Potential Of Magnetic Resonance Imaging Research Articles

Quantitative MRI imaging of parenchyma and venation networks in Brassica napus leaves: effects of development and dehydration

BackgroundCharacterisation of the structure and water status of leaf tissues is essential to the understanding of leaf hydraulic functioning under optimal and stressed conditions. Magnetic Resonance Imaging is unique in its capacity to access this information in a spatially resolved, non-invasive and non-destructive way. The purpose of this study was to develop an original approach based on transverse relaxation mapping by Magnetic Resonance Imaging for the detection of changes in water status and distribution at cell and tissue levels in Brassica napus leaves during blade development and dehydration.ResultsBy combining transverse relaxation maps with a classification scheme, we were able to distinguish specific zones of areoles and veins. The tissue heterogeneity observed in young leaves still occurred in mature and senescent leaves, but with different distributions of T2 values in accordance with the basipetal progression of leaf blade development, revealing changes in tissue structure. When subjected to severe water stress, all blade zones showed similar behaviours.ConclusionThis study demonstrates the great potential of Magnetic Resonance Imaging in assessing information on the structure and water status of leaves. The feasibility of in planta leaf measurements was demonstrated, opening up many opportunities for the investigation of leaf structure and hydraulic functioning during development and/or in response to abiotic stresses.

Magnetic resonance imaging-based radiomics analysis of the differential diagnosis of ovarian clear cell carcinoma and endometrioid carcinoma: a retrospective study.

To retrospectively evaluate the diagnostic potential of magnetic resonance imaging (MRI)-based features and radiomics analysis (RA)-based features for discriminating ovarian clear cell carcinoma (CCC) from endometrioid carcinoma (EC). Thirty-five patients with 40 ECs and 42 patients with 43 CCCs who underwent pretherapeutic MRI examinations between 2011 and 2022 were enrolled. MRI-based features of the two groups were compared. RA-based features were extracted from the whole tumor volume on T2-weighted images (T2WI), contrast-enhanced T1-weighted images (cT1WI), and apparent diffusion coefficient (ADC) maps. The least absolute shrinkage and selection operator (LASSO) regression with tenfold cross-validation method was performed to select features. Logistic regression analysis was conducted to construct the discriminating models. Receiver operating characteristic curve (ROC) analyses were performed to predict CCC. Four features with the highest absolute value of the LASSO algorithm were selected for theMRI-based, RA-based, and combined models: the ADC value, absence of thickening of the uterine endometrium, absence of peritoneal dissemination, and growth pattern of the solid component for the MRI-based model; Gray-Level Run Length Matrix (GLRLM) Long Run Low Gray-Level Emphasis (LRLGLE) on T2WI, spherical disproportion and Gray-Level Size Zone Matrix (GLSZM), Large Zone High Gray-Level Emphasis (LZHGE) on cT1WI, and GLSZM Normalized Gray-Level Nonuniformity (NGLN) on ADC map for the RA-based model; and the ADC value, spherical disproportion and GLSZM_LZHGE on cT1WI, and GLSZM_NGLN on ADC map for the combined model. Area under the ROC curves of those models were 0.895, 0.910, and 0.956. The diagnostic performance of the combined model was significantly superior (p = 0.02) to that of the MRI-based model. No significant differences were observed between the combined and RA-based models. Conventional MRI-based analysis can effectively distinguish CCC from EC. The combination of RA-based features with MRI-based features may assist in differentiating between the two diseases.

Segmentation method of magnetic resonance imaging brain tumor images based on improved UNet network.

