Clinical Feasibility of Synthetic MRI in Multiple Sclerosis: A Diagnostic and Volumetric Validation Study

The effect of alemtuzumab on neurodegeneration in relapsing-remitting multiple sclerosis: A five-year prospective mono-center study

BACKGROUND

Relapsing-remitting multiple sclerosis (RRMS) is an inflammatory and neurodegenerative disease. After two or more short courses of alemtuzumab (ALZ), an immune reconstitution is achieved, which long-term results in reduced disease activity. We aimed to investigate the effect of ALZ on measures of neurodegeneration (i.e., brain atrophy, and retinal layer thinning).

METHODS

We designed an observational prospective mono-center study in RRMS patients initiating ALZ treatment. Patients were assessed at baseline (month 0) and thereafter annually for five years with clinical measures, synthetic magnetic resonance imaging (SyMRI) and optical coherence tomography (OCT), with a re-baseline SyMRI scan and an OCT exam 24 months after initiating ALZ. Persons with neurological symptoms but without evidence of neurological disease served as symptomatic controls (SCs, n = 27).

RESULTS

Forty-nine RRMS patients were included. Baseline median expanded disability status scale [2.0 (IQR 1.5)] was unchanged during follow-up, 71 % were progression-free, 33 % achieved no evidence of disease activity-3 (NEDA-3). Between baseline and month 60, SyMRI showed a reduction of brain parenchymal fraction (BPF) and grey matter (GM) volume in patients. The BPF reduction was greater in RRMS patients than in SCs (p < 0.05), and more pronounced in patients with high pre-baseline disease activity than in those without (p < 0.01). OCT showed significant thinning of macular ganglion cell and inner plexiform layers (mGCIPL) and in peripapillary retinal nerve fiber layer (pRNFL) in patients. In contrast, absolute values of white matter (WM) volume and myelin content (MyC) quantified by SyMRI, were stable or increased after re-baseline (month 24) and up to month 60, and this increase appeared limited to patients without high pre-baseline disease activity and to patients with NEDA-3 or disability worsening during follow-up. A strong positive correlation between WM volume and GM volume at baseline was lost after ALZ intervention for their delta values, i.e., change from re-baseline (month 24) to month 60. While the positive baseline correlation between WM volume and MyC increased for their delta values, the positive baseline correlation between GM volume and MyC changed to negative for their delta values.

CONCLUSION

We showed that neurodegeneration continued in RRMS patients under ALZ treatment, but it appeared to be limited to BPF and GM, and more pronounced in patients with disease activity. Our data suggest that patients who respond to ALZ treatment show signs of remyelination. OCT and SyMRI have potential to quantify measures of neurodegeneration that is affected by treatment intervention in RRMS.

Improving the lesion appearance on FLAIR images synthetized from quantitative MRI: a fast, hybrid approach

OBJECTIVE

The image quality of synthetized FLAIR (fluid attenuated inversion recovery) images is generally inferior to its conventional counterpart, especially regarding the lesion contrast mismatch. This work aimed to improve the lesion appearance through a hybrid methodology.

MATERIALS AND METHODS

We combined a full brain 5-min MR-STAT acquisition followed by FLAIR synthetization step with an ultra-under sampled conventional FLAIR sequence and performed the retrospective and prospective analysis of the proposed method on the patient datasets and a healthy volunteer.

RESULTS

All performance metrics of the proposed hybrid FLAIR images on patient datasets were significantly higher than those of the physics-based FLAIR images (p < 0.005), and comparable to those of conventional FLAIR images. The small difference between prospective and retrospective analysis on a healthy volunteer demonstrated the validity of the retrospective analysis of the hybrid method as presented for the patient datasets.

DISCUSSION

The proposed hybrid FLAIR achieved an improved lesion appearance in the clinical cases with neurological diseases compared to the physics-based FLAIR images, Future prospective work on patient data will address the validation of the method from a diagnostic perspective by radiological inspection of the new images over a larger patient cohort.

Ultrafast Brain MRI at 3 T for MS: Evaluation of a 51-Second Deep Learning-Enhanced T2-EPI-FLAIR Sequence

In neuroimaging, there is no equivalent alternative to magnetic resonance imaging (MRI). However, image acquisitions are generally time-consuming, which may limit utilization in some cases, e.g., in patients who cannot remain motionless for long or suffer from claustrophobia, or in the event of extensive waiting times. For multiple sclerosis (MS) patients, MRI plays a major role in drug therapy decision-making. The purpose of this study was to evaluate whether an ultrafast, T2-weighted (T2w), deep learning-enhanced (DL), echo-planar-imaging-based (EPI) fluid-attenuated inversion recovery (FLAIR) sequence (FLAIRUF) that has targeted neurological emergencies so far might even be an option to detect MS lesions of the brain compared to conventional FLAIR sequences. Therefore, 17 MS patients were enrolled prospectively in this exploratory study. Standard MRI protocols and ultrafast acquisitions were conducted at 3 tesla (T), including three-dimensional (3D)-FLAIR, turbo/fast spin-echo (TSE)-FLAIR, and FLAIRUF. Inflammatory lesions were grouped by size and location. Lesion conspicuity and image quality were rated on an ordinal five-point Likert scale, and lesion detection rates were calculated. Statistical analyses were performed to compare results. Altogether, 568 different lesions were found. Data indicated no significant differences in lesion detection (sensitivity and positive predictive value [PPV]) between FLAIRUF and axially reconstructed 3D-FLAIR (lesion size ≥3 mm × ≥2 mm) and no differences in sensitivity between FLAIRUF and TSE-FLAIR (lesion size ≥3 mm total). Lesion conspicuity in FLAIRUF was similar in all brain regions except for superior conspicuity in the occipital lobe and inferior conspicuity in the central brain regions. Further findings include location-dependent limitations of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as well as artifacts such as spatial distortions in FLAIRUF. In conclusion, FLAIRUF could potentially be an expedient alternative to conventional methods for brain imaging in MS patients since the acquisition can be performed in a fraction of time while maintaining good image quality.

Compressed SENSitivity Encoding (SENSE): Qualitative and Quantitative Analysis

BACKGROUND

This study aimed to qualitatively and quantitatively evaluate T1-TSE, T2-TSE and 3D FLAIR sequences obtained with and without Compressed-SENSE technique by assessing the contrast (C), the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR).

METHODS

A total of 142 MRI images were acquired: 69 with Compressed-SENSE and 73 without Compressed-SENSE. All the MRI images were contoured, spatially aligned and co-registered using 3D Slicer Software. Two radiologists manually drew 12 regions of interests on three different structures of CNS: white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF).

RESULTS

C values were significantly higher in Compressed-SENSE T1-TSE compared to No Compressed-SENSE T1-TSE for three different structures of the CNS. C values were also significantly lower for Compressed-SENSE 3D FLAIR and Compressed-SENSE T2-TSE compared to the corresponding No Compressed-SENSE scans. While CNR values did not significantly differ in GM-WM between Compressed-SENSE and No Compressed-SENSE for the 3D FLAIR and T1-TSE sequences, the differences in GM-CSF and WM-CSF were always statistically significant.

CONCLUSION

Compressed-SENSE for 3D T2 FLAIR, T1w and T2w sequences enables faster MRI acquisition, reducing scan time and maintaining equivalent image quality. Compressed-SENSE is very useful in specific medical conditions where lower SAR levels are required without sacrificing the acquisition of helpful diagnostic sequences.

Evaluating age-and gender-related changes in brain volumes in normal adult using synthetic magnetic resonance imaging

OBJECTIVE

Normal aging is associated with brain volume change, and brain segmentation can be performed within an acceptable scan time using synthetic magnetic resonance imaging (MRI). This study aimed to investigate the brain volume changes in healthy adult according to age and gender, and provide age- and gender-specific reference values using synthetic MRI.

METHODS

A total of 300 healthy adults (141 males, median age 48; 159 females, median age 50) were underwent synthetic MRI on 3.0 T. Brain parenchymal volume (BPV), gray matter volume (GMV), white matter volume (WMV), myelin volume (MYV), and cerebrospinal fluid volume (CSFV) were calculated using synthetic MRI software. These volumes were normalized by intracranial volume to normalized GMV (nGMV), normalized WMV (nWMV), normalized MYV (nMYV), normalized BPV (nBPV), and normalized CSFV (nCSFV). The normalized brain volumes were plotted against age in both males and females, and a curve fitting model that best explained the age dependence of brain volume was identified. The normalized brain volumes were compared between different age and gender groups.

RESULTS

The approximate curves of nGMV, nWMV, nCSFV, nBPV, and nMYV were best fitted by quadratic curves. The nBPV decreased monotonously through all ages in both males and females, while the changes of nCSFV showed the opposite trend. The nWMV and nMYV in both males and females increased gradually and then decrease with age. In early adulthood (20s), nWMV and nMYV in males were lower and peaked later than that in females (p < .005). The nGMV in both males and females decreased in the early adulthood until the 30s and then remains stable. A significant decline in nWMV, nBPV, and nMYV was noted in the 60s (Turkey test, p < .05).

CONCLUSIONS

Our study provides age- and gender-specific reference values of brain volumes using synthetic MRI, which could be objective tools for discriminating brain disorders from healthy brains.

Gray matter volume in women with the BRCA mutation with and without ovarian removal: evidence for increased risk of late-life Alzheimer's disease or dementia

OBJECTIVE

Ovarian removal prior to spontaneous/natural menopause (SM) is associated with increased risk of late life dementias including Alzheimer's disease. This increased risk may be related to the sudden and early loss of endogenous estradiol. Women with breast cancer gene mutations (BRCAm) are counseled to undergo oophorectomy prior to SM to significantly reduce their risk of developing breast, ovarian, and cervical cancers. There is limited evidence of the neurological effects of ovarian removal prior to the age of SM showing women without the BRCAm had cortical thinning in medial temporal lobe structures. A second study in women with BRCAm and bilateral salpingo-oophorectomy (BSO) noted changes in cognition.

METHODS

The present, cross-sectional study examined whole-brain differences in gray matter (GM) volume using high-resolution, quantitative magnetic resonance imaging in women with BRCAm and intact ovaries (BRCA-preBSO [study cohort with BRCA mutation prior to oophorectomy]; n = 9) and after surgery with (BSO + estradiol-based therapy [ERT]; n = 10) and without (BSO; n = 10) postsurgical estradiol hormone therapy compared with age-matched women (age-matched controls; n = 10) with their ovaries.

RESULTS

The BRCA-preBSO and BSO groups showed significantly lower GM volume in the left medial temporal and frontal lobe structures. BSO + ERT exhibited few areas of lower GM volume compared with age-matched controls. Novel to this study, we also observed that all three BRCAm groups exhibited significantly higher GM volume compared with age-matched controls, suggesting continued plasticity.

CONCLUSIONS

The present study provides evidence, through lower GM volume, to support both the possibility that the BRCAm, alone, and early life BSO may play a role in increasing the risk for late-life dementia. At least for BRCAm with BSO, postsurgical ERT seems to ameliorate GM losses.

