Top

European Radiology

Published in:

01-02-2022 | Neuro

Single-direction diffusion-weighted imaging may be a simple complementary sequence for evaluating fetal corpus callosum

Authors: Cong Sun, Xinjuan Zhang, Xin Chen, Tianjia Zhu, Yufan Chen, Jinxia Zhu, Hao Huang, Guangbin Wang

Published in: European Radiology | Issue 2/2022

Abstract

Objectives

To explore the feasibility of single-direction diffusion-weighted imaging (DWI) for assessing the fetal corpus callosum (CC).

Methods

This prospective study included 67 fetuses with normal CC and 35 fetuses suspected with agenesis of the corpus callosum (ACC). The MR protocols included HASTE, TrueFISP, and single-direction DWI. Two radiologists independently evaluated the optimal visibility and the contrast ratio (CR) of the normal fetal CC. The Chi-squared test or Fisher’s exact test was used to compare the proportions of “good” visibility (score ≥ 3, and the CC was almost/entirely visible) between single-direction DWI and HASTE/TrueFISP. The CR difference between single-direction DWI and HASTE/TrueFISP was detected using the paired t-test. The diagnostic accuracies were determined by comparison with postnatal imaging. In fetuses suspected of ACC, we measured and compared the length and area of the mid-sagittal CC in the single-direction DWI images.

Results

The proportion of “good” visibility in single-direction DWI was higher than that in HASTE/TrueFISP, with p < 0.0001. The mean CR from single-direction DWI was also higher than that of TrueFISP and HASTE (both with p < 0.0001). The diagnostic accuracy of the single-direction DWI combined with HASTE/TrueFisp (97.1%, 34/35) was higher than that of the Haste/TrueFISP (74.3%, 26/35) (p = 0.013). The length and area of the PACC (p < 0.001, p = 0.001, respectively) and HCC (p < 0.001, p = 0.018, respectively) groups were significantly lower than those of the normal group.

Conclusions

The single-direction DWI is feasible in displaying fetal CC and can be a complementary sequence in diagnosing ACC.

Key Points

• We suggest a simple method for the display of the fetal CC.

• The optimal visibility and contrast ratio from single-direction DWI were higher than those from HASTE and TrueFISP.

• The diagnostic accuracy of the single-direction DWI combined with HASTE/TrueFISP sequences (97.1%, 34/35) was higher than that of the Haste/TrueFISP (74.3%, 26/35).

Available only for authorised users

Huang H, Xue R, Zhang J et al (2009) Anatomical characterization of human fetal brain development with diffusion tensor magnetic resonance imaging. J Neurosci 29:4263–4273. https://doi.org/10.1523/JNEUROSCI.2769-08.2009CrossRefPubMedPubMedCentral

Huang H, Zhang J, Jiang H et al (2005) DTI tractography based parcellation of white matter: application to the mid-sagittal morphology of corpus callosum. Neuroimage 26:195–205. https://doi.org/10.1016/j.neuroimage.2005.01.019CrossRefPubMed

Manevich-Mazor M, Weissmann-Brenner A, Bar Yosef O et al (2018) Added value of fetal MRI in the evaluation of fetal anomalies of the corpus callosum: a retrospective analysis of 78 cases. Ultraschall Med 39:513–525. https://doi.org/10.1055/s-0043-113820

Achiron R, Achiron A (2001) Development of the human fetal corpus callosum: a high-resolution, cross-sectional sonographic study: fetal corpus callosum development. Ultrasound Obstet Gynecol 18:343–347. https://doi.org/10.1046/j.0960-7692.2001.00512.xCrossRefPubMed

Cignini P, Padula F, Giorlandino M et al (2014) Reference charts for fetal corpus callosum length: a prospective cross-sectional study of 2950 fetuses. J Ultrasound Med 33:1065–1078. https://doi.org/10.7863/ultra.33.6.1065CrossRefPubMed

Horsfield MA, Jones DK (2002) Applications of diffusion-weighted and diffusion tensor MRI to white matter diseases - a review. NMR Biomed 15:570–577. https://doi.org/10.1002/nbm.787CrossRefPubMed

Feng L, Li H, Oishi K et al (2019) Age-specific gray and white matter DTI atlas for human brain at 33, 36 and 39 postmenstrual weeks. Neuroimage 185:685–698. https://doi.org/10.1016/j.neuroimage.2018.06.069CrossRefPubMed

Vasung L, Charvet CJ, Shiohama T et al (2019) Ex vivo fetal brain MRI: recent advances, challenges, and future directions. Neuroimage 195:23–37. https://doi.org/10.1016/j.neuroimage.2019.03.034CrossRefPubMed

Ouyang A, Jeon T, Sunkin SM et al (2015) Spatial mapping of structural and connectional imaging data for the developing human brain with diffusion tensor imaging. Methods 73:27–37. https://doi.org/10.1016/j.ymeth.2014.10.025CrossRefPubMed

10.

