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Article

Thoracic Biometry in Patients with Congenital Diaphragmatic Hernia, a Magnetic Resonance Imaging Study

by
Erick George Neștianu
1,2,*,
Septimiu Popescu
2,3,
Dragoș Ovidiu Alexandru
4,
Laura Giurcăneanu
5 and
Radu Vlădăreanu
1,6
1
Faculty of Medicine, “Carol Davila” University of Medicine and Pharmacy, 030167 Bucharest, Romania
2
Hôpital Bicêtre AP-HP, 94270 Le Kremlin-Bicêtre, France
3
Faculty of Medicine, L’Université Paris-Saclay, 75015 Paris, France
4
Department of Medical Informatics and Bio-Statistics, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania
5
University Hospital of Coventry and Warwickshire NHS Trust, Coventry CV2 2DX, UK
6
Department of Obstetrics and Gynecology, Elias University Emergency Hospital, 011461 Bucharest, Romania
*
Author to whom correspondence should be addressed.
Diagnostics 2024, 14(6), 641; https://doi.org/10.3390/diagnostics14060641
Submission received: 12 February 2024 / Revised: 9 March 2024 / Accepted: 14 March 2024 / Published: 18 March 2024
(This article belongs to the Special Issue Advanced MRI Imaging and Diagnostics in Lung Disease)

Abstract

:
This is a retrospective study investigating biometric measurements using magnetic resonance imaging (MRI) examinations in congenital diaphragmatic hernia (CDH). CDH is one of the more common causes of pulmonary hypoplasia, with grave consequences for the fetus. Inclusion criteria were patients diagnosed with CDH as the only observed anomaly, who underwent MRI examination after the second-trimester morphology ultrasound. The patients came from three university hospitals in Bucharest, Romania. In total, 19 patients were included in the study after applying exclusion criteria. Comparing the observed values of the thoracic transverse diameter, the thoracic anterior–posterior diameter, the thoracic circumference, the thoracic area, and the thoracic volume with values from the literature, we observed a predictive alteration of these parameters, with most showing Gaussian distribution. We observed statistical significance for most of our correlations, except between the observed and expected thoracic anterior–posterior diameters and the observed and expected thoracic volume values. This is very helpful when complex studies that can calculate the pulmonary volume cannot be obtained, as in the case of movement artifacts, and allows the clinicians to better assess the severity of the disease. MRI follow-up in CDH cases is a necessity, as it offers the most accurate thoracic biometry.

