Corpus callosum and subarachnoid space measurements in fetuses with congenital heart disease: a prospective case-control study

Verda Alpay; Fırat Ersan; Barış Boza

doi:10.14366/usg.25254

. 2026 Jun 20;45(5):482–490. doi: 10.14366/usg.25254

Corpus callosum and subarachnoid space measurements in fetuses with congenital heart disease: a prospective case-control study

Verda Alpay ^1,^✉, Fırat Ersan ¹, Barış Boza ¹

PMCID: PMC13620452 PMID: 42687692

Abstract

Purpose

This study investigated the associations of prenatally diagnosed congenital heart disease (CHD) with head circumference (HC) and supratentorial brain structures, specifically the corpus callosum (CC) and subarachnoid space (SAS), and determined whether these measurements varied according to expected fetal brain oxygen delivery.

Methods

This prospective case-control study included 102 pregnancies at 32 to 36 weeks of gestation: 51 fetuses with CHD and 51 healthy controls. CHD cases were grouped according to expected fetal brain oxygen delivery as class A (n=26, reduced supply) or class B (n=25, normal supply). Measurements included CC length, the heights of the genu, body, and splenium, SAS, and HC.

Results

Gestational age at delivery and birth weight were significantly lower in the CHD group than in controls (both P<0.01). Total CC length and all segmental heights (genu, body, and splenium) were significantly reduced in both CHD subgroups (class A and class B) compared with healthy controls (all P<0.01). However, no significant differences in CC parameters were observed between class A and class B (P>0.99). SAS (P=0.267) and HC (P=0.083) measurements did not differ significantly among the three study groups.

Conclusion

Fetuses with CHD exhibited significant structural reductions across all CC dimensions, independent of the expected cerebral oxygen delivery pattern, whereas global parameters (HC and SAS) did not differ significantly. These findings suggest that CHD-related prenatal brain alterations may involve white matter development even without measurable changes in global cranial parameters, supporting CC biometry as a potentially sensitive marker for early neurodevelopmental risk assessment.

Keywords: Congenital heart defects, Corpus callosum, Subarachnoid space, Head circumference, Neurosonography, Prenatal diagnosis

Graphical abstract

Introduction

Congenital heart disease (CHD), which affects up to 1% of live births, is significantly associated with neurodevelopmental impairment [1]. Although children with CHD rarely present with obvious neurological disabilities, many experience neurodevelopmental difficulties, which are now considered among the most important comorbidities in patients with CHD [2,3]. These difficulties include impairments in cognition, behavior, gross and fine motor skills, memory, speech, and overall intellectual function, and may persist into adolescence and young adulthood, even with optimal perinatal and perioperative care and in the absence of genetic syndromes [2,4].

Neurological impairment in CHD has historically been attributed to open-heart surgical repair and hypothermic circulatory arrest [5]. However, the etiology of neurodevelopmental difficulties in CHD is multifactorial and includes genetic predisposition, altered fetal hemodynamics, and potential placental dysfunction [3]. The detection of brain injury and immaturity on magnetic resonance imaging (MRI), even before surgery, suggests that disturbances in brain growth occur during fetal life [6]. In these cases, altered cardiovascular physiology may reduce cerebral oxygen and substrate delivery, thereby compromising normal brain growth and maturation [3].

Advanced fetal imaging techniques, such as neurosonography and MRI, have provided important insights into prenatal brain development in CHD. These studies have revealed a spectrum of abnormalities, ranging from macrostructural changes, such as reduced brain volume and altered cortical folding, to microstructural alterations, including white matter immaturity [7,8]. The corpus callosum (CC), the largest interhemispheric white matter commissure, is particularly sensitive to prenatal insults, and its development may serve as an indicator of diffuse white matter loss and overall brain health [9]. Previous research has shown that fetuses with CHD often have smaller CC dimensions than healthy controls, with more pronounced reductions in cases with poorer expected brain oxygen supply [9].

Despite increasing recognition of prenatal brain abnormalities in CHD, the effects of different fetal brain oxygen delivery patterns on specific brain structures require further investigation. Although structural brain abnormalities have been demonstrated in CHD, the relative contribution of CHD itself versus altered oxygenation remains unclear. In addition, the association of these structural changes with head circumference (HC) and broader supratentorial parameters, such as the subarachnoid space (SAS), a potential indirect marker of brain atrophy, has not been fully delineated [10].

This study aimed to address these gaps by measuring and comparing key fetal brain structures, with particular focus on the CC and SAS. Specifically, total CC length, the heights of its three subdivisions (the genu, body, and splenium), SAS, and HC were evaluated in fetuses with CHD and compared with those in healthy pregnancies. Subgroup differences were further explored in relation to anticipated fetal brain oxygen delivery by classifying CHD cases as class A (reduced oxygen supply) or class B (normal oxygen supply). By analyzing these parameters, this study provides further insight into the prenatal neurological impact of CHD.

Materials and Methods

Compliance with Ethical Standards

This prospective case-control study was conducted at a single tertiary perinatology center from October 2024 to September 2025. This study was approved by Başakşehir Çam and Sakura City Hospital Review Board and Ethics Committee (approval No. 186; October 16, 2024). The study was conducted in accordance with the Declaration of Helsinki, and written informed consent was obtained from all participants before inclusion.

Study Population

A total of 102 fetuses were evaluated. The study group included 51 fetuses diagnosed with isolated CHD between 32 and 36 weeks of gestation, and the control group included 51 gestational age-matched fetuses from uneventful pregnancies with structurally normal hearts and no other detected anomalies. The inclusion criteria were as follows: (1) pregnant women 18–40 years of age, (2) singleton pregnancy, (3) gestational age of 32 to 36 weeks confirmed by the last menstrual period and first-trimester crown-rump length measurement, and (4) absence of fetal growth restriction and associated structural or genetic anomalies. Cases with additional structural or chromosomal anomalies, perinatal infection, chronic maternal disease potentially affecting the fetal brain, or inadequate visualization preventing the required measurements were excluded. Maternal demographic characteristics, body mass index (BMI), pregnancy course, and birth parameters, including gestational age at delivery, mode of delivery, and birth weight, were collected from the hospital database.

