OBJECTIVES:Quantitative multinuclear MRI of bone is hindered by magnetic field (B0 and B1) inhomogeneities, calibration inconsistencies, and segmentation challenges. We developed a comprehensive and versatile MATLAB-based graphical interface that integrates voxel-wise B1 correction, auto and manual segmentation, coregistration, advanced visualization, and quantitative analysis with in-scan dual-density calibration, to generate reproducible bone matrix and mineral density maps from 1H and 31P ZTE MRI. MATERIALS AND METHODS:The postprocessing package was developed in MATLAB using a modular architecture comprising multiple m-files for B1 field correction, B0 bias correction, auto and manual image registration, and segmentation for quantitative data analysis. Otsu-based thresholding with min-max intensity normalization was employed for tissue segmentation and bias correction. Data from control, ovariectomized, and vitamin D-deficient rat femurs were analyzed using normality (Shapiro-Wilk) and variance (Levene) tests. Between-group comparisons used the Kruskal-Wallis test or analysis of variance with Bonferroni or Tukey post hoc tests, respectively. Cross-modality correlation analyses were conducted between MRI-derived measures and reference measures (µCT and gravimetry) using Pearson and Spearman coefficients. RESULTS:MRI-derived mineral density strongly correlated with µCT BMD (cortical [P = 0.22], trabecular [P = 0.31]), and the MRI matrix density correlated with the gravimetric data (cortical [P = 0.38], trabecular [P = 0.57]). No significant differences were observed between modalities for either cortical or trabecular bone. CONCLUSION:This standardized pipeline enables reproducible, calibrated bone density mapping for data sizes ranging from 64 × 64 × 64 to 512 × 512 × 512, with B1 and B0 corrections assessing matrix and mineral densities. Its implementation as a user-guided graphical user interface promotes adoption for preclinical and clinical quantitative bone imaging across experimental conditions.
Introduction:Breast cancer is a global issue impacting women's well-being, highlighting the importance of early detection to improve treatment outcomes and decrease mortality rates. This study aimed to assess various AI methodologies to classify breast images into normal, benign, and malignant. METHODS:A hybrid of 4 CNN-pertained networks-Res-Net18, Mobile-Net, Shuffle-Net, and Inception-V3-were applied on 269 mammograms and 267 dynamic contrast-enhanced MRI examinations. Transfer learning was used, adapting the last fully connected layers to classify 3 classes (normal, benign, and malignant) resulting in 12 features. Support vector machine was employed to categorize images. Classifier performances were evaluated using the confusion matrix, accuracy, precision, sensitivity, specificity, F1 score, and area under the receiver operating curve (AUC-ROC). RESULTS:Res-Net model achieved the highest accuracy, sensitivity, and specificity of 90.89%, 90.93%, and 95.39%, respectively. Whereas Shuffle-Net displayed the lowest accuracy of 84.76%. The AUC ranged between 0.95 and 0.97 among pretrained networks while it was higher (0.99) for the hybrid model. For MRI image classification, the Mobile-net network recorded the highest accuracy, sensitivity, and specificity of 88.55%, 88.49%, and 94.22%, respectively, while the Res-Net exhibited the lowest accuracy of 84.35%. The AUC ranged between 0.94 and 0.96 among pretrained networks while it was higher (0.98) for the Hybrid model. CONCLUSION:ResNet-18 showed the most optimal model for extracting features from mammograms compared with other CNN networks (Mobile-Net, Shuffle-Net, and Inception-V3) while Mobile-Net model was the most suitable in MRI. The effectiveness of deep learning in accurately classifying mammograms and MRI images can be improved by using a hybrid model.
