Magnetic Resonance Fingerprinting - a promising new approach to obtain standardized imaging biomarkers from MRI

T1 mapping from routine 3D T1-weighted inversion recovery sequences in clinical practice: comparison against reference inversion recovery fast field echo T1 scans and feasibility in multiple sclerosis

BACKGROUND AND PURPOSE

Quantitative T1 mapping can be an essential tool for assessing tissue injury in multiple sclerosis (MS). We introduce T1-REQUIRE, a method that converts a single high-resolution anatomical 3D T1-weighted Turbo Field Echo (3DT1TFE) scan into a parametric T1 map that could be used for quantitative assessment of tissue damage. We present the accuracy and feasibility of this method in MS.

METHODS

14 subjects with relapsing-remitting MS and 10 healthy subjects were examined. T1 maps were generated from 3DT1TFE images using T1-REQUIRE, which estimates T1 values using MR signal equations and internal tissue reference T1 values. Estimated T1 of lesions, white, and gray matter regions were compared with reference Inversion-Recovery Fast Field Echo T1 values and analyzed via correlation and Bland-Altman (BA) statistics.

RESULTS

159 T1-weighted (T1W) hypointense MS lesions and 288 gray matter regions were examined. T1 values for MS lesions showed a Pearson's correlation of r = 0.81 (p < 0.000), R2 = 0.65, and Bias = 4.18%. BA statistics showed a mean difference of -53.95 ms and limits of agreement (LOA) of -344.20 and 236.30 ms. Non-lesional normal-appearing white matter had a correlation coefficient of r = 0.82 (p < 0.000), R2 = 0.67, Bias = 8.78%, mean difference of 73.87 ms, and LOA of -55.67 and 203.41 ms.

CONCLUSIONS

We demonstrate the feasibility of retroactively derived high-resolution T1 maps from routinely acquired anatomical images, which could be used to quantify tissue pathology in MS. The results of this study will set the stage for testing this method in larger clinical studies for examining MS disease activity and progression.

Synthetic Knee MRI T1p Maps as an Avenue for Clinical Translation of Quantitative Osteoarthritis Biomarkers

A 2D U-Net was trained to generate synthetic T1p maps from T2 maps for knee MRI to explore the feasibility of domain adaptation for enriching existing datasets and enabling rapid, reliable image reconstruction. The network was developed using 509 healthy contralateral and injured ipsilateral knee images from patients with ACL injuries and reconstruction surgeries acquired across three institutions. Network generalizability was evaluated on 343 knees acquired in a clinical setting and 46 knees from simultaneous bilateral acquisition in a research setting. The deep neural network synthesized high-fidelity reconstructions of T1p maps, preserving textures and local T1p elevation patterns in cartilage with a normalized mean square error of 2.4% and Pearson's correlation coefficient of 0.93. Analysis of reconstructed T1p maps within cartilage compartments revealed minimal bias (-0.10 ms), tight limits of agreement, and quantification error (5.7%) below the threshold for clinically significant change (6.42%) associated with osteoarthritis. In an out-of-distribution external test set, synthetic maps preserved T1p textures, but exhibited increased bias and wider limits of agreement. This study demonstrates the capability of image synthesis to reduce acquisition time, derive meaningful information from existing datasets, and suggest a pathway for standardizing T1p as a quantitative biomarker for osteoarthritis.

3D magnetic resonance fingerprinting on a low-field 50 mT point-of-care system prototype: evaluation of muscle and lipid relaxation time mapping and comparison with standard techniques

OBJECTIVE

To implement magnetic resonance fingerprinting (MRF) on a permanent magnet 50 mT low-field system deployable as a future point-of-care (POC) unit and explore the quality of the parameter maps.

MATERIALS AND METHODS

3D MRF was implemented on a custom-built Halbach array using a slab-selective spoiled steady-state free precession sequence with 3D Cartesian readout. Undersampled scans were acquired with different MRF flip angle patterns and reconstructed using matrix completion and matched to the simulated dictionary, taking excitation profile and coil ringing into account. MRF relaxation times were compared to that of inversion recovery (IR) and multi-echo spin echo (MESE) experiments in phantom and in vivo. Furthermore, B₀ inhomogeneities were encoded in the MRF sequence using an alternating TE pattern, and the estimated map was used to correct for image distortions in the MRF images using a model-based reconstruction.

RESULTS

Phantom relaxation times measured with an optimized MRF sequence for low field were in better agreement with reference techniques than for a standard MRF sequence. In vivo muscle relaxation times measured with MRF were longer than those obtained with an IR sequence (T₁: 182 ± 21.5 vs 168 ± 9.89 ms) and with an MESE sequence (T₂: 69.8 ± 19.7 vs 46.1 ± 9.65 ms). In vivo lipid MRF relaxation times were also longer compared with IR (T₁: 165 ± 15.1 ms vs 127 ± 8.28 ms) and with MESE (T₂: 160 ± 15.0 ms vs 124 ± 4.27 ms). Integrated ΔB₀ estimation and correction resulted in parameter maps with reduced distortions.

DISCUSSION

It is possible to measure volumetric relaxation times with MRF at 2.5 × 2.5 × 3.0 mm³ resolution in a 13 min scan time on a 50 mT permanent magnet system. The measured MRF relaxation times are longer compared to those measured with reference techniques, especially for T₂. This discrepancy can potentially be addressed by hardware, reconstruction and sequence design, but long-term reproducibility needs to be further improved.

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.

Supratentorial Meningioma Consistency Prediction Utilizing Tumor to Cerebellar Peduncle Intensity on T1 and T2-Weighted and Fluid Attenuated Inversion Recovery Magnetic Resonance Imaging Sequences

OBJECTIVE

Predicting meningioma consistency with preoperative imaging is critical for surgery planning. Preoperative T1 and T2-weighted and fluid attenuated inversion recovery magnetic resonance imaging (MRI) findings of supratentorial meningioma tumors were studied and compared with intraoperative supratentorial meningioma tumor consistency based on the Cavitron ultrasound surgical aspirator (CUSA) and ZADA grading scales in this cohort to predict the tumor consistency before surgery.

METHODS

MRI from 78 consecutive patients who underwent supratentorial meningioma tumor resection between 2018 and 2021 were evaluated preoperatively. An intraoperative tumor consistency grade was applied to these lesions prospectively by the operating surgeon based on CUSA and ZADA grading scales. Tumor/cerebellar peduncle T2-weighted intensity, tumor/cerebellar peduncle T1-weighted intensity (TCT1I), and tumor/cerebellar peduncle fluid attenuated inversion recovery intensity (TCFI) ratios were calculated. Tumor consistency grades and MRI intensity ratios were correlated using one-way ANOVA.

