In recent years, the clinical interest and research evidence of intracranial vessel wall MR imaging (iVWI) in vasculopathy lesion detection and characterization have made the technique a mainstay of patient care. Employing techniques with sufficient blood signal suppression (black blood) allows for direct visualization of lesions in the vessel wall itself, and facilitates the detection, evaluation, diagnosis, and differentiation of various cerebrovascular diseases. Clinical applications have extended rapidly to include multiple indications and pathologies, but the level of evidence and confidence varies for each of these indications and needs to be stratified and updated. On the other hand, a recent academic survey emphasized the need for additional technical and educational support in the neuroradiology community. The aim of this article is to provide expert consensus from the Society for Magnetic Resonance Angiography (SMRA) working group members for current clinical practice of iVWI with three levels of recommendation and to explore possible future clinical research applications. Question By direct visualization of the intracranial vessel wall, iVWI facilitates the detection, evaluation, diagnosis, and differentiation of various cerebrovascular diseases. Findings Updated evidence indicates that iVWI is now useful for many clinical indications, although challenges remain in certain settings. Relevance statement With the advancement of hardware, improved resolution, innovation of sequences, post-processing, and analysis, iVWI has become promising in a variety of clinical indications to facilitate the evaluation and potentially improve the management of multiple cerebrovascular diseases.

MR vessel wall imaging is an advanced technique for evaluating intracranial arterial pathology by directly depicting abnormalities of the vessel wall, including abnormalities that may precede, accompany, or occur without luminal findings on routine angiographic imaging. Despite increasing clinical interest and a growing evidence base, intracranial MR vessel wall imaging remains inconsistently implemented and underutilized in routine practice. In this AJR Expert Panel Narrative Review, we evaluate the barriers that limit implementation and effective utilization of VWI in the clinical environment for evaluation of intracranial arterial pathology, so that these can be addressed with future efforts. The discussed barriers to broader adoption span four major domains: technical implementation, education and expertise, clinical workflow and communication, and evidence generation. Addressing these barriers will require coordinated efforts among radiologists, technologists, referring clinicians, MRI physicists, and vendors. The goal is not simply greater use of intracranial MR vessel wall imaging, but appropriate utilization. Broader adoption will require moving this from a technique primarily found at specialized centers to a reproducible, widely available clinical service through standardized acquisition, coordinated education, workflow integration, and multicenter evidence demonstrating management impact and patient benefit.

OBJECTIVE:There is a need for measures of disease severity for giant cell arteritis (GCA), which may enable identification of high-risk subgroups (eg, ophthalmic complications) and individualized approaches to therapy. We derived a continuous score using data from cranial vessel wall magnetic resonance imaging (VW-MRI) to quantify vascular burden in GCA and assessed the score's association with ophthalmic manifestations. METHODS:Patients with suspected new or relapsing GCA underwent cranial VW-MRI plus dedicated orbital MRI. A radiologist assessed VW-MRI enhancement of seven cranial structures bilaterally. Using a generalized linear mixed-effects model, a continuous MRI-derived patient-level score (range 1-10) of disease extent was developed: the Cranial Artery MRI Score for GCA (CAMRIS-GCA). CAMRIS-GCA was compared between clinical diagnosis (ocular GCA, nonocular GCA, or non-GCA) and patients with versus without ocular inflammation on MRI (defined as ophthalmic artery or optic nerve sheath enhancement). RESULTS:Seventy-four patients (17 ocular GCA, 16 nonocular GCA, and 41 non-GCA) were included. CAMRIS-GCA increased linearly across clinically defined groups of non-GCA, nonocular GCA, and ocular GCA (CAMRIS-GCA median 0.6 [interquartile range (IQR) 0-1.7] vs median 2.5 [IQR 0.5-6.6] vs median 4.8 [IQR 2.1-8.5]; P < 0.01). Patients with orbital inflammation on MRI (with or without visual symptoms) had a higher median CAMRIS-GCA compared to patients with negative orbital MRI (median 6.7 [IQR 5.6-8.5] vs median 0.4 [IQR 0-1.6]; P < 0.01). CONCLUSION:This proof-of-concept study introduces a quantitative MRI-derived vascular burden score in GCA and demonstrates its association with ophthalmic involvement. These early findings suggest that cranial VW-MRI may offer a prognostic value in identifying patients at risk for vision-threatening disease.

