Pelvic floor evaluation with transperineal ultrasound: a new approach

Vellucci, Francesca Letizia; Regini, Cristina; Barbanti, Chiara; Luisi, Stefano

doi:10.23736/s0026-4784.17.04121-1

Cited by 10 publications

(9 citation statements)

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“…Artificial intelligence algorithm was one of the most widely used and concerned technologies in the field of medical images. It showed excellent performance in medical image feature extraction, lesion segmentation, noise reduction, and edge detection [ 13 ]. At present, there are few studies on the application of this technology in ultrasonic image processing of pelvic floor dysfunction diseases.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Nursing Effect of Pelvic Floor Rehabilitation Training on Pelvic Organ Prolapse in Postpartum Pregnant Women under Ultrasound Imaging with Artificial Intelligence Algorithm

Yin

Wang

2022

Computational and Mathematical Methods in Medicine

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This study was aimed at exploring the application value of ultrasound technology and rehabilitation training based on artificial intelligence algorithm in postpartum recovery of pelvic organ prolapse. Sixty patients diagnosed as mild and moderate pelvic organ prolapse by pelvic organ prolapse quantification evaluation were selected as the research objects. The patients were randomly divided into experimental group (30 cases) and control group (30 cases). The patients in the control group were given routine guidance and postpartum health education 42 days after delivery and given no pelvic floor rehabilitation training, waiting for natural recovery. 42 days after delivery, the patients in the experimental group received pelvic floor rehabilitation training based on the patients in the control group. All patients underwent ultrasonography, the convolution neural network (CNN) algorithm was used for image denoising and edge feature extraction, and the performance of the algorithm was evaluated by the Dice coefficient, positive predictive value, sensitivity, and Hausdorff distance. The thickness of levator ani muscle, anterior and posterior diameter of perineal hiatus, pelvic floor muscle strength, and imaging data were compared between the two groups. The results revealed that the thickness of levator ani muscle in the experimental group was significantly greater than that in the control group after one month and three months of treatment ( 0.633 ± 0.26 cm vs. 0.519 ± 0.234 cm, 0.7 ± 0.214 cm vs. 0.507 ± 0.168 cm, P < 0.05 ). After one month and three months of treatment, the anterior and posterior diameter of perineal fissure in the experimental group was obviously smaller than that in the control group ( 4.76 ± 0.513 cm vs. 5.002 ± 0.763 cm, 4.735 ± 0.614 cm vs. 4.987 ± 0.581 cm, P < 0.05 ). The pelvic floor muscle strength of the experimental group was remarkably higher than that of the control group after one month and three months of treatment ( 3.183 ± 1.47 vs. 2.41 ± 1.57 , 3.365 ± 1.53 vs. 2.865 ± 1.69 , P < 0.05 ). The ultrasonic image was clearer, the focus was more prominent, and the image quality was significantly improved after being processed by artificial intelligence algorithm. The Dice coefficient, positive predictive value, sensitivity, and Hausdorff distance of the proposed algorithm were better than those of the traditional algorithm. Thus, artificial intelligence algorithm had a good effect in ultrasonic image processing. Pelvic floor rehabilitation training had a good effect on postpartum nursing of patients with pelvic organ prolapse.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Nursing Effect of Pelvic Floor Rehabilitation Training on Pelvic Organ Prolapse in Postpartum Pregnant Women under Ultrasound Imaging with Artificial Intelligence Algorithm

Yin

Wang

2022

Computational and Mathematical Methods in Medicine

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“…These investigations, however, did not look at changes in the contractility and distensibility of the levator hiatus during PFM contraction and the Valsalva maneuver employing 3D transperineal ultrasound (3D‐TPUS). Additionally, ultrasonography is the objective method as a standard diagnostic tool in functional urogynecology research 11 …”

Section: Introductionmentioning

confidence: 99%

“…Additionally, ultrasonography is the objective method as a standard diagnostic tool in functional urogynecology research. 11 Such functional PFM changes during pregnancy could contribute to the development of pelvic floor dysfunction (PFD). Therefore, a long-term study of GDM's role in PFM myopathy should offer the physiopathological basis for long-term UI triggered by GDM.…”

Section: Introductionmentioning

confidence: 99%

Pelvic floor muscle dysfunction at 3D transperineal ultrasound in maternal exposure to gestational diabetes mellitus: A prospective cohort study during pregnancy

Pinheiro

Filho

Prudêncio

et al. 2022

Neurourology and Urodynamics

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Aim: This study aimed to assess, for the first time, the dynamic morphometry of pelvic floor muscles (PFM) using three-dimensional transperineal ultrasound (3D-TPUS) and its progression at two-time points of gestation between women with and without gestational diabetes mellitus (GDM), and whether the PFM dysfunction is connected to GDM. Methods:The study comprised 83 consecutive pregnant women with (n = 38) and without (n = 45) GDM screened at 24-30 and 38-40 weeks of gestation. 3D-TPUS and a mobility test were used to quantify PFM dynamic morphometry during maximum contraction and the Valsalva maneuver. Results: When compared to the control group, GDM women had no significant variations in all levator hiatal dimensions at 24-30 weeks of gestation. Meanwhile, women with GDM experienced an increase in levator hiatal area (LHa) (p < 0.000) during PFM contraction and enlargement in LHa (p < 0.001) during Valsalva maneuver (p = 0.010) at 38-40 weeks of gestation.

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“…AI is more frequent in women (females:males = 3:1) and it is estimated that about 40% of women over 70 years old are affected. Evaluation of the pelvic floor is generally clinical, but in the last two decades, the use of ultrasound has become a mainstream diagnostic tool in the investigation of female pelvic organ prolapse, urinary and fecal incontinence and other defecation disorders, providing an immediate objective confirmation of clinical examination findings [2]. Both AI and urinary incontinence are major health problems.…”

Section: Introductionmentioning

confidence: 99%