Congenital orofacial cleft, the most common birth defect in the maxillofacial region, exhibits a wide range of prognosis depending on the severity of deformity and underlying etiology. Non-syndromic congenital orofacial clefts typically present with milder deformities and more favorable treatment outcomes, whereas syndromic congenital orofacial clefts often manifest with concomitant organ abnormalities, which pose greater challenges for treatment and result in poorer prognosis. This consensus provides an elaborate classification system for varying degrees of orofacial clefts along with corresponding diagnostic and therapeutic guidelines. Results serve as a crucial resource for families to navigate prenatal screening results or make informed decisions regarding treatment options while also contributing significantly to preventing serious birth defects within the development of population.
Humans ; Cleft Lip/diagnosis* ; Cleft Palate/diagnosis* ; Consensus ; Prenatal Diagnosis ; Female

Objective:To explore the value of prenatal three-dimensional ultrasonography（3DUS）in displaying auricular morphotyping and dimensions for predicting congenital aural atresia（CAA）.Methods:A retrospective collection of 227 fetuses who underwent ultrasound scans and retained auricular 3DUS volumes from January 2018 to December 2023 at the First Affiliated Hospital of Sun Yat-sen University was conducted. Fetuses were divided into two groups：a CAA group（52 fetuses，62 auricles）and a non-CAA group（175 fetuses，202 auricles），based on the presence or absence of external auditory canal identified through postnatal examination. According to 3DUS auricular contour and presence or absence of the concha，the auricles were divided into 4 types：type Ⅰ，C-shaped auricle with a concha；type Ⅱ，Irregular auricle with a concha；type Ⅲ，C-shaped auricle without a concha；type Ⅳ，Irregular auricle without a concha. And auricular length（AL）and width（AW）were measured to calculate the product of the auricular length and width（ALW）. Normal reference ranges for ALW from the non-CAA group were developed. Differences of the auricular morphotyping and Z-score of ALW（ALWZ）were compared between the two groups. Receiver operating characteristic（ROC）curves were used to evaluate the diagnostic efficiency of auricular morphotyping，ALWZ and the regression model. A Logistic regression model for CAA based on auricular morphotyping and ALWZ were established.Results:The auricular morphotyping and ALWZ between the two groups were different statistically（both P<0.05）. The AUC of the auricular morphotyping and ALWZ predicting CAA were 0.960（95% CI = 0.923 - 0.997）and 0.975（95% CI = 0.959 - 0.991）individually. Formula for CAA prediction model combining the two indicators（5.379 × morphotyping - 2.386 × ALWZ - Conclusions:The auricular morphotyping and dimensions can effectively predict CAA.

The integration of artificial intelligence（AI）with prenatal ultrasound is driving a paradigm shift in obstetric imaging，transitioning from an experience-based approach to a data-driven model and gradually transforming traditional clinical practices. This review systematically examines AI-driven advancements

Objective:To develop a deep learning-based artificial intelligence system for assessing image quality in early pregnancy ultrasound，and to evaluate its performance in anatomical structure identification and quality control.Methods:A retrospective study was conducted by collecting 17 910 static ultrasound images of 8 quality-control planes from fetuses at 11 to 13 +6 weeks of gestation who underwent routine first-trimester ultrasound examinations at the First Affiliated Hospital of Sun Yat-sen University from June 2018 to June 2024. The dataset was divided into a training set（12 536 images），a test set（3 582 images），and a validation set（1 792 images）in a 7∶2∶1 ratio to develop a prenatal-screening artificial intelligence system（PSAIS）and to evaluate its performance in the automatic recognition and quality control of standard planes during early pregnancy. The average precision and mean average precision（mAP）were used to measure the model's ability to recognize the anatomical structures on each plane. Intraclass correlation coefficient（ICC）and Kappa statistics were used to assess the consistency between PSAIS and expert-level sonographers in both plane image quality assessment and standardization. The efficiency of PSAIS was also compared to manual quality control. Results:In the test set，the mAP values for recognizing the anatomical structures of the 8 quality-control planes all exceeded 0.800. In the validation set，PSAIS demonstrated moderate to good agreement with two experts in image quality evaluation：the ICC ranged from 0.713 to 0.843 for one expert and 0.678 to 0.788 for the other，while the Kappa values ranged from 0.590 to 0.768 and 0.530 to 0.702，respectively. In terms of plane standardization scoring，PSAIS showed particularly high agreement with expert ratings on the transventricular view（compliance rate 94.6%，Kappa=0.860）and the four-chamber cardiac view with blood flow（compliance rate 94.1%，Kappa=0.778），with agreement above 70% for the remaining planes. Compared with manual quality-control，PSAIS significantly increased processing speed：the total processing time was only 413 seconds，markedly less than the 77 008 seconds and 94 918 seconds required for manual QC（ P<0.001）. Conclusions:The PSAIS system performs well in recognizing and controlling the quality of standard ultrasound planes in early pregnancy，demonstrating high consistency with expert evaluations and significantly improved processing efficiency. It has potential application value in enhancing the quality and efficiency of early pregnancy screening.

