Stratification of Anatomical Imaging Features Between High-Risk and Non-High-Risk Groups in Neuroblastoma

被引:0
|
作者
Wang, Haoru [1 ]
Chen, Xin [1 ]
He, Ling [1 ]
Cai, Jinhua [1 ]
机构
[1] Chongqing Med Univ, Natl Clin Res Ctr Child Hlth & Disorders, Dept Radiol,Childrens Hosp,Chongqing Key Lab Child, Minist Educ Key Lab Child Dev & Disorders, 136 Zhongshan Rd 2, Chongqing 400014, Peoples R China
关键词
children; computed tomography; image-defined risk factors; magnetic resonance imaging; neuroblastoma; CLASSIFICATION-SYSTEM; SINGLE;
D O I
10.1177/10732748251315883
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: This study compared anatomical imaging features between high-risk and non-high-risk groups in neuroblastoma with at least one image-defined risk factor (IDRF). It also assessed the diagnostic performance of these features in identifying the high-risk group. Methods: A retrospective analysis of neuroblastoma patients with at least one IDRF was conducted. Imaging features, including estimated tumor volume and IDRFs, were compared between the two groups. The diagnostic performance of these features was assessed using receiver operating characteristic (ROC) curves, and the areas under the ROC curves (AUCs) along with their 95% confidence intervals (CIs) were calculated. Additionally, to internally validate their diagnostic performance, the bootstrap resampling method with 1000 bootstrap resamples was employed. Results: The study included 255 patients (185 high-risk cases, 70 non-high-risk cases). Significant differences were found in estimated tumor volume and IDRF number between the high-risk and non-high-risk groups (P < 0.001). The estimated tumor volume and the IDRF number-based cluster were independent risk factors, and their combination achieved an AUC of 0.801 (95% CI: 0.747-0.848) for high-risk group diagnosis, with the average AUC of the 1000 bootstrap samples of 0.800 (95% CI: 0.798-0.802). In abdominal lesions, specific IDRF categories differed between high-risk and non-high-risk groups (P < 0.05). Conclusion: Our study reveals anatomical imaging differences between high-risk and non-high-risk groups in neuroblastoma with at least one IDRF.
引用
收藏
页数:12
相关论文
共 50 条
  • [31] Dinutuximab: A Review in High-Risk Neuroblastoma
    Sheridan M. Hoy
    Targeted Oncology, 2016, 11 : 247 - 253
  • [32] Retinoid therapy of high-risk neuroblastoma
    Reynolds, CP
    Matthay, KK
    Villablanca, JG
    Maurer, BJ
    CANCER LETTERS, 2003, 197 (1-2) : 185 - 192
  • [33] Influence of Sarcopenia in High-risk Neuroblastoma
    Kawakubo, Naonori
    Souzaki, Ryota
    Koga, Yuuki
    Kinoshita, Yoshiaki
    Ohga, Shouichi
    Taguchi, Tomoaki
    PEDIATRIC BLOOD & CANCER, 2017, 64 : S43 - S43
  • [34] The transcriptome landscape of high-risk neuroblastoma
    Wei, Jun S.
    Zhang, Shile
    Song, Young K.
    Asgharzadeh, Shahab
    Sindiri, Sivasish
    Wen, Xinyu
    Patidar, Rajesh
    Auvil, Jaime M. Guidry
    Gerhard, Daniela S.
    Seeger, Robert
    Maris, John M.
    Khan, Javed
    CANCER RESEARCH, 2016, 76
  • [35] High-Risk Neuroblastoma: A Surgical Perspective
    Jacobson, Jillian C.
    Clark, Rachael A.
    Chung, Dai H.
    CHILDREN-BASEL, 2023, 10 (02):
  • [36] Mouse models of high-risk neuroblastoma
    Alvin Kamili
    Caroline Atkinson
    Toby N. Trahair
    Jamie I. Fletcher
    Cancer and Metastasis Reviews, 2020, 39 : 261 - 274
  • [37] HIGH-RISK NEUROBLASTOMA: A Therapy in Evolution
    Fong, Abraham
    Park, Julie R.
    PEDIATRIC HEMATOLOGY AND ONCOLOGY, 2009, 26 (08) : 539 - 548
  • [38] Mouse models of high-risk neuroblastoma
    Kamili, Alvin
    Atkinson, Caroline
    Trahair, Toby N.
    Fletcher, Jamie I.
    CANCER AND METASTASIS REVIEWS, 2020, 39 (01) : 261 - 274
  • [39] High-Risk Neuroblastoma Treatment Review
    Smith, Valeria
    Foster, Jennifer
    CHILDREN-BASEL, 2018, 5 (09):
  • [40] The genetic landscape of high-risk neuroblastoma
    Trevor J Pugh
    Olena Morozova
    Edward F Attiyeh
    Shahab Asgharzadeh
    Jun S Wei
    Daniel Auclair
    Scott L Carter
    Kristian Cibulskis
    Megan Hanna
    Adam Kiezun
    Jaegil Kim
    Michael S Lawrence
    Lee Lichenstein
    Aaron McKenna
    Chandra Sekhar Pedamallu
    Alex H Ramos
    Erica Shefler
    Andrey Sivachenko
    Carrie Sougnez
    Chip Stewart
    Adrian Ally
    Inanc Birol
    Readman Chiu
    Richard D Corbett
    Martin Hirst
    Shaun D Jackman
    Baljit Kamoh
    Alireza Hadj Khodabakshi
    Martin Krzywinski
    Allan Lo
    Richard A Moore
    Karen L Mungall
    Jenny Qian
    Angela Tam
    Nina Thiessen
    Yongjun Zhao
    Kristina A Cole
    Maura Diamond
    Sharon J Diskin
    Yael P Mosse
    Andrew C Wood
    Lingyun Ji
    Richard Sposto
    Thomas Badgett
    Wendy B London
    Yvonne Moyer
    Julie M Gastier-Foster
    Malcolm A Smith
    Jaime M Guidry Auvil
    Daniela S Gerhard
    Nature Genetics, 2013, 45 : 279 - 284