RESULTS

Of the 78 patients, 52 (66.7%) were female and 26 (33.3%) were male. Tumor volume correlated with tumor consistency grades on both CUSA (P = 0.005) and ZADA (P = 0.024) grading scales. Also patients age correlated with tumor consistency according to ZADA grading scale (P = 0.024). TCT1I (P = 0.009) and TCFI (P < 0.005) ratios correlated significantly with tumor consistency grade according to CUSA. Similarly, TCT1I (P = 0.0032) and TCFI (P = 0.001) ratios was significantly associated with tumor consistency according to ZADA grading scales.

CONCLUSIONS

Our findings suggest that higher tumor/cerebellar peduncle T2-weighted intensity and TCFI ratios correlate with softer tumors, while higher TCT1I ratios reveal firmer tumors. These data can assist the surgeon predict the supratentorial meningioma consistency before surgery.

Multicenter Repeatability and Reproducibility of MR Fingerprinting in Phantoms and in Prostatic Tissue

PURPOSE

To evaluate multicenter repeatability and reproducibility of T1 and T2 maps generated using MR fingerprinting (MRF) in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom and in prostatic tissues.

METHODS

MRF experiments were performed on 5 different 3 Tesla MRI scanners at 3 different institutions: University Hospitals Cleveland Medical Center (Cleveland, OH), Brigham and Women's Hospital (Boston, MA) in the United States, and Diagnosticos da America (Rio de Janeiro, RJ) in Brazil. Raw MRF data were reconstructed using a Gadgetron-based MRF online reconstruction pipeline to yield quantitative T1 and T2 maps. The repeatability of T1 and T2 values over 6 measurements in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom was assessed to demonstrate intrascanner variation. The reproducibility between the 4 clinical scanners was assessed to demonstrate interscanner variation. The same-day test-retest normal prostate mean T1 and T2 values from peripheral zone and transitional zone were also compared using the intraclass correlation coefficient and Bland-Altman analysis.

RESULTS

The intrascanner variation of values measured using MRF was less than 2% for T1 and 4.7% for T2 for relaxation values, within the range of 307.7 to 2360 ms for T1 and 19.1 to 248.5 ms for T2 . Interscanner measurements showed that the T1 variation was less than 4.9%, and T2 variation was less than 8.1% between multicenter scanners. Both T1 and T2 values in in vivo prostatic tissue demonstrated high test-retest reliability (intraclass correlation coefficient > 0.92) and strong linear correlation (R2  > 0.840).

CONCLUSION

Prostate MRF measurements of T1 and T2 are repeatable and reproducible between MRI scanners at different centers on different continents for the above measurement ranges.

Multiplexed imaging in oncology

In oncology, technologies for clinical molecular imaging are used to diagnose patients, establish the efficacy of treatments and monitor the recurrence of disease. Multiplexed methods increase the number of disease-specific biomarkers that can be detected simultaneously, such as the overexpression of oncogenic proteins, aberrant metabolite uptake and anomalous blood perfusion. The quantitative localization of each biomarker could considerably increase the specificity and the accuracy of technologies for clinical molecular imaging to facilitate granular diagnoses, patient stratification and earlier assessments of the responses to administered therapeutics. In this Review, we discuss established techniques for multiplexed imaging and the most promising emerging multiplexing technologies applied to the imaging of isolated tissues and cells and to non-invasive whole-body imaging. We also highlight advances in radiology that have been made possible by multiplexed imaging.

Multiparametric Functional MRI of the Kidney: Current State and Future Trends with Deep Learning Approaches

BACKGROUND

 Until today, assessment of renal function has remained a challenge for modern medicine. In many cases, kidney diseases accompanied by a decrease in renal function remain undetected and unsolved, since neither laboratory tests nor imaging diagnostics provide adequate information on kidney status. In recent years, developments in the field of functional magnetic resonance imaging with application to abdominal organs have opened new possibilities combining anatomic imaging with multiparametric functional information. The multiparametric approach enables the measurement of perfusion, diffusion, oxygenation, and tissue characterization in one examination, thus providing more comprehensive insight into pathophysiological processes of diseases as well as effects of therapeutic interventions. However, application of multiparametric fMRI in the kidneys is still restricted mainly to research areas and transfer to the clinical routine is still outstanding. One of the major challenges is the lack of a standardized protocol for acquisition and postprocessing including efficient strategies for data analysis. This article provides an overview of the most common fMRI techniques with application to the kidney together with new approaches regarding data analysis with deep learning.

METHODS

 This article implies a selective literature review using the literature database PubMed in May 2021 supplemented by our own experiences in this field.

RESULTS AND CONCLUSION

 Functional multiparametric MRI is a promising technique for assessing renal function in a more comprehensive approach by combining multiple parameters such as perfusion, diffusion, and BOLD imaging. New approaches with the application of deep learning techniques could substantially contribute to overcoming the challenge of handling the quantity of data and developing more efficient data postprocessing and analysis protocols. Thus, it can be hoped that multiparametric fMRI protocols can be sufficiently optimized to be used for routine renal examination and to assist clinicians in the diagnostics, monitoring, and treatment of kidney diseases in the future.

KEY POINTS

  · Multiparametric fMRI is a technique performed without the use of radiation, contrast media, and invasive methods.. · Multiparametric fMRI provides more comprehensive insight into pathophysiological processes of kidney diseases by combining functional and structural parameters.. · For broader acceptance of fMRI biomarkers, there is a need for standardization of acquisition, postprocessing, and analysis protocols as well as more prospective studies.. · Deep learning techniques could significantly contribute to an optimization of data acquisition and the postprocessing and interpretation of larger quantities of data..

CITATION FORMAT

· Zhang C, Schwartz M, Küstner T et al. Multiparametric Functional MRI of the Kidney: Current State and Future Trends with Deep Learning Approaches. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1775-8633.

Relaxation time of brain tissue in the elderly assessed by synthetic MRI

BACKGROUND

Synthetic MRI (SyMRI) is a quantitative technique that allows measurements of T1 and T2 relaxation times (RTs). Brain RT evolution across lifespan is well described for the younger population. The aim was to study RTs of brain parenchyma in a healthy geriatric population in order to define the normal value of structures in this group population. Normal values for geriatric population could help find biomarker for age-related brain disease.

MATERIALS AND METHODS

Fifty-four normal-functioning individuals (22 females, 32 males) with mean age of 83 years (range 56-98) underwent SyMRI. RT values in manually defined ROIs (centrum semiovale, middle cerebellar peduncles, thalamus, and insular cortex) and in segmented whole-brain components (brain parenchyma, gray matter, white matter, myelin, CSF, and stromal structures) were extracted from the SyMRI segmentation software. Patients' results were combined into the group age. Main ROI-based and whole-brain results were compared for the all dataset and for age group results as well.

RESULTS

For white matter, RTs between ROI-based analyses and whole-brain results for T2 and for T1 were statistically different and a trend of increasing T1 in centrum semiovale and cerebellar peduncle was observed. For gray matter, thalamic T1 was statistically different from insular T1. A difference was also found between left and right insula (p < .0001). T1 RTs of ROI-based and whole-brain-based analyses were statistically different (p < .0001). No significant difference in T1 and T2 was found between age groups on ROI-based analysis, but T1 in centrum semiovale and thalamus increased with age. No statistical difference between age groups was found for the various segmented volumes except for myelin between 65-74 years of age and the 95-105 years of age groups (p = .038).

