T1-weighted Contrast Research Articles

Relaxation-weighted MRI analysis of biofilm EPS: Differentiating biopolymers, cells, and water

Biofilms are a highly complex community of microorganisms embedded in a protective extracellular polymeric substance (EPS). Successful biofilm control requires a variety of approaches to better understand the structure-function relationship of the EPS matrix. Magnetic resonance imaging (MRI) is a versatile tool which can measure spatial structure, diffusion, and flow velocities in three dimensions and in situ. It is well-suited to characterize biofilms under natural conditions and at different length scales. MRI contrast is dictated by T1 and T2 relaxation times which vary spatially depending on the local chemical and physical environment of the sample. Previous studies have demonstrated that MRI can provide important insights into the internal structure of biofilms, but the contribution of major biofilm components—such as proteins, polysaccharides, and cells—to MRI contrast is not fully understood. This study explores how these components affect contrast in T1-and T2-weighted MRI by analyzing artificial biofilms with well-defined properties modeled after aerobic granular sludge (AGS), compact spherical biofilm aggregates used in wastewater treatment. MRI of these biofilm models showed that certain gel-forming polysaccharides are a major source of T2 contrast, while other polysaccharides show minimal contrast. Proteins were found to reduce T2 contrast slightly when combined with polysaccharides, while cells had a negligible impact on T2 but showed T1 contrast. Patterns observed in the model biofilms served as a reference for examining T2 and T1-weighted contrast in the void spaces of two distinct AGS granules, allowing for a qualitative evaluation of the EPS components which may be present. Further insights provided by MRI may help improve understanding of the biofilm matrix and guide how to better manage biofilms in wastewater, clinical, and industrial settings.

Age-specific optimization of the T2-weighted MRI contrast in infant and toddler brain.

In 0-2-year-old brains, the T2-weighted (T2w) contrast between white matter (WM) and gray matter (GM) is weaker compared with that in adult brains and rapidly changes with age. This study aims to design variable-flip-angle (VFA) trains in 3D fast spin-echo sequence that adapt to the dynamically changing relaxation times to improve the contrast in the T2w images of the developing brains. T1 and T2 relaxation times in 0-2-year-old brains were measured, and several age groups were defined according to the age-dependent pattern of T2 values. Based on the static pseudo-steady-state theory and the extended phase graph algorithm, VFA trains were designed for each age group to maximize WM/GM contrast, constrained by the maximum specific absorption rate and overall signal intensity. The optimized VFA trains were compared with the default one used for adult brains based on the relative contrast between WM and GM. Dice coefficient was used to demonstrate the advantage of contrast-improved images as inputs for automatic tissue segmentation in infant brains. The 0-2-year-old pool was divided into groups of 0-8 months, 8-12 months, and 12-24 months. The optimal VFA trains were tested in each age group in comparison with the default sequence. Quantitative analyses demonstrated improved relative contrasts in infant and toddler brains by 1.5-2.3-fold at different ages. The Dice coefficient for contrast-optimized images was improved compared with default images (p < 0.001). An effective strategy was proposed to improve the 3D T2w contrast in 0-2-year-old brains.

Differentiation of MS lesions through analysis of microvascular distribution

Abstract Conventional MRI is crucial for diagnosing multiple sclerosis (MS) but lacks precision, leading to the clinico-radiological paradox and misdiagnosis risk, especially when confronted with unspecific lesions not related to MS. Advancements in perfusion-weighted imaging (PWI) with an algorithm designed for diseases with anticipated contrast agent extravasation offer insight into microvascular impairment and flow heterogeneity. Our study aimed to assess these factors in MS patients and their association with clinically relevant white matter injury and disease course. We evaluated 60 adults with white matter lesions (WML), including 50 diagnosed with MS or MS syndromes and 10 non-diseased symptomatic controls (SC) with unspecific WML. MRI included conventional three-dimensional (3D) T2-weighted fluid-attenuated inversion recovery (T2-FLAIR), 3D magnetization-prepared 2 rapid acquisition gradient-echo (MP2RAGE), post-contrast 3D T1-weighted (T1) images and Dynamic Susceptibility Contrast (DSC) PWI at 3T. WML masks of “unspecific T2-FLAIR lesions”, “MS T2-FLAIR lesions”, and “MS T1-lesions” were manually outlined and validated by a neuroradiologist. DSC-derived parameters were analyzed in WML masks and healthy-appearing tissue. MS T2-FLAIR lesions showed increased flow heterogeneity and vasodilation compared to unspecific T2-FLAIR lesions in SC, as well as compared to unspecific T2-FLAIR lesions within the MS group. MS T1-lesions exhibited more homogenized flow. Our findings suggest that DSC-PWI combined with lesion delineation, can provide clinically relevant differentiation of MS lesions from unspecific WML, highlighting potential microvascular pathology previously overlooked in MS.

