SU-E-T-565: Patient-Specific Evaluation of the Need for Adaptive Therapy in Lung SBRT

2011 ◽  
Vol 38 (6Part19) ◽  
pp. 3619-3619
Author(s):  
D Owen ◽  
A Cherpak ◽  
J Cygler ◽  
J Belec ◽  
B Clark
Keyword(s):  
Patient Specific ◽  
Lung Sbrt ◽  
Adaptive Therapy ◽  
Specific Evaluation

SU-F-T-270: A Technique for Modeling a Diode Array Into the TPS for Lung SBRT Patient Specific QA

2016 ◽  
Vol 43 (6Part17) ◽  
pp. 3524-3525
Author(s):  
C Curley ◽  
Z Ouhib ◽  
T Leventouri
Keyword(s):  
Patient Specific ◽  
Diode Array ◽  
Lung Sbrt ◽  
Patient Specific Qa

scholarly journals Understanding the potential benefits of adaptive therapy for metastatic melanoma

2020 ◽  
Author(s):  
Eunjung Kim ◽  
Joel S. Brown ◽  
Zeynep Eroglu ◽  
Alexander R.A. Anderson
Keyword(s):  
Mathematical Models ◽  
Underlying Mechanism ◽  
Resistant Cell ◽  
Phenotypic Switching ◽  
Patient Specific ◽  
Optimal Timing ◽  
Initial Population ◽  
Continuous Therapy ◽  
Adaptive Therapy ◽  
Resistant Cells

AbstractAdaptive therapy is an evolution-based treatment approach that aims to maintain tumor volume by employing minimum effective drug doses or timed drug holidays. For successful adaptive therapy outcomes, it is critical to find the optimal timing of treatment switch points. Mathematical models are ideal tools to facilitate adaptive therapy dosing and switch time points. We developed two different mathematical models to examine interactions between drug-sensitive and resistant cells in a tumor. The first model assumes genetically fixed drug-sensitive and resistant populations that compete for limited resources. Resistant cell growth is inhibited by sensitive cells. The second model considers phenotypic switching between drug-sensitive and resistant cells. We calibrated each model to fit melanoma patient biomarker changes over time and predicted patient-specific adaptive therapy schedules. Overall, the models predict that adaptive therapy would have delayed time to progression by 6-25 months compared to continuous therapy with dose rates of 6%-74% relative to continuous therapy. We identified predictive factors driving the clinical time gained by adaptive therapy. The first model predicts 6-20 months gained from continuous therapy when the initial population of sensitive cells is large enough, and when the sensitive cells have a large competitive effect on resistant cells. The second model predicts 20-25 months gained from continuous therapy when the switching rate from resistant to sensitive cells is high and the growth rate of sensitive cells is low. This study highlights that there is a range of potential patient specific benefits of adaptive therapy, depending on the underlying mechanism of resistance, and identifies tumor specific parameters that modulate this benefit.

Abstract A33: Patient-specific evaluation of chemoresistance and tumor recurrence using ovarian cancer stem cell spheroids

2018 ◽  
Author(s):  
Shreya Raghavan ◽  
Pooja Mehta ◽  
Michael Bregenzer ◽  
Maria Ward Rashidi ◽  
Elyse Fleck ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Stem Cell ◽  
Cancer Stem Cell ◽  
Tumor Recurrence ◽  
Patient Specific ◽  
Cell Spheroids ◽  
Specific Evaluation

scholarly journals Lumbosacral Biometrics and its Relevance to Patient-Specific Evaluation of Bone Mechanical Strength in Some Canine Breeds

2019 ◽  
Vol 5 (1) ◽  
pp. 05-09
Author(s):  
Nicole Rosenberger ◽  
Erica De Capitani ◽  
Seamus Hoey ◽  
David Kilroy ◽  
Arun HS Kumar
Keyword(s):  
Mechanical Strength ◽  
Patient Specific ◽  
Bone Mechanical Strength ◽  
Specific Evaluation

scholarly journals Feasibility of deriving a novel imaging biomarker based on patient-specific lung elasticity for characterizing the degree of COPD in lung SBRT patients

2019 ◽  
Vol 92 (1094) ◽  
pp. 20180296
Author(s):  
Katelyn Hasse ◽  
John Neylon ◽  
Yugang Min ◽  
Dylan O'Connell ◽  
Percy Lee ◽  
...  
Keyword(s):  
Imaging Biomarker ◽  
Patient Specific ◽  
Lung Sbrt

Patient-Specific Statistics-Based Decision Support in Health Monitoring Using Fuzzy Logic

2015 ◽  
Vol 1117 ◽  
pp. 273-276
Author(s):  
Edit Tóth-Laufer ◽  
Annamária R. Várkonyi-Kóczy
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
Membership Function ◽  
Health Monitoring ◽  
Processing Method ◽  
Reduced Model ◽  
Patient Specific ◽  
Monitoring Systems ◽  
Health Monitoring Systems ◽  
Specific Evaluation

In this paper, the usage possibilities of personal statistics are introduced, which can be applied to improve the patient-specific evaluation in health monitoring systems. The aim of these techniques is to obtain reliable results based on previous measurements. This goal can be achieved by membership function tuning or modification, as well as by a pre-processing method, which is used to judge whether a situation is normal or not. In the latter case, a further requirement, that the appropriate result should be available in time, can also be fulfilled. If the situation is judged to be critical then a reduced model is evaluated instead of the full one.

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