Song JW, Gruber GM, Patsch JM et al (2018) How accurate are prenatal tractography results? A postnatal in vivo follow-up study using diffusion tensor imaging. Pediatr Radiol 48:486–498. https://doi.org/10.1007/s00247-017-3982-yCrossRefPubMedPubMedCentral

11.

Mitter C, Prayer D, Brugger PC et al (2015) In vivo tractography of fetal association fibers. PLoS One 10:e0119536. https://doi.org/10.1371/journal.pone.0119536CrossRefPubMedPubMedCentral

12.

Ouyang M, Dubois J, Yu Q et al (2019) Delineation of early brain development from fetuses to infants with diffusion MRI and beyond. Neuroimage 185:836–850. https://doi.org/10.1016/j.neuroimage.2018.04.017CrossRefPubMed

13.

Huang H, Vasung L (2014) Gaining insight of fetal brain development with diffusion MRI and histology. Int J Dev Neurosci 32:11–22. https://doi.org/10.1016/j.ijdevneu.2013.06.005CrossRefPubMed

14.

Song L, Mishra V, Ouyang M et al (2017) Human fetal brain connectome: structural network development from middle fetal stage to birth. Front Neurosci 11:561. https://doi.org/10.3389/fnins.2017.00561CrossRefPubMedPubMedCentral

15.

Huang H (2010) Structure of the fetal brain: what we are learning from diffusion tensor imaging. Neuroscientist 16:634–649. https://doi.org/10.1177/1073858409356711CrossRefPubMed

16.

Huang H, Zhang J, Wakana S et al (2006) White and gray matter development in human fetal, newborn and pediatric brains. Neuroimage 33:27–38. https://doi.org/10.1016/j.neuroimage.2006.06.009CrossRefPubMed

17.

Milos R-I (2020) Developmental dynamics of the periventricular parietal crossroads of growing cortical pathways in the fetal brain - in vivo fetal MRI with histological correlation. Nuerolmage 210:116553CrossRef

18.

Khan S, Vasung L, Marami B et al (2019) Fetal brain growth portrayed by a spatiotemporal diffusion tensor MRI atlas computed from in utero images. Neuroimage 185:593–608. https://doi.org/10.1016/j.neuroimage.2018.08.030CrossRefPubMed

19.

Jakab A, Tuura R, Kellenberger C, Scheer I (2017) In utero diffusion tensor imaging of the fetal brain: a reproducibility study. Neuroimage Clin 15:601–612. https://doi.org/10.1016/j.nicl.2017.06.013CrossRefPubMedPubMedCentral

20.

Hunt D, Dighe M, Gatenby C, Studholme C (2020) Automatic, age consistent reconstruction of the corpus callosum guided by coherency from in utero diffusion-weighted MRI. IEEE Trans Med Imaging 39:601–610. https://doi.org/10.1109/TMI.2019.2932681CrossRefPubMed

21.

Marami B, Mohseni Salehi SS, Afacan O et al (2017) Temporal slice registration and robust diffusion-tensor reconstruction for improved fetal brain structural connectivity analysis. Neuroimage 156:475–488. https://doi.org/10.1016/j.neuroimage.2017.04.033

22.

Scola E, Sirgiovanni I, Avignone S et al (2016) Fetal development of the corpus callosum: insights from a 3T DTI and tractography study in a patient with segmental callosal agenesis. Neuroradiol J 29:323–325. https://doi.org/10.1177/1971400916665390CrossRefPubMedPubMedCentral

23.

Tagliafico A, Succio G, Neumaier CE et al (2012) Brachial plexus assessment with three-dimensional isotropic resolution fast spin echo MRI: comparison with conventional MRI at 3.0 T. Br J Radiol 85:e110–e116. https://doi.org/10.1259/bjr/28972953CrossRefPubMedPubMedCentral

24.

Yoneyama M, Takahara T, Kwee TC et al (2013) Rapid high resolution MR Neurography with a diffusion-weighted pre-pulse. Magn Reson Med Sci 12:111–119. https://doi.org/10.2463/mrms.2012-0063CrossRefPubMed

25.

Ghi T, Carletti A, Contro E et al (2010) Prenatal diagnosis and outcome of partial agenesis and hypoplasia of the corpus callosum. Ultrasound Obstet Gynecol 35:35–41. https://doi.org/10.1002/uog.7489CrossRefPubMed

26.

