Repeatability and reproducibility of human brain morphometry using three-dimensional magnetic resonance fingerprinting

Quantifying 3D MR fingerprinting (3D-MRF) reproducibility across subjects, sessions, and scanners automatically using MNI atlases

PURPOSE

Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point-of-care than weighted imaging. However, few direct cross-modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross-modal imaging performance in vivo via atlas-based sampling.

METHODS

We acquire whole-brain 3D-MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align all qualitative and quantitative DICOM stacks to Montreal Neurological Institute (MNI) 152 space, then samples each dataset's native space through transformation inversion to compare performance within atlas regions across subjects, scanners, and repetitions.

RESULTS

Voxel values within MRF-derived maps were found to be more repeatable (σT1  = 1.90, σT2  = 3.20) across sessions than vendor-reconstructed MPRAGE (σT1w  = 6.04) or turbo spin echo (σT2w  = 5.66) images. Additionally, MRF was found to be more reproducible across scanners (σT1  = 2.21, σT2  = 3.89) than either qualitative modality (σT1w  = 7.84, σT2w  = 7.76). Notably, differences between repeatability and reproducibility of in vivo MRF were insignificant, unlike the weighted images.

CONCLUSION

MRF data from many sessions and scanners can potentially be treated as a single dataset for harmonized analysis or longitudinal comparisons without the additional regularization steps needed for qualitative modalities.

Physics-Informed Discretization for Reproducible and Robust Radiomic Feature Extraction Using Quantitative MRI

OBJECTIVE

Given the limited repeatability and reproducibility of radiomic features derived from weighted magnetic resonance imaging (MRI), there may be significant advantages to using radiomics in conjunction with quantitative MRI. This study introduces a novel physics-informed discretization (PID) method for reproducible radiomic feature extraction and evaluates its performance using quantitative MRI sequences including magnetic resonance fingerprinting (MRF) and apparent diffusion coefficient (ADC) mapping.

MATERIALS AND METHODS

A multiscanner, scan-rescan dataset comprising whole-brain 3D quantitative (MRF T1, MRF T2, and ADC) and weighted MRI (T1w MPRAGE, T2w SPACE, and T2w FLAIR) from 5 healthy subjects was prospectively acquired. Subjects underwent 2 repeated acquisitions on 3 distinct 3 T scanners each, for a total of 6 scans per subject (30 total scans). First-order statistical (n = 23) and second-order texture (n = 74) radiomic features were extracted from 56 brain tissue regions of interest using the proposed PID method (for quantitative MRI) and conventional fixed bin number (FBN) discretization (for quantitative MRI and weighted MRI). Interscanner radiomic feature reproducibility was measured using the intraclass correlation coefficient (ICC), and the effect of image sequence (eg, MRF T1 vs T1w MPRAGE), as well as image discretization method (ie, PID vs FBN), on radiomic feature reproducibility was assessed using repeated measures analysis of variance. The robustness of PID and FBN discretization to segmentation error was evaluated by simulating segmentation differences in brainstem regions of interest. Radiomic features with ICCs greater than 0.75 following simulated segmentation were determined to be robust to segmentation.

RESULTS

First-order features demonstrated higher reproducibility in quantitative MRI than weighted MRI sequences, with 30% (n = 7/23) features being more reproducible in MRF T1 and MRF T2 than weighted MRI. Gray level co-occurrence matrix (GLCM) texture features extracted from MRF T1 and MRF T2 were significantly more reproducible using PID compared with FBN discretization; for all quantitative MRI sequences, PID yielded the highest number of texture features with excellent reproducibility (ICC > 0.9). Comparing texture reproducibility of quantitative and weighted MRI, a greater proportion of MRF T1 (n = 225/370, 61%) and MRF T2 (n = 150/370, 41%) texture features had excellent reproducibility (ICC > 0.9) compared with T1w MPRAGE (n = 148/370, 40%), ADC (n = 115/370, 32%), T2w SPACE (n = 98/370, 27%), and FLAIR (n = 102/370, 28%). Physics-informed discretization was also more robust than FBN discretization to segmentation error, as 46% (n = 103/222, 46%) of texture features extracted from quantitative MRI using PID were robust to simulated 6 mm segmentation shift compared with 19% (n = 42/222, 19%) of weighted MRI texture features extracted using FBN discretization.