BACKGROUND AND AIM:Brain metastases (BMs) are the most common intracranial malignancy, often arising from lung, breast, and melanoma cancers. Receptor tyrosine kinases, such as EGFR and HER2, drive tumor progression and resistance to therapy. Noninvasive detection of these biomarkers, especially in brain metastases, is crucial due to challenges with traditional biopsy methods. This systematic review and meta-analysis assess machine learning (ML)-based models for detecting EGFR mutations and HER2 overexpression in metastatic brain adenocarcinoma using MRI-derived radiomic features. METHODS:A systematic review and meta-analysis were conducted following PRISMA 2020 guidelines. Studies were identified via PubMed, Scopus, and Web of Science, focusing on ML applications to MRI radiomics for detecting EGFR and HER2 in brain metastases. Data on study design, imaging modality, model type, sample size, and performance metrics were extracted. Subgroup analyses were performed by model type (deep learning vs. classical ML) and sample size (<150 vs. ≥150 participants). A random-effects model was used to pool performance metrics, and risk of bias was assessed using the RoB 2 tool. STATA version 18 and Python 3.10 were used for analyses and visualizations. RESULTS:Of 383 identified studies, 31 (7925 participants) met the inclusion criteria. The pooled analysis showed strong diagnostic performance: AUC = 0.84, accuracy = 0.86, and sensitivity = 0.83. Subgroup analysis revealed higher AUC and accuracy in deep learning models compared with classical ML. Sensitivity analysis also indicated improved AUC in studies with larger sample sizes (≥150), though variability remained. No evidence of heterogeneity or publication bias was detected. CONCLUSION:ML models demonstrate strong diagnostic performance for detecting EGFR and HER2 in metastatic brain adenocarcinoma, supporting their potential as noninvasive diagnostic tools. However, these findings should be interpreted considering methodological heterogeneity and the limited use of external validation. Further prospective, multicenter studies are warranted to confirm their clinical applicability and generalizability.
Magnetic resonance imaging (MRI) is essential for diagnosis but often induces anxiety, especially in claustrophobic patients, potentially affecting image quality. This study compared oxygen saturation, heart rate, and anxiety levels between claustrophobic and non-claustrophobic patients undergoing closed and open MRI in Erbil, Iraq. The comparative study was conducted from October 2024 to April 2025 in the Radiology Departments of Consultant Medical City and Top Med Medical Complex Centers in Erbil using purposive sampling. The questionnaire contained 3 sections: sociodemographic variables, the Claustrophobia Questionnaire, and the State-Trait Anxiety Inventory-State Subscale. Physiological measures (oxygen saturation and heart rate) were recorded at 3 timepoints: pre-, mid-, and post-MRI. Statistical analyses included one-way ANOVA, repeated measures ANOVA, post hoc tests, and both univariate and multiple linear regression, using SPSS version 26. A total of 125 participants were involved in the study. The mean anxiety score was moderate, with higher levels in claustrophobic patients. Claustrophobia scores also fell within the moderate range, indicating psychological discomfort during the MRI procedure. Physiological measurements showed that claustrophobic patients, particularly those undergoing closed MRI, experienced elevated heart rates and reduced oxygen saturation compared to non-claustrophobic individuals. Statistical analysis indicated a strong positive association between anxiety and claustrophobia, with scan entry direction, age, and sex also being significant predictors of claustrophobic responses. Claustrophobic patients undergoing closed MRI experience increased anxiety and physiological distress. Open MRI systems and pre-scan anxiety screening are recommended to enhance patient comfort and diagnostic outcomes.
