Fetal body organ T2* relaxometry at low field strength (FOREST).

Fetal Magnetic Resonance Imaging (MRI) at low field strengths is an exciting new field in both clinical and research settings. Clinical low field (0.55T) scanners are beneficial for fetal imaging due to their reduced susceptibility-induced artifacts, increased T2* values, and wider bore (widening access for the increasingly obese pregnant population). However, the lack of standard automated image processing tools such as segmentation and reconstruction hampers wider clinical use. In this study, we present the Fetal body Organ T2* RElaxometry at low field STrength (FOREST) pipeline that analyzes ten major fetal body organs. Dynamic multi-echo multi-gradient sequences were acquired and automatically reoriented to a standard plane, reconstructed into a high-resolution volume using deformable slice-to-volume reconstruction, and then automatically segmented into ten major fetal organs. We extensively validated FOREST using an inter-rater quality analysis. We then present fetal T2* body organ growth curves made from 100 control subjects from a wide gestational age range (17-40 gestational weeks) in order to investigate the relationship of T2* with gestational age. The T2* values for all organs except the stomach and spleen were found to have a relationship with gestational age (p<0.05). FOREST is robust to fetal motion, and can be used for both normal and fetuses with pathologies. Low field fetal MRI can be used to perform advanced MRI analysis, and is a viable option for clinical scanning.

Development of fetal magnetic resonance imaging (MRI) phantom.

Background: Anthropomorphic phantoms play an important role in routine clinical practice. They can be used to calibrate magnetic resonance imaging (MRI) scanners, control the diagnostic equipment quality, and reduce the acquisition time. The latter is especially critical for diagnosing fetal anomalies, which requires optimal image quality within the shortest possible time. This paper aims to develop an MRI fetal phantom and determine the materials that best mimic the magnetic resonance (MR) characteristics of its internal organs. Future phantom features will include simulations of fetal limb movements. Methods: A single MRI study of a pregnant woman at 20 weeks 3 days of gestation was used as a reference and for image segmentation. Anonymized Digital Imaging and Communication in Medicine (DICOM) files were imported into 3D Slicer v. 5.2.1 for segmentation of the uterus, fetus, and internal organs. Based on the performed segmentation, a three-dimensional model was obtained for printing on a 3D printer. The mold was 3D printed on an Anycubic Photon M3 Max printer. The paper showcases the selection and manufacturing of compositions to simulate the relaxation times of the fetal organs. Formulations for emulsions and carrageenan- and agar-based hydrogels are presented. The selected compositions were used to fill the 3D printed model. Results: Statistical analysis showed no significant differences in absolute and relative signal values obtained from scans of a pregnant woman at 20 weeks and 3 days and a fetal phantom. Conclusions: During the study, an anthropomorphic fetal phantom was constructed, filled with compositions with relaxation times T1 and T2 similar to the control values of the corresponding tissues. The phantom can be used to set up and optimize fetal MRI protocols, train and educate medical students, residents, graduate students, and X-ray technicians, as well as to timely control image quality and equipment serviceability.

A rare case report: The value of fetal MRI to detect diprosopus twins.

Diprosopus is one of the rarest types of conjoined twins, caused by incomplete zygote separation in early pregnancy. It defines a condition with duplication of facial structures, monocephalic and 1 trunk. Early detection is difficult, but fetal MRI plays an important role in strengthening antenatal diagnosis of conjoined twin pregnancies and other major congenital abnormalities, complementing antenatal ultrasonography. A 28-year-old patient (G2P1A0) was referred from the regional general hospital for suspected malformations, including Dandy-Walker syndrome and a small mandible Antenatal 3-D ultrasound at 35 weeks revealed a single baby with macrosomia, hypoplasia of the vermis, and cleft lip with malformation of facial structures. A 3 Tesla MRI (Signa, GE Healthcare) revealed various developmental brain anomalies, including duplication of the frontotemporal lobes, corpus callosum agenesis, and small posterior fossa. The identification of 4 orbital structures raised suspicions of face duplication. This patient underwent a caesarean section and delivered a diprosopus twin baby. MRI emerged as an indispensable adjunct, complementing ultrasound in detecting congenital malformations. The success of this approach emphasizes collaborative efforts between clinicians and radiologists for accurate identification and management of complex fetal anomalies.

