Abstract
Background
Accurately quantifying event-free survival after induction of remission in high-risk neuroblastoma can lead to better subsequent treatment decisions, including whether more aggressive therapy or milder treatment is needed to reduce unnecessary treatment side effects, thereby improving patient survival.
Objective
To develop and validate a 123I-metaiodobenzylguanidine (MIBG) single-photon emission computed tomography-computed tomography (SPECT-CT)-based radiomics nomogram and evaluate its value in predicting event-free survival after induction of remission in high-risk neuroblastoma.
Materials and methods
One hundred and seventy-two patients with high-risk neuroblastoma who underwent an 123I-MIBG SPECT-CT examination were retrospectively reviewed. Eighty-seven patients with high-risk neuroblastoma met the final inclusion and exclusion criteria and were randomized into training and validation cohorts in a 7:3 ratio. The SPECT-CT images of patients were visually analyzed to assess the Curie score. The 3D Slicer software tool was used to outline the region of interest of the lumbar 3–5 vertebral bodies on the SPECT-CT images. Radiomics features were extracted and screened, and a radiomics model was constructed with the selected radiomics features. Univariate and multivariate Cox regression analyses were used to determine clinical risk factors and construct the clinical model. The radiomics nomogram was constructed using multivariate Cox regression analysis by incorporating radiomics features and clinical risk factors. C-index and time-dependent receiver operating characteristic curves were used to evaluate the performance of the different models.
Results
The Curie score had the lowest efficacy for the assessment of event-free survival, with a C-index of 0.576 and 0.553 in the training and validation cohorts, respectively. The radiomics model, constructed from 11 radiomics features, outperformed the clinical model in predicting event-free survival in both the training cohort (C-index, 0.780 vs. 0.653) and validation cohort (C-index, 0.687 vs. 0.667). The nomogram predicted the best prognosis for event-free survival in both the training and validation cohorts, with C-indices of 0.819 and 0.712, and 1-year areas under the curve of 0.899 and 0.748, respectively.
Conclusion
123I-MIBG SPECT-CT-based radiomics can accurately predict the event-free survival of high-risk neuroblastoma after induction of remission The constructed nomogram may enable an individualized assessment of high-risk neuroblastoma prognosis and assist clinicians in optimizing patient treatment and follow-up plans, thereby potentially improving patient survival.
Graphical abstract
Similar content being viewed by others
Data availability
The datasets analyzed during the current study are available from the corresponding author on reasonable request.
References
Maris JM (2010) Recent advances in neuroblastoma. N Engl J Med 362:2202–2211
Maris JM, Hogarty MD, Bagatell R, Cohn SL (2007) Neuroblastoma Lancet 369:2106–2120
Pinto NR, Applebaum MA, Volchenboum SL, Matthay KK, London WB, Ambros PF, Nakagawara A, Berthold F, Schleiermacher G, Park JR, Valteau-Couanet D, Pearson AD, Cohn SL (2015) Advances in risk classification and treatment strategies for Neuroblastoma. J Clin Oncol 33:3008–3017