CONCLUSIONS

SyMRI is a new tool that allows faster imaging and permits to obtain quantitative T1 and T2. By defining RT values of different brain components of normal-functioning elderly individuals, this technique may be used as a biomarker for clinical disorders like dementia.

T2 quantification in brain using 3D fast spin-echo imaging with long echo trains

Purpose

Three‐dimensional fast spin‐echo (FSE) sequences commonly use very long echo trains (>64 echoes) and severely reduced refocusing angles. They are increasingly used in brain exams due to high, isotropic resolution and reasonable scan time when using long trains and short interecho spacing. In this study, T₂ quantification in 3D FSE is investigated to achieve increased resolution when comparing with established 2D (proton‐density dual‐echo and multi‐echo spin‐echo) methods.

Methods

The FSE sequence design was explored to use long echo trains while minimizing T₂ fitting error and maintaining typical proton density and T₂‐weighted contrasts. Constant and variable flip angle trains were investigated using extended phase graph and Bloch equation simulations. Optimized parameters were analyzed in phantom experiments and validated in vivo in comparison to 2D methods for eight regions of interest in brain, including deep gray‐matter structures and white‐matter tracts.

Results

Phantom and healthy in vivo brain T₂ measurements showed that optimized variable echo‐train 3D FSE performs similarly to previous 2D methods, while achieving three‐fold‐higher slice resolution, evident visually in the 3D T₂ maps. Optimization resulted in better T₂ fitting and compared well with standard multi‐echo spin echo (within the 8‐ms confidence limits defined based on Bland‐Altman analysis).

Conclusion

T₂ mapping using 3D FSE with long echo trains and variable refocusing angles provides T₂ accuracy in agreement with 2D methods with additional high‐resolution benefits, allowing isotropic views while avoiding incidental magnetization transfer effects. Consequently, optimized 3D sequences should be considered when choosing T₂ mapping methods for high anatomic detail.

Magnetic Resonance Fingerprinting for Preoperative Meningioma Consistency Prediction

RATIONALE AND OBJECTIVES

Preoperative meningioma consistency prediction is highly beneficial for surgical planning and prognostication. We aimed to use magnetic resonance fingerprinting (MRF)-derived T1 and T2 values to preoperatively predict meningioma consistency.

MATERIALS AND METHODS

A total of 51 patients with meningiomas were enrolled in this study. MRF, T1-weighted imaging, T2-weighted imaging, and diffusion-weighted imaging were performed in all patients before surgery using a 3T MRI scanner. MRF-derived T1 and T2 values, T1-weightd and T2-weighted signal intensities, as well as apparent diffusion coefficient value yield from diffusion-weighted imaging were compared between the soft, moderate and hard meningiomas. Receiver operating characteristic curve analyses were used to determine the diagnostic performance of T1, T2 value, and a combination of T1 and T2 values.

RESULTS

After Bonferroni corrections, quantitative T1 and T2 values yielded from MRF were significantly different between the soft, moderate and hard meningiomas (all p < 0.05). T2 signal intensity was significantly different between the soft and hard, soft and moderate meningiomas (both p < 0.05), whereas was not significantly different between the moderate and hard meningiomas. However, T1 signal intensity and apparent diffusion coefficient value had no significant differences between the soft, moderate and hard meningiomas (all p > 0.05). The combination of T1 and T2 values had greater areas under receiver operating characteristic curve curves compared to individual T1 or T2 value.

CONCLUSION

MRF may help to preoperatively differentiate between the soft, moderate and hard meningiomas and may be useful in guiding the surgical planning.

Neuroimaging for the Primary Care Provider: A Review of Modalities, Indications, and Pitfalls

When evaluating a child with a potential neurologic or neurodevelopmental disorder, identifying indications for imaging and the correct imaging modality to order can be challenging. This article provides an overview of computed tomography, MRI, ultrasonography, and radiography with an emphasis on indications for use, pitfalls to be avoided, and recent advances. A discussion of the appropriate use of ionizing radiation, intravenous contrast, and sedation is also provided.

Magnetic resonance fingerprinting for preoperative differentiation between gonadotroph and non-gonadotroph pituitary macroadenomas

OBJECTIVES

To use magnetic resonance fingerprinting (MRF)-derived T1 and T2 values to differentiate gonadotroph from non-gonadotroph pituitary macroadenomas based on the 2017 World Health Organization classification of pituitary adenomas.

METHODS

A total of 57 patients with suspected pituitary macroadenomas were enrolled for analyses in this study between May 2018 and January 2020. Conventional magnetic resonance imaging (MRI) and MRF were performed in all patients before surgery using a 3-T MRI scanner. MRF-derived T1 and T2 values were compared between the gonadotroph and non-gonadotroph pituitary macroadenomas using a Mann-Whitney U test. The Knosp classification was used to evaluate cavernous sinus invasion by the adenomas. Receiver operating characteristic analyses were used to determine the diagnostic performance of T1 and T2 values.

RESULTS

Quantitative T1 and T2 values yielded from MRF of gonadotroph pituitary macroadenomas were significantly higher than those of the non-gonadotroph pituitary macroadenomas (p < 0.001 and = 0.002, respectively). The AUC for the T2 value (0.888) was significantly greater than that for the T1 value (0.742) (p = 0.034). The AUC for combined T1 and T2 values was 0.885. Non-gonadotroph pituitary macroadenomas were more likely to invade the cavernous sinus than gonadotroph pituitary macroadenomas (55% vs 26%, p = 0.026).

CONCLUSIONS

MRF may help to preoperatively differentiate between gonadotroph and non-gonadotroph pituitary macroadenomas and may be useful in guiding the treatment of these adenomas.

KEY POINTS

• Somatostatin receptor type 3 is the most abundant receptor subtype in gonadotroph pituitary adenomas. • Magnetic resonance fingerprinting may help to preoperatively differentiate between gonadotroph and non-gonadotroph pituitary macroadenomas. • Magnetic resonance fingerprinting shows potential for guiding the treatment of pituitary macroadenomas.

Quantitative T1 mapping of the normal brain from early infancy to adulthood

BACKGROUND

Quantitative mapping of MRI relaxation times is expected to uncover pathological processes in the brain more subtly than standard MRI techniques with weighted contrasts. So far, however, most mapping techniques suffer from a long measuring time, low spatial resolution or even sensitivity to magnetic field inhomogeneity.

OBJECTIVE

To obtain T1 relaxation times of the normal brain from early infancy to adulthood using a novel technique for fast and accurate T1 mapping at high spatial resolution.

MATERIALS AND METHODS

We performed whole-brain T1 mapping within less than 3 min in 100 patients between 2 months and 18 years of age with normal brain at a field strength of 3 T. We analyzed T1 relaxation times in several gray-matter nuclei and white matter. Subsequently, we derived regression equations for mean value and confidence interval.

