Magnetic Resonance Imaging Sequences Research Articles

MRI and single-cell RNA sequence results reveal the influence of anterior talofibular ligament injury on osteochondral lesions of the talus

Anterior talofibular ligament injuries and osteochondral lesions of the talus present unique challenges to orthopedic surgeons. This study aimed to investigate the relevant relationship between them by analyzing the Magnetic resonance imaging (MRI) results of clinical patients and single-cell RNA sequence (scRNA seq) results of healthy talus cartilage to discuss the risk factors. Data from 164 patients from 2018 to 2023 was retrospectively analyzed. The correlation analysis between ATFL injury grade and the Hepple stage of OLT determined by MRI was performed. Publicly available single-cell RNA datasets were collected. Single-cell RNA datasets from five volunteers of healthy talus cartilage were analyzed. ATFL injury grade was relevant with the Hepple stage of OLT (P < 0.05). The results of multivariate logistic regression analysis showed that injured area was the independent influencing factor of the incidence rate and the severity of OLT (P < 0.05). The Hepple stage of OLT was relevant with AOFAS and VAS (P < 0.05). Single-cell RNA sequence results showed that among the 9 subtypes of chondrocytes, the interaction strength between HTC-A and HTC-B is the highest. Their physical interactions are mainly achieved through the CD99 signaling pathway, and factor interactions are mainly achieved through the ANGPTL signaling pathway. Anterior talofibular ligament injury may lead to osteochondral lesions of the talus. Early medical intervention should be carried out for ligament injuries to restore joint stability and avoid cartilage damage.

Arterial Spin-Labeling MR Imaging in the Detection of Intracranial Arteriovenous Malformations in Patients with Hereditary Hemorrhagic Telangiectasia.

Hereditary hemorrhagic telangiectasia (HHT) is an autosomal dominant disease that causes vascular malformations in a variety of organs and tissues, including brain AVMs. Because brain AVMs have the potential to cause disabling or fatal intracranial hemorrhage, detection of these lesions before rupture is the goal of screening MR imaging/MRA examinations in patients with HHT. Prior studies have demonstrated superior sensitivity for HHT-related brain AVMs by using postcontrast MR imaging sequences as compared with MRA alone. We now present data regarding the incremental benefit of including arterial spin-labeling (ASL) perfusion sequences as part of MR imaging/MRA screening in patients with this condition. We retrospectively analyzed 831 patients at the UCSF Hereditary Hemorrhagic Telangiectasia Center of Excellence. Of these, 42 patients had complete MR imaging/MRA, ASL perfusion scans, and criterion-standard DSA data. Two neuroradiologists reviewed imaging studies and a third provided adjudication when needed. Eight patients had no brain AVMs detected on DSA. The remaining 34 patients had 57 brain AVMs on DSA. Of the 57 identified AVMs, 51 (89.5%) were detected on ASL and 43 (75.4%) were detected on conventional MR imaging/MRA sequences (P = .049), with 8 lesions detected on ASL perfusion but not on conventional MR imaging. ASL provides increased sensitivity for brain AVMs in patients with HHT. Inclusion of ASL should be considered as part of comprehensive MR imaging/MRA screening protocols for institutions taking care of patients with HHT.

Design and validation of the ADNI MR protocol.