Glioma is a primary malignant craniocerebral tumor commonly found in the central nervous system. According to research, preoperative diagnosis of glioma and a full understanding of its imaging features are very significant. Still, the traditional segmentation methods of image dispensation and machine wisdom are not acceptable in glioma segmentation. This analysis explores the potential of magnetic resonance imaging (MRI) brain tumor images as an effective segmentation method of glioma. This study used 200 MRI images from the affiliated hospital and applied the 2-dimensional residual block UNet (2DResUNet). Features were extracted from input images using a 2×2 kernel size (64-kernel) 1-step 2D convolution (Conv) layer. The 2DDenseUNet model implemented in this study incorporates a ResBlock mechanism within the UNet architecture, as well as a Gaussian noise layer for data augmentation at the input stage, and a pooling layer for replacing the conventional 2D convolutional layers. Finally, the performance of the proposed protocol and its effective measures in glioma segmentation were verified. The outcomes of the 5-fold cross-validation evaluation show that the proposed 2DResUNet and 2DDenseUNet structure has a high sensitivity despite the slightly lower evaluation result on the Dice score. At the same time, compared with other models used in the experiment, the DM-DA-UNet model proposed in this paper was significantly improved in various indicators, increasing the reliability of the model and providing a reference and basis for the accurate formulation of clinical treatment strategies. The method used in this study showed stronger feature extraction ability than the UNet model. In addition, our findings demonstrated that using generalized die harm and prejudiced cross entropy as loss functions in the training process effectively alleviated the class imbalance of glioma data and effectively segmented glioma. The method based on the improved UNet network has obvious advantages in the MRI brain tumor portrait segmentation procedure. The result showed that we developed a 2D residual block UNet, which can improve the incorporation of glioma segmentation into the clinical process.

Highly Sensitive Early Diagnosis of Kidney Damage Using Renal Clearable Zwitterion-Coated Ferrite Nanoprobe via Magnetic Resonance Imaging In Vivo.

Iron oxide nanoprobes exhibit substantial potential in magnetic resonance imaging (MRI) of kidney diseases and can eliminate the nephrotoxicity of gadolinium-based contrast agents (GBCAs). Nevertheless, there is an extreme shortage of highly sensitive and renal clearable iron oxide nanoprobes suitable for early kidney damage detection through MRI. Herein, a renal clearable ultra-small ferrite nanoprobe (UMFNPs@ZDS) is proposed for highly sensitive early diagnosis of kidney damage via structural and functional MRI in vivo for the first time. The nanoprobe comprises a ferrite core coated with a zwitterionic layer, and possesses a high T1 relaxivity (12.52 mm-1s-1), a small hydrodynamic size (6.43nm), remarkable water solubility, excellent biocompatibility, and impressive renal clearable ability. In a rat model of unilateral ureteral obstruction (UUO), the nanoprobe-based MRI can not only accurately visualize the locations of renal injury, but also provide comprehensive functional data including peak value, peak time, relative renal function (RRF), and clearance percentage via MRI. The findings prove the immense potential of ferrite nanoprobes as a superior alternative to GBCAs for the early diagnosis of kidney damage.

The Use of Magnetic Resonance Imaging in Radiation Therapy Treatment Simulation and Planning.

Ever since its introduction as a diagnostic imaging tool the potential of magnetic resonance imaging (MRI) in radiation therapy (RT) treatment simulation and planning has been recognized. Recent technical advances have addressed many of the impediments to use of this technology and as a result have resulted in rapid and growing adoption of MRI in RT. The purpose of this article is to provide a broad review of the multiple uses of MR in the RT treatment simulation and planning process, identify several of the most used clinical scenarios in which MR is integral to the simulation and planning process, highlight existing limitations and provide multiple unmet needs thereby highlighting opportunities for the diagnostic MR imaging community to contribute and collaborate with our oncology colleagues. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 5.

A resource for development and comparison of multimodal brain 3 T MRI harmonisation approaches

Abstract Despite the huge potential of magnetic resonance imaging (MRI) in mapping and exploring the brain, MRI measures can often be limited in their consistency, reproducibility, and accuracy which subsequently restricts their quantifiability. Nuisance nonbiological factors, such as hardware, software, calibration differences between scanners, and post-processing options, can contribute to, or drive trends in, neuroimaging features to an extent that interferes with biological variability. Such lack of consistency, known as lack of harmonisation, across neuroimaging datasets poses a great challenge for our capabilities in quantitative MRI. Here, we build a new resource for comprehensively mapping the extent of the problem and objectively evaluating neuroimaging harmonisation approaches. We use a travelling-heads paradigm consisting of multimodal MRI data of 10 travelling subjects, each scanned at five different sites on six different 3 T scanners from all the three major vendors and using five neuroimaging modalities, providing more comprehensive coverage than before. We also acquire multiple within-scanner repeats for a subset of subjects, setting baselines for multimodal scan-rescan variability. Having extracted hundreds of imaging-derived phenotypes, we compare three forms of variability: (i) between-scanner, (ii) within-scanner (within-subject), and (iii) biological (between-subject). We characterise the reliability of features across scanners and use our resource as a testbed to enable new investigations that until now have been relatively unexplored. Specifically, we identify optimal pipeline processing steps that minimise between-scanner variability in extracted features (implicit harmonisation). We also test the performance of post-processing harmonisation tools (explicit harmonisation) and specifically check their efficiency in reducing between-scanner variability against baseline standards provided by our data. Our explorations allow us to come up with good practice suggestions on processing steps and sets of features where results are more consistent, while our publicly released dataset (which we refer to as ON-Harmony) establishes references for future studies in this field.