Co-delivery of camptothecin and MiR-145 by lipid nanoparticles for MRI-visible targeted therapy of hepatocellular carcinoma

BackgroundCamptothecin (CPT) is one of the frequently used small chemotherapy drugs for treating hepatocellular carcinoma (HCC), but its clinical application is limited due to severe toxicities and acquired resistance. Combined chemo-gene therapy has been reported to be an effective strategy for counteracting drug resistance while sensitizing cancer cells to cytotoxic agents. Thus, we hypothesized that combining CPT with miR-145 could synergistically suppress tumor proliferation and enhance anti-tumor activity.MethodsLactobionic acid (LA) modified lipid nanoparticles (LNPs) were developed to co-deliver CPT and miR-145 into asialoglycoprotein receptors-expressing HCC in vitro and in vivo. We evaluated the synergetic antitumor effect of miR-145 and CPT using CCK8, Western blotting, apoptosis and wound scratch assay in vitro, and the mechanisms underlying the synergetic antitumor effects were further investigated. Tumor inhibitory efficacy, safety evaluation and MRI-visible ability were assessed using diethylnitrosamine (DEN) + CCl4-induced HCC mouse model.ResultsThe LA modification improved the targeting delivery of cargos to HCC cells and tissues. The LA-CMGL-mediated co-delivery of miR-145 and CPT is more effective on tumor inhibitory than LA-CPT-L or LA-miR-145-L treatment alone, both in vitro and in vivo, with almost no side effects during the treatment period. Mechanistically, miR-145 likely induces apoptosis by targeting SUMO-specific peptidase 1 (SENP1)-mediated hexokinase (HK2) SUMOylation and glycolysis pathways and, in turn, sensitizing the cancer cells to CPT. In vitro and in vivo tests confirmed that the loaded Gd-DOTA served as an effective T1-weighted contrast agent for noninvasive tumor detection as well as real-time monitoring of drug delivery and biodistribution.ConclusionsThe LA-CMGL-mediated co-delivery of miR-145 and CPT displays a synergistic therapy against HCC. The novel MRI-visible, actively targeted chemo-gene co-delivery system for HCC therapy provides a scientific basis and a useful idea for the development of HCC treatment strategies in the future.

Free-breathing time-resolved 4D MRI with improved T1-weighting contrast.

This work proposes MP-Grasp4D (magnetization-prepared golden-angle radial sparse parallel 4D) MRI, a free-breathing, inversion recovery (IR)-prepared, time-resolved 4D MRI technique with improved T1-weighted contrast. MP-Grasp4D MRI acquisition incorporates IR preparation into a radial gradient echo sequence. MP-Grasp4D employs a golden-angle navi-stack-of-stars sampling scheme, where imaging data of rotating radial stacks and navigator stacks (acquired at a consistent rotation angle) are alternately acquired. The navigator stacks are used to estimate a temporal basis for low-rank subspace-constrained reconstruction. This allows for the simultaneous capture of both IR-induced contrast changes and respiratory motion. One temporal frame of the imaging volume in MP-Grasp4D MRI is reconstructed from a single stack and an adjacent navigator stack on average, resulting in a nominal temporal resolution of 0.16 seconds per volume. Images corresponding to the optimal inversion time (TI) can be retrospectively selected for providing the best image contrast. Reader studies were conducted to assess the performance of MP-Grasp4D MRI in liver imaging across 30 subjects in comparison with standard Grasp4D MRI without IR preparation. MP-Grasp4D MRI received significantly higher scores (P < 0.05) than Grasp4D in all assessment categories. There was a moderate to almost perfect agreement (kappa coefficient from 0.42 to 0.9) between the two readers for image quality assessment. When the scan time is reduced, MP-Grasp4D MRI preserves image contrast and quality, demonstrating additional acceleration capability. MP-Grasp4D MRI improves T1-weighted contrast for free-breathing time-resolved 4D MRI and eliminates the need for explicit motion compensation. This method is expected to be valuable in different MRI applications such as MR-guided radiotherapy.

Optimization and validation of low-field MP2RAGE T1 mapping on 0.35T MR-Linac: Toward adaptive dose painting with hypoxia biomarkers.

