Artificial intelligence assistance for fetal development: evaluation of an automated software for biometry measurements in the mid-trimester

被引:3
|
作者
Han, Xuesong [1 ]
Yu, Junxuan [2 ,3 ,4 ]
Yang, Xin [2 ,3 ,4 ]
Chen, Chaoyu [2 ,3 ,4 ]
Zhou, Han [2 ,3 ,4 ]
Qiu, Chuangxin [2 ,3 ,4 ]
Cao, Yan [5 ]
Zhang, Tianjing [6 ]
Peng, Meiran [6 ]
Zhu, Guiyao [1 ]
Ni, Dong [2 ,3 ,4 ]
Zhang, Yuanji [2 ,3 ,4 ]
Liu, Nana [1 ]
机构
[1] Shenzhen Univ, Gen Hosp, Dept Ultrasonog, Shenzhen, Guangdong, Peoples R China
[2] Shenzhen Univ, Med Sch, Sch Biomed Engn, Natl Reg Key Technol Engn Lab Med Ultrasound, Shenzhen, Guangdong, Peoples R China
[3] Shenzhen Univ, Med Ultrasound Image Comp MUS Lab, Shenzhen, Guangdong, Peoples R China
[4] Shenzhen Univ, Marshall Lab Biomed Engn, Shenzhen, Guangdong, Peoples R China
[5] Shenzhen RayShape Med Technol Co Ltd, Shenzhen, Guangdong, Peoples R China
[6] NVIDIA, Shenzhen, Peoples R China
基金
中国国家自然科学基金;
关键词
Biometry measurement; Artificial intelligence; Fetal growth and development; HEAD CIRCUMFERENCE; 3RD TRIMESTER; WEIGHT; ULTRASOUND; DIAMETER;
D O I
10.1186/s12884-024-06336-y
中图分类号
R71 [妇产科学];
学科分类号
100211 ;
摘要
BackgroundThis study presents CUPID, an advanced automated measurement software based on Artificial Intelligence (AI), designed to evaluate nine fetal biometric parameters in the mid-trimester. Our primary objective was to assess and compare the CUPID performance of experienced senior and junior radiologists.Materials and methodsThis prospective cross-sectional study was conducted at Shenzhen University General Hospital between September 2022 and June 2023, and focused on mid-trimester fetuses. All ultrasound images of the six standard planes, that enabled the evaluation of nine biometric measurements, were included to compare the performance of CUPID through subjective and objective assessments.ResultsThere were 642 fetuses with a mean (+/- SD) age of 22 +/- 2.82 weeks at enrollment. In the subjective quality assessment, out of 642 images representing nine biometric measurements, 617-635 images (90.65-96.11%) of CUPID caliper placements were determined to be accurately placed and did not require any adjustments. Whereas, for the junior category, 447-691 images (69.63-92.06%) were determined to be accurately placed and did not require any adjustments. In the objective measurement indicators, across all nine biometric parameters and estimated fetal weight (EFW), the intra-class correlation coefficients (ICC) (0.843-0.990) and Pearson correlation coefficients (PCC) (0.765-0.978) between the senior radiologist and CUPID reflected good reliability compared with the ICC (0.306-0.937) and PCC (0.566-0.947) between the senior and junior radiologists. Additionally, the mean absolute error (MAE), percentage error (PE), and average error in days of gestation were lower between the senior and CUPID compared to the difference between the senior and junior radiologists. The specific differences are as follows: MAE (0.36-2.53 mm, 14.67 g) compared to (0.64- 8.13 mm, 38.05 g), PE (0.94-9.38%) compared to (1.58-16.04%), and average error in days (3.99-7.92 days) compared to (4.35-11.06 days). In the time-consuming task, CUPID only takes 0.05-0.07 s to measure nine biometric parameters, while senior and junior radiologists require 4.79-11.68 s and 4.95-13.44 s, respectively.ConclusionsCUPID has proven to be highly accurate and efficient software for automatically measuring fetal biometry, gestational age, and fetal weight, providing a precise and fast tool for assessing fetal growth and development.
