Prognostic Utility of Arterial Spin Labeling in Traumatic Brain Injury: From Pathophysiology to Precision Imaging
Abstract
1. Introduction
2. Epidemiology, Socioeconomic Impact, and the Need for Biomarkers in TBI
3. Pathophysiology of Cerebral Blood Flow After Traumatic Brain Injury
4. Injury
5. Methods
6. ASL Techniques and Quantitative Parameters
- Labeling duration (τ): commonly 1.5–2.0 s for pCASL;
- Post-labeling delay (PLD): typically, 1.5–2.0 s in adults, adjusted in pediatric or vascular-compromised populations;
- T1 of blood (T1b): ~1650 ms at 3T;
- Labeling efficiency (α): 0.85–0.95 for pCASL, lower in PASL;
- M0 reference image: used to normalize signal to absolute CBF (ml/100 g/min).
7. Technical Limitations and Artifacts
8. Prognostic Value of Arterial Spin Labeling in Traumatic Brain Injury
9. Integrative Prognostic Models in TBI and Future Directions
10. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Esterov, D.; Bellamkonda, E.; Mandrekar, J.; Ransom, J.E.; Brown, A.W. Cause of Death after Traumatic Brain Injury: A Population-Based Health Record Review Analysis Referenced for Nonhead Trauma. Neuroepidemiology 2021, 55, 180–187. [Google Scholar] [CrossRef] [PubMed]
- Zhong, H.; Feng, Y.; Shen, J.; Rao, T.; Dai, H.; Zhong, W.; Zhao, G. Global Burden of Traumatic Brain Injury in 204 Countries and Territories From 1990 to 2021. Am. J. Prev. Med. 2025, 68, 754–763. [Google Scholar] [CrossRef] [PubMed]
- Chen, Y.; Wang, S.; Xu, S.; Xu, N.; Zhang, L.; Zhou, J. Current advances in neurocritical care. J. Intensiv. Med. 2024, 5, 23–31. [Google Scholar] [CrossRef] [PubMed]
- Yen, C.; Lin, C.-L.; Chiang, M.-C. Exploring the Frontiers of Neuroimaging: A Review of Recent Advances in Understanding Brain Functioning and Disorders. Life 2023, 13, 1472. [Google Scholar] [CrossRef]
- Brody, D.L.; Mac Donald, C.L.; Shimony, J.S. Chapter 17—Current and future diagnostic tools for traumatic brain injury: CT, conventional MRI, and diffusion tensor imaging. In Handbook of Clinical Neurology; Grafman, J., Salazar, M.A., Eds.; Elsevier: Amsterdam, The Netherlands, 2015; Volume 127, pp. 267–275. [Google Scholar] [CrossRef]
- Grade, M.; Tamames, J.A.H.; Pizzini, F.B.; Achten, E.; Golay, X.; Smits, M. A neuroradiologist’s guide to arterial spin labeling MRI in clinical practice. Neuroradiology 2015, 57, 1181–1202. [Google Scholar] [CrossRef]
- Günther, M.; Bock, M.; Schad, L.R. Arterial spin labeling in combination with a look-locker sampling strategy: Inflow turbo-sampling EPI-FAIR (ITS-FAIR). Magn. Reson. Med. 2001, 46, 974–984. [Google Scholar] [CrossRef]
- Fantini, S.; Sassaroli, A.; Tgavalekos, K.T.; Kornbluth, J. Cerebral blood flow and autoregulation: Current measurement techniques and prospects for noninvasive optical methods. Neurophotonics 2016, 3, 031411. [Google Scholar] [CrossRef]
- Maas, A.I.R.; Stocchetti, N.; Bullock, R. Moderate and severe traumatic brain injury in adults. Lancet Neurol. 2008, 7, 728–741. [Google Scholar] [CrossRef]
- Povlishock, J.T. Traumatically Induced Axonal Injury: Pathogenesis and Pathobiological Implications. Brain Pathol. 1991, 2, 1–12. [Google Scholar] [CrossRef]
- Miller, G.F.; Daugherty, J.; Waltzman, D.; Sarmiento, K. Predictors of traumatic brain injury morbidity and mortality: Examination of data from the national trauma data bank. Injury 2021, 52, 1138–1144. [Google Scholar] [CrossRef]