AIMS:Cardiac tumors are aggressive and asymptomatic in early stages, causing late diagnosis and locoregional metastasis. Currently, the standard of care uses gadolinium-based contrast agents for MRI, and the associated hypersensitivity reactions are a significant concern, such as gadolinium deposition disease. In addition, the proximity of cardiac lesions closer to vital structures complicates surgical interventions. We envisage the development of a scalable, Gd-free, multimodal contrast agent based on EDTA bisamide with pyridine-based fluorophore (L1). The diagnostic arm should have manganese (Mn)-enhanced high relaxivity for MRI and high sensitivity for PET and/or optical imaging (eg, fluorescence lifetime imaging), with comparable/higher than commercial diagnostic agents, along with the multikinase targeted anticancer activity and strong affinity for human serum albumin. MATERIAL AND METHODS:Mn complex of EDTA bisamide of 4-(aminomethyl)pyridine (L1), MnL1, was reproduced in high yield (77%) and purity (98%), characterized by liquid chromatography-mass spectrometry (LC-MS). The solubility in water and stability in sodium acetate buffer were evaluated. T1 mapping followed by static and dynamic contrast-enhanced MRI (DCE_MRI) image acquisition, post-tail vein injection of healthy C57BL/6 mice through I.V. with 1mM of MnL1/PBS was carried out by 3T-MRI (BioSpec, Bruker), wherein standard gadobutrol was used as control. Optical properties of L1 dissolved in solvent mixtures of dimethyl sulfoxide were optimized using PhotonIMAGER RT OPTIMA by Biospace Lab with AlexaFluor750 as the positive control. Docking studies with FAP and EGFR kinases were conducted by AutoDock Vina, followed by MD simulation (My Presto). RESULTS:LC-MS: The highest UV absorption peak was correlated to more than 80% relative abundance of the highest molecular ion peak in mass spectra (cal: 525.18234; found 525.750), indicating strong chelation of L1 to Mn (II). 3T-MRI data of MnL1 revealed comparable performance with a standard gadobutrol. L1 exhibited multiple excitation wavelengths and NIR1 emission. DCE-MRI revealed contrasting dynamics with strong uptake in the kidney, liver, and heart. Docking studies revealed inhibition of FAP (allosteric) and EGFR (-7.0 and 6.7 Kcal/mol), validated by their respective cocrystallized ligands and commercial standards and by MD simulation, reflecting constant gyration ratios and strong hydrogen bonding. CONCLUSION:Preclinical MRI imaging justified the efficacy of Mn(II)L1. L1 validated as a promising visible and NIR1dye along with its ability to bind and inhibit pan-cancer targets, FAP (allosteric) and EGFR kinases. Previously validated features of lifetime sensing/high stokes shift and Cu (II) quenching are also noteworthy. Dual-echo acquisitions for quantitative DCE-MRI as a standalone (with T2* corrections) or in combination with PET/MRI of 64Cu-L1(separately studied) or as 52MnL1 by single injection envisaged. T1 mapping for therapy response monitoring based on the reduction of native tumor T1 upon binding of MnL1 to the kinase is hereby envisaged for the future.
BACKGROUND:Anterior shoulder dislocation is the most common dislocation in the musculoskeletal system, frequently occurring in traumatic events and athletic activities. Many anatomical features of this joint have been reported to be risk factors for anterior shoulder dislocation with inconsistent findings, in which these features can be detected using magnetic resonance imaging (MRI) as a safe observational tool rather than a diagnostic one. This study aims to determine the independent and most relevant risk factor(s) of anterior shoulder dislocation. MATERIALS AND METHODS:This retrospective case-control study was based on 2 groups (control and dislocated) of 49 MRI series each. These MRI series were selected after reviewing 3950 MRI series from patients who visited the orthopaedic clinic at a university hospital for shoulder issues. The study measured and statistically compared various parameters between the 2 groups, including glenoid version, coracohumeral distance, humeral containing angle, glenoid height, depth and width (diameter), humeral head diameter, glenoid width-to-depth ratio, glenoid height-to-diameter ratio, and humeral diameter-to-glenoid width ratio. RESULTS:Each group consisted of 49 MRI series from patients aged 17-75 years. The independent parameters associated with anterior shoulder dislocation were the height-to-width ratio and width-to-depth ratio with cut-off points of >1.65 and >13.15, respectively (P < 0.05). Other investigated risk factors were either not associated or were not significant predictors of shoulder dislocation. CONCLUSION:This study found that the glenoid width-to-depth ratio and the glenoid height-to-diameter ratio are the most relevant independent risk factors for developing anterior shoulder dislocation. A higher glenoid width-to-depth ratio and a higher glenoid height-to-diameter ratio were both associated with an increased risk of anterior shoulder dislocation compared with lower ratios.
ABSTRACT:Rectal MRI studies used to stage and guide surgical or nonsurgical management of rectal cancer may harbor incidental findings (IFs) of varying significance. St George's Hospital uses a four-sequence MRI protocol which does not employ diffusion-weighted imaging (DW-MRI). OBJECTIVES:To determine the frequency and significance of incidental findings identified when using a rectal MRI protocol which does not employ DW-MRI. METHODS:Retrospective analysis of rectal MRI study reports for IFs and stratifying their significance. Medical records were reviewed to clarify IFs of interest. RESULTS:One hundred thirty-four studies met the inclusion criteria for the study (75 men, mean age 65). 51/134 (38%) of studies had IFs. Fifteen percent (n = 7/46) of baseline studies for a new cancer had significant IFs. The commonest IF was diverticular disease (n = 10); however, a bladder malignancy was also identified. CONCLUSION:Clinically significant IFs exist in 12% of patients undergoing rectal MRI, and any type of IFs exist in 38% of patients undergoing rectal MRI studies. The rate of significant IFs is comparable with other authors both in rectal and prostate MRI but with fewer overall IFs, possibly due to the lack of DW-MRI sequences in our local protocol. Our study is the first to assess IFs using a rectal MRI protocol which does not employ DW-MRI, and the results should be considered by centers when planning their rectal MRI protocol.