Phase four of the Alzheimer's Disease Neuroimaging Initiative (ADNI4) magnetic resonance imaging (MRI) protocols aim to maintain longitudinal consistency across two decades of data acquisition, while adopting new technologies. Here we describe and justify the study's design and targeted biomarkers. The ADNI4 MRI protocol includes nine MRI sequences. Some sequences require the latest hardware and software system upgrades and are continuously rolled out as they become available at each site. The main sequence additions/changes in ADNI4 are: (1) compressed sensing (CS) T1-weighting, (2) pseudo-continuous arterial spin labeling (ASL) on all three vendors (GE, Siemens, Philips), (3) multiple-post-labeling-delay ASL, (4) 1 mm3 isotropic 3D fluid-attenuated inversion recovery, and (5) CS 3D T2-weighted. ADNI4 aims to help the neuroimaging community extract valuable imaging biomarkers and provide a database to test the impact of advanced imaging strategies on diagnostic accuracy and disease sensitivity among individuals lying on the cognitively normal to impaired spectrum. HIGHLIGHTS: A summary of MRI protocols for phase four of the Alzheimer's Disease Neuroimaging Initiative (ADNI 4). The design and justification for the ADNI 4 MRI protocols. Compressed sensing and multi-band advances have been applied to improve scan time. ADNI4 protocols aim to streamline safety screening and therapy monitoring. The ADNI4 database will be a valuable test bed for academic research.

MRI T1-Weighted Fat Segmentation Based on Active Contour for Osteosarcoma Patients

Osteosarcoma (OS) is the most common and frequent primary bone cancer in children and adolescents. This type of bone cancer often developed at the long bones’ extremities close to the metaphyseal growth plates. To address these issues, OS quantitative analysis is performed using Magnetic Resonance Imaging (MRI) to plan surgical procedures and track the effectiveness of treatment. Fat suppression is commonly employed to eliminate the fat signal from T1-Weighted MRI sequence. The suppressed fat signal in T1-Weighted is important and often used to identify abnormalities in other MRI sequences. In clinical, MRI images must be interpreted by a radiologist. Manually outlining the tumour location is laborious and subjective. Image processing involves segmentation to separate information from the desired target region of the image. Active Contour (AC) is an algorithm often used in medical images for segmentation. Nevertheless, the process of mask initialization can be challenging and requires careful attention. This study proposes a method to define the mask initialization so that the AC has a starting point to extract fat in T1-Weighted for the purpose of fat suppression. From the results obtained, AC with the proposed mask initialization method successfully segmented the fat in T1-Weighted MRI images with accuracy, precision, recall and F1-score of 0.92, 0.86, 0.88 and 0.89 respectively.

Overexpression of TIAM2S, a Critical Regulator for the Hippocampal-Medial Prefrontal Cortex Network, Progresses Age-Related Spatial Memory Impairment.

TIAM Rac1-associated GEF 2 short-form protein (TIAM2S) is abundant in specific brain tissues, especially in the hippocampus, a brain region critical for processing and consolidation of spatial memory. However, how TIAM2S plasticizes the microstructure and circuits of the hippocampus to shape spatial memory as a neuroplastic regulator during aging remains to be determined. In this study, transgenic mice overexpressing human TIAM2S protein (TIAM2S-TG mice) were included, and interdisciplinary approaches, such as spatial memory tests and multiparametric magnetic resonance imaging sequences, were conducted to determine the role and the mechanism of TIAM2S in age-related spatial memory deficits. Despite no changes in their neural and glial markers and neuropathological hallmark expression of the hippocampus, behavioral tests showed that the TIAM2S-TG mice, and not wild-type (WT) mice, developed spatial memory impairment at 18 months old. The T2-weighted and diffusion tensor image analyses were performed to further study the possible role of TIAM2S overexpression in altering the hippocampal structure or neuronal circlets of the mice, increasing their vulnerability to developing spatial memory deficits during aging. The results revealed that the 12-month-old TIAM2S-TG mice had hippocampal dysplasticity, with larger volume, increased fiber numbers, and changed mean fractional anisotropy compared to those in the age-matched WT mice. The fiber tractography analysis exhibited significantly attenuated structural connectivity between the hippocampus and medial prefrontal cortex in the TIAM2S-TG mice. In conclusion, overexpression of TIAM2S, a detrimental factor affecting hippocampus plasticity, causes attenuation of the connectivity within hippocampus-mPFC circuits, leading to age-related spatial memory impairment.