Monclair T, Brodeur GM, Ambros PF, Brisse HJ, Cecchetto G, Holmes K, Kaneko M, London WB, Matthay KK, Nuchtern JG, von Schweinitz D, Simon T, Cohn SL, Pearson AD, Force IT (2009) The International Neuroblastoma Risk Group (INRG) staging system: an INRG Task Force report. J Clin Oncol 27:298–303
Feng L, Lu X, Yang X, Kan Y, Sun D, Wang W, Yang J (2022) An 18F-FDG PET/CT radiomics nomogram for differentiation of high-risk and non-high-risk patients of the International Neuroblastoma Risk Group Staging System. Eur J Radiol 154:110444
Sato T, Hara K, Ohba G, Yamamoto H, Iguchi A (2021) Long-term survival of two patients with recurrent high-risk neuroblastoma. Pediatr Int 63:849–851
Bender HG, Irwin MS, Hogarty MD, Castleberry R, Maris JM, Kao PC, Zhang FF, Naranjo A, Cohn SL, London WB (2023) Survival of patients with Neuroblastoma after assignment to reduced therapy because of the 12- to 18-month change in age cutoff in children’s oncology group risk stratification. J Clin Oncol 41:3149–3159
Sun Q, Chen Y, Jin Q, Yuan X (2022) A nomogram for predicting recurrence-free survival of intermediate and high-risk neuroblastoma. Eur J Pediatr 181:4135–4147
Vallabhajosula S, Nikolopoulou A (2011) Radioiodinated metaiodobenzylguanidine (MIBG): radiochemistry, biology, and pharmacology. Semin Nucl Med 41:324–333
Olivier P, Colarinha P, Fettich J, Fischer S, Frökier J, Giammarile F, Gordon I, Hahn K, Kabasakal L, Mann M, Mitjavila M, Piepsz A, Porn U, Sixt R, van Velzen J (2003) Guidelines for radioiodinated MIBG scintigraphy in children. Eur J Nucl Med Mol Imaging 30:B45–50
Jacobson AF, Deng H, Lombard J, Lessig HJ, Black RR (2010) 123I-meta-iodobenzylguanidine scintigraphy for the detection of neuroblastoma and pheochromocytoma: results of a meta-analysis. J Clin Endocrinol Metab 95:2596–2606
Kiratli PO, Tuncel M, Bar-Sever Z (2016) Nuclear medicine in pediatric and adolescent tumors. Semin Nucl Med 46:308–323
Brisse HJ, McCarville MB, Granata C, Krug KB, Wootton-Gorges SL, Kanegawa K, Giammarile F, Schmidt M, Shulkin BL, Matthay KK, Lewington VJ, Sarnacki S, Hero B, Kaneko M, London WB, Pearson AD, Cohn SL, Monclair T (2011) Guidelines for imaging and staging of neuroblastic tumors: consensus report from the International Neuroblastoma Risk Group Project. Radiology 261:243–257
Biassoni L, Privitera L (2021) ) 123I-Meta-iodobenzylguanidine single-photon emission computerized tomography/computerized tomography scintigraphy in the management of neuroblastoma. Indian J Nucl Med 36:293–299
Feng L, Li S, Wang C, Yang J (2023) Current status and future perspective on molecular imaging and treatment of neuroblastoma. Semin Nucl Med 53:517–529
Wu Q, Yuan C, Liu N, Shu J, Wang J, Qian J, Zeng L, Zhang H, Wang X, Mei W (2022) Fast detection, a precise and sensitive diagnostic agent for breast cancer. J Exp Clin Cancer Res 41:201
Yanik GA, Parisi MT, Shulkin BL, Naranjo A, Kreissman SG, London WB, Villablanca JG, Maris JM, Park JR, Cohn SL, McGrady P, Matthay KK (2013) Semiquantitative mIBG scoring as a prognostic indicator in patients with stage 4 neuroblastoma: a report from the children’s oncology group. J Nucl Med 54:541–548
Betancur J, Otaki Y, Motwani M, Fish MB, Lemley M, Dey D, Gransar H, Tamarappoo B, Germano G, Sharir T, Berman DS, Slomka PJ (2018) Prognostic value of combined clinical and myocardial perfusion imaging data using machine learning. JACC-Cardiovascular Imaging 11:1000–1009
