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18-12-2024 | Cranial MRI | Research

A single 1-min brain MRI scan for generating multiple synthetic image contrasts in awake children from quantitative relaxometry maps

Authors: Anandh Kilpattu Ramaniharan, Amol Pednekar, Nehal A. Parikh, Usha D. Nagaraj, Mary Kate Manhard

Published in: Pediatric Radiology | Issue 2/2025

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Abstract

Background

Diagnostically adequate contrast and spatial resolution in brain MRI require prolonged scan times, leading to motion artifacts and image degradation in awake children. Rapid multi-parametric techniques can produce diagnostic images in awake children, which could help to avoid the need for sedation.

Objective

To evaluate the utility of a rapid echo-planar imaging (EPI)–based multi-inversion spin and gradient echo (MI-SAGE) technique for generating multi-parametric quantitative brain maps and synthetic contrast images in awake pediatric participants.

Materials and methods

In this prospective IRB-approved study, awake research participants 3–10 years old were scanned using MI-SAGE, MOLLI, GRASE, mGRE, and T1-, T2-, T2*-, and FLAIR-weighted sequences. The MI-SAGE T1, T2, and T2* maps and synthetic images were estimated offline. The MI-SAGE parametric values were compared to those from conventional mapping sequences including MOLLI, GRASE, and mGRE, with assessments of repeatability and reproducibility. Synthetic MI-SAGE images and conventional weighted images were reviewed by a neuroradiologist and scored using a 5-point Likert scale. Gray-to-white matter contrast ratios (GWRs) were compared between MI-SAGE synthetic and conventional weighted images. The results were analyzed using the Bland–Altman analysis and intra-class correlation coefficient (ICC).

Results

A total of 24 healthy participants aged 3 years to 10 years (mean ± SD, 6.5 ± 1.9; 12 males) completed full imaging exams including the 54-s MI-SAGE acquisition and were included in the analysis. The MI-SAGE T1, T2, and T2* had biases of 32%, -4%, and 23% compared to conventional mapping methods using MOLLI, GRASE, and mGRE, respectively, with moderate to very strong correlations (ICC=0.49–0.99). All MI-SAGE maps exhibited strong to very strong repeatability and reproducibility (ICC=0.80 to 0.99). The synthetic MI-SAGE had average Likert scores of 2.1, 2.1, 2.9, and 2.0 for T1-, T2-, T2*-, and FLAIR-weighted images, respectively, while conventional acquisitions had Likert scores of 3.5, 3.6, 4.6, and 3.8 for T1-, T2-, T2*-, and FLAIR-weighted images, respectively. The MI-SAGE synthetic T1w, T2w, T2*w, and FLAIR GWRs had biases of 17%, 3%, 7%, and 1% compared to the GWR of images from conventional T1w, T2w, T2*w, and FLAIR acquisitions respectively.

Conclusion

The derived T1, T2, and T2* maps were correlated with conventional mapping methods and showed strong repeatability and reproducibility. While synthetic MI-SAGE images had greater susceptibility artifacts and lower Likert scores than conventional images, the MI-SAGE technique produced synthetic weighted images with contrasts similar to conventional weighted images and achieved a ten-fold reduction in scan time.

