Pancreas MRI Segmentation Into Head, Body, and Tail Enables Regional Quantitative Analysis of Heterogeneous Disease.
Pancreas MRI Segmentation Into Head, Body, and Tail Enables Regional Quantitative Analysis of Heterogeneous Disease.
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DOI：
10.1002/jmri.28098
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发表时间：
2022-10
影响因子：
4.4
通讯作者：
Bulte, Daniel P.
中科院分区：
文献类型：
--
作者：
Triay Bagur, Alexandre;Aljabar, Paul;Ridgway, Gerard R.;Brady, Michael;Bulte, Daniel P.
胰腺的定量成像研究通常针对头部、身体和尾部这三个主要解剖部分，使用手动感兴趣区域策略来评估地理异质性。现有的自动化分析实现了整个器官的分割，提供了全面的量化，但未能解决空间异质性。开发和验证腹部MRI中胰腺分割为头部、身体和尾部区域的自动方法。回顾一下。来自英国生物库的150名名义上健康的受试者(100名为方法开发受试者，50名为验证受试者)。一个单独的390个英国生物库，包括2型糖尿病(T2 DM)受试者和匹配的非糖尿病患者。1.5 T三维两点狄克逊序列(用于分割和容量评估)和二维轴向多回波梯度回声序列。胰腺节段由验证队列中的四名评分员进行注释。使用骰子重叠(骰子相似系数[DSC])报告评价者间的一致性和评价者间的一致性。开发了一种基于模板配准的分割方法，并针对标注进行了评估。还给出了通过将三维部分分割与一个可用的质子密度脂肪分数(PDFF)图像相交的方法来评估局部胰腺脂肪的结果。Wilcoxon签名等级检验和Mann-Whitney U检验用于比较。用差示扫描量热法和音量差法进行评价。A P值 <； 被认为具有统计学意义。良好的内部一致性(DSC均值，头：0.982，体：0.940，尾：0.961)和评价间(DSC，均值，头：0.968，体：0.905，尾：0.943)一致性被观察到。人工标注与本方法的分割结果(Dsc均值，头部：0.965，正文：0.893，尾部：0.934)相比，差异无统计学意义(头部：P=0.4358，正文：P=0.0992，尾部：P=0.1080)。体重指数匹配的2型糖尿病患者与非糖尿病患者胰体PDFF差异有统计学意义。改进后的分词性能与人工标注没有什么不同。在2型糖尿病患者中的应用显示了评估胰腺疾病异质性的潜力。4 3
Quantitative imaging studies of the pancreas have often targeted the three main anatomical segments, head, body, and tail, using manual region of interest strategies to assess geographic heterogeneity. Existing automated analyses have implemented whole‐organ segmentation, providing overall quantification but failing to address spatial heterogeneity. To develop and validate an automated method for pancreas segmentation into head, body, and tail subregions in abdominal MRI. Retrospective. One hundred and fifty nominally healthy subjects from UK Biobank (100 subjects for method development and 50 subjects for validation). A separate 390 UK Biobank triples of subjects including type 2 diabetes mellitus (T2DM) subjects and matched nondiabetics. A 1.5 T, three‐dimensional two‐point Dixon sequence (for segmentation and volume assessment) and a two‐dimensional axial multiecho gradient‐recalled echo sequence. Pancreas segments were annotated by four raters on the validation cohort. Intrarater agreement and interrater agreement were reported using Dice overlap (Dice similarity coefficient [DSC]). A segmentation method based on template registration was developed and evaluated against annotations. Results on regional pancreatic fat assessment are also presented, by intersecting the three‐dimensional parts segmentation with one available proton density fat fraction (PDFF) image. Wilcoxon signed rank test and Mann–Whitney U‐test for comparisons. DSC and volume differences for evaluation. A P value < 0.05 was considered statistically significant. Good intrarater (DSC mean, head: 0.982, body: 0.940, tail: 0.961) agreement and interrater (DSC mean, head: 0.968, body: 0.905, tail: 0.943) agreement were observed. No differences (DSC, head: P = 0.4358, body: P = 0.0992, tail: P = 0.1080) were observed between the manual annotations and our method's segmentations (DSC mean, head: 0.965, body: 0.893, tail: 0.934). Pancreatic body PDFF was different between T2DM and nondiabetics matched by body mass index. The developed segmentation's performance was no different from manual annotations. Application on type 2 diabetes subjects showed potential for assessing pancreatic disease heterogeneity. 4 3
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影响因子：
10.9
作者：
Schlemper J;Oktay O;Schaap M;Heinrich M;Kainz B;Glocker B;Rueckert D
通讯作者：
Rueckert D
影响因子：
29.4
作者：
Cotter, Thomas G.;Rinella, Mary
通讯作者：
Rinella, Mary
影响因子：
19.7
作者：
Kuehn, Jens-Peter;Berthold, Friederike;Meffert, Peter J.
通讯作者：
Meffert, Peter J.
影响因子：
5.7
作者：
Ashburner J;Friston KJ
通讯作者：
Friston KJ
影响因子：
2.6
作者：
Nadarajah, C.;Fananapazir, G.;Sandrasegaran, K.
通讯作者：
Sandrasegaran, K.