Chidambaram S, Sounderajah V, Maynard N, Markar SR (2022) Diagnostic performance of artificial intelligence-centred systems in the diagnosis and postoperative surveillance of upper gastrointestinal malignancies using computed tomography imaging: a systematic review and Meta-analysis of diagnostic accuracy. Ann Surg Oncol 29:1977–1990
Feng L, Qian L, Yang S, Ren Q, Zhang S, Qin H, Wang W, Wang C, Zhang H, Yang J (2022) Clinical parameters combined with radiomics features of PET/CT can predict recurrence in patients with high-risk pediatric neuroblastoma. BMC Med Imaging 22:102
Feng L, Zhang S, Wang C, Li S, Kan Y, Wang C, Zhang H, Wang W, Yang J (2023) Axial skeleton radiomics of 18F-FDG PET/CT: impact on event-free survival prediction in high-risk pediatric neuroblastoma. Acad Radiol 30:2487–2496
Feng L, Yang X, Lu X, Kan Y, Wang C, Sun D, Zhang H, Wang W, Yang J (2022) ) 18F-FDG PET/CT-based radiomics nomogram could predict bone marrow involvement in pediatric neuroblastoma. Insights Imaging 13:144
Feng L, Qian L, Yang S, Ren Q, Zhang S, Qin H, Wang W, Wang C, Zhang H, Yang J (2022) Prediction for mitosis-karyorrhexis index status of pediatric neuroblastoma via machine learning based 18F-FDG PET/CT radiomics. Diagnostics (Basel) 12
Feng L, Yang X, Lu X, Kan Y, Wang C, Zhang H, Wang W, Yang J (2022) Diagnostic value of 18F-FDG PET/CT-based radiomics nomogram in bone marrow involvement of pediatric neuroblastoma. Acad Radiol 30:940–951
Chen Q, Pan T, Wang YN, Schoepf UJ, Bidwell SL, Qiao H, Feng Y, Xu C, Xu H, Xie G, Gao X, Tao XW, Lu M, Xu PP, Zhong J, Wei Y, Yin X, Zhang J, Zhang LJ (2023) A coronary CT angiography Radiomics model to identify vulnerable plaque and predict cardiovascular events. Radiology 307:e221693
Mattonen SA, Davidzon GA, Benson J, Leung ANC, Vasanawala M, Horng G, Shrager JB, Napel S, Nair VS (2019) Bone marrow and tumor radiomics at 18F-FDG PET/CT: impact on outcome prediction in non-small cell lung cancer. Radiology 293:451–459
Park JR, Kreissman SG, London WB, Naranjo A, Cohn SL, Hogarty MD, Tenney SC, Haas-Kogan D, Shaw PJ, Kraveka JM, Roberts SS, Geiger JD, Doski JJ, Voss SD, Maris JM, Grupp SA, Diller L (2019) Effect of tandem autologous stem cell transplant vs single transplant on event-free survival in patients with high-risk neuroblastoma: a randomized clinical trial. JAMA 322:746–755
Stauss J, Franzius C, Pfluger T, Juergens KU, Biassoni L, Begent J, Kluge R, Amthauer H, Voelker T, Højgaard L, Barrington S, Hain S, Lynch T, Hahn K (2008) Guidelines for 18F-FDG PET and PET-CT imaging in paediatric oncology. Eur J Nucl Med Mol Imaging 35:1581–1588
Boellaard R, Delgado-Bolton R, Oyen WJ, Giammarile F, Tatsch K, Eschner W, Verzijlbergen FJ, Barrington SF, Pike LC, Weber WA, Stroobants S, Delbeke D, Donohoe KJ, Holbrook S, Graham MM, Testanera G, Hoekstra OS, Zijlstra J, Visser E, Hoekstra CJ, Pruim J, Willemsen A, Arends B, Kotzerke J, Bockisch A, Beyer T, Chiti A, Krause BJ (2015) FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0. Eur J Nucl Med Mol Imaging 42:328–354
Zhou Z, Wang G, Qian L, Liu J, Yang X, Zhang S, Zhang M, Kan Y, Wang W, Yang J (2023) Evaluation of iodine-123-labeled metaiodobenzylguanidine single-photon emission computed tomography/computed tomography based on the International Society of Pediatric Oncology Europe Neuroblastoma score in children with neuroblastoma. Quant Imag Med Surg 13:3841–3851