Atlantoaxial intra-articular cage fusion by posterior intermuscular approach for treating reducible atlantoaxial dislocation: a technique note with case series.

To evaluate the clinical feasibility of atlantoaxial intra-articular cage (AIC) fusion via intermuscular approach for treating reducible atlantoaxial dislocation (AAD). An analysis was conducted on the data of 10 patients who underwent C1-C2 segmental fixation and AIC fusion for AAD by unilateral intermuscular approach and contralateral open approach. Outcome assessments included Japanese Orthopaedic Association score (JOA) and Visual Analog Scale Score for Neck Pain (VASSNP). The duration of surgical exposure, screw insertion and cage insertion, and postoperative drainage volume were also compared between two approaches. Bone fusion was evaluated through computed tomography (CT) reconstruction. Postoperative paravertebral tissue edema was evaluated by paravertebral tissue cross-sectional area (CSA) and signal intensity on T2 weighted sequence of magnetic resonance imaging (MRI) at 3 days postoperatively. The intermuscular approach exhibited a longer exposure time but lower drainage postoperatively compared to the open approach (P < 0.05). After operation, JOA scores significant improved (P < 0.05), while VASSNP scores significantly decreased (P < 0.05). There was no significant difference in preoperative CSA between two approaches (P > 0.05). However, compared to the open approach, the intermuscular approach exhibited less CSA (P < 0.05) and lower T2 signal intensity on MRI postoperatively, indicating less invasive to the paravertebral tissues. AIC fusion by intermuscular approach is an effective and safe technique in the treatment of reducible AAD. Intermuscular approach could reduce the postoperative drainage volume and the extent of paravertebral tissue edema compared to open approach.

Optimal Magnetic Resonance Sequence for Assessment of Central Cartilage Tumor Scalloping

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

Dose-Dependent Target Engagement of a Clinical iTBS Protocol: An Interleaved TMS-fMRI Study in Healthy Subjects

BackgroundIntermittent theta burst stimulation (iTBS) of the dorsolateral prefrontal cortex (DLPFC) is widely applied as a therapeutic intervention in mental health; however, the understanding of its mechanisms is still incomplete. Prior magnetic resonance imaging studies have mainly used offline iTBS or short sequences in concurrent transcranial magnetic stimulation functional magnetic resonance imaging (fMRI). This study investigated a full 600-stimuli iTBS protocol using interleaved transcranial magnetic stimulation fMRI in comparison with 2 control conditions in healthy subjects. MethodsIn a crossover design, 18 participants underwent 3 sessions of interleaved iTBS-fMRI: 1) the left DLPFC at 40% resting motor threshold (rMT) intensity, 2) the left DLPFC at 80% rMT intensity, and 3) the left primary motor cortex (M1) at 80% rMT intensity. We compared immediate blood oxygen level–dependent (BOLD) responses during interleaved iTBS-fMRI across these conditions including correlations between individual fMRI BOLD activation and iTBS-induced electric field strength at the target sites. ResultsWhole-brain analysis showed increased activation in several regions following iTBS. Specifically, the left DLPFC, as well as the bilateral M1, anterior cingulate cortex, and insula, showed increased activation during 80% rMT left DLPFC stimulation. Increased BOLD activity in the left DLPFC was observed with neither 40% rMT left DLPFC stimulation nor left M1 80% rMT iTBS, whereas activation in other regions was found to overlap between conditions. Of note, BOLD activation and electric field intensities were only correlated for M1 stimulation and not for the DLPFC conditions. ConclusionsThe study showed dosage- and target-specific BOLD activation during interleaved transcranial magnetic stimulation fMRI with 600-stimuli iTBS in healthy individuals. Future studies may use our approach for demonstrating target engagement.

