic tumor, and total tumor. A 3D U-Net neural network algorithm was developed for semantic segmentation of GBM. The training dataset was manually delineated by a group of expert neuroradiologists on MR images from the Brain Tumor Segmentation Challenge 2021 (BraTS2021) image repository, as ground truth labels for diverse glioma (GBM and low-grade glioma) subregions across four MR sequences (T1w, T1w-contrast enhanced, T2w, and FLAIR) in 1251 patients. The in-house test was performed on 50GBM patients from our cohort (PerProGlio project). By exploring various hyperparameters, the network's performance was optimized, and the most optimal parameter configuration was identified. The assessment of the optimized network's performance utilized Dice scores, precision, and sensitivity metrics. Our adaptation of the 3D U-net with additional residual blocks demonstrated reliable performance on both the BraTS2021 dataset and the in-house PerProGlio cohort, employing only T1w-ce sequences for enhancement and non-enhanced/necrotic tumor models and T1w-ce + T2w + FLAIR for peritumoral edema and total tumor. The mean Dice scores (training and test) were 0.89 and 0.75; 0.75 and 0.64; 0.79 and 0.71; and 0.60 and 0.55, for total tumor, edema, enhanced tumor, and non-enhanced/necrotic tumor, respectively. The results underscore the high precision with which our network can effectively segment GBM tumors and their distinct subregions. The level of accuracy achieved agrees with the coefficients recorded in previous GBM studies. In particular, our approach allows model specialization for each of the different tumor subregions employing only those MR sequences that provide value for segmentation.

Cardiovascular Magnetic Resonance Radiomics to Identify Components of the Extracellular Matrix in Dilated Cardiomyopathy.

Current cardiovascular magnetic resonance sequences cannot discriminate between different myocardial extracellular space (ECSs), including collagen, noncollagen, and inflammation. We sought to investigate whether cardiovascular magnetic resonance radiomics analysis can distinguish between noncollagen and inflammation from collagen in dilated cardiomyopathy. We identified data from 132 patients with dilated cardiomyopathy scheduled for an invasive septal biopsy who underwent cardiovascular magnetic resonance at 3 T. Cardiovascular magnetic resonance imaging protocol included native and postcontrast T1 mapping and late gadolinium enhancement (LGE). Radiomic features were computed from the midseptal myocardium, near the biopsy region, on native T1, extracellular volume (ECV) map, and LGE images. Principal component analysis was used to reduce the number of radiomic features to 5 principal radiomics. Moreover, a correlation analysis was conducted to identify radiomic features exhibiting a strong correlation (r>0.9) with the 5 principal radiomics. Biopsy samples were used to quantify ECS, myocardial fibrosis, and inflammation. Four histopathological phenotypes were identified: low collagen (n=20), noncollagenous ECS expansion (n=49), mild to moderate collagenous ECS expansion (n=42), and severe collagenous ECS expansion (n=21). Noncollagenous expansion was associated with the highest risk of myocardial inflammation (65%). Although native T1 and ECV provided high diagnostic performance in differentiating severe fibrosis (C statistic, 0.90 and 0.90, respectively), their performance in differentiating between noncollagen and mild to moderate collagenous expansion decreased (C statistic: 0.59 and 0.55, respectively). Integration of ECV principal radiomics provided better discrimination and reclassification between noncollagen and mild to moderate collagen (C statistic, 0.79; net reclassification index, 0.83 [95% CI, 0.45-1.22]; P<0.001). There was a similar trend in the addition of native T1 principal radiomics (C statistic, 0.75; net reclassification index, 0.93 [95% CI, 0.56-1.29]; P<0.001) and LGE principal radiomics (C statistic, 0.74; net reclassification index, 0.59 [95% CI, 0.19-0.98]; P=0.004). Five radiomic features per sequence were identified with correlation analysis. They showed a similar improvement in performance for differentiating between noncollagen and mild to moderate collagen (native T1, ECV, LGE C statistic, 0.75, 0.77, and 0.71, respectively). These improvements remained significant when confined to a single radiomic feature (native T1, ECV, LGE C statistic, 0.71, 0.70, and 0.64, respectively). Radiomic features extracted from native T1, ECV, and LGE provide incremental information that improves our capability to discriminate noncollagenous expansion from mild to moderate collagen and could be useful for detecting subtle chronic inflammation in patients with dilated cardiomyopathy.

Ultra-short time-echo based ray tracing for transcranial focused ultrasound aberration correction in human calvaria.

