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

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.

Effect of cerebrospinal fluid area mask correction on 123I-FP-CIT SPECT images in idiopathic normal pressure hydrocephalus

BACKGROUND

Cerebrospinal fluid (CSF) area mask correction reduces the influence of low [¹²³I]-N-fluoropropyl-2b-carbomethoxy-3b-(4-iodophenyl) nortropane (¹²³I-FP-CIT) accumulation in the volume of interest (VOI) by CSF area dilatation on the specific binding ratio (SBR) calculated using the Southampton method. We assessed the effect of CSF area mask correction on the SBR for idiopathic normal pressure hydrocephalus (iNPH) characterized by CSF area dilatation.

METHODS

We enrolled 25 patients with iNPH who were assessed using ¹²³I-FP-CIT single-photon emission computed tomography (SPECT) before shunt surgery or the tap test. The SBRs with and without CSF area mask correction were calculated, and changes in quantitative values were verified. Additionally, the number of voxels in the striatal and background (BG) VOI before and after CSF area mask correction were extracted. The number of voxels after correction was subtracted from that before correction, and the volume removed by the CSF area mask correction was calculated. The volumes removed from each VOI were compared to verify their effect on SBR.

RESULTS

The images of 20 and 5 patients with SBRs that were decreased and increased, respectively, by CSF area mask correction showed that the volumes removed from the BG region VOI were higher and lower, respectively than those in the striatal region.

CONCLUSIONS

The SBR before and after CSF area mask correction was associated with the ratio of the volume removed from the striatal and BG VOIs, and the SBR was high or low according to the ratio. The results suggest that CSF area mask correction is effective in patients with iNPH.

TRIAL REGISTRATION

This study was registered in the UMIN Clinical Trials Registry (UMIN-CTR) as UMIN study ID: UMIN000044826. 11/07/2021.

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.

Predicting hemorrhagic transformation after thrombectomy in acute ischemic stroke: a multimodal score of the regional pial collateral

PURPOSE

This study aims to analyze the multimodal score of the regional pial collateral in predicting hemorrhagic transformation (HT) after mechanical thrombectomy in acute ischemic stroke (AIS).

METHODS

On the basis of different brain regions and multiphase computed tomography angiography (mCTA), we evaluated the pial arterial filling status in extent, delay, and contrast washout. The prediction models of HT and symptomatic intracerebral hemorrhage (sICH) were established using mCTA (model-H1 and model-S1), CT perfusion (CTP, model-H2 and model-S2), and comprehensive parameters (model-H3 and model-S3). The receiver operating characteristic curve was used to analyze the prediction performance of each model.

RESULTS

Among the 102 patients with AIS who received thrombectomy, 36 (35.3%) developed HT, and 15 (14.7%) of whom had sICH. In model-H1 and model-S1, washout independently influenced HT (OR, 95%CI 0.398, 0.249-0.634) and sICH (OR, 95%CI 0.552, 0.342-0.892). In model-H2, the relative surface permeability independently influenced HT (OR, 95%CI 1.217, 1.082-1.370). Model-H3 and model-S3 improved the prediction performance (areas under the curve: HT, 0.957; sICH, 0.938). The correlation coefficients between relative cerebral blood volume and the three modes of pial arterial filling status were higher than those of other CTP parameters. The 90-day modified Rankin scale score in the sICH group was significantly increased (P < 0.05).

CONCLUSION

The multimodal regional pial collateral score has good value in the risk assessment of HT and sICH in patients with AIS after mechanical thrombectomy. The combination of multiple parameters can improve diagnostic performance.