1. Introduction

Before talking about congenital diaphragmatic hernia (CDH), first we must pass over what makes it such a difficult disease to manage, that being the apparition of pulmonary hypoplasia.
Pulmonary hypoplasia is characterized by an abnormal, incomplete development of the fetal lung with various consequences for the fetal development. This might lead to various levels of respiratory insufficiency after birth [1].
It affects about 1.4% of total live births, although the real prevalence is not known. The Fetal Medicine Foundation considers the prevalence to be about one in fifty thousand births [2,3].
The origin of pulmonary hypoplasia is the incomplete development of pulmonary tissue. This phenomenon can happen unilaterally or bilaterally. Clinically, respiratory failure might be present depending on the missing pulmonary volume, the number of remaining alveoli, and the correct development of the bronchial ramifications. Severity is heavily dependent on the moment the injuring factor appears during embryo development. Early lesions will cause more damage and increase the severity [4].
We know of multiple intrathoracic (extralobar sequestration, diaphragm agenesis, mediastinal masses or tumors) or extrathoracic (oligoamnios, preterm premature rupture of membranes, skeletal dysplasia, large intraabdominal masses, and neuromuscular conditions) causes that determine pulmonary hypoplasia, with different pathophysiological pathways [5,6,7].
Mechanical stimuli are also an important part of lung development. They appear at around ten weeks of gestation, providing needed stimulation to the epithelial cells by allowing the movement of fluids through the airways [8].
The leading cause of pulmonary hypoplasia is congenital diaphragmatic hernia, followed by pulmonary sequestration, mediastinal masses (teratoma, thymoma), and perfusion anomalies [9]. The most vulnerable to negative influences for the lung is the pseudo-glandular phase when we see a rapid development of vascular structures and the bronchial airways [2].
The first line in detecting CDH is the first-trimester ultrasound. In addition to observing the diaphragmatic defect and/or herniated organs in the thoracic cavity, a few standardized measurements are taken. The lung-to-head ratio (LHR) is a well-established measurement but one that is unreliable, tending to underestimate the severity of lung hypoplasia. In addition to this, we can also look at thoracic biometric values of the anterior and transverse diameters, thoracic area, and thoracic circumference.
Another element that we come to observe is a major mediastinal shift. As such, the position and size of the heart might also provide insight when assessing these cases. Although multiple 2D measurements can be made, the best assessment method is calculating the lung volume [10].
3D sonography is not used for routine lung volumetry because it is too time-consuming and might not be an accurate predictive tool. Using multiplanar mode allows the simultaneous display of three perpendicular views of the lung, thus obtaining its volume [10].
For a rigorous and accurate severity assessment, the patient should have a high-resolution ultrasound, with an eventual virtual organ computer-aided analysis (VOCAL) study, magnetic resonance imaging (MRI), echocardiography, and genetic testing between 20 and 24 weeks gestation. This leaves sufficient time to terminate the pregnancy if needed and also to offer rigorous parental counseling envisioning the possible treatments and management but also the possible complications and outcomes [11,12].
Fetal MRI is already an established and frequently used method to further explore lung hypoplasia in the case of CDH, providing excellent soft tissue contrast and high spatial resolution with a large field of view [10,13].
In the case of CDH, studies have shown that MRI is a better survival predictor, followed by the 3D and 2D methods, although the lung-to-head ratio (LHR) method is not to be ignored, still showing its utility in many cases [14].
In this study, we aim to look at the correlation between 2D and 3D volume biometric values obtained by MRI and ultrasound to see if other important features can be used in severity assessment other than the direct measurement of total pulmonary volume. The importance of correct diagnosis of pulmonary hypoplasia is due to the special treatment needed for these patients. They should be surveyed in specialized institutions with trained and experienced teams [15].