Stereotactic MR-guided Adaptive Radiation Therapy (SMART) dose painting for hypoxia has potential to improve treatment outcomes, but clinical implementation on low-field MR-Linac faces substantial challenges due to dramatically lower signal-to-noise ratio (SNR) characteristics. While quantitative MRI and T1 mapping of hypoxia biomarkers show promise, T1-to-noise ratio (T1NR) optimization at low fields is paramount, particularly for the clinical implementation of oxygen-enhanced (OE)-MRI. The 3D Magnetization Prepared (2) Rapid Gradient Echo (MP2RAGE) sequence stands out for its ability to acquire homogeneous T1-weighted contrast images with simultaneous T1 mapping. To optimize MP2RAGE for low-field T1 mapping; conduct experimental validation in a ground-truth phantom; establish feasibility and reproducibility of low-field MP2RAGE acquisition and T1 mapping in healthy volunteers. The MP2RAGE optimization was performed to maximize the contrast-to-noise ratio (CNR) of T1 values in white matter (WM) and gray matter (GM) brain tissues at 0.35T. Low-field MP2RAGE images were acquired on a 0.35T MR-Linac (ViewRay MRIdian) using a multi-channel head coil. Validation of T1 mapping was performed with a ground-truth Eurospin phantom, containing inserts of known T1 values (400-850ms), with one and two average (1A and 2A) MP2RAGE scans across four acquisition sessions, resulting in eight T1 maps. Mean (±SD) T1 relative error, T1NR, and intersession coefficient of variation (CV) were determined. Whole-brain MP2RAGE scans were acquired in 5 healthy volunteers across two sessions (A and B) and T1 maps were generated. Mean (±SD) T1 values for WM and GM were determined. Whole-brain T1 histogram analysis was performed, and reproducibility was determined with the CV between sessions. Voxel-by-voxel T1 difference maps were generated to evaluate 3D spatial variation. Low-field MP2RAGE optimization resulted in parameters: MP2RAGETR of 3250ms, inversion times (TI1/TI2) of 500/1200ms, and flip angles (α1/α2) of 7/5°. Eurospin T1 maps exhibited a mean (±SD) relative error of 3.45%±1.30%, T1NR of 20.13±5.31, and CV of 2.22%±0.67% across all inserts. Whole-brain MP2RAGE images showed high anatomical quality with clear tissue differentiation, resulting in mean (±SD) T1 values: 435.36±10.01ms for WM and 623.29±14.64ms for GM across subjects, showing excellent concordance with literature. Whole-brain T1 histograms showed high intrapatient and intersession reproducibility with characteristic intensity peaks consistent with voxel-level WM and GM T1 values. Reproducibility analysis revealed a CV of 0.46%±0.31% and 0.35%±0.18% for WM and GM, respectively. Voxel-by-voxel T1 difference maps show a normal 3D spatial distribution of noise in WM and GM. Low-field MP2RAGE proved effective in generating accurate, reliable, and reproducible T1 maps with high T1NR in phantom studies and in vivo feasibility established in healthy volunteers. While current work is focused on refining the MP2RAGE protocol to enable clinically efficient OE-MRI, this study establishes a foundation for TOLD T1 mapping for hypoxia biomarkers. This advancement holds the potential to facilitate a paradigm shift toward MR-guided biological adaptation and dose painting by leveraging 3D hypoxic spatial distributions and improving outcomes in conventionally challenging-to-treat cancers.

Brain Tumor Detection using Hybrid CNN in fMRI images

One of the deadliest brain tumors in the world. Both adults and children are at risk for the disease. Depending on their position, appearance and shape, it has a low survival rate and is available in different varieties. Incorrect classification of the brain tumor will have negative consequences. Early detection of the tumor type and stage is necessary for selecting a specific treatment. Identifying brain tumors can be done effectively by examining fMRI, or functional magnetic resonance imaging. Due to the various information and various types of tumors in brain, the manual process takes lot of time to identify, and there may be chances of human error. Therefore, it is necessary to have an intelligent diagnostic system. The recent evolution of image categorization systems has been influenced by the use of deep convolution neural networks (CNN). In this research work, a new hybrid paradigm with images combines a convolution neural network (CNN) and a masked autoencoder for distribution estimation (MADE). Three different forms of brain tumors were tested using T1-weighted contrast enhanced images. The CNN-MADE hybrid's excellent classification performance is demonstrated by the results, despite the limited availability of medical images. A new layered model was proposed to categorize brain tumors through MRI. The proposed approach is more successful than the alternatives based on the experiments' results.