- van Breugel, J.M.M.; Niemeyer, M.J.S.; Houwert, R.M.; Groenwold, R.H.H.; Leenen, L.P.H.; van Wessem, K.J.P. Global changes in mortality rates in polytrauma patients admitted to the ICU—A systematic review. World J. Emerg. Surg. 2020, 15, 55. [Google Scholar] [CrossRef]
- Amoo, M.; Henry, J.; O’hAlloran, P.J.; Brennan, P.; Ben Husien, M.; Campbell, M.; Caird, J.; Javadpour, M.; Curley, G.F. S100B, GFAP, UCH-L1 and NSE as predictors of abnormalities on CT imaging following mild traumatic brain injury: A systematic review and meta-analysis of diagnostic test accuracy. Neurosurg. Rev. 2021, 45, 1171–1193. [Google Scholar] [CrossRef]
- Freire, M.A.M.; Rocha, G.S.; Bittencourt, L.O.; Falcao, D.; Lima, R.R.; Cavalcanti, J.R.L.P. Cellular and Molecular Pathophysiology of Traumatic Brain Injury: What Have We Learned So Far? Biology 2023, 12, 1139. [Google Scholar] [CrossRef]
- Armstead, W.M. Cerebral Blood Flow Autoregulation and Dysautoregulation. Anesthesiol. Clin. 2016, 34, 465–477. [Google Scholar] [CrossRef]
- Rostami, E.; Engquist, H.; Enblad, P. Imaging of Cerebral Blood Flow in Patients with Severe Traumatic Brain Injury in the Neurointensive Care. Front. Neurol. 2014, 5, 114. [Google Scholar] [CrossRef]
- Kunz, A.; Iadecola, C. Chapter 14 Cerebral vascular dysregulation in the ischemic brain. In Handbook of Clinical Neurology; Fisher, M., Ed.; Elsevier: Amsterdam, The Netherlands, 2008; Volume 92, pp. 283–305. [Google Scholar] [CrossRef]
- Hoiland, R.L.; Bain, A.R.; Rieger, M.G.; Bailey, D.M.; Ainslie, P.N. Hypoxemia, oxygen content, and the regulation of cerebral blood flow. Am. J. Physiol. Integr. Comp. Physiol. 2016, 310, R398–R413. [Google Scholar] [CrossRef]
- Roy, T.K.; Secomb, T.W. Effects of impaired microvascular flow regulation on metabolism-perfusion matching and organ function. Microcirculation 2020, 28, e12673. [Google Scholar] [CrossRef] [PubMed]
- Huang, X.; Hussain, B.; Chang, J. Peripheral inflammation and blood–brain barrier disruption: Effects and mechanisms. CNS Neurosci. Ther. 2020, 27, 36–47. [Google Scholar] [CrossRef] [PubMed]
- Bouzat, P.; Sala, N.; Payen, J.-F.; Oddo, M. Beyond intracranial pressure: Optimization of cerebral blood flow, oxygen, and substrate delivery after traumatic brain injury. Ann. Intensiv. Care 2013, 3, 23. [Google Scholar] [CrossRef]
- Woods, J.G.; Schauman, S.S.; Chiew, M.; Chappell, M.A.; Okell, T.W. Time-encoded pseudo-continuous arterial spin labeling: Increasing SNR in ASL dynamic angiography. Magn. Reson. Med. 2022, 89, 1323–1341. [Google Scholar] [CrossRef]
- Alsop, D.C.; Detre, J.A.; Golay, X.; Günther, M.; Hendrikse, J.; Hernandez-Garcia, L.; Lu, H.; MacIntosh, B.; Parkes, L.M.; Smits, M.; et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: A consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn. Reson. Med. 2015, 73, 102–116. [Google Scholar] [CrossRef] [PubMed]
- Liu, T.T.; Wong, E.C.; Bolar, D.S.; Chen, C.; Barnes, R.S. A mathematical model for velocity-selective arterial spin labeling. Magn. Reson. Med. 2024, 91, 1384–1403. [Google Scholar] [CrossRef] [PubMed]
- Faraco, C.C.; Strother, M.K.; Dethrage, L.M.; Jordan, L.; Singer, R.; Clemmons, P.F.; Donahue, M.J. Dual echo vessel-encoded ASL for simultaneous BOLD and CBF reactivity assessment in patients with ischemic cerebrovascular disease. Magn. Reson. Med. 2014, 73, 1579–1592. [Google Scholar] [CrossRef] [PubMed]