OBJECTIVES:To develop and evaluate a deep learning technique for the differentiation of hepatocellular carcinoma (HCC) using "simplified intravoxel incoherent motion (IVIM) parameters" derived from only 3 b-value images. MATERIALS AND METHODS:Ninety-eight retrospective magnetic resonance imaging data were collected (68 men, 30 women; mean age 59 ± 14 years), including T2-weighted imaging with fat suppression, in-phase, out-of-phase, and diffusion-weighted imaging (b = 0, 100, 800 s/mm2). Ninety percent of data were used for stratified 10-fold cross-validation. After data preprocessing, diffusion-weighted imaging images were used to compute simplified IVIM and apparent diffusion coefficient (ADC) maps. A 17-layer 3D convolutional neural network (3D-CNN) was implemented, and the input channels were modified for different strategies of input images. RESULTS:The 3D-CNN with IVIM maps (ADC, f, and D*) demonstrated superior performance compared with other strategies, achieving an accuracy of 83.25 ± 6.24% and area under the receiver-operating characteristic curve of 92.70 ± 8.24%, significantly surpassing the baseline of 50% (P < 0.05) and outperforming other strategies in all evaluation metrics. This success underscores the effectiveness of simplified IVIM parameters in combination with a 3D-CNN architecture for enhancing HCC differentiation accuracy. CONCLUSIONS:Simplified IVIM parameters derived from 3 b-values, when integrated with a 3D-CNN architecture, offer a robust framework for HCC differentiation.
ABSTRACT:Magnetic resonance imaging (MRI) is used for diagnosing placenta accreta spectrum disorders (PASDs) because of its advanced soft-tissue contrast and spatial resolution capabilities, offering better contrast, improved spatial resolution, and a wider field of view compared with ultrasound. Using a 1.5-Tesla MRI protocol with multiple sequences, MRI can detect indicative signs of PASD such as placental signal heterogeneity, interruption of the myometrium-placenta interface, and abnormal vascularization. Specific sequences such as T2 SSFSE, FIESTA, and T1-weighted and diffusion-weighted imaging are used to assess placental attachment, myometrial invasion, and intraplacental hemorrhages. Significant MRI findings include thick low-signal T2 intraplacental bands, invasions into the cervix or bladder, and abnormal periplacental vascularity. MRI complements ultrasound and is crucial for the prenatal diagnosis of PASD, aiding in treatment planning and patient management, thereby reducing the associated fetal and maternal morbidity and mortality. The objective of this pictorial review was to outline the placental MRI technique and review the main imaging findings in placental MRI for PASD. This review encompasses anonymized patient images obtained following written consent.
BACKGROUND:Since magnetic resonance imaging (MRI) is an extensively used and fundamental diagnostic imaging method and anxiety is one of the most important confounding factors in its performance, using guided imagery is recommended. OBJECTIVE:This study aimed to assess the effectiveness of guided imagery on the anxiety of patients undergoing MRI in 2023. METHODS:88 patients were randomly assigned to intervention and control groups. The intervention group listened to the nature-based guided imagery audio file during their scan, and the control group did not receive any intervention. Data were collected using demographic information and the Spielberger Anxiety Questionnaire before and after the scan. RESULTS:There was no significant difference between the 2 groups before the intervention regarding demographic data and anxiety. In the intervention group, the mean anxiety decreased from 104.0 ± 14.6 to 92.4 ± 9.0, showing a significant reduction in the level of anxiety in both subscales (state and trait) and the total score (P < 0.001), compared with the control group and before the intervention. CONCLUSION:The results showed that using guided imagery could decrease anxiety levels in patients undergoing MRI. Since patients' anxiety is one of the most important nursing diagnoses, performing cognitive methods, including guided imagery, as a simple, safe, inexpensive, and effective intervention should be considered.