PSMA PET/MR is a New Imaging Option for Identifying Glioma Recurrence and Predicting Prognosis.

Glioma is characterized by a high recurrence rate, while the results of the traditional imaging methods (including magnetic resonance imaging, MRI) to distinguish recurrence from treatment-related changes (TRCs) are poor. Prostate-specific membrane antigen (PSMA) (US10815200B2, Deutsches Krebsforschungszentrum, German Cancer Research Center) is a type II transmembrane glycoprotein overexpressed in glioma vascular endothelium, and it is a promising target for imaging and therapy. The study aimed to assess the performance of PSMA positron emission tomography/ magnetic resonance (PET/MR) for diagnosing recurrence and predicting prognosis in glioma patients. Patients suspected of glioma recurrence who underwent 18F-PSMA-1007 PET/MR were prospectively enrolled. Eight metabolic parameters and fifteen texture features of the lesion were extracted from PSMA PET/MR. The ability of PSMA PET/MR to diagnose glioma recurrence was investigated and compared with conventional MRI. The diagnostic agreement was assessed using Cohen κ scores and the predictive parameters of PSMA PET/MR were obtained. Kaplan-Meier method and Cox proportional hazard model were used to analyze recurrence- free survival (RFS) and overall survival (OS). Finally, the expression of PSMA was analyzed by immunohistochemistry (IHC). Nineteen patients with a mean age of 48.11±15.72 were assessed. The maximum tumorto- parotid ratio (TPRmax) and texture features extracted from PET and T1-weighted contrast enhancement (T1-CE) MR showed differences between recurrence and TRCs (all p <0.05). PSMA PET/MR and conventional MRI exhibited comparable power in diagnosing recurrence with specificity and PPV of 100%. The interobserver concordance was fair between the two modalities (κ = 0.542, p = 0.072). The optimal cutoffs of metabolic parameters, including standardized uptake value (SUV, SUVmax, SUVmean, and SUVpeak) and TPRmax for predicting recurrence were 3.35, 1.73, 1.99, and 0.17 respectively, with the area under the curve (AUC) ranging from 0.767 to 0.817 (all p <0.05). In grade 4 glioblastoma (GBM) patients, SUVmax, SUVmean, SUVpeak, TBRmax, TBRmean, and TPRmax showed improved performance of AUC (0.833-0.867, p <0.05). Patients with SUVmax, SUVmean, or SUVpeak more than the cutoff value had significantly shorter RFS (all p <0.05). In addition, patients with SUVmean, SUVpeak, or TPRmax more than the cutoff value had significantly shorter OS (all p <0.05). PSMA expression of glioma vascular endothelium was observed in ten (10/11, 90.9%) patients with moderate-to-high levels in all GBM cases (n = 6/6, 100%). This primitive study shows multiparameter PSMA PET/MR to be useful in identifying glioma (especially GBM) recurrence by providing excellent tumor background comparison, tumor heterogeneity, recurrence prediction and prognosis information, although it did not improve the diagnostic performance compared to conventional MRI. Further and larger studies are required to define its potential clinical application in this setting.

Nano-photosensitizers with gallic acid-involved Fe–O–Cu “electronic storage station” bridging ligand-to-metal charge transfer for efficient catalytic theranostics

NH2-MIL-88B (Fe) (MOF) is a promising photocatalytic material for antitumor therapy because of its distinctive electronic structure. However, inadequate separation of photo-generated electrons and slow reaction rate in low/high-valence iron (Fe) cycles limit their clinical application. In the present study, “electronic storage station” as a ligand-to-metal charge transfer bridge bond was constructed to inhibit recombination of electron/hole under 650 nm laser irradiation. Cupric (Cu) ions and gallic acid (GA) were self-assembled into a MOF (denoted as CGMOF) to create an FeO(GA)Cu bridge bond. GA, characterized by robust electron delocalization and abundant electron-donating groups, significantly enhances electron transfer efficiency for photodynamic therapy (PDT). CGMOF can respond to endogenous glutathione and release cuprous ions, accelerating the iron ion/ferrous ion cycles for chemodynamic therapy (CDT). The released Fe species can serve as T2-weighted magnetic resonance imaging contrast. Extended X-ray absorption fine structure spectra confirmed the presence of GA-containing FeOCu bonds in CGMOF. Furthermore, a series of photo-electrochemical tests confirmed that the formation of FeO(GA)Cu bond prominently elevated the redox capacity and increased the carrier density of CGMOF by 2.74-fold compared to that of MOF. In addition, cinnamaldehyde was grafted onto CGMOF for tumor-responsive hydrogen peroxide self-supply. Concurrently, hyaluronic acid was surface-modified to achieve the targeted delivery of nano-photosensitizers. In summary, this study presents an innovative approach for engineering Fe-based metal–organic frameworks for synergetic PDT/CDT applications.