Magnetic Nanocomposites and Imprinted Polymers for Biomedical Applications of Nucleic Acids

Magnetic nanocomposites (MNCs) combine the features of magnetic nanoparticles and a second material, which provide distinct physical, chemical, and biological properties. The magnetic core for nanocomposite synthesis is extensively used due to its high saturation magnetization, chemical stability, large surface area, and easy functionalization. Moreover, magnetic nanoparticles (MNPs) have great potential for magnetic resonance imaging (MRI), magnetic particle imaging (MPI), hyperthermia, and targeted drug and gene delivery by an external magnetic field. Numerous composing units exist, which leads to the outstanding application of composites. This review focuses on nucleic acid-based bioapplications of MNCs with polymeric, organic, inorganic, biomolecules, and bioinspared surface coating. In addition, different forms, such as core–shell, doping, multilayer, yolk–shell, and Janus-shaped hybrids, are discussed, and their unique properties are highlighted. The unique types of nanocomposites as magnetic molecularly imprinted polymer (MMIP) properties are presented. This review presents only the synthesis of MNCs using ready-made magnetic cores. These restrictions are associated with many materials, the quantitative and qualitative magnetic core composition, and synthesis procedures. This review aims to discuss the features of nucleic acid-based MNC information available to researchers in this field and guide them through some problems in the area, structure variation, and surface functionalization possibilities. The most recent advancements of MNCs and imprinted polymers in nucleic acid-based therapy, diagnostics, theranostics, magnetic separation, biocatalytic, and biosensing are introduced.

A Comparison of MRI Quantitative Susceptibility Mapping and TRUST-Based Measures of Brain Venous Oxygen Saturation in Sickle Cell Anaemia.

In recent years, interest has grown in the potential for magnetic resonance imaging (MRI) measures of venous oxygen saturation (Yv) to improve neurological risk prediction. T2-relaxation-under-spin-tagging (TRUST) is an MRI technique which has revealed changes in Yv in patients with sickle cell anemia (SCA). However, prior studies comparing Yv in patients with SCA relative to healthy controls have reported opposing results depending on whether the calibration model, developed to convert blood T2 to Yv, is based on healthy human hemoglobin (HbA), bovine hemoglobin (HbBV) or sickle hemoglobin (HbS). MRI Quantitative Susceptibility Mapping (QSM) is an alternative technique that may hold promise for estimating Yv in SCA as blood magnetic susceptibility is linearly dependent upon Yv, and no significant difference has been found between the magnetic susceptibility of HbA and HbS. Therefore, the aim of this study was to compare estimates of Yv using QSM and TRUST with five published calibration models in healthy controls and patients with SCA. 17 patients with SCA and 13 healthy controls underwent MRI. Susceptibility maps were calculated from a multi-parametric mapping acquisition and Yv was calculated from the mean susceptibility in a region of interest in the superior sagittal sinus. TRUST estimates of T2, within a similar but much smaller region, were converted to Yv using five different calibration models. Correlation and Bland-Altman analyses were performed to compare estimates of Yv between TRUST and QSM methods. For each method, t-tests were also used to explore group-wise differences between patients with SCA and healthy controls. In healthy controls, significant correlations were observed between QSM and TRUST measures of Yv, while in SCA, there were no such correlations. The magnitude and direction of group-wise differences in Yv varied with method. The TRUST-HbBV and QSM methods suggested decreased Yv in SCA relative to healthy controls, while the TRUST-HbS (p < 0.01) and TRUST-HbA models suggested increased Yv in SCA as in previous studies. Further validation of all MRI measures of Yv, relative to ground truth measures such as O15 PET and jugular vein catheterization, is required in SCA before QSM or TRUST methods can be considered for neurological risk prediction.

