Utilizing Retinal Arteriole/Venule Ratio to Estimate Intracranial Pressure

doi:10.21203/rs.3.rs-4918744/v1

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Utilizing Retinal Arteriole/Venule Ratio to Estimate Intracranial Pressure

https://doi.org/10.21203/rs.3.rs-4918744/v1

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Journal Publication

published 08 Nov, 2024

Read the published version in Acta Neurochirurgica →

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Purpose

Intracranial pressure (ICP) control is important to avoid secondary brain injury in patients with intracranial pathologies. Current methods for measuring ICP are invasive and carry risks of infection and hemorrhage. Previously we found correlation between ICP and the arteriole-venous ratio (A/V ratio) of retinal vessels in an outpatient setting. This study investigated the usability of fundoscopy for non-invasive ICP estimation with the addition of intraocular pressure (IOP) in patients in a neuro-intensive care unit (NICU)

Methods

This single-center prospective cohort study was conducted at the NICU of Odense University Hospital from September 2020 to May 2021. Adult patients with a Glasgow Coma Score of 8 or less, who underwent invasive pressure neuromonitoring were included. Fundoscopy videos were captured daily and analyzed using deep learning algorithms. The A/V ratio was calculated and correlated with ICP. The data was analyzed using mixed-effect linear regression models.

Results

Forty patients were enrolled, whereof 15 were included in the final analysis. ICP ranged from − 1 to 111 mmHg (mean: 10.4, SD: 6.1), and IOP ranged from 4 to 13 mmHg (mean: 7.4, SD: 2.1). The A/V ratio showed a significant negative correlation with ICP > 15 mmHg (regression slope: -0.0659, 95%-CI: [-0.0665;-0.0653], p < 0.001). No significant change in A/V ratio was observed for ICP ≤ 15 mmHg. A similar significant correlation was found for ICP > IOP (regression slope: -0.0055, 95%-CI: [-0.0062;-0.0048], p < 0.001). Taking the IOP into account did not improve the model. The sensitivity analysis showed a sensitivity of 80.08% and a specificity of 22.51%, with an AUC of 0.6389.

Conclusion

In line with our previous work, non-invasive fundoscopy is a potential tool for detecting elevated ICP. However, challenges such as image quality and diagnostic specificity remains. Further research with larger, multi-center studies are needed to validate the utility. Standardization may enhance the technique's clinical applicability.

Intracranial Pressure (ICP)

Fundoscopy

Retinal ateriole/venule Ratio

Non-invasive monitoring

Trauma

Intracranial pressure (ICP) control is important to avoid secondary brain injury in patients with intracranial pathologies(4, 6, 17). Intracranial hypertension has been shown to increase mortality and morbidity in several conditions such as meningitis and severe head trauma(17, 18). ICP exceeding 20 mmHg is usually considered elevated and measures should be taken to achieve ICP control(13).

The first ICP measure was performed by Queckenstedt in 1916 by a lumbar puncture(16). However, it was Lundberg who performed the first catheterization to monitor and treat the ICP(16). This method was accepted in the 1970s and has since 2007 been a key part of managing serve traumatic brain injury (3). ICP is usually measured using invasive techniques such as intraparenchymal monitors or external ventricular drains (EVD). While these methods provide accurate readings, they require surgery and are thus associated with risks such as infection and hemorrhage(12, 19). These procedures are typically performed in neurosurgical centers and are not readily available in hospitals without a neurosurgical unit or in prehospital settings. Because of this, there has been a growing interest in the development of reliable, non-invasive alternatives, which can be used without specialized training. This is particularly relevant in low-income countries and low dense populated areas with limited access to neuromonitoring, neuroimaging and treatments(5).

Several non-invasive ICP modalities have been investigated since the 1970s (9, 11). However, none of these have yet been implemented clinically as continuous monitoring or screening tools. Fundoscopy with assessment of retinal vessel diameter represent a novel development within this field (2). The basis for the modality is a measurement of the ratio between the diameter of the retinal arteriole and venule (A/V ratio). Theoretically, an increase in ICP compromise venous outflow, thus a distension of the venule and a lower A/V ratio may be observed(1, 8, 10, 14). We demonstrated this phenomenon in 2020(2), where we also showed a difference in the A/V ratio when ICP was above and below 15 mmHg. This study was, however, limited to patients with normal ICP. Furthermore, we suggested that the change in A/V ratio and correlation with ICP could be affected by the IOP, suggesting the combination of ocular hemodynamics and vascular compliance in relation to ICP.