Takahara T, Hendrikse J, Kwee TC et al (2010) Diffusion-weighted MR neurography of the sacral plexus with unidirectional motion probing gradients. Eur Radiol 20:1221–1226. https://doi.org/10.1007/s00330-009-1665-2CrossRefPubMed

27.

Bydder GM, Rutherford MA, Hajnal JV (2001) How to perform diffusion-weighted imaging. Childs Nerv Syst 17:195–201. https://doi.org/10.1007/s003810000281CrossRefPubMed

28.

Liu B, Xin W, Tan J-R et al (2019) Myelin sheath structure and regeneration in peripheral nerve injury repair. Proc Natl Acad Sci 116:22347–22352. https://doi.org/10.1073/pnas.1910292116CrossRefPubMedPubMedCentral

29.

Bando Y (2019) Roads to formation of normal myelin structure and pathological myelin structure. In: Sango K, Yamauchi J, Ogata T, Susuki K (eds) Myelin. Springer Singapore, Singapore, pp 257–264CrossRef

30.

Jiang S, Xue H, Counsell S et al (2009) Diffusion tensor imaging (DTI) of the brain in moving subjects: application to in-utero fetal and ex-utero studies. Magn Reson Med 62:645–655. https://doi.org/10.1002/mrm.22032CrossRefPubMed

31.

Diogo MC, Prayer D, Gruber GM et al (2019) Echo-planar FLAIR sequence improves subplate visualization in fetal MRI of the brain. Radiology 292:159–169. https://doi.org/10.1148/radiol.2019181976CrossRefPubMed

32.

Kasprian G, Brugger PC, Schöpf V et al (2013) Assessing prenatal white matter connectivity in commissural agenesis. Brain 136:168–179. https://doi.org/10.1093/brain/aws332CrossRefPubMed

33.

Mitter C, Jakab A, Brugger PC et al (2015) Validation of in utero tractography of human fetal commissural and internal capsule fibers with histological structure tensor analysis. Front Neuroanat 9:164. https://doi.org/10.3389/fnana.2015.00164CrossRefPubMedPubMedCentral

34.

Kuklisova-Murgasova M, Quaghebeur G, Rutherford MA et al (2012) Reconstruction of fetal brain MRI with intensity matching and complete outlier removal. Med Image Anal 16:1550–1564. https://doi.org/10.1016/j.media.2012.07.004CrossRefPubMedPubMedCentral

35.

Kuklisova-Murgasova M, Lockwood Estrin G, Nunes RG et al (2018) Distortion correction in fetal EPI Using non-rigid registration with a Laplacian constraint. IEEE Trans Med Imaging 37:12–19. https://doi.org/10.1109/TMI.2017.2667227CrossRefPubMed

36.

Deprez M, Price A, Christiaens D et al (2020) Higher order spherical harmonics reconstruction of fetal diffusion MRI with intensity correction. IEEE Trans Med Imaging 39:1104–1113. https://doi.org/10.1109/TMI.2019.2943565CrossRefPubMed

37.

Gholipour A, Rollins CK, Velasco-Annis C et al (2017) A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth. Sci Rep 7:476. https://doi.org/10.1038/s41598-017-00525-wCrossRefPubMedPubMedCentral

Title: Single-direction diffusion-weighted imaging may be a simple complementary sequence for evaluating fetal corpus callosum
Authors: Cong Sun
Xinjuan Zhang
Xin Chen
Tianjia Zhu
Yufan Chen
Jinxia Zhu
Hao Huang
Guangbin Wang
Publication date: 01-02-2022
Publisher: Springer Berlin Heidelberg
Published in: European Radiology / Issue 2/2022
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-021-08176-2

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Single-direction diffusion-weighted imaging may be a simple complementary sequence for evaluating fetal corpus callosum

Abstract

Objectives

Methods

Results

Conclusions

Key Points

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Objectives

Methods

Results

Conclusions

Key Points

Please log in to get access to this content

Other articles of this Issue 2/2022

Virtual clinical trial to compare cancer detection using combinations of 2D mammography, digital breast tomosynthesis and synthetic 2D imaging

Evaluation of a fractional-order calculus diffusion model and bi-parametric VI-RADS for staging and grading bladder urothelial carcinoma

MRI software for diffusion-perfusion mismatch analysis may impact on patients’ selection and clinical outcome

Deep learning radiomic nomogram to predict recurrence in soft tissue sarcoma: a multi-institutional study

Comparison of low-contrast detectability between uniform and anatomically realistic phantoms—influences on CT image quality assessment

Clinical and prognostic significance of emergency MRI findings in neck infections