Quantitative Method for Monitoring Tumor Evolution During and After Therapy

<b>Objectives</b>: The quantitative analysis of tumor progression-monitored during and immediately after therapeutic interventions-can yield valuable insights into both long-term disease dynamics and treatment efficacy. Methods: We used a computational approach designed to support clinical decision-making, with a focus on personalized patient care, based on modeling therapy effects using effective parameters of the Gompertz law. <b>Results</b>: The method is applied to data from in vivo models undergoing neoadjuvant chemoradiotherapy, as well as conventional and FLASH radiation treatments. <b>Conclusions</b>: This user-friendly, phenomenological model captures distinct phases of treatment response and identifies a critical dose threshold distinguishing complete response from partial response or tumor regrowth. These findings lay the groundwork for real-time quantitative monitoring of disease progression during therapy and contribute to a more tailored and predictive clinical strategy.

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Publication Details

Journal
Journal of Personalized Medicine
Published
2025-06-28
DOI
https://doi.org/10.3390/jpm15070275
Citations
1
Primary Topic
Radiation Therapy and Dosimetry
Type
article
Field-Weighted Citation Impact
1.52
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article

Quantitative Method for Monitoring Tumor Evolution During and After Therapy

P. Castorina, Filippo Castiglione, Emanuele Martorana, Stefano Forte et al.
1 citations
Journal of Personalized Medicine
Radiation Therapy and Dosimetry
1.52
article

Quantitative Method for Monitoring Tumor Evolution During and After Therapy

P. Castorina, Filippo Castiglione, Emanuele Martorana, Stefano Forte, Gianluca Ferini
article en
1 citations

Abstract

<b>Objectives</b>: The quantitative analysis of tumor progression-monitored during and immediately after therapeutic interventions-can yield valuable insights into both long-term disease dynamics and treatment efficacy. Methods: We used a computational approach designed to support clinical decision-making, with a focus on personalized patient care, based on modeling therapy effects using effective parameters of the Gompertz law. <b>Results</b>: The method is applied to data from in vivo models undergoing neoadjuvant chemoradiotherapy, as well as conventional and FLASH radiation treatments. <b>Conclusions</b>: This user-friendly, phenomenological model captures distinct phases of treatment response and identifies a critical dose threshold distinguishing complete response from partial response or tumor regrowth. These findings lay the groundwork for real-time quantitative monitoring of disease progression during therapy and contribute to a more tailored and predictive clinical strategy.

Journal of Personalized MedicineVol. 15(7)
Charles University (CZ), Università degli Studi di Enna Kore (IT), Technology Innovation Institute (AE), Istituto Nazionale di Fisica Nucleare, Sezione di Catania (IT), National Research Council (IT)
Peace, Justice and strong institutions
Openalex Percentile: Top 17%
Radiation Therapy and Dosimetry
1.52
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Quantitative Method for Monitoring Tumor Evolution During and After Therapy — P. Castorina, Filippo Castiglione, et al. · Journal of Personalized Medicine (2025) | TGRS Research Map | TGRS