Thomas Koopman1, Roland M Martens2, Cristina Lavini3, Maqsood Yaqub4, Jonas A Castelijns5, Ronald Boellaard6, J Tim Marcus7. 1. Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, de Boelelaan 1117, Amsterdam, the Netherlands. Electronic address: t.koopman@amsterdamumc.nl. 2. Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, de Boelelaan 1117, Amsterdam, the Netherlands. Electronic address: ro.martens@amsterdamumc.nl. 3. Department of Radiology, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands. Electronic address: c.lavini@amsterdamumc.nl. 4. Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, de Boelelaan 1117, Amsterdam, the Netherlands. Electronic address: maqsood.yaqub@amsterdamumc.nl. 5. Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, de Boelelaan 1117, Amsterdam, the Netherlands; Department of Radiology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital (NKI-AVL), Plesmanlaan 121, Amsterdam, the Netherlands. Electronic address: j.castelijns@amsterdamumc.nl. 6. Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, de Boelelaan 1117, Amsterdam, the Netherlands; Department of Nuclear Medicine & Molecular Imaging, University Medical Center Groningen, Hanzeplein 1, Groningen, the Netherlands. Electronic address: r.boellaard@amsterdamumc.nl. 7. Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, de Boelelaan 1117, Amsterdam, the Netherlands. Electronic address: jt.marcus@amsterdamumc.nl.
Abstract
BACKGROUND: Quantification of pharmacokinetic parameters in dynamic contrast enhanced (DCE) MRI is heavily dependent on the arterial input function (AIF). In the present patient study on advanced stage head and neck squamous cell carcinoma (HNSCC) we have acquired DCE-MR images before and during chemo radiotherapy. We determined the repeatability of image-derived AIFs and of the obtained kinetic parameters in muscle and compared the repeatability of muscle kinetic parameters obtained with image-derived AIF's versus a population-based AIF. MATERIALS AND METHODS: We compared image-derived AIFs obtained from the internal carotid, external carotid and vertebral arteries. Pharmacokinetic parameters (ve, Ktrans, kep) in muscle-located outside the radiation area-were obtained using the Tofts model with the image-derived AIFs and a population averaged AIF. Parameter values and repeatability were compared. Repeatability was calculated with the pre- and post-treatment data with the assumption of no DCE-MRI measurable biological changes between the scans. RESULTS: Several parameters describing magnitude and shape of the image-derived AIFs from the different arteries in the head and neck were significantly different. Use of image-derived AIFs led to higher pharmacokinetic parameters compared to use of a population averaged AIF. Median muscle pharmacokinetic parameters values obtained with AIFs in external carotids, internal carotids, vertebral arteries and with a population averaged AIF were respectively: ve (0.65, 0.74, 0.58, 0.32), Ktrans (0.30, 0.21, 0.13, 0.06), kep (0.41, 0.32, 0.24, 0.18). Repeatability of pharmacokinetic parameters was highest when a population averaged AIF was used; however, this repeatability was not significantly different from image-derived AIFs. CONCLUSION: Image-derived AIFs in the neck region showed significant variations in the AIFs obtained from different arteries, and did not improve repeatability of the resulting pharmacokinetic parameters compared with the use of a population averaged AIF. Therefore, use of a population averaged AIF seems to be preferable for pharmacokinetic analysis using DCE-MRI in the head and neck area.
BACKGROUND: Quantification of pharmacokinetic parameters in dynamic contrast enhanced (DCE) MRI is heavily dependent on the arterial input function (AIF). In the present patient study on advanced stage head and neck squamous cell carcinoma (HNSCC) we have acquired DCE-MR images before and during chemo radiotherapy. We determined the repeatability of image-derived AIFs and of the obtained kinetic parameters in muscle and compared the repeatability of muscle kinetic parameters obtained with image-derived AIF's versus a population-based AIF. MATERIALS AND METHODS: We compared image-derived AIFs obtained from the internal carotid, external carotid and vertebral arteries. Pharmacokinetic parameters (ve, Ktrans, kep) in muscle-located outside the radiation area-were obtained using the Tofts model with the image-derived AIFs and a population averaged AIF. Parameter values and repeatability were compared. Repeatability was calculated with the pre- and post-treatment data with the assumption of no DCE-MRI measurable biological changes between the scans. RESULTS: Several parameters describing magnitude and shape of the image-derived AIFs from the different arteries in the head and neck were significantly different. Use of image-derived AIFs led to higher pharmacokinetic parameters compared to use of a population averaged AIF. Median muscle pharmacokinetic parameters values obtained with AIFs in external carotids, internal carotids, vertebral arteries and with a population averaged AIF were respectively: ve (0.65, 0.74, 0.58, 0.32), Ktrans (0.30, 0.21, 0.13, 0.06), kep (0.41, 0.32, 0.24, 0.18). Repeatability of pharmacokinetic parameters was highest when a population averaged AIF was used; however, this repeatability was not significantly different from image-derived AIFs. CONCLUSION: Image-derived AIFs in the neck region showed significant variations in the AIFs obtained from different arteries, and did not improve repeatability of the resulting pharmacokinetic parameters compared with the use of a population averaged AIF. Therefore, use of a population averaged AIF seems to be preferable for pharmacokinetic analysis using DCE-MRI in the head and neck area.
Authors: Jonghyun Bae; Zhengnan Huang; Florian Knoll; Krzysztof Geras; Terlika Pandit Sood; Li Feng; Laura Heacock; Linda Moy; Sungheon Gene Kim Journal: Magn Reson Med Date: 2022-01-09 Impact factor: 4.668
Authors: Ryan T Woodall; Prativa Sahoo; Yujie Cui; Bihong T Chen; Mark S Shiroishi; Cristina Lavini; Paul Frankel; Margarita Gutova; Christine E Brown; Jennifer M Munson; Russell C Rockne Journal: Neurooncol Adv Date: 2021-11-22