Assessment of imaging risks for recurrence after stereotactic radiosurgery for brain metastases (IRRaS-BM)

BackgroundThe identification of viable tumors and radiation necrosis after stereotactic radiosurgery (SRS) is crucial for patient management. Tumor habitat analysis involving the grouping of similar voxels can identify subregions that share common biology and enable the depiction of areas of tumor recurrence and treatment-induced change. This study aims to validate an imaging biomarker for tumor recurrence after SRS for brain metastasis by conducting tumor habitat analysis using multi-parametric MRI.MethodsIn this prospective study (NCT05868928), patients with brain metastases will undergo multi-parametric MRI before SRS, and then follow-up MRIs will be conducted every 3 months until 24 months after SRS. The multi-parametric MRI protocol will include T2-weighted and contrast-enhanced T1-weighted imaging, diffusion-weighted imaging, and dynamic susceptibility contrast imaging. Using k-means voxel-wise clustering, this study will define three structural MRI habitats (enhancing, solid low-enhancing, and nonviable) on T1- and T2-weighted images and three physiologic MRI habitats (hypervascular cellular, hypovascular cellular, and nonviable) on apparent diffusion coefficient maps and cerebral blood volume maps. Using RANO-BM criteria as the reference standard, via Cox proportional hazards analysis, the study will prospectively evaluate associations between parameters of the tumor habitats and the time to recurrence. The DICE similarity coefficients between the recurrence site and tumor habitats will be calculated.DiscussionThe tumor habitat analysis will provide an objective and reliable measure for assessing tumor recurrence from brain metastasis following SRS. By identifying subregions for local recurrence, our study could guide the next therapeutic targets for patients after SRS.Trial registrationThis study is registered at ClinicalTrials.gov (NCT05868928).

Nanostructured gadolinium(III) micelles: Synthesis, characterization, cytotoxic activities, and MRI applications in vivo

Gadolinium-based contrast agents (GBCAs) are used in around 40 % of MRI procedures. Despite initial perceptions of minimal risk, their long-term use has emphasized the need to reduce toxicity and develop more efficient GBCAs with extended blood retention. Advancements in nanomaterials have led to improved GBCAs, enhancing MRI diagnostics. This study synthesizes and characterizes nanostructured gadolinium(III) micelles as superior MRI contrast agents. The complexes, [Gd(L)2], where L is a ligand of the N-alkyl-N-methylglucamine surfactant series (L8, L10 or L12, L10), form nanostructured micelles in aqueous solution. Gd(L8)2 and Gd(L10)2 relaxivities remained stable across concentrations. Compared to Gd-DTPA, Gd(III) micelles showed enhanced T1-weighted MRI contrast. Gd(L12)2 micelles exhibited cytotoxicity against B16F10 melanoma cells (IC50 42.5 ± 2.2 μM) and L292L929 fibroblasts (IC50 52.0 ± 2.5 μM), with a selectivity index of 1.2. In vivo application in mice brain T2-weighted images suggests nanostructured Gd(III) micelles are promising MRI contrast agents for targeting healthy organs or tumors.

Iron gallic acid biomimetic nanoparticles for targeted magnetic resonance imaging.

Developing T1-weighted magnetic resonance imaging (MRI) contrast agents with enhanced biocompatibility and targeting capabilities is crucial owing to concerns over current agents' potential toxicity and suboptimal performance. Drawing inspiration from "biomimetic camouflage," we isolated cell membranes (CMs) from human glioblastoma (T98G) cell lines via the extrusion method to facilitate homotypic glioma targeting. At an 8:1 mass ratio of ferric chloride hexahydrate to gallic acid (GA), the resulting iron (Fe)-GA nanoparticles (NPs) proved effective as a T1-weighted MRI contrast agent. T98G CM-coated Fe-GA NPs demonstrated improved homotypic glioma targeting, validated through Prussian blue staining and in vitro MRI. This biomimetic camouflage strategy holds promise for the development of targeted theranostic agents in a safe and effective manner.

Mn(II)-Aloe-Emodin Nanoscale Coordination Polymer Enhances Ferroptosis by Synergistically Enhancing Reactive Oxygen Species Generation via the Nrf2-GPX4 Axis.

