Diagnostic Value of Apparent Diffusion Coefficient in Predicting Pathological T Stage in Patients with Thymic Epithelial Tumor

Overview

Journal Cancer Imaging

Publisher Springer Nature

Specialties Oncology
Radiology

Date 2022 Oct 5

PMID 36199129

Authors

Chao-Chun Chang

Chia-Ying Lin

Li-Ting Huang

Ming-Tsung Chuang

Ying-Hung Lu

Wei-Li Huang

Ying-Yuan Chen

Wu-Wei Lai

Yau-Lin Tseng

Yi-Ting Yen

Affiliations

Soon will be listed here.

Abstract

Purposes: This study aimed to evaluate the diagnostic capacity of apparent diffusion coefficient (ADC) in predicting pathological Masaoka and T stages in patients with thymic epithelial tumors (TETs).

Methods: Medical records of 62 patients who were diagnosed with TET and underwent diffusion-weighted imaging (DWI) prior to surgery between August 2017 and July 2021 were retrospectively analyzed. ADC values were calculated from DWI images using b values of 0, 400, and 800 s/mm. Pathological stages were determined by histological examination of surgical specimens. Cut-off points of ADC values were calculated via receiver operating characteristic (ROC) analysis.

Results: Patients had a mean age of 56.3 years. Mean ADC values were negatively correlated with pathological Masaoka and T stages. Higher values of the area under the ROC curve suggested that mean ADC values more accurately predicated pathological T stages than pathological Masaoka stages. The optimal cut-off points of mean ADC were 1.62, 1.31, and 1.48 × 10 mm/sec for distinguishing pathological T2-T4 from pathological T1, pathological T4 from pathological T1-T3, and pathological T3-T4 from pathological T2, respectively.

Conclusion: ADC seems to more precisely predict pathological T stages, compared to pathological Masaoka stage. The cut-off values of ADC identified may be used to preoperatively predict pathological T stages of TETs.

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References

Priola A, Priola S, Giraudo M, Gned D, Fornari A, Ferrero B . Diffusion-weighted magnetic resonance imaging of thymoma: ability of the Apparent Diffusion Coefficient in predicting the World Health Organization (WHO) classification and the Masaoka-Koga staging system and its prognostic significance on.... Eur Radiol. 2015; 26(7):2126-38. DOI: 10.1007/s00330-015-4031-6. View

Broncano J, Alvarado-Benavides A, Bhalla S, Alvarez-Kindelan A, Raptis C, Luna A . Role of advanced magnetic resonance imaging in the assessment of malignancies of the mediastinum. World J Radiol. 2019; 11(3):27-45. PMC: 6441936. DOI: 10.4329/wjr.v11.i3.27. View

Conforti F, Pala L, Giaccone G, De Pas T . Thymic epithelial tumors: From biology to treatment. Cancer Treat Rev. 2020; 86:102014. DOI: 10.1016/j.ctrv.2020.102014. View

Ahmad U . The eighth edition TNM stage classification for thymic tumors: What do I need to know?. J Thorac Cardiovasc Surg. 2021; 161(4):1524-1529. DOI: 10.1016/j.jtcvs.2020.10.131. View

Perri F, Pisconti S, Conson M, Pacelli R, Della Vittoria Scarpati G, Gnoni A . Adjuvant treatment in patients at high risk of recurrence of thymoma: efficacy and safety of a three-dimensional conformal radiation therapy regimen. Onco Targets Ther. 2015; 8:1345-9. PMC: 4467740. DOI: 10.2147/OTT.S75232. View

Seki S, Koyama H, Ohno Y, Nishio M, Takenaka D, Maniwa Y . Diffusion-weighted MR imaging vs. multi-detector row CT: Direct comparison of capability for assessment of management needs for anterior mediastinal solitary tumors. Eur J Radiol. 2014; 83(5):835-42. DOI: 10.1016/j.ejrad.2014.01.005. View

Liu H, Gu Z, Qiu B, Detterbeck F, Roden A, Ruffini E . A Recurrence Predictive Model for Thymic Tumors and Its Implication for Postoperative Management: a Chinese Alliance for Research in Thymomas Database Study. J Thorac Oncol. 2019; 15(3):448-456. DOI: 10.1016/j.jtho.2019.10.018. View