The 51 fetuses with CHD were divided into two categories according to the expected effect of fetal cardiac lesions on cerebral oxygenation, as described by Masoller et al. [5]. Class A CHD included cases with lesions expected to cause a moderate to severe reduction in brain oxygen supply, including severe left outflow tract obstruction (hypoplastic left heart syndrome [HLHS], critical aortic stenosis, and coarctation of the aorta) with reverse flow in the aortic isthmus, transposition of the great arteries (TGA), and transposition-type double-outlet right ventricle (DORV). Class B CHD included cases expected to have a nearly normal pattern of fetal brain oxygen delivery, including ventricular septal defects, hypoplastic right heart, tetralogy of Fallot, congenitally corrected TGA, non-transposition-type DORV, Ebstein anomaly, and right aortic arch.

Neurosonographic and echocardiographic examinations were performed by experienced maternal-fetal medicine specialists (V.A., B.B., and F.E.) using Hitachi Arietta 850 ultrasound devices (Hitachi, Tokyo, Japan) equipped with 3.5-MHz convex transabdominal and 2–10-MHz transvaginal probes, in accordance with International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) guidelines [11,12]. Neurosonography was performed using both transabdominal and transvaginal approaches to optimize image quality according to fetal position and maternal habitus. In all cases, CC measurements were obtained exclusively from an adequate midsagittal plane that fulfilled strict anatomical criteria, regardless of probe type. The same measurement landmarks and standardized protocols were applied to both transabdominal and transvaginal acquisitions in accordance with ISUOG guidelines [11]. The CC was identified in this plane as a slightly hypoechoic structure with visible genu, body, and splenium (Fig. 1) [11]. The image set used for CC assessment met strict criteria, including visualization of the cavum septi pellucidi, thalamus, midbrain, cerebellar vermis, and cisterna magna [13,14]. CC measurements included total length and the height of the genu, body, and splenium. CC length was measured as the outer-to-outer length from the most anterior part of the genu to the most posterior part of the splenium along a straight rostrocaudal line [14]. Height measurements of the genu, body, and splenium were obtained between the inner borders within the hypoechoic area of the CC (Fig. 2) [14]. To evaluate the SAS, the anterior craniocortical width was measured in the coronal plane at the level of the foramen of Monro and was defined as the longest distance between the inner table of the calvarium and the cortical surface of the brain (Fig. 3) [15]. HC was also recorded. Each measurement was repeated three times by the same operator, and the mean of the three measurements was used to minimize intra-observer variability.

Fig. 1. — The CC length was measured as the outer-to-outer distance from the most anterior part of the genu to the most posterior part of the splenium along a straight rostrocaudal line.

Fig. 2. — The height measurements of the genu, body, and splenium were obtained as the inner-to-inner distances within the hypoechoic area.

Fig. 3. — The anterior craniocortical width was measured at the level of the foramen of Monro as the longest distance between the inner table of the calvarium and the cortical surface.

Inter- and intra-observer reliability for CC measurements was assessed in a randomly selected subset of 25 fetuses. Inter-observer agreement was evaluated by three independent observers, and intra-observer reliability was assessed using repeated measurements by the same observer at different time points. Intraclass correlation coefficients (ICCs) were calculated using a two-way random-effects model for absolute agreement. ICC values exceeded 0.90 for all CC parameters, indicating excellent reproducibility.

Statistical Analysis

Statistical analyses were performed using SPSS version 24.0 (IBM Corp., Armonk, NY, USA). Before group comparisons, the distribution of continuous variables was assessed for normality by examining histograms, evaluating skewness and kurtosis, and applying the Kolmogorov-Smirnov and Shapiro-Wilk tests. Normally distributed continuous variables are expressed as mean±standard deviation and were compared using one-way analysis of variance (ANOVA). The Bonferroni post hoc test was used for pairwise comparisons. Non-normally distributed variables are expressed as median (minimum-maximum) and were compared using the Mann-Whitney U test. Categorical variables are presented as frequencies and percentages and were compared using the chi-square test. A P-value <0.05 was considered to indicate statistical significance.

Total CC length was prespecified as the primary outcome measure because of its established role as a global marker of white matter development. CC segmental heights, SAS, and HC were considered secondary exploratory outcomes, and the associated findings should be interpreted accordingly.

Adjusted analyses were performed using analysis of covariance (ANCOVA) to account for potential confounding. CC measurements were entered as dependent variables, group status (CHD vs. control) as the fixed factor, and gestational age at examination and estimated fetal weight (EFW) as covariates. Adjusted group means and corresponding P-values were reported.

An a priori power analysis was performed using G*Power version 3.1.9.6 (University of Düsseldorf, Düsseldorf, Germany) to estimate the required sample size. Based on the study by Perez-Cruz et al. [9], which reported a medium effect size (Cohen f=0.30), the minimum required total sample size for a one-way ANOVA with three groups was 102 participants (power=0.80, α=0.05), corresponding to 51 controls, 26 class A cases, and 25 class B cases.

Results

A total of 102 pregnant women were enrolled, including 51 carrying fetuses diagnosed with CHD and 51 with healthy pregnancies. Fetuses with CHD were further categorized into two subgroups according to expected fetal brain oxygen delivery. Class A included fetuses with expected reduced oxygen supply (n=26), whereas class B included fetuses with expected normal oxygen supply (n=25). Demographic characteristics and perinatal outcomes of the study and control groups are presented in Table 1.

Table 1.

Demographic characteristics and perinatal outcomes of fetuses with CHD and controls

	Total (n=102)	CHD (n=51)	Control (n=51)	P-value^a)
Age (year)^b)	29.6±5.09	30.16±5.47	29.04±4.66	0.270
Gravida (n)^c)	2 (1–9)	2 (1–9)	2 (1–7)	0.555
Parity (n)^c)	1 (0–5)	1 (0–5)	1 (0–4)	0.550
BMI (kg/m²)^b)	29.09±3.69	29.14±3.57	29.04±3.83	0.897
GA at diagnosis^b)	33.26±0.95	33.17±0.85	33.33±1.05	0.332
GA at delivery (week)^b)	38.54±1.38	38.15±1.44	38.93±1.22	0.004
Birth weight (g)^b)	3,218±429	3,100±487	3,337±325	0.005
Birth method^d)
SVB	41 (40.2)	11 (21.5)	30 (58.8)	0.001
CS	61 (59.8)	40 (78.5)	21 (41.2)

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CHD, congenital heart disease; BMI, body mass index; GA, gestational age; SVB, spontaneous vaginal birth; CS, cesarean section.