Ferroptosis induction is particularly promising for cancer therapy when the apoptosis pathway is compromised. Current strategies in nanomedicine for inducing ferroptosis primarily focus on promoting the accumulation of reactive oxygen species (ROS). However, the presence of intracellular antioxidants, such as nuclear factor erythroid 2-related factor 2 (Nrf2), can limit the effectiveness of such therapy by activating detoxification systems and eliminating ROS. To overcome this challenge, we developed a synergistic ferroptosis-inducing agentby modifying manganese (Mn2+)-1,8-dihydroxy-3-hydroxymethyl-anthraquinone (aloe-emodin, AE) with polyvinyl pyrrolidone (PVP) to create nanoparticles (MAP NPs). In the tumor microenvironment, these NPs degraded and released AE and Mn(II), facilitating the generation of ROS and Mn(IV) through a Fenton-like reaction between hydrogen peroxide (H2O2) and Mn(II). Mn(IV) subsequently interacts with glutathione (GSH) to induce a cyclic catalytic effect, and the depletion of GSH diminished the activation of glutathione-dependent peroxidase 4 (GPX4). Furthermore, AE inhibits the activity of Nrf2 and depleted GSH, thereby synergistically enhancing antitumor efficacy. Here it is demonstrated that MAP NPs effectively generate a robust ROS storm within tumor cells, suggesting that high-performance ferroptosis therapy is effective. Additionally, the inclusion of Mn(II) in the MAP NPs enables real-time monitoring of therapeutic efficacy via magnetic resonance T1-weighted contrast imaging.

Ti3C2Tx MXene quantum dots coated hollow manganese dioxide nanoparticles for tumor combination therapy and magnetic resonance imaging

Chemodynamic therapy (CDT) is a new cancer treatment that uses low-valence transition metal ions to catalyze intracellular Fenton/Fenton-like reactions, producing hydroxyl radicals (•OH) to eliminate cancer cells. However, achieving satisfactory therapeutic outcomes with CDT alone can be challenging. In this work, we reported an anticancer drug delivery DOX@HMDN-TQDs@PEI-PEG (DMTP) based on hollow mesoporous manganese dioxide nanoparticle (HMDN), which has the potential to improve cancer therapy by combining synergistic therapeutic and tumor magnetic resonance imaging (MRI) capability. After loading the anticancer drug doxorubicin hydrochloride (DOX), the pores of HMDN were sealed with polyethyleneimine (PEI) modified Ti3C2Tx MXene quantum dots (TQDs) and finally modified with polyethylene glycol (PEG) to obtain the final system. HMDN depletes glutathione (GSH), which is harmful to CDT, in cancer cells, and generates Mn2+ that can be used for both CDT and MRI. TQDs can also be used for highly effective photothermal therapy (PTT) that enhances CDT. The combination of DOX with chemotherapy can significantly inhibit tumor growth. In addition, DMTP combines the capability of tumor MRI as Mn2+ is also a T1-weighted contrast agent. This multifunctional delivery system provides new ideas for research related to tumor diagnosis and treatment.

11.7T Diffusion Magnetic Resonance Imaging and Tractography to Probe Human Brain Organoid Microstructure

BackgroundHuman brain organoids are 3-dimensional cellular models that mimic architectural features of a developing brain. Generated from human induced pluripotent stem cells, these organoids offer an unparalleled physiologically relevant in vitro system for disease modeling and drug screening. In the current study, we sought to establish a foundation for a magnetic resonance imaging (MRI)–based, label-free imaging system that offers high-resolution capabilities for deep tissue imaging of whole organoids. MethodsAn 11.7T Bruker/89 mm microimaging system was used to collect high-resolution multishell 3-dimensional diffusion images of 2 induced pluripotent stem cell–derived human hippocampal brain organoids. The MRI features identified in the study were interpreted on the basis of similarities with immunofluorescence microscopy. ResultsMRI microscopy at ≤40 μm isotropic resolution provided a 3-dimensional view of organoid microstructure. T2-weighted contrast showed a rosette-like internal structure and a protruding spherical structure that correlated with immunofluorescence staining for the choroid plexus. Diffusion tractography methods can be used to model tissue microstructural features and possibly map neuronal organization. This approach complements traditional immunohistochemistry imaging methods without the need for tissue clearing. ConclusionsThis proof-of-concept study shows, for the first time, the application of high-resolution diffusion MRI microscopy to image 2-mm diameter spherical human brain organoids. Application of ultrahigh-field MRI and diffusion tractography is a powerful modality for whole organoid imaging and has the potential to make a significant impact for probing microstructural changes in brain organoids used to model psychiatric disorders, neurodegenerative diseases, and viral infections of the human brain, as well as for assessing neurotoxicity in drug screening.

