Arterial CO₂ pressure changes during hypercapnia are associated with changes in brain parenchymal volume

The cerebral vasculature plays a critical role in maintaining an optimal supply of cerebral blood flow (CBF) to the brain. This is dependent on cerebral autoregulation and cerebrovascular reactivity (CVR). Autoregulation refers to the mechanism to adjust cerebral perfusion pressure in order to maintain a stable cerebral blood flow, whereas CVR is the capacity to change cerebral blood vessel diameter in response to a vasoactive stimulus. Such vasoactive stimuli are lowered pH, which induces vasodilation directly, and CO₂, which induces vasodilation both directly and indirectly [1].

Dilation of the cerebral arteries, arterioles and capillaries prompts an increase in cerebral blood volume (CBV) and CBF [2, 3]. An increase in CBV is accompanied by an outflow of cerebrospinal fluid (CSF) to the spinal canal in order to maintain intracranial pressure within the fixed volume formed by the cranium and dura mater as postulated by Burrow’s correction of the Monro-Kellie doctrine (Fig. 1) [4]. As well, CSF can drain to the venous sinuses through the subarachnoid villi. Changes in CBV occur constantly as a response to the cardiac cycle, respiratory cycle, fluctuations in blood gases and locally in response to changes in neural activation [5‐7]. CBV also changes in response to respiratory acidosis and metabolic acidosis induced in disease or experimental settings. In experimental settings, the most commonly used vasoactive stimulus is an increase in the partial arterial pressure of CO₂ (PaCO₂) by means of a hypercapnic breathing challenge. In these cases, the vasodilatory response is larger than, for example, during the cardiac cycle. Consequently, CBV and CSF volume changes are also expected to be a multitude larger.

The CBV should be taken into account in longitudinal and cross-sectional studies investigating brain volume, as changes in CBV can impact cerebral tissue volume measurements. Intracranial tissue volumes are typically obtained using T1-weighted structural images. Since the longitudinal relaxation times (T1) of grey matter and blood at 3 T are similar [8], blood signals from within grey matter are indiscernible from grey matter tissue signals. Therefore, CBV changes can cause a considerable change in segmented grey matter volume [8‐10]. Moreover, a change may occur in partial volume of grey matter relative to the surrounding white matter, which can confound tissue class assignment at tissue borders. As such, changes in (baseline) PaCO₂ can affect measured tissue volumes on T1-weighted images [10].

Hypercapnia is commonly assumed to predominantly affect grey matter volume measures. Accordingly, observed cortical thickness is increased during hypercapnia [10]. Following the Monro-Kellie hypothesis, we hypothesise that compensating volume changes should be observed in brain parenchymal and CSF volumes on structural magnetic resonance imaging (MRI) in response to cerebral blood volume increases during hypercapnia. In this feasibility study, we investigate the hypothesis application to structural MRI in observing compensating intracranial volume changes during hypercapnia.

Segmentation quality was deemed poor in one out of eight subjects due to excessive motion during hypercapnia. Consequently, seven subjects (four males and three females) were included into the volumetric analysis. The median age of the included patients was 32 years (range 24–64). Baseline characteristics are presented in Table 1. The median mmHg EtCO₂ increase was 8.68 (IQR 6.77, 9.60) mmHg (p = 0.016), and no significant change in EtO₂ was observed (p = 0.156).

Median BPV during NC was 1234 mL (IQR 1162, 1305), which increased by 0.53% (IQR 0.35, 0.72) during HC (p = 0.016; Table 2). This was an absolute brain volume increase of 6.0 mL (IQR 4.5, 8.5) (p = 0.016) (Fig. 1). Grey matter showed a non-significant relative increase of 0.31% (IQR -0.06, 0.75; p = 0.469) and an absolute volume increase of 2.0 mL (IQR -0.5, 5.0; p = 0.498). In contrast, white matter volume increased by 0.80% (IQR 0.48, 1.21; p = 0.016), which is an absolute volume increase of 4.0 mL (IQR 2.5, 7.0; p = 0.022) (Fig. 2). A global decrease in CSF volume (3.4%, IQR 2.1, 4.8; p = 0.031) was measured with a median change of -10.0 mL (IQR -13.5, -6.5; p = 0.034) during hypercapnia compared to normocapnia. As well, a decrease in ventricular volume occurred during HC compared to NC: the median relative volume change was -1.59% (IQR -2.84, -1.14) and the absolute median volume change was -0.38 mL (IQR -0.26, -0.53; p = 0.016).

We found an increase in brain parenchymal volume and a decrease in CSF volume on three-dimensional T1-weighted MRI during hypercapnia. These results demonstrate the feasibility of widely used, structural MRI sequences to observe volumetric reactivity capability of the brain. As well, the results convey several implications for interpreting volumetric MRI results and its potential applications. For instance, diseases and pharmaceutical drugs with vasoactive properties may influence brain and CSF volume assessment. This can affect studies with longitudinal or cross-sectional design such as those regarding atrophy measurements. Also, segmentation analyses of conventional imaging sequences could be used to infer CVR when a vasodilatory stimulus is given.