^a)P-values<0.05 were considered statistically significant. ^b)Normally distributed continuous variables are expressed as mean±standard deviation and were compared using the Student t-test. ^c)Non-normally distributed data are expressed as median (minimum–maximum) and were compared using the Mann-Whitney U test. ^d)Categorical variables are presented as number (%) and were compared using the chi-square test.

The mean maternal age and gestational age at diagnosis were 30.16±5.47 years and 33.17±0.85 weeks in the CHD group and 29.04±4.66 years and 33.33±1.05 weeks in the control group, respectively. No statistically significant differences were observed in these parameters (P=0.270 and P=0.332, respectively). Similarly, maternal BMI did not differ significantly between groups (29.14±3.57 vs. 29.04±3.83, P=0.897). Obstetric history, including gravida and parity, also did not differ significantly between groups (P=0.555 and P=0.550, respectively). In contrast, gestational age at delivery and birth weight were significantly lower in the CHD group than in the control group (P=0.004 and P=0.005, respectively). Consistent with these findings, the cesarean section rate was significantly higher in the CHD group (P=0.001).

The distribution of CHD subtypes is presented in Table 2. HLHS was the most frequent class A lesion, whereas ventricular septal defect was the most common class B lesion.

Table 2.

Number of CHD cases by expected fetal brain oxygen delivery

Type of CHD	CHD class A (n=26)	CHD class B (n=25)
Hypoplastic left heart syndrome	13	-
Transposition of the great arteries	8	-
Critical aortic stenosis	2	-
Coarctation of aorta	2	-
DORV, transposition type	1	-
Tetralogy of Fallot	-	5
Ventricular septal defect	-	6
Pulmonary atresia with VSD	-	2
Hypoplastic right heart	-	3
ccTGA	-	3
DORV, non-transposition type	-	2
Right aortic arch	-	2
Ebstein anomaly	-	2

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CHD, congenital heart disease; DORV, double-outlet right ventricle; VSD, ventricular septal defect; ccTGA, congenitally corrected transposition of the great arteries.

Comparisons of supratentorial structure measurements among class A CHD, class B CHD, and control groups are summarized in Table 3. Mean CC length (40.9±2.69 mm, 40.8±3.39 mm, and 42.7±2.20 mm), genu height (3.62±0.56 mm, 3.63±0.86 mm, and 4.44±0.70 mm), body height (2.84±0.53 mm, 2.81±0.54 mm, and 3.59±0.40 mm), and splenium height (3.91±0.51 mm, 3.82±0.60 mm, and 4.81±0.67 mm) were significantly lower in both CHD groups than in controls. One-way ANOVA confirmed significant group differences in CC length (F_2,99=6.48, P=0.002), genu height (F_2,99=16.5, P=0.001), body height (F_2,99=32.8, P=0.001), and splenium height (F_2,99=29.5, P=0.001). Conversely, SAS, measured as anterior craniocortical width (F_2,99=1.33, P=0.267), and HC (F_2,99=43.5, P=0.083) were comparable among the study groups. After adjustment using ANCOVA for gestational age at examination and EFW, fetuses with CHD continued to show significantly smaller CC length and segmental measurements than controls (all adjusted P=0.002). The direction and magnitude of the differences were consistent with the unadjusted analyses. Comparisons between class A and class B CHD groups showed small effect sizes for CC measurements (Cohen d, approximately 0.15–0.30), with 95% confidence intervals crossing zero, indicating that differences between subgroups could not be statistically demonstrated.

Table 3.

Comparison of corpus callosum, subarachnoid space, and head circumference measurements in fetuses with congenital heart disease

	Class A (n=26)	Class B (n=25)	Control (n=51)	P-value^a)
Total corpus callosum length (mm)^b)	40.9±2.69	40.8±3.39	42.7±2.20	0.002
Genu height (mm)^b)	3.62±0.56	3.63±0.86	4.44±0.70	0.001
Body height (mm)^b)	2.84±0.53	2.81±0.54	3.59±0.40	0.001
Splenium height (mm)^b)	3.91±0.51	3.82±0.60	4.81±0.67	0.001
Subarachnoid space (anterior craniocortical width) (mm)^b)	2.66±0.62	2.68±0.65	2.90±0.79	0.267
Head circumference (mm)^b)	302.6±13.7	306.7±11.3	309.5±13	0.083

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^a)P<0.05 were considered statistically significant. ^b)Normally distributed continuous variables are expressed as mean±standard deviation and were compared using one-way analysis of variance with the Bonferroni post hoc test for pairwise comparisons.

Post hoc Bonferroni analysis revealed that CC length, genu height, body height, and splenium height were significantly reduced in both class A and class B compared with controls (all P=0.001), whereas no significant differences were detected between class A and class B (P>0.99). The distribution of total CC length across the study groups is shown in Fig. 4.

Discussion

This study investigated the relationship between prenatally diagnosed CHD, HC, and supratentorial brain structures, specifically the CC and SAS, in the context of the high incidence of neurodevelopmental impairment among children with CHD [16]. The findings demonstrated consistent and significant reductions in all measured CC dimensions, including total length and segmental heights, in fetuses with CHD compared with healthy controls. The persistence of these differences after adjustment for gestational age and EFW supports an association between CHD and altered CC development. This observation is consistent with research suggesting that the developing fetal brain is vulnerable in the context of CHD [3]. A recent neurosonography study by Perez-Cruz et al. [9] similarly demonstrated smaller CC dimensions in fetuses with isolated major CHD during the third trimester, with more pronounced reductions in lesions associated with severely compromised cerebral oxygen supply, particularly left outflow tract obstruction and TGA [9]. A recent MRI study also reported smaller region-specific brain volumes, including the CC, in fetuses with CHD before 32 weeks of gestation [17]. Persistent reductions in CC dimensions have also been confirmed postnatally in children with CHD, with more marked effects in specific regions such as the isthmus and splenium [18,19].