Comparison between Magnetic Resonance Imaging and Ultrasound in Diagnosing Uterine Fibroids in Hail Area, Saudi Arabia

Uterine fibroids (also known as leiomyomas or myomas) are the most common benign uterine tumors. Aim of the study: We aimed to evaluate the role and potential of Magnetic resonance imaging (MRI) to add information to the ultrasound report by comparing the total number, size, and location of fibroids present. This is a comparative cross-sectional study including 50 patients, aged from 20 to 50 years; they were diagnosed as uterine fibroids patients by ultrasound. The data were obtained from the P

Which Parameter Influences Local Disease-Free Survival after Radiation Therapy Due to Osteolytic Metastasis? A Retrospective Study with Pre- and Post-Radiation Therapy MRI including Diffusion-Weighted Images.

Although radiation therapy (RT) plays an important role in the palliation of localized bone metastases, there is no consensus on a reliable method for evaluating treatment response. Therefore, we retrospectively evaluated the potential of magnetic resonance imaging (MRI) using apparent diffusion coefficient (ADC) maps and conventional images in whole-tumor volumetric analysis of texture features for assessing treatment response after RT. For this purpose, 28 patients who received RT for osteolytic bone metastasis and underwent both pre- and post-RT MRI were enrolled. Volumetric ADC histograms and conventional parameters were compared. Cox regression analyses were used to determine whether the change ratio in these parameters was associated with local disease progression-free survival (LDPFS). The ADCmaximum, ADCmean, ADCmedian, ADCSD, maximum diameter, and volume of the target lesions after RT significantly increased. Change ratios of ADCmean < 1.41, tumor diameter ≥ 1.17, and tumor volume ≥ 1.55 were significant predictors of poor LDPFS. Whole-tumor volumetric ADC analysis might be utilized for monitoring patient response to RT and potentially useful in predicting clinical outcomes.

Exploring the predictive value of lesion topology on motor function outcomes in a porcine ischemic stroke model

Harnessing the maximum diagnostic potential of magnetic resonance imaging (MRI) by including stroke lesion location in relation to specific structures that are associated with particular functions will likely increase the potential to predict functional deficit type, severity, and recovery in stroke patients. This exploratory study aims to identify key structures lesioned by a middle cerebral artery occlusion (MCAO) that impact stroke recovery and to strengthen the predictive capacity of neuroimaging techniques that characterize stroke outcomes in a translational porcine model. Clinically relevant MRI measures showed significant lesion volumes, midline shifts, and decreased white matter integrity post-MCAO. Using a pig brain atlas, damaged brain structures included the insular cortex, somatosensory cortices, temporal gyri, claustrum, and visual cortices, among others. MCAO resulted in severely impaired spatiotemporal gait parameters, decreased voluntary movement in open field testing, and higher modified Rankin Scale scores at acute timepoints. Pearson correlation analyses at acute timepoints between standard MRI metrics (e.g., lesion volume) and functional outcomes displayed moderate R values to functional gait outcomes. Moreover, Pearson correlation analyses showed higher R values between functional gait deficits and increased lesioning of structures associated with motor function, such as the putamen, globus pallidus, and primary somatosensory cortex. This correlation analysis approach helped identify neuroanatomical structures predictive of stroke outcomes and may lead to the translation of this topological analysis approach from preclinical stroke assessment to a clinical biomarker.

Microfluidic-based fabrication and characterization of drug-loaded PLGA magnetic microspheres with tunable shell thickness

To overcome the shortcoming of conventional transarterial chemoembolization (cTACE) like high systemic release, a novel droplet-based flow-focusing microfluidic device was fabricated and the biocompatible poly(lactic-co-glycolic acid) (PLGA) magnetic drug-eluting beads transarterial chemoembolization (TACE) microspheres with tunable size and shell thickness were prepared via this device. Paclitaxel, as a model active, was loaded through O/O/W emulsion method with high efficiency. The size and the shell thickness vary when adjusting the flow velocity and/or solution concentration, which caters for different clinical requirements to have different drug loading and release behavior. Under the designed experimental conditions, the average diameter of the microspheres is 60 ± 2 μm and the drug loading efficiency has reached 6%. The drug release behavior of the microspheres shows the combination of delayed release and smoothly sustained release profiles and the release kinetics differ within different shell thickness. The microspheres also own the potential of magnetic resonance imaging (MRI) visuality because of the loaded magnetic nanoparticles. The microsphere preparation method and device we proposed are simple, feasible, and effective, which have a good application prospect.