PURPOSE:Recent studies have identified the T1 reduction rates (k1) from gadoxetic acid-enhanced magnetic resonance (MR) imaging as a biomarker for liver function. In this study, we validate k1 maps as a functional biomarker and develop 4π noncoplanar treatment plans using k1 maps to guide the optimization for liver functional avoidance stereotactic body radiation therapy (FA-SBRT). METHODS AND MATERIALS:One hundred six patients underwent precontrast and postcontrast T1 mapping MR. Mean k1 values extracted from liver mask excluding gross tumor volume (liver-GTV) were correlated with Child-Pugh and albumin-bilirubin scores. The high-function (HF) liver region was identified and masked using a patient-specific threshold from the Gaussian decomposition of the k1 histogram. Twenty patients were retrospectively planned with coplanar and noncoplanar 4π-SBRT with and without functional avoidance. Tumor coverage was maintained at a minimum of 90% planning target volume to receive prescription, and standard organ at risk constraints were set for all plans. Dose metrics included mean dose to the HF liver and HF liver volume receiving 6 Gy, which was shown to impact patient liver function. A paired, 2-tailed t test was used to determine the statistical significance. RESULTS:k1 values were inversely correlated with Child-Pugh and albumin-bilirubin scores. The 4π FA-SBRT plans reduced the mean dose to the HF liver volume by 21.8% (from 9.2 Gy to 6.5 Gy) (P < .0001) and the volume of HF liver receiving >6 Gy by 39.5% (from 507.5 cm3 to 302.2 cm3) compared with the 20-beam coplanar geometry (P < .0001). All reductions were statistically significant (P < .01). CONCLUSIONS:This study validates k1 derived from free-breathing T1 mapping MR as a liver function biomarker in a cancer patient cohort. Gaussian decomposition can threshold the k1 distribution to create patient-specific HF liver masks. The 4π FA-SBRT planning guided by k1 maps significantly reduced the mean dose to the HF liver, as well as the volume of HF receiving >6 Gy.

This study introduces a novel inversion formula for the multi-coil MRI forward operator applicable to arbitrary sampling trajectories. Traditional MRI reconstruction leverages fast Fourier transforms (FFTs) for Cartesian sampling and nonuniform FFTs for non-Cartesian patterns. However, subsampled k-space reconstruction typically relies on iterative least-squares (LS) solutions, which are computationally intensive due to the complex structure introduced by multiple coil sensitivities. We hypothesize that the MRI multi-coil forward operator exhibits the low displacement rank (LDR) property, enabling an efficient inversion using triangular Toeplitz operators with a computational complexity of 𝒪(α N log ^2 N) , with α being a small integer. The hypothesis is supported through numerical simulations. For demonstration of the feasibility of such inversion formula, we propose a learning-based approach to determine the necessary LDR parameters, demonstrating successful forward and inverse operator representations across various sampling patterns, including Cartesian and radial trajectories. The proposed inversion formula offers a significant acceleration in MR reconstruction, reducing computational complexity by a factor of approximately 26 compared to conventional conjugate gradient methods. The proposed inversion formula will greatly enhance reconstruction speed and simplify reconstruction pipelines, including iterative reconstructions and deep learning solutions incorporating data-consistency layers. Future work will focus on deriving the LDR parameters analytically to further streamline the inversion process. The code is available at https://github.com/mikecjz/structured-nets .

BACKGROUND:Liver tumors have low contrast on 4DCT. A novel Multitasking (MT)MR imaging technique has been implemented on the MR simulator, providing both T1 and T2-weighted 4DMR images in a single 8-min free-breathing scan for better tumor delineation and motion evaluation. This study reports our early clinical experience of MTMR regarding tumor visibility, motion characteristics, and resultant dosimetry compared to post-contrast 4DCT for liver SBRT. METHODS:Phantom motion validation was performed. Tumor contrast-to-noise ratio (CNR) and motion were analyzed in 54 patients. Replanning for 17 patients (21 tumor volumes) was performed, and planning target volume receiving greater than 90% of the prescription (PTV_V90) was compared based on optimized dose distributions for each 4D dataset-derived PTV. RESULTS:Phantom motions in both 4DCT and MTMR datasets were within <1.8 mm of the programmed ground truth. The absolute CNR of MTMR-T1w and MTMR-T2w were significantly greater than post-contrast 4DCT. Tumor superior-inferior motions were significantly greater in MTMR than in 4DCT, while PTV volumes were not significantly different between the two 4D datasets. The PTV_V90 calculated from individual MTMR-T1w and 4DCT optimized plans were similar. However, a statistically significant 5 % reduction of PTV_V90 was observed when the optimized PTV_MTMR dose was superimposed on the respective PTV_4DCT, or vice versa for the re-planning patient cohort. CONCLUSION:This study demonstrates that the MTMR sequence offers superior tumor visualization and detects greater superior-inferior motion compared to 4DCT, enhancing the precision of radiotherapy planning for liver SBRT. While both imaging methods achieve comparable target volume coverage with individually optimized plans, discrepancies in tumor positioning lead to reduced coverage when plans are cross-applied, highlighting the importance of motion assessment accuracy. MTMR's ability to provide multiple contrast-weighted images in a single scan addresses limitations of traditional 4DCT and multi-sequence MR protocols, particularly for patients unable to receive contrast.