The etiology of these CC abnormalities is multifactorial, and chronic fetal hypoxemia may contribute by disrupting normal axonal growth and myelination [9]. An association between low oxygen supply and reduced CC dimensions has also been demonstrated in growth-restricted fetuses [20]. Prolonged exposure to low oxygen concentrations during the third trimester can lead to diffuse myelination disturbances and altered white matter development [7]. The vulnerability of immature oligodendrocytes to chronic hypoxia, particularly in the late third trimester, is a key mechanism underlying white matter injury [9]. Because normal CC growth in late pregnancy is largely driven by axonal growth in an anterior-posterior direction, the observed reductions in CC dimensions may reflect injury to developing white matter [21]. In the present study, all CC segments, from the genu to the splenium, were markedly reduced in fetuses with CHD, whereas Perez-Cruz et al. [9] reported selective reduction in posterior CC regions with preservation of anterior regions. This discrepancy may be attributable to differences in measurement techniques or the CHD subtypes included in each study. Overall, the observed reduction in CC dimensions in this CHD cohort supports an association between CHD and altered white matter development and suggests that CC measurements may be feasible prenatal markers for assessing white matter development and identifying fetuses with CHD who are at increased risk of suboptimal neurodevelopmental outcomes.

In contrast to previous research, a notable finding of this study was that reductions in CC dimensions were observed in both class A and class B CHD groups, regardless of expected oxygen supply status, with no significant differences between these classifications [9]. This finding suggests that CHD itself, rather than the expected oxygen delivery pattern alone, may be associated with alterations in structural brain development. However, although no statistically significant differences were observed between CHD subgroups classified by expected cerebral oxygen delivery, the absence of significance should not be interpreted as evidence of equivalence or independence. Rather, CC alterations were observed across different CHD subtypes, whereas subgroup analyses may have been underpowered to detect more subtle differences. These findings are consistent with previous studies indicating that impaired fetal brain growth may occur across various CHD types, regardless of their specific hemodynamic effects [22]. Although some studies have reported more pronounced effects in fetuses with reduced brain oxygen supply [9], the present data suggest a broader impact on CC development independent of the oxygenation classification used here. This may indicate that even “normal” oxygen supply in the context of CHD is insufficient to support optimal brain development, or that additional factors, such as genetic predisposition, subtle hemodynamic alterations not fully captured by the oxygenation classification, or inflammatory processes, contribute to these structural changes [3,7,17]. The presence of these changes across both oxygenation classes further supports an association between CHD and altered fetal neurodevelopment.

In contrast to the significant reductions observed in CC dimensions, this study found no statistically significant differences in HC among the class A CHD, class B CHD, and control groups. This result contrasts with several previous reports of smaller HC in fetuses and neonates with CHD. For instance, Kinnear et al. [23] observed lower HC Z-scores in fetuses with HLHS, and Masoller et al. [24] documented smaller HC in a substantial proportion of fetuses with CHD as early as the second trimester. However, other studies are consistent with the present findings. Jansen et al. [25], for example, reported that although fetuses with prenatally detected isolated CHD showed a progressive decline in HC growth with advancing gestational age, their HC values often remained within the normal range. These findings suggest that HC, as a global parameter, may not always reflect subtle or region-specific disturbances in brain development, particularly when growth restriction does not meet diagnostic thresholds for microcephaly. This limitation of HC supports the need for more sensitive markers, such as specific brain volumetric analyses or white matter integrity assessments, which are known to be affected in CHD.

The literature on fetal SAS development, including the study by Malinger et al. [10], provides normal ranges and describes dynamic changes throughout gestation. SAS width has been proposed as an indirect method for assessing brain growth [26]. SAS dilatation may be benign but can also indicate serious disorders, including cortical malformations or brain atrophy, in both microcephalic and normocephalic infants [15,26]. This study found no significant difference in SAS between the control and CHD groups. Although the SAS in fetuses with CHD has been less extensively studied, some reports have described increased cerebrospinal fluid (CSF) spaces, including dilatation of the cavum septi pellucidi, particularly in cases of critical CHD accompanied by reduced brain volume [27,28]. Similarly, Ren et al. [29] used volumetric MRI to evaluate intracranial structures in fetuses with CHD and demonstrated increased extracerebral fluid (e-CSF) volumes, along with a higher e-CSF–to–intracranial cavity volume ratio compared with controls. The present findings are consistent with those of Jansen et al. [30], who reported no significant differences in extracerebral fluid volume between fetuses with CHD and controls when assessed by three-dimensional sonographic volume acquisition in the second and third trimesters. The discrepancy among studies may be explained by differences in the specific regions evaluated, because global SAS measurements may not capture subtle, localized alterations in CSF spaces. It may also relate to the lack of significant HC differences in this cohort, because enlarged SAS is often linked to brain atrophy or abnormal head size in other fetal conditions, such as microcephaly or macrocephaly.

HC and SAS measurements are global, indirect markers of fetal brain growth rather than region-specific indicators of white matter integrity. HC primarily reflects overall cranial growth and may remain within normal limits despite underlying microstructural or regional brain alterations, particularly in the absence of overt growth restriction or microcephaly. Similarly, enlargement of the SAS has been proposed as an indirect marker of brain atrophy or extracerebral CSF expansion; however, such changes are typically associated with more advanced or diffuse cerebral volume loss. In the context of CHD, subtle disturbances in white matter development may occur without measurable changes in HC or SAS dimensions. Therefore, the absence of significant HC and SAS differences in this cohort does not exclude altered brain development but rather suggests that these global parameters may lack sensitivity for detecting early or region-specific neurodevelopmental alterations associated with CHD.

This study also found a statistically significant difference in gestational age at delivery, with earlier delivery in the CHD group (38.15±1.44 weeks) than in the control group (38.93±1.22 weeks). Earlier delivery is a recognized feature of CHD pregnancies and may result from planned interventions, such as elective induction or cesarean section, or from earlier pregnancy complications in these high-risk cases [24]. Although not a direct measure of brain structure, earlier delivery could indirectly influence postnatal neurodevelopmental outcomes by limiting the duration of in utero brain maturation, a period critical for rapid brain growth and cortical development [3].

