ArticleRadiation oncology (London, England)2015
A proliferation saturation index to predict radiation response and personalize radiotherapy fractionation.
Article in Radiation oncology (London, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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Who cites it
62 citing papers in PubMed, 132 citations in OpenAlex.
- Toward Personalized Computer Simulation of Breast Cancer Treatment: A Multiscale Pharmacokinetic and Pharmacodynamic Model Informed by Multitype Patient Data.Cancer research · 2019Trial
- Effective tumor kinetics inferred from single routine H&E biopsies enable counterfactual virtual radiotherapy trials.medRxiv : the preprint server for health sciences · 2026Article
- Gompertz growth with a shared carrying capacity optimally simulates primary and metastatic tumor growth dynamics.British journal of cancer · 2026Article
- Simulating Cancer Recurrence Patterns From Post-Treatment Viable Tumor Burden Distributions.JCO clinical cancer informatics · 2026Article
- Mathematical Oncology: How Modeling Is Transforming Clinical Decision-Making.Cancer research · 2025Review
- Measurable imaging-based changes in enhancement of intrahepatic cholangiocarcinoma after radiotherapy reflect physical mechanisms of response.NPJ systems biology and applications · 2025Article
- Forecasting Chemoradiation Response Midtreatment for High-Grade Gliomas Through Patient-Specific Biology-Based Modeling.International journal of radiation oncology, biology, physics · 2025Article
- Employing nullclines to balance treatment efficacy and neurotoxicity for sustained tumor control.Mathematical biosciences · 2025Article
- Analysing the Structural Identifiability and Observability of Mechanistic Models of Tumour Growth.Bioengineering (Basel, Switzerland) · 2025Article
- Predicting and monitoring response to head and neck cancer radiotherapy using multimodality imaging and radiobiological digital twin simulations.Physics in medicine and biology · 2025Article
- Identifiability and model selection frameworks for models of high-grade glioma response to chemoradiation.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- The temporal response of a glioma cell population to irradiation: modelling the effect of dose and cell density.Royal Society open science · 2025Article
- Harnessing Flex Point Symmetry to Estimate Logistic Tumor Population Growth.Bulletin of mathematical biology · 2024Article
- Calibrating tumor growth and invasion parameters with spectral spatial analysis of cancer biopsy tissues.NPJ systems biology and applications · 2024Article
- Practical parameter identifiability and handling of censored data with Bayesian inference in mathematical tumour models.NPJ systems biology and applications · 2024Article
- Multi-modality imaging parameters that predict rapid tumor regression in head and neck radiotherapy.Physics and imaging in radiation oncology · 2024Article
- To modulate or to skip: De-escalating PARP inhibitor maintenance therapy in ovarian cancer using adaptive therapy.Cell systems · 2024Article
- Predicting Radiotherapy Patient Outcomes with Real-Time Clinical Data Using Mathematical Modelling.Bulletin of mathematical biology · 2024Article
- Simulating tumor volume dynamics in response to radiotherapy: Implications of model selection.Journal of theoretical biology · 2024Article
- Intra-promoter switch of transcription initiation sites in proliferation signaling-dependent RNA metabolism.Nature structural & molecular biology · 2023Article
2 more citing papers are in PubMed but not listed here.
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundAlthough altered protocols that challenge conventional radiation fractionation have been tested in prospective clinical trials, we still have limited understanding of how to select the most appropriate fractionation schedule for individual patients. Currently, the prescription of definitive radiotherapy is based on the primary site and stage, without regard to patient-specific tumor or host factors that may influence outcome. We hypothesize that the proportion of radiosensitive proliferating cells is dependent on the saturation of the tumor carrying capacity. This may serve as a prognostic factor for personalized radiotherapy (RT) fractionation.
methodsWe introduce a proliferation saturation index (PSI), which is defined as the ratio of tumor volume to the host-influenced tumor carrying capacity. Carrying capacity is as a conceptual measure of the maximum volume that can be supported by the current tumor environment including oxygen and nutrient availability, immune surveillance and acidity. PSI is estimated from two temporally separated routine pre-radiotherapy computed tomography scans and a deterministic logistic tumor growth model. We introduce the patient-specific pre-treatment PSI into a model of tumor growth and radiotherapy response, and fit the model to retrospective data of four non-small cell lung cancer patients treated exclusively with standard fractionation. We then simulate both a clinical trial hyperfractionation protocol and daily fractionations, with equal biologically effective dose, to compare tumor volume reduction as a function of pretreatment PSI.
resultsWith tumor doubling time and radiosensitivity assumed constant across patients, a patient-specific pretreatment PSI is sufficient to fit individual patient response data (R(2) = 0.98). PSI varies greatly between patients (coefficient of variation >128 %) and correlates inversely with radiotherapy response. For this study, our simulations suggest that only patients with intermediate PSI (0.45-0.9) are likely to truly benefit from hyperfractionation. For up to 20 % uncertainties in tumor growth rate, radiosensitivity, and noise in radiological data, the absolute estimation error of pretreatment PSI is <10 % for more than 75 % of patients.
conclusionsRoutine radiological images can be used to calculate individual PSI, which may serve as a prognostic factor for radiation response. This provides a new paradigm and rationale to select personalized RT dose-fractionation.
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