The value of synthetic MRI in detecting the brain changes and hearing impairment of children with sensorineural hearing loss

Introduction

Sensorineural hearing loss (SNHL) can arise from a diverse range of congenital and acquired factors. Detecting it early is pivotal for nurturing speech, language, and cognitive development in children with SNHL. In our study, we utilized synthetic magnetic resonance imaging (SyMRI) to assess alterations in both gray and white matter within the brains of children affected by SNHL.

Methods

The study encompassed both children diagnosed with SNHL and a control group of children with normal hearing {1.5-month-olds (n = 52) and 3-month-olds (n = 78)}. Participants were categorized based on their auditory brainstem response (ABR) threshold, delineated into normal, mild, moderate, and severe subgroups.Clinical parameters were included and assessed the correlation with SNHL. Quantitative analysis of brain morphology was conducted using SyMRI scans, yielding data on brain segmentation and relaxation time.Through both univariate and multivariate analyses, independent factors predictive of SNHL were identified. The efficacy of the prediction model was evaluated using receiver operating characteristic (ROC) curves, with visualization facilitated through the utilization of a nomogram. It's important to note that due to the constraints of our research, we worked with a relatively small sample size.

Results

Neonatal hyperbilirubinemia (NH) and children with inner ear malformation (IEM) were associated with the onset of SNHL both at 1.5 and 3-month groups. At 3-month group, the moderate and severe subgroups exhibited elevated quantitative T1 values in the inferior colliculus (IC), lateral lemniscus (LL), and middle cerebellar peduncle (MCP) compared to the normal group. Additionally, WMV, WMF, MYF, and MYV were significantly reduced relative to the normal group. Additionally, SNHL-children with IEM had high T1 values in IC, and LL and reduced WMV, WMF, MYV and MYF values as compared with SNHL-children without IEM at 3-month group. LL-T1 and WMF were independent risk factors associated with SNHL. Consequently, a prediction model was devised based on LL-T1 and WMF. ROC for training set, validation set and external set were 0.865, 0.806, and 0.736, respectively.

Conclusion

The integration of T1 quantitative values and brain volume segmentation offers a valuable tool for tracking brain development in children affected by SNHL and assessing the progression of the condition's severity.

Generalizable synthetic MRI with physics-informed convolutional networks

BACKGROUND

Magnetic resonance imaging (MRI) provides state-of-the-art image quality for neuroimaging, consisting of multiple separately acquired contrasts. Synthetic MRI aims to accelerate examinations by synthesizing any desirable contrast from a single acquisition.

PURPOSE

We developed a physics-informed deep learning-based method to synthesize multiple brain MRI contrasts from a single 5-min acquisition and investigate its ability to generalize to arbitrary contrasts.

METHODS

A dataset of 55 subjects acquired with a clinical MRI protocol and a 5-min transient-state sequence was used. The model, based on a generative adversarial network, maps data acquired from the five-minute scan to "effective" quantitative parameter maps (q*-maps), feeding the generated PD, T1, and T2 maps into a signal model to synthesize four clinical contrasts (proton density-weighted, T1-weighted, T2-weighted, and T2-weighted fluid-attenuated inversion recovery), from which losses are computed. The synthetic contrasts are compared to an end-to-end deep learning-based method proposed by literature. The generalizability of the proposed method is investigated for five volunteers by synthesizing three contrasts unseen during training and comparing these to ground truth acquisitions via qualitative assessment and contrast-to-noise ratio (CNR) assessment.

RESULTS

The physics-informed method matched the quality of the end-to-end method for the four standard contrasts, with structural similarity metrics above0.75 ± 0.08 $0.75\pm 0.08$ ( ± $\pm$ std), peak signal-to-noise ratios above22.4 ± 1.9 $22.4\pm 1.9$ , representing a portion of compact lesions comparable to standard MRI. Additionally, the physics-informed method enabled contrast adjustment, and similar signal contrast and comparable CNRs to the ground truth acquisitions for three sequences unseen during model training.

CONCLUSIONS

The study demonstrated the feasibility of physics-informed, deep learning-based synthetic MRI to generate high-quality contrasts and generalize to contrasts beyond the training data. This technology has the potential to accelerate neuroimaging protocols.

Quantitative evaluation of meniscus injury using synthetic magnetic resonance imaging

BACKGROUND

Magnetic resonance imaging (MRI) can diagnose meniscal lesions anatomically, while quantitative MRI can reflect the changes of meniscal histology and biochemical structure. Our study aims to explore the association between the measurement values obtained from synthetic magnetic resonance imaging (SyMRI) and Stoller grades. Additionally, we aim to assess the diagnostic accuracy of SyMRI in determining the extent of meniscus injury. This potential accuracy could contribute to minimizing unnecessary invasive examinations and providing guidance for clinical treatment.

METHODS

Total of 60 (n=60) patients requiring knee arthroscopic surgery and 20 (n=20) healthy subjects were collected from July 2022 to November 2022. All subjects underwent conventional MRI and SyMRI. Manual measurements of the T1, T2 and proton density (PD) values were conducted for both normal menisci and the most severely affected position of injured menisci. These measurements corresponded to the Stoller grade of meniscus injuries observed in the conventional MRI. All patients and healthy subjects were divided into normal group, degeneration group and torn group according to the Stoller grade on conventional MRI. One-way analysis of variance (ANOVA) was employed to compare the T1, T2 and PD values of the meniscus among 3 groups. The accuracy of SyMRI in diagnosing meniscus injury was assessed by comparing the findings with arthroscopic observations. The diagnostic efficiency of meniscus degeneration and tear between conventional MRI and SyMRI were analyzed using McNemar test. Furthermore, a receiver operating characteristic curve (ROC curve) was constructed and the area under the curve (AUC) was utilized for evaluation.

RESULTS

According to the measurements of SyMRI, there was no statistical difference of T1 value or PD value measured by SyMRI among the normal group, degeneration group and torn group, while the difference of T2 value was statistically significant among 3 groups (P=0.001). The arthroscopic findings showed that 11 patients were meniscal degeneration and 49 patients were meniscal tears. The arthroscopic findings were used as the gold standard, and the difference of T1 and PD values among the 3 groups was not statistically significant, while the difference of T2 values (32.81±2.51 of normal group, 44.85±3.98 of degeneration group and 54.42±3.82 of torn group) was statistically significant (P=0.001). When the threshold of T2 value was 51.67 (ms), the maximum Yoden index was 0.787 and the AUC value was 0.934.

CONCLUSIONS

The measurement values derived from SyMRI could reflect the Stoller grade, illustrating that SyMRI has good consistency with conventional MRI. Moreover, the notable consistency observed between SyMRI and arthroscopy suggests a potential role for SyMRI in guiding clinical diagnoses.

Automatic estimation of brain parenchymal fraction in patients with multple sclerosis: a comparison between synthetic MRI and an established automated brain segmentation software based on FSL

PURPOSE

We aimed to validate the estimation of the brain parenchymal fraction (BPF) in patients with multiple sclerosis (MS) using synthetic magnetic resonance imaging (SyMRI) by comparison with software tools of the FMRIB Software Library (FSL). In addition to a cross-sectional method comparison, longitudinal volume changes were assessed to further elucidate the suitability of SyMRI for quantification of disease-specific changes.

METHODS

MRI data from 216 patients with MS and 28 control participants were included for volume estimation by SyMRI and FSL-SIENAX. Moreover, longitudinal data from 35 patients with MS were used to compare registration-based percentage brain volume changes estimated using FSL-SIENA to difference-based calculations of volume changes using SyMRI.

RESULTS

We observed strong correlations of estimated brain volumes between the two methods. While SyMRI overestimated grey matter and BPF compared to FSL-SIENAX, indicating a systematic bias, there was excellent agreement according to intra-class correlation coefficients for grey matter and good agreement for BPF and white matter. Bland-Altman plots suggested that the inter-method differences in BPF were smaller in patients with brain atrophy compared to those without atrophy. Longitudinal analyses revealed a tendency for higher atrophy rates for SyMRI than for SIENA, but SyMRI had a robust correlation and a good agreement with SIENA.

CONCLUSION

In summary, BPF based on data from SyMRI and FSL-SIENAX is not directly transferable because an overestimation and higher variability of SyMRI values were observed. However, the consistency and correlations between the two methods were satisfactory, and SyMRI was suitable to quantify disease-specific atrophy in MS.

High-fidelity direct contrast synthesis from magnetic resonance fingerprinting

PURPOSE

This work was aimed at proposing a supervised learning-based method that directly synthesizes contrast-weighted images from the Magnetic Resonance Fingerprinting (MRF) data without performing quantitative mapping and spin-dynamics simulations.

METHODS

To implement our direct contrast synthesis (DCS) method, we deploy a conditional generative adversarial network (GAN) framework with a multi-branch U-Net as the generator and a multilayer CNN (PatchGAN) as the discriminator. We refer to our proposed approach as N-DCSNet. The input MRF data are used to directly synthesize T1-weighted, T2-weighted, and fluid-attenuated inversion recovery (FLAIR) images through supervised training on paired MRF and target spin echo-based contrast-weighted scans. The performance of our proposed method is demonstrated on in vivo MRF scans from healthy volunteers. Quantitative metrics, including normalized root mean square error (nRMSE), peak signal-to-noise ratio (PSNR), structural similarity (SSIM), learned perceptual image patch similarity (LPIPS), and Fréchet inception distance (FID), were used to evaluate the performance of the proposed method and compare it with others.

RESULTS

In-vivo experiments demonstrated excellent image quality with respect to that of simulation-based contrast synthesis and previous DCS methods, both visually and according to quantitative metrics. We also demonstrate cases in which our trained model is able to mitigate the in-flow and spiral off-resonance artifacts typically seen in MRF reconstructions, and thus more faithfully represent conventional spin echo-based contrast-weighted images.

CONCLUSION

We present N-DCSNet to directly synthesize high-fidelity multicontrast MR images from a single MRF acquisition. This method can significantly decrease examination time. By directly training a network to generate contrast-weighted images, our method does not require any model-based simulation and therefore can avoid reconstruction errors due to dictionary matching and contrast simulation (code available at:https://github.com/mikgroup/DCSNet).

Direct synthesis of multi-contrast brain MR images from MR multitasking spatial factors using deep learning

PURPOSE

To develop a deep learning method to synthesize conventional contrast-weighted images in the brain from MR multitasking spatial factors.

METHODS

Eighteen subjects were imaged using a whole-brain quantitative T1 -T2 -T1ρ MR multitasking sequence. Conventional contrast-weighted images consisting of T1 MPRAGE, T1 gradient echo, and T2 fluid-attenuated inversion recovery were acquired as target images. A 2D U-Net-based neural network was trained to synthesize conventional weighted images from MR multitasking spatial factors. Quantitative assessment and image quality rating by two radiologists were performed to evaluate the quality of deep-learning-based synthesis, in comparison with Bloch-equation-based synthesis from MR multitasking quantitative maps.

RESULTS

The deep-learning synthetic images showed comparable contrasts of brain tissues with the reference images from true acquisitions and were substantially better than the Bloch-equation-based synthesis results. Averaging on the three contrasts, the deep learning synthesis achieved normalized root mean square error = 0.184 ± 0.075, peak SNR = 28.14 ± 2.51, and structural-similarity index = 0.918 ± 0.034, which were significantly better than Bloch-equation-based synthesis (p < 0.05). Radiologists' rating results show that compared with true acquisitions, deep learning synthesis had no notable quality degradation and was better than Bloch-equation-based synthesis.

