Uterine Fundus Remodeling after Hysteroscopic Metroplasty: A Prospective Pilot Study

Casadio, Paolo; Magnarelli, Giulia; Rosa, Michele La; Alletto, Andrea; Arena, Alessandro; Fontana, Enrico; Morra, C; Talamo, Maria; Fabbri, Matilde; Giovannico, Kevin; Virgilio, Agnese; Raimondo, Diego; Guasina, Francesca; Paradisi, Roberto; Seracchioli, Renato

doi:10.3390/jcm10020260

Cited by 7 publications

(2 citation statements)

References 27 publications

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“…After DL model building, the model should undergo external validation and improvement, with the inclusion of further images and videos from other centers. When a high DL model performance is obtained, the inclusion of cases with other rarer intrauterine pathologies (e.g., Mullerian malformations, atypical polypoid adenomioma, pecoma, sarcoma, trophoblastic disease, retained products of conception) [27][28][29][30] might make the DL model testable in the clinical practice thorough comparison of diagnostic performance by expert endoscopists.…”

Section: Discussionmentioning

confidence: 99%

Detection and Classification of Hysteroscopic Images Using Deep Learning

Raimondo,

Raffone,

Salucci

et al. 2024

Cancers

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Background: Although hysteroscopy with endometrial biopsy is the gold standard in the diagnosis of endometrial pathology, the gynecologist experience is crucial for a correct diagnosis. Deep learning (DL), as an artificial intelligence method, might help to overcome this limitation. Unfortunately, only preliminary findings are available, with the absence of studies evaluating the performance of DL models in identifying intrauterine lesions and the possible aid related to the inclusion of clinical factors in the model. Aim: To develop a DL model as an automated tool for detecting and classifying endometrial pathologies from hysteroscopic images. Methods: A monocentric observational retrospective cohort study was performed by reviewing clinical records, electronic databases, and stored videos of hysteroscopies from consecutive patients with pathologically confirmed intrauterine lesions at our Center from January 2021 to May 2021. Retrieved hysteroscopic images were used to build a DL model for the classification and identification of intracavitary uterine lesions with or without the aid of clinical factors. Study outcomes were DL model diagnostic metrics in the classification and identification of intracavitary uterine lesions with and without the aid of clinical factors. Results: We reviewed 1500 images from 266 patients: 186 patients had benign focal lesions, 25 benign diffuse lesions, and 55 preneoplastic/neoplastic lesions. For both the classification and identification tasks, the best performance was achieved with the aid of clinical factors, with an overall precision of 80.11%, recall of 80.11%, specificity of 90.06%, F1 score of 80.11%, and accuracy of 86.74 for the classification task, and overall detection of 85.82%, precision of 93.12%, recall of 91.63%, and an F1 score of 92.37% for the identification task. Conclusion: Our DL model achieved a low diagnostic performance in the detection and classification of intracavitary uterine lesions from hysteroscopic images. Although the best diagnostic performance was obtained with the aid of clinical data, such an improvement was slight.

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Section: Discussionmentioning

confidence: 99%

Detection and Classification of Hysteroscopic Images Using Deep Learning

Raimondo,

Raffone,

Salucci

et al. 2024

Cancers

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“…As the imaging technology develops, the use of 3D ultrasonography is getting more and more popular. 3D ultrasound could measure the lateral wall thickness and cavity depth of the uterus precisely [ 29 ], making it possible to develop objective and standardized diagnostic criteria. Alonso Pacheco et al [ 30 ] have proposed an IYT classification system based on transvaginal 3D ultrasound for T-shaped uterus, whose value will be confirmed in the future.…”

Section: Discussionmentioning

confidence: 99%

Reproductive outcome of hysteroscopic metroplasty for women with T-shaped uterus: a retrospective study

Zhang

Zhu

et al. 2022

Reprod Health

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Background T-shaped uterus is a Müllerian malformation with unapparent clinical manifestations. Intrauterine adhesion and tuberculosis may lead to T-shaped uterus, too. Hysteroscopic metroplasty is a treatment option for T-shaped uterus, while the postoperative reproductive outcomes have not been thoroughly investigated. The aim of this study was to determine the reproductive outcome in Chinese women with T-shaped uterus who had hysteroscopic metroplasty with cold scissors. Methods This retrospective cohort study was conducted in the reproductive surgery unit of a university-affiliated hospital. One hundred and eleven patients with T-shaped uterus who underwent hysteroscopic metroplasty from Jan. 2017 to Sept. 2019 were followed-up by telephone in Apr. 2021. All patients received hysteroscopic metroplasty using microcissors, followed by estrogen-progesterone sequential treatment, with or without intrauterine device (IUD) implantation. According to whether they had had history of intrauterine operation, patients were divided into congenital group and acquired group. The main outcome measure was postoperative live birth rate. χ2 test and t test were used for comparison between groups. Cochran-Mantel–Haenszel test were used for stratified analysis. P < 0.05 was considered statistically significant. Results One hundred and eleven patients were included in total, with 46 in congenital group and 65 in acquired group. After hysteroscopic metroplasty, in the congenital group, the pregnancy rate increased from 28.3% to 87.0% (P < 0.001) and the live birth rate increased from 23.1% to 79.5% (P = 0.001); in the acquired group, the pregnancy rate slightly dropped from 98.5% to 72.3% (P < 0.001) while the live birth rate increased from 20.8% to 74.5% (P < 0.001). No statistically significant difference was observed in postoperative reproductive outcome indicators between the two subgroups except mode of conception. Conclusions For both groups, hysteroscopic metroplasty may improve reproductive outcomes for patients with T-shaped uterus.

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