- Buxton, R.B.; Frank, L.R.; Wong, E.C.; Siewert, B.; Warach, S.; Edelman, R.R. A general kinetic model for quantitative perfusion imaging with arterial spin labeling. Magn. Reson. Med. 1998, 40, 383–396. [Google Scholar] [CrossRef]
- Chappell, M.A.; Groves, A.R.; Whitcher, B.; Woolrich, M.W. Variational Bayesian Inference for a Nonlinear Forward Model. IEEE Trans. Signal Process. 2008, 57, 223–236. [Google Scholar] [CrossRef]
- Adebimpe, A.; Bertolero, M.; Dolui, S.; Cieslak, M.; Murtha, K.; Baller, E.B.; Boeve, B.; Boxer, A.; Butler, E.R.; Cook, P.; et al. ASLPrep: A platform for processing of arterial spin labeled MRI and quantification of regional brain perfusion. Nat. Methods 2022, 19, 683–686. [Google Scholar] [CrossRef]
- Detre, J.A.; Rao, H.; Wang, D.J.; Chen, Y.F.; Wang, Z. Applications of arterial spin labeled MRI in the brain. J. Magn. Reson. Imaging 2012, 35, 1026–1037. [Google Scholar] [CrossRef]
- Haller, S.; Zaharchuk, G.; Thomas, D.L.; Lovblad, K.-O.; Barkhof, F.; Golay, X. Arterial Spin Labeling Perfusion of the Brain: Emerging Clinical Applications. Radiology 2016, 281, 337–356. [Google Scholar] [CrossRef]
- Petersen, E.T.; Zimine, I.; Ho, Y.-C.L.; Golay, X. Non-invasive measurement of perfusion: A critical review of arterial spin labelling techniques. Br. J. Radiol. 2006, 79, 688–701. [Google Scholar] [CrossRef]
- Zhang, N.; Gordon, M.L.; Goldberg, T.E. Cerebral blood flow measured by ASL MRI at resting state in normal aging and Alzhimer’s disease. Neurosci. Biobehav. Rev. 2017, 72, 168–175. [Google Scholar] [CrossRef]
- Mutsaerts, H.J.; Petr, J.; Groot, P.; Vandemaele, P.; Ingala, S.; Robertson, A.D.; Václavů, L.; Groote, I.; Kuijf, H.; Zelaya, F.; et al. ExploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies. NeuroImage 2020, 219, 117031. [Google Scholar] [CrossRef]
- Dolui, S.; Vidorreta, M.; Wang, Z.; Nasrallah, I.M.; Alavi, A.; Wolk, D.A.; Detre, J.A. Comparison of PASL, PCASL, and background-suppressed 3D PCASL in mild cognitive impairment. Hum. Brain Mapp. 2017, 38, 5260–5273. [Google Scholar] [CrossRef] [PubMed]
- Anwar, U.; Arslan, T.; Lomax, P. Cerebral Blood Flow Monitoring with a Portable Radio Frequency Sensing System. In Proceedings of the 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 15–19 July 2024; pp. 1–5. [Google Scholar]
- Kelly, D.F.; Kordestani, R.K.; Martin, N.A.; Nguyen, T.; Hovda, D.A.; Bergsneider, M.; McArthur, D.L.; Becker, D.P. Hyperemia following traumatic brain injury: Relationship to intracranial hypertension and outcome. J. Neurosurg. 1996, 85, 762–771. [Google Scholar] [CrossRef] [PubMed]
- Ware, J.B.; Dolui, S.; Duda, J.; Gaggi, N.; Choi, R.; Detre, J.A.; Whyte, J.; Diaz-Arrastia, R.; Kim, J.J. Relationship of Cerebral Blood Flow to Cognitive Function and Recovery in Early Chronic Traumatic Brain Injury. J. Neurotrauma 2020, 37, 2180–2187. [Google Scholar] [CrossRef] [PubMed]
- Ding, K.; Tarumi, T.; Tomoto, T.; Mccolloster, M.; Le, T.; Dieppa, M.; Diaz-Arrastia, R.; Bell, K.; Madden, C.; Cullum, C.M.; et al. Impaired cerebral blood flow regulation in chronic traumatic brain injury. Brain Res. 2020, 1743, 146924. [Google Scholar] [CrossRef]