CONCLUSION

A deep learning technique was developed to synthesize conventional weighted images from MR multitasking spatial factors in the brain, enabling the simultaneous acquisition of multiparametric quantitative maps and clinical contrast-weighted images in a single scan.

Synthetic MRI plus FSE-PROPELLER DWI for differentiating malignant from benign head and neck tumors: a preliminary study

Background

Preoperative classification of head and neck (HN) tumors remains challenging, especially distinguishing early cancerogenic masses from benign lesions. Synthetic MRI offers a new way for quantitative analysis of tumors. The present study investigated the application of synthetic MRI and stimulus and fast spin echo diffusion-weighted imaging with periodically rotated overlapping parallel lines with enhanced reconstruction (FSE-PROPELLER DWI) to differentiate malignant from benign HN tumors.

Materials and methods

Forty-eight patients with pathologically confirmed HN tumors were retrospectively recruited between August 2022 and October 2022. The patients were divided into malignant (n = 28) and benign (n = 20) groups. All patients were scanned using synthetic MRI and FSE-PROPELLER DWI. T1, T2, and proton density (PD) values were acquired on the synthetic MRI and ADC values on the FSE-PROPELLER DWI.

Results

Benign tumors (ADC: 2.03 ± 0.31 × 10-3 mm2/s, T1: 1741.13 ± 662.64 ms, T2: 157.43 ± 72.23 ms) showed higher ADC, T1, and T2 values compared to malignant tumors (ADC: 1.46 ± 0.37 × 10-3 mm2/s, T1: 1390.06 ± 241.09 ms, T2: 97.64 ± 14.91 ms) (all P<0.05), while no differences were seen for PD values. ROC analysis showed that T2+ADC (cut-off value, > 0.55; AUC, 0.950) had optimal diagnostic performance vs. T1 (cut-off value, ≤ 1675.84 ms; AUC, 0.698), T2 (cut-off value, ≤ 113.24 ms; AUC, 0.855) and PD (cut off value, > 80.67 pu; AUC, 0.568) alone in differentiating malignant from benign lesions (all P<0.05); yet, the difference in AUC between ADC and T2+ADC or T2 did not reach statistical significance.

Conclusion

Synthetic MRI and FSE-PROPELLER DWI can quantitatively differentiate malignant from benign HN tumors. T2 value is comparable to ADC value, and T2+ADC values could improve diagnostic efficacy., apparent diffusion coeffificient, head and neck tumors.

[Usefulness of Voxel-Based Quantification (VBQ) Smoothing in Relaxation Time Mapping]

PURPOSE

Voxel-based quantification (VBQ) smoothing is a technique used to smooth quantitative parametric maps in the Montreal Neurological Institute standard space. Although VBQ smoothing could suppress changes in quantitative values at tissue boundaries, its effectiveness on relaxation time (T1 and T2 values and proton density PD) maps has not been investigated. The purpose of this study was to clarify the usefulness of VBQ smoothing in relaxation time mapping.

METHOD

T1 and T2 values and PD maps of the brains of 20 healthy participants were obtained using a two-dimensional multi-dynamic multi-echo sequence. VBQ and Gaussian smoothing were applied to the relaxation time maps by varying the kernel size by 1 mm from 1 to 6 mm. Changes in relaxation time before and after VBQ and Gaussian smoothing for the putamen, caudate nucleus, substantia nigra, and corpus callosum on the relaxation time maps were evaluated.

RESULT

The changes in relaxation time after VBQ smoothing application were smaller than those in that after Gaussian smoothing application. Although the differences in the relaxation time for all tissues before and after VBQ and Gaussian smoothing applications increased with increasing kernel size for all relaxation times for both methods, the changes in the relaxation time for VBQ smoothing were smaller than those in that for Gaussian smoothing.

CONCLUSION

VBQ smoothing can suppress the change in the relaxation time on the boundary of the tissue and is thus a useful smoothing technique in relaxation time mapping.

Accuracy of skull stripping in a single-contrast convolutional neural network model using eight-contrast magnetic resonance images

In automated analyses of brain morphometry, skull stripping or brain extraction is a critical first step because it provides accurate spatial registration and signal-intensity normalization. Therefore, it is imperative to develop an ideal skull-stripping method in the field of brain image analysis. Previous reports have shown that convolutional neural network (CNN) method is better at skull stripping than non-CNN methods. We aimed to evaluate the accuracy of skull stripping in a single-contrast CNN model using eight-contrast magnetic resonance (MR) images. A total of 12 healthy participants and 12 patients with a clinical diagnosis of unilateral Sturge-Weber syndrome were included in our study. A 3-T MR imaging system and QRAPMASTER were used for data acquisition. We obtained eight-contrast images produced by post-processing T1, T2, and proton density (PD) maps. To evaluate the accuracy of skull stripping in our CNN method, gold-standard intracranial volume (ICVG) masks were used to train the CNN model. The ICVG masks were defined by experts using manual tracing. The accuracy of the intracranial volume obtained from the single-contrast CNN model (ICVE) was evaluated using the Dice similarity coefficient [= 2(ICVE ⋂ ICVG)/(ICVE + ICVG)]. Our study showed significantly higher accuracy in the PD-weighted image (WI), phase-sensitive inversion recovery (PSIR), and PD-short tau inversion recovery (STIR) compared to the other three contrast images (T1-WI, T2-fluid-attenuated inversion recovery [FLAIR], and T1-FLAIR). In conclusion, PD-WI, PSIR, and PD-STIR should be used instead of T1-WI for skull stripping in the CNN models.

Potential clinical feasibility of synthetic MRI in bladder tumors: a comparative study with conventional MRI

Background

Synthetic magnetic resonance imaging (MRI) can provide quantitative information about inherent tissue properties and synthesize tailored contrast-weighted images simultaneously in a single scan. This study aimed to investigate the clinical feasibility of synthetic MRI in bladder tumors.

Methods

A total of 47 patients (37 males; mean age: 66±10 years old) with postoperative pathology-confirmed papillary urothelial neoplasms of the bladder were enrolled in this retrospective study. A 2-dimensional (2D) multi-dynamic multi-echo pulse sequence was performed for synthetic MRI at 3T. The overall image quality, lesion conspicuity, contrast resolution, resolution of subtle anatomic structures, motion artifact, blurring, and graininess of images were subjectively evaluated by 2 radiologists independently using a 5-point Likert scale for qualitative analysis. The signal intensity ratio (SIR), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured for quantitative analysis. Linear weighted Kappa, Wilcoxon's signed-rank test, and the Mann-Whitney U-test were used for statistical analysis.

Results

The interobserver consistency was excellent (κ values: 0.607-1). Synthetic T1-weighted (syn-T1w) and synthetic T2-weighted (syn-T2w) images obtained scores of 4 in most subjective terms, which were relatively smaller than those of conventional images. The SIR and SNR of syn-T1w were significantly higher than those of con-T1w images (SIR 2.37±0.86 vs. 1.47±0.20, P<0.001; SNR 21.83±9.43 vs. 14.81±3.30, P<0.001). No difference was found in SIR between syn-T2w and conventional T2-weighted (con-T2w) images, whereas the SNR of the syn-T2w was significantly lower (8.79±4.06 vs. 26.49±6.80, P<0.001). Additionally, the CNR of synthetic images was significantly lower than that of conventional images (T1w 1.41±0.72 vs. 2.68±1.04; T2w 1.40±0.87 vs. 4.03±1.55, all P<0.001).

Conclusions

Synthetic MRI generates morphologic magnetic resonance (MR) images with diagnostically acceptable image quality in bladder tumors, especially T1-weighted images with high image contrast of tumors relative to urine. Further technological improvements are needed for synthetic MRI to reduce noise. Combined with T1, T2, and proton density (PD) quantitative data, synthetic MRI has potential for clinical application in bladder tumors.

The advantages of the magnetic resonance image compilation (MAGiC) method for the prognosis of neonatal hypoglycemic encephalopathy

Objectives

To explore the prognostic value of magnetic resonance image compilation (MAGiC) in the quantitative assessment of neonatal hypoglycemic encephalopathy (HE).

Methods

A total of 75 neonatal HE patients who underwent synthetic MRI were included in this retrospective study. Perinatal clinical data were collected. T1, T2 and proton density (PD) values were measured in the white matter of the frontal lobe, parietal lobe, temporal lobe and occipital lobe, centrum semiovale, periventricular white matter, thalamus, lenticular nucleus, caudate nucleus, corpus callosum and cerebellum, which were generated by MAGiC. The patients were divided into two groups (group A: normal and mild developmental disability; group B: severe developmental disability) according to the score of Bayley Scales of Infant Development (Bayley III) at 9-12 months of age. Student's t test, Wilcoxon test, and Fisher's test were performed to compare data across the two groups. Multivariate logistic regression was used to identify the predictors of poor prognosis, and receiver operating characteristic (ROC) curves were created to evaluate the diagnostic accuracy.

Results

T1 and T2 values of the parietal lobe, occipital lobe, center semiovale, periventricular white matter, thalamus, and corpus callosum were higher in group B than in group A (p < 0.05). PD values of the occipital lobe, center semiovale, thalamus, and corpus callosum were higher in group B than in group A (p < 0.05). Multivariate logistic regression analysis showed that the duration of hypoglycemia, neonatal behavioral neurological assessment (NBNA) scores, T1 and T2 values of the occipital lobe, and T1 values of the corpus callosum and thalamus were independent predictors of severe HE (OR > 1, p < 0.05). The T2 values of the occipital lobe showed the best diagnostic performance, with an AUC value of 0.844, sensitivity of 83.02%, and specificity of 88.16%. Furthermore, the combination of MAGiC quantitative values and perinatal clinical features can improve the AUC (AUC = 0.923) compared with the use of MAGiC or perinatal clinical features alone.

Conclusion

The quantitative values of MAGiC can predict the prognosis of HE early, and the prediction efficiency is further optimized after being combined with clinical features.

[Evaluation of the Accuracy of Relaxation Time Measurements Using 3D-QALAS at 3.0 T MRI and Comparison with 2D-MDME]

PURPOSE

Three-dimensional (3D) quantification using an interleaved Look-Locker acquisition sequence with a T₂ preparation pulse (QALAS) is a quantitative sequence used to measure relaxation times. The accuracy of the relaxation time measurement of 3D-QALAS at 3.0 T and the bias of 3D-QALAS have not yet been assessed. The purpose of this study was to clarify the accuracy of the relaxation time measurements using 3D-QALAS at 3.0 T MRI.

METHODS

The accuracy of the T₁ and T₂ values for 3D-QALAS was evaluated using a phantom. Subsequently, the T₁ and T₂ values and proton density of the brain parenchyma in healthy subjects were measured using 3D-QALAS and compared with those of 2D multi-dynamic multi-echo (MDME).