Liu B, Servaes S, Zhuang H (2018) SPECT/CT MIBG imaging is crucial in the follow-up of the patients with high-risk neuroblastoma. Clin Nucl Med 43:232–238
Matthay KK, Edeline V, Lumbroso J, Tanguy ML, Asselain B, Zucker JM, Valteau-Couanet D, Hartmann O, Michon J (2003) Correlation of early metastatic response by 123I-metaiodobenzylguanidine scintigraphy with overall response and event-free survival in stage IV neuroblastoma. J Clin Oncol 21:2486–2491
Naranjo A, Parisi MT, Shulkin BL, London WB, Matthay KK, Kreissman SG, Yanik GA (2011) Comparison of ¹²³I-metaiodobenzylguanidine (MIBG) and ¹³¹I-MIBG semi-quantitative scores in predicting survival in patients with stage 4 neuroblastoma: a report from the Children’s Oncology Group. Pediatr Blood Cancer 56:1041–1045
Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin JC, Pujol S, Bauer C, Jennings D, Fennessy F, Sonka M, Buatti J, Aylward S, Miller JV, Pieper S, Kikinis R (2012) 3D slicer as an image computing platform for the quantitative Imaging Network. Magn Reson Imaging 30:1323–1341
Liu J, Li C, Yang X, Lu X, Zhang M, Qian L, Wang W, Kan Y, Yang J (2022) The Diagnostic Value of 18F-FDG PET/CT Bone Marrow Uptake Pattern in Detecting Bone Marrow Involvement in Pediatric Neuroblastoma Patients. Contrast Media Mol Imaging 2022:7556315
Zhou HF, Han YQ, Lu J, Wei JW, Guo JH, Zhu HD, Huang M, Ji JS, Lv WF, Chen L, Zhu GY, Jin ZC, Tian J, Teng GJ (2019) Radiomics facilitates candidate selection for Irradiation stents among patients with unresectable pancreatic Cancer. Front Oncol 9:973
Zhang X, Chen L, Jiang H, He X, Feng L, Ni M, Ma M, Wang J, Zhang T, Wu S, Zhou R, Jin C, Zhang K, Qian W, Chen Z, Zhuo C, Zhang H, Tian M (2022) A novel analytic approach for outcome prediction in diffuse large B-cell lymphoma by [18F]FDG PET/CT. Eur J Nucl Med Mol Imaging 49:1298–1310
van Griethuysen JJM, Fedorov A, Parmar C, Hosny A, Aucoin N, Narayan V, Beets-Tan RGH, Fillion-Robin JC, Pieper S, Aerts H (2017) Computational radiomics system to decode the radiographic phenotype. Cancer Res 77:e104–e107
De Preter K, Mestdagh P, Vermeulen J, Zeka F, Naranjo A, Bray I, Castel V, Chen C, Drozynska E, Eggert A, Hogarty MD, Izycka-Swieszewska E, London WB, Noguera R, Piqueras M, Bryan K, Schowe B, van Sluis P, Molenaar JJ, Schramm A, Schulte JH, Stallings RL, Versteeg R, Laureys G, Van Roy N, Speleman F, Vandesompele J (2011) miRNA expression profiling enables risk stratification in archived and fresh neuroblastoma tumor samples. Clin Cancer Res 17:7684–7692
Vik TA, Pfluger T, Kadota R, Castel V, Tulchinsky M, Farto JC, Heiba S, Serafini A, Tumeh S, Khutoryansky N, Jacobson AF (2009) 123I-mIBG scintigraphy in patients with known or suspected neuroblastoma: results from a prospective multicenter trial. Pediatr Blood Cancer 52:784–790
Liu Y, Chang Y, Zha X, Bao J, Wu Q, Dai H, Hu C (2022) A combination of radiomic features, imaging characteristics, and serum tumor biomarkers to predict the possibility of the high-grade subtypes of lung adenocarcinoma. Acad Radiol 29:1792–1801
Chen QL, Li MM, Xue T, Peng H, Shi J, Li YY, Duan SF, Feng F (2023) Radiomics nomogram integrating intratumoural and peritumoural features to predict lymph node metastasis and prognosis in clinical stage IA non-small cell lung cancer: a two-centre study. Clin Radiol 78:e359–e367