By this study we utilize simple imaging techniques and advanced deep learning algorithms for retinal video analysis. This study aims to investigate the feasibility of using non-invasive fundoscopy to assess ICP by evaluating the correlation between the retinal A/V ratio and ICP in patients admitted to a neuro-intensive care unit (NICU). Moreover, the dynamic between ICP, IOP and A/V ratio will be investigated.

Setting and study participation. This single-center, observational, prospective cohort study was performed in the Neuro Intensive Care Unit (NICU). The study was performed according to the Declaration of Helsinki and was approved by the Regional Committee on Health Research Ethics for Southern Denmark (S-20190107), the Danish Data Protection Agency (20/4618) and in agreement with current local and national guidelines and regulations. Participants were included from September 2020 to May 2021. Given the nature of the study, unconscious patients could be included initially without their personal consent in accordance with approved study protocol. Informed consent was obtained from next-of-kin either prior to or after the fundoscopy was performed. Patients who regained consciousness were asked for consent as well.

The inclusion criteria were patients aged ≥18 admitted to the NICU who underwent invasive pressure neuromonitoring with either external ventricular drainage (EVD) or an intraparenchymal pressure monitor (IPPM). All participants had a Glasgow Coma Score of 8 or less.

Retinal videos of both eyes were captured daily. The ICP was recorded with a standard webcam pointed at the patient monitor. ICP and A/V ratio were then correlated according to specific time stamps. No mydriatic drugs were used. The IOP was obtained after each video session. Clinical and demographic data were collected from the electronic patient records as shown in Table 1. There were no adverse events reported following the fundoscopy.

Fundoscopies were performed using the Epicam M camera (Epipole Ltd., Rosyth, UK), which is CE-marked and compliant with Quality Management Software with ISO 13485. The Epicam is a handheld monochromatic sensor image camera that produces serial still images (15 images/second) of 1280 x 1024 pixels and can be manually focused (± 15 diopters). The videos were obtained using designated Epicam software (Epicam viewer software 3.1.1., Epipole Ltd.). IOP was obtained by a CE-marked ic100 tonometer TA011 (Icare Finland Oy, Finland) that was approved by the Reduction of Hazardous Substances in Electrical and Electronic Equipment (RoHS) Directive 2011/65/EU and has an accuracy of ± 1.2 mmHg up to 20 mmHg and ± 2.2 mmHg for > 20 mmHg. Both tonometry and fundoscopy was performed by the same operator.

Blinding. Fundoscopy and video analysis was done by separate individuals to ensure sufficient blinding and bias minimization. The fundoscopy operator matched each patient to the corresponding ICP acquired from the webcam data and performed statistics in collaboration with OPEN, SDU.

Retinal video analysis. Retinal video processing and analysis was performed by an external company (Statumanu ICP ApS, Denmark). StatuManu was given access to pseudo anonymized data only. Retinal video analysis was performed using a deep learning model which was trained on more than 200,000 fundus and non-fundus images. It is partly based on an image classifier called Efficientnet(20). The video recordings had a frame rate of 15 frames/second. The deep learning algorithm separated the videos into frames. It categorized each frame as ‘fundus’ or ‘no fundus’, based on the whether the optic disc and retinal vessels were present.

The optic disc was identified using ‘YOLOv7 object detection model’. Images without the optic disc present were discarded. Blood vessels in the remaining images were segmented using a deep learning vessel segmentation model. The highest quality image was chosen as a reference image, and its quality was assessed by an Edge Detection Filter (Tenengrad Gradient Magnitude) on a 1.5height/width crop around the optic disc. The remaining vessel segmentations were aligned to match the reference image.

The measurement points on each vessel were determined using a deep learning algorithm (Human Pose Estimation)(15). This algorithm had been retrained on retinal fundus images with marked measurement points to identify measurement points instead of poses.