引用
收藏
页数:11
相关论文
共 19 条
  • [1] Artificial intelligence assistance for fetal head biometry: Assessment of automated measurement software
    Grandjean, G. Ambroise
    Hossu, G.
    Bertholdt, C.
    Noble, P.
    Morel, O.
    Grange, G.
    DIAGNOSTIC AND INTERVENTIONAL IMAGING, 2018, 99 (11) : 709 - 716
  • [2] Validation of Reference Charts for Mid-Trimester Fetal Biometry
    van de Kamp, K.
    Pajkrt, E.
    Zwinderman, A. H.
    van der Post, J. A.
    Snijders, R. J. M.
    FETAL DIAGNOSIS AND THERAPY, 2019, 45 (01) : 42 - 49
  • [3] Mid-trimester sonographic fetal thymus measurements do not predict preterm birth
    Brandt, Justin
    Bastek, Jamie
    Wang, Eileen
    Purisch, Stephanie
    Schwartz, Nadav
    AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY, 2015, 212 (01) : S178 - S178
  • [4] Mid-trimester sonographic fetal thymus measurements do not predict small for gestational age
    Brandt, Justin
    Bastek, Jamie
    Wang, Eileen
    Schwartz, Nadav
    AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY, 2015, 212 (01) : S393 - S394
  • [5] Open-legs axial plane: A standardized methodology and reference values for fetal genital biometry in mid-trimester ultrasound
    Lopez-Soto, Alvaro
    Meseguer-Gonzalez, Jose L.
    Garvi-Morcillo, Javier
    Beltran-Sanchez, Antonio
    Jodar-Perez, Angeles
    Martinez-Rivero, Inmaculada
    Garcia-Izquierdo, Olivia
    Urbano-Reyes, Maribel
    Lopez-Perez, Rocio
    Martinez-Cendan, Juan P.
    EUROPEAN JOURNAL OF OBSTETRICS & GYNECOLOGY AND REPRODUCTIVE BIOLOGY, 2021, 263 : 50 - 55
  • [6] Relationship between mid-trimester ultrasound fetal liver length measurements and gestational diabetes mellitus
    Perovic, Milan
    Gojnic, Miroslava
    Arsic, Biljana
    Pantic, Igor
    Stefanovic, Tomislav
    Kovacevic, Gordana
    Kovacevic, Milica
    Garalejic, Eliana
    Dugalic, Stefan
    Radakovic, Jovana
    Babic, Uros
    Isenovic, Esma R.
    JOURNAL OF DIABETES, 2015, 7 (04) : 497 - 505
  • [7] Development of an artificial intelligence powered software for automated analysis of skeletal muscle ultrasonography
    Zoe Calulo Rivera
    Felipe González-Seguel
    Arimitsu Horikawa-Strakovsky
    Catherine Granger
    Aarti Sarwal
    Sanjay Dhar
    George Ntoumenopoulos
    Jin Chen
    V. K. Cody Bumgardner
    Selina M. Parry
    Kirby P. Mayer
    Yuan Wen
    Scientific Reports, 15 (1)
  • [8] Colour Doppler evaluation of umbilical arteries in relation to bony landmarks in fetal pelvis as a clue to mid-trimester diagnosis of bladder exstrophy
    Aneja, K.
    Bhalla, A. A.
    ULTRASOUND IN OBSTETRICS & GYNECOLOGY, 2023, 62 : 163 - 163
  • [9] Automated weight-bearing foot measurements using an artificial intelligence-based software
    Lassalle, Louis
    Regnard, Nor-eddine
    Ventre, Jeanne
    Marty, Vincent
    Clovis, Lauryane
    Zhang, Zekun
    Nitche, Nicolas
    Guermazi, Ali
    Laredo, Jean-Denis
    SKELETAL RADIOLOGY, 2025, 54 (02) : 229 - 241
  • [10] Color Doppler evaluation of umbilical arteries in relation to bony landmarks in the fetal pelvis as a clue to the mid-trimester diagnosis of bladder exstrophy: A novel observation
    Aneja, Kavita
    Bhalla, Aradhana Aggarwal
    Nanda, Anupam
    Khurana, Ashok
    JOURNAL OF CLINICAL ULTRASOUND, 2023, 51 (04) : 644 - 651