Magnetic resonance guided transcranial focused ultrasound holds great promises for treating neurological disorders. This technique relies on skull aberration correction which requires computed tomography (CT) scans of the skull of the patients. Recently, ultra-short time-echo (UTE) magnetic resonance (MR) sequences have unleashed the MRI potential to reveal internal bone structures. In this study, we measure the efficacy of transcranial aberration correction using UTE images.&#xD;Approach. We compare the efficacy of transcranial aberration correction using UTE scans to CT based correction on four skulls and two targets using a clinical device (Exablate Neuro, Insightec, Israel). We also evaluate the performance of a custom ray tracing algorithm using both UTE and CT estimates of acoustic properties and compare these against the performance of the manufacturer's proprietary aberration correction software. &#xD;Main results. UTE estimated skull maps in Hounsfield units (HU) had a mean absolute error of 242 ± 20 HU (n=4). The UTE skull maps were sufficiently accurate to improve pressure at the target (no correction: 0.44 ± 0.10, UTE correction: 0.79 ± 0.05, manufacturer CT: 0.80 ± 0.05), pressure confinement ratios (no correction: 0.45 ± 0.10, UTE correction: 0.80 ± 0.05, manufacturer CT: 0.81 ± 0.05), and targeting error (no correction: 1.06 ± 0.42 mm, UTE correction 0.30 ± 0.23 mm, manufacturer CT: 0.32 ± 0.22) (n=8 for all values). When using CT, our ray tracing algorithm performed slightly better than UTE based correction with pressure at the target (UTE: 0.79 ± 0.05, CT: 0.84 ± 0.04), pressure confinement ratios (UTE: 0.80 ± 0.05, CT: 0.84 ± 0.04), and targeting error (UTE: 0.30 ± 0.23 mm, CT: 0.17 ± 0.15). &#xD;Significance. These 3D transcranial measurements suggest that UTE sequences could replace CT scans in the case of MR guided focused ultrasound with minimal reduction in performance which will avoid ionizing radiation exposure to the patients and reduce procedure time and cost.&#xD.

Multi-sequence generative adversarial network: better generation for enhanced magnetic resonance imaging images.

MRI is one of the commonly used diagnostic methods in clinical practice, especially in brain diseases. There are many sequences in MRI, but T1CE images can only be obtained by using contrast agents. Many patients (such as cancer patients) must undergo alignment of multiple MRI sequences for diagnosis, especially the contrast-enhanced magnetic resonance sequence. However, some patients such as pregnant women, children, etc. find it difficult to use contrast agents to obtain enhanced sequences, and contrast agents have many adverse reactions, which can pose a significant risk. With the continuous development of deep learning, the emergence of generative adversarial networks makes it possible to extract features from one type of image to generate another type of image. We propose a generative adversarial network model with multimodal inputs and end-to-end decoding based on the pix2pix model. For the pix2pix model, we used four evaluation metrics: NMSE, RMSE, SSIM, and PNSR to assess the effectiveness of our generated model. Through statistical analysis, we compared our proposed new model with pix2pix and found significant differences between the two. Our model outperformed pix2pix, with higher SSIM and PNSR, lower NMSE and RMSE. We also found that the input of T1W images and T2W images had better effects than other combinations, providing new ideas for subsequent work on generating magnetic resonance enhancement sequence images. By using our model, it is possible to generate magnetic resonance enhanced sequence images based on magnetic resonance non-enhanced sequence images. This has significant implications as it can greatly reduce the use of contrast agents to protect populations such as pregnant women and children who are contraindicated for contrast agents. Additionally, contrast agents are relatively expensive, and this generation method may bring about substantial economic benefits.

Changes in soil organic carbon components and microbial community following spent mushroom substrate application.