At the 2024 ISMRM Annual Meeting in Singapore, a member-initiated session on MRI for biology-guided radiation therapy (RT), endorsed by the ISMRM MR in RT Study Group, was successfully organized. The session convened a diverse group of global experts in quantitative MRI for RT, who presented the latest research on the technical development and clinical translation of various quantitative MRI techniques for biology-guided RT planning and delivery. The session highlighted clinical needs and a variety of MRI techniques, including MR spectroscopic imaging, oxygen-enhanced MRI, four-dimensional MR fingerprinting, dynamic contrast-enhanced MRI, and 129Xe MRI. Additionally, technical aspects and challenges for clinical translation of quantitative MRI into biology-guided RT were presented, both in the context of RT planning and adaptation. This article summarizes the progress made in this emerging field, identifies key challenges that need to be addressed, and outlines areas for future research. These insights are crucial for the integration of quantitative MRI techniques into RT clinical practice, ultimately aiming to improve patient outcomes through more personalized RT approaches.

Background:Clinical intracranial vessel wall imaging (VWI) requires high spatial resolution leading to long scan times and artifacts. Purpose:To accelerate standard-of-care (SOC) 3D T1-weighted variable-flip-angle turbo-spin-echo (VFA-TSE) sequence with parallel imaging (Generalized Autocalibrating Partially Parallel Acquisitions, GRAPPA) using compressed sensing (CS) or Controlled Aliasing in Parallel Imaging Results in Higher Acceleration (CAIPIRINHA, CAIPI) with either standard or large field-of-view (FOV) configurations to reduce scan time, artifacts and accommodate head sizes. Study Type:Prospective study. Subjects:Ten healthy volunteers. Field Strength/Sequence:3 Telsa, 20-channel head coil, T1-weighted VFA-TSE. Assessment:Accelerated sequences were compared to SOC GRAPPA (R=2), including standard FOV CAIPI (SFCAIPI, R=4), CS (SFCS7, R=7), and large FOV CS (LFCS7, R=7; LFCS10, R=10). Four neuroradiologists rated image quality (IQ) and signal-to-noise ratio (SNR) using a 4-point Likert scale. Scores of 3-4 were categorized as clinically interpretable. Lumen and wall diameters were measured. Statistical Analysis:Descriptive statistics are reported. McNemar's test compared proportions of IQ- and SNR-based clinically interpretable scans between relevant sequences of interest. Inter- and intra-rater reliabilities were calculated with Fleiss Kappa and weighted Cohen's Kappa, respectively. Lumen and wall diameters of the CS- and CAIPI-accelerated sequences were compared to SOC using paired t-tests. Results:SFCAIPI showed the lowest mean IQ and SNR scores. SFCS7 showed no significant difference in the proportion of IQ-based clinically interpretable scans compared to SFGRAPPA. When testing FOV, LFCS7 (35/40 scans; time of acquisition (TA)=3:45) showed a significantly higher proportion of IQ-based clinically interpretable scans compared to SFCS7 (27/40, p=0.03; TA=6:37). Upon increasing acceleration (R=10), there was no difference in the proportion of IQ-based clinically interpretable scans between LFCS7 and LFCS10 (36/40, p=0.65). Large FOV eliminated aliasing artifacts compared standard FOV (aliasing in 7 of 10 subjects). LFCS10 (TA=4:55) achieved a 50.6% reduction in TA relative to SFGRAPPA (TA=9:57). Conclusion:Large FOV CS VWI sequence with 10x acceleration achieved a 50.6% reduction in scan time while delivering image quality comparable to SOC standard FOV GRAPPA.