2. Materials and Methods

This is a multicenter retrospective study. Data were collected between January 2019 and December 2022 from three university hospitals in Bucharest, Romania, specializing in antenatal diagnosis and treatment.
We included patients who underwent second-trimester fetal morphology screening in these hospitals. Pregnancy had to occur naturally, without in vitro fertilization, and CDH had to be the only observable anomaly in these patients. All patients signed a formal consent form before entering the study. Approval from the hospitals’ Ethical Committee was also obtained before the beginning of the study in December 2017, protocol number 3180.Patient follow-up was performed as per ISUOG guidelines for the second and third trimesters.
The inclusion criteria were as follows: naturally pregnant women (not by in vitro fertilization) who had undergone the second-trimester fetal morphology ultrasound in specialized diagnosis centers that had discovered a CDH as the only observable malformation and who had had a follow-up MRI examination to confirm or complete the ultrasound diagnosis.
The ultrasound examination was performed on devices dedicated to obstetrical and fetal morphology analysis using specialized transducers.
For the MRI examination, we used 1.5 Tesla machines, as current guidelines dictate, with the aid of body coils. The usual sequences used were Fast Imaging Employing Steady State Acquisition (FIESTA), Single Shot Fast Spin Echo (SSFSE), Liver Acquisition with Volume Acceleration (LAVA), and occasionally diffusion-weighted Weighted Image (DWI). The slice thickness was between 2 and 6 mm depending on the presence or absence of movement artifacts. The investigation was made with the mother in a supine or lateral position, using sedation (premedication with 7.5 mg of Zopiclone) in most cases.
Fetal lung volume was calculated by using a new method to reduce the overestimation of the lung volume. The first step was tracing the lung area of both lungs on each slice. We then obtained the mean between every 2 consecutive slices and multiplied the value by the distance between them. Finally, we calculated the sum of all these values and obtained the TLV for each lung. For easier viewing of this parameter, we calculated the total lung volume ratio (TLVR) by calculating the ratio between our observed value and the expected lung volume values obtained from reference articles that measured standard values for lung volumetry using MRI. To be more precise, we looked at the studies of Meyers et al., Rypens et al., Osada et al., and Sefidbakht et al. [16,17,18,19] and calculated a mean from them that was used as our reference. Figure 1 and Figure 2.
We also compared our findings with the expected values obtained by using ultrasound volumetry as per the work of Lian et al. [20].
For a better visualization of these values, we calculated the total lung volume MRI index by dividing the observed value of the lung volume by the expected value calculated with the aforementioned method. We also made the same calculation using expected pulmonary volume values from ultrasound studies [20].
Lung tracing was undertaken in general in the axial plane, but we also made use of the coronal or sagittal planes in some cases where the axial acquisition was artifacts by the movement of the fetus.
We also measured fetal biometrics such as the transverse and anterior–posterior diameters of the thoracic cavity. To further study the effect of the herniated organs on the thoracic cavity we also measured the thoracic area and perimeter following the same methods used by ** the herniation defect and its size. This information is of great help to the surgeon, who will have to rigorously plan ahead of time in complicated cases. Moreover, as shown in the studies of Prayer et al., 3D reconstruction is feasible and repeatable. They have proven a high correlation with postnatal and postmortem data, observing that the relative size of the diaphragmatic defect remains the same after the second trimester. This might become a new standard for surgery preparations, as with the advances in 3D printing and new regenerative tissue engineering, we might see the apparition of specially made-to-measure patches that can be used to close the diaphragmatic defect. Our team has also started using this method to help with the surgery prep, and we have had good feedback from the surgery teams. Although the dimensions and morphology of the defect were not a key part of this study, we started collecting data and are interested in further looking into this subject in the future.
Among other therapeutic options that can benefit from early diagnosis and staging is the fetoscopic endoluminal tracheal occlusion (FETO). It is an invasive method that requires an experienced team to operate. It requires a fetoscopic approach that aims to implant a detachable balloon during gestation in the trachea of the fetus. The balloon is then removed around 34 weeks. Inclusion criteria for the procedure might vary from center to center, but they usually include singleton pregnancy and isolated CDH with a severe prognosis [31]. Regarding lung size, an increase in volume has been observed in a majority of patients. Ultrasound changes can be visualized as soon as 48 h after the procedure. At the moment, the exact indications and results of the method are still being discussed. While studies show an increase in survivability, they have also proved that there is a high probability of premature birth and other complications, such as premature rupture of membranes. A connection has also been seen between rates of extracorporeal membrane oxygenation (ECMO) utilization and severe pulmonary hypertension. It appears that the risk for these two complications is less in patients that underwent ECMO [32].
An older technique that might still prove its usefulness is the in utero correction of the defect. With newer and more advanced materials and imaging methods, this rather old method might still be improved upon and come forth as a viable alternative to the FETO procedure. It is worth mentioning that there is great debate about which method is more suited to be used in the case of CDH, with both having pros and cons. As the FETO technique is more recent, there is a need for further and rigorous study of the method before it can be considered the standard of therapy in these cases. It is important to take notice of the fact that in utero correction has been proven to be effective only as long as there is no liver ascension in the thoracic cavity. This clearly shows that this method is also not perfect and that it can be improved upon [33,34].
Among the limitations of our study, we have to take into account that not all the patients were monitored in the same hospital and that many of them came from other hospitals for investigations. This makes communication with the clinician difficult, and it also has the added effect of not having access to the full case file of the patients and most importantly to the ultrasound imaging. Another limitation is the fact that there were some cases when the MRI series were suboptimal in terms of quality, but this is to be expected when working with fetuses that present physiological movements during gestation. Finally, we may add the fact that we lack access to the patient files and imaging from other hospitals, thus having a smaller lot of patients in this study. In the future, we hope to recruit more patients for our studies.