Application of MRI Radiomics-Based Machine Learning Model to Improve Contralateral BI-RADS 4 Lesion Assessment.

ObjectiveThis study aimed to explore the potential of magnetic resonance imaging (MRI) radiomics-based machine learning to improve assessment and diagnosis of contralateral Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions in women with primary breast cancer.Materials and MethodsA total of 178 contralateral BI-RADS 4 lesions (97 malignant and 81 benign) collected from 178 breast cancer patients were involved in our retrospective dataset. T1 + C and T2 weighted images were used for radiomics analysis. These lesions were randomly assigned to the training (n = 124) dataset and an independent testing dataset (n = 54). A three-dimensional semi-automatic segmentation method was performed to segment lesions depicted on T2 and T1 + C images, 1,046 radiomic features were extracted from each segmented region, and a least absolute shrinkage and operator feature selection method reduced feature dimensionality. Three support vector machine (SVM) classifiers were trained to build classification models based on the T2, T1 + C, and fusion image features, respectively. The diagnostic performance of each model was evaluated and tested using the independent testing dataset. The area under the receiver operating characteristic curve (AUC) was used as a performance metric.ResultsThe T1+C image feature-based model and T2 image feature-based model yielded AUCs of 0.71 ± 0.07 and 0.69 ± 0.07 respectively, and the difference between them was not significant (P > 0.05). After fusing T1 + C and T2 imaging features, the proposed model’s AUC significantly improved to 0.77 ± 0.06 (P < 0.001). The fusion model yielded an accuracy of 74.1%, which was higher than that of the T1 + C (66.7%) and T2 (59.3%) image feature-based models.ConclusionThe MRI radiomics-based machine learning model is a feasible method to assess contralateral BI-RADS 4 lesions. T2 and T1 + C image features provide complementary information in discriminating benign and malignant contralateral BI-RADS 4 lesions.

Diagnostic potential of magnetic resonance imaging (MRI) of the first carpometacarpal joint in hand osteoarthritis

Aim of this workTo assess the magnetic resonance imaging (MRI) findings compared to plain X-ray in patients with primary nodal osteoarthritis (OA) of first the carpometacarpal (CMC) joint of the thumb. Patients and methodsThis study included 35 Egyptian patients with primary nodal hand OA (HOA) and 15 healthy subjects of matched age. Each subject had plain X-rays graded by Kellgren and Lawrence (K–L) score for HOA. MRI testing of both hands done by using T1/T2 weighted axial and coronal images. ResultsThe mean age was 57.2 ± 8.3 years (45–72 years) and they were 24 females and 11 males. Disease duration of patients ranged (8 months to 10 years, 2.04 ± 1.06 years). In all HOA patients there were signs of knee OA involvement; synovial thickening in 51.4% of patients, knee effusion in 8.6%, limited knee ROM in 28.6% and night pain in 60%. There was a superiority of the MRI in detecting synovitis (71.4%), flexor tenosynovitis (71.4%), collateral ligament (60%), bone marrow lesion (85.7%) and cysts (57.1%) compared to the X-ray which could not detect them. MRI significantly detected osteophytes (88.6%), joint space narrowing (91.4%), erosions (85.7%) and malalignment (57.1%) compared to X-ray (51.4%, 62.9%, 34.3% and 14.3% respectively) (p < 0.001, p = 0.004, p < 0.001 and p < 0.001). ConclusionMRI is superior in detecting HOA changes compared to conventional radiography. As OA is recognized to involve the whole joint, modern imaging techniques such as MRI could be a valuable tool for better evaluation of HOA.

Non-Invasive Assessment of Hypoxia and Neovascularization with MRI for Identification of Aggressive Breast Cancer.