Calculating vessel width and area. Using the defined measurement points, the widths of each vessel were calculated (Fig. 1). Using the calculated width, the area of a vessel at the point of a cross section could also be calculated:

$$\:Are{a}_{vessel}=\pi\:{\left(\frac{width}{2}\right)}^{2}$$

The ratio between the retinal artery and vein was calculated as the ratio between the areas of the two vessels:

$$\:A{V}_{area}=\left(\frac{{\left(\frac{arter{y}_{width}}{2}\right)}^{2}}{{\left(\frac{vei{n}_{width}}{2}\right)}^{2}}\right)$$

The A/V ratio was calculated for each measurement point and correlated with ICP according to time stamps.

Statistical considerations. The data analysis was performed using Stata 17 (StataCorp LLC, College station, Texas, USA). Patients’ A/V ratio differs from one another as shown in our previous study(2) hence we used a mixed-effect linear regression model for the hierarchical structured data. The correlations between ICP, IOP and A/V ratio from the pooled data were assessed. Furthermore, the A/V ratio was correlated with ICP for ICP≤IOP and ICP > IOP for visualization. The two slopes were then compared using a Wald test to investigate whether ICP > IOP or ICP > 15 mmHg correlated better with the A/V ratio.

40 NICU patients were enrolled in the study. One patient withdrew consent and further 24 patients were excluded by the algorithm due to poor image quality. This left 15 patients included in the final analysis.Baseline characteristics are presented in Table 1. We analyzed a total of 7762 data points with corresponding time matched ICP obtained from the NICU monitor device. IOP ranged from 4 to 13 mmHg (mean: 7.4, SD: 2.1), and ICP ranged from − 1 to 111 mmHg (mean: 10.4, SD: 6.1). Six patients had ICP above 15 mmHg.

Table 1

– Demographic data of the 15 patients included.
Baseline characteristics, n = 15
Gender (Male/Female)	4/11 (27/73)
Mean age (years), [SD]	62.13 [13.91]
Mean BMI (kg/m), [SD]	26.97 [4.27]
Diagnosis at admission
Intracranial hemorrhage, n (%)	5 (33.3)
Subarachnoid hemorrhage, n (%)	5 (33.3)
Traumatic brain injury, n (%)	5 (33.3)

We grouped the patients according to reference ICP as either ICP ≤ 15 mmHg or ICP > 15 mmHg. We found a statistically significant coefficient (regression slope: -0.0659, 95%-CI: [-0.0665;-0.0653], p < 0.001) for the A/V ratio in ICP > 15 mmHg. In the group with ICP≤15 mmHg there was no significant change in A/V ratio with ICP increases below 15 mmHg (regression slope: -2.75x10^− 14, 95%-CI: [-0.0004;0.0004], p = 1.0) (Table 2).

Since IOP might affect vessel diameter due to the external pressure on the vessels, the analyses were repeated with IOP in focus. The correlation between ICP and A/V ratio given ICP > IOP showed a significant negative coefficient (regression slope: -0.0055, 95%-CI: [-0.0062;-0.0048], p < 0.001). However, for ICP≤IOP there was no significant coefficient (regression slope: 0.0022, 95%-CI: [-0.0006;0.0050], p = 0.131) (Table 2).

Table 2

Regression analysis results comparing slopes by ICP and IOP thresholds.
Group	Slope (Mean)	Std. Error	95% Confidence interval	p-value
ICP > 15 mmHg	-0.0659	0.0003	[-0.0665;-0.0653]	< 0.001
ICP≤15 mmHg	-2.75x10^− 14	0.0004	[-0.0004-0.0004]	1.000
ICP > IOP	-0.0055	0.0003	[-0.0062;-0.0048]	< 0.001
ICP≤IOP	0.0022	0.0014	[-0.0006;0.0050]	0.131

A Wald test was used to compare the slope coefficient of ICP > 15 mmHg with the slope coefficient of ICP > IOP. The difference between the slopes was found to be -0.0604 (SE: -0.0005, 95% CI: [-0.0613;-0.0595] (Table 3). The z-statistic was − 130, with a corresponding p-value of < 0.0001. These results suggest that the slope of the relationship between the A/V ratio and ICP > 15 mmHg was significantly different from the slope with ICP > IOP. Specifically, the slope with ICP > 15 mmHg is significantly more negative compared to the slope with ICP > IOP. These findings indicate that the ICP has a greater impact on the A/V ratio than the IOP. Therefore, when the A/V ratio indicates increased ICP, the IOP is less relevant.