Chu F, Liu Y, Liu Q, Li W, Jia Z, Wang C, Wang Z, Lu S, Li P, Zhang Y, Liao Y, Xu M, Yao X, Wang S, Liu C, Zhang H, Wang S, Yan X, Kamel IR, Sun H, Yang G, Zhang Y, Qu J (2022) Development and validation of MRI-based radiomics signatures models for prediction of disease-free survival and overall survival in patients with esophageal squamous cell carcinoma. Eur Radiol 32:5930–5942
Ren C, Zhang J, Qi M, Zhang J, Zhang Y, Song S, Sun Y, Cheng J (2021) Machine learning based on clinico-biological features integrated 18F-FDG PET/CT radiomics for distinguishing squamous cell carcinoma from adenocarcinoma of lung. Eur J Nucl Med Mol Imaging 48:1538–1549
Jiang Y, Chen C, Xie J, Wang W, Zha X, Lv W, Chen H, Hu Y, Li T, Yu J, Zhou Z, Xu Y, Li G (2018) Radiomics signature of computed tomography imaging for prediction of survival and chemotherapeutic benefits in gastric cancer. EBioMedicine 36:171–182
Simon T, Hero B, Hunneman DH, Berthold F (2003) Tumour markers are poor predictors for relapse or progression in neuroblastoma. Eur J Cancer 39:1899–1903
Li J, Liu X, Chen M, Wang J, Wang X (2021) Values of serum CA125, NSE and 24-hour urine VMA in diagnosis and prediction of treatment of paediatric neuroblastoma. Int J Clin Pract 75:e14932
Fiz F, Masci C, Costa G, Sollini M, Chiti A, Ieva F, Torzilli G, Vigano L (2022) PET/CT-based radiomics of mass-forming intrahepatic cholangiocarcinoma improves prediction of pathology data and survival. Eur J Nucl Med Mol Imaging 49:3387–3400
London WB, Castel V, Monclair T, Ambros PF, Pearson AD, Cohn SL, Berthold F, Nakagawara A, Ladenstein RL, Iehara T, Matthay KK (2011) Clinical and biologic features predictive of survival after relapse of neuroblastoma: a report from the International Neuroblastoma Risk Group project. J Clin Oncol 29:3286–3292
Acknowledgements
The authors thank the staff of the Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China, for their selfless and valuable assistance.
Funding
This work was supported by the National Natural Science Foundation of China (No. 82102088 and 82272034).
Author information
Authors and Affiliations
Contributions
Conceptualization: L.F. and J.Y.; data curation: L.F. and X.Y.; formal analysis: C.W. and W.W.; funding acquisition: W.W. and J.Y.; investigation: X.Y. and C.W.; methodology: L.F., C.W., and H.Z.; project administration: J.Y.; resources: W.W. and J.Y.; software: C.W. and H.Z.; supervision: J.Y.; validation: L.F., X.Y., C.W., and W.W.; visualization: L.F., H.Z., W.W., and J.Y.; writing—original draft preparation: L.F., X.Y., C.W., H.Z., W.W., and J.Y.; writing—review and editing: L.F., X.Y., C.W., H.Z., W.W., and J.Y. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Ethical approval
All procedures performed in the study were in accordance with the principles of the 1964 Declaration of Helsinki and its later amendments. This study was approved by the Institutional Review Board.
Informed consent
The requirement to obtain informed consent was waived by the Institutional Review Board due to the use of retrospective anonymized data.
Conflicts of interest
None
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Feng, L., Yang, X., Wang, C. et al. Predicting event-free survival after induction of remission in high-risk pediatric neuroblastoma: combining 123I-MIBG SPECT-CT radiomics and clinical factors. Pediatr Radiol 54, 805–819 (2024). https://doi.org/10.1007/s00247-024-05901-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00247-024-05901-z