RESULTS

T1 relaxation times of the pediatric brain rapidly decrease in all regions within the first 3 years of age, followed by a significantly weaker decrease until adulthood. These characteristics are more pronounced in white matter than in deep gray matter.

CONCLUSION

Regardless of age, quantitative T1 mapping of the pediatric brain is feasible in clinical practice. Normal age-dependent values should contribute to improved discrimination of subtle intracerebral alterations.

Pulse sequences for measuring exchange rates between proton species: From unlocalised NMR spectroscopy to chemical exchange saturation transfer imaging

Within the field of NMR spectroscopy, the study of chemical exchange processes through saturation transfer techniques has a long history. In the context of MRI, chemical exchange techniques have been adapted to increase the sensitivity of imaging to small fractions of exchangeable protons, including the labile protons of amines, amides and hydroxyls. The MR contrast is generated by frequency-selective irradiation of the labile protons, which results in a reduction of the water signal associated with transfer of the labile protons' saturated magnetization to the protons of the surrounding free water. The signal intensity depends on the rate of chemical exchange and the concentration of labile protons as well as on the properties of the irradiation field. This methodology is referred to as CEST (chemical exchange saturation transfer) imaging. Applications of CEST include imaging of molecules with short transverse relaxation times and mapping of physiological parameters such as pH, temperature, buffer concentration and chemical composition due to the dependency of this chemical exchange effect on all these parameters. This article aims to describe these effects both theoretically and experimentally. In depth analysis and mathematical modelling are provided for all pulse sequences designed to date to measure the chemical exchange rate. Importantly, it has become clear that the background signal from semi-solid protons and the presence of the Nuclear Overhauser Effect (NOE), either through direct dipole-dipole mechanisms or through exchange-relayed signals, complicates the analysis of CEST effects. Therefore, advanced methods to suppress these confounding factors have been developed, and these are also reviewed. Finally, the experimental work conducted both in vitro and in vivo is discussed and the progress of CEST imaging towards clinical practice is presented.

Applying Artificial Intelligence to Mitigate Effects of Patient Motion or Other Complicating Factors on Image Quality

Artificial intelligence, particularly deep learning, offers several possibilities to improve the quality or speed of image acquisition in magnetic resonance imaging (MRI). In this article, we briefly review basic machine learning concepts and discuss commonly used neural network architectures for image-to-image translation. Recent examples in the literature describing application of machine learning techniques to clinical MR image acquisition or postprocessing are discussed. Machine learning can contribute to better image quality by improving spatial resolution, reducing image noise, and removing undesired motion or other artifacts. As patients occasionally are unable to tolerate lengthy acquisition times or gadolinium agents, machine learning can potentially assist MRI workflow and patient comfort by facilitating faster acquisitions or reducing exogenous contrast dosage. Although artificial intelligence approaches often have limitations, such as problems with generalizability or explainability, there is potential for these techniques to improve diagnostic utility, throughput, and patient experience in clinical MRI practice.

Acceleration of 2D-MR fingerprinting by reducing the number of echoes with increased in-plane resolution: a volunteer study

Objective

To compare the absolute values and repeatability of magnetic resonance fingerprinting (MRF) with 3000 and 1500 echoes/slice acquired in 41 s and 20 s (MRF3k and MRF1.5k, respectively).

Materials and methods

MRF3k and MRF1.5k scans based on fast imaging with steady precession (FISP) were conducted using a 3 T scanner. Inter-scan agreement and intra-scan repeatability were investigated in 41 and 28 subjects, respectively. Region-of-interest (ROI) analysis was conducted on T1 values of MRF3k by two raters, and their agreement was evaluated using intraclass correlation coefficients (ICCs). Between MRF3k and MRF1.5k, differences in T1 and T2 values and inter-measurement correlation coefficients (CCs) were investigated. Intra-measurement repeatability was evaluated using coefficients of variation (CVs). A p value < 0.05 was considered statistically significant.

Results

The ICCs of ROI measurements were 0.77–0.96. Differences were observed between the two MRF scans, but the CCs of the overall ROIs were 0.99 and 0.97 for the T1 and T2 values, respectively. The mean and median CVs of repeatability were equal to or less than 1.58% and 3.13% in each of the ROIs for T1 and T2, respectively; there were some significant differences between MRF3k and MRF1.5k, but they were small, measuring less than 1%.

Discussion

Both MRF3k and MRF1.5k had high repeatability, and a strong to very strong correlation was observed, with a trend toward slightly higher values in MRF1.5k.

Electronic supplementary material

The online version of this article (10.1007/s10334-020-00842-8) contains supplementary material, which is available to authorized users.

Clinical MR Biomarkers

Non-invasive magnetic resonance imaging (MRI) techniques are increasingly applied in the clinic with a fast growing body of evidence regarding its value for clinical decision making. In contrast to biochemical or histological markers, the key advantages of imaging biomarkers are the non-invasive nature and the spatial and temporal resolution of these approaches. The following chapter focuses on clinical applications of novel MR biomarkers in humans with a strong focus on oncologic diseases. These include both clinically established biomarkers (part 1-4) and novel MRI techniques that recently demonstrated high potential for clinical utility (part 5-7).

snapMRF: GPU-accelerated magnetic resonance fingerprinting dictionary generation and matching using extended phase graphs

PURPOSE

Magnetic resonance fingerprinting (MRF) is a state-of-the-art quantitative MRI technique with a computationally demanding reconstruction process, the accuracy of which depends on the accuracy of the signal model employed. Having a fast, validated, open-source MRF reconstruction would improve the dependability and accuracy of clinical applications of MRF.

METHODS

We parallelized both dictionary generation and signal matching on the GPU by splitting the simulation and matching of dictionary atoms across threads. Signal generation was modeled using both Bloch equation simulation and the extended phase graph (EPG) formalism. Unit tests were implemented to ensure correctness. The new package, snapMRF, was tested with a calibration phantom and an in vivo brain.

RESULTS

Compared with other online open-source packages, dictionary generation was accelerated by 10-1000× and signal matching by 10-100×. On a calibration phantom, T₁ and T₂ values were measured with relative errors that were nearly identical to those from existing packages when using the same sequence and dictionary configuration, but errors were much lower when using variable sequences that snapMRF supports but that competitors do not.

CONCLUSION

Our open-source package snapMRF was significantly faster and retrieved accurate parameters, possibly enabling real-time parameter map generation for small dictionaries. Further refinements to the acquisition scheme and dictionary setup could improve quantitative accuracy.

Magnetic resonance fingerprinting of temporal lobe white matter in mesial temporal lobe epilepsy

Objective

Mesial temporal lobe epilepsy (MTLE) is a network disorder. We aimed to quantify the white matter alterations in the temporal lobe of MTLE patients with hippocampal sclerosis (MTLE‐HS) by using magnetic resonance fingerprinting (MRF), a novel imaging technique, which allows simultaneous measurements of multiple parameters with a single acquisition.