The aim of this study was to investigate the potential of magnetic resonance imaging (MRI) for a non-invasive synergistic assessment of tumor microenvironment (TME) hypoxia and induced neovascularization for the identification of aggressive breast cancer. Fifty-three female patients with breast cancer underwent multiparametric breast MRI including quantitative blood-oxygen-level-dependent (qBOLD) imaging for hypoxia and vascular architecture mapping for neovascularization. Quantitative MRI biomarker maps of oxygen extraction fraction (OEF), metabolic rate of oxygen (MRO2), mitochondrial oxygen tension (mitoPO2), microvessel radius (VSI), microvessel density (MVD), and microvessel type indicator (MTI) were calculated. Histopathology was the standard of reference. Histopathological markers (vascular endothelial growth factor receptor 1 (FLT1), podoplanin, hypoxia-inducible factor 1-alpha (HIF-1alpha), carbonic anhydrase 9 (CA IX), vascular endothelial growth factor C (VEGF-C)) were used to confirm imaging biomarker findings. Univariate and multivariate regression analyses were performed to differentiate less aggressive luminal from aggressive non-luminal (HER2-positive, triple negative) malignancies and assess the interplay between hypoxia and neoangiogenesis markers. Aggressive non-luminal cancers (n = 40) presented with significantly higher MRO2 (i.e., oxygen consumption), lower mitoPO2 values (i.e., hypoxia), lower MTI, and higher MVD than less aggressive cancers (n = 13). Data suggest that a model derived from OEF, mitoPO2, and MVD can predict tumor proliferation rate. This novel MRI approach, which can be easily implemented in routine breast MRI exams, aids in the non-invasive identification of aggressive breast cancer.

Noninvasive imaging of vascular permeability to predict the risk of rupture in abdominal aortic aneurysms using an albumin-binding probe

Abdominal aortic aneurysm (AAA) remains a fatal disease. Its development encompasses a complex interplay between hemodynamic stimuli on and changes in the arterial wall. Currently available biomarkers fail to predict the risk of AAA rupture independent of aneurysm size. Therefore, novel biomarkers for AAA characterization are needed. In this study, we used a mouse model of AAA to investigate the potential of magnetic resonance imaging (MRI) with an albumin-binding probe to assess changes in vascular permeability at different stages of aneurysm growth. Two imaging studies were performed: a longitudinal study with follow-up and death as endpoint to predict rupture risk and a week-by-week study to characterize AAA development. AAAs, which eventually ruptured, demonstrated a significantly higher in vivo MR signal enhancement from the albumin-binding probe (p = 0.047) and a smaller nonenhancing thrombus area compared to intact AAAs (p = 0.001). The ratio of albumin-binding-probe enhancement of the aneurysm wall to size of nonenhancing-thrombus-area predicted AAA rupture with high sensitivity/specificity (100%/86%). More advanced aneurysms with higher vascular permeability demonstrated an increased uptake of the albumin-binding-probe. These results indicate that MRI with an albumin-binding probe may enable noninvasive assessment of vascular permeability in murine AAAs and prediction of rupture risk.

Residual Visual Responses in Patients With Retinitis Pigmentosa Revealed by Functional Magnetic Resonance Imaging.

PurposeWe evaluated the potential of magnetic resonance imaging in identifying signs of cortical visual processing with greater sensitivity than standard ophthalmological measures in patients with retinitis pigmentosa (RP) at advanced stages.MethodsEight patients affected with RP with only bare light perception and weak or absent visual evoked potential (VEP) or electroretinogram (ERG) responses to flashes of light were tested. Visual impairment was evaluated by means of psychophysical testing, where patients were asked to discriminate the drifting direction of a contrast modulated grating. Patients underwent magnetic resonance imaging scanning, and the behavioral performance was correlated with both blood oxygenation level-dependent (BOLD) signal elicited by flashes of lights and cortical thickness measured in primary visual area.ResultsContrast sensitivity to drifting gratings of very low spatial and temporal frequency was greatly impaired, yet measurable in all patients. Weak luminance flashes elicited significant BOLD responses in the striate and extrastriate cortex, despite that the stimuli were not perceived during scanning. Importantly, patients with less severe impairment of contrast sensitivity showed stronger V1 BOLD responses. Striate cortical thickness did not correlate with visual sensitivity.ConclusionsBOLD responses provide a sensitive and reliable index of visual sparing more than VEPs or ERGs, which are often absent in RP patients. The minimal residual vision can be assessed by optimal visual stimulation in two alternative forced choice discrimination tasks and by BOLD responses. Imaging techniques provide useful information to monitor progressive vision loss.Translational RelevanceFunctional magnetic resonance imaging might be a practical tool for assessing visual sparing, as it is more feasible and sensitive than psychophysical or ophthalmological testing.

