Quantitative magnetic resonance imaging and automated textural radiomics for assessment of human placenta accreta spectrum

用于评估人类植入性胎盘谱的定量磁共振成像和自动纹理放射组学

• 批准号: 10693182
• 负责人: Quyen Ngoc Do
• 金额: $ 11.38万
• 依托单位: UT SOUTHWESTERN MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-24 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10693182
• 关键词: Abnormal placentation; Advisory Committees; Affect; Anatomy; Biology; Blood Vessels; Cellularity; Cesarean section; Characteristics; Chemistry; Cicatrix; Clinical; Counseling; Data; Data Analyses; Data Set; Development; Development Plans; Diagnosis; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Exhibits; First Pregnancy Trimester; Functional disorder; Future; Gestational Age; Goals; Hemorrhage; Heterogeneity; High Risk Woman; High-Risk Pregnancy; Human; Hysterectomy; Image; Image Analysis; Imaging Techniques; Implant; Invaded; Knowledge; Leadership; Life; Magnetic Resonance; Magnetic Resonance Imaging; Manuals; Maps; Maternal Mortality; Measurement; Measures; Mentorship; Modeling; Monitor; Morbidity - disease rate; Motion; Nature; Noise; Operative Surgical Procedures; Outcome; Pathologic; Patients; Pattern; Perfusion; Perinatal; Physics; Physiological; Physiology; Pilot Projects; Placenta; Placenta Accreta; Positioning Attribute; Pregnancy; Protocols documentation; Recording of previous events; Reproducibility; Research; Research Design; Research Personnel; Resolution; Respiration; Risk; Risk Factors; Risk Marker; Severities; Severity of illness; Statistical Data Interpretation; T2 weighted imaging; Technical Expertise; Testing; Texture; Third Pregnancy Trimester; Tissues; Training; Uterus; Visualization; Woman; Work; arterial spin labeling; automated algorithm; career; career development; deep learning; deep learning algorithm; experience; fetal; high risk; imaging modality; implantation; improved; interest; intrapartum; maternal morbidity; multidisciplinary; novel; predictive marker; predictive modeling; prospective; radiomics; recruit; skills; soft tissue; surgery outcome; tool; ultrasound

PROJECT SUMMARY Placenta Accreta Spectrum (PAS) disorder is a condition in which the placenta fails to separate partially or totally from the uterine wall, resulting in significant intrapartum maternal morbidity and mortality at delivery. Depending on the extent of the placental invasion into surrounding tissue, hysterectomy may be lifesaving. Assessment of PAS severity prior to delivery is crucial for multidisciplinary surgical planning and patient counseling. However, there is an unmet clinical need for quantitative, objective measures of abnormal placentation that can serve as predictors of risk of invasion and hysterectomy. The overall goal of the proposed project is to prospectively assess PAS in high-risk women across gestation using quantitative multi-parametric magnetic resonance (MR) imaging and automated textural radiomics and to correlate findings with surgical outcomes. Coming from a highly interdisciplinary background of MR chemistry, biology, and physics, the candidate's long-term career goal is to become an independent investigator with in-depth knowledge and skills to conduct translational placental imaging research. The candidate's short-term goal is to complete a pilot study under the mentorship of an interdisciplinary advisory committee to evaluate PAS in women with high-risk pregnancies using multi-parametric MRI and textural radiomics. To meet these goals, the following research aims are proposed: 1) Evaluate placental invasion across gestation using multi-parametric MR imaging and deep learning based novel quantification tools in PAS high- risk pregnancies, and 2) Extract the radiomic pattern across gestation of high-risk PAS placenta and determine its association with clinical surgical outcome. These research aims will serve as the platform for the career development plan and training aims which include: 1) Gain knowledge in translational prospective research design, 2) Improve technical skills in advanced clinical MR acquisition development, 3) Acquire applied statistical and data analysis skills, and 4) Develop mentorship and leadership skills while under training. Together, the research and training aims will provide the training, experience and preliminary data for an R01 application. The future R01 will develop a clinical and surgical outcome prediction model for high-risk PAS pregnancies, potentially improving maternal and fetal outcomes. The training will position the candidate to become a leader in translational placental imaging research.

项目摘要 胎盘植入频谱（PAS）障碍是一种胎盘未能部分分离的情况 或完全从子宫壁脱落，导致分娩时产妇发病率和死亡率很高。 根据胎盘侵入周围组织的程度，子宫切除术可能挽救生命。 分娩前PAS严重程度的评估对于多学科手术计划和患者 辅导然而，对于异常的、非特异性的、定量的、客观的测量存在未满足的临床需求。 胎盘型可作为子宫浸润和子宫切除风险的预测指标。拟议的总体目标 一个项目是前瞻性地评估PAS在高风险妇女在整个妊娠期使用定量多参数 磁共振（MR）成像和自动纹理放射组学，并将结果与手术 结果。 来自MR化学，生物学和物理学的高度跨学科背景， 候选人的长期职业目标是成为一名具有深入知识和技能的独立调查员 进行胎盘成像研究。候选人的短期目标是完成一个试点 在一个跨学科咨询委员会的指导下进行研究，以评估高危妇女的PAS 妊娠使用多参数MRI和纹理放射组学。 为了实现这些目标，提出了以下研究目标：1）评估胎盘侵袭， 妊娠期使用多参数MR成像和基于深度学习的新型量化工具， 风险妊娠，以及2）提取高风险PAS胎盘妊娠期间的放射组学模式，并确定 其与临床手术结果的相关性。这些研究目标将作为职业生涯的平台 发展计划和培训目标包括：1）获得翻译前瞻性研究的知识 设计，2）提高高级临床MR采集开发的技术技能，3）采集应用 统计和数据分析技能，以及4）在培训期间发展指导和领导技能。 研究和培训目标将共同为以下方面提供培训、经验和初步数据： R01应用程序未来的R01将为高风险患者开发临床和手术结局预测模型。 PAS妊娠，可能改善母体和胎儿结局。培训将使候选人能够 成为转化胎盘成像研究的领导者。

项目成果

Inter-reader agreement of multi-variable MR evaluation of Placenta Accreta Spectrum (PAS) and association with cesarean hysterectomy.

• DOI: 10.1016/j.placenta.2022.07.005
• 发表时间: 2022-08
• 期刊: PLACENTA
• 影响因子: 3.8
• 作者: Khan, Ambereen;Do, Quyen N.;Xi, Yin;Spong, Catherine Y.;Happe, Sarah K.;Dashe, Jodi S.;Twickler, Diane M.
• 通讯作者: Twickler, Diane M.