Graphical Abstract

Literature
1.
go back to reference Raschle N, Zuk J, Ortiz-Mantilla S et al (2012) Pediatric neuroimaging in early childhood and infancy: challenges and practical guidelines. Ann N Y Acad Sci 1252:43–50CrossRefPubMedPubMedCentral Raschle N, Zuk J, Ortiz-Mantilla S et al (2012) Pediatric neuroimaging in early childhood and infancy: challenges and practical guidelines. Ann N Y Acad Sci 1252:43–50CrossRefPubMedPubMedCentral
2.
go back to reference Barkovich MJ, Li Y, Desikan RS et al (2019) Challenges in pediatric neuroimaging. Neuroimage 185:793–801CrossRefPubMed Barkovich MJ, Li Y, Desikan RS et al (2019) Challenges in pediatric neuroimaging. Neuroimage 185:793–801CrossRefPubMed
4.
go back to reference Bednarz HM, Kana RK (2018) Advances, challenges, and promises in pediatric neuroimaging of neurodevelopmental disorders. Neurosci Biobehav Rev 90:50–69CrossRefPubMed Bednarz HM, Kana RK (2018) Advances, challenges, and promises in pediatric neuroimaging of neurodevelopmental disorders. Neurosci Biobehav Rev 90:50–69CrossRefPubMed
5.
go back to reference Hazlett HC, Gu H, McKinstry RC et al (2012) Brain volume findings in 6-month-old infants at high familial risk for autism. Am J Psychiatry 169:601–608CrossRefPubMedPubMedCentral Hazlett HC, Gu H, McKinstry RC et al (2012) Brain volume findings in 6-month-old infants at high familial risk for autism. Am J Psychiatry 169:601–608CrossRefPubMedPubMedCentral
6.
go back to reference Catalina Camacho M, King LS, Ojha A et al (2020) Cerebral blood flow in 5-to 8-month-olds: regional tissue maturity is associated with infant affect. Dev Sci 23:e12928CrossRefPubMed Catalina Camacho M, King LS, Ojha A et al (2020) Cerebral blood flow in 5-to 8-month-olds: regional tissue maturity is associated with infant affect. Dev Sci 23:e12928CrossRefPubMed
7.
9.
go back to reference Vossough A (2023) Newer MRI techniques in pediatric neuroimaging. Seminars in Roentgenology. Elsevier, pp 131–144 Vossough A (2023) Newer MRI techniques in pediatric neuroimaging. Seminars in Roentgenology. Elsevier, pp 131–144
10.
go back to reference Kozak BM, Jaimes C, Kirsch J, Gee MS (2020) MRI techniques to decrease imaging times in children. Radiographics 40:485–502CrossRefPubMed Kozak BM, Jaimes C, Kirsch J, Gee MS (2020) MRI techniques to decrease imaging times in children. Radiographics 40:485–502CrossRefPubMed
11.
go back to reference Jaimes C, Robson CD, Machado-Rivas F et al (2021) Success of nonsedated neuroradiologic MRI in children 1–7 years old. Am J Roentgenol 216:1370–1377CrossRef Jaimes C, Robson CD, Machado-Rivas F et al (2021) Success of nonsedated neuroradiologic MRI in children 1–7 years old. Am J Roentgenol 216:1370–1377CrossRef
12.
go back to reference Harrington SG, Jaimes C, Weagle KM et al (2022) Strategies to perform magnetic resonance imaging in infants and young children without sedation. Pediatr Radiol 52:374–381 Harrington SG, Jaimes C, Weagle KM et al (2022) Strategies to perform magnetic resonance imaging in infants and young children without sedation. Pediatr Radiol 52:374–381
13.
go back to reference Doria AS, Chaudry GA, Nasui C et al (2010) The use of parallel imaging for MRI assessment of knees in children and adolescents. Pediatr Radiol 40:284–293CrossRefPubMed Doria AS, Chaudry GA, Nasui C et al (2010) The use of parallel imaging for MRI assessment of knees in children and adolescents. Pediatr Radiol 40:284–293CrossRefPubMed
14.
go back to reference Setsompop K, Gagoski BA, Polimeni JR et al (2012) Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty. Magn Reson Med 67:1210–1224CrossRefPubMed Setsompop K, Gagoski BA, Polimeni JR et al (2012) Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty. Magn Reson Med 67:1210–1224CrossRefPubMed
15.
go back to reference Barth M, Breuer F, Koopmans PJ et al (2016) Simultaneous multislice (SMS) imaging techniques. Magn Reson Med 75:63–81CrossRefPubMed Barth M, Breuer F, Koopmans PJ et al (2016) Simultaneous multislice (SMS) imaging techniques. Magn Reson Med 75:63–81CrossRefPubMed
17.
go back to reference Chandra SS, Bran Lorenzana M, Liu X et al (2021) Deep learning in magnetic resonance image reconstruction. J Med Imaging Radiat Oncol 65:564–577CrossRefPubMed Chandra SS, Bran Lorenzana M, Liu X et al (2021) Deep learning in magnetic resonance image reconstruction. J Med Imaging Radiat Oncol 65:564–577CrossRefPubMed
18.
go back to reference Poustchi-Amin M, Mirowitz SA, Brown JJ et al (2001) Principles and applications of echo-planar imaging: a review for the general radiologist. Radiographics 21:767–779CrossRefPubMed Poustchi-Amin M, Mirowitz SA, Brown JJ et al (2001) Principles and applications of echo-planar imaging: a review for the general radiologist. Radiographics 21:767–779CrossRefPubMed