Evaluation of the Articular Disc Using the Magnetic Resonance Cartigram in Asymptomatic and Symptomatic Temporomandibular Disorders

Abstract Objectives The study is aimed to perform magnetic resonance (MR) cartigram of the articular disc in patients with asymptomatic and symptomatic temporomandibular disorders (TMD). Methods Thirty-nine volunteers were divided into three groups: 16 symptomatic TMD, 16 asymptomatic TMD, and 7 controls. The articular disc was divided into three segments (anterior, middle, and posterior) and analyzed using morphological magnetic resonance imaging (MRI) and T2 mapping sequences. T2 relaxation values were measured and assessed by an experienced radiologist and two observers. The T2 values in the discs were compared between the control, asymptomatic, and symptomatic groups using the Kruskal–Wallis test. The right and left discs were compared using the Wilcoxon signed rank test. Inter-examiner reliability among different examiners was evaluated. Results The controls had the highest T2 values compared with the other groups. The comparison among the right and left sides of all the groups revealed statistically significant results in the anterior portion in the asymptomatic group and the middle portion in the symptomatic group (p &lt; 0.05). The inter-examiner reliability coefficients among the three examiners were consistently high, with values of 0.921, 0.920, and 0.930. Conclusion Our study found the T2 relaxation time span was shorter than that reported in previous studies, which could be attributed to the early stage of cartilage deterioration in the individuals with TMD inferring treatment at this phase may be eventually effective with a good prognosis.

Preoperative prediction of microvascular invasion risk in hepatocellular carcinoma with MRI: peritumoral versus tumor region

ObjectivesTo explore the predictive performance of tumor and multiple peritumoral regions on dynamic contrast-enhanced magnetic resonance imaging (MRI), to identify optimal regions of interest for developing a preoperative predictive model for the grade of microvascular invasion (MVI).MethodsA total of 147 patients who were surgically diagnosed with hepatocellular carcinoma, and had a maximum tumor diameter ≤ 5 cm were recruited and subsequently divided into a training set (n = 117) and a testing set (n = 30) based on the date of surgery. We utilized a pre-trained AlexNet to extract deep learning features from seven different regions of the maximum transverse cross-section of tumors in various MRI sequence images. Subsequently, an extreme gradient boosting (XGBoost) classifier was employed to construct the MVI grade prediction model, with evaluation based on the area under the curve (AUC).ResultsThe XGBoost classifier trained with data from the 20-mm peritumoral region showed superior AUC compared to the tumor region alone. AUC values consistently increased when utilizing data from 5-mm, 10-mm, and 20-mm peritumoral regions. Combining arterial and delayed-phase data yielded the highest predictive performance, with micro- and macro-average AUCs of 0.78 and 0.74, respectively. Integration of clinical data further improved AUCs values to 0.83 and 0.80.ConclusionCompared with those of the tumor region, the deep learning features of the peritumoral region provide more important information for predicting the grade of MVI. Combining the tumor region and the 20-mm peritumoral region resulted in a relatively ideal and accurate region within which the grade of MVI can be predicted.Clinical relevance statementThe 20-mm peritumoral region holds more significance than the tumor region in predicting MVI grade. Deep learning features can indirectly predict MVI by extracting information from the tumor region and directly capturing MVI information from the peritumoral region.Key PointsWe investigated tumor and different peritumoral regions, as well as their fusion.MVI predominantly occurs in the peritumoral region, a superior predictor compared to the tumor region.The peritumoral 20 mm region is reasonable for accurately predicting the three-grade MVI.Graphical

Magnetic resonance imaging phantom-based S1 vertebral scores are indicators of fat-water-like osteoporotic changes in postmenopausal women: a pilot study.