Holoprosencephaly spectrum: an up-to-date overview of classification, genetics and neuroimaging.

Holoprosencephaly (HPE) is a complex forebrain congenital malformation with widely variable outcomes. It represents a disorder of ventral induction, which begins in the fifth gestational week. Its main feature is forebrain cleavage failure, which prevents the brain complete division into right and left hemispheres, the normal development of midline structures, and the deep brain structure. Based on the severity of prosencephalic cleavage failure, three classic forms (lobar, semilobar, and alobar) were described, and subsequently, interhemispheric variant (syntelencephaly) and septopreoptic variants were proposed. This review proposes a practical imaging approach to diagnosing HPE spectrum disorders, allowing an easier recognition and earlier diagnosis, which is essential for prenatal care and adequate parental counseling. In addition, we intend to simplify the understanding of HPE through a didactic discussion, schematic illustrations, and descriptions of each entity's current classification and critical neuroimaging features, as well as the main differential diagnosis of HPE.

Fetal-BET: Brain Extraction Tool for Fetal MRI.

Goal: In this study, we address the critical challenge of fetal brain extraction from MRI sequences. Fetal MRI has played a crucial role in prenatal neurodevelopmental studies and in advancing our knowledge of fetal brain development in-utero. Fetal brain extraction is a necessary first step in most computational fetal brain MRI pipelines. However, it poses significant challenges due to 1) non-standard fetal head positioning, 2) fetal movements during examination, and 3) vastly heterogeneous appearance of the developing fetal brain and the neighboring fetal and maternal anatomy across gestation, and with various sequences and scanning conditions. Development of a machine learning method to effectively address this task requires a large and rich labeled dataset that has not been previously available. Currently, there is no method for accurate fetal brain extraction on various fetal MRI sequences. Methods: In this work, we first built a large annotated dataset of approximately 72,000 2D fetal brain MRI images. Our dataset covers the three common MRI sequences including T2-weighted, diffusion-weighted, and functional MRI acquired with different scanners. These data include images of normal and pathological brains. Using this dataset, we developed and validated deep learning methods, by exploiting the power of the U-Net style architectures, the attention mechanism, feature learning across multiple MRI modalities, and data augmentation for fast, accurate, and generalizable automatic fetal brain extraction. Results: Evaluations on independent test data, including data available from other centers, show that our method achieves accurate brain extraction on heterogeneous test data acquired with different scanners, on pathological brains, and at various gestational stages. Conclusions:By leveraging rich information from diverse multi-modality fetal MRI data, our proposed deep learning solution enables precise delineation of the fetal brain on various fetal MRI sequences. The robustness of our deep learning model underscores its potential utility for fetal brain imaging.

Preserved prenatal lung growth assessed by fetal MRI in the omicron-dominated phase of the SARS-CoV-2 pandemic.