19.
go back to reference Blystad I, Warntjes JBM, Smedby O et al (2012) Synthetic MRI of the brain in a clinical setting. Acta Radiol 53:1158–1163CrossRefPubMed Blystad I, Warntjes JBM, Smedby O et al (2012) Synthetic MRI of the brain in a clinical setting. Acta Radiol 53:1158–1163CrossRefPubMed
20.
go back to reference Keenan KE, Biller JR, Delfino JG et al (2019) Recommendations towards standards for quantitative MRI (qMRI) and outstanding needs. J Magn Reson Imaging 49:e26CrossRefPubMedPubMedCentral Keenan KE, Biller JR, Delfino JG et al (2019) Recommendations towards standards for quantitative MRI (qMRI) and outstanding needs. J Magn Reson Imaging 49:e26CrossRefPubMedPubMedCentral
22.
go back to reference Manhard MK, Stockmann J, Liao C et al (2021) A multi-inversion multi-echo spin and gradient echo echo planar imaging sequence with low image distortion for rapid quantitative parameter mapping and synthetic image contrasts. Magn Reson Med 86:866–880CrossRefPubMedPubMedCentral Manhard MK, Stockmann J, Liao C et al (2021) A multi-inversion multi-echo spin and gradient echo echo planar imaging sequence with low image distortion for rapid quantitative parameter mapping and synthetic image contrasts. Magn Reson Med 86:866–880CrossRefPubMedPubMedCentral
23.
go back to reference Ordidge R, Gibbs P, Chapman B et al (1990) High-speed multislice T1 mapping using inversion-recovery echo-planar imaging. Magn Reson Med 16:238–245CrossRefPubMed Ordidge R, Gibbs P, Chapman B et al (1990) High-speed multislice T1 mapping using inversion-recovery echo-planar imaging. Magn Reson Med 16:238–245CrossRefPubMed
24.
go back to reference Clare S, Jezzard P (2001) Rapid T1 mapping using multislice echo planar imaging. Magn Reson Med 45:630–634CrossRefPubMed Clare S, Jezzard P (2001) Rapid T1 mapping using multislice echo planar imaging. Magn Reson Med 45:630–634CrossRefPubMed
25.
go back to reference Renvall V, Witzel T, Wald LL, Polimeni JR (2016) Automatic cortical surface reconstruction of high-resolution T1 echo planar imaging data. Neuroimage 134:338–354CrossRefPubMed Renvall V, Witzel T, Wald LL, Polimeni JR (2016) Automatic cortical surface reconstruction of high-resolution T1 echo planar imaging data. Neuroimage 134:338–354CrossRefPubMed
26.
go back to reference Schmiedeskamp H, Straka M, Newbould RD et al (2012) Combined spin-and gradient-echo perfusion-weighted imaging. Magn Reson Med 68:30–40CrossRefPubMed Schmiedeskamp H, Straka M, Newbould RD et al (2012) Combined spin-and gradient-echo perfusion-weighted imaging. Magn Reson Med 68:30–40CrossRefPubMed
27.
go back to reference Eichner C, Jafari-Khouzani K, Cauley S et al (2014) Slice accelerated gradient-echo spin-echo dynamic susceptibility contrast imaging with blipped CAIPI for increased slice coverage. Magn Reson Med 72:770–778CrossRefPubMed Eichner C, Jafari-Khouzani K, Cauley S et al (2014) Slice accelerated gradient-echo spin-echo dynamic susceptibility contrast imaging with blipped CAIPI for increased slice coverage. Magn Reson Med 72:770–778CrossRefPubMed
28.
go back to reference Jia F, Liao Y, Li X et al (2022) Preliminary study on quantitative assessment of the fetal brain using MOLLI T1 mapping sequence. J Magn Reson Imaging 56:1505–1512CrossRefPubMed Jia F, Liao Y, Li X et al (2022) Preliminary study on quantitative assessment of the fetal brain using MOLLI T1 mapping sequence. J Magn Reson Imaging 56:1505–1512CrossRefPubMed
29.
go back to reference Chu M-L, Chien C-P, Wu W-C, Chung H-W (2019) Gradient-and spin-echo (GRASE) MR imaging: a long-existing technology that may find wide applications in modern era. Quant Imaging Med Surg 9:1477CrossRefPubMedPubMedCentral Chu M-L, Chien C-P, Wu W-C, Chung H-W (2019) Gradient-and spin-echo (GRASE) MR imaging: a long-existing technology that may find wide applications in modern era. Quant Imaging Med Surg 9:1477CrossRefPubMedPubMedCentral
30.
go back to reference Bloch F (1946) Nuclear induction. Phys Rev 70:460 Bloch F (1946) Nuclear induction. Phys Rev 70:460
31.
go back to reference Evans JD (1996) Straightforward statistics for the behavioral sciences. Thomson Brooks/Cole Publishing Co Evans JD (1996) Straightforward statistics for the behavioral sciences. Thomson Brooks/Cole Publishing Co
32.