RESULTS

In the phantom study, the average T₁ value of 3D-QALAS was 8.3% prolonged than that for conventional inversion recovery spin-echo; the average T₂ value for 3D-QALAS was 18.4% shorter than that for multi-echo spin-echo. The in vivo assessment showed that the mean T₁ and T₂ values and PD for 3D-QALAS were prolonged by 5.3%, shortened by 9.6%, and increased by 7.0%, respectively, compared with those for 2D-MDME.

CONCLUSION

Although 3D-QALAS at 3.0 T has high accuracy T₁ value, which is less than 1000 ms, the T₁ value could be overestimated for tissues with it longer than that T₁ value. The T₂ value for 3D-QALAS could be underestimated for tissues with T₂ values, and this tendency increases with longer T₂ values.

Application of magnetic resonance image compilation (MAGiC) in the diagnosis of middle-aged and elderly women with osteoporosis

OBJECTIVE

To investigate the feasibility of diagnosing osteoporosis (OP) in women through magnetic resonance image compilation (MAGiC).

METHODS

A total of 110 patients who underwent lumbar magnetic resonance imaging and dual X-ray absorptiometry examinations were collected and divided into two groups according bone mineral density: osteoporotic group (OP) and non-osteoporotic group (non-OP). The variation trends of T1 (longitudinal relaxation time), T2 (transverse relaxation time) and BMD (bone mineral density) with the increase of age, and the correlation of T1 and T2 with BMD were examined by establishing a clinical mathematical model.

RESULTS

With the increase of age, BMD and T1 value decreased gradually, while T2 value increased. T1 and T2 had statistical significance in diagnosing OP (P < 0.001), and there is moderate positive correlation between T1 and BMD values (R = 0.636, P < 0.001), while moderate negative correlation between T2 and BMD values (R=-0.694, P < 0.001). Receiver characteristic curve test showed that T1 and T2 had high accuracy in diagnosing OP (T1 AUC = 0.982, T2 AUC = 0.978), and the critical values of T1 and T2 for evaluating osteoporosis were 0.625s and 0.095s, respectively. Besides, the combined utilization of T1 and T2 had higher diagnostic efficiency (AUC = 0.985). Combined T1 and T2 had higher diagnostic efficiency (AUC = 0.985). Function fitting results of OP group: BMD=-0.0037* age - 0.0015*T1 + 0.0037*T2 + 0.86, sum of squared error (SSE) = 0.0392, and non-OP group: BMD = 0.0024* age - 0.0071*T1 + 0.0007*T2 + 1.41, SSE = 0.1007.

CONCLUSION

T1 and T2 value of MAGiC have high efficiency in diagnosing OP by establishing a function fitting formula of BMD with T1, T2 and age.

Reliability of spinal cord measures based on synthetic T1-weighted MRI derived from multiparametric mapping (MPM)

Short MRI acquisition time, high signal-to-noise ratio, and high reliability are crucial for image quality when scanning healthy volunteers and patients. Cross-sectional cervical cord area (CSA) has been suggested as a marker of neurodegeneration and potential outcome measure in clinical trials and is conventionally measured on T₁-weigthed 3D Magnetization Prepared Rapid Acquisition Gradient-Echo (MPRAGE) images. This study aims to reduce the acquisition time for the comprehensive assessment of the spinal cord, which is typically based on MPRAGE for morphometry and multi-parameter mapping (MPM) for microstructure. The MPRAGE is replaced by a synthetic T₁-w MRI (synT₁-w) estimated from the MPM, in order to measure CSA. SynT₁-w images were reconstructed using the MPRAGE signal equation based on quantitative maps of proton density (PD), longitudinal (R₁) and effective transverse (R₂*) relaxation rates. The reliability of CSA measurements from synT₁-w images was determined within a multi-center test-retest study format and validated against acquired MPRAGE scans by assessing the agreement between both methods. The response to pathological changes was tested by longitudinally measuring spinal cord atrophy following spinal cord injury (SCI) for synT₁-w and MPRAGE using linear mixed effect models. CSA measurements based on the synT₁-w MRI showed high intra-site (Coefficient of variation [CoV]: 1.43% to 2.71%) and inter-site repeatability (CoV: 2.90% to 5.76%), and only a minor deviation of -1.65 mm² compared to MPRAGE. Crucially, by assessing atrophy rates and by comparing SCI patients with healthy controls longitudinally, differences between synT₁-w and MPRAGE were negligible. These results demonstrate that reliable estimates of CSA can be obtained from synT₁-w images, thereby reducing scan time significantly.

Image quality using synthetic brain MRI: an age-stratified study

BACKGROUND

Synthetic magnetic resonance imaging (MRI) might replace the conventional MR sequences in brain evaluation to shorten scan time and obtain multiple quantitative parameters.

PURPOSE

To evaluate the image quality of multiple-delay-multiple-echo (MDME) sequence-derived synthetic brain MR images compared to conventional images by considering a multi-age sample.

MATERIAL AND METHODS

Image sets of conventional and synthetic MRI of 200 participants were included. On the basis of the presence of intracranial lesions, the participants were divided into a normal group and a pathological group. Two neuroradiologists compared the anonymous and unordered images. Image quality, artifacts, and diagnostic performance were analyzed.

RESULTS

In the quantitative analysis, comparing with conventional images, MDME sequence-derived synthetic MRI demonstrated an equal/greater signal-to-noise ratio and contrast-to-noise ratio (CNR) in all age groups. Specifically, for participants aged ≤2 years, synthetic T2-fluid-attenuated inversion recovery imaging showed a significantly higher cerebellum gray/white matter CNR (P < 0.05). In the qualitative and artifact analyses, except for the superior sagittal sinus and cranial nerves, synthetic MRI showed good imaging quality (≥3 points) in all brain structures. On synthetic T1-weighted imaging, high signal intensity within the superior sagittal sinus was found in most of our participants (107/118, 90.7%). No difference was observed between synthetic and conventional MRI in diagnosing the lesions.

CONCLUSION

MDME sequence-derived synthetic MRI showed similar image quality and diagnostic performance with a shorter acquisition time than conventional MRI. However, the high signal intensity within the superior sagittal sinus on synthetic T1-weighted images requires consideration.

Improved visualization of the subthalamic nucleus on synthetic MRI with optimized parameters: initial study

BACKGROUND

Synthetic magnetic resonance imaging (SyMRI) enables to reformat various images by adjusting the MR parameters.

PURPOSE

To investigate whether customization of the repetition time (TR), echo time (TE), and inversion time (TI) in SyMRI could improve the visualization of subthalamic nucleus (STN).

MATERIAL AND METHODS

We examined five healthy volunteers using both coronal SyMRI and quantitative susceptibility mapping (QSM), seven patients with Parkinson's disease (PD) using coronal SyMRI, and 15 patients with PD using coronal QSM. Two neuroradiologists reformatted SyMRI (optimized SyMRI) by adjusting TR, TE, and TI to achieve maximum tissue contrast between the STN and the adjacent brain parenchyma. The optimized MR parameters in the PD patients varied according to the individual. For regular SyMRI (T2-weighted imaging [T2WI] and STIR), optimized SyMRI, and QSM, qualitative visualization scores of the STN (STN score) were recorded. The contrast-to-noise ratio (CNR) of the STN was also measured.

RESULTS

For the STN scores in both groups, the optimized SyMRI were significantly higher than the regular SyMRI (P < 0.05), and there were no significant differences between optimized SyMRI and QSM. For the CNR of differentiation of the STN from the substantia nigra, the optimized SyMRI was higher than the regular SyMRI (volunteer: T2WI P = 0.10 and STIR P = 0.26; PD patient: T2WI P = 0.43 and STIR P = 0.25), but the optimized SyMRI was lower than the QSM (volunteer: P = 0.26; PD patient: P = 0.03).

CONCLUSIONS

On SyMRI, optimization of MR parameters (TR, TE, and TI) on an individual basis may be useful to increase the conspicuity of the STN.

Clinical Feasibility of Automated Brain Tissue and Myelin Volumetry of Normal Brian Using Synthetic Magnetic Resonance Imaging With Fast Imaging Protocol: A Single-Center Pilot Study

OBJECTIVE

This study aimed to investigate the clinical feasibility of synthetic magnetic resonance imaging (MRI) with fast imaging protocol for automated brain tissue and myelin volumetry in healthy volunteers at 3.0-T MRI.

METHODS

Thirty-four healthy volunteers were scanned using synthetic MRI with 3 sets of scan parameters: groups Fast (FAS; 2 minutes, 29 seconds), Routine (ROU; 4 minutes, 7 seconds), and Research (RES; 7 minutes, 46 seconds). White matter (WM), gray matter (GM), cerebrospinal fluid (CSF), non-WM/GM/CSF (NoN), brain parenchymal volume (BPV), intracranial volume (ICV), and myelin volume (MYV) were compared between 3 groups. Linear correlation analysis was performed for measured volumes of groups FAS and ROU versus group RES.

RESULTS

Significant differences were found in all the measured brain tissue volumes between groups FAS and ROU (P < 0.001), FAS and RES (P < 0.05), and ROU and RES (P < 0.05), except for NoN between groups ROU and RES (P = 0.0673), ICV between groups FAS and ROU (P = 0.2552), and ICV between groups FAS and RES (P = 0.4898). The intergroup coefficients of variation were 4.36% for WM, 6.39% for GM, 10.14% for CSF, 67.5% for NoN, 1.21% for BPV, 0.08% for ICV, and 5.88% for MYV. Strong linear correlation was demonstrated for WM, GM, CSF, BPV, ICV, and MYV (R = 0.9230-1.131) between FAS versus RES, and ROU versus RES.

CONCLUSIONS

Using synthetic MRI with fast imaging protocol can change the measured brain tissue volumes of volunteers. It is necessary to use consistent acquisition protocols for comparing or following up cases quantitatively.

Quantitative association of cerebral blood flow, relaxation times and proton density in young and middle-aged primary insomnia patients: A prospective study using three-dimensional arterial spin labeling and synthetic magnetic resonance imaging

Objectives

To quantitatively measure the T1 value, T2 value, proton density (PD) value, and cerebral blood flow (CBF) in young and middle-aged primary insomnia (PI) patients, and analyze the correlations between relaxation times, PD, and CBF to explore potential brain changes.

Methods

Cranial magnetic resonance (MR) images of 44 PI patients and 30 healthy subjects were prospectively collected for analysis. The T1, T2, PD, and CBF values of the frontal lobe, parietal lobe, temporal lobe, and occipital lobe were independently measured using three-dimensional arterial spin labeling (3D-ASL), synthetic magnetic resonance imaging (syMRI) and a whole-brain automatic segmentation method. The differences of these imaging indices were compared between PI patients and healthy subjects. Follow-up MR images were obtained from PI patients after 6 months to compare with pre-treatment images. The Wilcoxon signed rank test and Spearman rank were used for statistical analysis.

Results

Bilateral CBF asymmetry was observed in 38 patients, with significant differences in both the T2 value and CBF between the four lobes of the brain (p < 0.01). However, no significant difference was found in the T1 and PD values between the bilateral lobes. A negative correlation was found between CBF and T2 values in the right four lobes of patients with primary insomnia (PI). During follow-up examinations, five PI patients showed a disappearance of insomnia symptoms and a decrease in CBF in both brain lobes.