A prospective study. To assess fat-water-like tissue changes on the 1st sacral vertebra using novel magnetic resonance imaging (MRI) phantombased F- and W-scores and evaluate their diagnostic performances in osteoporosis detection. Using an uncommonly advanced MRI technique, previous studies have found that fat-water changes were consistent with osteoporosis. The role of routine MRI sequences can be extended in this regard. The S1 vertebra is considered a crucial anatomical site in spine surgeries because it seldom suffers from fractures. Thus, S1 could indicate osteoporotic fat-water changes. Forty-two female volunteers (aged 62.3±6.3 years) underwent spine examination with both MRI (including a phantom) and dual-energy X-ray absorptiometry (DXA) following ethical approval. MRI phantom-based F- and W-scoreS1 were defined by normalizing S1 vertebral signal intensities (SIs) by coconut oil and water SIs of the phantom on T1- and T2-weighted imaging, respectively. Using receiver operating characteristic analysis, the diagnostic performances of the new scores for evaluating osteoporosis and vertebral fractures were investigated against standard areal bone mineral density measured with DXA (DXA-aBMD). The F-scoreS1 and W-scoreS1 were greater (4.11 and 2.43, respectively) in patients with osteoporosis than those without osteoporosis (3.25 and 1.92, respectively) and achieved areas under the curve (AUCs) of 0.82 and 0.76 (p<0.05), respectively, for osteoporosis detection. Similarly, the mean F-scoreS1 and W-scoreS1 were higher (4.11 and 2.63, respectively) in patients with vertebral fractures than in those without fractures (3.30 and 1.82, respectively) and had greater AUCs (0.90 for W-scoreS1 and 0.74 for F-scoreS1) than DXA-aBMD (AUC, 0.26; p<0.03). In addition, the F- and W-scoreS1 demonstrated a strong correlation (r=0.65, p<0.001). The new S1 vertebral-based MRI scores were developed to detect osteoporotic changes and demonstrated improvements over DXA-aBMD in differentiating patients with vertebral fractures.

The Role of Advanced Magnetic Resonance Imaging Sequences in Multiple Sclerosis.

Background The neurological condition known as multiple sclerosis (MS) is crippling and has a complicated pathogenesis as well as a wide range of clinical symptoms, including fatigue, difficulty walking, numbness or tingling, muscle spasms and spasticity, weakness, vision problems, dizziness and vertigo, bladder and bowel dysfunction, cognitive impairment, and emotional changes. The complete scope of MS pathology cannot be fully captured by conventional magnetic resonance imaging (MRI) sequences, which has led to the investigation of sophisticated MRI methods for better diagnosis and treatment. Objective This study aims to evaluate the clinical relevance of advanced MRI sequences in multiple sclerosis. Methodology A retrospective cohort study was conducted across multiple specialized medical centers renowned for treating neurological disorders, particularly multiple sclerosis, and involved 310 patients with diverse geography seeking treatment throughout 2022. Records were searched to obtain patient information, demographics, and treatment history. Descriptive statistics and t-tests were among the statistical studies that investigated relationships between MRI biomarkers and clinical factors to help with the diagnosis and treatment of MS. A p-value of <0.05 was significant. Results The research group consisted of 310 MS patients, the majority of whom were female (67.42%) and had a mean age of 34.7 years. With hypertension (14.52%) and hyperlipidemia (19.35%) as prevalent comorbidities, the majority of patients (72.26%) were on disease-modifying treatments. The results of advanced MRI showed that lesions with white matter had higher mean diffusivity (1.25 ± 0.15 mm²/s) on DWI, lesions with reduced magnetization transfer ratio (MTR) (0.15 ± 0.03) on MTI, and lesions with reduced fractional anisotropy (FA) (0.40 ± 0.08) on diffusion tensor imaging (DTI). Additionally, the blood oxygen level-dependent (BOLD) signals in cognitive processing regions (0.75 ± 0.10) on functional MRI were different from those with normal-appearing white matter (0.40 ± 0.08). Conclusion Advanced MRI sequences are essential for bettering MS diagnosis, prognosis, and treatment because they link imaging biomarkers to important clinical parameters, which improves patient care and quality of life.