OBJECTIVES:The radiological imaging industry is developing and starting to offer a range of novel artificial intelligence software solutions for clinical radiology. Deep learning reconstruction of magnetic resonance imaging data seems to allow for the acceleration and undersampling of imaging data. Resulting reduced acquisition times would lead to greater machine utility and to greater cost-efficiency of machine operations. MATERIALS AND METHODS:Our case shows images from magnetic resonance arthrography under traction of the right hip joint from a 30-year-old, otherwise healthy, male patient. RESULTS:The undersampled image data when reconstructed by a deep learning tool can contain false-positive cartilage delamination and false-positive diffuse cartilage defects. CONCLUSIONS:In the future, precision of this novel technology will have to be put to thorough testing. Bias of systems, in particular created by the choice of training data, will have to be part of those assessments.
BACKGROUND:Altered size in the corpus callosum (CC) has been reported in individuals with autism spectrum disorder (ASD), but few studies have investigated younger children. Moreover, knowledge about the age-related changes in CC size in individuals with ASD is limited.OBJECTIVES:Our objective was to investigate the age-related size of the CC and compare them with age-matched healthy controls between the ages of 2 and 18 years.METHODS:Structural-weighted images were acquired in 97 male patients diagnosed with ASD; published data were used for the control group. The CC was segmented into 7 distinct subregions (rostrum, genu, rostral body, anterior midbody, posterior midbody, isthmus, and splenium) as per Witelson's technique using ITK-SNAP software. We calculated both the total length and volume of the CC as well as the length and height of its 7 subregions. The length of the CC measures was studied as both continuous and categorical forms. For the continuous form, Pearson's correlation was used, while categorical forms were based on age ranges reflecting brain expansion during early postnatal years. Differences in CC measures between adjacent age groups in individuals with ASD were assessed using a Student t-test. Mean and standard deviation scores were compared between ASD and control groups using the Welch t-test.RESULTS:Age showed a moderate positive association with the total length of the CC (r = 0.43; Padj = 0.003) among individuals with ASD. Among the subregions, a positive association was observed only in the anterior midbody of the CC (r = 0.41; Padj = 0.01). No association was found between the age and the height of individual subregions or with the total volume of the CC. In comparison with healthy controls, individuals with ASD exhibited shorter lengths and heights of the genu and splenium of the CC across wide age ranges.CONCLUSION:Overall, our results highlight a distinct abnormal developmental trajectory of CC in ASD, particularly in the genu and splenium structures, potentially reflecting underlying pathophysiological mechanisms that warrant further investigation.
BACKGROUND:Currently, there is no evidence that MRI produces harmful effects on premature newborns, as well as short-term and long-term safety issues regarding radiofrequency fields and loud acoustic environment, while the examination that is being performed has not been clearly investigated. MRI of the brain conducted on preterm infants should be part of the diagnostic workup, when necessary. This article is intended to evaluate the short-term safety of MRI performed in preterm infants, when required, by analyzing all vital parameters available before, during, and after the MRI procedures.METHODS:We conducted a systematic review of the literature on electronic medical databases (PubMed and ClinicalTrials.gov) following the Preferred Reported Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We included all preterm infants who underwent MRI whose clinical, hemodynamic, and respiratory parameters were reported. The quality of the included articles was assessed using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies) tool.RESULTS:Six studies were included with a total of 311 preterm infants. No severe adverse event, such as death, occurred during MRI procedures. Vital signs remained stable in about two-thirds of all patients.CONCLUSIONS:Given the general clinical safety of MRI, we suggest it as a tool to be used in preterm infants in Neonatal Intensive Care Units, when necessary. We further suggest the development of standard protocols to guide the use of MRI in preterm infants to maximize the clinical safety of the procedure.