Introduction:Coronary involvement in immunoglobulin G4-related disease (IgG4-RD) has remained underexplored despite its risk posed in terms of major adverse cardiovascular events (MACEs). The study provides a comprehensive review, particularly focusing on multimodal imaging characteristics and clinical applicability. Methods:A systematic review was conducted on IgG4-related coronary involvement, supplemented by serial cases from our center included. We analyzed clinical features and multimodal imaging, focusing on the presence or absence of cardiovascular symptoms. Results:A total of 134 IgG4-RD patients with coronary involvement were included and analyzed, including 118 from the literature and 16 from our center. Seven (5%) patients died from secondary myocardial ischemia/infarction. Coronary anomalies commonly affected the left anterior descending artery (LAD) (79%) and presented as diffuse wall thickening or periarterial soft tissue encasement (85%). Stenosis was frequent (47%) and often secondary. Symptoms, primarily induced by myocardial ischemia or infarction (84%), were largely due to stenosis (68%). Chest computed tomography (CT) and coronary computed tomography angiography (CTA) were the primary imaging modalities (81%), particularly in symptomatic cases (88%). Positron emission tomography-computed tomography (PET-CT) was applied in 55 patients (41%) and often in asymptomatic cases (51%). CMR, though less adopted (23%), demonstrated potential in detecting coronary lesions (77%). Glucocorticoid therapy is the most common (76%), with the best response of periarterial encasement (66%). Surgery was less common (32%), primarily being applied to aneurysms (63%). Conclusion:Coronary involvement in IgG4-RD presents four phenotypes, sometimes with an insidious onset and as the sole affected site, poses a potential risk for MACEs. Multimodal imaging is essential for early diagnosis and effective monitoring, with coronary CMR showing promise for early detection without the risk of radiation-induced inflammation and fibrosis.

Purpose To develop a multiparametric dynamic contrast imaging (mpDYCI) technique that enables simultaneous quantification of brain tissue perfusion, microvasculature permeability, transmembrane water efflux, and susceptibility and can be integrated into the routine brain tumor imaging protocol for voxelwise multifaceted quantitative brain tumor assessment. Materials and Methods In this prospective study conducted from March 2023 to April 2024, the mpDYCI technique was evaluated. The mpDYCI technique builds on an MR Multitasking-based dynamic T1 and T2* mapping method and incorporates several technical optimizations in pulse sequence, image reconstruction, T1/T2* quantification, and quantitative metric estimation to achieve robust whole-brain multiparametric quantification. The intersession repeatability and accuracy of mpDYCI metrics were assessed, using intraclass correlation coefficient (ICC), through digital phantom and in vivo experiments involving healthy individuals and individuals with brain tumors. The feasibility of integrating mpDYCI into the routine brain imaging protocol and its clinical utilities based on complementary information from intrinsically coregistered multiple quantitative metrics were also explored. Results In vivo experiments were performed in six healthy participants (mean age, 33 years; range, 27-48 years; three female) and 55 participants with brain tumors (mean age, 56 years; range, 24-81 years; 36 female). Quantitative metrics derived from mpDYCI demonstrated good to excellent repeatability (ICC ≥ 0.80) and excellent agreement with reference standards (range, 6.86%-15.21% percentage error or ICC ≥ 0.93). Histogram analysis, voxel clustering, and histologic validation confirmed the capability of mpDYCI to capture the intratumoral heterogeneity. Low voxelwise correlations between each pair of mpDYCI metrics (correlation coefficient ≤ 0.33 except for one pair) suggested that each metric provides complementary information. Furthermore, mpDYCI exhibited the potential to help differentiate treatment-related effects from true tumor progression in brain metastases. Conclusion With a single 7.5-minute scan and single-dose contrast media injection, mpDYCI can simultaneously quantify perfusion, permeability, water efflux, and susceptibility, thereby enabling comprehensive voxelwise characterization of brain tumors. Keywords: MR Perfusion, CNS, Brain/Brain Stem, Tumor Immune Microenvironment, Reconstruction Algorithms, MR-Dynamic Contrast Enhanced, MR Imaging, Brain Tumor Heterogeneity, Multiparametric MR Imaging, Dynamic Contrast-enhanced MRI, Dynamic Susceptibility Contrast MRI, Quantitative Susceptibility Mapping Supplemental material is available for this article. © RSNA, 2025.