Kong L, Zhang W, Zhou Y, Xu H, Shi H, Feng Q . Histogram analysis of apparent diffusion coefficient maps for assessing thymic epithelial tumours: correlation with world health organization classification and clinical staging. Br J Radiol. 2017; 91(1084):20170580. PMC: 5965997. DOI: 10.1259/bjr.20170580. View

Chang C, Lin C, Chu C, Hsiung Y, Chuang M, Tseng Y . Extracellular volume fraction measurement correlates with lymphocyte abundance in thymic epithelial tumors. Cancer Imaging. 2020; 20(1):71. PMC: 7539449. DOI: 10.1186/s40644-020-00349-4. View

10.

Weis C, Yao X, Deng Y, Detterbeck F, Marino M, Nicholson A . The impact of thymoma histotype on prognosis in a worldwide database. J Thorac Oncol. 2015; 10(2):367-72. PMC: 4318643. DOI: 10.1097/JTO.0000000000000393. View

11.

Fliedner F, Engel T, El-Ali H, Hansen A, Kjaer A . Diffusion weighted magnetic resonance imaging (DW-MRI) as a non-invasive, tissue cellularity marker to monitor cancer treatment response. BMC Cancer. 2020; 20(1):134. PMC: 7031987. DOI: 10.1186/s12885-020-6617-x. View

12.

Tomiyama N, Honda O, Tsubamoto M, Inoue A, Sumikawa H, Kuriyama K . Anterior mediastinal tumors: diagnostic accuracy of CT and MRI. Eur J Radiol. 2007; 69(2):280-8. DOI: 10.1016/j.ejrad.2007.10.002. View

13.

Abou Youssef H, Elzorkany M, Hussein S, Taymour T, Abdel Gawad M . Evaluation of mediastinal lymphadenopathy by diffusion weighted MRI; correlation with histopathological results. Adv Respir Med. 2019; 87(3):175-183. DOI: 10.5603/ARM.2019.0033. View

14.

Drevet G, Collaud S, Tronc F, Girard N, Maury J . Optimal management of thymic malignancies: current perspectives. Cancer Manag Res. 2019; 11:6803-6814. PMC: 6660626. DOI: 10.2147/CMAR.S171683. View

15.

Radovich M, Pickering C, Felau I, Ha G, Zhang H, Jo H . The Integrated Genomic Landscape of Thymic Epithelial Tumors. Cancer Cell. 2018; 33(2):244-258.e10. PMC: 5994906. DOI: 10.1016/j.ccell.2018.01.003. View

16.

Kanemura H, Tamura T, Nishimura N, Kobayashi D, Higashi T . Thymic epithelial tumor treatment in Japan: analysis of hospital cancer registry and insurance claims data, 2012-2014. Jpn J Clin Oncol. 2019; 50(3):310-317. PMC: 7061247. DOI: 10.1093/jjco/hyz167. View

17.

Li X, Qu J, Luo J, Li J, Zhang H, Shao N . Effect of intravenous gadolinium-DTPA on diffusion-weighted imaging of brain tumors: a short temporal interval assessment. J Magn Reson Imaging. 2014; 40(3):616-21. DOI: 10.1002/jmri.24386. View

18.

Li B, Xin Y, Xiao G, Li G, Duan S, Han Y . Predicting pathological subtypes and stages of thymic epithelial tumors using DWI: value of combining ADC and texture parameters. Eur Radiol. 2019; 29(10):5330-5340. DOI: 10.1007/s00330-019-06080-4. View

19.

Usuda K, Maeda S, Motono N, Ueno M, Tanaka M, Machida Y . Diffusion Weighted Imaging Can Distinguish Benign from Malignant Mediastinal Tumors and Mass Lesions: Comparison with Positron Emission Tomography. Asian Pac J Cancer Prev. 2015; 16(15):6469-75. DOI: 10.7314/apjcp.2015.16.15.6469. View

20.

Guerrera F, Rendina E, Venuta F, Margaritora S, Ciccone A, Novellis P . Does the World Health Organization histological classification predict outcomes after thymomectomy? Results of a multicentre study on 750 patients. Eur J Cardiothorac Surg. 2014; 48(1):48-54. DOI: 10.1093/ejcts/ezu368. View