Conclusion

Insomnia symptoms may be associated with high CBF, and most PI patients have higher CBF and lower T2 values in the right cerebral hemispheres. The right hemisphere appears to play a critical role in the pathophysiology of PI. The 3D-ASL and syMRI technologies can provide a quantitative imaging basis for investigating the brain conditions and changes in young and middle-aged PI patients.

Commercial volumetric MRI reporting tools in multiple sclerosis: a systematic review of the evidence

PURPOSE

MRI is integral to the diagnosis of multiple sclerosis (MS) and is important for clinical prognostication. Quantitative volumetric reporting tools (QReports) can improve the accuracy and objectivity of MRI-based assessments. Several QReports are commercially available; however, validation can be difficult to establish and does not currently follow a common pathway. To aid evidence-based clinical decision-making, we performed a systematic review of commercial QReports for use in MS including technical details and published reports of validation and in-use evaluation.

METHODS

We categorized studies into three types of testing: technical validation, for example, comparison to manual segmentation, clinical validation by clinicians or interpretation of results alongside clinician-rated variables, and in-use evaluation, such as health economic assessment.

RESULTS

We identified 10 companies, which provide MS lesion and brain segmentation and volume quantification, and 38 relevant publications. Tools received regulatory approval between 2006 and 2020, contextualize results to normative reference populations, ranging from 620 to 8000 subjects, and require T1- and T2-FLAIR-weighted input sequences for longitudinal assessment of whole-brain volume and lesions. In MS, six QReports provided evidence of technical validation, four companies have conducted clinical validation by correlating results with clinical variables, only one has tested their QReport by clinician end-users, and one has performed a simulated in-use socioeconomic evaluation.

CONCLUSION

We conclude that there is limited evidence in the literature regarding clinical validation and in-use evaluation of commercial MS QReports with a particular lack of clinician end-user testing. Our systematic review provides clinicians and institutions with the available evidence when considering adopting a quantitative reporting tool for MS.

Accelerated Synthetic MRI with Deep Learning-Based Reconstruction for Pediatric Neuroimaging

BACKGROUND AND PURPOSE

Synthetic MR imaging is a time-efficient technique. However, its rather long scan time can be challenging for children. This study aimed to evaluate the clinical feasibility of accelerated synthetic MR imaging with deep learning-based reconstruction in pediatric neuroimaging and to investigate the impact of deep learning-based reconstruction on image quality and quantitative values in synthetic MR imaging.

MATERIALS AND METHODS

This study included 47 children 2.3-14.7 years of age who underwent both standard and accelerated synthetic MR imaging at 3T. The accelerated synthetic MR imaging was reconstructed using a deep learning pipeline. The image quality, lesion detectability, tissue values, and brain volumetry were compared among accelerated deep learning and accelerated and standard synthetic data sets.

RESULTS

The use of deep learning-based reconstruction in the accelerated synthetic scans significantly improved image quality for all contrast weightings (P < .001), resulting in image quality comparable with or superior to that of standard scans. There was no significant difference in lesion detectability between the accelerated deep learning and standard scans (P > .05). The tissue values and brain tissue volumes obtained with accelerated deep learning and the other 2 scans showed excellent agreement and a strong linear relationship (all, R 2 > 0.9). The difference in quantitative values of accelerated scans versus accelerated deep learning scans was very small (tissue values, <0.5%; volumetry, -1.46%-0.83%).

CONCLUSIONS

The use of deep learning-based reconstruction in synthetic MR imaging can reduce scan time by 42% while maintaining image quality and lesion detectability and providing consistent quantitative values. The accelerated deep learning synthetic MR imaging can replace standard synthetic MR imaging in both contrast-weighted and quantitative imaging.

Time-saving synthetic magnetic resonance imaging protocols for pediatric neuroimaging: impact of echo train length and bandwidth on image quality

BACKGROUND

Synthetic MRI is a time-efficient imaging technique that provides both quantitative MRI and contrast-weighted images simultaneously. However, a rather long single scan time can be challenging for children.

OBJECTIVE

To evaluate the clinical feasibility of time-saving synthetic MRI protocols adjusted for echo train length and receiver bandwidth in pediatric neuroimaging based on image quality assessment and quantitative data analysis.

MATERIALS AND METHODS

In total, we included 33 children ages 1.6-17.4 years who underwent synthetic MRI using three sets of echo train length and receiver bandwidth combinations (echo train length [E]12-bandwidth [B in KHz]22, E16-B22 and E16-B83) at 3 T. The image quality and lesion conspicuity of synthetic contrast-weighted images were compared between the suggested protocol (E12-B22) and adjusted protocols (E16-B22 and E16-B83). We also compared tissue values (T1, T2, proton-density values) and brain volumetry.

RESULTS

For the E16-B83 combination, image quality was sufficient except for 15.2% of T1-W and 3% of T2-W fluid-attenuated inversion recovery (FLAIR) images, with remarkable scan time reduction (up to 35%). The E16-B22 combination demonstrated a comparable image quality to E12-B22 (P&gt;0.05) with a scan time reduction of up to 8%. There were no significant differences in lesion conspicuity among the three protocols (P&gt;0.05). Tissue value measurements and brain tissue volumes obtained with the E12-B22 protocol and adjusted protocols showed excellent agreement and strong correlations except for gray matter volume and non-white matter/gray matter/cerebrospinal fluid volume in E12-B22 vs. E16-B83.

CONCLUSION

The adjusted synthetic protocols produced image quality sufficient or comparable to that of the suggested protocol while maintaining lesion conspicuity with reduced scan time. The quantitative values were generally consistent with the suggested MRI-protocol-derived values, which supports the clinical application of adjusted protocols in pediatric neuroimaging.

Characterization of meningiomas with synthetic imaging

INTRODUCTION

Synthetic magnetic resonance imaging (SyMRI) is a novel quantitative and qualitative technique that permits the reconstruction of multiple image contrasts and quantitative maps from a single scan, thereby providing quantitative information and reducing scan times. The purpose of this study is to characterize intracranial meningiomas using SyMRI.

METHODS

The study included 35 patients with meningiomas (6 males, 29 females; mean age 61 ± 17 years; range 21-90 years). Using 3T MR scanners, SyMRI was performed in addition to conventional FSET2, FLAIR, DWI, T1, and T1 with gadolinium. SyMRI software was used to generate T1, T2, and PD quantitative maps. Osirix MD was used to measure quantitative values of T1, T2, and PD using a ROI.

RESULTS

We analyzed 42 meningiomas, 8 of which were associated with edema, and 5 contained calcifications. Mean relaxivity values of meningiomas on synthetic T1, T2, and PD maps at 3T MRI were 1382.6 ± 391.7 ms, 95.6 ± 36.5 ms, and 89.1 ± 9.7 pu, respectively. Signal intensities in terms of T1, T2, and PD did not differ significantly between meningiomas with and without edema (p = .994, p = .356, and p = .221, respectively), nor between meningiomas containing and not containing calcifications (p = .840, p = .710, and p = .455, respectively). Values of T1 and T2 measured in meningiomas and the normal-appearing white matter approximated reference values found in the literature with other quantitative methods.

CONCLUSION

The presented method offers a novel approach to characterize meningiomas through their relaxation parameters measured with a SyMRI sequence.

Synthetic double inversion recovery imaging in brain MRI: quantitative evaluation and feasibility of synthetic MRI and a comparison with conventional double inversion recovery and fluid-attenuated inversion recovery sequences

Background and purpose

Synthetic MR imaging (SyMRI) allows the reconstruction of various contrast images, including double inversion recovery (DIR), from a single scan. This study aimed to investigate the advantages of SyMRI by comparing synthetic DIR images with synthetic T2-weighted fluid-attenuated inversion recovery (T2W-FLAIR) and conventional DIR images.

Materials and methods

We retrospectively reviewed the imaging data of 100 consecutive patients who underwent brain MRI between December 2018 and March 2019. Synthetic DIR, T2W-FLAIR, T1-weighted, and phase-sensitive inversion recovery (PSIR) images were generated from SyMRI data. For synthetic DIR, the two inversion times required to suppress white matter and cerebrospinal fluid (CSF) were manually determined by two radiologists. Quantitative analysis was performed by manually tracing the region of interest (ROI) at the sites of the lesion, white matter, and CSF. Synthetic DIR, synthetic T2W-FLAIR, and conventional DIR images were compared on the basis of using the gray matter-to-white matter, lesion-to-white matter, and lesion-to-CSF contrast-to-noise ratios.

Results

The two radiologists showed no differences in setting inversion time (TI) values, and their evaluations showed excellent interobserver agreement. The mean signal intensities obtained with synthetic DIR were significantly higher than those obtained with synthetic T2W-FLAIR and conventional DIR.

Conclusion

Synthetic DIR images showed a higher contrast than synthetic T2WFLAIR and conventional DIR images.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-022-00877-4.

Synthetic MRI with Magnetic Resonance Spin TomogrAphy in Time-Domain (MR-STAT): Results from a Prospective Cross-Sectional Clinical Trial

BACKGROUND

Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) can reconstruct whole-brain multi-parametric quantitative maps (eg, T₁ , T₂ ) from a 5-minute MR acquisition. These quantitative maps can be leveraged for synthetization of clinical image contrasts.

PURPOSE

The objective was to assess image quality and overall diagnostic accuracy of synthetic MR-STAT contrasts compared to conventional contrast-weighted images.

STUDY TYPE

Prospective cross-sectional clinical trial.

POPULATION

Fifty participants with a median age of 45 years (range: 21-79 years) consisting of 10 healthy participants and 40 patients with neurological diseases (brain tumor, epilepsy, multiple sclerosis or stroke).

FIELD STRENGTH/SEQUENCE

3T/Conventional contrast-weighted imaging (T₁ /T₂ weighted, proton density [PD] weighted, and fluid-attenuated inversion recovery [FLAIR]) and a MR-STAT acquisition (2D Cartesian spoiled gradient echo with varying flip angle preceded by a non-selective inversion pulse).

ASSESSMENT

Quantitative T₁ , T₂ , and PD maps were computed from the MR-STAT acquisition, from which synthetic contrasts were generated. Three neuroradiologists blinded for image type and disease randomly and independently evaluated synthetic and conventional datasets for image quality and diagnostic accuracy, which was assessed by comparison with the clinically confirmed diagnosis.

STATISTICAL TESTS

Image quality and consequent acceptability for diagnostic use was assessed with a McNemar's test (one-sided α = 0.025). Wilcoxon signed rank test with a one-sided α = 0.025 and a margin of Δ = 0.5 on the 5-level Likert scale was used to assess non-inferiority.

RESULTS

All data sets were similar in acceptability for diagnostic use (≥3 Likert-scale) between techniques (T₁ w:P = 0.105, PDw:P = 1.000, FLAIR:P = 0.564). However, only the synthetic MR-STAT T₂ weighted images were significantly non-inferior to their conventional counterpart; all other synthetic datasets were inferior (T₁ w:P = 0.260, PDw:P = 1.000, FLAIR:P = 1.000). Moreover, true positive/negative rates were similar between techniques (conventional: 88%, MR-STAT: 84%).

DATA CONCLUSION

MR-STAT is a quantitative technique that may provide radiologists with clinically useful synthetic contrast images within substantially reduced scan time.