The Value of Radiomic Features of Primary Breast Tumor in STIR Sequences in Predicting Axilla Metastasis

Background: Detection of axillary metastases in breast cancer is critical for treatment options and prognosis. The aim of this study is to investigate the value of radiomic features obtained from short tau inversion recovery (STIR) sequences in magnetic resonance imaging (MRI) of primary tumor in breast cancer in predicting axillary lymph node metastasis (ALNM). Methods: Lesions of 165 patients with a mean age of 51.12 ±11 (range 28-82) with newly diagnosed invasive breast cancer who underwent breast MRI before treatment were manually segmented from STIR sequences in the 3D Slicer program in all sections. Machine learning (ML) analysis was performed using the extracted 851 features Python 3.11, Pycaret library program. Datasets were randomly divided into train (123, 80%) and independent test (63, 20%) datasets. The performances of ML algorithms were compared with area under curve (AUC), accuracy, recall, presicion and F1 scores. Results: Accuracy and AUC in the training set were in the range of 57 %-86 % and 0.50-0.95, respectively. The best model in the training set was the catBoost classifier with an AUC of 0.95 and 84% accuracy. The AUC, accuracy, recall, precision values and F1 score of the CatBoost classifier on the test set were 0.92, 84 %, 89 %, 85 %, 86 %, respectively. Conclusion: Radiomic features obtained from primary tumors on STIR sequences have the potential to predict ALNM in invasive breast cancer.

Prostate Cancer Screening in Young Men.

Background: Prostate cancer (PCa) screening strategies are being developed and evaluated in several countries. However, most of the evidence regarding PCa screening has been generated in study populations aged 50 and older. Aims: This study summarizes findings of a screening trial in younger men and discuss those findings in the context of other screening trials. Methods: Non-systematic review. Results: Screening of 45-year-old men resulted in a low PCa detection rate. Nonetheless, almost 70% of screen-detected PCa at this age was clinically significant. In young men ISUP GG 1 screen-detected cancers warrant rigorous follow-up. A baseline, midlife prostate-specific antigen (PSA) value at age 45 may safely exclude the vast majority of men from further screening investigations for at least 5 years. At age 45, a confirmatory PSA value reduces the number of subsequent tests almost by half. Sequential magnetic resonance imaging (MRI) as a reflex test subsequent to an elevated PSA ≥ 3 ng/mL needs further investigation in young men. Conclusions: Screening in young men needs to be carefully investigated in order to avoid overscreening and overdiagnosis.

Real-World Validation of Coregistration and Structured Reporting for Magnetic Resonance Imaging Monitoring in Multiple Sclerosis.

The objectives of this research were to assess the effectiveness of computer-assisted detection reading (CADR) and structured reports in monitoring patients with multiple sclerosis (MS) and to evaluate the role of radiology technicians in this context. Eighty-seven patients with MS who underwent at least 2 sequential magnetic resonance imaging (MRI) follow-ups analyzed by 2 radiologists and a technician. Progression of disease (POD) was identified through the emergence of T2 fluid-attenuated inversion recovery white matter hyperintensities or contrast enhancements and evaluated both qualitatively (progression vs stability) and quantitatively (count of new white matter hyperintensities). CADR increased the accuracy by 11%, enhancing interobserver consensus on qualitative progression and saving approximately 2 minutes per examination. Although structured reports did not improve these metrics, it may improve clinical communication and permit technicians to achieve approximately 80% accuracy in MRI readings. The use of CADR improves the accuracy, agreement, and interpretation time in MRI follow-ups of MS. With the help of computer tools, radiology technicians could represent a significant aid in the follow-up of these patients.

