SU-E-T-295: Optimizing Radiotherapy for Glioblastoma Using A Patient-Specific Mathematical Model

2013 ◽  
Vol 40 (6Part15) ◽  
pp. 272-272
Author(s):  
D Corwin ◽  
C Holdsworth ◽  
R Rockne ◽  
R Stewart ◽  
M Phillips ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Patient Specific

scholarly journals NIMG-33CORRELATING A PATIENT-SPECIFIC MATHEMATICAL MODEL OF GLIOBLASTOMA PROLIFERATION-INVASION WITH IMAGE-GUIDED BIOPSIES

2015 ◽  
Vol 17 (suppl 5) ◽  
pp. v161.1-v161
Author(s):  
Andrea Hawkins-Daarud ◽  
Hani Malone ◽  
Timothy Ung ◽  
Anthony Rosenberg ◽  
Joshua Jacobs ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Patient Specific ◽  
Image Guided

scholarly journals On the effect of antiresorptive drugs on the bone remodeling of the mandible after dental implantation: a mathematical model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mehran Ashrafi ◽  
Farzan Ghalichi ◽  
Behnam Mirzakouchaki ◽  
Manuel Doblare
Keyword(s):  
Mathematical Model ◽  
Bone Density ◽  
Bone Remodeling ◽  
Dental Implants ◽  
Implant Design ◽  
Patient Specific ◽  
Dental Implantation ◽  
Antiresorptive Agents ◽  
Antiresorptive Drugs

AbstractBone remodeling identifies the process of permanent bone change with new bone formation and old bone resorption. Understanding this process is essential in many applications, such as optimizing the treatment of diseases like osteoporosis, maintaining bone density in long-term periods of disuse, or assessing the long-term evolution of the bone surrounding prostheses after implantation. A particular case of study is the bone remodeling process after dental implantation. Despite the overall success of this type of implants, the increasing life expectancy in developed countries has boosted the demand for dental implants in patients with osteoporosis. Although several studies demonstrate a high success rate of dental implants in osteoporotic patients, it is also known that the healing time and the failure rate increase, necessitating the adoption of pharmacological measures to improve bone quality in those patients. However, the general efficacy of these antiresorptive drugs for osteoporotic patients is still controversial, requiring more experimental and clinical studies. In this work, we investigate the effect of different doses of several drugs, used nowadays in osteoporotic patients, on the evolution of bone density after dental implantation. With this aim, we use a pharmacokinetic–pharmacodynamic (PK/PD) mathematical model that includes the effect of antiresorptive drugs on the RANK/RANK-L/OPG pathway, as well as the mechano-chemical coupling with external mechanical loads. This mechano-PK/PD model is then used to analyze the evolution of bone in normal and osteoporotic mandibles after dental implantation with different drug dosages. We show that using antiresorptive agents such as bisphosphonates or denosumab increases bone density and the associated mechanical properties, but at the same time, it also increases bone brittleness. We conclude that, despite the many limitations of these very complex models, the one presented here is capable of predicting qualitatively the evolution of some of the main biological and chemical variables associated with the process of bone remodeling in patients receiving drugs for osteoporosis, so it could be used to optimize dental implant design and coating for osteoporotic patients, as well as the drug dosage protocol for patient-specific treatments.

scholarly journals Applying a patient-specific bio-mathematical model of glioma growth to develop virtual [18F]-FMISO-PET images

2011 ◽  
Vol 29 (1) ◽  
pp. 31-48 ◽  
Author(s):  
S. Gu ◽  
G. Chakraborty ◽  
K. Champley ◽  
A. M. Alessio ◽  
J. Claridge ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Patient Specific ◽  
Glioma Growth

scholarly journals Bifurcation analysis of a mathematical model of atopic dermatitis to determine patient-specific effects of treatments on dynamic phenotypes

2018 ◽  
Vol 448 ◽  
pp. 66-79 ◽  
Author(s):  
Gouhei Tanaka ◽  
Elisa Domínguez-Hüttinger ◽  
Panayiotis Christodoulides ◽  
Kazuyuki Aihara ◽  
Reiko J. Tanaka
Keyword(s):  
Mathematical Model ◽  
Atopic Dermatitis ◽  
Bifurcation Analysis ◽  
Patient Specific ◽  
Specific Effects

IDH–wild-type glioblastoma cell density and infiltration distribution influence on supramarginal resection and its impact on overall survival: a mathematical model

2021 ◽  
pp. 1-9
Author(s):  
Shashwat Tripathi ◽  
Tito Vivas-Buitrago ◽  
Ricardo A. Domingo ◽  
Gaetano De Biase ◽  
Desmond Brown ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Overall Survival ◽  
Cell Density ◽  
Patient Specific ◽  
Wild Type ◽  
Tumor Invasiveness ◽  
Postoperative Mri ◽  
T1 Contrast ◽  
Supramarginal Resection ◽  
The Impact