Despite providing valuable insights, this study has several limitations. Although an a priori power analysis was performed, the sample size of 102 fetuses was relatively modest, especially for detailed subgroup analyses. The classification of CHD into “reduced” versus “normal” oxygen supply categories was based on expected physiological patterns rather than direct, real-time measurements of fetal brain oxygenation. Although this classification is clinically relevant and widely used, it may not fully capture the dynamic and complex nature of cerebral hemodynamics in individual fetuses. Another potential limitation is the use of both transabdominal and transvaginal probes for image acquisition. Although identical measurement protocols and anatomical landmarks were applied once an adequate midsagittal plane was obtained, subtle differences in image resolution or acquisition conditions between probe types cannot be completely excluded. A formal subgroup or sensitivity analysis according to probe type was not performed and should be considered in future studies. Furthermore, the study relied solely on ultrasound measurements, which are practical but may have inherent limitations in spatial resolution and visualization of subtle brain microstructures compared with advanced fetal MRI techniques. Most importantly, the absence of postnatal neurodevelopmental follow-up prevents direct correlation of the observed prenatal brain structural changes with later neurological outcomes. Although an a priori power analysis was performed for the overall three-group comparison, the study was not specifically powered to detect differences between class A and class B CHD subgroups. Given the modest subgroup sample sizes, smaller effect sizes may not have been detectable, and the possibility of type II error cannot be excluded. Accordingly, subgroup comparisons should be interpreted as exploratory rather than confirmatory. Finally, because multiple correlated neurosonographic parameters were evaluated, findings related to secondary outcomes should be interpreted as exploratory and hypothesis-generating rather than confirmatory.

Future research should build on these findings through larger prospective cohort studies with longitudinal neurodevelopmental follow-up into childhood and adolescence. Advanced fetal imaging modalities, such as quantitative MRI, could provide more granular data on brain volume, white matter microstructure, and metabolic changes. These techniques could also support direct in vivo measurement of cerebral oxygen delivery and consumption, providing a more precise understanding of the relationship between oxygen supply and brain development. Further investigation of underlying mechanisms, including genetic predisposition and placental function, is also warranted. Ultimately, these efforts may help develop more precise prenatal parameters for neurodevelopmental risk assessment and identify potential targets for early interventions to reduce adverse outcomes in this vulnerable population.

In conclusion, this study demonstrated that CHD was associated with significant differences in prenatal CC development, independent of the expected cerebral oxygen delivery pattern. Although no significant differences were observed in HC or SAS, consistent reductions in total CC length and all measured CC segments highlight the specific vulnerability of white matter development in CHD. These findings emphasize the prenatal origin of neurodevelopmental challenges frequently encountered in children with CHD. By identifying the CC as a potential marker of prenatal brain developmental alterations, this study contributes to a deeper understanding of the neurological impact of CHD during fetal life. Reductions in CC dimensions were observed across fetuses with CHD, regardless of subgroup classification by expected cerebral oxygen delivery. However, differences between oxygenation-based subgroups could not be statistically demonstrated, and larger studies are needed to clarify potential subgroup-specific effects. These insights may guide early diagnostic strategies and parental counseling while also underscoring the need for further investigation into underlying mechanisms and long-term neurodevelopmental outcomes.

Key points

Fetuses with congenital heart disease showed significant reductions in all corpus callosum segments, independent of expected brain oxygenation patterns. Head circumference and subarachnoid space measurements did not differ significantly, whereas corpus callosum measurements appeared to be sensitive markers of altered white matter development. The neurodevelopmental effects of congenital heart disease appear to begin prenatally; corpus callosum assessment may help identify fetuses at higher risk for adverse neurological outcomes.

Footnotes

Author Contributions

Conceptualization: Alpay V, Ersan F. Data acquisition: Ersan F, Boza B. Data analysis or interpretation: Boza B. Drafting of the manuscript: Alpay V. Critical revision of the manuscript: Alpay V, Ersan F, Boza B. Approval of the final version of the manuscript: all authors.

Conflict of Interest

No potential conflict of interest relevant to this article was reported.

