Image-based diagnosis of residual or recurrent nasopharyngeal carcinoma may be a phantom tumor phenomenon

被引:4
|
作者
Lee, Ching-Chi [1 ]
Lee, Jih-Chin [1 ]
Huang, Wen-Yen [2 ]
Juan, Chun-Jung [3 ]
Jen, Yee-Min [2 ,4 ]
Lin, Li-Fan [5 ]
机构
[1] Triserv Gen Hosp, Natl Def Med Ctr, Dept Otolaryngol Head & Neck Surg, 323 Sect 2 Cheng Kong Rd, Taipei, Taiwan
[2] Triserv Gen Hosp, Natl Def Med Ctr, Dept Radiat Oncol, 323 Sect 2 Cheng Kong Rd, Taipei, Taiwan
[3] Triserv Gen Hosp, Natl Def Med Ctr, Dept Radiol, 323 Sect 2 Cheng Kong Rd, Taipei, Taiwan
[4] Yee Zen Gen Hosp, Radiat Oncol Dept, Yangmei, Taiwan
[5] Triserv Gen Hosp, Dept Nucl Med, Natl Def Med Ctr, Taipei, Taiwan
关键词
evaluation of treatment response; image diagnosis; nasopharyngeal cancer; phantom tumor; recurrence or residual tumor; reirradiation; BARR-VIRUS DNA; RADIATION-THERAPY; SOLID TUMORS; EBV DNA; SALVAGE; PET/CT;
D O I
10.1097/MD.0000000000024555
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Some nasopharyngeal carcinoma (NPC) patients may present convincing radiological evidence mimicking residual or recurrent tumor after radiotherapy. However, by means of biopsies and long term follow-up, the radiologically diagnosed residuals/recurrences are not always what they appear to be. We report our experience on this "phantom tumor" phenomenon. This may help to avoid the unnecessary and devastating re-irradiation subsequent to the incorrect diagnosis. In this longitudinal cohort study, we collected 19 patients of image-based diagnosis of residual/recurrent NPC during the period from Feb, 2010 to Nov. 2016, and then observed them until June, 2019. They were subsequently confirmed to have no residual/recurrent lesions by histological or clinical measures. Image findings and pathological features were analyzed. Six patients showed residual tumors after completion of radiotherapy and 13 were radiologically diagnosed to have recurrences based on magnetic resonance imaging (MRI) criteria 6 to 206 months after radiotherapy. There were 3 types of image patterns: extensive recurrent skull base lesions (10/19); a persistent or residual primary lesion (3/19); lesions both in the nasopharynx and skull base (6/19). Fourteen patients had biopsy of the lesions. The histological diagnoses included necrosis/ inflammation in 10 (52.7%), granulation tissue with inflammation in 2, and reactive epithelial cell in 1. Five patients had no pathological proof and were judged to have no real recurrence/residual tumor based on the absence of detectable plasma EB virus DNA and subjective judgment. These 5 patients have remained well after an interval of 38-121 months without anti-cancer treatments. Image-based diagnosis of residual or recurrent nasopharyngeal carcinoma may be unreliable. False positivity, the "phantom tumor phenomenon", is not uncommon in post-radiotherapy MRI. This is particularly true if the images show extensive skull base involvement at 5 years or more after completion of radiotherapy. MRI findings compatible with NPC features must be treated as a real threat until proved otherwise. However, the balance between under- and over-diagnosis must be carefully sought. Without a pathological confirmation, the diagnosis of residual or recurrent NPC must be made taking into account physical examination results, endoscopic findings and Epstein-Barr virus viral load. A subjective medical judgment is needed based on clinical and laboratory data and the unique anatomic complexities of the nasopharynx.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] Meta-analysis of 18F-FDG PET/CT for diagnosis of residual/recurrent nasopharyngeal carcinoma after radiotherapy
    Zhou, H.
    Zhou, Y.
    Li, L.
    EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2015, 42 : S606 - S607
  • [22] Three-dimensional small-volume irradiation for residual or recurrent nasopharyngeal carcinoma
    Nishioka, T
    Shirato, H
    Kagei, K
    Fukuda, S
    Hashimoto, S
    Ohmori, K
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2000, 48 (02): : 495 - 500
  • [23] A nomogram based on tumor response to induction chemotherapy may predict survival in locoregionally advanced nasopharyngeal carcinoma
    Jiang, Yu-Ting
    Chen, Kai-Hua
    Liang, Zhong-Guo
    Yang, Jie
    Wei, Si-Qi
    Qu, Song
    Li, Ling
    Zhu, Xiao-Dong
    HEAD AND NECK-JOURNAL FOR THE SCIENCES AND SPECIALTIES OF THE HEAD AND NECK, 2022, 44 (06): : 1301 - 1312
  • [24] Image-based surgical risk factors for Wilms tumor
    Takaharu Oue
    Akihiro Yoneda
    Noriaki Usui
    Takashi Sasaki
    Masahiro Zenitani
    Natsumi Tanaka
    Shuichiro Uehara
    Soji Ibuka
    Yuichi Takama
    Hiroomi Okuyama
    Pediatric Surgery International, 2018, 34 : 29 - 34
  • [25] A Generative Approach for Image-Based Modeling of Tumor Growth
    Menze, Bjoern H.
    Van Leemput, Koen
    Honkela, Antti
    Konukoglu, Ender
    Weber, Marc-Andre
    Ayache, Nicholas
    Golland, Polina
    INFORMATION PROCESSING IN MEDICAL IMAGING, 2011, 6801 : 735 - 747
  • [26] Image-based Pediatric Skeletal Dosimetry for the UF Hybrid Computational Phantom Series
    Pafundi, D. H.
    Lee, C.
    Lodwick, D. L.
    Shahlaee, A. H.
    EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2008, 35 : S135 - S135
  • [27] Image-based speckle tracking for tissue motion characterization in a deformable cardiovascular phantom
    Chan, R.
    Manzke, R.
    Dalal, S.
    Stanton, D.
    Chang, P.
    Settlemier, S.
    Salgo, I.
    Tournoux, F.
    MEDICAL IMAGING 2008: ULTRASONIC IMAGING AND SIGNAL PROCESSING, 2008, 6920
  • [28] Image-based surgical risk factors for Wilms tumor
    Oue, Takaharu
    Yoneda, Akihiro
    Usui, Noriaki
    Sasaki, Takashi
    Zenitani, Masahiro
    Tanaka, Natsumi
    Uehara, Shuichiro
    Ibuka, Soji
    Takama, Yuichi
    Okuyama, Hiroomi
    PEDIATRIC SURGERY INTERNATIONAL, 2018, 34 (01) : 29 - 34
  • [29] Image-Based Cardiac Diagnosis With Machine Learning: A Review
    Martin-Isla, Carlos
    Campello, Victor M.
    Izquierdo, Cristian
    Raisi-Estabragh, Zahra
    Baessler, Bettina
    Petersen, Steffen E.
    Lekadir, Karim
    FRONTIERS IN CARDIOVASCULAR MEDICINE, 2020, 7
  • [30] Deep Learning for Medical Image-Based Cancer Diagnosis
    Jiang, Xiaoyan
    Hu, Zuojin
    Wang, Shuihua
    Zhang, Yudong
    CANCERS, 2023, 15 (14)