CONCLUSIONS

The proposed PID method yields radiomic features extracted from quantitative MRI sequences that are more reproducible and robust than radiomic features extracted from weighted MRI using conventional (FBN) discretization approaches. Quantitative MRI sequences also demonstrated greater scan-rescan robustness and first-order feature reproducibility than weighted MRI.

Quantitative T1 mapping detects blood-brain barrier breakdown in apparently non-enhancing multiple sclerosis lesions

OBJECTIVES

The disruption of the blood-brain barrier (BBB) is a key and early feature in the pathogenesis of demyelinating multiple sclerosis (MS) lesions and has been neuropathologically demonstrated in both active and chronic plaques. The local overt BBB disruption in acute demyelinating lesions is captured as signal hyperintensity in post-contrast T1-weighted images because of the contrast-related shortening of the T1 relaxation time. On the contrary, the subtle BBB disruption in chronic lesions is not visible at conventional radiological evaluation but it might be of clinical relevance. Indeed, persistent, subtle BBB leakage might be linked to low-grade inflammation and plaque evolution. Here we hypothesised that 3D Quantitative Transient-state Imaging (QTI) was able to reveal and measure T1 shortening (ΔT1) reflecting small amounts of contrast media leakage in apparently non-enhancing lesions (ANELs).

MATERIALS AND METHODS

Thirty-four patients with relapsing remitting MS were included in the study. All patients underwent a 3 T MRI exam of the brain including conventional sequences and QTI acquisitions (1.1 mm isotropic voxel) performed both before and after contrast media administration. For each patient, a ΔT1 map was obtained via voxel-wise subtraction of pre- and post- contrast QTI-derived T1 maps. ΔT1 values measured in ANELs were compared with those recorded in enhancing lesions and in the normal appearing white matter. A reference distribution of ΔT1 in the white matter was obtained from datasets acquired in 10 non-MS patients with unrevealing MR imaging.

RESULTS

Mean ΔT1 in ANELs (57.45 ± 48.27 ms) was significantly lower than in enhancing lesions (297.71 ± 177.52 ms; p < 0. 0001) and higher than in the normal appearing white matter (36.57 ± 10.53 ms; p < 0.005). Fifty-two percent of ANELs exhibited ΔT1 higher than those observed in the white matter of non-MS patients.

CONCLUSIONS

QTI-derived quantitative ΔT1 mapping enabled to measure contrast-related T1 shortening in ANELs. ANELs exhibiting ΔT1 values that deviate from the reference distribution in non-MS patients may indicate persistent, subtle, BBB disruption. Access to this information may be proved useful to better characterise pathology and objectively monitor disease activity and response to therapy.

Magnetic Resonance Fingerprinting: A Review of Clinical Applications

ABSTRACT

Magnetic resonance fingerprinting (MRF) is an approach to quantitative magnetic resonance imaging that allows for efficient simultaneous measurements of multiple tissue properties, which are then used to create accurate and reproducible quantitative maps of these properties. As the technique has gained popularity, the extent of preclinical and clinical applications has vastly increased. The goal of this review is to provide an overview of currently investigated preclinical and clinical applications of MRF, as well as future directions. Topics covered include MRF in neuroimaging, neurovascular, prostate, liver, kidney, breast, abdominal quantitative imaging, cardiac, and musculoskeletal applications.

Accuracy, repeatability, and reproducibility of T1 and T2 relaxation times measurement by 3D magnetic resonance fingerprinting with different dictionary resolutions

OBJECTIVES

To assess the accuracy, repeatability, and reproducibility of T₁ and T₂ relaxation time measurements by three-dimensional magnetic resonance fingerprinting (3D MRF) using various dictionary resolutions.