A median 6 mL increase in BPV was observed during a 9-mmHg hypercapnia stimulus, which is in agreement with an earlier study reporting on ΔCBV as a response to a 10-mmHg hypercapnia stimulus [15]. PaCO₂ and blood pH effects can occur in various contexts, and our results highlight that they warrant careful consideration in the interpretation and analysis of intracranial volumetric data. An increase in PaCO₂ and/or a reduction in blood pH can occur in a range of settings aside from a hypercapnic breathing paradigm. As abnormal baseline PaCO₂ can affect volume measures [10], awareness of its occurrence is important in the abundant longitudinal and cross-sectional studies that investigate brain volume changes. One example of an acute onset respiratory acidosis is the administration of sedative agents in patients undergoing MRI or exercise tasks during MRI [16‐18]. In addition, respiratory acidosis can occur in restrictive or obstructive lung disease in which impaired respiratory exchange causes CO₂ retention, whereas metabolic acidosis may occur in patients with chronic kidney disease due to impaired H⁺ excretion [19, 20]. In cross-sectional studies, differences in PaCO₂ could confound volumetric MRI results if one group experienced an increased PaCO₂ while the other group(s) did not. In longitudinal studies, long-term CBV changes related to age and specific pathologies should be regarded [10]. The size of the effects remains to be investigated, but it could have implications for an extensive amount of studies investigating brain volume.

In addition, our approach can be applied as a structural CVR measure. A drawback of our study design is that no data were collected on cerebral blood volume. Therefore, future research is required with CBV measurements along structural CVR to validate the current proof-of-concept study. Structural images are always part of the scan protocol for clinical purposes, and they are readily available even at non-academic hospitals. The 3D T1-based approach offers an excellent contrast between brain parenchyma and CSF. Yet, it also carries the limitation of low contrast to identify the exact spatial boundaries of CSF, dura mater and skull, thereby limiting the method’s ability to detect peripheral CSF volume changes accurately. This makes the sequence suitable for detecting brain volume changes, but not ideal for the detection of total CSF volume changes as indicated by the variability in obtained intracranial volume.

We hypothesised that using high-resolution 3D T1-weighted images would enable us to distinguish volume changes separately for grey matter and white matter. However, the observed volumetric changes during hypercapnia in grey matter and white matter (~ 3 mL) are close to the threshold of volume changes that can reliably be detected with automatic segmentation [21]. As such, we focused on the changes in total brain volume and peripheral CSF. However, for segmenting these larger volumes, 3D T2-weighted sequences are expected to be more accurate and precise than 3D T1-weighted sequences and likely would have been a more appropriate sequence for detecting the hypercapnia-induced larger volume changes. In fact, contrary to T1-weighted images, T2-weighted images carry a high positive contrast between brain tissue and CSF, but also between the peripheral CSF and dura mater and skull. Accordingly, a more reliable measure of total CSF volume and changes therein is expected. Fast 3D T2-weighted sequences are available to determine CSF and brain volume changes [21]. Short imaging time is of particular importance for any sequence used in clinical settings, where CVR assessment can aid in treatment selection and function as a marker of disease severity along with the structural markers [22, 23]. The use of structural images for CVR measurements reduces scan time and cost, because only one additional scan during hypercapnia is appended to the scan protocol.

Limitations of our study are the relatively small sample size and the homogeneous group of healthy subjects. Subsequent studies should elicit whether this method is also applicable for older individuals and for various patient populations. Also, no quantitative T1 measurements were performed in the current study for comparison with morphological changes. While a study with a comparable hypercapnia challenge did observe an increase in grey matter volume using 7-T MRI [10], no significant increase in grey matter volume was found in our study (Additional file 1: Figure S1). In that study, segmentation was performed on “UNI” images (a T1-weighted sequence unaffected by T2*, proton density and field inhomogeneities), proton density and field inhomogeneities. Whereas this does not affect total brain volume, our increase in white matter volume rather than grey matter volume might be explained by these biases. Further, an earlier reported difference in the effect of hypercapnia on T1 in grey matter compared to white matter may contribute to the found changes. A significant decrease in grey matter T1 has been found during hypercapnia, while no significant change occurred in white matter T1 [10]. Therefore, hypercapnia may increase the probability of white matter assignment in voxels at grey-white matter boundaries [24, 25]. Moreover, a previous study showed the dilation of cerebral arteries during hypercapnia [26]. A considerable amount of these arteries are co-located with the segmented white matter. As their signal intensity is closer to white matter than to grey matter, they can contribute to a higher segmented white matter volume during hypercapnia. Future studies should investigate the effect of baseline hemodynamic characteristics on brain volume assessments to ensure that they do not confound brain volumetric studies.

In conclusion, we showed that arterial CO₂ pressure changes during hypercapnia are associated with changes in BPV and CSF volume in accordance with the Monro-Kellie hypothesis. The found volume changes highlight the relevance of accounting for hemodynamic parameters when interpreting volumetric MRI studies. The proposed volumetric approach to measure CVR may offer a new marker of intracranial tissue reactivity.