Suppr超能文献

用基于全自动胰腺分割的 MRI 放射组学模型替代增强型磁共振胰胆管成像,以评估慢性胰腺炎患者的胰腺外分泌功能。

Replacing secretin-enhanced MRCP with MRI radiomics model based on a fully automated pancreas segmentation for assessing pancreatic exocrine function in chronic pancreatitis.

机构信息

Department of Radiology, Changhai Hospital, Navy Medical University, Changhai Road 168, Shanghai, 200434, China.

出版信息

Eur Radiol. 2023 May;33(5):3580-3591. doi: 10.1007/s00330-023-09448-9. Epub 2023 Mar 8.

Abstract

OBJECTIVES

To develop and validate a radiomics nomogram based on a fully automated pancreas segmentation to assess pancreatic exocrine function. Furthermore, we aimed to compare the performance of the radiomics nomogram with the pancreatic flow output rate (PFR) and conclude on the replacement of secretin-enhanced magnetic resonance cholangiopancreatography (S-MRCP) by the radiomics nomogram for pancreatic exocrine function assessment.

METHODS

All participants underwent S-MRCP between April 2011 and December 2014 in this retrospective study. PFR was quantified using S-MRCP. Participants were divided into normal and pancreatic exocrine insufficiency (PEI) groups using the cut-off of 200 µg/L of fecal elastase-1. Two prediction models were developed including the clinical and non-enhanced T1-weighted imaging radiomics model. A multivariate logistic regression analysis was conducted to develop the prediction models. The models' performances were determined based on their discrimination, calibration, and clinical utility.

RESULTS

A total of 159 participants (mean age [Formula: see text] standard deviation, 45 years [Formula: see text] 14;119 men) included 85 normal and 74 PEI. All the participants were divided into a training set comprising 119 consecutive patients and an independent validation set comprising 40 consecutive patients. The radiomics score was an independent risk factor for PEI (odds ratio = 11.69; p < 0.001). In the validation set, the radiomics nomogram exhibited the highest performance (AUC, 0.92) in PEI prediction, whereas the clinical nomogram and PFR had AUCs of 0.79 and 0.78, respectively.

CONCLUSION

The radiomics nomogram accurately predicted pancreatic exocrine function and outperformed pancreatic flow output rate on S-MRCP in patients with chronic pancreatitis.

KEY POINTS

• The clinical nomogram exhibited moderate performance in diagnosing pancreatic exocrine insufficiency. • The radiomics score was an independent risk factor for pancreatic exocrine insufficiency, and every point rise in the rad-score was associated with an 11.69-fold increase in pancreatic exocrine insufficiency risk. • The radiomics nomogram accurately predicted pancreatic exocrine function and outperformed the clinical model and pancreatic flow output rate quantified by secretin-enhanced magnetic resonance cholangiopancreatography on MRI in patients with chronic pancreatitis.

摘要

目的

开发并验证一个基于全自动胰腺分割的放射组学列线图,以评估胰腺外分泌功能。此外,我们旨在比较放射组学列线图与胰腺分泌率(PFR)的性能,并得出用放射组学列线图替代磁共振胰胆管成像增强后(S-MRCP)用于胰腺外分泌功能评估的结论。

方法

本回顾性研究纳入 2011 年 4 月至 2014 年 12 月间接受 S-MRCP 的所有参与者。使用 S-MRCP 定量测量 PFR。使用粪便弹性蛋白酶-1 的 200μg/L 截断值将参与者分为正常组和胰腺外分泌功能不全(PEI)组。建立了包括临床和非增强 T1 加权成像放射组学模型的两种预测模型。通过多变量逻辑回归分析来建立预测模型。根据其区分度、校准度和临床实用性来确定模型的性能。

结果

共纳入 159 名参与者(平均年龄[Formula: see text]标准差,45 岁[Formula: see text]14 岁;119 名男性),包括 85 名正常组和 74 名 PEI 组。所有参与者被分为一个包含 119 例连续患者的训练集和一个包含 40 例连续患者的独立验证集。放射组学评分是 PEI 的独立危险因素(比值比 = 11.69;p < 0.001)。在验证集中,放射组学列线图在预测 PEI 方面表现出最高的性能(AUC,0.92),而临床列线图和 PFR 的 AUC 分别为 0.79 和 0.78。

结论

放射组学列线图可准确预测慢性胰腺炎患者的胰腺外分泌功能,且在 S-MRCP 上优于胰腺分泌率。

关键点

  • 临床列线图在诊断胰腺外分泌功能不全方面表现出中等性能。

  • 放射组学评分是胰腺外分泌功能不全的独立危险因素,放射组学评分每增加 1 分,患胰腺外分泌功能不全的风险就会增加 11.69 倍。

  • 放射组学列线图可准确预测胰腺外分泌功能,且在慢性胰腺炎患者中,优于基于 S-MRCP 的磁共振胰胆管成像增强后评估胰腺外分泌功能的临床模型和胰腺分泌率。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验