Methods

We consecutively recruited 27 unilateral MTLE‐HS patients and 22 healthy controls. Measurements including T1, T2, and PD values in the temporopolar white matter and temporal stem were recorded and analyzed.

Results

We found increased T2 value in both sides, and increased T1 value in the ipsilateral temporopolar white matter of MTLE‐HS patients, as compared with healthy controls. The T1 and T2 values were higher in the ipsilateral than the contralateral side. In the temporal stem, increased T1 and T2 values in the ipsilateral side of the MTLE‐HS patients were also observed. Only increased T2 values were observed in the contralateral temporal stem. No significant differences in PD values were observed in either the temporopolar white matter or temporal stem of the MTLE‐HS patients. Correlation analysis revealed that T1 and T2 values in the ipsilateral temporopolar white matter were negatively correlated with the age at epilepsy onset.

Interpretation

By using MRF, we were able to assess the alterations of T1 and T2 in the temporal lobe white matter of MTLE‐HS patients. MRF could be a promising imaging technique in identifying mild changes in MTLE patients, which might optimize the pre‐surgical evaluation and therapeutic interventions in these patients.

Recent Advances in Pediatric Brain, Spine, and Neuromuscular Magnetic Resonance Imaging Techniques

Magnetic resonance imaging (MRI) is a powerful radiologic tool with the ability to generate a variety of proton-based signal contrast from tissues. Owing to this immense flexibility in signal generation, new MRI techniques are constantly being developed, tested, and optimized for clinical utility. In addition, the safe and nonionizing nature of MRI makes it a suitable modality for imaging in children. In this review article, we summarize a few of the most popular advances in MRI techniques in recent years. In particular, we highlight how these new developments have affected brain, spine, and neuromuscular imaging and focus on their applications in pediatric patients. In the first part of the review, we discuss new approaches such as multiphase and multidelay arterial spin labeling for quantitative perfusion and angiography of the brain, amide proton transfer MRI of the brain, MRI of brachial plexus and lumbar plexus nerves (i.e., neurography), and T2 mapping and fat characterization in neuromuscular diseases. In the second part of the review, we focus on describing new data acquisition strategies in accelerated MRI aimed collectively at reducing the scan time, including simultaneous multislice imaging, compressed sensing, synthetic MRI, and magnetic resonance fingerprinting. In discussing the aforementioned, the review also summarizes the advantages and disadvantages of each method and their current state of commercial availability from MRI vendors.

Detection of IV-gadolinium Leakage from the Cortical Veins into the CSF Using MR Fingerprinting

Purpose:

It has been reported that leakage of intravenously administered gadolinium-based contrast agents (IV-GBCAs) into the cerebrospinal fluid (CSF) from the cortical veins even in healthy subjects can be detected using a highly sensitive pulse sequence such as heavily T₂-weighted 3D fluid-attenuated inversion recovery and 3D-real inversion recovery (IR). The purpose of this study was to evaluate the feasibility of MR fingerprinting to detect GBCA leakage from the cortical veins after IV-GBCA.

Materials:

Fourteen patients with suspected endolymphatic hydrops (EH) who received a single dose of IV-GBCA (39–79 years old) were included. The real IR images as well as MR fingerprinting images were obtained at 4 h after IV-GBCA. T₁ and T₂ values were obtained using MR fingerprinting and analyzed in ROIs covering intense GBCA leakage, and non-leakage areas of the CSF as determined on real IR images. The scan time for real IR imaging was 10 min and that for MR fingerprinting was 41 s.

Results:

The mean T₁ value of the ROI in the area of GBCA leakage was 2422 ± 261 ms and that in the non-leakage area was 3851 ± 235 ms (P < 0.01). There was no overlap between the T₁ values in the area of GBCA leakage and those in the non-leakage area.

The mean T₂ value in the area of GBCA leakage was 319 ± 90 ms and that in the non-leakage area was 670 ± 166 ms (P < 0.01). There was some overlap between the T₂ values in the area of GBCA leakage and those in the non-leakage area.

Conclusion:

Leaked GBCA from the cortical veins into the surrounding CSF can be detected using MR fingerprinting obtained in <1 min.

Imaging the aged brain: pertinence and methods

The global population is ageing at an accelerating speed. The ability to perform working memory tasks together with rapid processing becomes increasingly difficult with increases in age. With increasing national average life spans and a rise in the prevalence of age-related disease, it is pertinent to discuss the unique perspectives that can be gained from imaging the aged brain. Differences in structure, function, blood flow, and neurovascular coupling are present in both healthy aged brains and in diseased brains and have not yet been explored to their full depth in contemporary imaging studies. Imaging methods ranging from optical imaging to magnetic resonance imaging (MRI) to newer technologies such as photoacoustic tomography each offer unique advantages and challenges in imaging the aged brain. This paper will summarize first the importance and challenges of imaging the aged brain and then offer analysis of potential imaging modalities and their representative applications. The potential breakthroughs in brain imaging are also envisioned.

Magnetic Resonance Fingerprinting to Characterize Childhood and Young Adult Brain Tumors

OBJECT

Magnetic resonance fingerprinting (MRF) allows rapid, simultaneous mapping of T1 and T2 relaxation times and may be an important diagnostic tool to measure tissue characteristics in pediatric brain tumors. We examined children and young adults with primary brain tumors to determine whether MRF can discriminate tumor from normal-appearing white matter and distinguish tumor grade.

METHODS

MRF was performed in 23 patients (14 children and 9 young adults) with brain tumors (19 low-grade glioma, 4 high-grade tumors). T1 and T2 values were recorded in regions of solid tumor (ST), peritumoral white matter (PWM), and contralateral white matter (CWM). Nonparametric tests were used for comparison between groups and regions.

RESULTS

Median scan time for MRF and a sequence for tumor localization was 11 min. MRF-derived T1 and T2 values distinguished ST from CWM (T1: 1,444 ± 254 ms vs. 938 ± 96 ms, p = 0.0002; T2: 61 ± 22 ms vs. 38 ± 9 ms, p = 0.0003) and separated high-grade tumors from low-grade tumors (T1: 1,863 ± 70 ms vs. 1,355 ± 187 ms, p = 0.007; T2: 90 ± 13 ms vs. 56 ± 19 ms, p = 0.013). PWM was distinct from CWM (T1: 1,261 ± 359 ms vs. 933 ± 104 ms, p = 0.0008; T2: 65 ± 51 ms vs. 38 ± 8 ms, p = 0.008), as well as from tumor (T1: 1,261 ± 371 ms vs. 1,462 ± 248 ms, p = 0.047).

CONCLUSIONS

MRF is a fast sequence that can rapidly distinguish important tissue components in pediatric brain tumor patients. MRF-derived T1 and T2 distinguished tumor from normal-appearing white matter, differentiated tumor grade, and found abnormalities in peritumoral regions. MRF may be useful for rapid quantitative measurement of tissue characteristics and distinguish tumor grade in children and young adults with brain tumors.