METHODS

The ISMRM/NIST phantom was scanned daily for 10 days in two 3 T MR scanners using a 3D MRF sequence reconstructed using four dictionaries with varying step sizes and one dictionary with wider ranges. Thirty-nine healthy volunteers were enrolled: 20 subjects underwent whole-brain MRF scans in both scanners and the rest in one scanner. ROI/VOI analyses were performed on phantom and brain MRF maps. Accuracy, repeatability, and reproducibility metrics were calculated.

RESULTS

In the phantom study, all dictionaries showed high T₁ linearity to the reference values (R² > 0.99), repeatability (CV < 3%), and reproducibility (CV < 3%) with lower linearity (R² > 0.98), repeatability (CV < 6%), and reproducibility (CV ≤ 4%) for T₂ measurement. The volunteer study demonstrated high T₁ reproducibility of within-subject CV (wCV) < 4% by all dictionaries with the same ranges, both in the brain parenchyma and CSF. Yet, reproducibility was moderate for T₂ measurement (wCV < 8%). In CSF measurement, dictionaries with a smaller range showed a seemingly better reproducibility (T₁, wCV 3%; T₂, wCV 8%) than the much wider range dictionary (T₁, wCV 5%; T₂, wCV 13%). Truncated CSF relaxometry values were evident in smaller range dictionaries.

CONCLUSIONS

The accuracy, repeatability, and reproducibility of 3D MRF across various dictionary resolutions were high for T₁ and moderate for T₂ measurements. A lower-resolution dictionary with a well-defined range may be adequate, thus significantly reducing the computational load.

KEY POINTS

• A lower-resolution dictionary with a well-defined range may be sufficient for 3D MRF reconstruction. • CSF relaxation times might be underestimated due to truncation by the upper dictionary range. • Dictionary with a higher upper range might be advisable, especially for CSF evaluation and elderly subjects whose perivascular spaces are more prominent.

Normative quantitative relaxation atlases for characterization of cortical regions using magnetic resonance fingerprinting

Quantitative magnetic resonance (MR) has been used to study cyto- and myelo-architecture of the human brain non-invasively. However, analyzing brain cortex using high-resolution quantitative MR acquisition can be challenging to perform using 3T clinical scanners. MR fingerprinting (MRF) is a highly efficient and clinically feasible quantitative MR technique that simultaneously provides T1 and T2 relaxation maps. Using 3D MRF from 40 healthy subjects (mean age = 25.6 ± 4.3 years) scanned on 3T magnetic resonance imaging, we generated whole-brain gyral-based normative MR relaxation atlases and investigated cortical-region-based T1 and T2 variations. Gender and age dependency of T1 and T2 variations were additionally analyzed. The coefficient of variation of T1 and T2 for each cortical-region was 3.5% and 7.3%, respectively, supporting low variability of MRF measurements across subjects. Significant differences in T1 and T2 were identified among 34 brain regions (P < 0.001), lower in the precentral, postcentral, paracentral lobule, transverse temporal, lateral occipital, and cingulate areas, which contain sensorimotor, auditory, visual, and limbic functions. Significant correlations were identified between age and T1 and T2 values. This study established whole-brain MRF T1 and T2 atlases of healthy subjects using a clinical 3T scanner, which can provide a quantitative and region-specific baseline for future brain studies and pathology detection.

Radiomics with 3-dimensional magnetic resonance fingerprinting: influence of dictionary design on repeatability and reproducibility of radiomic features

Objectives

We aimed to investigate the influence of magnetic resonance fingerprinting (MRF) dictionary design on radiomic features using in vivo human brain scans.