Traumatic brain injury (TBI) is a common diagnosis requiring acute hospitalization. Long-term, TBI is a significant source of health and socioeconomic impact in the United States and globally. The goal of clinicians who manage TBI is to prevent secondary brain injury. In this population, post-traumatic cerebral infarction (PTCI) acutely after TBI is an important but under-recognized complication that is associated with negative functional outcomes. In this comprehensive review, we describe the incidence and pathophysiology of PTCI. We then discuss the diagnostic and treatment approaches for the most common etiologies of isolated PTCI, including brain herniation syndromes, cervical artery dissection, venous thrombosis, and post-traumatic vasospasm. In addition to these mechanisms, hypercoagulability and microcirculatory failure can also exacerbate ischemia. We aim to highlight the importance of this condition and future clinical research needs with the goal of improving patient outcomes after TBI.

Motivation: The intrinsic “black-blood (BB)” property in 3D TSE is insufficient for vessel wall imaging and other neuroimaging applications. Additional blood suppression preparations can diminish T1 weighting and SNR. Goal(s): To develop and validate a new approach compatible with 3D TSE to enhance BB effects while minimizing sacrifice in T1 weighting and overall SNR. Approach: An interleaved flow-sensitive dephasing scheme was developed, and verified in healthy volunteers and assessed in 32 patients with one of four neurological diseases. Results: iFSD-SPACE achieved the lowest lumen SNR and the highest wall-lumen CNR. iFSD-SPACE yielded significantly higher white-matter SNR and gray-to-white matter CNR than DANTE and MSDE. Impact: iFSD is a 3D TSE-compatible blood flow suppression technique that overcomes the limitations of existing BB magnetization preparation methods and holds the potential to greatly enhance the performance of 3D TSE in several neuroimaging applications.

The dynamic susceptibility contrast (DSC) MRI measures of relative cerebral blood volume (rCBV) play a central role in monitoring therapeutic response and disease progression in patients with gliomas. Previous investigations have demonstrated promise of using rCBV in classifying tumor grade, elucidating tumor viability after therapy, and differentiating pseudoprogression and pseudoresponse. However, the quantification and reproducibility of rCBV measurements across patients, devices, and software remain a critical barrier to routine or clinical trial use of longitudinal DSC MRI in patients with gliomas. To address this limitation, the RSNA DSC MRI Biomarker Committee of the Quantitative Imaging Biomarkers Alliance developed a Profile that defines statistics-based claims for the precision of longitudinal measurements. Although rCBV is the clinical marker of interest, the Profile focused on the reproducibility of the measured quantitative imaging biomarker, which is the area under the contrast agent concentration-time curve (AUC) normalized by the mean value of normal-appearing contralateral white matter tissue (tissue-normalized AUC values). Based on previous reports of within-subject coefficient of variation (wCV) in the tissue-normalized AUC values for enhancing gliomas (wCV = 0.31), an increase of 182% or more with respect to the baseline tissue-normalized AUC value indicates that an increase has occurred with 95% confidence. In contrast, a decrease of 64% or more with respect to baseline suggests that a decrease has occurred with 95% confidence. Similarly, an increase of 399% or more in the tissue-normalized AUC values in normal brain gray matter tissue (wCV = 0.40) suggests that an increase has occurred with 95% confidence, whereas a decrease of 80% or more with respect to baseline suggests that a decrease has occurred with 95% confidence. This article provides the rationale for these claims and the compliance activities needed to achieve these claims. Potential updates to incorporate new data based on advances in technology and clinical care in the Profile are also discussed.

Asymptomatic Leucine-Rich Repeat Kinase 2 Gene (LRRK2) carriers are at risk for developing Parkinson's disease (PD). We studied presymptomatic substantia nigra pars compacta (SNc) regional neurodegeneration in asymptomatic LRRK2 carriers compared to idiopathic PD patients using neuromelanin-sensitive MRI technique (NM-MRI). Fifteen asymptomatic LRRK2 carriers, 22 idiopathic PD patients, and 30 healthy controls (HCs) were scanned using NM-MRI. We computed volume and contrast-to-noise ratio (CNR) derived from the whole SNc and the sensorimotor, associative, and limbic SNc regions. An analysis of covariance was performed to explore the differences of whole and regional NM-MRI values among the groups while controlling the effect of age and sex. In whole SNc, LRRK2 had significantly lower CNR than HCs but non-significantly higher volume and CNR than PD patients, and PD patients significantly lower volume and CNR compared to HCs. Inside SNc regions, there were significant group effects for CNR in all regions and for volumes in the associative region, with a trend in the sensorimotor region but no significant changes in the limbic region. PD had reduced volume and CNR in all regions compared to HCs. Asymptomatic LRRK2 carriers showed globally decreased SNc volume and CNR suggesting early nigral neurodegeneration in these subjects at risk of developing PD.