OBJECTIVES: With SARS-CoV-2 evolving, disease severity and presentation have changed due to changes in mechanisms of entry and effector site as well as due to effects of vaccination- and/or infection-acquired immunity. We re-assessed fetal lung pathology in pregnancies with uncomplicated SARS-CoV-2 infections during the late, omicron-dominated pandemic phase to inform disease understanding and pregnancy consultation. METHODS: In this case-control study, fetal lung volumes were assessed by fetal MRI in 24 pregnancies affected by mild maternal SARS-CoV-2 infection during the omicron-dominated pandemic phase with prevailing immunity through vaccination and/or prior SARS-CoV-2 infection. RESULTS: Fetal lung volumes (normalized to estimated fetal weight) in 24 pregnancies (GA 33.3 ± 3.8, 12 female fetuses) following mild, uncomplicated SARS-CoV-2 infection did not differ significantly from both, published reference values (96.3% ± 22.5% of 50th percentile reference values, p = 0.43), or fetal lung volumes of a site-specific, non-COVID control group (n = 15, 94.2% ± 18.5%, p = 0.76). Placental assessment revealed no group differences in thrombotic changes or placental heterogeneity (p > 0.05, respectively), and fetal lung volume did not correlate with placental heterogeneity when adjusting for gestational age at scan (p > 0.05). CONCLUSION: Assessment of fetal lung volume by MRI revealed unaffected lung growth in pregnancies affected by uncomplicated SARS-CoV-2 infection in the omicron-dominated pandemic phase in the presence of prevailing hybrid immunity. This finding contrasts sharply with the observed reduction in fetal lung volume following maternal alpha-variant infection in the pre-vaccination era and might reflect tropism- as well as immunity-related effects. KEY POINTS: Question: Is fetal lung development affected by mild maternal SARS-CoV-2 infection during the omicron-dominated phase of the pandemic? FINDINGS: Fetal lung volume in 24 affected pregnancies did not differ significantly from published reference values or fetal lung volumes in 15 site-specific, non-COVID-affected control pregnancies. CLINICAL RELEVANCE: Preserved fetal lung volume following mild maternal SARS-CoV-2 infection during the omicron-dominated phase contrasts with previous findings of reduced volume in unvaccinated pregnancies during the alpha-dominated pandemic phase. These observations might reflect tropism- as well as immunity-related effects.

ScribSD+: Scribble-supervised medical image segmentation based on simultaneous multi-scale knowledge distillation and class-wise contrastive regularization.

Despite that deep learning has achieved state-of-the-art performance for automatic medical image segmentation, it often requires a large amount of pixel-level manual annotations for training. Obtaining these high-quality annotations is time-consuming and requires specialized knowledge, which hinders the widespread application that relies on such annotations to train a model with good segmentation performance. Using scribble annotations can substantially reduce the annotation cost, but often leads to poor segmentation performance due to insufficient supervision. In this work, we propose a novel framework named as ScribSD+ that is based on multi-scale knowledge distillation and class-wise contrastive regularization for learning from scribble annotations. For a student network supervised by scribbles and the teacher based on Exponential Moving Average (EMA), we first introduce multi-scale prediction-level Knowledge Distillation (KD) that leverages soft predictions of the teacher network to supervise the student at multiple scales, and then propose class-wise contrastive regularization which encourages feature similarity within the same class and dissimilarity across different classes, thereby effectively improving the segmentation performance of the student network. Experimental results on the ACDC dataset for heart structure segmentation and a fetal MRI dataset for placenta and fetal brain segmentation demonstrate that our method significantly improves the student's performance and outperforms five state-of-the-art scribble-supervised learning methods. Consequently, the method has a potential for reducing the annotation cost in developing deep learning models for clinical diagnosis.

Characterizing T1 in the fetal brain and placenta over gestational age at 0.55T.

PURPOSE: T1 mapping and T1-weighted contrasts have a complimentary but currently under utilized role in fetal MRI. Emerging clinical low field scanners are ideally suited for fetal T1 mapping. The advantages are lower T1 values which results in higher efficiency and reduced field inhomogeneities resulting in a decreased requirement for specialist tools. In addition the increased bore size associated with low field scanners provides improved patient comfort and accessibility. This study aims to demonstrate the feasibility of fetal brain T1 mapping at 0.55T. METHODS: An efficient slice-shuffling inversion-recovery echo-planar imaging (EPI)-based T1-mapping and postprocessing was demonstrated for the fetal brain at 0.55T in a cohort of 38 fetal MRI scans. Robustness analysis was performed and placental measurements were taken for validation. RESULTS: High-quality T1 maps allowing the investigation of subregions in the brain were obtained and significant correlation with gestational age was demonstrated for fetal brain T1 maps ( p < 0 . 05 $$ p<0.05 $$ ) as well as regions-of-interest in the deep gray matter and white matter. CONCLUSIONS: Efficient, quantitative T1 mapping in the fetal brain was demonstrated on a clinical 0.55T MRI scanner, providing foundations for both future research and clinical applications including low-field specific T1-weighted acquisitions.