go back to reference Putcha D, Katsumi Y, Brickhouse M et al (2023) Gray to white matter signal ratio as a novel biomarker of neurodegeneration in Alzheimer’s disease. NeuroImage: Clin 37:103303 Putcha D, Katsumi Y, Brickhouse M et al (2023) Gray to white matter signal ratio as a novel biomarker of neurodegeneration in Alzheimer’s disease. NeuroImage: Clin 37:103303
33.
go back to reference Bunce C (2009) Correlation, agreement, and Bland-Altman analysis: statistical analysis of method comparison studies. Am J Ophthalmol 148:4–6CrossRefPubMed Bunce C (2009) Correlation, agreement, and Bland-Altman analysis: statistical analysis of method comparison studies. Am J Ophthalmol 148:4–6CrossRefPubMed
34.
go back to reference Shardt YA, Shardt YA (2015) Using MATLAB® for statistical analysis. Statistics for chemical and process engineers: a modern approach. pp 337–362 Shardt YA, Shardt YA (2015) Using MATLAB® for statistical analysis. Statistics for chemical and process engineers: a modern approach. pp 337–362
35.
go back to reference Prism G (2020) GraphPad Prism. J Cell Biol 222:1 Prism G (2020) GraphPad Prism. J Cell Biol 222:1
36.
go back to reference Zhang H, Lai C, Liu R et al (2019) Age-specific optimization of T1-weighted brain MRI throughout infancy. Neuroimage 199:387–395CrossRefPubMed Zhang H, Lai C, Liu R et al (2019) Age-specific optimization of T1-weighted brain MRI throughout infancy. Neuroimage 199:387–395CrossRefPubMed
37.
go back to reference Stanisz GJ, Odrobina EE, Pun J et al (2005) T1, T2 relaxation and magnetization transfer in tissue at 3T. Magn Reson Med 54:507–512CrossRefPubMed Stanisz GJ, Odrobina EE, Pun J et al (2005) T1, T2 relaxation and magnetization transfer in tissue at 3T. Magn Reson Med 54:507–512CrossRefPubMed
38.
go back to reference Bojorquez JZ, Bricq S, Acquitter C et al (2017) What are normal relaxation times of tissues at 3 T? Magn Reson Imaging 35:69–80CrossRefPubMed Bojorquez JZ, Bricq S, Acquitter C et al (2017) What are normal relaxation times of tissues at 3 T? Magn Reson Imaging 35:69–80CrossRefPubMed
39.
go back to reference Wansapura JP, Holland SK, Dunn RS, Ball WS Jr (1999) NMR relaxation times in the human brain at 3.0 tesla. J Magn Reson Imaging 9:531–538CrossRefPubMed Wansapura JP, Holland SK, Dunn RS, Ball WS Jr (1999) NMR relaxation times in the human brain at 3.0 tesla. J Magn Reson Imaging 9:531–538CrossRefPubMed
40.
go back to reference Andica C, Hagiwara A, Hori M et al (2019) Review of synthetic MRI in pediatric brains: basic principle of MR quantification, its features, clinical applications, and limitations. J Neuroradiol 46:268–275CrossRefPubMed Andica C, Hagiwara A, Hori M et al (2019) Review of synthetic MRI in pediatric brains: basic principle of MR quantification, its features, clinical applications, and limitations. J Neuroradiol 46:268–275CrossRefPubMed
41.
go back to reference Wang G, Gong E, Banerjee S et al (2020) Synthesize high-quality multi-contrast magnetic resonance imaging from multi-echo acquisition using multi-task deep generative model. IEEE Trans Med Imaging 39:3089–3099CrossRefPubMed Wang G, Gong E, Banerjee S et al (2020) Synthesize high-quality multi-contrast magnetic resonance imaging from multi-echo acquisition using multi-task deep generative model. IEEE Trans Med Imaging 39:3089–3099CrossRefPubMed
42.
go back to reference Kumar S, Saber H, Charron O et al (2024) Correcting synthetic MRI contrast-weighted images using deep learning. Magn Reson Imaging 106:43–54CrossRefPubMed Kumar S, Saber H, Charron O et al (2024) Correcting synthetic MRI contrast-weighted images using deep learning. Magn Reson Imaging 106:43–54CrossRefPubMed
43.
go back to reference Tanenbaum LN, Tsiouris AJ, Johnson AN et al (2017) Synthetic MRI for clinical neuroimaging: results of the magnetic resonance image compilation (MAGiC) prospective, multicenter, multireader trial. Am J Neuroradiol 38:1103–1110CrossRefPubMedPubMedCentral Tanenbaum LN, Tsiouris AJ, Johnson AN et al (2017) Synthetic MRI for clinical neuroimaging: results of the magnetic resonance image compilation (MAGiC) prospective, multicenter, multireader trial. Am J Neuroradiol 38:1103–1110CrossRefPubMedPubMedCentral
Metadata
Title
A single 1-min brain MRI scan for generating multiple synthetic image contrasts in awake children from quantitative relaxometry maps
Authors
Anandh Kilpattu Ramaniharan
Amol Pednekar
Nehal A. Parikh
Usha D. Nagaraj
Mary Kate Manhard
Publication date
18-12-2024
Publisher
Springer Berlin Heidelberg
Keyword
Cranial MRI
Published in
Pediatric Radiology / Issue 2/2025
Print ISSN: 0301-0449
Electronic ISSN: 1432-1998
DOI
https://doi.org/10.1007/s00247-024-06113-1

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