OBJECTIVE Recent studies have proposed resection of the T2 FLAIR hyperintensity beyond the T1 contrast enhancement (supramarginal resection [SMR]) for IDH–wild-type glioblastoma (GBM) to further improve patients’ overall survival (OS). GBMs have significant variability in tumor cell density, distribution, and infiltration. Advanced mathematical models based on patient-specific radiographic features have provided new insights into GBM growth kinetics on two important parameters of tumor aggressiveness: proliferation rate (ρ) and diffusion rate (D). The aim of this study was to investigate OS of patients with IDH–wild-type GBM who underwent SMR based on a mathematical model of cell distribution and infiltration profile (tumor invasiveness profile). METHODS Volumetric measurements were obtained from the selected regions of interest from pre- and postoperative MRI studies of included patients. The tumor invasiveness profile (proliferation/diffusion [ρ/D] ratio) was calculated using the following formula: ρ/D ratio = (4π/3)2/3 × (6.106/[VT21/1 − VT11/1])2, where VT2 and VT1 are the preoperative FLAIR and contrast-enhancing volumes, respectively. Patients were split into subgroups based on their tumor invasiveness profiles. In this analysis, tumors were classified as nodular, moderately diffuse, or highly diffuse. RESULTS A total of 101 patients were included. Tumors were classified as nodular (n = 34), moderately diffuse (n = 34), and highly diffuse (n = 33). On multivariate analysis, increasing SMR had a significant positive correlation with OS for moderately and highly diffuse tumors (HR 0.99, 95% CI 0.98–0.99; p = 0.02; and HR 0.98, 95% CI 0.96–0.99; p = 0.04, respectively). On threshold analysis, OS benefit was seen with SMR from 10% to 29%, 10% to 59%, and 30% to 90%, for nodular, moderately diffuse, and highly diffuse, respectively. CONCLUSIONS The impact of SMR on OS for patients with IDH–wild-type GBM is influenced by the degree of tumor invasiveness. The authors’ results show that increasing SMR is associated with increased OS in patients with moderate and highly diffuse IDH–wild-type GBMs. When grouping SMR into 10% intervals, this benefit was seen for all tumor subgroups, although for nodular tumors, the maximum beneficial SMR percentage was considerably lower than in moderate and highly diffuse tumors.

Predicting Patient-Specific Radiotherapy Protocols Based on Mathematical Model Choice for Proliferation Saturation Index

2017 ◽  
Vol 80 (5) ◽  
pp. 1195-1206 ◽  
Author(s):  
Jan Poleszczuk ◽  
Rachel Walker ◽  
Eduardo G. Moros ◽  
Kujtim Latifi ◽  
Jimmy J. Caudell ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Saturation Index ◽  
Patient Specific ◽  
Model Choice

scholarly journals Mathematical model of a personalized neoantigen cancer vaccine and the human immune system

2021 ◽  
Vol 17 (9) ◽  
pp. e1009318
Author(s):  
Marisabel Rodriguez Messan ◽  
Osman N. Yogurtcu ◽  
Joseph R. McGill ◽  
Ujwani Nukala ◽  
Zuben E. Sauna ◽  
...  
Keyword(s):  
Mathematical Model ◽  
T Cells ◽  
Immune System ◽  
Immune Responses ◽  
Cancer Vaccine ◽  
Tumor Size ◽  
Cancer Vaccines ◽  
Patient Specific ◽  
Human Immune System ◽  
Human Immune

Cancer vaccines are an important component of the cancer immunotherapy toolkit enhancing immune response to malignant cells by activating CD4+ and CD8+ T cells. Multiple successful clinical applications of cancer vaccines have shown good safety and efficacy. Despite the notable progress, significant challenges remain in obtaining consistent immune responses across heterogeneous patient populations, as well as various cancers. We present a mechanistic mathematical model describing key interactions of a personalized neoantigen cancer vaccine with an individual patient’s immune system. Specifically, the model considers the vaccine concentration of tumor-specific antigen peptides and adjuvant, the patient’s major histocompatibility complexes I and II copy numbers, tumor size, T cells, and antigen presenting cells. We parametrized the model using patient-specific data from a clinical study in which individualized cancer vaccines were used to treat six melanoma patients. Model simulations predicted both immune responses, represented by T cell counts, to the vaccine as well as clinical outcome (determined as change of tumor size). This model, although complex, can be used to describe, simulate, and predict the behavior of the human immune system to a personalized cancer vaccine.

scholarly journals SO083VASCULAR STIFFNESS ESTIMATED NON-INVASIVELY USING PULSE WAVE PROPAGATION CORRESPONDS TO VASCULAR BIOPSY FINDINGS