Automatic cortical surface parcellation in the fetal brain using attention-gated spherical U-net.

Cortical surface parcellation for fetal brains is essential for the understanding of neurodevelopmental trajectories during gestations with regional analyses of brain structures and functions. This study proposes the attention-gated spherical U-net, a novel deep-learning model designed for automatic cortical surface parcellation of the fetal brain. We trained and validated the model using MRIs from 55 typically developing fetuses [gestational weeks: 32.9 ± 3.3 (mean ± SD), 27.4-38.7]. The proposed model was compared with the surface registration-based method, SPHARM-net, and the original spherical U-net. Our model demonstrated significantly higher accuracy in parcellation performance compared to previous methods, achieving an overall Dice coefficient of 0.899 ± 0.020. It also showed the lowest error in terms of the median boundary distance, 2.47 ± 1.322 (mm), and mean absolute percent error in surface area measurement, 10.40 ± 2.64 (%). In this study, we showed the efficacy of the attention gates in capturing the subtle but important information in fetal cortical surface parcellation. Our precise automatic parcellation model could increase sensitivity in detecting regional cortical anomalies and lead to the potential for early detection of neurodevelopmental disorders in fetuses.

Correlation of fetal lung area with MRI derived pulmonary volume.

BACKGROUND: Neonatal chest-Xray (CXR)s are commonly performed as a first line investigation for the evaluation of respiratory complications. Although lung area derived from CXRs correlates well with functional assessments of the neonatal lung, it is not currently utilised in clinical practice, partly due to the lack of reference ranges for CXR-derived lung area in healthy neonates. Advanced MR techniques now enable direct evaluation of both fetal pulmonary volume and area. This study therefore aims to generate reference ranges for pulmonary volume and area in uncomplicated pregnancies, evaluate the correlation between prenatal pulmonary volume and area, as well as to assess the agreement between antenatal MRI-derived and neonatal CXR-derived pulmonary area in a cohort of fetuses that delivered shortly after the antenatal MRI investigation. METHODS: Fetal MRI datasets were retrospectively analysed from uncomplicated term pregnancies and a preterm cohort that delivered within 72 h of the fetal MRI. All examinations included T2 weighted single-shot turbo spin echo images in multiple planes. In-house pipelines were applied to correct for fetal motion using deformable slice-to-volume reconstruction. An MRI-derived lung area was manually segmented from the average intensity projection (AIP) images generated. Postnatal lung area in the preterm cohort was measured from neonatal CXRs within 24 h of delivery. Pearson correlation coefficient was used to correlate MRI-derived lung volume and area. A two-way absolute agreement was performed between the MRI-derived AIP lung area and CXR-derived lung area. RESULTS: Datasets from 180 controls and 10 preterm fetuses were suitable for analysis. Mean gestational age at MRI was 28.6 ± 4.2 weeks for controls and 28.7 ± 2.7 weeks for preterm neonates. MRI-derived lung area correlated strongly with lung volumes (p < 0.001). MRI-derived lung area had good agreement with the neonatal CXR-derived lung area in the preterm cohort [both lungs = 0.982]. CONCLUSION: MRI-derived pulmonary area correlates well with absolute pulmonary volume and there is good correlation between MRI-derived pulmonary area and postnatal CXR-derived lung area when delivery occurs within a few days of the MRI examination. This may indicate that fetal MRI derived lung area may prove to be useful reference ranges for pulmonary areas derived from CXRs obtained in the perinatal period.

Magnetic resonance imaging of intracranial anomalies in pregnancies complicated by twin anemia-polycythemia sequence.

