Research Progress on Intrapartum Ultrasound Multi-Parameter Quantitative Assessment for Early Diagnosis and Decision Support in Dystocia

doi:10.12280/gjfckx.20260333

Abstract

Abstract:

Intrapartum ultrasound multi-parameter quantitative assessment is based on indices such as the angle of progression (AOP), head-perineum distance (HPD), midline angle (MLA), occiput-spine angle (OSA) and cervico-thoracic angle (CCA), etc. This technique transforms the spatial relationship between the fetus and the maternal pelvis into objective geometric parameters. It provides a novel approach for the early clinical identification of dystocia and assists in clinical decision-making. Current studies indicate that AOP and HPD hold clear value in predicting spontaneous vaginal delivery and evaluating the difficulty of instrumental delivery. The combination of multiple parameters with artificial intelligence analysis can help identify causes of dystocia such as persistent occiput posterior position and fetal head asynclitism in advance. However, the technique currently faces challenges including the absence of a unified standard operating procedure, lack of an established standardized training system, and inability to accurately measure uterine contraction force. Future efforts should focus on conducting large-scale, multicenter randomized controlled trials to validate the actual effectiveness of ultrasound quantitative parameter-based intrapartum intervention protocols in reducing cesarean section rates and optimizing maternal and neonatal outcomes, thereby providing evidence-based support for precise management of labor.

Key words: Ultrasonography, Multi-parameter quantitative assessment, Dystocia, Early diagnosis, Artificial intelligence

XIAO Kang, LIANG Guang-ju, YANG Ying-jie, LIU Tao. Research Progress on Intrapartum Ultrasound Multi-Parameter Quantitative Assessment for Early Diagnosis and Decision Support in Dystocia[J]. Journal of International Obstetrics and Gynecology, 2026, 53(5): 525-529.

Figures/Tables 2

References 31

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参数	定义与测量	主要临床意义	代表性预测阈值
AOP	经会阴矢状面，耻骨联合下缘中点与胎头颅骨最低点切线夹角^[3,6]	量化胎头下降角度与俯屈程度，预测分娩方式、产程时长	预测阴道分娩：≥117°^[12]；预测第二产程≤60 min：≥ 126.25°^[13-14]
HPD	经会阴矢状面，胎头先露最低点至会阴体表面的直线距离^[7-8]	量化胎头下降绝对距离，预测分娩结局、手术助产难度	预测阴道分娩：≤4.54 cm^[14]；预测手术困难：宫缩期HPD较大^[8]
MLA	经腹横切面，胎儿大脑中线与母体骨盆前后径轴线夹角^[9]	客观量化胎头旋转程度，辅助诊断枕横/后位	旋转良好：≤45°^[3]；用于AI胎方位识别的关键特征^[15]
OSA	经腹/会阴矢状面，胎儿枕骨与脊柱的夹角^[10-11]	评估胎头俯屈程度，与异常胎位（如面先露）相关	面先露时特征性增大^[16]
CCA	经腹/会阴矢状面，胎儿颈部与胸部前缘的夹角^[11]	辅助评估胎头俯屈不良，尤其是枕后位时的仰伸程度	俯屈不良：>33°^[10]

参数	定义与测量	主要临床意义	代表性预测阈值
AOP	经会阴矢状面，耻骨联合下缘中点与胎头颅骨最低点切线夹角^[3,6]	量化胎头下降角度与俯屈程度，预测分娩方式、产程时长	预测阴道分娩：≥117°^[12]；预测第二产程≤60 min：≥ 126.25°^[13-14]
HPD	经会阴矢状面，胎头先露最低点至会阴体表面的直线距离^[7-8]	量化胎头下降绝对距离，预测分娩结局、手术助产难度	预测阴道分娩：≤4.54 cm^[14]；预测手术困难：宫缩期HPD较大^[8]
MLA	经腹横切面，胎儿大脑中线与母体骨盆前后径轴线夹角^[9]	客观量化胎头旋转程度，辅助诊断枕横/后位	旋转良好：≤45°^[3]；用于AI胎方位识别的关键特征^[15]
OSA	经腹/会阴矢状面，胎儿枕骨与脊柱的夹角^[10-11]	评估胎头俯屈程度，与异常胎位（如面先露）相关	面先露时特征性增大^[16]
CCA	经腹/会阴矢状面，胎儿颈部与胸部前缘的夹角^[11]	辅助评估胎头俯屈不良，尤其是枕后位时的仰伸程度	俯屈不良：>33°^[10]

评估维度	有利指标（支持继续阴道试产/助产）	不利指标（提示困难/需警惕）	临床决策提示
胎方位	枕前位	持续性枕后位或枕横位	持续性枕后位或枕横位可尝试手转胎位或特定体位矫正；持续性枕后位需评估器械助产风险或考虑剖宫产^[21-22]
胎头下降（AOP/HPD）	AOP≥150°，HPD≤ 25 mm	AOP<120°，HPD≥40 mm	AOP>135°且HPD小，自然分娩率高；AOP小、HPD大提示胎头位置高，器械助产失败风险高，需上级医师评估，做好中转剖宫产准备^[3,26]
胎头旋转（MLA）	MLA≤45°	MLA≥45°（尤其胎头未达棘下）	MLA小提示胎头旋转良好，下降深入；MLA大且胎头位置高，需关注旋转阻滞^[3,9]
多参数整合	≥2个有利因素组合：阴道分娩（自然或助产）成功率高^[20]；≥2个不利因素组合：器械助产失败或损伤风险显著升高，应强烈考虑由经验丰富医师操作或中转剖宫产^[14,19,26]

评估维度	有利指标（支持继续阴道试产/助产）	不利指标（提示困难/需警惕）	临床决策提示
胎方位	枕前位	持续性枕后位或枕横位	持续性枕后位或枕横位可尝试手转胎位或特定体位矫正；持续性枕后位需评估器械助产风险或考虑剖宫产^[21-22]
胎头下降（AOP/HPD）	AOP≥150°，HPD≤ 25 mm	AOP<120°，HPD≥40 mm	AOP>135°且HPD小，自然分娩率高；AOP小、HPD大提示胎头位置高，器械助产失败风险高，需上级医师评估，做好中转剖宫产准备^[3,26]
胎头旋转（MLA）	MLA≤45°	MLA≥45°（尤其胎头未达棘下）	MLA小提示胎头旋转良好，下降深入；MLA大且胎头位置高，需关注旋转阻滞^[3,9]
多参数整合	≥2个有利因素组合：阴道分娩（自然或助产）成功率高^[20]；≥2个不利因素组合：器械助产失败或损伤风险显著升高，应强烈考虑由经验丰富医师操作或中转剖宫产^[14,19,26]