R Ber1, D Hoffman2, C Hoffman3,4, A Polat2, E Derazne4, A Mayer3, E Katorza2. 1. From the Departments of Obstetrics and Gynecology (R.B., D.H., A.P., E.K.) berlerner@gmail.com. 2. From the Departments of Obstetrics and Gynecology (R.B., D.H., A.P., E.K.). 3. Diagnostic Imaging (C.H., A.M.), Chaim Sheba Medical Center, Tel Hashomer, affiliated with the Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel. 4. Sackler Faculty of Medicine (C.H., E.D.), Tel-Aviv University, Tel-Aviv, Israel.
Abstract
BACKGROUND AND PURPOSE: Measuring the volume of fetal brain structures is challenging due to fetal motion, low resolution, and artifacts caused by maternal tissue. Our aim was to introduce a new, simple, Matlab-based semiautomated method to measure the volume of structures in the fetal brain and present normal volumetric curves of the structures measured. MATERIALS AND METHODS: The volume of the supratentorial brain, left and right hemispheres, cerebellum, and left and right eyeballs was measured retrospectively by the new semiautomated method in MR imaging examinations of 94 healthy fetuses. Four volume ratios were calculated. Interobserver agreement was calculated with the intraclass correlation coefficient, and a Bland-Altman plot was drawn for comparison of manual and semiautomated method measurements of the supratentorial brain. RESULTS: We present normal volumetric curves and normal percentile values of the structures measured according to gestational age and of the ratios between the cerebellum and the supratentorial brain volume and the total eyeball and the supratentorial brain volume. Interobserver agreement was good or excellent for all structures measured. The Bland-Altman plot between manual and semiautomated measurements showed a maximal relative difference of 7.84%. CONCLUSIONS: We present a technologically simple, reproducible method that can be applied prospectively and retrospectively on any MR imaging protocol, and we present normal volumetric curves measured. The method shows results like manual measurements while being less time-consuming and user-dependent. By applying this method on different cranial and extracranial structures, anatomic and pathologic, we believe that fetal volumetry can turn from a research tool into a practical clinical one.
BACKGROUND AND PURPOSE: Measuring the volume of fetal brain structures is challenging due to fetal motion, low resolution, and artifacts caused by maternal tissue. Our aim was to introduce a new, simple, Matlab-based semiautomated method to measure the volume of structures in the fetal brain and present normal volumetric curves of the structures measured. MATERIALS AND METHODS: The volume of the supratentorial brain, left and right hemispheres, cerebellum, and left and right eyeballs was measured retrospectively by the new semiautomated method in MR imaging examinations of 94 healthy fetuses. Four volume ratios were calculated. Interobserver agreement was calculated with the intraclass correlation coefficient, and a Bland-Altman plot was drawn for comparison of manual and semiautomated method measurements of the supratentorial brain. RESULTS: We present normal volumetric curves and normal percentile values of the structures measured according to gestational age and of the ratios between the cerebellum and the supratentorial brain volume and the total eyeball and the supratentorial brain volume. Interobserver agreement was good or excellent for all structures measured. The Bland-Altman plot between manual and semiautomated measurements showed a maximal relative difference of 7.84%. CONCLUSIONS: We present a technologically simple, reproducible method that can be applied prospectively and retrospectively on any MR imaging protocol, and we present normal volumetric curves measured. The method shows results like manual measurements while being less time-consuming and user-dependent. By applying this method on different cranial and extracranial structures, anatomic and pathologic, we believe that fetal volumetry can turn from a research tool into a practical clinical one.
Authors: S Fried; M Gafner; D Jeddah; N Gosher; D Hoffman; R Ber; A Mayer; E Katorza Journal: AJNR Am J Neuroradiol Date: 2021-08-12 Impact factor: 4.966
Authors: C Jandeaux; G Kuchcinski; C Ternynck; A Riquet; X Leclerc; J-P Pruvo; G Soto-Ares Journal: AJNR Am J Neuroradiol Date: 2019-10-17 Impact factor: 3.825