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胰腺囊性肿瘤评估中的影像组学进展。

Radiomics advances in the evaluation of pancreatic cystic neoplasms.

作者信息

Mao Kuan-Zheng, Ma Chao, Song Bin

机构信息

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.

Department of Pancreatic Surgery, Changhai Hospital of Shanghai, Naval Medical University, Shanghai, 200433, China.

出版信息

Heliyon. 2024 Jan 30;10(3):e25535. doi: 10.1016/j.heliyon.2024.e25535. eCollection 2024 Feb 15.

Abstract

With the development of medical imaging, the detection rate of pancreatic cystic neoplasms (PCNs) has increased greatly. Serous cystic neoplasm, solid pseudopapillary neoplasm, intraductal papillary mucinous neoplasm and mucinous cystic neoplasm are the main subtypes of PCN, and their treatment options vary greatly due to the different biological behaviours of the tumours. Different from conventional qualitative imaging evaluation, radiomics is a promising noninvasive approach for the diagnosis, classification, and risk stratification of diseases involving high-throughput extraction of medical image features. We present a review of radiomics in the diagnosis of serous cystic neoplasm and mucinous cystic neoplasm, risk classification of intraductal papillary mucinous neoplasm and prediction of solid pseudopapillary neoplasm invasiveness compared to conventional imaging diagnosis. Radiomics is a promising tool in the field of medical imaging, providing a noninvasive, high-performance model for preoperative diagnosis and risk stratification of PCNs and improving prospects regarding management of these diseases. Further studies are warranted to investigate MRI image radiomics in connection with PCNs to improve the diagnosis and treatment strategies in the management of PCN patients.

摘要

随着医学影像学的发展,胰腺囊性肿瘤(PCNs)的检出率大幅提高。浆液性囊性肿瘤、实性假乳头状肿瘤、导管内乳头状黏液性肿瘤和黏液性囊性肿瘤是PCN的主要亚型,由于肿瘤的生物学行为不同,其治疗选择差异很大。与传统的定性影像学评估不同,放射组学是一种很有前景的非侵入性方法,可用于疾病的诊断、分类和风险分层,涉及高通量提取医学图像特征。我们综述了放射组学在浆液性囊性肿瘤和黏液性囊性肿瘤诊断、导管内乳头状黏液性肿瘤风险分类以及实性假乳头状肿瘤侵袭性预测方面与传统影像学诊断的比较。放射组学是医学影像学领域一种很有前景的工具,为PCNs的术前诊断和风险分层提供了一种非侵入性、高性能的模型,并改善了这些疾病的管理前景。有必要进一步开展研究,探讨与PCNs相关的MRI图像放射组学,以改善PCN患者管理中的诊断和治疗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a567/10850586/67771a150669/gr1.jpg

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