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Arterial input function

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An example of an arterial input function showing the concentration of tracer in blood plasma over time.

Arterial input function (AIF), also known as a plasma input function, refers to the concentration of tracer in blood-plasma in an artery measured over time. The oldest record on PubMed shows that AIF was used by Harvey et al.[1] in 1962 to measure the exchange of materials between red blood cells and blood plasma, and by other researchers in 1983 for positron emission tomography (PET) studies.[2][3] Nowadays, kinetic analysis is performed in various medical imaging techniques, which requires an AIF as one of the inputs to the mathematical model, for example, in dynamic PET imaging[4], or perfusion CT[5], or dynamic contrast-enhanced magnetic resonance imaging (dce-MRI).[6][7]

How is AIF obtained

AIF can be obtained in several different ways, for example, using the invasive method of continuous arterial sampling using an online blood monitor[8], using the invasive method of arterial blood samples obtained at discrete time points post-injection[4], using a minimally invasive method using a population-based AIF where an input function in a subject is estimated partly from the prior information obtained from a previous population and partly from the blood information from the subject itself obtained at the time of scanning[9], or using an image-derived arterial input function (IDAIF) obtained by placing a region of interest (ROI) over an artery and calibrating the resulting curves against venous blood samples obtained during the later phases (30 to 60 minutes) of the dynamic scan[10] when venous and arterial tracer concentrations become equal.[4] A dynamic scan is a scan where two dimensional (2D) or three dimensional (3D) images are acquired again and again over a time-period forming a time-series of 2D/3D image datasets. For example, a dynamic PET scan acquired over a period of one hour contains the first few short image frames acquired for 5 seconds duration to capture the fast dynamics of the tracer immediately after a tracer-injection and later frames acquired for 30 seconds. Each data-point in the AIF curve represents a measurement of tracer-concentration from an artery obtained from each of these image time-frame acquired over time, with external corrections applied to it.

These four methods are described in more details as follows:

Continuous arterial sampling

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Discrete arterial sampling

More content to be added soon

Population-based method

Frost et al, Blake et al, Cook et al.

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Image-derived method

An IDAIF obtained by measuring the tracer counts over the aorta[11], carodit artery[12], or radial artery[13] offers an alternative to invasive arterial blood sampling. An IDAIF at the aorta can be determined by measuring the tracer counts over the left ventricle, ascending aorta, and abdominal aorta and this has been previously validated by various researchers.[14][11]

More content to be added soon

Relation between AIF and TAC

An IDAIF obtained by measuring the tracer counts over the aorta[4], carodit artery[15], or radial artery[8] offers an alternative to invasive arterial blood sampling. An IDAIF at the aorta can be determined by measuring the tracer counts over the left ventricle, ascending aorta, and abdominal aorta and this has been previously validated by various researchers[10][4]. The arterial time-activity curve (TAC) from the image data requires corrections for metabolites formed over time, differences between whole blood and plasma activity, which are not constant over time, correction for partial volume errors (PVE) due to the small size of the ROI, spill-over errors due to activity from neighbouring tissues outside the ROI,[16] error due to patient movement, and noise introduced due to the limited number of counts acquired in each image time frame because of the short time frames. These errors are corrected using late venous blood samples,[4][10] and the resulting curve is called an arterial input function (AIF).