Table 3

Results of two-sample z test comparing slopes.
Group	Mean (slope)	Std. Error	95% confidence interval
ICP > 15 mmHg	-0.065886	0.0003005	[-0.066475;-0.065297]
ICP > IOP	-0.0054981	0.0003393	[-0.0061631;-0.0048331]
Difference	-0.0603879	0.0004532	[-0.0612762;-0.0594996]

From the mixed-effect linear regression model, we found an interclass correlation coefficient (ICC) of 0.3895 (SE: 0.088, 95% CI: [0.236;0.568]), indicating that 39% of the variance in ICP measurements can be attributed to differences between patients. This is a moderate level of correlation, suggesting that there is a significant amount of variance explained by patient-specific factors. The model had an R-squared value of 0.5509, indicating, that 55.09% of the variance in ICP measurements can be explained by the predicted values from the model. The F-statistics for the model was 9520.03 (p < 0.001), demonstrating that the model is highly significant.

The modalities’ ability to differentiate between ICP≤15 mmHg and ICP > 15 mmHg was assessed in a sensitivity analysis when not accounting for individual A/V ratios with an area under the curve (AUC) of 0.64. This analysis showed a sensitivity of 80.1%, a specificity of 22.5%, a positive predictive value of 75.7% and negative predictive value of 27.3%, with an A/V ratio cut-off point of 0.75.

This study assessed the potential of non-invasive fundoscopy to estimate ICP by assessing the correlation between the retinal A/V ratio, IOP and ICP. The findings indicate a significant change in A/V ratio with an increasing ICP, particularly > 15 mmHg or ICP > IOP. The slope with ICP > 15 mmHg was significantly more negative than the slope with ICP > IOP, and the stronger negative slope in the ICP > 15 mmHg indicates a more pronounced effect of the increasing ICP on the A/V ratio, whereas the influence of IOP appears to less relevant. Therefore, it is evident that ICP has a greater impact on A/V ratio than IOP. Consequently, when the A/V ratio indicates increased ICP, the IOP is not of great importance. The significant negative correlation between the A/V ratio and ICP > 15 mmHg is the foundation of non-invasive fundoscopy’s potential of identifying patients with elevated ICP, since there is no significant change in A/V ratio for ICP≤15 mmHg, while there is a significant change in A/V ratio ICP > 15 mmHg. Therefore, it is possible to detect relative changes in ICP if multiple measurement points are available on the same patient. The observed relationship supports the hypothesis that increased ICP affects retinal hemodynamics, leading to a lower A/V ratio due to venous distension and compromised venous drainage. This aligns with previous studies that have documented changes in retinal hemodynamics in response to intracranial pressure variations(2, 7, 10).

The study's sensitivity and specificity analysis of >/≤15 mmHg revealed an area under the curve (AUC) of 0.64. Patients exhibit individual A/V ratios to similar ICP but show similar changes in A/V ratio in relation to ICP(2, 7). Despite this problematic physiological variance, the model still correctly identifies 80.1% of cases with ICP > 15 mmHg. However, only 22.5% of cases with ICP≤15 is classified as negative, hence resulting in false positives. This low diagnostic specificity should in future studies be accounted for by improving image quality and investigating whether other variables could be implementing in the model. Further, it should be investigated in future studies if the AI-algorithm could provide retinal findings to enhance the diagnostic specificity and sensitivity.

This study has several limitations. Firstly, the small sample size, with only 15 patients included in the final analysis, limits the generalizability of the findings. The deep learning algorithm exclusion 24 patients from the analysis due to poor image quality due to the widely used anesthetic fentanyl that induces miosis. The CE branded Epicam M camera is optimal for ≥ 4 mm pupils. Therefore, mydriatic drugs would greatly increase the image quality. The miosis and camera quality could also be reasons for the variance in A/V ratio, suggesting further studies also work on enhancing image quality. Secondly, because of the risk of secondary brain injury, the patients were under tight ICP control in the NICU, thus only six patients had an ICP > 15 mmHg. The inaccessibility to high ICP in a human population suggests animal studies with fixed different ICP values should be performed to investigate correlation of high ICP > 25 mmHg.

