- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Annual Issues
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Abstract and Applied Analysis
Volume 2013 (2013), Article ID 341346, 5 pages
On Analytical Methods in Neuroblastoma Detection
1Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
2Hospital La Fe, Bulevar Sur s/n, 46026 Valencia, Spain
Received 11 September 2013; Accepted 7 October 2013
Academic Editor: Constantin Udriste
Copyright © 2013 R. Martínez-Díaz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- J. Foo and K. Leder, “Dynamics of cancer recurrence,” Annals of Applied Probability, vol. 23, no. 4, pp. 1437–1468, 2013.
- N. Bellomo and M. Delitala, “From the mathematical kinetic, and stochastic game theory to modelling mutations, onset, progression and immune competition of cancer cells,” Physics of Life Reviews, vol. 5, no. 4, pp. 183–206, 2008.
- C. Bianca and M. Delitala, “On the modelling of genetic mutations and immune system competition,” Computers & Mathematics with Applications, vol. 61, no. 9, pp. 2362–2375, 2011.
- C. Bianca and M. Pennisi, “Immune systems modelling by top-down and bottom-up approaches,” International Mathematical Forum, vol. 7, no. 3, pp. 109–128, 2012.
- C. Cattani and A. Ciancio, “Separable transition density in the hybrid model for tumor-immune system competition,” Computational and Mathematical Methods in Medicine, vol. 2012, Article ID 610124, 6 pages, 2012.
- C. Cattani, A. Ciancio, and A. d'Onofrio, “Metamodeling the learning-hiding competition between tumours and the immune system: a kinematic approach,” Mathematical and Computer Modelling, vol. 52, no. 1-2, pp. 62–69, 2010.
- W. P. Mueller, E. Coppenrath, and T. P. Uger, “Nuclear medicine and multimodality imaging of pediatric neuroblastoma,” Pediatric Radiology, vol. 43, no. 4, pp. 418–427, 2013.
- S. E. Sharp, M. T. Parisi, M. J. Gelfand, G. A. Yanik, and B. L. Shulkin, “Functionalmetabolic imaging of neuroblastoma,” Quarterly Journal of Nuclear Medicine and Molecular Imaging, vol. 57, pp. 6–20, 2013.
- M. Nakajo, B. Shapiro, and J. Copp, “The normal and abnormal distribution of the adrenomedullary imaging agent m-[i-131]iodobenzylguanidine (i-131 mibg) in man: evaluation by scintigraphy,” Journal of Nuclear Medicine, vol. 24, no. 8, pp. 672–682, 1983.
- E. Bombardieri, F. Giammarile, C. Aktolun et al., “131i/123i-Metaiodobenzylguanidine (mibg) scintigraphy: procedure guidelines for tumour imaging,” European Journal of Nuclear Medicine and Molecular Imaging, vol. 37, no. 12, pp. 2436–2446, 2010.
- K. K. Matthay, B. Shulkin, R. Ladenstein et al., “Criteria for evaluation of disease extent by 123i-metaiodobenzylguanidine scans in neuroblastoma: a report for the International neuroblastoma risk group (inrg) task force,” British Journal of Cancer, vol. 102, no. 9, pp. 1319–1326, 2010.
- M. N. Maisey, T. K. Natarajan, P. J. Hurley, and H. N. Wagner Jr., “Validation of a rapid computerized method of measuring 99mTc pertechnetate uptake for routine assessment of thyroid structure and function,” Journal of Clinical Endocrinology and Metabolism, vol. 36, no. 2, pp. 317–322, 1973.
- W. Chen, Q. Cao, and V. Dilsizian, “Variation of heart-to-mediastinal ratio in123I-miBG cardiac sympathetic imaging: its affecting factors and potential corrections,” Current Cardiology Reports, vol. 13, no. 2, pp. 132–137, 2011.