An overview of deep learning in medical imaging focusing on MRI

What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started around 2009 when so-called deep artificial neural networks began outperforming other established models on a number of important benchmarks. Deep neural networks are now the state-of-the-art machine learning models across a variety of areas, from image analysis to natural language processing, and widely deployed in academia and industry. These developments have a huge potential for medical imaging technology, medical data analysis, medical diagnostics and healthcare in general, slowly being realized. We provide a short overview of recent advances and some associated challenges in machine learning applied to medical image processing and image analysis. As this has become a very broad and fast expanding field we will not survey the entire landscape of applications, but put particular focus on deep learning in MRI. Our aim is threefold: (i) give a brief introduction to deep learning with pointers to core references; (ii) indicate how deep learning has been applied to the entire MRI processing chain, from acquisition to image retrieval, from segmentation to disease prediction; (iii) provide a starting point for people interested in experimenting and perhaps contributing to the field of deep learning for medical imaging by pointing out good educational resources, state-of-the-art open-source code, and interesting sources of data and problems related medical imaging.

The application of magnetic resonance fingerprinting to single voxel proton spectroscopy

Magnetic resonance fingerprinting has been proposed as a method for undersampling k-space while simultaneously yielding multiparametric tissue maps. In the context of single voxel spectroscopy, fingerprinting can provide a unified framework for parameter estimation. We demonstrate the utility of such a magnetic resonance spectroscopic fingerprinting (MRSF) framework for simultaneously quantifying metabolite concentrations, T₁ and T₂ relaxation times and transmit inhomogeneity for major singlets of N-acetylaspartate, creatine and choline. This is achieved by varying T_R , T_E and the flip angle of the first pulse in a PRESS sequence between successive excitations (i.e. successive T_R values). The need for multiparametric schemes such as MRSF for accurate medical diagnostics is demonstrated with the aid of realistic in vivo simulations; these show that certain schemes lead to substantial increases to the area under receiver operating characteristics of metabolite concentrations, when viewed as classifiers of pathologies. Numerical simulations and phantom and in vivo experiments using several different schedules of variable length demonstrate superior precision and accuracy for metabolite concentrations and longitudinal relaxation, and similar performance for the quantification of transverse relaxation.

Feasibility of a Synthetic MR Imaging Sequence for Spine Imaging

BACKGROUND AND PURPOSE

Synthetic MR imaging is a method that can produce multiple contrasts from a single sequence, as well as quantitative maps. Our aim was to determine the feasibility of a synthetic MR image for spine imaging.

MATERIALS AND METHODS

Thirty-eight patients with clinical indications of infectious, degenerative, and neoplastic disease underwent an MR imaging of the spine (11 cervical, 8 dorsal, and 19 lumbosacral MR imaging studies). The SyntAc sequence, with an acquisition time of 5 minutes 40 seconds, was added to the usual imaging protocol consisting of conventional sagittal T1 TSE, T2 TSE, and STIR TSE.

RESULTS

Synthetic T1-weighted, T2-weighted, and STIR images were of adequate quality, and the acquisition time was 53% less than with conventional MR imaging. The image quality was rated as "good" for both synthetic and conventional images. Interreader agreement concerning lesion conspicuity was good with a Cohen κ of 0.737. Artifacts consisting of white pixels/spike noise across contrast views, as well as flow artifacts, were more common in the synthetic sequences, particularly in synthetic STIR. There were no statistically significant differences between readers concerning the scores assigned for image quality or lesion conspicuity.

CONCLUSIONS

Our study shows that synthetic MR imaging is feasible in spine imaging and produces, in general, good image quality and diagnostic confidence. Furthermore, the non-negligible time savings and the ability to obtain quantitative measurements as well as to generate several contrasts with a single acquisition should promise a bright future for synthetic MR imaging in clinical routine.

Exploring Applications of Radiomics in Magnetic Resonance Imaging of Head and Neck Cancer: A Systematic Review

Background

Radiomics has been widely investigated for non-invasive acquisition of quantitative textural information from anatomic structures. While the vast majority of radiomic analysis is performed on images obtained from computed tomography, magnetic resonance imaging (MRI)-based radiomics has generated increased attention. In head and neck cancer (HNC), however, attempts to perform consistent investigations are sparse, and it is unclear whether the resulting textural features can be reproduced. To address this unmet need, we systematically reviewed the quality of existing MRI radiomics research in HNC.

Methods

Literature search was conducted in accordance with guidelines established by Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Electronic databases were examined from January 1990 through November 2017 for common radiomic keywords. Eligible completed studies were then scored using a standardized checklist that we developed from Enhancing the Quality and Transparency of Health Research guidelines for reporting machine-learning predictive model specifications and results in biomedical research, defined by Luo et al. (1). Descriptive statistics of checklist scores were populated, and a subgroup analysis of methodology items alone was conducted in comparison to overall scores.

Results

Sixteen completed studies and four ongoing trials were selected for inclusion. Of the completed studies, the nasopharynx was the most common site of study (37.5%). MRI modalities varied with only four of the completed studies (25%) extracting radiomic features from a single sequence. Study sample sizes ranged between 13 and 118 patients (median of 40), and final radiomic signatures ranged from 2 to 279 features. Analyzed endpoints included either segmentation or histopathological classification parameters (44%) or prognostic and predictive biomarkers (56%). Liu et al. (2) addressed the highest number of our checklist items (total score: 48), and a subgroup analysis of methodology checklist items alone did not demonstrate any difference in scoring trends between studies [Spearman’s ρ = 0.94 (p < 0.0001)].

Conclusion

Although MRI radiomic applications demonstrate predictive potential in analyzing diverse HNC outcomes, methodological variances preclude accurate and collective interpretation of data.

Clinical equivalence assessment of T2 synthesized pediatric brain magnetic resonance imaging

BACKGROUND AND PURPOSE

Automated synthetic magnetic resonance imaging (MRI) provides qualitative, weighted image contrasts as well as quantitative information from one scan and is well-suited for various applications such as analysis of white matter disorders. However, the synthesized contrasts have been poorly evaluated in pediatric applications. The purpose of this study was to compare the image quality of synthetic T2 to conventional turbo spin-echo (TSE) T2 in pediatric brain MRI.

MATERIALS AND METHODS

This was a mono-center prospective study. Synthetic and conventional MRI acquisitions at 1.5 Tesla were performed for each patient during the same session using a prototype accelerated T2 mapping sequence package (TA_synthetic=3:07min, TA_conventional=2:33min). Image sets were blindly and randomly analyzed by pediatric neuroradiologists. Global image quality, morphologic legibility of standard structures and artifacts were assessed using a 4-point Likert scale. Inter-observer kappa agreements were calculated. The capability of the synthesized contrasts and conventional TSE T2 to discern normal and pathologic cases was evaluated.