Objective:To explore the value of prenatal three-dimensional ultrasonography（3DUS）in displaying auricular morphotyping and dimensions for predicting congenital aural atresia（CAA）.Methods:A retrospective collection of 227 fetuses who underwent ultrasound scans and retained auricular 3DUS volumes from January 2018 to December 2023 at the First Affiliated Hospital of Sun Yat-sen University was conducted. Fetuses were divided into two groups：a CAA group（52 fetuses，62 auricles）and a non-CAA group（175 fetuses，202 auricles），based on the presence or absence of external auditory canal identified through postnatal examination. According to 3DUS auricular contour and presence or absence of the concha，the auricles were divided into 4 types：type Ⅰ，C-shaped auricle with a concha；type Ⅱ，Irregular auricle with a concha；type Ⅲ，C-shaped auricle without a concha；type Ⅳ，Irregular auricle without a concha. And auricular length（AL）and width（AW）were measured to calculate the product of the auricular length and width（ALW）. Normal reference ranges for ALW from the non-CAA group were developed. Differences of the auricular morphotyping and Z-score of ALW（ALWZ）were compared between the two groups. Receiver operating characteristic（ROC）curves were used to evaluate the diagnostic efficiency of auricular morphotyping，ALWZ and the regression model. A Logistic regression model for CAA based on auricular morphotyping and ALWZ were established.Results:The auricular morphotyping and ALWZ between the two groups were different statistically（both P<0.05）. The AUC of the auricular morphotyping and ALWZ predicting CAA were 0.960（95% CI = 0.923 - 0.997）and 0.975（95% CI = 0.959 - 0.991）individually. Formula for CAA prediction model combining the two indicators（5.379 × morphotyping - 2.386 × ALWZ - Conclusions:The auricular morphotyping and dimensions can effectively predict CAA.

The integration of artificial intelligence（AI）with prenatal ultrasound is driving a paradigm shift in obstetric imaging，transitioning from an experience-based approach to a data-driven model and gradually transforming traditional clinical practices. This review systematically examines AI-driven advancements