The design of a sample rapid magnetic resonance imaging (MRI) acquisition protocol supporting assessment of multiple articular tissues and pathologies in knee osteoarthritis

ObjectiveThis expert opinion paper proposes a design for a state-of-the-art magnetic resonance image (MRI) acquisition protocol for knee osteoarthritis clinical trials in early and advanced disease. Semi-quantitative and quantitative imaging endpoints are supported, partly amendable to automated analysis. Several (peri-) articular tissues and pathologies are covered, including synovitis. MethodA PubMed literature search was conducted, with focus on the past 5 years. Further, osteoarthritis imaging experts provided input. Specific MRI sequences, orientations, spatial resolutions and parameter settings were identified to align with study goals. We strived for implementation on standard clinical scanner hardware, with a net acquisition time ≤30 ​min. ResultsShort- and long-term longitudinal MRIs should be obtained at ≥1.5T, if possible without hardware changes during the study. We suggest a series of gradient- and spin-echo-sequences, supporting MOAKS, quantitative analysis of cartilage morphology and T2, and non-contrast-enhanced depiction of synovitis. These sequences should be properly aligned and positioned using localizer images. One of the sequences may be repeated in each participant (re-test), optimally at baseline and follow-up, to estimate within-study precision. All images should be checked for quality and protocol-adherence as soon as possible after acquisition. Alternative approaches are suggested that expand on the structural endpoints presented. ConclusionsWe aim to bridge the gap between technical MRI acquisition guides and the wealth of imaging literature, proposing a balance between image acquisition efficiency (time), safety, and technical/methodological diversity. This approach may entertain scientific innovation on tissue structure and composition assessment in clinical trials on disease modification of knee osteoarthritis.

Brain Magnetic Resonance Imaging in Wilson's Disease-Significance and Practical Aspects-A Narrative Review.

Wilson's disease (WD) is a genetic disorder of copper metabolism with pathological copper accumulation in many organs, resulting in clinical symptoms, mostly hepatic and neuropsychiatric. As copper accumulates in the brain during WD, and almost 50% of WD patients at diagnosis present with neurological symptoms, neuroimaging studies (especially brain magnetic resonance imaging (MRI)) are part of WD diagnosis. The classical sequences (T1, T2, and fluid-attenuated inversion recovery) were used to describe brain MRI; however, with the development of neuroradiology, several papers proposed the use of new MRI sequences and techniques like susceptibility-weighted images, T2*, diffusion MRI, tractography, volumetric assessment and post-processing brain MRI analysis of paramagnetic accumulation-quantitative susceptibility mapping. Based on these neuroradiological data in WD, currently, brain MRI semiquantitative scale and the pathognomonic neuroradiological brain MRI signs in WD were proposed. Further, the volumetric studies and brain iron accumulation MRI analysis suggested brain atrophy and iron accumulation as biomarkers of neurological WD disease severity. All these results highlight the significance of brain MRI examinations in WD. Due to the extreme progress of these studies, based on the available literature, the authors present the current state of knowledge about the significance, practical aspects, and future directions of brain MRI in WD.

Development of Myelin Growth Charts of the White Matter Using T1 Relaxometry.

Myelin maturation occurs in late fetal life to early adulthood, with the most rapid changes observed in the first few years of infancy. To quantify the degree of myelination, a specific MR imaging sequence is required to measure the changes in tissue proton relaxivity (R1). R1 positively correlates with the degree of myelination maturation at a given age. Similar to head circumference charts, these data can be used to develop normal growth charts for specific white matter tracts to detect pathologies involving abnormal myelination. This is a cross-sectional study using normal clinical pediatric brain MR images with the MP2RAGE sequence to generate T1 maps. The T1 maps were segmented to 75 brain regions from a brain atlas (white matter and gyri). Statistical modeling for all subjects across regions and the age range was computed, and estimates of population-level percentile ranking were computed to describe the effective myelination rate as a function of age. Test-retest analysis was performed to assess reproducibility. Logistic trendline and regression were performed for selected white matter regions and plotted for growth charts. After exclusion for abnormal MR imaging or diseases affecting myelination from the electronic medical record, 103 subject MR images were included, ranging from birth to 17 years of age. Test-retest analysis resulted in a high correlation for white matter (r = 0.88) and gyri (r = 0.95). All white matter regions from the atlas had significant P values for logistic regression with R 2 values ranging from 0.41 to 0.99. These data can serve as a myelination growth chart to permit patient comparisons with normal levels with respect to age and brain regions, thus improving detection of developmental disorders affecting myelin.

