Publication

Simulation of hypoxia PET-tracer uptake in tumours: Dependence of clinical uptake-values on transport parameters and arterial input function

Paredes-Cisneros, I., Karger, C. P., Caprile, P., Nolte, D., Espinoza, I. & Gago-Arias, A., Feb-2020, In : Physica medica-European journal of medical physics. 70, p. 109-117 9 p.

Research output: Contribution to journalArticleAcademicpeer-review

APA

Paredes-Cisneros, I., Karger, C. P., Caprile, P., Nolte, D., Espinoza, I., & Gago-Arias, A. (2020). Simulation of hypoxia PET-tracer uptake in tumours: Dependence of clinical uptake-values on transport parameters and arterial input function. Physica medica-European journal of medical physics, 70, 109-117. https://doi.org/10.1016/j.ejmp.2020.01.012

Author

Paredes-Cisneros, Isabela ; Karger, Christian P. ; Caprile, Paola ; Nolte, David ; Espinoza, Ignacio ; Gago-Arias, Araceli. / Simulation of hypoxia PET-tracer uptake in tumours : Dependence of clinical uptake-values on transport parameters and arterial input function. In: Physica medica-European journal of medical physics. 2020 ; Vol. 70. pp. 109-117.

Harvard

Paredes-Cisneros, I, Karger, CP, Caprile, P, Nolte, D, Espinoza, I & Gago-Arias, A 2020, 'Simulation of hypoxia PET-tracer uptake in tumours: Dependence of clinical uptake-values on transport parameters and arterial input function', Physica medica-European journal of medical physics, vol. 70, pp. 109-117. https://doi.org/10.1016/j.ejmp.2020.01.012

Standard

Simulation of hypoxia PET-tracer uptake in tumours : Dependence of clinical uptake-values on transport parameters and arterial input function. / Paredes-Cisneros, Isabela; Karger, Christian P.; Caprile, Paola; Nolte, David; Espinoza, Ignacio; Gago-Arias, Araceli.

In: Physica medica-European journal of medical physics, Vol. 70, 02.2020, p. 109-117.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Paredes-Cisneros I, Karger CP, Caprile P, Nolte D, Espinoza I, Gago-Arias A. Simulation of hypoxia PET-tracer uptake in tumours: Dependence of clinical uptake-values on transport parameters and arterial input function. Physica medica-European journal of medical physics. 2020 Feb;70:109-117. https://doi.org/10.1016/j.ejmp.2020.01.012


BibTeX

@article{fa74bf52118d483297137aee3fa7b542,
title = "Simulation of hypoxia PET-tracer uptake in tumours: Dependence of clinical uptake-values on transport parameters and arterial input function",
abstract = "Poor radiotherapy outcome is in many cases related to hypoxia, due to the increased radioresistance of hypoxic tumour cells. Positron emission tomography may be used to non-invasively assess the oxygenation status of the tumour using hypoxia-specific radiotracers. Quantification and interpretation of these images remains challenging, since radiotracer binding and oxygen tension are not uniquely related. Computer simulation is a useful tool to improve the understanding of tracer dynamics and its relation to clinical uptake parameters currently used to quantify hypoxia. In this study, a model for simulating oxygen and radiotracer distribution in tumours was implemented to analyse the impact of physiological transport parameters and of the arterial input function (AIF) on: oxygenation histograms, time-activity curves, tracer binding and clinical uptake-values (tissue-to-blood ratio, TBR, and a composed hypoxia-perfusion metric, FHP). Results were obtained for parallel and orthogonal vessel architectures and for vascular fractions (VFs) of 1{\%} and 3{\%}. The most sensitive parameters were the AIF and the maximum binding rate (K-max). TBR allowed discriminating VF for different AIF, and FHP for different K-max, but neither TBR nor FHP were unbiased in all cases. Biases may especially occur in the comparison of TBR- or FHP-values between different tumours, where the relation between measured and actual AIF may vary. Thus, these parameters represent only surrogates rather than absolute measurements of hypoxia in tumours.",
keywords = "Hypoxia tracer uptake, Positron-emission-tomography (PET), Radiotherapy, Computer simulation, SQUAMOUS-CELL CARCINOMA, OXYGENATION, HEAD, MODEL, FLUOROMISONIDAZOLE, FMISO, FAZA",
author = "Isabela Paredes-Cisneros and Karger, {Christian P.} and Paola Caprile and David Nolte and Ignacio Espinoza and Araceli Gago-Arias",
year = "2020",
month = "2",
doi = "10.1016/j.ejmp.2020.01.012",
language = "English",
volume = "70",
pages = "109--117",
journal = "Physica medica-European journal of medical physics",
issn = "1120-1797",
publisher = "ELSEVIER SCI LTD",

