Computational and Mathematical Methods in Medicine

Predictive Models of Tumour Response to Treatment Using Functional Imaging Techniques


Publishing date
21 Nov 2014
Status
Published
Submission deadline
25 Jul 2014

1Faculty of Science, University of Oradea, 410087 Romania; School of Chemistry and Physics, University of Adelaide, North Terrace, Adelaide, SA 5000, Australia

2Department of Medical Physics, Royal Adelaide Hospital; School of Chemistry and Physics, University of Adelaide, North Terrace, Adelaide, SA 5000, Australia

3Medical Radiation Physics Division, Stockholm University and Karolinska Institutet, Stockholm, Sweden

4Department of Medical and Health Sciences, Radiation Physics, Linköping University, 581 85 Linköping, Sweden


Predictive Models of Tumour Response to Treatment Using Functional Imaging Techniques

Description

Together with technological and radiobiological advances, tumour modelling is a fast developing area of oncology which plays a key role in predicting treatment outcome in cancer patients. Despite the complexity of tumour biology and its microenvironment, computational and mathematical models of virtual cancer behaviour and response to treatment are successfully developed and employed for clinical research. For accurate tumour models, more in-depth metabolic information is needed which can be offered by various diagnostic methods.

Latest technical and molecular developments in the field of nuclear medicine offer new possibilities in functional imaging, overcoming some of the confines imposed by previous diagnostic techniques. Positron emission tomography (PET) is the most advanced technology designed to provide metabolic information of disease, treatment monitoring, and also evaluation of treatment outcome. Together with other quantitative imaging techniques, such as dynamic contrast-enhanced MRI, PET is a promising diagnostic tool assisting in patient stratification for specific therapies, evaluation of drug efficacy, assessment of chemo- and radiotherapy outcome, and prediction of survival.

The aim of the current special issue of Computational and Mathematical Methods in Medicine is to bring together articles on various aspects of tumour modelling focusing on treatment response and prediction of clinical outcome based on functional imaging techniques. Potential topics include, but are not limited to:

  • Modelling of tumour response to treatment using image guidance
  • Dose painting and treatment adaptation using functional image guidance
  • Modelling hypoxia and angiogenesis using functional imaging techniques
  • Evaluation of drug efficacy with a tumour modelling approach
  • PET/MR-determined tumour resistance to chemo- and radiotherapy
  • Modelling of response to treatment modifiers
  • Novel PET radiotracers and treatment prediction
  • Individualised treatment planning models
  • Evaluation and modelling of targeted therapies and radioisotope uptake based on imaging information

Before submission authors should carefully read over the journal’s Author Guidelines, which are located at http://www.hindawi.com/journals/cmmm/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/cmmm/premu/ according to the following timetable:


Articles

  • Special Issue
  • - Volume 2015
  • - Article ID 571351
  • - Editorial

Predictive Models of Tumour Response to Treatment Using Functional Imaging Techniques

Loredana G. Marcu | Eva Bezak | ... | Alexandru Dasu
  • Special Issue
  • - Volume 2015
  • - Article ID 934380
  • - Review Article

Towards Multidimensional Radiotherapy: Key Challenges for Treatment Individualisation

Iuliana Toma-Dasu | Alexandru Dasu
  • Special Issue
  • - Volume 2015
  • - Article ID 415923
  • - Review Article

PET-Specific Parameters and Radiotracers in Theoretical Tumour Modelling

Matthew Jennings | Loredana G. Marcu | Eva Bezak
  • Special Issue
  • - Volume 2015
  • - Article ID 103843
  • - Research Article

Multimodality Functional Imaging in Radiation Therapy Planning: Relationships between Dynamic Contrast-Enhanced MRI, Diffusion-Weighted MRI, and 18F-FDG PET

Moisés Mera Iglesias | David Aramburu Núñez | ... | Victor Muñoz
  • Special Issue
  • - Volume 2014
  • - Article ID 847162
  • - Research Article

Modeling the Relationship between Fluorodeoxyglucose Uptake and Tumor Radioresistance as a Function of the Tumor Microenvironment

Jeho Jeong | Joseph O. Deasy
  • Special Issue
  • - Volume 2014
  • - Article ID 624642
  • - Review Article

Hypoxia in Head and Neck Cancer in Theory and Practice: A PET-Based Imaging Approach

Loredana G. Marcu | Wendy M. Harriss-Phillips | Sanda M. Filip
  • Special Issue
  • - Volume 2014
  • - Article ID 982978
  • - Research Article

Delay Differential Model for Tumour-Immune Response with Chemoimmunotherapy and Optimal Control

F. A. Rihan | D. H. Abdelrahman | ... | M. A. Abdeen
Computational and Mathematical Methods in Medicine
 Journal metrics
Acceptance rate38%
Submission to final decision61 days
Acceptance to publication39 days
CiteScore1.840
Impact Factor1.563
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