Abstract In this case report, we describe a 76-year-old woman, presenting with dizziness for the past 2 months, without other focal neurological signs. A magnetic resonance imaging of the brain was ordered by her GP. The MRI demonstrated multiple ring-enhancing lesions, both supratentorial and infratentorial. Lumbar puncture showed normal findings, in particular a normal cell count and culture. Because of the radiologic appearance, initially thought to be suggestive of cerebral abscesses, antibiotics were started. However, further workup revealed a new diagnosis of a stage IV (metastatic) small cell lung carcinoma, making diffuse brain metastases more likely. The patient was transferred to oncology/pneumology, where she was started on whole-brain radiotherapy, after which systemic therapy would start. However, because of further clinical deterioration, she was admitted at the palliative ward, where she died only 3 months after the initial presentation. In this case report, we emphasize the importance of keeping a broad differential diagnosis and briefly review the various possible pathologies causing ring-enhancing lesions.
Abstract: In this case report we describe the case of a 66-year old man with subacute gait difficulties, with a progression to confusion coma with multiple generalised epileptic seizures during the following days. Biochemical analysis showed hyperglycaemia, cerebrospinal fluid (CSF) testing showed a mild lymphocytic pleocytosis and an elevated protein and lactate. Broad-spectrum antibiotics and antiviral therapy where initiated. However, all other CSF testing remained negative. Magnetic resonance imaging of the brain showed remarkably symmetric hyperintense T2 white matter lesions most noticable in the corpus callosum. The lesion pattern was suggestive of a metabolic or toxic encephalopathy, the preponderance for the corpus callosum was furthermore suggestive for Marchiafava-Bignami disease (MDB), as was the clinical course since admission of the patient. A high dose IV substitution of vitamin B1, B6 and B12 was started and antibiotic and antiviral therapy was discontinued. After one day the patient showed progressive regaining of consciousness and he returned to premorbid functioning in a matter of 1-2 weeks. MRI of the brain after 1 week showed notable improvement of the white matter lesions. At routine follow-up two weeks later he presented with icterus and a diagnosis of Epstein-Barr virus (EBV) hepatitis was made, lymph node biopsies showed an EBV positive diffuse large cell B-cell lymphoma (DLCBL). MDB is mostly associated with severe alcoholism, with malnourishment being the second leading cause, however there are case reports describing MDB in patients with chronically poorly controlled diabetes mellitus. We hypothesize that his condition may have been precipitated by his poorly controlled diabetes mellitus. However it is also possible that weight loss (probably related to the DLCBL diagnosis) might have contributed to a state of malnourishment and therefore played a role in the aetiology as well.
ABSTRACT:This report presents imaging from a mediastinal mass in a patient with colon cancer. At baseline and surveillance chest computed tomography examinations, it was characterized as a pericardial cyst. However, during chemotherapy, complications arose and this mass was further characterized with a chest MRI. It was then decided to be removed, and histopathology confirmed the diagnosis of a hemangioma.
Peripheral artery disease (PAD) causes lower extremity dysfunction and is associated with an increased risk of cardiovascular mortality and morbidity. In this study, we analyzed how non-invasive 2-dimensional-phase-contrast magnetic resonance imaging (2D-PC-MRI) measured velocity markers of the distal superficial femoral artery (SFA) are associated with clinical and functional characteristics of PAD. A total of 70 (27 diabetic and 43 non-diabetic) PAD patients were included in this secondary analysis of data collected from the Effect of Lipid Modification on Peripheral Artery Disease after Endovascular Intervention Trial (ELIMIT). Electrocardiographically (ECG)-gated 2D-PC-MRI was performed at a proximal and a distal imaging location of the distal SFA. Baseline characteristics did not differ between diabetic and non-diabetic PAD patients. Claudication onset time (COT) was shorter in diabetic PAD patients compared to non-diabetics (0.56 (inter quartile range (IQR): 0.3, 2.04) minutes vs. 1.30 (IQR: 1.13, 2.15) minutes, p = 0.025). In a pooled analysis of all 70 PAD patients, maximum velocity was significantly higher in the proximal compared with the distal SFA segment (43.97 (interquartile range (IQR): 20.4, 65.2) cm/s; vs. 34.9 (IQR: 16.87, 51.71) cm/s; p < 0.001). The maximum velocities in both the proximal and distal SFA segments were significantly higher in diabetic PAD patients compared with non-diabetics (proximal: 53.6 (IQR: 38.73, 89.43) cm/s vs. 41.49 (IQR: 60.75, 15.9) cm/s, p = 0.033; distal: 40.8 (IQR: 23.7, 71.90) cm/s vs. 27.4 (IQR: 41.67, 12.54) cm/s, p = 0.012). Intra-observer variability, as assessed by intraclass correlation (ICC) analysis, was excellent for SFA mean and maximum velocities (0.996 (confidence interval [CI]: 0.996, 0.997); 0.999 (CI: 0.999, 0.999)). In conclusion, 2D-PC-MRI SFA velocity measures are reproducible and may be of interest in assessing diabetic and non-diabetic PAD patients.