- Thomas, B.P.; Tarumi, T.; Wang, C.; Zhu, D.C.; Tomoto, T.; Cullum, C.M.; Dieppa, M.; Diaz-Arrastia, R.; Bell, K.; Madden, C.; et al. Hippocampal and rostral anterior cingulate blood flow is associated with affective symptoms in chronic traumatic brain injury. Brain Res. 2021, 1771, 147631. [Google Scholar] [CrossRef]
- Wang, Z.; Shen, Y.; Zhang, X.; Li, Q.; Dong, C.; Wang, S.; Sun, H.; Chen, M.; Xu, X.; Pan, P.; et al. Prognostic value of multi-PLD ASL radiomics in acute ischemic stroke. Front. Neurol. 2025, 15, 1544578. [Google Scholar] [CrossRef]
- Qin, Q.; Alsop, D.C.; Bolar, D.S.; Hernandez-Garcia, L.; Meakin, J.; Liu, D.; Nayak, K.S.; Schmid, S.; van Osch, M.J.P.; Wong, E.C.; et al. Velocity-selective arterial spin labeling perfusion MRI: A review of the state of the art and recommendations for clinical implementation. Magn. Reson. Med. 2022, 88, 1528–1547. [Google Scholar] [CrossRef]
- Qin, Q.; van Zijl, P.C. Velocity-selective-inversion prepared arterial spin labeling. Magn. Reson. Med. 2015, 76, 1136–1148. [Google Scholar] [CrossRef]
- Gaggi, N.L.; Ware, J.B.; Dolui, S.; Brennan, D.; Torrellas, J.; Wang, Z.; Whyte, J.; Diaz-Arrastia, R.; Kim, J.J. Temporal dynamics of cerebral blood flow during the first year after moderate-severe traumatic brain injury: A longitudinal perfusion MRI study. NeuroImage Clin. 2023, 37, 103344. [Google Scholar] [CrossRef]
- MRC CRASH Trial Collaborators; Perel, P.; Arango, M.; Clayton, T.; Edwards, P.; Komolafe, E.; Poccock, S.; Roberts, I.; Shakur, H.; Steyerberg, E.; et al. Predicting outcome after traumatic brain injury: Practical prognostic models based on large cohort of international patients. BMJ 2008, 336, 425–429. [Google Scholar] [CrossRef]
- Steyerberg, E.W.; Mushkudiani, N.; Perel, P.; Butcher, I.; Lu, J.; McHugh, G.S.; Murray, G.D.; Marmarou, A.; Roberts, I.; Habbema, J.D.F.; et al. Predicting Outcome after Traumatic Brain Injury: Development and International Validation of Prognostic Scores Based on Admission Characteristics. PLoS Med. 2008, 5, e165. [Google Scholar] [CrossRef]
- The CRASH trial management group The CRASH trial protocol (Corticosteroid randomisation after significant head injury) [74459797]. BMC Emerg. Med. 2001, 1, 1. [CrossRef]
- Luciw, N.J.; Shirzadi, Z.; Black, S.E.; Goubran, M.; MacIntosh, B.J. Automated generation of cerebral blood flow and arterial transit time maps from multiple delay arterial spin-labeled MRI. Magn. Reson. Med. 2022, 88, 406–417. [Google Scholar] [CrossRef] [PubMed]
- Fatima, S.; Hussain, A.; Bin Amir, S.; Ahmed, S.H.; Aslam, S.M.H. XGBoost and Random Forest Algorithms: An in Depth Analysis. Pak. J. Sci. Res. 2023, 3, 26–31. [Google Scholar] [CrossRef]
- Rainio, O.; Teuho, J.; Klén, R. Evaluation metrics and statistical tests for machine learning. Sci. Rep. 2024, 14, 6086. [Google Scholar] [CrossRef] [PubMed]
- McCrea, M.A.; Giacino, J.T.; Barber, J.; Temkin, N.R.; Nelson, L.D.; Levin, H.S.; Dikmen, S.; Stein, M.; Bodien, Y.G.; Boase, K.; et al. Functional Outcomes Over the First Year After Moderate to Severe Traumatic Brain Injury in the Prospective, Longitudinal TRACK-TBI Study. JAMA Neurol. 2021, 78, 982–992. [Google Scholar] [CrossRef]
- Pavlovic, D.; Pekic, S.; Stojanovic, M.; Popovic, V. Traumatic brain injury: Neuropathological, neurocognitive and neurobehavioral sequelae. Pituitary 2019, 22, 270–282. [Google Scholar] [CrossRef]
- Stein, S.C.; Burnett, M.G.; Glick, H.A. Indications for CT Scanning in Mild Traumatic Brain Injury: A Cost-Effectiveness Study. J. Trauma Inj. Infect. Crit. Care 2006, 61, 558–566. [Google Scholar] [CrossRef]