}

RIS

TY - JOUR

T1 - Simulation of hypoxia PET-tracer uptake in tumours

T2 - Dependence of clinical uptake-values on transport parameters and arterial input function

AU - Paredes-Cisneros, Isabela

AU - Karger, Christian P.

AU - Caprile, Paola

AU - Nolte, David

AU - Espinoza, Ignacio

AU - Gago-Arias, Araceli

PY - 2020/2

Y1 - 2020/2

N2 - Poor radiotherapy outcome is in many cases related to hypoxia, due to the increased radioresistance of hypoxic tumour cells. Positron emission tomography may be used to non-invasively assess the oxygenation status of the tumour using hypoxia-specific radiotracers. Quantification and interpretation of these images remains challenging, since radiotracer binding and oxygen tension are not uniquely related. Computer simulation is a useful tool to improve the understanding of tracer dynamics and its relation to clinical uptake parameters currently used to quantify hypoxia. In this study, a model for simulating oxygen and radiotracer distribution in tumours was implemented to analyse the impact of physiological transport parameters and of the arterial input function (AIF) on: oxygenation histograms, time-activity curves, tracer binding and clinical uptake-values (tissue-to-blood ratio, TBR, and a composed hypoxia-perfusion metric, FHP). Results were obtained for parallel and orthogonal vessel architectures and for vascular fractions (VFs) of 1% and 3%. The most sensitive parameters were the AIF and the maximum binding rate (K-max). TBR allowed discriminating VF for different AIF, and FHP for different K-max, but neither TBR nor FHP were unbiased in all cases. Biases may especially occur in the comparison of TBR- or FHP-values between different tumours, where the relation between measured and actual AIF may vary. Thus, these parameters represent only surrogates rather than absolute measurements of hypoxia in tumours.

AB - Poor radiotherapy outcome is in many cases related to hypoxia, due to the increased radioresistance of hypoxic tumour cells. Positron emission tomography may be used to non-invasively assess the oxygenation status of the tumour using hypoxia-specific radiotracers. Quantification and interpretation of these images remains challenging, since radiotracer binding and oxygen tension are not uniquely related. Computer simulation is a useful tool to improve the understanding of tracer dynamics and its relation to clinical uptake parameters currently used to quantify hypoxia. In this study, a model for simulating oxygen and radiotracer distribution in tumours was implemented to analyse the impact of physiological transport parameters and of the arterial input function (AIF) on: oxygenation histograms, time-activity curves, tracer binding and clinical uptake-values (tissue-to-blood ratio, TBR, and a composed hypoxia-perfusion metric, FHP). Results were obtained for parallel and orthogonal vessel architectures and for vascular fractions (VFs) of 1% and 3%. The most sensitive parameters were the AIF and the maximum binding rate (K-max). TBR allowed discriminating VF for different AIF, and FHP for different K-max, but neither TBR nor FHP were unbiased in all cases. Biases may especially occur in the comparison of TBR- or FHP-values between different tumours, where the relation between measured and actual AIF may vary. Thus, these parameters represent only surrogates rather than absolute measurements of hypoxia in tumours.

KW - Hypoxia tracer uptake

KW - Positron-emission-tomography (PET)

KW - Radiotherapy

KW - Computer simulation

KW - SQUAMOUS-CELL CARCINOMA

KW - OXYGENATION

KW - HEAD

KW - MODEL

KW - FLUOROMISONIDAZOLE

KW - FMISO

KW - FAZA

U2 - 10.1016/j.ejmp.2020.01.012

DO - 10.1016/j.ejmp.2020.01.012

M3 - Article

VL - 70

SP - 109

EP - 117

JO - Physica medica-European journal of medical physics

JF - Physica medica-European journal of medical physics

SN - 1120-1797

ER -

ID: 128595375