In conclusion, this study demonstrates the potential of non-invasive fundoscopy as a tool for estimating ICP, corroborating previous findings from our group and enhancing understanding of ocular hemodynamics in relation to ICP. Despite challenges such as image quality and diagnostic specificity, our findings underscore the promise of fundoscopy in clinical applications, particularly in resource-limited settings where invasive monitoring is impractical or impossible.

Future research should prioritize larger, multi-center studies to validate these findings across diverse patient populations and broader ranges of ICP. Additionally, exploring the integration of this non-invasive method into clinical practice and optimizing hardware are crucial steps forward. Animal studies investigating high ICP levels above 25 mmHg could provide further insight into the application of fundoscopy in neurocritical care.

AUC // area under the curve
A/V ratio // Arteriole/Venule ratio
BMI // Body mass index
EVD // External ventricular drain
ICP // Intracranial pressure
IOP // Intraocular pressure
IPPM // Intraparenchymal pressure monitor
mmHg // millimeters of mercury
NICU // Neuro intensive care unit
RoHS // Reduction of Hazardous Substances
SD // Standard deviation

Author Mathias Just Nortvig has received funding by StatuManu ICP ApS for his Ph.D. and undergraduate project and worked as a medical consultant for the company for six month.

Author Mikkel Christian Schou Andersen received partial funding for his Ph.D. by StatuManu ICP ApS.

Author Niclas Lynge Eriksen received funding for his undergraduate project by StatuManu ICP ApS.

All other authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.

Ethical approval:

All procedures performed in studies involving human participants were in accordance with the ethical standards of the Regional Committee on Health Research Ethics for Southern Denmark (S-20190107) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent:

Informed consent was obtained from all individual participants included in the study or from their next-of-kin.

Clinical investigator

MD Asger Bjørnkær Nielsen assisted in obtaining data from included participant.

Author contribution

Mathias Just Nortvig, Mikkel C. Schou Andersen, Christian Bonde Pedersen and Frantz Rom Poulsen planned and organized the project. The data collection was performed by Mathias Just Nortvig and assisted by Asger Bjørnkær Nielsen. The statistical analysis was performed by Mathias Just Nortvig. The data was interpreted by Mathias Just Nortvig, Mikkel C. Schou Andersen and Frantz Rom Poulsen. Preparation and creation of the original draft of the article was performed by Mathias Just Nortvig and all authors commented on previous versions of the manuscript. The manuscript was reviewed, edited and accepted by Mathias Just Nortvig, Mikkel C. Schou Andersen, Jan Saipe Aunan-Diop, Niclas Lynge Eriksen, Christian Bonde Pedersen and Frantz Rom Poulsen.

Data availability statement

All obtained data are available upon reasonable requests. The authors Mathias Just Nortvig, Mikkel Schou Andersen or Frantz Rom Poulsen can be contacted on respectively [email protected], [email protected] or [email protected] for data request.

Acknowledgement

A special thanks to Jakob Find Madsen, the founder of StatuManu, for his help analyzing the data and for lending us the fundoscopy equipment. We would also like to thank Sören Möller from OPEN, SDU, for assisting in the statistical analysis of the data. Lastly, we would like to thank Claire Gudex from BRIDGE, SDU, for her editing the final draft of the article.