See also

References

  1. ^ HARVEY, RB (1962). "Renal extraction of para-aminohippurate and creatinine measured by continuous in vivo sampling of arterial and renal-vein blood". Ann N Y Acad Sci. 102: 46–54.
  2. ^ Herscovitch, P (1983). "Brain blood flow measured with intravenous H2(15)O. I. Theory and error analysis". J Nucl Med. 24(9): 782–9.
  3. ^ "Measurements of regional tissue and blood-pool radiotracer concentrations from serial tomographic images of the heart". J Nucl Med. 24(11): 987–96. 1983.
  4. ^ a b c d e f Cook, Gary J. R.; Lodge, Martin A.; Marsden, Paul K.; Dynes, Angela; Fogelman, Ignac (1999). "Non-invasive assessment of skeletal kinetics using fluorine-18 fluoride positron emission tomography: evaluation of image and population-derived arterial input functions". European Journal of Nuclear Medicine and Molecular Imaging. 26 (11): 1424–1429. doi:10.1007/s002590050474. ISSN 1619-7070.
  5. ^ Lui, Y.W.; Tang, E.R.; Allmendinger, A.M.; Spektor, V. (2010). "Evaluation of CT Perfusion in the Setting of Cerebral Ischemia: Patterns and Pitfalls". American Journal of Neuroradiology. 31 (9): 1552–1563. doi:10.3174/ajnr.a2026. ISSN 0195-6108.
  6. ^ Schabel, Matthias C. (2012-01-31). "A unified impulse response model for DCE-MRI". Magnetic Resonance in Medicine. 68 (5): 1632–1646. doi:10.1002/mrm.24162. ISSN 0740-3194.
  7. ^ Tanuj Puri, Sarah Wiscombe, Sally Marshall, John Simpson, Josephine Naish, Pete Thelwall. Changes in pulmonary vascular properties in a human model of acute lung injury measured using DCE-MRI, In 20th Annual Scientific Meeting of the British Chapter of International Society for Magnetic Resonance in Medicine (ISMRM), Edinburgh, UK, September 2014
  8. ^ a b Marques, Tiago Reis; Ashok, Abhishekh H.; Angelescu, Ilinca; Borgan, Faith; Myers, Jim; Lingford-Hughes, Anne; Nutt, David J.; Veronese, Mattia; Turkheimer, Federico E.; Howes, Oliver D. (2020-04-15). "GABA-A receptor differences in schizophrenia: a positron emission tomography study using [11C]Ro154513". Molecular Psychiatry. doi:10.1038/s41380-020-0711-y. ISSN 1359-4184.
  9. ^ Blake, Glen Mervyn; Siddique, Musib; Puri, Tanuj; Frost, Michelle Lorraine; Moore, Amelia Elizabeth; Cook, Gary James R.; Fogelman, Ignac (2012). "A semipopulation input function for quantifying static and dynamic 18F-fluoride PET scans:". Nuclear Medicine Communications. 33 (8): 881–888. doi:10.1097/MNM.0b013e3283550275. ISSN 0143-3636.
  10. ^ a b c Puri, Tanuj; Blake, Glen M.; Siddique, Musib; Frost, Michelle L.; Cook, Gary J.R.; Marsden, Paul K.; Fogelman, Ignac; Curran, Kathleen M. (2011). "Validation of new image-derived arterial input functions at the aorta using 18F-fluoride positron emission tomography:". Nuclear Medicine Communications. 32 (6): 486–495. doi:10.1097/MNM.0b013e3283452918. ISSN 0143-3636.
  11. ^ a b Cook, Gary J. R.; Lodge, Martin A.; Marsden, Paul K.; Dynes, Angela; Fogelman, Ignac (1999). "Non-invasive assessment of skeletal kinetics using fluorine-18 fluoride positron emission tomography: evaluation of image and population-derived arterial input functions". European Journal of Nuclear Medicine and Molecular Imaging. 26 (11): 1424–1429. doi:10.1007/s002590050474. ISSN 1619-7070.
  12. ^ Sari, Hasan; Erlandsson, Kjell; Law, Ian; Larsson, Henrik BW; Ourselin, Sebastien; Arridge, Simon; Atkinson, David; Hutton, Brian F (2017). "Estimation of an image derived input function with MR-defined carotid arteries in FDG-PET human studies using a novel partial volume correction method". Journal of Cerebral Blood Flow & Metabolism. 37 (4): 1398–1409. doi:10.1177/0271678X16656197. ISSN 0271-678X.
  13. ^ Marques, Tiago Reis; Ashok, Abhishekh H.; Angelescu, Ilinca; Borgan, Faith; Myers, Jim; Lingford-Hughes, Anne; Nutt, David J.; Veronese, Mattia; Turkheimer, Federico E.; Howes, Oliver D. (2020-04-15). "GABA-A receptor differences in schizophrenia: a positron emission tomography study using [11C]Ro154513". Molecular Psychiatry. doi:10.1038/s41380-020-0711-y. ISSN 1359-4184.
  14. ^ Puri, Tanuj; Blake, Glen M.; Siddique, Musib; Frost, Michelle L.; Cook, Gary J.R.; Marsden, Paul K.; Fogelman, Ignac; Curran, Kathleen M. (2011). "Validation of new image-derived arterial input functions at the aorta using 18F-fluoride positron emission tomography:". Nuclear Medicine Communications. 32 (6): 486–495. doi:10.1097/MNM.0b013e3283452918. ISSN 0143-3636.
  15. ^ Sari, Hasan; Erlandsson, Kjell; Law, Ian; Larsson, Henrik BW; Ourselin, Sebastien; Arridge, Simon; Atkinson, David; Hutton, Brian F (2017). "Estimation of an image derived input function with MR-defined carotid arteries in FDG-PET human studies using a novel partial volume correction method". Journal of Cerebral Blood Flow & Metabolism. 37 (4): 1398–1409. doi:10.1177/0271678X16656197. ISSN 0271-678X.
  16. ^ Nuyts, J (1996). "Three-Dimensional Correction for Spillover and Recovery of Myocardial PET Images". Journal of Nuclear Medicine. 37(5): 767–74.
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