Objective:To develop a deep learning-based artificial intelligence system for assessing image quality in early pregnancy ultrasound，and to evaluate its performance in anatomical structure identification and quality control.Methods:A retrospective study was conducted by collecting 17 910 static ultrasound images of 8 quality-control planes from fetuses at 11 to 13 +6 weeks of gestation who underwent routine first-trimester ultrasound examinations at the First Affiliated Hospital of Sun Yat-sen University from June 2018 to June 2024. The dataset was divided into a training set（12 536 images），a test set（3 582 images），and a validation set（1 792 images）in a 7∶2∶1 ratio to develop a prenatal-screening artificial intelligence system（PSAIS）and to evaluate its performance in the automatic recognition and quality control of standard planes during early pregnancy. The average precision and mean average precision（mAP）were used to measure the model's ability to recognize the anatomical structures on each plane. Intraclass correlation coefficient（ICC）and Kappa statistics were used to assess the consistency between PSAIS and expert-level sonographers in both plane image quality assessment and standardization. The efficiency of PSAIS was also compared to manual quality control. Results:In the test set，the mAP values for recognizing the anatomical structures of the 8 quality-control planes all exceeded 0.800. In the validation set，PSAIS demonstrated moderate to good agreement with two experts in image quality evaluation：the ICC ranged from 0.713 to 0.843 for one expert and 0.678 to 0.788 for the other，while the Kappa values ranged from 0.590 to 0.768 and 0.530 to 0.702，respectively. In terms of plane standardization scoring，PSAIS showed particularly high agreement with expert ratings on the transventricular view（compliance rate 94.6%，Kappa=0.860）and the four-chamber cardiac view with blood flow（compliance rate 94.1%，Kappa=0.778），with agreement above 70% for the remaining planes. Compared with manual quality-control，PSAIS significantly increased processing speed：the total processing time was only 413 seconds，markedly less than the 77 008 seconds and 94 918 seconds required for manual QC（ P<0.001）. Conclusions:The PSAIS system performs well in recognizing and controlling the quality of standard ultrasound planes in early pregnancy，demonstrating high consistency with expert evaluations and significantly improved processing efficiency. It has potential application value in enhancing the quality and efficiency of early pregnancy screening.

Objective:To summarize the prenatal sonographic characteristics of affected joints of fetal arthrogryposis multiplex congenita (AMC) by comparing the ultrasonographic features and the postnatal pathological manifestations.Methods:The cases of AMC detected by antenatal ultrasound and confirmed by postnatal pathology were collected in the First Affiliated Hospital of Sun Yat-Sen University and Kaiping Central Hospital from January 2015 to June 2020. The differences between prenatal ultrasonic manifestations, types of affected joints and postnatal pathological features were analyzed. And the different involvements of joints in AMC cases with or without other system abnormalities were also explored separately.Results:A total of 31 cases of AMC were included, in which 11 cases were with other system abnormalities and 20 cases without. No significant difference was observed in number of affected joints between these two groups ( P>0.05). The prenatal sonogram features were completely consistent with the postnatal pathological manifestations in 21 (21/31, 67.7%) cases. Among 31 cases, the involvement rates of joints were: interphalangeal joints of fingers (23/31, 74.2%), knee joints (20/31, 64.5%) and ankle joints (19/31, 61.3%), temporomandibular joint (11/31, 35.5%), wrists (11/31, 35.5%), elbow joints (10/31, 32.3%), interphalangeal joints of toes (6/31, 19.4%), spinal joints (2/31, 6.5%), shoulder joint (1/31, 3.2%) and hip joint (1/31, 3.2%), respectively. The coincidence rates of prenatal ultrasound in involved joints were: interphalangeal joints of fingers (100%), ankles (100%), spines (100%), hips (100%), wrists (90.9%), knees (75.0%), elbows (70.0%), jaws (54.5%), interphalangeal joints of toes (50.0%), and shoulders (0), respectively. Conclusions:When postural abnormalities of fetal upper and lower extremities are detected by prenatal ultrasound screening, especially overlapping fingers, extended knee and club foot, AMC should be kept on alert. Simultaneously, other joints should be carefully scanned to improve the prenatal detection rate of AMC.