Cryptogenic stroke refers to a stroke of undetermined etiology. It accounts for approximately one-fifth of ischemic strokes and has a higher prevalence in younger patients. Embolic stroke of undetermined source (ESUS) refers to a subgroup of patients with nonlacunar cryptogenic strokes in whom embolism is the suspected stroke mechanism. Under the classifications of cryptogenic stroke or ESUS, there is wide heterogeneity in possible stroke mechanisms. In the absence of a confirmed stroke etiology, there is no established treatment for secondary prevention of stroke in patients experiencing cryptogenic stroke or ESUS, despite several clinical trials, leaving physicians with a clinical dilemma. Both conventional and advanced MRI techniques are available in clinical practice to identify differentiating features and stroke patterns and to determine or infer the underlying etiologic cause, such as atherosclerotic plaques and cardiogenic or paradoxical embolism due to occult pelvic venous thrombi. The aim of this review is to highlight the diagnostic utility of various MRI techniques in patients with cryptogenic stroke or ESUS. Future trends in technological advancement for promoting the adoption of MRI in such a special clinical application are also discussed.

Objective.We aim to develop a Multi-modal Fusion and Feature Enhancement U-Net (MFFE U-Net) coupling with stem cell niche proximity estimation to improve voxel-wise Glioblastoma (GBM) recurrence prediction.Approach.57 patients with pre- and post-surgery magnetic resonance (MR) scans were retrospectively solicited from 4 databases. Post-surgery MR scans included two months before the clinical diagnosis of recurrence and the day of the radiologicaly confirmed recurrence. The recurrences were manually annotated on the T1ce. The high-risk recurrence region was first determined. Then, a sparse multi-modal feature fusion U-Net was developed. The 50 patients from 3 databases were divided into 70% training, 10% validation, and 20% testing. 7 patients from the 4th institution were used as external testing with transfer learning. Model performance was evaluated by recall, precision, F1-score, and Hausdorff Distance at the 95% percentile (HD95). The proposed MFFE U-Net was compared to the support vector machine (SVM) model and two state-of-the-art neural networks. An ablation study was performed.Main results.The MFFE U-Net achieved a precision of 0.79 ± 0.08, a recall of 0.85 ± 0.11, and an F1-score of 0.82 ± 0.09. Statistically significant improvement was observed when comparing MFFE U-Net with proximity estimation couple SVM (SVMPE), mU-Net, and Deeplabv3. The HD95 was 2.75 ± 0.44 mm and 3.91 ± 0.83 mm for the 10 patients used in the model construction and 7 patients used for external testing, respectively. The ablation test showed that all five MR sequences contributed to the performance of the final model, with T1ce contributing the most. Convergence analysis, time efficiency analysis, and visualization of the intermediate results further discovered the characteristics of the proposed method.Significance. We present an advanced MFFE learning framework, MFFE U-Net, for effective voxel-wise GBM recurrence prediction. MFFE U-Net performs significantly better than the state-of-the-art networks and can potentially guide early RT intervention of the disease recurrence.

All T1-weighted images are built upon one of two fundamental pulse sequences, spin-echo and gradient echo, each of which has distinct signal characteristics and clinical applications. Moreover, within each broadly defined category of T1-weighting, acquisition parameters can be modified to affect image quality, contrast, and scan duration; each tailored sequence has unique advantages, drawbacks, clinical indications, and potential artifacts. In this review, we describe key features that distinguish different types of T1-weighted sequences and discuss the utility of each sequence for specific clinical settings, including neuro-oncology, vasculopathy, and pediatric neuroradiology. In addition, we provide case examples from our institution that illustrate common artifacts and pitfalls associated with image interpretation. The findings described herein provide a framework to individualize the imaging protocol based on patient presentation and clinical indication.