activity
20192026
most citedPredictive Digital Twin for Optimizing Patient-Specific Radiotherapy Regimens under Uncertainty in High-Grade Gliomas

100 citations · 119 across the 12 of their papers we have counts for

collaborators

12 papers

math.NA2026

Cahn-Hilliard phase-field modeling of tumor growth via locally adaptive isogeometric analysis with THB-splines

Dhiraj S. Bombarde, Carlotta Giannelli, Alessandro Reali +1

Predicting tumor dynamics in biological systems under physiologically relevant conditions using mathematical and computational models remains a challenging problem. Continuum model…

q-bio.TO2025

Validating the predictions of mathematical models describing tumor growth and treatment response

Guillermo Lorenzo, David A. Hormuth, Chengyue Wu +7

Despite advances in methods to interrogate tumor biology, the observational and population-based approach of classical cancer research and clinical oncology does not enable anticip…

q-bio.TO2023★ 1 cited

Patient-specific computational forecasting of prostate cancer growth during active surveillance using an imaging-informed biomechanistic model

Guillermo Lorenzo, Jon S. Heiselman, Michael A. Liss +5

Active surveillance (AS) is a suitable management option for newly-diagnosed prostate cancer (PCa), which usually presents low to intermediate clinical risk. Patients enrolled in A…

physics.med-ph2023★ 3 cited

Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data

Guillermo Lorenzo, Syed Rakin Ahmed, David A. Hormuth +5

Despite the remarkable advances in cancer diagnosis, treatment, and management that have occurred over the past decade, malignant tumors remain a major public health problem. Furth…

cs.CE2023★ 100 cited

Predictive Digital Twin for Optimizing Patient-Specific Radiotherapy Regimens under Uncertainty in High-Grade Gliomas

Anirban Chaudhuri, Graham Pash, David A. Hormuth +6

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipa…

q-bio.TO2022★ 2 cited

Identifying mechanisms driving the early response of triple negative breast cancer patients to neoadjuvant chemotherapy using a mechanistic model integrating in vitro and in vivo imaging data

Guillermo Lorenzo, Angela M. Jarrett, Christian T. Meyer +3

Neoadjuvant chemotherapy (NAC) is a standard-of-care treatment for locally advanced triple negative breast cancer (TNBC) before surgery. The early assessment of TNBC response to NA…

q-bio.TO2022★ 7 cited

Oncology and mechanics: landmark studies and promising clinical applications

Stéphane Urcun, Guillermo Lorenzo, Davide Baroli +5

Clinical management of cancer has continuously evolved for several decades. Biochemical, molecular and genomics approaches have brought and still bring numerous insights into cance…

physics.bio-ph2022

Data-driven simulation of Fisher-Kolmogorov tumor growth models using Dynamic Mode Decomposition

Alex Viguerie, Malú Grave, Gabriel F. Barros +3

The computer simulation of organ-scale biomechanistic models of cancer personalized via routinely collected clinical and imaging data enables to obtain patient-specific predictions…

q-bio.TO2021★ 6 cited

Quantitative in vivo imaging to enable tumor forecasting and treatment optimization

Guillermo Lorenzo, David A. Hormuth, Angela M. Jarrett +6

Current clinical decision-making in oncology relies on averages of large patient populations to both assess tumor status and treatment outcomes. However, cancers exhibit an inheren…

math.OC2020

Optimal control of cytotoxic and antiangiogenic therapies on prostate cancer growth

Pierluigi Colli, Hector Gomez, Guillermo Lorenzo +3

Prostate cancer can be lethal in advanced stages, for which chemotherapy may become the only viable therapeutic option. While there is no clear clinical management strategy fitting…

q-bio.PE2020

Simulating the spread of COVID-19 via spatially-resolved susceptible-exposed-infected-recovered-deceased (SEIRD) model with heterogeneous diffusion

Alex Viguerie, Guillermo Lorenzo, Ferdinando Auricchio +6

We present an early version of a Susceptible-Exposed-Infected-Recovered-Deceased (SEIRD) mathematical model based on partial differential equations coupled with a heterogeneous dif…

math.AP2019

Mathematical analysis and simulation study of a phase-field model of prostate cancer growth with chemotherapy and antiangiogenic therapy effects

Pierluigi Colli, Hector Gomez, Guillermo Lorenzo +3

Cytotoxic chemotherapy is a common treatment for advanced prostate cancer. These tumors are also known to rely on angiogenesis, i.e., the growth of local microvasculature via chemi…