Methods

Scan-rescans of three-dimensional MRF and conventional T1-weighted imaging were performed on 21 healthy volunteers (9 males and 12 females; mean age, 41.3 ± 14.6 years; age range, 22–72 years). Five patients with multiple sclerosis (3 males and 2 females; mean age, 41.2 ± 7.3 years; age range, 32–53 years) were also included. MRF data were reconstructed using various dictionaries with different step sizes. First- and second-order radiomic features were extracted from each dataset. Intra-dictionary repeatability and inter-dictionary reproducibility were evaluated using intraclass correlation coefficients (ICCs). Features with ICCs > 0.90 were considered acceptable. Relative changes were calculated to assess inter-dictionary biases.

Results

The overall scan-rescan ICCs of MRF-based radiomics ranged from 0.86 to 0.95, depending on dictionary step size. No significant differences were observed in the overall scan-rescan repeatability of MRF-based radiomic features and conventional T1-weighted imaging (p = 1.00). Intra-dictionary repeatability was insensitive to dictionary step size differences. MRF-based radiomic features varied among dictionaries (overall ICC for inter-dictionary reproducibility, 0.62–0.99), especially when step sizes were large. First-order and gray level co-occurrence matrix features were the most reproducible feature classes among different step size dictionaries. T1 map-derived radiomic features provided higher repeatability and reproducibility among dictionaries than those obtained with T2 maps.

Conclusion

MRF-based radiomic features are highly repeatable in various dictionary step sizes. Caution is warranted when performing MRF-based radiomics using datasets containing maps generated from different dictionaries.

Key Points

• MRF-based radiomic features are highly repeatable in various dictionary step sizes.

• Use of different MRF dictionaries may result in variable radiomic features, even when the same MRF acquisition data are used.

• Caution is needed when performing radiomic analysis using data reconstructed from different dictionaries.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-08555-3.

Simultaneous relaxometry and morphometry of human brain structures with 3D magnetic resonance fingerprinting: a multicenter, multiplatform, multifield-strength study

Relaxation times and morphological information are fundamental magnetic resonance imaging-derived metrics of the human brain that reflect the status of the underlying tissue. Magnetic resonance fingerprinting (MRF) enables simultaneous acquisition of T1 and T2 maps inherently aligned to the anatomy, allowing whole-brain relaxometry and morphometry in a single scan. In this study, we revealed the feasibility of 3D MRF for simultaneous brain structure-wise morphometry and relaxometry. Comprehensive test-retest scan analyses using five 1.5-T and three 3.0-T systems from a single vendor including different scanner types across 3 institutions demonstrated that 3D MRF-derived morphological information and relaxation times are highly repeatable at both 1.5 T and 3.0 T. Regional cortical thickness and subcortical volume values showed high agreement and low bias across different field strengths. The ability to acquire a set of regional T1, T2, thickness, and volume measurements of neuroanatomical structures with high repeatability and reproducibility facilitates the ability of longitudinal multicenter imaging studies to quantitatively monitor changes associated with underlying pathologies, disease progression, and treatments.

Optimized multi-axis spiral projection MR fingerprinting with subspace reconstruction for rapid whole-brain high-isotropic-resolution quantitative imaging

PURPOSE

To improve image quality and accelerate the acquisition of 3D MR fingerprinting (MRF).

METHODS

Building on the multi-axis spiral-projection MRF technique, a subspace reconstruction with locally low-rank constraint and a modified spiral-projection spatiotemporal encoding scheme called tiny golden-angle shuffling were implemented for rapid whole-brain high-resolution quantitative mapping. Reconstruction parameters such as the locally low-rank regularization parameter and the subspace rank were tuned using retrospective in vivo data and simulated examinations. B₀ inhomogeneity correction using multifrequency interpolation was incorporated into the subspace reconstruction to further improve the image quality by mitigating blurring caused by off-resonance effect.

RESULTS

The proposed MRF acquisition and reconstruction framework yields high-quality 1-mm isotropic whole-brain quantitative maps in 2 min at better quality compared with 6-min acquisitions of prior approaches. The proposed method was validated to not induce bias in T₁ and T₂ mapping. High-quality whole-brain MRF data were also obtained at 0.66-mm isotropic resolution in 4 min using the proposed technique, where the increased resolution was shown to improve visualization of subtle brain structures.