A combinatorial MRI sequence-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer

This study aimed to develop an optimal radiomics model for preoperatively predicting microsatellite instability (MSI) in patients with rectal cancer (RC) based on multiparametric magnetic resonance imaging. The retrospective study included 308 RC patients who did not receive preoperative antitumor therapy, among whom 51 had MSI. Radiomics features were extracted and dimensionally reduced from T2-weighted imaging (T2WI), T1-weighted imaging (T1WI), diffusion-weighted imaging (DWI), and T1-weighted contrast enhanced (T1CE) images for each patient, and the features of each sequence were combined. Multifactor logistic regression was used to screen the optimal feature set for each combination. Different machine learning methods were applied to construct predictive MSI status models. Relative standard deviation values were determined to evaluate model performance and select the optimal model. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analyses were performed to evaluate model performance. The model constructed using the k-nearest neighbor (KNN) method combined with T2WI and T1CE images performed best. The area under the curve values for prediction of MSI with this model were 0.849 (0.804–0.887), with a sensitivity of 0.784 and specificity of 0.805. The Delong test showed no significant difference in diagnostic efficacy between the KNN-derived model and the traditional logistic regression model constructed using T1WI + DWI + T1CE and T2WI + T1WI + DWI + T1CE data (P > 0.05) and the diagnostic efficiency of the KNN-derived model was slightly better than that of the traditional model. From ROC curve analysis, the KNN-derived model significantly distinguished patients at low- and high-risk of MSI with the optimal threshold of 0.2, supporting the clinical applicability of the model. The model constructed using the KNN method can be applied to noninvasively predict MSI status in RC patients before surgery based on radiomics features from T2WI and T1CE images. Thus, this method may provide a convenient and practical tool for formulating treatment strategies and optimizing individual clinical decision-making for patients with RC.

Folate Receptor Targeting Mn(II) Complex Encapsulated Porous Silica Nanoparticle as an MRI Contrast Agent for Early-State Detection of Cancer.

Cancer is recognized as one of the major causes of mortality, however, early-stage detection can increase the survival chance greatly. It is recognized that folate receptors are gradually overexpressed in the cellular membrane with the progress of cancer from stage 1 to stage 4. Utilizing the fact, herein, developed a porous silica nanoparticle system C1@SiO2-FA-NP; A) impregnated with thermodynamically stable Mn(II) complex (1) molecules within the core of the nanoparticle, and B) surface functionalized with folate units. It exhibited a high longitudinal relaxivity value r1 = 21.45 mM-1s-1 that substantially increased to r1 = 40.97 mM-1s-1 in the presence of 0.67mM concentration of BSA under the physiological condition. The in vitro fluorescent images after surface conjugation of C1@SiO2-FA-NP with FITC (fluorescein isothiocyanate) buttressed the inclusion of the nanoparticle exclusively within the cancerous HeLa cells than that of healthy HEK293 cells. The importance of the surface-bound folate unit in the nanoparticle is further established by comparing the fluorescent images of HeLa cells in the absence of the group. Finally, the applicability of C1@SiO2-FA-NP as the T1-weighted MRI contrast agent for early-stage cancer diagnosis is established within C57BL/6 mice after infecting the mice with HeLa cells.

A Novel Positive-Contrast Magnetic Resonance Imaging Line Marker for High-Dose-Rate (HDR) MRI-Assisted Radiosurgery (MARS).

Magnetic resonance imaging (MRI) can facilitate accurate organ delineation and optimal dose distributions in high-dose-rate (HDR) MRI-Assisted Radiosurgery (MARS). Its use for this purpose has been limited by the lack of positive-contrast MRI markers that can clearly delineate the lumen of the HDR applicator and precisely show the path of the HDR source on T1- and T2-weighted MRI sequences. We investigated a novel MRI positive-contrast HDR brachytherapy or interventional radiotherapy line marker, C4:S, consisting of C4 (visible on T1-weighted images) complexed with saline. Longitudinal relaxation time (T1) and transverse relaxation time (T2) for C4:S were measured on a 1.5 T MRI scanner. High-density polyethylene (HDPE) tubing filled with C4:S as an HDR brachytherapy line marker was tested for visibility on T1- and T2-weighted MRI sequences in a tissue-equivalent female ultrasound training pelvis phantom. Relaxivity measurements indicated that C4:S solution had good T1-weighted contrast (relative to oil [fat] signal intensity) and good T2-weighted contrast (relative to water signal intensity) at both room temperature (relaxivity ratio > 1; r2/r1 = 1.43) and body temperature (relaxivity ratio > 1; r2/r1 = 1.38). These measurements were verified by the positive visualization of the C4:S (C4/saline 50:50) HDPE tube HDR brachytherapy line marker on both T1- and T2-weighted MRI sequences. Orientation did not affect the relaxivity of the C4:S contrast solution. C4:S encapsulated in HDPE tubing can be visualized as a positive line marker on both T1- and T2-weighted MRI sequences. MRI-guided HDR planning may be possible with these novel line markers for HDR MARS for several types of cancer.