Diagnostic Potential of Magnetic Resonance Imaging in Chronic Abdominal Pain

Introduction: About half of the adult patients suffering from chronic abdominal pain may have no organ-related cause. Our purpose was to evaluate the additional information of magnetic resonance imaging (MRI) in diagnosing the underlying organic causes of such pain. Methods: We performed retrospective audit of 636 consecutive abdominal MRI in patients suffering from nonspecific abdominal pain (NSAP) during years 2014–2017. Medical history, clinical examination, endoscopy reports, and the results of MRI were compared in all patients. The hypothesis was that MRI increases markedly the diagnostic specificity of patients’ symptoms. Results: The mean age of patients was 66 ± 14 years and 60 percent were females. Duration of abdominal pain ranged from 1 month to 30 years (median 1.1 ± 4.0 years). Concurrently with abdominal MRI (n = 636), also ultrasound (n = 106, 17%), colonoscopy (n = 222, 35%), and gastroscopy (n = 217, 34%) were performed. Abdominal MRI revealed additional information in 161/636 (25%) of NSAP patients. Spinal and pelvic bone abnormalities (n = 107) and malignant tumors (n= 31) were the most significant organ-specific findings changing the treatment algorithm. Conclusions: When computerized tomography is not available in outpatient clinics, abdominal MRI increases markedly diagnostic specificity and alters the treatment in 1 of 4 patients suffering from NSAP. Abdominal MRI is therefore suggested for patients suffering from severe symptoms of NSAP.

Monitoring of diffusion properties and transverse relaxation time of mouse ischaemic muscle after administration of human mesenchymal stromal cells derived from adipose tissue.

ObjectivesApplication of non‐invasive imaging methods plays an important role in the assessment of cellular therapy effects in peripheral artery disease. The purpose of this work was to evaluate the kinetics of MRI‐derived parameters characterizing ischaemic hindlimb muscle after administration of human mesenchymal stromal cells derived from adipose tissue (hADSC) in mice.Materials and methodsMRI experiments were performed on a 9.4T Bruker system. The measurement protocol included transverse relaxation time mapping and diffusion tensor imaging. The monitoring period encompassed 14 days after femoral artery ligation and subsequent cell administration. The effect of hADSC transplantation was compared with the effect of normal human dermal fibroblasts (NHDFs) and phosphate‐buffered saline injection.ResultsThe most significant differences between the hADSC group and the remaining ones were observed around day 3 after ischaemia induction (increased transverse relaxation time in the hADSC group in comparison with the control group) and around day 7 (increased transverse relaxation time and decreased third eigenvalue of the diffusion tensor in the hADSC group in comparison with the control and NHDF groups) at the site of hADSC injection. Histologically, it was associated with increased macrophage infiltration at days 3‐7 and with the presence of small regenerating fibres in the ischaemic tissue at day 7.ConclusionsOur results underscore the important role of macrophages in mediating the therapeutic effects of hADSCs and confirm the huge potential of magnetic resonance imaging in monitoring of cellular therapy effects.

Comparison of T1 Mapping and T1rho Values with Conventional Diffusion-weighted Imaging to Assess Fibrosis in a Rat Model of Unilateral Ureteral Obstruction

The aim of this study was to investigate the potential of magnetic resonance imaging (MRI) T1 mapping and T1 relaxation time in the rotating frame (T1rho) for assessment of renal fibrosis in a rat model of unilateral ureteral obstruction (UUO). UUO was created in 36 rats. Six rats were scanned at each of the six time points (on days 0, 1, 3, 5, 10, and 15 after UUO). The contralateral kidneys were examined as controls. Hematoxylin-eosin, Masson's trichrome, and alpha-smooth muscle actin (α-SMA) antibody staining assays were performed. MRI data obtained with a 3.0T scanner were analyzed with α-SMA expression and Masson's staining. The T1 relaxation times and T1rho values increased, and the mean apparent diffusion coefficient (ADC) values decreased with time after UUO. Simple regression analysis indicated that the mean ADCs, T1 relaxation times, and T1rho values had strong correlations with the α-SMA expression levels (R2 = 0.34, R2 = 0.66, R2 = 0.71, respectively; P< .001) and positive Masson's staining (R2 = 0.38, R2 = 0.67, R2 = 0.65, respectively; P< .001). The T1 mapping and T1rho parameters had better correlations with α-SMA expression and Masson's staining than ADC values.