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Malgorzata Debowska ◽  
Bengt Lindholm ◽  
Lu Dai ◽  
Jacek Waniewski ◽  
Abdul Rashid Tony Qureshi ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Wave Propagation ◽  
Vascular Calcification ◽  
Pulse Pressure ◽  
Pulse Wave ◽  
Vascular Stiffness ◽  
Patient Specific ◽  
P Value ◽  
Pulse Wave Propagation ◽  
Pressure Profiles

Abstract Background and Aims Patients with chronic kidney disease (CKD) are at high risk of cardiovascular disease (CVD) due to complex processes in the uremic milieu linked to CKD - mineral and bone disorders (CKD-MBD). These processes alter structure and function of heart and vasculature e.g. by causing ectopic calcification that makes vessels stiffer thus affecting pulse (pressure) wave profiles. Our study aimed to derive patient-specific parameters using pulse wave propagation model including arterial stiffness and compare those parameters with cardiovascular status including biopsy proven severity of vascular calcification. Method In a group of 81 CKD (stage 5) patients undergoing living donor kidney transplantation, the degree of medial calcification in epigastric artery was histologically graded as 0 (n=22), 1 (n=31), 2 (n=21) and 3 (n=7) representing no, minimal, moderate and extensive signs of vascular calcification, respectively. Concomitantly 82 features were determined including demographic and anthropometric features, blood biomarkers related to CKD - MBD and other measurements. Pressure profiles (circles in Fig. 1) in radial artery were recorded using applanation tonometer (SphygmoCor, AtCor Medical, Australia) and used to derive patient-specific parameters from a mathematical model describing blood flow and pressure in 55 major arteries. Results The model was able to reproduce all recorded pressure profiles with high accuracy with average relative error less than 8% (compare solid line and circles in Fig. 1). Vascular stiffness, derived from the model, in arterial branches located in the area of artery for which calcification was histologically quantified, was significantly higher for higher calcification score (p-value < 0.001). The estimated stiffness correlated with the level of troponin T (rho=0.65**), advanced glycation end-products (by skin autofluorescence, rho=0.55*), osteoprotegerin (rho=0.44**), hepcidin 25 (rho=0.32*, interleukin 6 (rho=0.29*) and choline (rho=0.28**), (‘**’ and ‘*’ denote p-value < 0.01 and 0.05, respectively). Stiffer arteries were found in patients with diagnosed CVD (p-value < 0.01). Conclusion We demonstrate that a mathematical model based on a single peripheral recording of pulse pressure profile has the potential to provide information about cardiovascular status in the individual patient. Also, the estimated stiffness correlates well with several well-established CVD risk factors. Our mathematical model of the arterial tree, if validated in larger cohorts of patients, may be used as computational tool to predict vascular stiffness without need of arterial biopsy.

scholarly journals A personalized computational model of edema formation in myocarditis based on long-axis biventricular MRI images

2019 ◽  
Vol 20 (S6) ◽  
Author(s):  
Ruy Freitas Reis ◽  
Juliano Lara Fernandes ◽  
Thaiz Ruberti Schmal ◽  
Bernardo Martins Rocha ◽  
Rodrigo Weber dos Santos ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Immune Response ◽  
Computational Model ◽  
Cardiac Tissue ◽  
Geometrical Model ◽  
Specific Model ◽  
Patient Specific ◽  
Edema Formation ◽  
Promising Tool ◽  
Inflammatory Edema

Abstract Background Myocarditis is defined as the inflammation of the myocardium, i.e. the cardiac muscle. Among the reasons that lead to this disease, we may include infections caused by a virus, bacteria, protozoa, fungus, and others. One of the signs of the inflammation is the formation of edema, which may be a consequence of the interaction between interstitial fluid dynamics and immune response. This complex physiological process was mathematically modeled using a nonlinear system of partial differential equations (PDE) based on porous media approach. By combing a model based on Biot’s poroelasticity theory with a model for the immune response we developed a new hydro-mechanical model for inflammatory edema. To verify this new computational model, T2 parametric mapping obtained by Magnetic Resonance (MR) imaging was used to identify the region of edema in a patient diagnosed with unspecific myocarditis. Results A patient-specific geometrical model was created using MRI images from the patient with myocarditis. With this model, edema formation was simulated using the proposed hydro-mechanical mathematical model in a two-dimensional domain. The computer simulations allowed us to correlate spatiotemporal dynamics of representative cells of the immune systems, such as leucocytes and the pathogen, with fluid accumulation and cardiac tissue deformation. Conclusions This study demonstrates that the proposed mathematical model is a very promising tool to better understand edema formation in myocarditis. Simulations obtained from a patient-specific model reproduced important aspects related to the formation of cardiac edema, its area, position, and shape, and how these features are related to immune response.

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