Mandibular Measurements at the 20-Week Anatomy Ultrasound as a Prenatal Diagnostic Predictor of Pierre Robin Sequence

Background Pierre Robin Sequence (PRS) is characterized by micrognathia, glossoptosis, and upper airway obstruction. Early recognition and appropriate perinatal management is crucial for optimizing outcomes. This study aimed to evaluate 20-week fetal ultrasounds to determine if specific mandibular measurements could predict PRS diagnosis and disease severity. Methods A retrospective case-control study of 48 patients with PRS and gender-matched controls was performed. Medical records were reviewed for respiratory and surgical interventions. Three parameters to assess micrognathia were measured on mid-sagittal profile ultrasound images: frontal nasal-mental angle (FNMA), facial-maxillary angle (FMA), and alveolar overjet. Student's t-test and univariate logistic regression was performed. P ≤ 0.05 was considered statistically significant. Results Patients with PRS demonstrated a significantly smaller mean FNMA compared to the control group, 129.3 ± 8.6° and 137.4 ± 3.2°, respectively (p < 0.0001), as well as significantly smaller mean FMA, 63.2 ± 9.2° and 74.8 ± 6.1°, respectively (p < 0.0001). The PRS group also demonstrated significantly larger mean alveolar overjet compared to the control group, 3.9 ± 1.4 mm and 2.1 ± 0.9 mm, respectively (p < 0.0001). The odds of respiratory intervention increased among cases when FMA was <68°. Additionally, there was a significant difference in median overjet between patients with PRS who did and did not require respiratory intervention. Conclusions Mandibular features on the 20-week ultrasound can be measured to predict diagnosis and severity of PRS. This is an important first step to prepare for potential respiratory intervention at delivery to minimize perinatal hypoxia. Alveolar overjet, previously not described in prenatal ultrasound literature, is measurable and has utility in prenatal screening for PRS, as do FMA and FNMA.

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Machine Learning Models on ADC Features to Assess Brain Changes of Children With Pierre Robin Sequence

Frontiers in Neurology ◽

10.3389/fneur.2021.580440 ◽

2021 ◽

Vol 12 ◽

Author(s):

Ying Wang ◽

Feng Yang ◽

Meijiao Zhu ◽

Ming Yang

Keyword(s):

Machine Learning ◽

Validation Dataset ◽

Support Vector ◽

Control Group ◽

Pierre Robin Sequence ◽

Learning Models ◽

Robin Sequence ◽

Brain Changes ◽

Pierre Robin ◽

Machine Learning Models

In order to evaluate brain changes in young children with Pierre Robin sequence (PRs) using machine learning based on apparent diffusion coefficient (ADC) features, we retrospectively enrolled a total of 60 cases (42 in the training dataset and 18 in the testing dataset) which included 30 PRs and 30 controls from the Children's Hospital Affiliated to the Nanjing Medical University from January 2017–December 2019. There were 21 and nine PRs cases in each dataset, with the remainder belonging to the control group in the same age range. A total of 105 ADC features were extracted from magnetic resonance imaging (MRI) data. Features were pruned using least absolute shrinkage and selection operator (LASSO) regression and seven ADC features were developed as the optimal signatures for training machine learning models. Support vector machine (SVM) achieved an area under the receiver operating characteristic curve (AUC) of 0.99 for the training set and 0.85 for the testing set. The AUC of the multivariable logistic regression (MLR) and the AdaBoost for the training and validation dataset were 0.98/0.84 and 0.94/0.69, respectively. Based on the ADC features, the two groups of cases (i.e., the PRs group and the control group) could be well-distinguished by the machine learning models, indicating that there is a significant difference in brain development between children with PRs and normal controls.

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6: Prenatal Diagnostic of Pierre-Robin Sequence (PRS) Using Ultrasound

Plastic & Reconstructive Surgery Global Open ◽

10.1097/01.gox.0000770056.06953.44 ◽

2021 ◽

Vol 9 (7S) ◽

pp. 24-25

Author(s):

Raeesa Islam ◽

Erin Anstadt ◽

Madeleine Bruce ◽

Miles Pfaff ◽

Timothy Canavan ◽

...

Keyword(s):

Pierre Robin Sequence ◽

Robin Sequence ◽

Prenatal Diagnostic ◽

Pierre Robin

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Three-dimensional analysis of airway space and mandibular morphology in Pierre Robin sequence using cone beam computed tomography.