RESULTS

Sixty patients were included. The overall diagnostic quality of the synthesized contrasts was non-inferior to conventional imaging scale (P=0.06). There was no significant difference in the legibility of normal and pathological anatomic structures of synthetized and conventional TSE T2 (all P>0.05) as well as for artifacts except for phase encoding (P=0.008). Inter-observer agreement was good to almost perfect (kappa between 0.66 and 1).

CONCLUSIONS

T2 synthesized contrasts, which also provides quantitative T2 information that could be useful, could be suggested as an equivalent technique in pediatric neuro-imaging, compared to conventional TSE T2.

PRO-QUEST: a rapid assessment method based on progressive saturation for quantifying exchange rates using saturation times in CEST

PURPOSE

To develop a new MRI technique to rapidly measure exchange rates in CEST MRI.

METHODS

A novel pulse sequence for measuring chemical exchange rates through a progressive saturation recovery process, called PRO-QUEST (progressive saturation for quantifying exchange rates using saturation times), has been developed. Using this method, the water magnetization is sampled under non-steady-state conditions, and off-resonance saturation is interleaved with the acquisition of images obtained through a Look-Locker type of acquisition. A complete theoretical framework has been set up, and simple equations to obtain the exchange rates have been derived.

RESULTS

A reduction of scan time from 58 to 16 minutes has been obtained using PRO-QUEST versus the standard QUEST. Maps of both T₁ of water and B₁ can simply be obtained by repetition of the sequence without off-resonance saturation pulses. Simulations and calculated exchange rates from experimental data using amino acids such as glutamate, glutamine, taurine, and alanine were compared and found to be in good agreement. The PRO-QUEST sequence was also applied on healthy and infarcted rats after 24 hours, and revealed that imaging specificity to ischemic acidification during stroke was substantially increased relative to standard amide proton transfer-weighted imaging.

CONCLUSION

Because of the reduced scan time and insensitivity to nonchemical exchange factors such as direct water saturation, PRO-QUEST can serve as an excellent alternative for researchers and clinicians interested to map pH changes in vivo.

Normal Values of Magnetic Relaxation Parameters of Spine Components with the Synthetic MRI Sequence

BACKGROUND AND PURPOSE

SyMRI is a technique developed to perform quantitative MR imaging. Our aim was to analyze its potential use for measuring relaxation times of normal components of the spine and to compare them with values found in the literature using relaxometry and other techniques.

MATERIALS AND METHODS

Thirty-two spine MR imaging studies (10 cervical, 5 dorsal, 17 lumbosacral) were included. A modified multiple-dynamic multiple-echo sequence was added and processed to obtain quantitative T1 (millisecond), T2 (millisecond), and proton density (percentage units [pu]) maps for each patient. An ROI was placed on representative areas for CSF, spinal cord, intervertebral discs, and vertebral bodies, to measure their relaxation.

RESULTS

Relaxation time means are reported for CSF (T1 = 4273.4 ms; T2 = 1577.6 ms; proton density = 107.5 pu), spinal cord (T1 = 780.2 ms; T2 = 101.6 ms; proton density = 58.7 pu), normal disc (T1 = 1164.9 ms; T2 = 101.9 ms; proton density = 78.9 pu), intermediately hydrated disc (T1 = 723 ms; T2 = 66.8 ms; proton density = 60.8 pu), desiccated disc (T1 = 554.4 ms; T2 = 55.6 ms; proton density = 47.6 ms), and vertebral body (T1 = 515.3 ms; T2 = 100.8 ms; proton density = 91.1 pu). Comparisons among the mean T1, T2, and proton density values showed significant differences between different spinal levels (cervical, dorsal, lumbar, and sacral) for CSF (proton density), spinal cord (T2 and proton density), normal disc (T1, T2, and proton density), and vertebral bodies (T1 and proton density). Significant differences were found among mean T1, T2, and proton density values of normal, intermediately hydrated, and desiccated discs.

CONCLUSIONS

Measurements can be easily obtained on SyMRI and correlated with previously published values obtained using conventional relaxometry techniques.

Advances in High-Field MRI

MRI techniques and systems have evolved dramatically over recent years. These advances include higher field strengths, new techniques, faster gradients, improved coil technology, and more robust sequence protocols. This article reviews the most commonly used advanced MRI techniques, including diffusion-weighted imaging, magnetic resonance spectrography, diffusion tensor imaging, and cerebrospinal fluid flow tracking.

Magnetic Resonance Fingerprinting-An Overview

Magnetic Resonance Fingerprinting (MRF) is a new approach to quantitative magnetic resonance imaging that allows simultaneous measurement of multiple tissue properties in a single, time-efficient acquisition. The ability to reproducibly and quantitatively measure tissue properties could enable more objective tissue diagnosis, comparisons of scans acquired at different locations and time points, longitudinal follow-up of individual patients and development of imaging biomarkers. This review provides a general overview of MRF technology, current preclinical and clinical applications and potential future directions. MRF has been initially evaluated in brain, prostate, liver, cardiac, musculoskeletal imaging, and measurement of perfusion and microvascular properties through MR vascular fingerprinting.

Deducing magnetic resonance neuroimages based on knowledge from samples

PURPOSE

Because individual variance always exists, using the same set of predetermined parameters for magnetic resonance imaging (MRI) may not be exactly suitable for each participant. We propose a knowledge-based method that can repair MRI data of undesired contrast as if a new scan were acquired using imaging parameters that had been individually optimized.

METHODS

The method employed a strategy called analogical reasoning to deduce voxel-wise relaxation properties using morphological and biological similarity. The proposed framework involves steps of intensity normalization, tissue segmentation, relaxation time deducing, and image deducing.

RESULTS

This approach has been preliminarily validated using conventional MRI data at 3T from several examples, including 5 normal and 9 clinical datasets. It can effectively improve the contrast of real MRI data by deducing imaging data using optimized imaging parameters based on deduced relaxation properties. The statistics of deduced images shows a high correlation with real data that were actually collected using the same set of imaging parameters.

CONCLUSION

The proposed method of deducing MRI data using knowledge of relaxation times alternatively provides a way of repairing MRI data of less optimal contrast. The method is also capable of optimizing an MRI protocol for individual participants, thereby realizing personalized MR imaging.

MR Fingerprinting of Adult Brain Tumors: Initial Experience

BACKGROUND AND PURPOSE

MR fingerprinting allows rapid simultaneous quantification of T1 and T2 relaxation times. This study assessed the utility of MR fingerprinting in differentiating common types of adult intra-axial brain tumors.

MATERIALS AND METHODS

MR fingerprinting acquisition was performed in 31 patients with untreated intra-axial brain tumors: 17 glioblastomas, 6 World Health Organization grade II lower grade gliomas, and 8 metastases. T1, T2 of the solid tumor, immediate peritumoral white matter, and contralateral white matter were summarized within each ROI. Statistical comparisons on mean, SD, skewness, and kurtosis were performed by using the univariate Wilcoxon rank sum test across various tumor types. Bonferroni correction was used to correct for multiple-comparison testing. Multivariable logistic regression analysis was performed for discrimination between glioblastomas and metastases, and area under the receiver operator curve was calculated.