PURPOSE: To describe fetal brain Magnetic Resonance Imaging (MRI) findings in a large series of monochorionic (MC) pregnancies complicated by Twin Anemia-Polycythemia Sequence (TAPS) prenatally diagnosed, so to characterize the potential intracranial complications associated with this condition, their frequency and potential treatment options. METHODS: This is a retrospective study of MC twin pregnancies complicated by TAPS and undergone fetal MRI in a single institution from 2006 to 2023. MRI control was performed and post-natal ultrasound (US) or MRI were available. RESULTS: 1250 MC pregnancies were evaluated in our institution. 50 pregnancies (4%) were diagnosed with TAPS, 29 underwent a fetal brain MRI. 13/29 pregnancies (44.8%) demonstrated brain findings at MRI in at least a twin. Neuroradiological findings were detected in 14/57 twins (24.6%). We detected four main categories of findings: hemorrhagic lesions, T2-weighted white-matter hyperintensities (WMH), brain edema-swelling and venous congestion. Nineteen findings were present in the anemic and three in the polycythemic twins, with a statistically significant ratio between the two groups (p-value = 0.01). Intrauterine MRI follow-up demonstrated the sequalae of hemorrhagic lesions. A complete regression of brain swelling, veins prominence and T2-WMHs was demonstrated after treatment. Postnatal imaging confirmed prenatal features. CONCLUSIONS: Our work demonstrates that TAPS-related MRI anomalies consisted in edematous/hemorrhagic lesions that occur mostly in anemic rather than in polycythemic twins. Fetoscopic laser surgery could have a potential decongestant role. Therefore, prenatal MRI may help in counselling and management in TAPS pregnancies, especially for the planning of therapy and the monitoring of its efficacy.

Maternal tadalafil treatment does not increase uterine artery blood flow or oxygen delivery in the pregnant ewe.

Increasing placental perfusion (PP) could improve outcomes of growth-restricted fetuses. One way of increasing PP may be by using phosphodiesterase (PDE)-5 inhibitors, which induce vasodilatation of vascular beds. We used a combination of clinically relevant magnetic resonance imaging (MRI) techniques to characterize the impact that tadalafil infusion has on maternal, placental and fetal circulations. At 116-117 days' gestational age (dGA; term, 150 days), pregnant ewes (n = 6) underwent fetal catheterization surgery. At 120-123 dGA ewes were anaesthetized and MRI scans were performed during three acquisition windows: a basal state and then ∼15-75 min (TAD 1) and ∼75-135 min (TAD 2) post maternal administration (24 mg; intravenous bolus) of tadalafil. Phase contrast MRI and T2 oximetry were used to measure blood flow and oxygen delivery. Placental diffusion and PP were assessed using the Diffusion-Relaxation Combined Imaging for Detailed Placental Evaluation-'DECIDE' technique. Uterine artery (UtA) blood flow when normalized to maternal left ventricular cardiac output (LVCO) was reduced in both TAD periods. DECIDE imaging found no impact of tadalafil on placental diffusivity or fetoplacental blood volume fraction. Maternal-placental blood volume fraction was increased in the TAD 2 period. Fetal D O 2 ${D_{{{\mathrm{O}}_2}}}$ and V ̇ O 2 ${\dot V_{{{\mathrm{O}}_2}}}$ were not affected by maternal tadalafil administration. Maternal tadalafil administration did not increase UtA blood flow and thus may not be an effective vasodilator at the level of the UtAs. The increased maternal-placental blood volume fraction may indicate local vasodilatation of the maternal intervillous space, which may have compensated for the reduced proportion of UtA D O 2 ${D_{{{\mathrm{O}}_2}}}$ .

Fully automated planning for anatomical fetal brain MRI on 0.55T.

PURPOSE: Widening the availability of fetal MRI with fully automatic real-time planning of radiological brain planes on 0.55T MRI. METHODS: Deep learning-based detection of key brain landmarks on a whole-uterus echo planar imaging scan enables the subsequent fully automatic planning of the radiological single-shot Turbo Spin Echo acquisitions. The landmark detection pipeline was trained on over 120 datasets from varying field strength, echo times, and resolutions and quantitatively evaluated. The entire automatic planning solution was tested prospectively in nine fetal subjects between 20 and 37 weeks. A comprehensive evaluation of all steps, the distance between manual and automatic landmarks, the planning quality, and the resulting image quality was conducted. RESULTS: Prospective automatic planning was performed in real-time without latency in all subjects. The landmark detection accuracy was 4.2 ± $$ \pm $$ 2.6 mm for the fetal eyes and 6.5 ± $$ \pm $$ 3.2 for the cerebellum, planning quality was 2.4/3 (compared to 2.6/3 for manual planning) and diagnostic image quality was 2.2 compared to 2.1 for manual planning. CONCLUSIONS: Real-time automatic planning of all three key fetal brain planes was successfully achieved and will pave the way toward simplifying the acquisition of fetal MRI thereby widening the availability of this modality in nonspecialist centers.

