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CT成像在解决分化型甲状腺癌可切除性问题中的作用:基于成像的TI和ETE的马氏分级系统

Role of CT imaging in addressing resectability issues in differentiated thyroid cancer: imaging-based Mahajan grading system for TI and ETE.

作者信息

Mahajan Abhishek, Rastogi Shivam, Shukla Shreya, Agarwal Ujjwal, Vaish Richa, Chakrabarty Nivedita, Ashtekar Renuka, Deokar Shonal, Shaikh Atif, Pai Prathamesh, Chaturvedi Pankaj, Ghosh Laskar Sarbani, Smriti Vasundhara, Rane Swapnil U, Bal Munita, Patil Asawari, Mittal Neha, Noronha Vanita, Patil Vijay, Prabhash Kumar, Dcruz Anil K

机构信息

Imaging Department, The Clatterbridge Cancer Centre NHS Foundation Trust, Liverpool, United Kingdom.

Faculty of Health and Life Sciences, University of Liverpool, Liverpool, United Kingdom.

出版信息

Front Oncol. 2024 Sep 13;14:1382518. doi: 10.3389/fonc.2024.1382518. eCollection 2024.

DOI:10.3389/fonc.2024.1382518
PMID:39346728
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11427697/
Abstract

BACKGROUND AND OBJECTIVE

Extrathyroidal extension (ETE) is the term used to describe the growth of the primary thyroid tumor beyond the thyroid capsule. ETE is a critical prognostic marker for thyroid tumors, necessitating accurate preoperative assessment. This study aims to evaluate the diagnostic performance of computed tomography (CT)-based grading for ETE and tracheal invasion (TI) for preoperative prediction in patients with differentiated papillary thyroid carcinoma (PTC) and compare the diagnostic accuracy with ultrasound (US).

MATERIALS AND METHODS

This retrospective study was approved by our institutional review board. Preoperative US and CT were performed for 83 patients who underwent surgery for PTC between 1 January 2010 and 31 December 2020. The US and CT features of ETE and TI of each case were retrospectively and independently investigated by two radiologists. The diagnostic performances of US and CT, including their specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV) for ETE, and their accuracy in predicting ETE and TI were analyzed. As per the grading for ETE on USG and CT, lesions were graded into three grades and Mahajan grading was also devised on CT to predict the TI and graded into four grades.

RESULTS

The accuracy and specificity of CT are relatively good for identifying tumor infiltration into the adjacent structures and range from 82% to 87% and 95% to 98%, respectively. It, however, has a low sensitivity, between 14.3% and 77.78%, when compared to US, which suggests that in case of any doubt regarding CT evidence of tumor infiltration into surrounding structures, additional clinical examination must be performed. CT showed better sensitivity (78%) and specificity (75%) in detecting TI compared to previous studies. The diagnostic accuracy of CT Mahajan grading was 91.5% with 0.005 in the prediction of TI.

CONCLUSION

Preoperative US should be regarded as a first-line imaging modality for predicting minimal ETE, and CT should be additionally performed for the evaluation of maximal ETE. The specificity and PPV of CT are higher than those of US in detecting overall ETE and TI of PTC. The US- and CT-based grading systems have the potential to optimize preoperative surgical planning.

摘要

背景与目的

甲状腺外扩展(ETE)是用于描述原发性甲状腺肿瘤生长超出甲状腺包膜的术语。ETE是甲状腺肿瘤的关键预后指标,需要进行准确的术前评估。本研究旨在评估基于计算机断层扫描(CT)的ETE分级及气管侵犯(TI)对分化型甲状腺乳头状癌(PTC)患者术前预测的诊断性能,并将诊断准确性与超声(US)进行比较。

材料与方法

本回顾性研究经机构审查委员会批准。对2010年1月1日至2020年12月31日期间接受PTC手术的83例患者进行了术前超声和CT检查。两名放射科医生对每个病例的ETE和TI的超声和CT特征进行了回顾性和独立研究。分析了超声和CT的诊断性能,包括它们对ETE的特异性、敏感性、阳性预测值(PPV)和阴性预测值(NPV),以及它们在预测ETE和TI方面的准确性。根据超声和CT上ETE的分级,病变分为三个等级,还在CT上设计了马哈拉詹分级以预测TI并分为四个等级。

结果

CT在识别肿瘤向相邻结构浸润方面的准确性和特异性相对较好,分别为82%至87%和95%至98%。然而,与超声相比,其敏感性较低,在14.3%至77.78%之间,这表明如果对肿瘤浸润周围结构的CT证据存在任何疑问,必须进行额外的临床检查。与先前研究相比,CT在检测TI方面显示出更好的敏感性(78%)和特异性(75%)。CT马哈拉詹分级在预测TI方面的诊断准确性为91.5%,P值为0.005。

结论

术前超声应被视为预测微小ETE的一线成像方式,对于评估最大ETE应额外进行CT检查。在检测PTC的总体ETE和TI方面,CT的特异性和PPV高于超声。基于超声和CT的分级系统有潜力优化术前手术规划。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/c880138f9029/fonc-14-1382518-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/8eaee568569f/fonc-14-1382518-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/16341e436fc4/fonc-14-1382518-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/7385764a527d/fonc-14-1382518-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/b8fd9ab2f8a8/fonc-14-1382518-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/dc8c2a760ccf/fonc-14-1382518-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/c880138f9029/fonc-14-1382518-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/8eaee568569f/fonc-14-1382518-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/16341e436fc4/fonc-14-1382518-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/7385764a527d/fonc-14-1382518-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/b8fd9ab2f8a8/fonc-14-1382518-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/dc8c2a760ccf/fonc-14-1382518-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ed/11427697/c880138f9029/fonc-14-1382518-g006.jpg

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