Quantitative ultrasonography of the periventricular white and grey matter of the developing brain.
This study addresses the value of operator-independent computer processing of ultrasonograms of the developing brain. With this aim, routine cranial ultrasonograms obtained from 39 term and preterm infants without clinical or sonographic evidence of brain damage were analyzed by five observers. The procedure, respectively, included: 1. the definition of four regions of interest (ROI), one white matter and one grey matter area on each side of the brain; 2. digitization of the sonogram data within these ROIs; 3. correction for the equipment settings, using data from a tissue-mimicking phantom as a reference; and 4. calculation of four sonogram characteristics (i.e., mean echo level, MEAN, signal-to-noise ratio, SNR, and axial and lateral correlation, CORAX and CORLAT, of the echo level co-occurrence matrix). Significant differences between both sides of the brain or a significant influence of ROI size were not found. The interobserver spread was considerable, but less than the intersubject spread. Two sonogram characteristics seemed strongly correlated in white and grey matter (CORAX and CORLAT) and another only in white matter (SNR with CORAX and CORLAT). MEAN seemed not to be correlated with any other characteristic. Furthermore, it was found that maturation equally decreases white and grey matter MEAN and, thus, hardly affects the ratio between the two. An effect on the other sonogram characteristics was only found in the white matter (i.e., an increase of SNR and a decrease of CORAX and CORLAT). Except for MEAN, the grey matter sonogram characteristics seem hardly affected by maturation. In view of these findings, we conclude that quantitative ultrasonography reveals white and grey matter maturation and, furthermore, provides a conceptional-age-independent reference (MEAN white:grey matter ratio) that might be found to facilitate the detection of pathologic brain alterations.
Mullaart
R A
RA
Child Neurology Department, Nijmegen Pediatric University Hospital, The Netherlands. r.mullaart@cksiknc.azn.nl
Thijssen
J M
JM
Rotteveel
J J
JJ
Valckx
F M
FM
van Geemen
A J
AJ
D000367:Age Factors; D001921:Brain / Q000254:growth & development*; D002552:Cerebral Ventricles / Q000000981:diagnostic imaging*; D002675:Child, Preschool; D006801:Humans; D007223:Infant; D016014:Linear Models; D015588:Observer Variation; D019047:Phantoms, Imaging; D012016:Reference Values; D018709:Statistics, Nonparametric; D014463:Ultrasonography / Q000295:instrumentation / Q000379:methods / Q000706:statistics & numerical data