5. Conclusions

Correct assessment and management of CDH patients can be difficult, and, in some cases, MRI or 3D ultrasound studies might not be easily accessible. In these cases, to not lose time in a somewhat small window, we should look at more accessible 2D techniques that are readily available. From what we have found, the transverse diameter, thoracic area, and thoracic circumference are the most reliable values when it comes to assessing severity. We should also not forget about the LHR, but we advise against using it as the only source of severity assessment. This information allows us to also put a greater value on highly artifacted MRI examinations in which volumetry is not obtainable, as we could also make good use of the available sections. Early diagnosis will allow better management of each patient, as the development of FETO might prove to have great benefits in the future, aiding in the recovery of lost pulmonary volume.

Author Contributions

Conceptualization, R.V.; Methodology, E.G.N.; Software, D.O.A.; Validation, E.G.N., S.P., L.G. and R.V.; Formal analysis, L.G.; Investigation, E.G.N. and L.G.; Resources, E.G.N.; Data curation, S.P.; Writing—original draft, E.G.N.; Writing—review & editing, E.G.N., S.P. and R.V.; Supervision, R.V. All authors have read and agreed to the published version of the manuscript.

Funding

Publication of this paper was supported by the University of Medicine and Pharmacy Carol Davila, through the institutional program Publish not Perish.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee) of Elias Emergency Hospital of Bucharest (protocol code 3180, December 2017).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. MRI axial T2 weighted image of the fetus showing the tracing method for calculating the lung volume, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the lug area on the nonherniated side.
Figure 1. MRI axial T2 weighted image of the fetus showing the tracing method for calculating the lung volume, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the lug area on the nonherniated side.
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Figure 2. Ultrasound axial four-chamber image of the fetus showing the tracing method for calculating the LHR, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the lug area on the nonherniated side.
Figure 2. Ultrasound axial four-chamber image of the fetus showing the tracing method for calculating the LHR, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the lug area on the nonherniated side.
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Figure 3. MRI axial T2 weighted image of the fetus showing how to measure the anterior–posterior and transverse diameters of the thorax, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green lines represent the lug transverse and anterior-posterior diameters.
Figure 3. MRI axial T2 weighted image of the fetus showing how to measure the anterior–posterior and transverse diameters of the thorax, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green lines represent the lug transverse and anterior-posterior diameters.
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Figure 4. Ultrasound axial four-chamber image of the fetus showing how to measure the anterior–posterior and transverse diameters of the thorax, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green lines represent the lug transverse and anterior-posterior diameters.
Figure 4. Ultrasound axial four-chamber image of the fetus showing how to measure the anterior–posterior and transverse diameters of the thorax, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green lines represent the lug transverse and anterior-posterior diameters.
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Figure 5. MRI axial T2 weighted image of the fetus showing how to measure the thoracic circumference, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the thoracic circumference.
Figure 5. MRI axial T2 weighted image of the fetus showing how to measure the thoracic circumference, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the thoracic circumference.
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Figure 6. Ultrasound axial four-chamber image of the fetus showing how to measure the thoracic circumference, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the thoracic circumference.
Figure 6. Ultrasound axial four-chamber image of the fetus showing how to measure the thoracic circumference, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the thoracic circumference.
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Figure 7. MRI axial T2 weighted image of the fetus showing how to measure the thoracic area, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the thoracic area.