Abdul-Rahman A, Morgan W, Jo Khoo Y, Lind C, Kermode A, Carroll W et al (2022) Linear interactions between intraocular, intracranial pressure, and retinal vascular pulse amplitude in the fourier domain. PLoS ONE 17(6):e0270557
Andersen MS, Pedersen CB, Poulsen FR (2020) A new novel method for assessing intracranial pressure using non-invasive fundus images: a pilot study. Sci Rep 10(1):13062
Bratton SL, Chestnut RM, Ghajar J, McConnell Hammond FF, Harris OA, Hartl R et al (2007) Guidelines for the management of severe traumatic brain injury. VI. Indications for intracranial pressure monitoring. J Neurotrauma 24(Suppl 1):S37–44
Carney N, Totten AM, O'Reilly C, Ullman JS, Hawryluk GW, Bell MJ et al (2017) Guidelines for the Management of Severe Traumatic Brain Injury, Fourth Edition. Neurosurgery 80(1):6–15
Godoy DA, Rabinstein AA (2022) How to manage traumatic brain injury without invasive monitoring? Curr Opin Crit Care 28(2):111–122
Güiza F, Depreitere B, Piper I, Citerio G, Chambers I, Jones PA et al (2015) Visualizing the pressure and time burden of intracranial hypertension in adult and paediatric traumatic brain injury. Intensive Care Med 41(6):1067–1076
Hagen SM, Wibroe EA, Korsbaek JJ, Andersen MS, Nielsen AB, Nortvig MJ et al (2023) Retinal vessel dynamics analysis as a surrogate marker for raised intracranial pressure in patients with suspected idiopathic intracranial hypertension. Cephalalgia 43(3):3331024221147494
Havens SJ, Gulati V (2016) Neovascular Glaucoma. Dev Ophthalmol 55:196–204
Khan MN, Shallwani H, Khan MU, Shamim MS (2017) Noninvasive monitoring intracranial pressure - A review of available modalities. Surg Neurol Int 8:51
Moss HE, Vangipuram G, Shirazi Z, Shahidi M (2018) Retinal Vessel Diameters Change Within 1 Hour of Intracranial Pressure Lowering. Transl Vis Sci Technol 7(2):6
Price DA, Grzybowski A, Eikenberry J, Januleviciene I, Verticchio Vercellin AC, Mathew S et al (2020) Review of non-invasive intracranial pressure measurement techniques for ophthalmology applications. Br J Ophthalmol 104(7):887–892
Raboel PH, Bartek J Jr., Andresen M, Bellander BM, Romner B (2012) Intracranial Pressure Monitoring: Invasive versus Non-Invasive Methods-A Review. Crit Care Res Pract 2012:950393
Rangel-Castilla L, Gopinath S, Robertson CS (2008) Management of intracranial hypertension. Neurol Clin 26(2):521–541 x
Rios-Montenegro EN, Anderson DR, David NJ (1973) Intracranial pressure and ocular hemodynamics. Arch Ophthalmol 89(1):52–58
Sigal L (2014) Human Pose Estimation. In: Ikeuchi K (ed) Computer Vision: A Reference Guide. Springer US, Boston, MA, pp 362–370
Sonig A, Jumah F, Raju B, Patel NV, Gupta G, Nanda A (2020) The Historical Evolution of Intracranial Pressure Monitoring. World Neurosurg 138:491–497
Stein DM, Hu PF, Brenner M, Sheth KN, Liu KH, Xiong W et al (2011) Brief episodes of intracranial hypertension and cerebral hypoperfusion are associated with poor functional outcome after severe traumatic brain injury. J Trauma 71(2):364–373 discussion 73 – 4
Tariq A, Aguilar-Salinas P, Hanel RA, Naval N, Chmayssani M (2017) The role of ICP monitoring in meningitis. Neurosurg Focus 43(5):E7
Tavakoli S, Peitz G, Ares W, Hafeez S, Grandhi R (2017) Complications of invasive intracranial pressure monitoring devices in neurocritical care. Neurosurg Focus 43(5):E6
Xu R, Lin H, Lu K, Cao L, Liu Y (2021) A Forest Fire Detection System Based on Ensemble Learning. Forests 12(2):217

Competing interest reported. Author Mathias Just Nortvig has received funding by StatuManu ICP ApS for his Ph.D. and undergraduate project and worked as a medical consultant for the company for six month. Author Mikkel C Schou Andersen received partial funding for his Ph.D. by StatuManu ICP ApS. Author Niclas Lynge Eriksen received funding for his undergraduate project by StatuManu ICP ApS.

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Utilizing Retinal Arteriole/Venule Ratio to Estimate Intracranial Pressure

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