首页> 外文期刊>Journal of magnetic resonance imaging: JMRI >Developing and validating a multivariable prediction model to improve the diagnostic accuracy in determination of cervical versus endometrial origin of uterine adenocarcinomas: A prospective MR study combining diffusion‐weighted imaging and spectroscopy
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Developing and validating a multivariable prediction model to improve the diagnostic accuracy in determination of cervical versus endometrial origin of uterine adenocarcinomas: A prospective MR study combining diffusion‐weighted imaging and spectroscopy

机译:开发和验证多变量预测模型,提高子宫腺癌宫颈与子宫内膜源测定的诊断准确性:漫射加权成像和光谱组合的前瞻性研究

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Background A triage test to assist clinical decision‐making on choosing primary chemoradiation for cervical carcinomas or primary surgery for endometrial carcinomas is important. Purpose or Hypothesis To develop and validate a multiparametric prediction model based on MR imaging and spectroscopy in distinguishing adenocarcinomas of uterine cervical or endometrial origin. Study Type Prospective diagnostic accuracy study. Population Eighty‐seven women: 25 cervical and 62 endometrial adenocarcinomas divided into training (n?=?43; cervical/endometrial adenocarcinomas?=?11/32) and validation (n?=?44; 14/30) datasets. Field Strength/Sequence The 3T diffusion‐weighted (DW) MR imaging and MR spectroscopy. Assessment Morphology, volumetric DW MR imaging and spectroscopy (MDS) scoring system with total points 0–5, based on presence of the following MR features assessed independently by two radiologists: (a) epicenter at the cervix, (b) rim enhancement, (c) disrupted cervical stromal integrity, (d) mean volumetric apparent diffusion coefficient values (ADCmean) higher than 0.98?×?10‐3?mm 2 /s, (e) fatty acyl δ 1.3?ppm more than 161.92?mM. Histopathology as gold standard. Statistical Tests Logistic regression and receiver operator characteristic (ROC) curves analysis. Results For both the training and validation datasets, the MDS score achieved an accuracy of 93.0% and 84.1%, significantly higher than that of morphology (88.4% and 79.5%), ADC value (74.4% and 68.2%), and spectroscopy (81.4% and 68.2%; P ??0.05 for all). The performances of the scoring were superior to the morphology in the training dataset (areas under the receiver operating characteristics curve [AUC]?=?0.95 vs. 0.89; P ?=?0.046), but not in the validation dataset (AUC?=?0.90 vs. 0.85; P ?=?0.289). Data Conclusion MDS score has potentials to improve distinguishing adenocarcinomas of cervical or endometrial origin, and warrants large‐scale studies for further validation. Level of Evidence: 1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1654–1666.
机译:背景技术在为子宫内膜癌中选择用于宫颈癌或初级手术的临床决策,以帮助临床决策的分类试验很重要。目的或假设基于MR成像和光谱分析子宫宫颈或子宫内膜源性腺癌的MR成像和光谱的多射性预测模型。研究类型预期诊断准确性研究。人口八十七名女性:25例宫颈和62个子宫内膜腺癌分为训练(N?=?43;宫颈/子宫内膜腺癌?=?11/32)和验证(n?=?44; 14/30)数据集。场强/序列3T扩散加权(DW)MR成像和MR光谱。评估形态,体积DW MR成像和光谱(MDS)评分系统的总点0-5,基于以下MR特征独立于两个放射科医生进行评估:(a)子宫颈震中,(b)rim增强,( c)破坏宫颈基质完整性,(D)平均容量表观扩散系数值(ADCmean)高于0.98Ω·×10-3×mm 2 / s,(e)脂肪酰基δ1.3≤mm≤1.3μm≤1.3。组织病理学为黄金标准。统计测试Logistic回归和接收器操作员特征(ROC)曲线分析。培训和验证数据集的结果,MDS评分的准确性为93.0%和84.1%,显着高于形态学(88.4%和79.5%),ADC值(74.4%和68.2%)和光谱(81.4 %和68.2%; p?&Δ0.05)。评分的性能优于训练数据集的形态(接收器操作特性曲线下的区域[AUC]?=?0.95与0.89; p?= 0.046),但不在验证数据集(AUC?= ?0.90 vs. 0.85; p?= 0.289)。数据结论MDS评分具有改善宫颈或子宫内膜源性腺癌的潜力,并认证进行进一步验证的大规模研究。证据水平:1技术疗效:第3阶段J. MANG。恢复。 2018年成像; 47:1654-1666。

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