Figure 7. MRI axial T2 weighted image of the fetus showing how to measure the thoracic area, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the thoracic area.
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Figure 8. Ultrasound axial four-chamber image of the fetus showing how to measure the thoracic area, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the thoracic area.
Figure 8. Ultrasound axial four-chamber image of the fetus showing how to measure the thoracic area, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the thoracic area.
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Figure 9. MRI sagittal T2 weighted image of the fetus showing the tracing method for calculating the thoracic volume, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the thoracic area on the herniated side. The p in the image stands for perimeter.
Figure 9. MRI sagittal T2 weighted image of the fetus showing the tracing method for calculating the thoracic volume, using the RadiAnt DICOM Viewer program, version number 2022.1.1. The green line represents the thoracic area on the herniated side. The p in the image stands for perimeter.
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Table 1. Statistical analysis of the distribution of various variables from our study.
Table 1. Statistical analysis of the distribution of various variables from our study.
VariableMinimumMaximumMeanStd. Deviationp Anderson–DarlingInterpretation
Observed thoracic tr mm42.0077.0059.219.350.8132Gaussian distribution
Observed thoracic ap mm30.0065.0044.0010.390.0556Gaussian distribution
Observed thoracic circumference mm147.00286.00217.5840.640.6961Gaussian distribution
Observed thoracic area mm21219.004656.002765.531037.800.0721Gaussian distribution
Observed thoracic volume mL31.42177.7984.6050.380.0040non-Gaussian distribution
Observed lung-to-thoracic volume ratio0.050.390.180.080.0407non-Gaussian distribution
Expected thoracic tr mm40.8066.3054.747.950.1238Gaussian distribution
Expected thoracic ap mm29.4056.4043.798.830.1289Gaussian distribution
Expected thoracic circumference mm144.60254.30204.0934.230.1457Gaussian distribution
Expected thoracic area mm21565.004599.003070.321010.040.0578Gaussian distribution
Expected total pulmonary volume (mL) VOCAL study13.5464.6738.4516.990.0589Gaussian distribution
Expected thoracic volume27.10114.2370.2228.750.0761Gaussian distribution
Total pulmonary volume index VOCAL comparison0.080.690.370.140.2561Gaussian distribution
Expected lung-to-thoracic volume ratio0.500.570.540.020.1867Gaussian distribution
Observed total pulmonary volume (mL)1.680031.470014.03167.32880.9550Gaussian distribution
Expected total pulmonary volume (mL) mean MRI studies15.244464.078639.776815.26390.1321Gaussian distribution
Total pulmonary volume index MRI comparison0.07090.62810.34940.13440.4444Gaussian distribution
Table 2. Statistical analysis of the correlation between various variables from our study.
Table 2. Statistical analysis of the correlation between various variables from our study.
Variable 1Variable 2p StudentSignificance
Observed thoracic tr mmExpected thoracic tr mm0.0002HS
Observed thoracic ap mmExpected thoracic ap mm0.8797NS
Observed thoracic circumference mmExpected thoracic circumference mm0.0005HS
Observed thoracic area mm2Expected thoracic area mm20.0042S
Observed thoracic volume mLExpected thoracic volume0.0518NS
Observed lung-to-thoracic volume ratioExpected lung-to-thoracic volume ratio0.0000HS
Observed total pulmonary volume (mL)Expected total pulmonary volume (mL) mean MRI studies0.0000HS
Observed total pulmonary volume (mL)Expected total pulmonary volume (mL) VOCAL study0.0000HS
Total pulmonary volume index MRI comparisonTotal pulmonary volume index VOCAL comparison0.0035S
Expected total pulmonary volume (mL) mean MRI studiesExpected total pulmonary volume (mL) VOCAL study0.0112S
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MDPI and ACS Style

Neștianu, E.G.; Popescu, S.; Alexandru, D.O.; Giurcăneanu, L.; Vlădăreanu, R. Thoracic Biometry in Patients with Congenital Diaphragmatic Hernia, a Magnetic Resonance Imaging Study. Diagnostics 2024, 14, 641. https://doi.org/10.3390/diagnostics14060641

AMA Style

Neștianu EG, Popescu S, Alexandru DO, Giurcăneanu L, Vlădăreanu R. Thoracic Biometry in Patients with Congenital Diaphragmatic Hernia, a Magnetic Resonance Imaging Study. Diagnostics. 2024; 14(6):641. https://doi.org/10.3390/diagnostics14060641

Chicago/Turabian Style

Neștianu, Erick George, Septimiu Popescu, Dragoș Ovidiu Alexandru, Laura Giurcăneanu, and Radu Vlădăreanu. 2024. "Thoracic Biometry in Patients with Congenital Diaphragmatic Hernia, a Magnetic Resonance Imaging Study" Diagnostics 14, no. 6: 641. https://doi.org/10.3390/diagnostics14060641

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