Megan Hall, Jordina Aviles Verdera, Daniel Cromb, Sara Neves Silva, Mary Rutherford, Serena J Counsell, Joseph V Hajnal, Lisa Story, Jana Hutter
{"title":"从 0.55T 到 3T 的场强范围内,胎盘 T2* 作为胎盘功能的测量指标。","authors":"Megan Hall, Jordina Aviles Verdera, Daniel Cromb, Sara Neves Silva, Mary Rutherford, Serena J Counsell, Joseph V Hajnal, Lisa Story, Jana Hutter","doi":"10.1038/s41598-024-77406-6","DOIUrl":null,"url":null,"abstract":"<p><p>Placental MRI is increasingly implemented in clinical obstetrics and research. Functional imaging, especially T2*, has been shown to vary across gestation and in pathology. Translation into the clinical arena has been slow because of time taken to mask the region of interest and owing to differences in T2* results depending on field strength. This paper contributes methodology to remove these barriers by utilising data from 0.55, 1.5 and 3T MRI to provide a fully automated segmentation tool; determining field strength dependency of placental assessment techniques; and deriving normal ranges for T2* by gestational age but independent of field strength. T2* datasets were acquired across field strengths. Automatic quantification including fully automatic masking was achieved and tested in 270 datasets across fields. Normal curves for quantitative placental mean T2*, volume and other derived measurements were obtained in 273 fetal MRI scans and z-scores calculated. The fully automatic segmentation achieved excellent quantification results (Dice scores of 0.807 at 3T, 0.796 at 1.5T and 0.815 at 0.55T.). Similar changes were seen between placental T2* and gestational age across all three field strengths (p < 0.05). Z-scores were generated. This study provides confidence in the translatability of T2* trends across field strengths in fetal imaging.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"14 1","pages":"28594"},"PeriodicalIF":3.8000,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Placental T2* as a measure of placental function across field strength from 0.55T to 3T.\",\"authors\":\"Megan Hall, Jordina Aviles Verdera, Daniel Cromb, Sara Neves Silva, Mary Rutherford, Serena J Counsell, Joseph V Hajnal, Lisa Story, Jana Hutter\",\"doi\":\"10.1038/s41598-024-77406-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Placental MRI is increasingly implemented in clinical obstetrics and research. Functional imaging, especially T2*, has been shown to vary across gestation and in pathology. Translation into the clinical arena has been slow because of time taken to mask the region of interest and owing to differences in T2* results depending on field strength. This paper contributes methodology to remove these barriers by utilising data from 0.55, 1.5 and 3T MRI to provide a fully automated segmentation tool; determining field strength dependency of placental assessment techniques; and deriving normal ranges for T2* by gestational age but independent of field strength. T2* datasets were acquired across field strengths. Automatic quantification including fully automatic masking was achieved and tested in 270 datasets across fields. Normal curves for quantitative placental mean T2*, volume and other derived measurements were obtained in 273 fetal MRI scans and z-scores calculated. The fully automatic segmentation achieved excellent quantification results (Dice scores of 0.807 at 3T, 0.796 at 1.5T and 0.815 at 0.55T.). Similar changes were seen between placental T2* and gestational age across all three field strengths (p < 0.05). Z-scores were generated. This study provides confidence in the translatability of T2* trends across field strengths in fetal imaging.</p>\",\"PeriodicalId\":21811,\"journal\":{\"name\":\"Scientific Reports\",\"volume\":\"14 1\",\"pages\":\"28594\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Reports\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41598-024-77406-6\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Reports","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41598-024-77406-6","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Placental T2* as a measure of placental function across field strength from 0.55T to 3T.
Placental MRI is increasingly implemented in clinical obstetrics and research. Functional imaging, especially T2*, has been shown to vary across gestation and in pathology. Translation into the clinical arena has been slow because of time taken to mask the region of interest and owing to differences in T2* results depending on field strength. This paper contributes methodology to remove these barriers by utilising data from 0.55, 1.5 and 3T MRI to provide a fully automated segmentation tool; determining field strength dependency of placental assessment techniques; and deriving normal ranges for T2* by gestational age but independent of field strength. T2* datasets were acquired across field strengths. Automatic quantification including fully automatic masking was achieved and tested in 270 datasets across fields. Normal curves for quantitative placental mean T2*, volume and other derived measurements were obtained in 273 fetal MRI scans and z-scores calculated. The fully automatic segmentation achieved excellent quantification results (Dice scores of 0.807 at 3T, 0.796 at 1.5T and 0.815 at 0.55T.). Similar changes were seen between placental T2* and gestational age across all three field strengths (p < 0.05). Z-scores were generated. This study provides confidence in the translatability of T2* trends across field strengths in fetal imaging.
期刊介绍:
We publish original research from all areas of the natural sciences, psychology, medicine and engineering. You can learn more about what we publish by browsing our specific scientific subject areas below or explore Scientific Reports by browsing all articles and collections.
Scientific Reports has a 2-year impact factor: 4.380 (2021), and is the 6th most-cited journal in the world, with more than 540,000 citations in 2020 (Clarivate Analytics, 2021).
•Engineering
Engineering covers all aspects of engineering, technology, and applied science. It plays a crucial role in the development of technologies to address some of the world''s biggest challenges, helping to save lives and improve the way we live.
•Physical sciences
Physical sciences are those academic disciplines that aim to uncover the underlying laws of nature — often written in the language of mathematics. It is a collective term for areas of study including astronomy, chemistry, materials science and physics.
•Earth and environmental sciences
Earth and environmental sciences cover all aspects of Earth and planetary science and broadly encompass solid Earth processes, surface and atmospheric dynamics, Earth system history, climate and climate change, marine and freshwater systems, and ecology. It also considers the interactions between humans and these systems.
•Biological sciences
Biological sciences encompass all the divisions of natural sciences examining various aspects of vital processes. The concept includes anatomy, physiology, cell biology, biochemistry and biophysics, and covers all organisms from microorganisms, animals to plants.
•Health sciences
The health sciences study health, disease and healthcare. This field of study aims to develop knowledge, interventions and technology for use in healthcare to improve the treatment of patients.