Motion Correction for Brain MRI Using Deep Learning and a Novel Hybrid Loss Function

Purpose: Motion-induced magnetic resonance imaging (MRI) artifacts can deteriorate image quality and reduce diagnostic accuracy, but motion by human subjects is inevitable and can even be caused by involuntary physiological movements. Deep-learning-based motion correction methods might provide a solution. However, most studies have been based on directly applying existing models, and the trained models are rarely accessible. Therefore, we aim to develop and evaluate a deep-learning-based method (Motion Correction-Net, or MC-Net) for suppressing motion artifacts in brain MRI scans. Methods: A total of 57 subjects, providing 20,889 slices in four datasets, were used. Furthermore, 3T 3D sagittal magnetization-prepared rapid gradient-echo (MP-RAGE) and 2D axial fluid-attenuated inversion-recovery (FLAIR) sequences were acquired. The MC-Net was derived from a UNet combined with a two-stage multi-loss function. T1-weighted axial brain images contaminated with synthetic motions were used to train the network to remove motion artifacts. Evaluation used simulated T1- and T2-weighted axial, coronal, and sagittal images unseen during training, as well as T1-weighted images with motion artifacts from real scans. The performance indices included the peak-signal-to-noise ratio (PSNR), the structural similarity index measure (SSIM), and visual reading scores from three blinded clinical readers. A one-sided Wilcoxon signed-rank test was used to compare reader scores, with p &lt; 0.05 considered significant. Intraclass correlation coefficients (ICCs) were calculated for inter-rater evaluations. Results: The MC-Net outperformed other methods in terms of PSNR and SSIM for the T1 axial test set. The MC-Net significantly improved the quality of all T1-weighted images for all directions (i.e., the mean SSIM of axial, sagittal, and coronal slices improved from 0.77, 0.64, and 0.71 to 0.92, 0.75, and 0.84; the mean PSNR improved from 26.35, 24.03, and 24.55 to 29.72, 24.40, and 25.37, respectively) and for simulated as well as real motion artifacts, both using quantitative measures and visual scores. However, MC-Net performed poorly for images with untrained T2-weighted contrast because the T2 contrast was unseen during training and is different from T1 contrast. Conclusion: The proposed two-stage multi-loss MC-Net can effectively suppress motion artifacts in brain MRI without compromising image quality. Given the efficiency of MC-Net (with a single-image processing time of ~40 ms), it can potentially be used in clinical settings.

Carbon-coated (Eu/Dy-Enabled) erbium hydroxide nanostructures for biomedical imaging

Lanthanides possess versatile optical and magnetic properties, making them an excellent candidate for multimodal imaging. This study focuses on carbon-coated Erbium Hydroxide Nanoparticles (Er(OH)3 NPs), their cytotoxicity, and their potential for biomedical imaging. Er(OH)3 NPs were synthesized via a simple solvothermal method with the incorporation of different lanthanide dopants (Eu, Dy) to enhance the optical and magnetic properties. The spherical morphology, monodispersity, elemental composition, and effective carbon coating were demonstrated using characterizations such as SEM, EDS, and DLS. These monodisperse NPs were further evaluated for their cytotoxicity in Hep2c cervical cancer cells via colorimetric assays, thus proving carbon coating effectively reduces the cytotoxicity. Photoluminescence data of these NPs show multiple emission peaks with a maximum peak at 433 nm when excited at 253 nm. Magnetic resonance imaging (MRI), and computed tomography (CT) scans of these NPs were carried out to evaluate the multimodal imaging potential as contrast agents. The CT contrast shows comparable results to those of iodine-based contrast agents while the MRI scans of the carbon-coated samples show T2-weighted contrast. These findings provide insights into the potential use of Lanthanide-Enabled Er(OH)3 NPs (LEENs) as multimodal contrast agents.