EVIDENCE LEVEL

1 Technical Efficacy: Stage 2.

Synthetic MRI for stroke: a qualitative and quantitative pilot study

Synthetic MR provides qualitative and quantitative multi-parametric data about tissue properties in a single acquisition. Its use in stroke imaging is not yet established. We compared synthetic and conventional image quality and studied synthetic relaxometry of acute and chronic ischemic lesions to investigate its interest for stroke imaging. We prospectively acquired synthetic and conventional brain MR of 43 consecutive adult patients with suspected stroke. We studied a total of 136 lesions, of which 46 DWI-positive with restricted ADC (DWI + /rADC), 90 white matter T2/FLAIR hyperintensities (WMH) showing no diffusion restriction, and 430 normal brain regions (NBR). We assessed image quality for lesion definition according to a 3-level score by two readers of different experiences. We compared relaxometry of lesions and regions of interest. Synthetic images were superior to their paired conventional images for lesion definition except for sFLAIR (sT1 or sPSIR vs. cT1 and sT2 vs. cT2 for DWI + /rADC and WMH definition; p values < .001) with substantial to almost perfect inter-rater reliability (κ ranging from 0.711 to 0.932, p values < .001). We found significant differences in relaxometry between lesions and NBR and between acute and chronic lesions (T1, T2, and PD of DWI + /rADC or WMH vs. mirror NBR; p values < .001; T1 and PD of DWI + /rADC vs. WMH; p values of 0.034 and 0.008). Synthetic MR may contribute to stroke imaging by fast generating accessible weighted images for visual inspection derived from rapidly acquired relaxometry data. Moreover, this synthetic relaxometry could differentiate acute and chronic ischemic lesions.

Quantitative Synthetic Magnetic Resonance Imaging for Brain Metastases: A Feasibility Study

Simple Summary

This preliminary study aims to characterize brain metastases (BM) using T1 and T2 maps generated from newer, rapid, synthetic MRI (MAGnetic resonance image Compilation; MAGiC) in a clinical setting. In addition, synthetic MR could provide contrast images analogous to standard T1- and T2-weighted images. The reproducibility and repeatability of this method have been previously established for brain imaging. This study reports and analyzes the quantitative T1 and T2 values for 11 BM patients (17 BM lesions) with a total of 82 regions of interest (ROIs) delineated by an experienced neuroradiologist. The initial results, which need to be further validated in a larger patient cohort, demonstrated the ability of T1 and T2 metric values to characterize BMs and normal-appearing brain tissues. The T1 and T2 metrics could be potential surrogate biomarkers for BM free water content (cellularity) and tumor morphology, respectively.

Abstract

The present preliminary study aims to characterize brain metastases (BM) using T1 and T2 maps generated from newer, rapid, synthetic MRI (MAGnetic resonance image Compilation; MAGiC) in a clinical setting. We acquired synthetic MRI data from 11 BM patients on a 3T scanner. A multiple-dynamic multiple-echo (MDME) sequence was used for data acquisition and synthetic image reconstruction, including post-processing. MDME is a multi-contrast sequence that enables absolute quantification of physical tissue properties, including T1 and T2, independent of the scanner settings. In total, 82 regions of interest (ROIs) were analyzed, which were obtained from both normal-appearing brain tissue and BM lesions. The mean values obtained from the 48 normal-appearing brain tissue regions and 34 ROIs of BM lesions (T1 and T2) were analyzed using standard statistical methods. The mean T1 and T2 values were 1143 ms and 78 ms, respectively, for normal-appearing gray matter, 701 ms and 64 ms for white matter, and 4206 ms and 390 ms for cerebrospinal fluid. For untreated BMs, the mean T1 and T2 values were 1868 ms and 100 ms, respectively, and 2211 ms and 114 ms for the treated group. The quantitative T1 and T2 values generated from synthetic MRI can characterize BM and normal-appearing brain tissues.

Assessment of 2D conventional and synthetic MRI in multiple sclerosis

PURPOSE

To qualitatively and quantitatively compare synthetic and conventional MRI sequences acquired on a 1.5-T system for patients with multiple sclerosis (MS).

METHODS

Prospective study that involved twenty-seven consecutive relapsing-remitting MS patients scanned on a 1.5-T MRI scanner. The MRI protocol included 2D transverse conventional spin-echo sequences: proton density-weighted (PD), T2-weighted, T2-FLAIR, and T1-weighted. Synthetic images were generated using 2D transverse QRAPMASTER and SyMRI software with the same voxel size, repetition, echo, and inversion times as the conventional sequences. Four raters performed a crosstab qualitative analysis that involved evaluating global image quality, contrast, flow artefacts, and confidence in lesion assessment introducing the concepts of predominance, agreement, and disagreement. A quantitative analysis was also performed and included evaluating the number of lesions (periventricular, juxtacortical, brainstem, and cerebellum) and the contrast-to-noise ratio between regions (CSF, white matter, grey matter, lesions).

RESULTS

The global image quality assessment showed predominance for better scores for conventional sequences over synthetic sequences, whereas contrast, confidence in lesion assessment, and flow artefacts showed predominance for agreement between sequences. There was predominance for disagreement between all pairs of raters in most of the evaluated qualitative parameters. Synthetic PD and T2-FLAIR images showed higher contrast-to-noise ratios than the corresponding conventional images for most comparison between regions. There were no significant differences in the number of lesions detected for most of the study regions between conventional and synthetic images.

CONCLUSION

Synthetic MRI can be potentially used as an alternative to conventional brain MRI sequences in the assessment of MS.

The effect of scan parameters on T1, T2 relaxation times measured with multi-dynamic multi-echo sequence: a phantom study

Multi-Dynamic Multi-Echo (MDME) Sequence is a new method which can acquire various contrast-weighted images using quantitative relaxometric parameters measured from multicontrast images. The purpose of our study was to investigate the effect of scan parameters of MDME Sequence on measured T1, T2 values of phantoms at 3.0 T MRI scanner. Gray matter, white matter and cerebrospinal fluid simulation phantoms with different relaxation times (named GM, WM, CSF, respectively) were used in our study. All the phantoms were scanned 9 times on different days using MDME sequence with variations of echo train length, matrix, and acceleration factor. The T1, T2 measurements were acquired after each acquisition. The repeatability was characterized as the intragroup coefficient of variation (CV) of measured values over 9 times, and the discrepancies of measurements across different groups were characterized as intergroup CVs. The highest intragroup CVs of T1-GM, T2-GM, T1-WM, T2-WM, T1-CSF, T2-SCF were 1.36%, 1.75%, 0.74%, 1.41%, 1.70%, 7.79%, respectively. The highest intergroup CVs of T1-GM, T2-GM, T1-WM, T2-WM, T1-CSF, T2-SCF were 0.54%, 1.86%, 1.70%, 0.94%, 1.00%, 2.17%, respectively. Quantitative T1, T2 measurements of gray matter, white matter and cerebrospinal fluid simulation phantoms derived from the MDME sequence were not obviously affected by variations of scanning parameters, such as echo train length, matrix, and acceleration factor on 3T scanner.

Synthetic MR: Physical principles, clinical implementation, and new developments

Current clinical MR imaging practices rely on the qualitative assessment of images for diagnosis and treatment planning. While contrast in MR images is dependent on the spin parameters of the imaged tissue, pixel values on MR images are relative and are not scaled to represent any tissue properties. Synthetic MR is a fully featured imaging workflow consisting of efficient multiparameter mapping acquisition, synthetic image generation, and volume quantitation of brain tissues. As the application becomes more widely available on multiple vendors and scanner platforms, it has also gained widespread adoption as clinicians begin to recognize the benefits of rapid quantitation. This review will provide details about the sequence with a focus on the physical principles behind its relaxometry mechanisms. It will present an overview of the products in their current form and some potential issues when implementing it in the clinic. It will conclude by highlighting some recent advances of the technique, including a 3D mapping method and its associated applications. This article is protected by copyright. All rights reserved.

The Karolinska NeuroCOVID study protocol: Neurocognitive impairment, biomarkers and advanced imaging in critical care survivors

Background

This is the study plan of the Karolinska NeuroCOVID study, a study of neurocognitive impairment after severe COVID‐19, relating post‐intensive care unit (ICU) cognitive and neurological deficits to biofluid markers and MRI. The COVID‐19 pandemic has posed enormous health challenges to individuals and health‐care systems worldwide. An emerging feature of severe COVID‐19 is that of temporary and extended neurocognitive impairment, exhibiting a myriad of symptoms and signs. The causes of this symptomatology have not yet been fully elucidated.

Methods

In this study, we aim to investigate patients treated for severe COVID‐19 in the ICU, as to describe and relate serum‐, plasma‐ and cerebrospinal fluid‐borne molecular and cellular biomarkers of immune activity, coagulopathy, cerebral damage, neuronal inflammation, and degeneration, to the temporal development of structural and functional changes within the brain as evident by serial MRI and extensive cognitive assessments at 3–12 months after ICU discharge.

Results

To date, we have performed 51 3‐month follow‐up MRIs in the ICU survivors. Of these, two patients (~4%) have had incidental findings on brain MRI findings requiring activation of the Incidental Findings Management Plan. Furthermore, the neuropsychological and neurological examinations have so far revealed varying and mixed patterns. Several patients expressed cognitive and/or mental concerns and fatigue, complaints closely related to brain fog.

Conclusion

The study goal is to gain a better understanding of the pathological mechanisms and neurological consequences of this new disease, with a special emphasis on neurodegenerative and neuroinflammatory processes, in order to identify targets of intervention and rehabilitation.

Application of MAGnetic resonance imaging compilation in acute ischemic stroke

BACKGROUND

Synthetic magnetic resonance imaging (MRI) MAGnetic resonance imaging compilation (MAGiC) is a new MRI technology. Conventional T1, T2, T2-fluid-attenuated inversion recovery (FLAIR) contrast images, quantitative images of T1 and T2 mapping, and MAGiC phase sensitive inversion recovery (PSIR) Vessel cerebrovascular images can be obtained simultaneously through post-processing at the same time after completing a scan. In recent years, studies have reported that MAGiC can be applied to patients with acute ischemic stroke. We hypothesized that the synthetic MRI vascular screening scheme can evaluate the degree of cerebral artery stenosis in patients with acute ischemic stroke.

AIM

To explore the application value of vascular images obtained by synthetic MRI in diagnosing acute ischemic stroke.

METHODS

A total of 64 patients with acute ischemic stroke were selected and examined by MRI in the current retrospective cohort study. The scanning sequences included traditional T1, T2, and T2-FLAIR, three-dimensional time-of-flight magnetic resonance angiography (3D TOF MRA), diffusion-weighted imaging (DWI), and synthetic MRI. Conventional contrast images (T1, T2, and T2-FLAIR) and intracranial vessel images (MAGiC PSIR Vessel] were automatically reconstructed using synthetic MRI raw data. The contrast-to-noise ratio (CNR) values of traditional T1, T2, and T2-FLAIR images and MAGiC reconstructed T1, T2, and T2-FLAIR images in DWI diffusion restriction areas were measured and compared. MAGiC PSIR Vessel and TOF MRA images were used to measure and calculate the stenosis degree of bilateral middle cerebral artery stenosis areas. The consistency of MAGiC PSIR Vessel and TOF MRA in displaying the degree of vascular stenosis with computed tomography angiography (CTA) was compared.