NEMESIS ◽

10.14428/nemesis.v2i1.2923 ◽

2018 ◽

Vol 2 (1) ◽

pp. 27 ◽

Cited By ~ 1

Author(s):

Raphael Olszewski ◽

Timothée Dontaine ◽

Guillaume A Odri ◽

Francis Zech ◽

Benedicte Bayet ◽

...

Keyword(s):

Null Hypothesis ◽

Cone Beam ◽

Control Group ◽

Cephalometric Analysis ◽

Pierre Robin Sequence ◽

3D Slicer ◽

Significant Difference ◽

Mandibular Morphology ◽

And Control ◽

Pierre Robin

Objectives: The Pierre Robin sequence (PRS) is defined by retromicrognathia, glossoptosis, and sleep apnea and can also be associated with cleft palate. Diagnosis, management and mandibular catch-up growth are still controversial issues in PRS patients. The aim of our retrospective study was to evaluate in three dimensions (3D) the airway space and mandibular morphology in PRS compared to a normal control group patients in the pre-orthodontic period of life. The null hypothesis was that we would not find a significant difference between the PRS and control group patients in oropharyngeal airway volume measurements. Material and methods: We analyzed 9 PRS patients (mean age: 8 years-old) who underwent cleft palate surgery in the first four months of life, performed by the same surgeon using the same technique. Cone-beam computed tomography (CBCT) was performed in these patients after local ethical committee approval. The control group consisted of 15 patients (mean age: 9 years-old) with CBCT already performed for other reasons. 3D Slicer was used in both groups for semi-automatic segmentation of the airway space. Two independent observers performed semi-automatic segmentations twice in each patient with a one- week interval between the two series of measurements. Airway volume was automatically measured using 3D Slicer. We also developed a 3D cephalometric analysis with Maxilim software in order to define a 3D mandibular morphology which consisted of 25 landmarks, 4 planes, and 23 distances. Two independent observers performed the 3D cephalometric analysis twice for each patient, with a one- week interval between the two series of measurements. Results: There was no significant difference in the intra- and inter-observer measurements between the PRS and control groups for airway space volume (p<0.05). However, there was a significant difference in the shape of the mandible between the PRS group and the control group (p<0.05). Conclusions: Vertical ramus width and mandibular global anteroposterior length were significantly lower in the PRS group. Mandibular hypoplasia could be found in PRS patients not only in the horizontal dimension. Nemesis relevance: the null hypothesis was confirmed. Moreover we failed to find exactly the same control group under 9 years-old due to radioprotection restrictions of application of cone beam CT in children.

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Predictor of postoperative dyspnea for Pierre Robin Sequence infants

Open Medicine ◽

10.1515/med-2020-0231 ◽

2020 ◽

Vol 15 (1) ◽

pp. 915-920

Author(s):

Ning Yin ◽

Lei Fang ◽

Li Zhang ◽

Yousong Cai ◽

Guoxiang Fan ◽

...

Keyword(s):

Weight Gain ◽

Binary Logistic Regression ◽

Physiological Status ◽

Pierre Robin Sequence ◽

Binary Logistic Regression Model ◽

Robin Sequence ◽

Lehane Grade ◽

Significant Difference ◽

American Society ◽

Pierre Robin

AbstractThe aim of this retrospective study is to determine the predictive factors of postoperative dyspnea in infants with Pierre Robin sequence (PRS). Forty children with PRS, who underwent general anesthesia, were retrospectively analyzed. The patient’s physiological status and anesthesiology data were collected accordingly, demographic characteristics including age, gender, height and weight at surgery, weight gain, preoperative airway status, tracheal intubation route, American Society of Anesthesiologists grading and airway Cormack–Lehane classification. Weight gain, dyspnea before the operation, Cormack–Lehane grade distribution showed a significant difference between patients with and without postoperative dyspnea (p = 0.0175, p = 0.0026, and p = 0.0038, respectively). Incompetent weight gain was identified as a predictor (p = 0.0371) of PRS postoperative dyspnea through the binary logistic regression model. In conclusion, this study established an early alerting model by monitoring the weight gain, dyspnea before the operation, Cormack–Lehane grade as potential combinations to predict the risk of postoperative dyspnea for PRS.

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