Article Figures & Data
Figures
- Fig 1.
Anatomic, MD, and FA map of a neonate. A, At 30 weeks' gestational age; B, at term age; and C, after perinatal asphyxia scanned on day 4, with abnormal low signal intensity in the central gray matter on the MD map. Notice the decrease in MD values and increase in FA values between the preterm and a term brain. The MD maps and FA maps are equally scaled for the 3 subjects, respectively, 0–2 × 10−3 mm2/s and 0–1.
- Fig 2.
Effects of motion and pulsation. A, Almost complete signal loss caused by head motion; B, signal drop-out caused by pulsation; and C, 3-plane view in which the effects of pulsation (arrow) and motion (arrowhead) are visible.
- Fig 3.
Effects of different tensor estimation methods. Data of 2 datasets are displayed: on the left, data without gross motion artifacts, and on the right, data with gross motion artifacts for one of the gradient directions. Both MD and FA maps are depicted, showing no visible differences for the good dataset and clearly visible differences for the dataset with motion. Especially the FA maps show that the ordinary least-squares (OLS) estimation results in very high FA values that are not related to the known anatomy. In the graphs, the pixel value of the OLS or weighted least-squares (WLS) tensor estimation is plotted against the pixel value of the RESTORE tensor estimation (x-axis), and the line of identity is included. The spread around the line of identity is broader for the dataset, with motion indicating an effect of the tensor estimation method on the resulting FA or MD value. For the graphs, the images were eroded to exclude the outer rim, which contains poor-quality data caused by partial volume effects. Scaling: MD, 0–2 × 10−3 mm2/s; FA, 0–1.
- Fig 4.
Examples of residuals. A through D, Residuals from a subject with good data quality. Higher residuals are present at the border and in the ventricles. A and B, Axial images; C, coronal view; and D, sagittal view. E and F, Effects of motion and eddy current correction with higher residuals before correction and lower values after correction; G, higher residuals caused by ghosting; H, high residuals caused by susceptibility artifacts; I through L, residuals from a subject with gross motion artifacts showing both sections with low (no motion) and high (motion) residuals. The sagittal view (L) shows a pattern with alternating sections of high and lower residuals. Each subject is individually scaled.
- Fig 5.
Detection of outliers. A, Percentage of outliers per DWI is a tool to indicate potential problems with the DTI dataset. In this case, DWI 11 and 12 have a high percentage of outliers. B, Percentage outliers per section facilitates easy detection of the problematic sections. During the acquisition of gradient direction 12, several sections are affected by movement of the infant. C and D, Examples of the resulting images; E, nonaffected image. Because of the interleaved section acquisition, there is an alternating pattern for the odd and even sections. Scaling is similar for DWI.
- Fig 6.
Outlier profile for different datasets. Outliers are only depicted for those sections that contain >1000 voxels with signal intensity. A, Dataset without gross motion artifacts; B, dataset with 1 corrupted gradient direction; C, dataset with multiple corrupted gradient directions. Scaling is for 0–40% outliers.
- Fig 7.
Quality assessment in 2 term-born neonates with brain pathology. The damaged brain areas have much lower MD (A and E) and apparent high FA (B and F) values. The percentage outliers (C and G) are low and are distributed uniformly. Because the residuals are also dependent on the underlying MD and FA values, they (D and H) are large in the damaged areas. Scaling: MD, 0–2 × 10−3 mm2/s; FA, 0–1; outliers, 0–40%.
Tables
PMA FS Neo Coil TR TE FOV Thk Image Resolution b-Value No. b = 0 No. Dir Sedation Reference 40–45 3 − 7745 48 180 2 1.41 800 1 32 + van Pul et al67 Term 3 − 8400 84 220 2.2 2.20 750 ? ? ± Wintermark et al68 31–41 1.5 + 4000 60 210 3.0 0.82 1000 1 ? − Arrigoni et al69 38–41 3 − >3000 71 150 1.9 1.88 700 5 30 − Oishi et al70 Term 3 7680 82 2.0 2.00 1000 7 42 − Wang et al71 37–43 1.5 6000 88 200 2.5 1.56 1000 1 15 + Hasegawa et al72 40–44 3 7465 54 2.0 1.40 1000 1 32 + de Bruine et al73 Term 1.5 + 4047 59 210 3.0 0.82 1000 1 6 − Righini et al74 24–33/TEA 1.5 + 7000 100 3.0 1.40 600 1 6 − Bonifacio et al75 24–33/TEA 1.5 + 4900 104 160 3.0 1.30 600/700 1 12 − Bonifacio et al75 Term 3 5200 73 2.0 2.00 1000 1 6 − Gilmore et al76 25–32 1.5 + 9150 98 200 3.0 0.78 1000 1 25 − Dudink et al77 35–42 1.5 − 5888 92 220 2.3 2.00 600 1 32 − Liu et al78 39–41 1.5 − 7000 74 180 2.2 1.40 700 1 15 + Skiold et al5 Term 1.5 − 8000 100 240 3.0 1.88 700 1 10 − Malik et al79 Term 1.5 − 6000 106 230 2.5 0.90 1100 16 44 − Rose et al80 38–45 3 − 8000 79 224 2.0 1.75 750 1 15 ± Anjari et al13 30 1.5 + 11725 90.5 220 3.0 0.86 750 3 25 − Erasmus MC – Sophia Term 1.5 + 11725 85.6 220 3.0 0.66 1000 3 25 − Erasmus MC – Sophia Note:—Image resolution is all squared (mm); b-values are s/mm2.
PMA indicates postmenstrual age at image acquisition (weeks); TEA, term equivalent age; FS, field strength (T); TR, repetition time (ms); TE, echo time (ms); FOV, field of view (mm); Thk, section thickness (mm); No. Dir, number of diffusion encoding directions; +, used; and −, not used; Neo, neonatal; Erasmus MC-Sophia is the hospital where the authors are affiliated.
- Table 2:
Outliers in a small pilot study (27 preterm infants scanned at 30 weeks' gestational age)
>10% Outliers >30% Outliers >50% Outliers No. of subjects >10 sections 27 15 10 No. of subjects >20 sections 26 10 1 Mean No. of sections with outliers 50 15 9 Range No. of sections with outliers 17–79 1–38 0–24 Mean percentage of sections with outliers 9.5 2.9 1.7 Range of percentage of sections with outliers 3.3–15.7 0.2–7.0 0.0–4.4
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