Congenital and gynecological tumors: A review.

Congenital tumors are rare, and malignant congenital tumors are uncommon. Benign tu,mors might be life-threatening, depending on the location and size of the tumor. Different factors affect congenital tumors, such as maternal and placental hormones and environmental factors such as drugs, radiation, and infection. Developing fetal imaging methods and continuous follow-up during pregnancy are important factors in congenital tumor prognosis. Ultrasound is the most common method used for fetal evaluation. The complementary evaluation method is MRI. Both methods are helpful and widely spread for the detection of congenital tumors. These imaging methods help the medical team make a suitable decision about therapy. Some of these tumors regressed spontaneously, and some need surgical treatments. Treatment of tumors has developed rapidly, and recently molecular-targeted drugs have been used.

Craniofacial phenotyping with fetal MRI: a feasibility study of 3D visualisation, segmentation, surface-rendered and physical models.

This study explores the potential of 3D Slice-to-Volume Registration (SVR) motion-corrected fetal MRI for craniofacial assessment, traditionally used only for fetal brain analysis. In addition, we present the first description of an automated pipeline based on 3D Attention UNet trained for 3D fetal MRI craniofacial segmentation, followed by surface refinement. Results of 3D printing of selected models are also presented.Qualitative analysis of multiplanar volumes, based on the SVR output and surface segmentations outputs, were assessed with computer and printed models, using standardised protocols that we developed for evaluating image quality and visibility of diagnostic craniofacial features. A test set of 25, postnatally confirmed, Trisomy 21 fetal cases (24-36 weeks gestational age), revealed that 3D reconstructed T2 SVR images provided 66-100% visibility of relevant craniofacial and head structures in the SVR output, and 20-100% and 60-90% anatomical visibility was seen for the baseline and refined 3D computer surface model outputs respectively. Furthermore, 12 of 25 cases, 48%, of refined surface models demonstrated good or excellent overall quality with a further 9 cases, 36%, demonstrating moderate quality to include facial, scalp and external ears. Additional 3D printing of 12 physical real-size models (20-36 weeks gestational age) revealed good/excellent overall quality in all cases and distinguishable features between healthy control cases and cases with confirmed anomalies, with only minor manual adjustments required before 3D printing.Despite varying image quality and data heterogeneity, 3D T2w SVR reconstructions and models provided sufficient resolution for the subjective characterisation of subtle craniofacial features. We also contributed a publicly accessible online 3D T2w MRI atlas of the fetal head, validated for accurate representation of normal fetal anatomy.Future research will focus on quantitative analysis, optimizing the pipeline, and exploring diagnostic, counselling, and educational applications in fetal craniofacial assessment.

The association between fetal intracranial hemorrhages detected on MRI and neurodevelopment.

