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1.
World J Clin Cases ; 8(21): 5389-5393, 2020 Nov 06.
Artículo en Inglés | MEDLINE | ID: mdl-33269274

RESUMEN

BACKGROUND: Conjoined twins are a rare occurrence, and the majority of these malformations are detected during second trimester screening. CASE SUMMARY: Herein we report a case of conjoined twins, which was diagnosed by ultrasound at 8 wk gestation and was normal at 7 wk gestation. The two fetuses shared one heart and were diagnosed as thoracopagus twins. This is the first report of conjoined twins diagnosed at 8 wk gestation. The pregnancy was terminated electively at 9 wk gestation. Because some congenital malformations can be diagnosed earlier, a prenatal ultrasound examination at an early gestational stage cannot be dismissed. CONCLUSION: This case demonstrates that a 7-8 wk gestation might be the earliest period when conjoined twins can be diagnosed by ultrasound.

2.
Chin Med J (Engl) ; 132(16): 1974-1982, 2019 Aug 20.
Artículo en Inglés | MEDLINE | ID: mdl-31348028

RESUMEN

OBJECTIVE: Ultrasound imaging is well known to play an important role in the detection of thyroid disease, but the management of thyroid ultrasound remains inconsistent. Both standardized diagnostic criteria and new ultrasound technologies are essential for improving the accuracy of thyroid ultrasound. This study reviewed the global guidelines of thyroid ultrasound and analyzed their common characteristics for basic clinical screening. Advances in the application of a combination of thyroid ultrasound and artificial intelligence (AI) were also presented. DATA SOURCES: An extensive search of the PubMed database was undertaken, focusing on research published after 2001 with keywords including thyroid ultrasound, guideline, AI, segmentation, image classification, and deep learning. STUDY SELECTION: Several types of articles, including original studies and literature reviews, were identified and reviewed to summarize the importance of standardization and new technology in thyroid ultrasound diagnosis. RESULTS: Ultrasound has become an important diagnostic technique in thyroid nodules. Both standardized diagnostic criteria and new ultrasound technologies are essential for improving the accuracy of thyroid ultrasound. In the standardization, since there are no global consensus exists, common characteristics such as a multi-feature diagnosis, the performance of lymph nodes, explicit indications of fine needle aspiration, and the diagnosis of special populations should be focused on. Besides, evidence suggests that AI technique has a good effect on the unavoidable limitations of traditional ultrasound, and the combination of diagnostic criteria and AI may lead to a great promotion in thyroid diagnosis. CONCLUSION: Standardization and development of novel techniques are key factors to improving thyroid ultrasound, and both should be considered in normal clinical use.


Asunto(s)
Inteligencia Artificial , Glándula Tiroides/diagnóstico por imagen , Aprendizaje Profundo , Humanos , Nódulo Tiroideo/diagnóstico por imagen
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