Prenatal diagnosis of ultrasound soft markers in a single medical center of mainland China

Zhou, Yanhong; Wu, Siqi; Han, Jin Hee; Li, Zhen; Yang, Xin; Li, Ru; Zhang, Yongling; Jing, Xiangyi; Li, Fucheng; Liu, Huishu

doi:10.1186/s13039-022-00633-x

Cited by 3 publications

(1 citation statement)

References 48 publications

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“…The utilization of non-invasive prenatal screening has the potential to reduce the need for invasive tests such as amniocentesis or chorionic villus sampling [59]. Furthermore, soft markers, including the absence or small size of the nasal bone, increased nuchal fold thickness, and enlarged ventricles, can be detected through ultrasound examinations performed between the 14th and 24th weeks of gestation [60,61]. An elevated fetal nuchal translucency measurement is indeed associated with an increased risk of Down syndrome.…”

Section: Prenatal Diagnosticsmentioning

confidence: 99%

Unraveling Down Syndrome: From Genetic Anomaly to Artificial Intelligence-Enhanced Diagnosis

Koul,

Ahmad,

Bhat

et al. 2023

Biomedicines

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Down syndrome arises from chromosomal non-disjunction during gametogenesis, resulting in an additional chromosome. This anomaly presents with intellectual impairment, growth limitations, and distinct facial features. Positive correlation exists between maternal age, particularly in advanced cases, and the global annual incidence is over 200,000 cases. Early interventions, including first and second-trimester screenings, have improved DS diagnosis and care. The manifestations of Down syndrome result from complex interactions between genetic factors linked to various health concerns. To explore recent advancements in Down syndrome research, we focus on the integration of artificial intelligence (AI) and machine learning (ML) technologies for improved diagnosis and management. Recent developments leverage AI and ML algorithms to detect subtle Down syndrome indicators across various data sources, including biological markers, facial traits, and medical images. These technologies offer potential enhancements in accuracy, particularly in cases complicated by cognitive impairments. Integration of AI and ML in Down syndrome diagnosis signifies a significant advancement in medical science. These tools hold promise for early detection, personalized treatment, and a deeper comprehension of the complex interplay between genetics and environmental factors. This review provides a comprehensive overview of neurodevelopmental and cognitive profiles, comorbidities, diagnosis, and management within the Down syndrome context. The utilization of AI and ML represents a transformative step toward enhancing early identification and tailored interventions for individuals with Down syndrome, ultimately improving their quality of life.

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Section: Prenatal Diagnosticsmentioning

confidence: 99%

Unraveling Down Syndrome: From Genetic Anomaly to Artificial Intelligence-Enhanced Diagnosis

Koul,

Ahmad,

Bhat

et al. 2023

Biomedicines

View full text Add to dashboard Cite

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Chromosome abnormalities and copy number variations in fetuses with ultrasound soft markers: a retrospective study

Zhang,

Chen,

et al. 2023

Preprint

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Purpose Although previous results revealed that genetic aberrations were associated with ultrasound soft markers, the detection rates of chromosomal aberrations and P/LP CNVs varied among different studies. Thus, the detection of chromosome abnormalities and copy number variations (CNVs) in fetuses with ultrasound soft markers were investigated in our study. Methods A total of 2422 fetuses, including 1005 fetuses with ultrasound soft markers and 1417 fetuses without ultrasound soft markers, were included in our study. CNV-seq, combined with karyotyping or QF-PCR, was performed to detect chromosome abnormalities and CNVs. Statistical analysis was performed using SPSS 19.0. Results Our study detected 28 and 22 chromosome abnormalities in fetuses with and without ultrasound soft markers, respectively. Meanwhile, 24 and 10 P/LP CNVs were detected in fetuses with and without ultrasound soft markers, respectively. These results revealed that the detection rates of chromosome abnormalities and P/LP CNVs were significantly increased in fetuses with ultrasound soft markers. Subsequent analysis unveiled that the detection rates of chromosome abnormalities and P/LP CNVs varied in fetuses with different ultrasound soft markers. The detection rates of chromosome abnormalities in fetuses with thickened NT elevated significantly, while P/LP CNVs were more likely detected in fetuses with renal abnormalities. Additionally, our results showed that the detection rates of chromosome abnormalities were positively correlated with NT thickness in fetuses with thickened NT. Conclusion Our results revealed that fetuses with ultrasound soft markers had a higher risk of chromosome abnormalities and P/LP CNVs.

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Chromosomal Microarray Analysis in Fetuses with Ultrasound Abnormalities

Chen,

Lan,

et al. 2024

IJGM

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Objective To explore and evaluate the value of chromosomal microarray analysis (CMA) in prenatal diagnosis of fetuses with ultrasound abnormalities. Methods A retrospective analysis was performed on 370 fetuses with ultrasound abnormalities received invasive prenatal diagnosis at Meizhou People’s Hospital from October 2022 to December 2023. Fetal specimens were analyzed by CMA, and the detection rates of aneuploidy and pathogenic (P)/likely pathogenic (LP) copy number variations (CNVs) in ultrasound structural abnormalities (malformations of fetal anatomy) and non-structural abnormalities (abnormalities of fetal nonanatomical structure) were analyzed. Results There were 114 (30.8%) cases with isolated ultrasound structural abnormalities, 226 (61.1%) cases with isolated non-structural abnormalities (182 isolated ultrasound soft markers abnormalities, 30 isolated fetal growth restriction (FGR), and 8 isolated abnormalities of amniotic fluid volume), and 30 (8.1%) cases with both structural and non-structural abnormalities. The overall detection rate of aneuploidy and P/LP CNVs in isolated ultrasonic structural abnormalities was 5.3%, among which cardiovascular system abnormalities were the highest. In addition, the largest number of fetuses with non-structural abnormalities was nuchal translucency (NT) thickening (n = 81), followed by ventriculomegaly (n = 29), and nasal bone dysplasia (n = 24). The detection rate of chromosomal abnormalities of fetuses with abnormal ultrasound soft markers was 9.9%, and the detection rate in single abnormal ultrasound soft marker, and multiple ultrasound soft markers abnormalities was 9.7% (16/165) and 11.8% (2/17), respectively. Moreover, the detection rate of chromosomal abnormalities of fetuses with FGR and structural abnormalities combined with non-structural abnormalities was 6.7% (2/30), and 13.3% (4/30), respectively. Conclusion The incidence of chromosomal abnormalities (aneuploidy and P/LP CNVs) varies among different fetal ultrasound abnormalities.

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Prenatal diagnosis of ultrasound soft markers in a single medical center of mainland China

Cited by 3 publications

References 48 publications

Unraveling Down Syndrome: From Genetic Anomaly to Artificial Intelligence-Enhanced Diagnosis

Unraveling Down Syndrome: From Genetic Anomaly to Artificial Intelligence-Enhanced Diagnosis

Chromosome abnormalities and copy number variations in fetuses with ultrasound soft markers: a retrospective study

Chromosomal Microarray Analysis in Fetuses with Ultrasound Abnormalities

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