Objective To explore the prenatal ultrasound diagnosis and postnatal clinical outcomes of fetuses with hepatohilar cystic occupying lesions . Methods T his was a retrospective study that included all fetuses found to have hepatohilar cystic occupying lesions diagnosed by ultrasound in the First Affiliated Hospital of Sun Yat‐sen University between January 2008 and December 2017 . According to the morphology of the cyst and max diameter ,the cases were divided into four groups . Cases with polygonal cysts and max diameter over 30 mm were assigned to group 1 ,non‐polygonal cysts and max diameter over 30 mm to group 2 ,polygonal cysts and max diameter under 30 mm to group 3 ,non‐polygonal cysts and max diameter under 30 mm to group 4 . T he birth status ,ultrasound review image ,surgical treatment and pathological findings were tracked to analyze the prognosis of these fetuses . Results Among 47 cases of fetal hepatohilar cystic occupying lesions ,38 fetuses were born and 9 were terminated with only 1 case taking pathological examination . T here were 39 cases with pregnancy outcomes . T wenty‐seven cases ( 69 .2% ,27/39) were diagnosed as congenital biliary dilatation ( CBD) ,5 cases ( 12 .8% ,5/39) were found cysts resolved in postnatal ultrasound examinations . Biliary atresia was diagnosed in 3 cases ( 7 .8% ,3/39 ) by operation ; M esenteric cysts ( 5 .1% ,2/39) were diagnosed in 2 cases by ultrasound . One ( 2 .6% ,1/39) was diagnosed as double‐gallbladder by ultrasound . 1 ( 2 .6% , 1/39 ) was diagnosed as teratoma by operation . M ost cases were in the group 3 ,but there was no significant difference compared with other groups ( all P ＞ 0 .05) . Conclusions More than half of hepatohilar cystic occupying lesions diagnosed in prenatal ultrasound are proved to be CBD with good prognosis . T he cysts in few cases can be resolved after born . 7 .8% of cases are biliary atresia with poor prognosis ,w hich give messages to prenatal clinical consultation .

Objective To investigate the clinical performance of ultrasound screening for fetal structural anomalies at 11-13+6 weeks of gestation and to evaluate the relation of structural anomalies with karyotypes and copy number variations. Methods A retrospective analysis was conducted on fetuses with structural anomalies detected by ultrasound examination at 11-13+6 gestational weeks in First Affiliated Hospital of Sun Yat-Sen University from January 2013 to December 2017. Karyotype and chromosomal microarray analysis(CMA) were offered to these fetuses and ultrasound scans were repeated at 16-18 gestational weeks. All fetuses were followed up to termination or birth. Fisher's exact test was used for statistical analysis. Results A total of 362 fetuses with structural anomalies were studied including 101 (27.9%) fatal malformations, 253 (69.9%) major malformations and eight (0.2%) minor malformations. Cardiac malformation (32.6%, 118/362), central nervous system anomalies (24.9%, 90/362) and anterior abdominal wall defects (20.9%, 76/362) were the three most common abnormalities. Invasive prenatal test was performed in 107 cases including 25 fatal, 79 major and three minor malformations. Thirty (28%) out of the 107 cases had abnormal karyotypes, which were chromosomal aneuploidies (n=28) and chromosomal fragment abnormalities (n=2). Among the 99 cases received CMA, 25 had abnormal karyotypes, and copy number variations were identified in eight [three (4.05%) were pathogenic variations] out of the rest 74 with normal karyotypes. The incidence of chromosomal abnormalities in fetuses with major malformations was higher than that of fetuses with fatal malformation [32.9% (26/79) vs 12.0% (3/25), P=0.045]. Altogether, 117 cases repeated second-trimester ultrasound among which 16 (13.7%) were normal; 19 (16.2%) had cardiac defect which was discordant with the first-trimester evaluation and five (4.2%) were found to have additional malformations. Diagnosis of the other 77 cases were consistent with the first-trimester ultrasound findings. After the second-trimester ultrasound scanning, 49 pregnancies were terminated; 39 twin pregnancies and four triplet pregnancies underwent selective fetal reduction; 25 continued to delivery with good neonatal outcomes. Out of the 23 699 cases without abnormal ultrasound findings at 11-13+6 gestational weeks, 20 182 (85.2%) were successfully followed up, among which structural abnormalities were found in 178 during the second trimester and in 31 after birth. Conclusions A detailed ultrasound examination at 11-13+6 weeks of gestation is important to identify fetal structural defects. However, it could not replace the second-trimester ultrasound. There is a high risk of chromosomal abnormalities in fetuses with early-detected structural defects. CMA is able to identify pathogenic copy number variations with a relatively low detection rate.