PURPOSE: Fetal intracranial hemorrhage is rarely identified in prenatal imaging. When identified, sparse data regarding neurodevelopmental outcomes worsens prenatal dilemmas. This MRI-based study aimed to assess prenatal characteristics and neurodevelopmental outcomes of fetal intracranial hemorrhage. METHODS: A historical cohort study which identified fetal intracranial hemorrhage in 22 individual fetal MRI scans, as part of the assessment of abnormal prenatal sonographic findings. Severity was graded by the grading system commonly used in neonates, with modifications. Prenatal data was collected. Neurodevelopmental outcome was assessed clinically by Vineland-II Adaptive Behavior Scales. RESULTS: Eight fetuses had intraventricular hemorrhage grade I-II, twelve had intraventricular hemorrhage grade III-IV, and two had infratentorial hemorrhage. The most prevalent risk factors were maternal chronic diseases and chronic use of medications. There was male predominance. Pregnancy was terminated in eleven cases. No surviving child who participated in the Vineland assessment had a grade IV hemorrhage. Vineland scores were normal in 9/11 children and moderately low in 2/11. The mean composite score of the cohort was not different from the mean score expected for age. Clinically, one child had hypotonia. CONCLUSIONS: Prognosis for fetuses with ICH without parenchymal involvement is potentially more favorable than expected from the intraventricular hemorrhage grading-scale adopted from the preterm neonates. Parenchymal involvement may predict a worse outcome, but it is not the sole predicting feature. This information may be valuable during prenatal counseling.

Fetal MRI Analysis of Corpus Callosal Abnormalities: Classification, and Associated Anomalies.

BACKGROUND: Corpus callosal abnormalities (CCA) are midline developmental brain malformations and are usually associated with a wide spectrum of other neurological and non-neurological abnormalities. The study aims to highlight the diagnostic role of fetal MRI to characterize heterogeneous corpus callosal abnormalities using the latest classification system. It also helps to identify associated anomalies, which have prognostic implications for the postnatal outcome. METHODS: In this study, retrospective data from antenatal women who underwent fetal MRI between January 2014 and July 2023 at Rush University Medical Center were evaluated for CCA and classified based on structural morphology. Patients were further assessed for associated neurological and non-neurological anomalies. RESULTS: The most frequent class of CCA was complete agenesis (79.1%), followed by hypoplasia (12.5%), dysplasia (4.2%), and hypoplasia with dysplasia (4.2%). Among them, 17% had isolated CCA, while the majority (83%) had complex forms of CCA associated with other CNS and non-CNS anomalies. Out of the complex CCA cases, 58% were associated with other CNS anomalies, while 8% were associated with non-CNS anomalies. 17% of cases had both. CONCLUSION: The use of fetal MRI is valuable in the classification of abnormalities of the corpus callosum after the confirmation of a suspected diagnosis on prenatal ultrasound. This technique is an invaluable method for distinguishing between isolated and complex forms of CCA, especially in cases of apparent isolated CCA. The use of diffusion-weighted imaging or diffusion tensor imaging in fetal neuroimaging is expected to provide further insights into white matter abnormalities in fetuses diagnosed with CCA in the future.

Static and dynamic responses to hyperoxia of normal placenta across gestation with T2*-weighted MRI sequences.

OBJECTIVES: T2*-weighted magnetic resonance imaging (MRI) sequences have been identified as non-invasive tools with which to study placental oxygenation in vivo. This study aimed to use these to investigate both static and dynamic responses to hyperoxia of the normal placenta across gestation. METHODS: We conducted a single-center prospective study including 52 uncomplicated pregnancies. Two T2*-weighted sequences (T2* relaxometry) were performed, one before and one after maternal hyperoxia. The distribution of placental T2* values was modeled by fitting a gamma probability density function (T2* ~ Γ α ß ), describing the structure of the histogram using the mean T2* value, the shape parameter (α) and the rate (ß). A dynamic acquisition (blood-oxygen-level-dependent (BOLD) MRI) was also performed before and during maternal oxygen supply, until placental oxygen saturation had been achieved. The signal change over time was modeled using a sigmoid function, to determine the intensity of enhancement (ΔBOLD (% with respect to baseline)), a temporal variation coefficient (λ (min-1), controlling the slope of the curve) and the maximum steepness (Vmax (% of placental enhancement/min)). RESULTS: The histogram analysis of the T2* values in normoxia showed a whole-placenta variation, with a decreasing linear trend in the mean T2* value (Pearson's correlation coefficient (R) = -0.83 (95% CI, -0.9 to -0.71), P < 0.001), along with an increasingly peaked and narrower distribution of T2* values with advancing gestation. After maternal hyperoxia, the mean T2* ratios (mean T2*hyperoxia/mean T2*baseline) were positively correlated with gestational age, while the other histogram parameters remained stable, suggesting a translation of the histogram towards higher values with a similar appearance after maternal hyperoxia. ΔBOLD showed a non-linear increase across gestation. Conversely, λ showed an inverted trend across gestation, with a weaker correlation (R = -0.33 (95% CI, -0.58 to -0.02), P = 0.04, R2 = 0.1). As a combination of ΔBOLD and λ, the changes in Vmax throughout gestation were influenced mainly by the changes in ΔBOLD and showed a positive non-linear correlation with gestational age. CONCLUSIONS: Our results suggest that the decrease in the T2* placental signal as gestation progresses does not reflect placental dysfunction. The BOLD dynamic signal change is representative of a free-diffusion model of oxygenation and highlights the increasing differences in oxygen saturation between mother and fetus as gestation progresses (ΔBOLD) and in the placental permeability to oxygen (λ). © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