Accelerated cardiac magnetic resonance imaging using deep learning for volumetric assessment in children

BackgroundVentricular volumetry using a short-axis stack of two-dimensional (D) cine balanced steady-state free precession (bSSFP) sequences is crucial in any cardiac magnetic resonance imaging (MRI) examination. This task becomes particularly challenging in children due to multiple breath-holds.ObjectiveTo assess the diagnostic performance of accelerated 3-RR cine MRI sequences using deep learning reconstruction compared with standard 2-D cine bSSFP sequences.Material and methodsTwenty-nine consecutive patients (mean age 11 ± 5, median 12, range 1–17 years) undergoing cardiac MRI were scanned with a conventional segmented 2-D cine and a deep learning accelerated cine (three heartbeats) acquisition on a 1.5-tesla scanner. Short-axis volumetrics were performed (semi-)automatically in both datasets retrospectively by two experienced readers who visually assessed image quality employing a 4-point grading scale. Scan times and image quality were compared using the Wilcoxon rank-sum test. Volumetrics were assessed with linear regression and Bland–Altman analyses, and measurement agreement with intraclass correlation coefficient (ICC).ResultsMean acquisition time was significantly reduced with the 3-RR deep learning cine compared to the standard cine sequence (45.5 ± 13.8 s vs. 218.3 ± 44.8 s; P < 0.001). No significant differences in biventricular volumetrics were found. Left ventricular (LV) mass was increased in the deep learning cine compared with the standard cine sequence (71.4 ± 33.1 g vs. 69.9 ± 32.5 g; P < 0.05). All volumetric measurements had an excellent agreement with ICC > 0.9 except for ejection fraction (EF) (LVEF 0.81, RVEF 0.73). The image quality of deep learning cine images was decreased for end-diastolic and end-systolic contours, papillary muscles, and valve depiction (2.9 ± 0.5 vs. 3.5 ± 0.4; P < 0.05).ConclusionDeep learning cine volumetrics did not differ significantly from standard cine results except for LV mass, which was slightly overestimated with deep learning cine. Deep learning cine sequences result in a significant reduction in scan time with only slightly lower image quality.Graphical

Efficient segmentation of fetal brain MRI based on the physical resolution.

The image resolution of fetal brain magnetic resonance imaging (MRI) is a critical factor in brain development measures, which is mainly determined by the physical resolution configured in the MRI sequence. However, fetal brain MRI are commonly reconstructed to 3D images with a higher apparent resolution, compared to the original physical resolution. This work is to demonstrate that accurate segmentation can be achieved based on the MRI physical resolution, and the high apparent resolution segmentation can be achieved by a simple deep learning module. This retrospective study included 150 adult and 80 fetal brain MRIs. The adult brain MRIs were acquired at a high physical resolution, which were downsampled to visualize and quantify its impacts on the segmentation accuracy. The physical resolution of fetal images was estimated based on MRI acquisition settings and the images were downsampled accordingly before segmentation and restored using multiple upsampling strategies. Segmentation accuracy of ConvNet models were evaluated on the original and downsampled images. Dice coefficients were calculated, and compared to the original data. When the apparent resolution was higher than the physical resolution, the accuracy of fetal brain segmentation had negligible degradation (accuracy reduced by 0.26%, 1.1%, and 1.8% with downsampling factors of 4/3, 2, and 4 in each dimension, without significant differences from the original data). Using a downsampling factor of 4 in each dimension, the proposed method provided 7× smaller and 10× faster models. Efficient and accurate fetal brain segmentation models can be developed based on the physical resolution of MRI acquisitions.