RESULTS

Among the 64 patients with acute ischemic stroke, 79 vascular stenosis areas showed that the correlation between MAGiC PSIR Vessel and CTA (r = 0.90, P < 0.01) was higher than that between TOF MRA and CTA (r = 0.84, P < 0.01). With a degree of vascular stenosis > 50% assessed by CTA as a reference, the area under the receiver operating characteristic (ROC) curve of MAGiC PSIR Vessel [area under the curve (AUC) = 0.906, P < 0.01] was higher than that of TOF MRA (AUC = 0.790, P < 0.01). Among the 64 patients with acute ischemic stroke, 39 were scanned for traditional T1, T2, and T2-FLAIR images and MAGiC images simultaneously, and CNR values in DWI diffusion restriction areas were measured, which were: Traditional T2 = 21.2, traditional T1 = -6.7, and traditional T2-FLAIR = 11.9; and MAGiC T2 = 7.1, MAGiC T1 = -3.9, and MAGiC T2-FLAIR = 4.5.

CONCLUSION

The synthetic MRI vascular screening scheme for patients with acute ischemic stroke can accurately evaluate the degree of bilateral middle cerebral artery stenosis, which is of great significance to early thrombolytic interventional therapy and improving patients' quality of life.

Synthetic MRI with T2-based Water Suppression to Reduce Hyperintense Artifacts due to CSF-Partial Volume Effects in the Brain

Purpose:

Our purpose was to assess our proposed new synthetic MRI (synMRI) technique, combined with T₂-based water suppression (T₂wsup), to reduce cerebral spinal fluid (CSF)–partial volume effects (PVEs). These PVEs are problematic in the T₂-weighted fluid-attenuation inversion recovery (FLAIR) images obtained by conventional synMRI techniques.

Methods:

Our T₂wsup was achieved by subtracting additionally acquired long TE spin echo (SE) images of water signals dominant from the originally acquired images after T₂ decay correction and a masking on the long TE image using the water volume (V_w) map to preserve tissue SNR, followed by quantitative mapping and then calculation of the synthetic images. A simulation study based on a two-compartment model including tissue and water in a voxel and a volunteer MR study were performed to assess our proposed method. Parameters of long TE and a threshold value in the masking were assessed and optimized experimentally. Quantitative parameter maps of standard and with T₂wsup were generated, then wsup-synthetic FLAIR and SE images were calculated using those suitable combinations and compared.

Results:

Our simulation clarified that the CSF–PVE artifacts in the standard synthetic FLAIR increase T₂ as the water volume increases in a voxel, and the volunteer MR brain study demonstrated that the hyperintense artifacts on synthetic images were reduced to < 10% of V_w in those with the standard synMRI while keeping the tissue SNR by selecting optimal masking parameters on additional long TE images of TE = 300 ms. In addition, the wsup-synthetic SE provided better gray-white matter contrasts compared with the wsup-synthetic FLAIR while keeping CSF suppression.

Conclusion:

Our proposed T₂wsup-synMRI technique makes it easy to reduce the CSF–PVE artifacts problematic in the synthetic FLAIR images using the current synMRI technique by adding long TE images and simple processing. Although further optimizations in data acquisition and processing techniques are required before actual clinical use, we expect our technique to become clinically useful.

Brain Volumetric Measurements in Children With Attention Deficit Hyperactivity Disorder: A Comparative Study Between Synthetic and Conventional Magnetic Resonance Imaging

Objective: To investigate the profiles of brain volumetric measurements in children with attention deficit hyperactivity disorder (ADHD), and the consistency of these brain volumetric measurements derived from the synthetic and conventional T1 weighted MRI (SyMRI and cT1w MRI).

Methods: Brain SyMRI and cT1w images were prospectively collected for 38 pediatric patients with ADHD and 38 healthy children (HC) with an age range of 6–14 years. The gray matter volume (GMV), white matter volume (WMV), cerebrospinal fluid (CSF), non-WM/GM/CSF (NoN), myelin, myelin fraction (MYF), brain parenchyma volume (BPV), and intracranial volume (ICV) were automatically estimated from SyMRI data, and the four matching measurements (GMV, WMV, BPV, ICV) were extracted from cT1w images. The group differences of brain volumetric measurements were performed, respectively, using analysis of covariance. Pearson correlation analysis and interclass correlation coefficient (ICC) were applied to evaluate the association between synthetic and cT1w MRI-derived measurements.

Results: As for the brain volumetric measurements extracted from SyMRI, significantly decreased GMV, WMV, BPV, and increased NON volume (p < 0.05) were found in the ADHD group compared with HC; No group differences were found in ICV, CSF, myelin volume and MYF (p > 0.05). With regard to GMV, WMV, BPV, and ICV estimated from cT1w images, the group differences between ADHD and HC were consistent with the results estimated from SyMRI. And these four measurements showed noticeable correlation between the two approaches (r = 0.692, 0.643, 0.898, 0.789, respectively, p < 0.001; ICC values are 0.809, 0.782, 0.946, 0.873, respectively).

Conclusion: Our study demonstrated a global brain development disability, but normal whole-brain myelination in children with ADHD. Moreover, our results demonstrated the high consistency of brain volumetric indices between synthetic and cT1w MRI in children, which indicates the high reliability of SyMRI in the child-brain volumetric analysis.

Technical and clinical validation of commercial automated volumetric MRI tools for dementia diagnosis-a systematic review

Developments in neuroradiological MRI analysis offer promise in enhancing objectivity and consistency in dementia diagnosis through the use of quantitative volumetric reporting tools (QReports). Translation into clinical settings should follow a structured framework of development, including technical and clinical validation steps. However, published technical and clinical validation of the available commercial/proprietary tools is not always easy to find and pathways for successful integration into the clinical workflow are varied. The quantitative neuroradiology initiative (QNI) framework highlights six necessary steps for the development, validation and integration of quantitative tools in the clinic. In this paper, we reviewed the published evidence regarding regulatory-approved QReports for use in the memory clinic and to what extent this evidence fulfils the steps of the QNI framework. We summarize unbiased technical details of available products in order to increase the transparency of evidence and present the range of reporting tools on the market. Our intention is to assist neuroradiologists in making informed decisions regarding the adoption of these methods in the clinic. For the 17 products identified, 11 companies have published some form of technical validation on their methods, but only 4 have published clinical validation of their QReports in a dementia population. Upon systematically reviewing the published evidence for regulatory-approved QReports in dementia, we concluded that there is a significant evidence gap in the literature regarding clinical validation, workflow integration and in-use evaluation of these tools in dementia MRI diagnosis.

Simple parameters of synthetic MRI for assessment of bone density in patients with spinal degenerative disease

OBJECTIVE

Good bone quality is the key to avoiding osteoporotic fragility fractures and poor outcomes after lumbar instrumentation and fusion surgery. Although dual-energy x-ray absorptiometry (DEXA) screening is the current standard for evaluating osteoporosis, many patients lack DEXA measurements before undergoing lumbar spine surgery. The present study aimed to investigate the utility of using simple quantitative parameters generated with novel synthetic MRI to evaluate bone quality, as well as the correlations of these parameters with DEXA measurements.

METHODS

This prospective study enrolled patients with symptomatic lumbar degenerative disease who underwent DEXA and conventional and synthetic MRI. The quantitative parameters generated with synthetic MRI were T1 map, T2 map, T1 intensity, proton density (PD), and vertebral bone quality (VBQ) score, and these parameters were correlated with T-score of the lumbar spine.

RESULTS

There were 62 patients and 238 lumbar segments eligible for analysis. PD and VBQ score moderately correlated with T-score of the lumbar spine (r = -0.565 and -0.651, respectively; both p < 0.001). T1 intensity correlated fairly well with T-score (r = -0.411, p < 0.001). T1 and T2 correlated poorly with T-score. Receiver operating characteristic curve analysis demonstrated area under the curve values of 0.808 and 0.794 for detecting osteopenia/osteoporosis (T-score ≤ -1.0) and osteoporosis (T-score ≤ -2.5) with PD (both p < 0.001).

CONCLUSIONS

PD and T1 intensity values generated with synthetic MRI demonstrated significant correlation with T-score. PD has excellent ability for predicting osteoporosis and osteopenia.

Reduced myelin in patients with isolated hippocampal sclerosis as assessed by SyMRI

Purpose

Synthetic MRI (SyMRI) enables to quantify brain tissue and morphometry. We aimed to investigate the WM and myelin alterations in patients with unilateral hippocampal sclerosis (HS) with SyMRI.

Methods

Adult patients with isolated unilateral HS and age-matched control subjects (CSs) were included in this study. The SyMRI sequence QRAPMASTER in the coronal plane perpendicular to the hippocampi was obtained from the whole brain. Automatic segmentation of the whole brain was processed by SyMRI Diagnostic software (Version 11.2). Two neuroradiologists also performed quantitative analyses independently from symmetrical 14 ROIs placed in temporal and extratemporal WM, hippocampi, and amygdalae in both hemispheres.

Results

Sixteen patients (F/M = 6/10, mean age = 32.5 ± 11.3 years; right/left HS: 8/8) and 10 CSs (F/M = 5/5, mean age = 30.7 ± 7 years) were included. Left HS patients had significantly lower myelin and WM volumes than CSs (p < .05). Myelin was reduced significantly in the ipsilateral temporal lobe of patients than CSs, greater in left HS (p < .05). Histopathological examination including luxol fast blue stain also revealed myelin pallor in all of 6 patients who were operated. Ipsilateral temporal pole and sub-insular WM had significantly reduced myelin than the corresponding contralateral regions in patients (p < .05). No significant difference was found in WM values. GM values were significantly lower in hippocampi in patients than CSs (p < .05).

Conclusion

SyMRI revealed myelin reduction in the ipsilateral temporal lobe and sub-insular WM of patients with HS. Whether this finding correlates with electrophysiological features and SyMRI could serve as lateralization of temporal lobe epilepsy need to be investigated.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00234-021-02824-6.

Clinical Application of MPRAGE Wave Controlled Aliasing in Parallel Imaging (Wave-CAIPI): A Comparative Study with MPRAGE GRAPPA

Purpose: To compare reliability and elucidate clinical application of magnetization-prepared rapid gradient-echo (MPRAGE) with 9-fold acceleration by using wave-controlled aliasing in parallel imaging (Wave-CAIPI 3 × 3) in comparison to conventional MPRAGE accelerated by using generalized autocalibrating partially parallel acquisition (GRAPPA) 2 × 1.

Methods: A total of 26 healthy volunteers and 33 patients were included in this study. Subjects were scanned with two MPRAGEs, GRAPPA 2 × 1 and Wave-CAIPI 3 × 3 acquired in 5 min 21 s and 1 min 42 s, respectively, on a 3T MR scanner. Healthy volunteers underwent additional two MPRAGEs (CAIPI 3 × 3 and GRAPPA 3 × 3). The image quality of the four MPRAGEs was visually evaluated with a 5-point scale in healthy volunteers, and the SNR of four MPRAGEs was also calculated by measuring the phantom 10 times with each MPRAGE. Based on the results of the visual evaluation, voxel-based morphometry (VBM) analyses, including subfield analysis, were performed only for GRAPPA 2 × 1 and Wave-CAIPI 3 × 3. Correlation of segmentation results between GRAPPA 2 × 1 and Wave-CAIPI 3 × 3 was assessed.