References

1.Peyvandi S, Latal B, Miller SP, McQuillen PS. The neonatal brain in critical congenital heart disease: insights and future directions. Neuroimage. 2019;185:776–782. doi: 10.1016/j.neuroimage.2018.05.045. [DOI] [PubMed] [Google Scholar]
2.Naef N, Liamlahi R, Beck I, Bernet V, Dave H, Knirsch W, et al. Neurodevelopmental profiles of children with congenital heart disease at school age. J Pediatr. 2017;188:75–81. doi: 10.1016/j.jpeds.2017.05.073. [DOI] [PubMed] [Google Scholar]
3.Lee FT, Seed M, Sun L, Marini D. Fetal brain issues in congenital heart disease. Transl Pediatr. 2021;10:2182–2196. doi: 10.21037/tp-20-224. [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Everwijn SM, van Bohemen JF, van Geloven N, Jansen FA, Teunissen AK, Rozendaal L, et al. Serial neurosonography in fetuses with congenital heart defects shows mild delays in cortical development. Prenat Diagn. 2021;41:1649–1657. doi: 10.1002/pd.6038. [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Masoller N, Sanz-Cortes M, Crispi F, Gomez O, Bennasar M, Egana-Ugrinovic G, et al. Severity of fetal brain abnormalities in congenital heart disease in relation to the main expected pattern of in utero brain blood supply. Fetal Diagn Ther. 2016;39:269–278. doi: 10.1159/000439527. [DOI] [PubMed] [Google Scholar]
6.Miller SP, McQuillen PS, Hamrick S, Xu D, Glidden DV, Charlton N, et al. Abnormal brain development in newborns with congenital heart disease. N Engl J Med. 2007;357:1928–1938. doi: 10.1056/nejmoa067393. [DOI] [PubMed] [Google Scholar]
7.Leonetti C, Back SA, Gallo V, Ishibashi N. Cortical dysmaturation in congenital heart disease. Trends Neurosci. 2019;42:192–204. doi: 10.1016/j.tins.2018.12.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Clouchoux C, du Plessis AJ, Bouyssi-Kobar M, Tworetzky W, McElhinney DB, Brown DW, et al. Delayed cortical development in fetuses with complex congenital heart disease. Cereb Cortex. 2013;23:2932–2943. doi: 10.1093/cercor/bhs281. [DOI] [PubMed] [Google Scholar]
9.Perez-Cruz M, Gomez O, Gibert M, Masoller N, Marimon E, Lip-Sosa D, et al. Corpus callosum size by neurosonography in fetuses with congenital heart defect and relationship with expected pattern of brain oxygen supply. Ultrasound Obstet Gynecol. 2022;59:220–225. doi: 10.1002/uog.23684. [DOI] [PubMed] [Google Scholar]
10.Malinger G, Lerman-Sagie T, Achiron R, Lipitz S. The subarachnoid space: normal fetal development as demonstrated by transvaginal ultrasound. Prenat Diagn. 2000;20:890–893. doi: 10.1002/1097-0223(200011)20:11<890::aid-pd945>3.0.co;2-z. [DOI] [PubMed] [Google Scholar]
11.Paladini D, Malinger G, Birnbaum R, Monteagudo A, Pilu G, Salomon LJ, et al. ISUOG Practice Guidelines (updated): sonographic examination of the fetal central nervous system. Part 2: performance of targeted neurosonography. Ultrasound Obstet Gynecol. 2021;57:661–671. doi: 10.1002/uog.23616. [DOI] [PubMed] [Google Scholar]
12.Carvalho JS, Axt-Fliedner R, Chaoui R, Copel JA, Cuneo BF, Goff D, et al. ISUOG Practice guidelines (updated): fetal cardiac screening. Ultrasound Obstet Gynecol. 2023;61:788–803. doi: 10.1002/uog.26224. [DOI] [PubMed] [Google Scholar]
13.Youssef A, Ghi T, Pilu G. How to image the fetal corpus callosum. Ultrasound Obstet Gynecol. 2013;42:718–720. doi: 10.1002/uog.12367. [DOI] [PubMed] [Google Scholar]
14.Pashaj S, Merz E, Wellek S. Biometry of the fetal corpus callosum by three-dimensional ultrasound. Ultrasound Obstet Gynecol. 2013;42:691–698. doi: 10.1002/uog.12501. [DOI] [PubMed] [Google Scholar]
15.Corbacioglu Esmer A, Yuksel A, Aksu Uzunhan T, Demir O, Sarac Sivrikoz T, Aydinli N. Evaluation of fetal subarachnoid space using transabdominal ultrasonography and normal values during pregnancy. Springerplus. 2016;5:1439. doi: 10.1186/s40064-016-3121-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Verrall CE, Blue GM, Loughran-Fowlds A, Kasparian N, Gecz J, Walker K, et al. 'Big issues' in neurodevelopment for children and adults with congenital heart disease. Open Heart. 2019;6:e000998. doi: 10.1136/openhrt-2018-000998. [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Rollins CK, Ortinau CM, Stopp C, Friedman KG, Tworetzky W, Gagoski B, et al. Regional brain growth trajectories in fetuses with congenital heart disease. Ann Neurol. 2021;89:143–157. doi: 10.1002/ana.25940. [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Ng IH, Bonthrone AF, Kelly CJ, Cordero-Grande L, Hughes EJ, Price AN, et al. Investigating altered brain development in infants with congenital heart disease using tensor-based morphometry. Sci Rep. 2020;10:14909. doi: 10.1038/s41598-020-72009-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Hagmann C, Singer J, Latal B, Knirsch W, Makki M. Regional microstructural and volumetric magnetic resonance imaging (MRI) abnormalities in the corpus callosum of neonates with congenital heart defect undergoing cardiac surgery. J Child Neurol. 2016;31:300–308. doi: 10.1177/0883073815591214. [DOI] [PubMed] [Google Scholar]
20.Malavolti AM, Chau V, Brown-Lum M, Poskitt KJ, Brant R, Synnes A, et al. Association between corpus callosum development on magnetic resonance imaging and diffusion tensor imaging, and neurodevelopmental outcome in neonates born very preterm. Dev Med Child Neurol. 2017;59:433–440. doi: 10.1111/dmcn.13364. [DOI] [PubMed] [Google Scholar]
21.Paul LK. Developmental malformation of the corpus callosum: a review of typical callosal development and examples of developmental disorders with callosal involvement. J Neurodev Disord. 2011;3:3–27. doi: 10.1007/s11689-010-9059-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Paladini D, Finarelli A, Donarini G, Parodi S, Lombardo V, Tuo G, et al. Frontal lobe growth is impaired in fetuses with congenital heart disease. Ultrasound Obstet Gynecol. 2021;57:776–782. doi: 10.1002/uog.22127. [DOI] [PubMed] [Google Scholar]
23.Kinnear C, Haranal M, Shannon P, Jaeggi E, Chitayat D, Mital S. Abnormal fetal cerebral and vascular development in hypoplastic left heart syndrome. Prenat Diagn. 2019;39:38–44. doi: 10.1002/pd.5395. [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Masoller N, Martinez JM, Gomez O, Bennasar M, Crispi F, Sanz-Cortes M, et al. Evidence of second-trimester changes in head biometry and brain perfusion in fetuses with congenital heart disease. Ultrasound Obstet Gynecol. 2014;44:182–187. doi: 10.1002/uog.13373. [DOI] [PubMed] [Google Scholar]
25.Jansen FA, van Zwet EW, Rijlaarsdam ME, Pajkrt E, van Velzen CL, Zuurveen HR, et al. Head growth in fetuses with isolated congenital heart defects: lack of influence of aortic arch flow and ascending aorta oxygen saturation. Ultrasound Obstet Gynecol. 2016;48:357–364. doi: 10.1002/uog.15980. [DOI] [PubMed] [Google Scholar]
26.Paciorkowski AR, Greenstein RM. When is enlargement of the subarachnoid spaces not benign? A genetic perspective. Pediatr Neurol. 2007;37:1–7. doi: 10.1016/j.pediatrneurol.2007.04.001. [DOI] [PubMed] [Google Scholar]
27.Turgut E, Ozdemir H, Turan G, Karcaaltincaba D, Bayram M. Evaluation of intracranial structures of fetuses with congenital heart defects. J Ultrasound Med. 2023;42:419–425. doi: 10.1002/jum.16049. [DOI] [PubMed] [Google Scholar]
28.Saadeh M, Zhao Y, Galadima H, Chaoui R, Sinkovskaya E, Abuhamad A. Relationship between cavum septi pellucidi measurements and fetal hypoplastic left heart syndrome or dextro-transposition of the great arteries. J Ultrasound Med. 2018;37:1673–1680. doi: 10.1002/jum.14515. [DOI] [PubMed] [Google Scholar]
29.Ren JY, Zhu M, Dong SZ. Three-dimensional volumetric magnetic resonance imaging detects early alterations of the brain growth in fetuses with congenital heart disease. J Magn Reson Imaging. 2021;54:263–272. doi: 10.1002/jmri.27526. [DOI] [PubMed] [Google Scholar]
30.Jansen FA, van Zwet EW, Everwijn SM, Teunissen AK, Rozendaal L, van Lith JM, et al. Fetuses with isolated congenital heart defects show normal cerebral and extracerebral fluid volume growth: a 3D sonographic study in the second and third trimester. Fetal Diagn Ther. 2019;45:212–220. doi: 10.1159/000488674. [DOI] [PMC free article] [PubMed] [Google Scholar]