Biomarker | Primary Utility | Notes |
---|---|---|
GFAP (Glial Fibrillary Acidic Protein) | Detection of brain lesions, even in CT-negative patients | Useful in early diagnosis and triage |
S100B | Reduces unnecessary CT imaging in mild TBI | High sensitivity; recommended in Scandinavian guidelines |
NF-L (Neurofilament Light) | Monitoring of axonal injury | Elevated in both acute and chronic phases of TBI |
Tau | Indicator of neurodegenerative processes | Linked to chronic outcomes and repetitive mild TBI |
GFAP + UCH-L1 | FDA-approved combination for identifying intracranial lesions in mild TBI | Superior diagnostic accuracy compared to single markers |
ASL Technique | Labeling Method | Typical PLD | Vendors | Advantages | Disadvantages | TBI Application |
---|---|---|---|---|---|---|
pCASL | Pseudocontinuous arterial spin labeling | 1800–2000 ms | Siemens, GE, Philips, Canon, United Imaging | Clinical standard; widely available; absolute CBF quantification | Sensitive to ATT variability; requires accurate hardware calibration | Widely used in clinical TBI for CBF quantification |
PASL | Pulsed ASL (FAIR/QUIPSS II/PICORE) | 800–1500 ms | Siemens, GE | Short scan times; simple to implement; useful in pediatrics and subacute settings | Low SNR; sensitive to motion and transit time artifacts | Used in pediatric and subacute TBI studies |
VSASL | Velocity-selective labeling (velocity-dependent) | N/A | Research-only; limited commercial availability | Insensitive to ATT; useful in low/variable flow (e.g., severe TBI) | Lower spatial resolution; higher noise sensitivity; experimental | Best for acute/severe TBI with delayed or variable blood flow |
Multi-PLD ASL | pCASL with multiple post-labeling delays | 200–2500 ms | Siemens, Philips, GE (research platforms) | Enables simultaneous CBF and ATT estimation; accurate in heterogeneous perfusion | Longer acquisition time; complex post-processing | Ideal for chronic TBI with heterogeneous perfusion profiles |
Dual-echo ASL | Combined ASL and BOLD acquisition | Variable | GE, Siemens, Philips (experimental) | Simultaneous acquisition of perfusion and functional BOLD signal | Experimental; lower perfusion specificity | Applied in cognitive/task-based studies in chronic TBI |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
De Rosa, S.; Carton, F.; Grecucci, A.; Feraco, P. Prognostic Utility of Arterial Spin Labeling in Traumatic Brain Injury: From Pathophysiology to Precision Imaging. NeuroSci 2025, 6, 73. https://doi.org/10.3390/neurosci6030073
De Rosa S, Carton F, Grecucci A, Feraco P. Prognostic Utility of Arterial Spin Labeling in Traumatic Brain Injury: From Pathophysiology to Precision Imaging. NeuroSci. 2025; 6(3):73. https://doi.org/10.3390/neurosci6030073
Chicago/Turabian StyleDe Rosa, Silvia, Flavia Carton, Alessandro Grecucci, and Paola Feraco. 2025. "Prognostic Utility of Arterial Spin Labeling in Traumatic Brain Injury: From Pathophysiology to Precision Imaging" NeuroSci 6, no. 3: 73. https://doi.org/10.3390/neurosci6030073
APA StyleDe Rosa, S., Carton, F., Grecucci, A., & Feraco, P. (2025). Prognostic Utility of Arterial Spin Labeling in Traumatic Brain Injury: From Pathophysiology to Precision Imaging. NeuroSci, 6(3), 73. https://doi.org/10.3390/neurosci6030073