Results: In visual evaluations, scores for MPRAGE GRAPPA 2 × 1 (mean rank: 4.00) were significantly better than those for Wave-CAIPI 3 × 3 (mean rank: 3.00), CAIPI 3 × 3 (mean rank: 1.83), and GRAPPA 3 × 3 (mean rank: 1.17), and scores for Wave-CAIPI 3×3 were significantly better than those for CAIPI 3 × 3 and GRAPPA 3 × 3. Image noise was evident at the center for additional MPRAGE CAIPI 3 × 3 and GRAPPA 3 × 3. The correlation of segmentation results between GRAPPA 2 × 1 and Wave-CAIPI 3 × 3 was higher than 0.85 in all VOIs except globus pallidus. Subfield analysis of hippocampus also showed a high correlation between GRAPPA 2 × 1 and Wave-CAIPI 3 × 3.

Conclusion: MPRAGE Wave-CAIPI 3 × 3 shows relatively better contrast, despite of its short scan time of 1 min 42 s. The volumes derived from automated segmentation of MPRAGE Wave-CAIPI are considered to be reliable measures.

Current Perspectives of Artificial Intelligence in Pediatric Neuroradiology: An Overview

Artificial Intelligence, Machine Learning, and myriad related techniques are becoming ever more commonplace throughout industry and society, and radiology is by no means an exception. It is essential for every radiologists of every subspecialty to gain familiarity and confidence with these techniques as they become increasingly incorporated into the routine practice in both academic and private practice settings. In this article, we provide a brief review of several definitions and techniques that are commonly used in AI, and in particular machine vision, and examples of how they are currently being applied to the setting of clinical neuroradiology. We then review the unique challenges that the adoption and application of faces within the subspecialty of pediatric neuroradiology, and how these obstacles may be overcome. We conclude by presenting specific examples of how AI is currently being applied within the field of pediatric neuroradiology and the potential opportunities that are available for future applications.

Clinical adaptation of synthetic MRI-based whole brain volume segmentation in children at 3 T: comparison with modified SPM segmentation methods

PURPOSE

To validate the use of synthetic magnetic resonance imaging (SyMRI) volumetry by comparing with child-optimized SPM 12 volumetry in 3 T pediatric neuroimaging.

METHODS

In total, 106 children aged 4.7-18.7 years who underwent both synthetic and 3D T1-weighted imaging and had no abnormal imaging/neurologic findings were included for the SyMRI vs. SPM T1-only segmentation (SPM T1). Forty of the 106 children who underwent an additional 3D T2-weighted imaging were included for the SyMRI vs. SPM multispectral segmentation (SPM multi). SPM segmentation using an age-appropriate atlas and inverse-transforming template-space intracranial mask was compared with SyMRI segmentation. Volume differences between SyMRI and SPM T1 were plotted against age to evaluate the influence of age on volume difference.

RESULTS

Measurements derived from SyMRI and two SPM methods showed excellent agreements and strong correlations except for the CSF volume (CSFV) (intraclass correlation coefficients = 0.87-0.98; r = 0.78-0.96; relative volume difference other than CSFV = 6.8-18.5% [SyMRI vs. SPM T1] and 11.3-22.7% [SyMRI vs. SPM multi]). Dice coefficients of all brain tissues (except CSF) were in the range 0.78-0.91. The Bland-Altman plot and age-related volume difference change suggested that the volume differences between the two methods were influenced by the volume of each brain tissue and subject's age (p < 0.05).

CONCLUSION

SyMRI and SPM segmentation results were consistent except for CSFV, which supports routine clinical use of SyMRI-based volumetry in pediatric neuroimaging. However, caution should be taken in the interpretation of the CSF segmentation results.

Synthetic MRI in subarachnoid haemorrhage

AIM

To evaluate the reliability of synthetic magnetic resonance imaging (SyMRI) for detecting complications associated with subarachnoid haemorrhage (SAH), such as ischaemic lesions, hydrocephalus, or bleeding complications.

MATERIALS AND METHODS

Twenty patients with SAH, who underwent a conventional brain MRI and a SyMRI on a 3 T MRI machine. Comparable conventional and synthetic T2-weighted fluid attenuated inversion recovery (FLAIR) images were acquired. The presence of ischaemic lesions, hydrocephalus, extra-axial blood collections as well as the volumes of grey matter (GMv), white matter (WMv), and cerebrospinal (CSFv) were compared. The acquisition times of both sequences was also analysed.

RESULTS

The concordance between the two techniques was excellent for the detection of ischaemic lesions and extra-axial collections (kappa = 0.80 and 0.88 respectively) and good for the detection of hydrocephalus (kappa = 0.69). No significant differences were detected in the number of ischaemic lesions (p=0.31) or in the Evans index (p=0.11). The WMv and CSFv measures were also similar (p=0.18 and p=0.94, respectively), as well as the volume of ischaemic lesions (p=0.79). Compared to conventional MRI, the SyMRI acquisition time was shorter regardless of the number of sections (32% and 6% time reduction for 4 or 3 mm section thickness, respectively).

CONCLUSIONS

SyMRI allows the detection of potential complications of SAH in a similar way to conventional MRI with a shorter acquisition time.

Quantitative Analysis of Synthetic Magnetic Resonance Imaging in Alzheimer's Disease

Objectives: The purpose of this study was to evaluate the feasibility and whether synthetic MRI can benefit diagnosis of Alzheimer’s disease (AD).

Materials and Methods: Eighteen patients and eighteen age-matched normal controls (NCs) underwent MR examination. The mini-mental state examination (MMSE) scores were obtained from all patients. The whole brain volumetric characteristics, T1, T2, and proton density (PD) values of different cortical and subcortical regions were obtained. The volumetric characteristics and brain regional relaxation values between AD patients and NCs were compared using independent-samples t-test. The correlations between these quantitative parameters and MMSE score were assessed by the Pearson correlation in AD patients.

Results: Although the larger volume of cerebrospinal fluid (CSF), lower brain parenchymal volume (BPV), and the ratio of brain parenchymal volume to intracranial volume (BPV/ICV) were found in AD patients compared with NCs, there were no significant differences (p > 0.05). T1 values of right insula cortex and T2 values of left hippocampus and right insula cortex were significantly higher in AD patients than in NCs, but T1 values of left caudate showed a reverse trend (p < 0.05). As the MMSE score decreased in AD patients, the BPV and BPV/ICV decreased, while the volume of CSF and T1 values of bilateral insula cortex and bilateral hippocampus as well as T2 values of bilateral hippocampus increased (p < 0.05).

Conclusion: Synthetic MRI not only provides more information to differentiate AD patients from normal controls, but also reflects the disease severity of AD.

Histogram analysis of quantitative parameters from synthetic MRI: Correlations with prognostic factors and molecular subtypes in invasive ductal breast cancer

PURPOSE

To evaluate intra-tumoral heterogeneity through a histogram analysis of quantitative parameters obtained from synthetic MRI (magnetic resonance imaging), and determine correlations of these histogram characteristics with prognostic factors and molecular subtypes of invasive ductal carcinoma (IDC).

METHODS

A total of 122 IDC from 122 women who underwent preoperative synthetic MRI and DCE (dynamic contrast enhancement)-MRI were investigated. The synthetic MRI parameters (T1, T2, and PD (proton density)) were obtained. For each parameter, the minimum, 10th percentile, mean, median, 90th percentile, maximum, skewness, and kurtosis values of tumor were calculated, and correlations with prognostic factors and subtypes were assessed. The Mann-Whitney U test or the Student^'s t test were utilized to analyze the association between the histogram features of synthetic MRI parameters and prognostic factors. The Kruskal-Wallis test followed by the post-hoc test was used to analyze differences of synthetic MRI parameters among molecular subtypes.

RESULTS

IDC with high histopathologic grade showed statistically higher PD_maxium, T1_mean and T1_median values than those with low grade (p = 0.003, p = 0.007, p = 0.003). The T1_10th were significantly higher in cancers with PR (progesterone receptor) negativity than those with PR positivity (p = 0.005). ER-negative cancers had significant higher values of T2_10th, T2_mean, and T2_median than ER-positive cancers (p = 0.006, 0.002, and 0.006, respectively). The values of PD_median were significantly higher in IDC with HER2 (human epidermal growth factor receptor 2) positivity than those with HER2 negativity (p = 0.001). When discriminating molecular subtypes of IDC, the T2_mean achieved the highest performance. The T2_mean values of TN (triple-negative), luminal B and luminal A types are arranged in descending order (p <  0.0001).

CONCLUSIONS

Histogram features derived from synthetic MRI quantifies the distributions of tissue relaxation time and proton density, and may serve as a potential biomarker for discriminating histopathological grade, hormone receptor status, HER2 expression status and breast cancer subtypes.

Deep-Learning Generated Synthetic Double Inversion Recovery Images Improve Multiple Sclerosis Lesion Detection

OBJECTIVES

The aim of the study was to implement a deep-learning tool to produce synthetic double inversion recovery (synthDIR) images and compare their diagnostic performance to conventional sequences in patients with multiple sclerosis (MS).

MATERIALS AND METHODS

For this retrospective analysis, 100 MS patients (65 female, 37 [22-68] years) were randomly selected from a prospective observational cohort between 2014 and 2016. In a subset of 50 patients, an artificial neural network (DiamondGAN) was trained to generate a synthetic DIR (synthDIR) from standard acquisitions (T1, T2, and fluid-attenuated inversion recovery [FLAIR]). With the resulting network, synthDIR was generated for the remaining 50 subjects. These images as well as conventionally acquired DIR (trueDIR) and FLAIR images were assessed for MS lesions by 2 independent readers, blinded to the source of the DIR image. Lesion counts in the different modalities were compared using a Wilcoxon signed-rank test, and interrater analysis was performed. Contrast-to-noise ratios were compared for objective image quality.

RESULTS

Utilization of synthDIR allowed to detect significantly more lesions compared with the use of FLAIR images (31.4 ± 20.7 vs 22.8 ± 12.7, P < 0.001). This improvement was mainly attributable to an improved depiction of juxtacortical lesions (12.3 ± 10.8 vs 7.2 ± 5.6, P < 0.001). Interrater reliability was excellent in FLAIR 0.92 (95% confidence interval [CI], 0.85-0.95), synthDIR 0.93 (95% CI, 0.87-0.96), and trueDIR 0.95 (95% CI, 0.85-0.98).Contrast-to-noise ratio in synthDIR exceeded that of FLAIR (22.0 ± 6.4 vs 16.7 ± 3.6, P = 0.009); no significant difference was seen in comparison to trueDIR (22.0 ± 6.4 vs 22.4 ± 7.9, P = 0.87).

CONCLUSIONS

Computationally generated DIR images improve lesion depiction compared with the use of standard modalities. This method demonstrates how artificial intelligence can help improving imaging in specific pathologies.