[b1-usg-25254] 1.Peyvandi S, Latal B, Miller SP, McQuillen PS. The neonatal brain in critical congenital heart disease: insights and future directions. Neuroimage. 2019;185:776–782. doi: 10.1016/j.neuroimage.2018.05.045. [DOI] [PubMed] [Google Scholar]

[b2-usg-25254] 2.Naef N, Liamlahi R, Beck I, Bernet V, Dave H, Knirsch W, et al. Neurodevelopmental profiles of children with congenital heart disease at school age. J Pediatr. 2017;188:75–81. doi: 10.1016/j.jpeds.2017.05.073. [DOI] [PubMed] [Google Scholar]

[b3-usg-25254] 3.Lee FT, Seed M, Sun L, Marini D. Fetal brain issues in congenital heart disease. Transl Pediatr. 2021;10:2182–2196. doi: 10.21037/tp-20-224. [DOI] [PMC free article] [PubMed] [Google Scholar]

[b4-usg-25254] 4.Everwijn SM, van Bohemen JF, van Geloven N, Jansen FA, Teunissen AK, Rozendaal L, et al. Serial neurosonography in fetuses with congenital heart defects shows mild delays in cortical development. Prenat Diagn. 2021;41:1649–1657. doi: 10.1002/pd.6038. [DOI] [PMC free article] [PubMed] [Google Scholar]

[b5-usg-25254] 5.Masoller N, Sanz-Cortes M, Crispi F, Gomez O, Bennasar M, Egana-Ugrinovic G, et al. Severity of fetal brain abnormalities in congenital heart disease in relation to the main expected pattern of in utero brain blood supply. Fetal Diagn Ther. 2016;39:269–278. doi: 10.1159/000439527. [DOI] [PubMed] [Google Scholar]

[b6-usg-25254] 6.Miller SP, McQuillen PS, Hamrick S, Xu D, Glidden DV, Charlton N, et al. Abnormal brain development in newborns with congenital heart disease. N Engl J Med. 2007;357:1928–1938. doi: 10.1056/nejmoa067393. [DOI] [PubMed] [Google Scholar]

[b7-usg-25254] 7.Leonetti C, Back SA, Gallo V, Ishibashi N. Cortical dysmaturation in congenital heart disease. Trends Neurosci. 2019;42:192–204. doi: 10.1016/j.tins.2018.12.003. [DOI] [PMC free article] [PubMed] [Google Scholar]

[b8-usg-25254] 8.Clouchoux C, du Plessis AJ, Bouyssi-Kobar M, Tworetzky W, McElhinney DB, Brown DW, et al. Delayed cortical development in fetuses with complex congenital heart disease. Cereb Cortex. 2013;23:2932–2943. doi: 10.1093/cercor/bhs281. [DOI] [PubMed] [Google Scholar]

[b9-usg-25254] 9.Perez-Cruz M, Gomez O, Gibert M, Masoller N, Marimon E, Lip-Sosa D, et al. Corpus callosum size by neurosonography in fetuses with congenital heart defect and relationship with expected pattern of brain oxygen supply. Ultrasound Obstet Gynecol. 2022;59:220–225. doi: 10.1002/uog.23684. [DOI] [PubMed] [Google Scholar]

[b10-usg-25254] 10.Malinger G, Lerman-Sagie T, Achiron R, Lipitz S. The subarachnoid space: normal fetal development as demonstrated by transvaginal ultrasound. Prenat Diagn. 2000;20:890–893. doi: 10.1002/1097-0223(200011)20:11<890::aid-pd945>3.0.co;2-z. [DOI] [PubMed] [Google Scholar]

[b11-usg-25254] 11.Paladini D, Malinger G, Birnbaum R, Monteagudo A, Pilu G, Salomon LJ, et al. ISUOG Practice Guidelines (updated): sonographic examination of the fetal central nervous system. Part 2: performance of targeted neurosonography. Ultrasound Obstet Gynecol. 2021;57:661–671. doi: 10.1002/uog.23616. [DOI] [PubMed] [Google Scholar]

[b12-usg-25254] 12.Carvalho JS, Axt-Fliedner R, Chaoui R, Copel JA, Cuneo BF, Goff D, et al. ISUOG Practice guidelines (updated): fetal cardiac screening. Ultrasound Obstet Gynecol. 2023;61:788–803. doi: 10.1002/uog.26224. [DOI] [PubMed] [Google Scholar]

[b13-usg-25254] 13.Youssef A, Ghi T, Pilu G. How to image the fetal corpus callosum. Ultrasound Obstet Gynecol. 2013;42:718–720. doi: 10.1002/uog.12367. [DOI] [PubMed] [Google Scholar]

[b14-usg-25254] 14.Pashaj S, Merz E, Wellek S. Biometry of the fetal corpus callosum by three-dimensional ultrasound. Ultrasound Obstet Gynecol. 2013;42:691–698. doi: 10.1002/uog.12501. [DOI] [PubMed] [Google Scholar]