Abstract Background: Skeletal bone age assessment for medical reasons is usually performed by conventional x-ray with use of ionizing radiation. Few pilot studies have shown the possible use of magnetic resonance imaging (MRI). Purpose: To comprehensively evaluate feasibility and value of MRI for skeletal bone age (SBA) assessment in healthy male children. Materials and Methods: In this prospective cross-sectional study, 63 male soccer athletes with mean age of 12.35 ± 1.1 years were examined. All participants underwent 3.0 Tesla MRI with coronal T1-weighted turbo spin echo (TSE), coronal proton density (PD)–weighted turbo spin echo (TSE), and T1-weighted three-dimensional (3D) volume interpolated breath-hold examination (VIBE) sequence. Subsequently, SBA was assessed by 3 independent blinded radiologists with different levels of experience using the common Greulich-Pyle (GP) atlas and the Tanner-Whitehouse (TW2) method. Results: In a mean total acquisition time of 5:04 ± 0:47 min, MR image quality was sufficient in all cases. MRI appraisal was significantly faster (P < 0.0001) by GP with mean duration of 1:22 ± 0:08 min vs. 7:39 ± 0:28 min by TW. SBA assessment by GP resulted in mean age of 12.8 ± 1.2 years, by TW 13.0 ± 1.4 years. Interrater reliabilities were excellent for both GP (ICC = 0.912 (95% confidence interval [CI] = 0.868–0.944) and TW (ICC = 0.988 (95% CI = 0.980–0.992) and showed statistical significance (P < 0.001). Subdivided, for GP, ICCs were 0.822 (95% CI = 0.680–0.907) and 0.843 (95% CI = 0.713–0.919) in Under 12 and Under 14 group. For TW, ICCs were 0.978 (95% CI = 0.958–0.989) in Under 12 and 0.979 (95% CI = 0.961–0.989) in Under 14 group. Conclusion: MRI is a clinically feasible, rapidly evaluable method to assess skeletal bone age of healthy male children. Using the Greulich-Pyle (GP) atlas or the Tanner-Whitehouse (TW2) method, reliable results are obtained independent of the radiologist's experience level.
ME-LLR is demonstrated to suppress non-physiologic noise, enhance functional connectivity map quality, and could potentially facilitate scan time reduction in ME-fMRI.
Abstract Functional 1H magnetic resonance spectroscopy (fMRS) is a derivative of dynamic MRS imaging. This modality links physiologic metabolic responses with available activity and measures absolute or relative concentrations of various metabolites. According to clinical evidence, the mitochondrial glycolysis pathway is disrupted in many nervous system disorders, especially Alzheimer disease, resulting in the activation of anaerobic glycolysis and an increased rate of lactate production. Our study evaluates fMRS with J-editing as a cutting-edge technique to detect lactate in Alzheimer disease. In this modality, functional activation is highlighted by signal subtractions of lipids and macromolecules, which yields a much higher signal-to-noise ratio and enables better detection of trace levels of lactate compared with other modalities. However, until now, clinical evidence is not conclusive regarding the widespread use of this diagnostic method. The complex machinery of cellular and noncellular modulators in lactate metabolism has obscured the potential roles fMRS imaging can have in dementia diagnosis. Recent developments in MRI imaging such as the advent of 7 Tesla machines and new image reconstruction methods, coupled with a renewed interest in the molecular and cellular basis of Alzheimer disease, have reinvigorated the drive to establish new clinical options for the early detection of Alzheimer disease. Based on the latter, lactate has the potential to be investigated as a novel diagnostic and prognostic marker for Alzheimer disease.