A case report of single umbilical artery combined with fetal bladder exstrophy in singleton pregnancy and related literature review.

BACKGROUND: According to prenatal ultrasonographic studies, single umbilical artery may be present alone or in association with other fetal abnormalities. So far, the exact pathogenesis of bladder exstrophy is unclear. Some scholars believe that bladder exstrophy and cloacal exstrophy should be regarded as a disease spectrum to explore their pathogenesis. If bladder exstrophy and cloacal exstrophy are regarded as the same disease spectrum, then we can speculate that the single umbilical artery should have the probability of being accompanied by bladder exstrophy at the same time. CASE PRESENTATION: For the first time, we report a rare case of fetal bladder exstrophy with single umbilical artery in single pregnancy. This patient underwent targeted color Doppler ultrasound at 26 weeks of pregnancy which first suspected bladder exstrophy with single umbilical artery and fetal MRI for diagnosis at 38 + 3 weeks of pregnancy which confirmed the suspicion. After the diagnosis was confirmed, the patient was scheduled for a multidisciplinary discussion. Ultimately the patient opted for induced fetal demise at 38 + 5 weeks of pregnancy and the physical appearance of the fetal demise affirmed previous ultrasound and MRI examination results. CONCLUSIONS: Our report is the first finding of single umbilical artery combined with bladder exstrophy in a singleton pregnancy. Accordingly, our case enhances the evidence that cloacal exstrophy and bladder exstrophy should be treated as the same disease spectrum. In addition, we conducted a literature review on the diagnostic progress of single umbilical artery combined with bladder exstrophy, hoping to provide useful references for the diagnosis of this disease.

Prenatal features of congenital peribronchial myofibroblastic tumor.

Here, we report a case of a congenital peribronchial myofibroblastic tumor (CPMT). A 34-year-old primigravida was referred to our hospital at 31 gestation weeks because of suspected congenital pulmonary airway malformation (CPAM). Fetal ultrasonography showed a mass measuring 4.6 × 4.0 × 3.9 cm with mixed high and low echogenicity in the left lung, which was associated with microvascular blood flow in the tumor. Fetal magnetic resonance imaging (MRI) revealed a low-intensity left lobe lung lesion on a T2-weighted image. These findings suggested that the mass was a CPAM with atypical hypointense findings on MRI T2-weighted images or a rare primary pulmonary tumor, such as a CPMT. Unfortunately, the fetus died in utero at 34 gestation weeks due to cardiovascular failure, which could have resulted from direct encasement of the great vessels or cardiac compression due to rapid tumor growth. The autopsy findings confirmed the diagnosis of CPMT. Primary pulmonary tumors, such as CPMT, are extremely rare lung diseases that develop in utero. These tumors often rapidly grow during pregnancy, resulting in intrauterine fetal death. However, if the patient survives surgical mass resection, the prognosis is good. Given the adverse outcomes observed in our case, careful fetal monitoring is required in case of suspected CPMT during the third trimester of pregnancy. Moreover, in case the well-being of the fetus cannot be assured, immediate delivery should be considered, even in the preterm period, followed by surgery.