[b15-usg-25254] 15.Corbacioglu Esmer A, Yuksel A, Aksu Uzunhan T, Demir O, Sarac Sivrikoz T, Aydinli N. Evaluation of fetal subarachnoid space using transabdominal ultrasonography and normal values during pregnancy. Springerplus. 2016;5:1439. doi: 10.1186/s40064-016-3121-5. [DOI] [PMC free article] [PubMed] [Google Scholar]

[b16-usg-25254] 16.Verrall CE, Blue GM, Loughran-Fowlds A, Kasparian N, Gecz J, Walker K, et al. 'Big issues' in neurodevelopment for children and adults with congenital heart disease. Open Heart. 2019;6:e000998. doi: 10.1136/openhrt-2018-000998. [DOI] [PMC free article] [PubMed] [Google Scholar]

[b17-usg-25254] 17.Rollins CK, Ortinau CM, Stopp C, Friedman KG, Tworetzky W, Gagoski B, et al. Regional brain growth trajectories in fetuses with congenital heart disease. Ann Neurol. 2021;89:143–157. doi: 10.1002/ana.25940. [DOI] [PMC free article] [PubMed] [Google Scholar]

[b18-usg-25254] 18.Ng IH, Bonthrone AF, Kelly CJ, Cordero-Grande L, Hughes EJ, Price AN, et al. Investigating altered brain development in infants with congenital heart disease using tensor-based morphometry. Sci Rep. 2020;10:14909. doi: 10.1038/s41598-020-72009-3. [DOI] [PMC free article] [PubMed] [Google Scholar]

[b19-usg-25254] 19.Hagmann C, Singer J, Latal B, Knirsch W, Makki M. Regional microstructural and volumetric magnetic resonance imaging (MRI) abnormalities in the corpus callosum of neonates with congenital heart defect undergoing cardiac surgery. J Child Neurol. 2016;31:300–308. doi: 10.1177/0883073815591214. [DOI] [PubMed] [Google Scholar]

[b20-usg-25254] 20.Malavolti AM, Chau V, Brown-Lum M, Poskitt KJ, Brant R, Synnes A, et al. Association between corpus callosum development on magnetic resonance imaging and diffusion tensor imaging, and neurodevelopmental outcome in neonates born very preterm. Dev Med Child Neurol. 2017;59:433–440. doi: 10.1111/dmcn.13364. [DOI] [PubMed] [Google Scholar]

[b21-usg-25254] 21.Paul LK. Developmental malformation of the corpus callosum: a review of typical callosal development and examples of developmental disorders with callosal involvement. J Neurodev Disord. 2011;3:3–27. doi: 10.1007/s11689-010-9059-y. [DOI] [PMC free article] [PubMed] [Google Scholar]

[b22-usg-25254] 22.Paladini D, Finarelli A, Donarini G, Parodi S, Lombardo V, Tuo G, et al. Frontal lobe growth is impaired in fetuses with congenital heart disease. Ultrasound Obstet Gynecol. 2021;57:776–782. doi: 10.1002/uog.22127. [DOI] [PubMed] [Google Scholar]

[b23-usg-25254] 23.Kinnear C, Haranal M, Shannon P, Jaeggi E, Chitayat D, Mital S. Abnormal fetal cerebral and vascular development in hypoplastic left heart syndrome. Prenat Diagn. 2019;39:38–44. doi: 10.1002/pd.5395. [DOI] [PMC free article] [PubMed] [Google Scholar]

[b24-usg-25254] 24.Masoller N, Martinez JM, Gomez O, Bennasar M, Crispi F, Sanz-Cortes M, et al. Evidence of second-trimester changes in head biometry and brain perfusion in fetuses with congenital heart disease. Ultrasound Obstet Gynecol. 2014;44:182–187. doi: 10.1002/uog.13373. [DOI] [PubMed] [Google Scholar]

[b25-usg-25254] 25.Jansen FA, van Zwet EW, Rijlaarsdam ME, Pajkrt E, van Velzen CL, Zuurveen HR, et al. Head growth in fetuses with isolated congenital heart defects: lack of influence of aortic arch flow and ascending aorta oxygen saturation. Ultrasound Obstet Gynecol. 2016;48:357–364. doi: 10.1002/uog.15980. [DOI] [PubMed] [Google Scholar]

[b26-usg-25254] 26.Paciorkowski AR, Greenstein RM. When is enlargement of the subarachnoid spaces not benign? A genetic perspective. Pediatr Neurol. 2007;37:1–7. doi: 10.1016/j.pediatrneurol.2007.04.001. [DOI] [PubMed] [Google Scholar]

[b27-usg-25254] 27.Turgut E, Ozdemir H, Turan G, Karcaaltincaba D, Bayram M. Evaluation of intracranial structures of fetuses with congenital heart defects. J Ultrasound Med. 2023;42:419–425. doi: 10.1002/jum.16049. [DOI] [PubMed] [Google Scholar]

[b28-usg-25254] 28.Saadeh M, Zhao Y, Galadima H, Chaoui R, Sinkovskaya E, Abuhamad A. Relationship between cavum septi pellucidi measurements and fetal hypoplastic left heart syndrome or dextro-transposition of the great arteries. J Ultrasound Med. 2018;37:1673–1680. doi: 10.1002/jum.14515. [DOI] [PubMed] [Google Scholar]

[b29-usg-25254] 29.Ren JY, Zhu M, Dong SZ. Three-dimensional volumetric magnetic resonance imaging detects early alterations of the brain growth in fetuses with congenital heart disease. J Magn Reson Imaging. 2021;54:263–272. doi: 10.1002/jmri.27526. [DOI] [PubMed] [Google Scholar]

[b30-usg-25254] 30.Jansen FA, van Zwet EW, Everwijn SM, Teunissen AK, Rozendaal L, van Lith JM, et al. Fetuses with isolated congenital heart defects show normal cerebral and extracerebral fluid volume growth: a 3D sonographic study in the second and third trimester. Fetal Diagn Ther. 2019;45:212–220. doi: 10.1159/000488674. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Corpus callosum and subarachnoid space measurements in fetuses with congenital heart disease: a prospective case-control study

Verda Alpay

Fırat Ersan

Barış Boza