While spent mushroom substrate (SMS) has shown promise in increasing soil organic carbon (SOC) and improving soil quality, research on the interplay between SOC components and microbial community following the application of diverse SMS types remains scant. A laboratory soil incubation experiment was conducted with application of two types of SMSs from cultivation of Pleurotus eryngii (PE) and Agaricus bisporus (AB), each at three application rates (3, 5.5, and 8%). Advanced techniques, including solid-state 13C nuclear magnetic resonance (NMR) and high-throughput sequencing, were employed to investigate on SOC fractions and chemical structure, microbial community composition and functionality. Compared to SMS-AB, SMS-PE application increased the relative abundances of carbohydrate carbon and O-alkyl C in SOC. In addition, SMS-PE application increased the relative abundance of the bacterial phylum Proteobacteria and those of the fungal phyla Basidiomycota and Ascomycota. The relative abundances of cellulose-degrading bacterial (e.g., Flavisolibacter and Agromyces) and fungal genera (e.g., Myceliophthora, Thermomyces, and Conocybe) were increased as well. The application of SMS-AB increased the aromaticity index of SOC, the relative abundance of aromatic C, and the contents of humic acid and heavy fraction organic carbon. In addition, SMS-AB application significantly increased the relative abundances of the bacterial phyla Firmicutes and Actinobacteria. Notably, the genera Actinomadura, Ilumatobacter, and Bacillus, which were positively correlated with humic acid, experienced an increase in relative abundance. Functional prediction revealed that SMS-PE application elevated carbohydrate metabolism and reduced the prevalence of fungal pathogens, particularly Fusarium. The application of high-rate SMS-AB (8%) enhanced bacterial amino acid metabolism and the relative abundances of plant pathogenic fungi. Our research provides strategies for utilizing SMS to enrich soil organic carbon and fortify soil health, facilitating the achievement of sustainable soil management.

Generalizing the Enhanced-Deep-Super-Resolution Neural Network to Brain MR Images: A Retrospective Study on the Cam-CAN Dataset.

The Enhanced-Deep-Super-Resolution (EDSR) model is a state-of-the-art convolutional neural network suitable for improving image spatial resolution. It was previously trained with general-purpose pictures and then, in this work, tested on biomedical magnetic resonance (MR) images, comparing the network outcomes with traditional up-sampling techniques. We explored possible changes in the model response when different MR sequences were analyzed. T1w and T2w MR brain images of 70 human healthy subjects (F:M, 40:30) from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) repository were down-sampled and then up-sampled using EDSR model and BiCubic (BC) interpolation. Several reference metrics were used to quantitatively assess the performance of up-sampling operations (RMSE, pSNR, SSIM, and HFEN). Two-dimensional and three-dimensional reconstructions were evaluated. Different brain tissues were analyzed individually. The EDSR model was superior to BC interpolation on the selected metrics, both for two- and three- dimensional reconstructions. The reference metrics showed higher quality of EDSR over BC reconstructions for all the analyzed images, with a significant difference of all the criteria in T1w images and of the perception-based SSIM and HFEN in T2w images. The analysis per tissue highlights differences in EDSR performance related to the gray-level values, showing a relative lack of outperformance in reconstructing hyperintense areas. The EDSR model, trained on general-purpose images, better reconstructs MR T1w and T2w images than BC, without any retraining or fine-tuning. These results highlight the excellent generalization ability of the network and lead to possible applications on other MR measurements.

Detection of Dural Defect Localization Using 4-Dimensional Dynamic Computed Tomography Myelography for Patients with Superficial Siderosis

There are cases of superficial siderosis (SS) with spinal ventral fluid-filled collection in the spinal canal. In our previous study, the balanced steady-state free precession sequence magnetic resonance imaging is useful in identifying the location of dural defects. However, because of its narrow scan area and long scan time, it cannot easily detect the defect location in some patients with small dural defect. In this study, we applied 4-dimensional (4D) dynamic computed tomography (CT) imaging, including time-axis imaging, to myelography using the latest CT imaging equipment, which can perform short-time continuous imaging, to identify the dural defect site. Twenty SS patients with ventral fluid-filled collection in the spinal canal (9 males, 11 females; mean age 61.6years) underwent 4D dynamic CT myelography. A 192-row helical CT (SOMATOM Force, SIEMENS, Munich, Germany) with high-speed scanning capability was used to obtain 9-11 scans per minute at low dose while passing contrast medium into the subarachnoid space. Then, contrast leakage sites were identified. The contrast leakage sites could be identified in all 20 cases: C7/Th1, 2 cases; Th1/2, 5 cases; Th2/3, 9 cases; Th3/4, 1 case; Th5/6, 1 case; Th7/8, 1 case; and Th8/9, 1 case. Eighteen cases underwent surgical operation, and actual dural defects were confirmed at the contrast leakage sites. The mean±standard deviation of leakage time from contrast agent injection was 19.0±9.2s. The 4D dynamic CT myelography can be used to reliably identify the location of spinal fluid leakage. In SS cases, dural defects could be visualized in an average of 19seconds.