RESULTS

Mean T2 values could differentiate solid tumor regions of lower grade gliomas from metastases (mean, 172 ± 53 ms, and 105 ± 27 ms, respectively; P = .004, significant after Bonferroni correction). The mean T1 of peritumoral white matter surrounding lower grade gliomas differed from peritumoral white matter around glioblastomas (mean, 1066 ± 218 ms, and 1578 ± 331 ms, respectively; P = .004, significant after Bonferroni correction). Logistic regression analysis revealed that the mean T2 of solid tumor offered the best separation between glioblastomas and metastases with an area under the curve of 0.86 (95% CI, 0.69-1.00; P < .0001).

CONCLUSIONS

MR fingerprinting allows rapid simultaneous T1 and T2 measurement in brain tumors and surrounding tissues. MR fingerprinting-based relaxometry can identify quantitative differences between solid tumor regions of lower grade gliomas and metastases and between peritumoral regions of glioblastomas and lower grade gliomas.

Clinical validation of synthetic brain MRI in children: initial experience

INTRODUCTION

The purpose of this study was to determine the diagnostic accuracy of synthetic MR sequences generated through post-acquisition processing of a single sequence measuring inherent R1, R2, and PD tissue properties compared with sequences acquired conventionally as part of a routine clinical pediatric brain MR exam.

METHODS

Thirty-two patients underwent routine clinical brain MRI with conventional and synthetic sequences acquired (22 abnormal). Synthetic axial T1, T2, and T2 fluid attenuation inversion recovery or proton density-weighted sequences were made to match the comparable clinical sequences. Two exams for each patient were de-identified. Four blinded reviewers reviewed eight patients and were asked to generate clinical reports on each exam (synthetic or conventional) at two different time points separated by a mean of 33 days. Exams were rated for overall and specific finding agreement (synthetic/conventional and compared to gold standard consensus review by two senior reviewers with knowledge of clinical report), quality, and diagnostic confidence.

RESULTS

Overall agreement between conventional and synthetic exams was 97%. Agreement with consensus readings was 84% (conventional) and 81% (synthetic), p = 0.61. There were no significant differences in sensitivity, specificity, or accuracy for specific imaging findings involving the ventricles, CSF, brain parenchyma, or vasculature between synthetic or conventional exams (p > 0.05). No significant difference in exam quality, diagnostic confidence, or noise/artifacts was noted comparing studies with synthetic or conventional sequences.

CONCLUSIONS

Diagnostic accuracy and quality of synthetically generated sequences are comparable to conventionally acquired sequences as part of a standard pediatric brain exam. Further confirmation in a larger study is warranted.

Imaging biobanks in oncology: European perspective

Imaging biobanks as defined by the European Society of Radiology are "organised databases of medical images, and associated imaging biomarkers (radiology and beyond), shared among multiple researchers, linked to other biorepositories". Oncologic imaging biobanks are developed mainly for research purposes. These biobanks may be developed in academic centers, or with the support of industry. The awareness of their importance is gradually increasing in the oncologic community. It is difficult to determine which oncologic domain of research will benefit from the implementation of imaging biobanks. One of the most foreseeable applications could be the correlation between imaging phenotype and genotype. For this reason imaging biobanks should be embedded in wider biobanks networks, as for example the European-based Biobanking and BioMolecular resources Research Infrastructure.

Reporting knee meniscal tears: technical aspects, typical pitfalls and how to avoid them

Magnetic resonance imaging (MRI) is the most accurate imaging technique in the diagnosis of meniscal lesions and represents a standard tool in knee evaluation. MRI plays a critical role in influencing the treatment decision and enables information that would obviate unnecessary surgery including diagnostic arthroscopy. An accurate interpretation of the knee depends on several factors, starting with technical aspects including radiofrequency coils, imaging protocol and magnetic field strength. The use of dedicated high-resolution orthopaedic coils with a different number of integrated elements is mandatory in order to ensure high homogeneity of the signal and high-resolution images. The clinical imaging protocol of the knee includes different MRI sequences with high-spatial resolution in all orientations: sagittal, coronal, and axial. Usually, the slice thickness is 3 mm or less, even with standard two-dimensional fast spin echo sequences. A common potential reason for pitfalls and errors of interpretation is the unawareness of the normal tibial attachments and capsular attachment of the menisci. Complete description of meniscal tears implies that the radiologist should be aware of the patterns and the complex classification of the lesions.

TEACHING POINTS

• Technical factors may influence MRI interpretation. • Unawareness of the normal meniscal anatomy may lead to errors of interpretation. • Description of meniscal tears implies the knowledge of meniscal tear classification.

MR Fingerprinting for Rapid Quantitative Abdominal Imaging

PURPOSE

To develop a magnetic resonance (MR) "fingerprinting" technique for quantitative abdominal imaging.

MATERIALS AND METHODS

This HIPAA-compliant study had institutional review board approval, and informed consent was obtained from all subjects. To achieve accurate quantification in the presence of marked B0 and B1 field inhomogeneities, the MR fingerprinting framework was extended by using a two-dimensional fast imaging with steady-state free precession, or FISP, acquisition and a Bloch-Siegert B1 mapping method. The accuracy of the proposed technique was validated by using agarose phantoms. Quantitative measurements were performed in eight asymptomatic subjects and in six patients with 20 focal liver lesions. A two-tailed Student t test was used to compare the T1 and T2 results in metastatic adenocarcinoma with those in surrounding liver parenchyma and healthy subjects.

RESULTS

Phantom experiments showed good agreement with standard methods in T1 and T2 after B1 correction. In vivo studies demonstrated that quantitative T1, T2, and B1 maps can be acquired within a breath hold of approximately 19 seconds. T1 and T2 measurements were compatible with those in the literature. Representative values included the following: liver, 745 msec ± 65 (standard deviation) and 31 msec ± 6; renal medulla, 1702 msec ± 205 and 60 msec ± 21; renal cortex, 1314 msec ± 77 and 47 msec ± 10; spleen, 1232 msec ± 92 and 60 msec ± 19; skeletal muscle, 1100 msec ± 59 and 44 msec ± 9; and fat, 253 msec ± 42 and 77 msec ± 16, respectively. T1 and T2 in metastatic adenocarcinoma were 1673 msec ± 331 and 43 msec ± 13, respectively, significantly different from surrounding liver parenchyma relaxation times of 840 msec ± 113 and 28 msec ± 3 (P < .0001 and P < .01) and those in hepatic parenchyma in healthy volunteers (745 msec ± 65 and 31 msec ± 6, P < .0001 and P = .021, respectively).

CONCLUSION

A rapid technique for quantitative abdominal imaging was developed that allows simultaneous quantification of multiple tissue properties within one 19-second breath hold, with measurements comparable to those in published literature.