CONCLUSIONS

The proposed tiny golden-angle shuffling, MRF with optimized spiral-projection trajectory and subspace reconstruction enables high-resolution quantitative mapping in ultrafast acquisition time.

Automated design of pulse sequences for magnetic resonance fingerprinting using physics-inspired optimization

Magnetic resonance fingerprinting (MRF) is a method to extract quantitative tissue properties such as [Formula: see text] and [Formula: see text] relaxation rates from arbitrary pulse sequences using conventional MRI hardware. MRF pulse sequences have thousands of tunable parameters, which can be chosen to maximize precision and minimize scan time. Here, we perform de novo automated design of MRF pulse sequences by applying physics-inspired optimization heuristics. Our experimental data suggest that systematic errors dominate over random errors in MRF scans under clinically relevant conditions of high undersampling. Thus, in contrast to prior optimization efforts, which focused on statistical error models, we use a cost function based on explicit first-principles simulation of systematic errors arising from Fourier undersampling and phase variation. The resulting pulse sequences display features qualitatively different from previously used MRF pulse sequences and achieve fourfold shorter scan time than prior human-designed sequences of equivalent precision in [Formula: see text] and [Formula: see text] Furthermore, the optimization algorithm has discovered the existence of MRF pulse sequences with intrinsic robustness against shading artifacts due to phase variation.

MR Imaging in the 21st Century: Technical Innovation over the First Two Decades

Clinical MRI systems have continually improved over the years since their introduction in the 1980s. In MRI technical development, the developments in each MRI system component, including data acquisition, image reconstruction, and hardware systems, have impacted the others. Progress in each component has induced new technology development opportunities in other components. New technologies outside of the MRI field, for example, computer science, data processing, and semiconductors, have been immediately incorporated into MRI development, which resulted in innovative applications. With high performance computing and MR technology innovations, MRI can now provide large volumes of functional and anatomical image datasets, which are important tools in various research fields. MRI systems are now combined with other modalities, such as positron emission tomography (PET) or therapeutic devices. These hybrid systems provide additional capabilities.

In this review, MRI advances in the last two decades will be considered. We will discuss the progress of MRI systems, the enabling technology, established applications, current trends, and the future outlook.

Accelerated 3D whole-brain T1, T2, and proton density mapping: feasibility for clinical glioma MR imaging

Purpose

Advanced MRI-based biomarkers offer comprehensive and quantitative information for the evaluation and characterization of brain tumors. In this study, we report initial clinical experience in routine glioma imaging with a novel, fully 3D multiparametric quantitative transient-state imaging (QTI) method for tissue characterization based on T1 and T2 values.

Methods

To demonstrate the viability of the proposed 3D QTI technique, nine glioma patients (grade II–IV), with a variety of disease states and treatment histories, were included in this study. First, we investigated the feasibility of 3D QTI (6:25 min scan time) for its use in clinical routine imaging, focusing on image reconstruction, parameter estimation, and contrast-weighted image synthesis. Second, for an initial assessment of 3D QTI-based quantitative MR biomarkers, we performed a ROI-based analysis to characterize T1 and T2 components in tumor and peritumoral tissue.

Results

The 3D acquisition combined with a compressed sensing reconstruction and neural network-based parameter inference produced parametric maps with high isotropic resolution (1.125 × 1.125 × 1.125 mm³ voxel size) and whole-brain coverage (22.5 × 22.5 × 22.5 cm³ FOV), enabling the synthesis of clinically relevant T1-weighted, T2-weighted, and FLAIR contrasts without any extra scan time. Our study revealed increased T1 and T2 values in tumor and peritumoral regions compared to contralateral white matter, good agreement with healthy volunteer data, and high inter-subject consistency.

Conclusion

3D QTI demonstrated comprehensive tissue assessment of tumor substructures captured in T1 and T2 parameters. Aiming for fast acquisition of quantitative MR biomarkers, 3D QTI has potential to improve disease characterization in brain tumor patients under tight clinical time-constraints.