Skip to main content
An official website of the United States government
Principal Investigator
Catherine Daniela Chong
Awardee Organization

Mayo Clinic Arizona
United States

Fiscal Year
2024
Activity Code
R33
Early Stage Investigator Grants (ESI)
Not Applicable
Project End Date

Biomarker Signature to Predict the Persistence of Post-Traumatic Headache

There is currently no recognized way of accurately predicting who will recover from post-traumatic headache (PTH) during the acute phase following concussion and who will go on to develop persistent post-traumatic headache (PPTH), a condition that is difficult to treat effectively. Clinical experience with treating secondary headaches suggests that treatment is most effective when initiated early after headache onset, before headache patterns become persistent. So, why don't clinicians treat all patients with PTH acutely following concussion? Although it is likely to be beneficial to treat those patients who are at high risk for PPTH as early as possible, medication side effects and toxicities make it potentially harmful to administer unnecessary medication to those patients who would recover on their own without treatment. The inability to identify which concussed patients with acute PTH are at high risk for PTH persistence leaves clinicians without the knowledge needed to make informed decisions regarding how aggressive to manage patients with acute PTH. Study Goal: to develop a prognostic biomarker signature for PPTH using clinical data as well as structural and functional brain neuroimaging and to assess the predictive accuracy of an ensemble biomarker signature for the early identification of patients at high risk for PTH persistence. The accurate prediction of individuals who are at high risk for PTH persistence would allow clinicians to recommend early and more aggressive management with the intention of preventing PTH persistence. A predictive model for PPTH could also guide clinical trials that will test the utility of innovative therapies to prevent PPTH by allowing for enrichment of the subject cohort with patients at high risk of PPTH. R61 Phase: During the R61 phase this study will develop brain imaging and clinical feature prognostic biomarker signatures for PPTH using machine-learning algorithms. The imaging and clinical biomarker signatures will be developed by laboratories that will first work in-parallel, and then the laboratories will combine the neuroimaging and clinical biomarkers using an ensemble approach. Results of this study will determine important clinical factors (e.g. demographics, medical history, brain injury characteristics, headache characteristics, speech patterns) and brain imaging markers (e.g. regional volumes, cortical thickness, white matter tract integrity, perfusion, functional connectivity) for predicting PTH persistence Additionally, the predictive weight of specific clinical factors and neuroimaging features for characterizing patients who are at higher risk for developing PPTH will be determined. R33 Phase: Once the predictive weights of clinical factors and neuroimaging features are determined, the clinical testing battery and neuroimaging sequences can be pruned down and optimized to include only those that have high predictive power for PPTH. The scanning sequences used in this study are commonly available MRI sequences, making their use feasible across healthcare centers. This optimized and shortened testing sequence can be translated into clinical practice and integrated into PTH clinical trials for early identification of those individuals who are at high risk for PTH persistence.

Publications

  • Nikolova S, Schwedt TJ, Li J, Wu T, Dumkrieger GM, Ross KB, Berisha V, Chong CD. T2* reduction in patients with acute post-traumatic headache. Cephalalgia : an international journal of headache. 2022 Apr;42(4-5):357-365. Epub 2021 Oct 13. PMID: 34644192
  • Mao L, Dumkrieger G, Ku D, Ross K, Berisha V, Schwedt TJ, Li J, Chong CD. Developing multivariable models for predicting headache improvement in patients with acute post-traumatic headache attributed to mild traumatic brain injury: A preliminary study. Headache. 2023 Jan;63(1):136-145. Epub 2023 Jan 18. PMID: 36651586
  • Smith DC, Zhang J, Jayasuriya S, Berisha V, Starling A, Schwedt TJ, Chong CD. The impact of headache intensity on speech in participants with migraine and acute post-traumatic headache. Headache. 2025 Mar;65(3):506-515. Epub 2024 Aug 28. PMID: 39194058
  • Nikolova S, Chong C, Li J, Wu T, Dumkrieger G, Esterov D, Ross K, Starling A, Thomas A, Leonard M, Smith D, Schwedt TJ. Periaqueductal gray functional connectivity abnormalities associated with acute post-traumatic headache. Journal of neurology. 2025 Apr 23;272(5):356. PMID: 40266360
  • Rahman Siddiquee MM, Shah J, Chong C, Nikolova S, Dumkrieger G, Li B, Wu T, Schwedt TJ. Headache classification and automatic biomarker extraction from structural MRIs using deep learning. Brain communications. 2022 Nov 26;5(1):fcac311. doi: 10.1093/braincomms/fcac311. eCollection 2023. PMID: 36751567
  • Nikolova S, Chong CD, Dumkrieger GM, Li J, Wu T, Schwedt TJ. Longitudinal differences in iron deposition in periaqueductal gray matter and anterior cingulate cortex are associated with response to erenumab in migraine. Cephalalgia : an international journal of headache. 2023 Feb;43(2):3331024221144783. PMID: 36756979
  • Chong CD, Zhang J, Li J, Wu T, Dumkrieger G, Nikolova S, Ross K, Stegmann G, Liss J, Schwedt TJ, Jayasuriya S, Berisha V. Altered speech patterns in subjects with post-traumatic headache due to mild traumatic brain injury. The journal of headache and pain. 2021 Jul 23;22(1):82. PMID: 34301180
  • Siddiquee MMR, Shah J, Wu T, Chong C, Schwedt T, Li B. HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human Disease. Simulation and synthesis in medical imaging : ... International Workshop, SASHIMI ..., held in conjunction with MICCAI ..., proceedings. SASHIMI (Workshop). 2022 Sep;13570:43-54. Epub 2022 Sep 21. PMID: 38694707
  • Braunecker BJ, Smith D, Dodoo CA, Schwedt TJ, Chong CD. Insomnia symptoms amongst those with acute post-traumatic headache attributed to mild traumatic brain injury. Headache. 2025 Jun 11. Epub 2025 Jun 11. PMID: 40497559
  • Mao L, Li J, Schwedt TJ, Wu T, Ross K, Dumkrieger G, Smith DC, Chong CD. Identifying and predicting headache trajectories among those with acute post-traumatic headache. Headache. 2025 Jul-Aug;65(7):1124-1133. Epub 2025 May 30. PMID: 40444600
  • Chong CD, Nikolova S, Dumkrieger G, Wu T, Berisha V, Li J, Ross K, Schwedt TJ. Thalamic subfield iron accumulation after acute mild traumatic brain injury as a marker of future post-traumatic headache intensity. Headache. 2023 Jan;63(1):156-164. Epub 2023 Jan 18. PMID: 36651577
  • Siddiquee MMR, Shah J, Wu T, Chong C, Schwedt TJ, Dumkrieger G, Nikolova S, Li B. Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR Images. IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision. 2024 Jan;2024:7558-7567. Epub 2024 Apr 9. PMID: 38720667
  • Nikolova S, Chong C, Li J, Wu T, Dumkrieger G, Ross K, Starling A, Schwedt TJ. Brain Structural and Functional Abnormalities Associated with Acute Post-Traumatic Headache: Iron Deposition and Functional Connectivity. Research square. 2024 Mar 28. PMID: 38585756
  • Nikolova S, Chong C, Li J, Wu T, Dumkrieger G, Ross K, Starling A, Schwedt TJ. Brain structural and functional abnormalities associated with acute post-traumatic headache: iron deposition and functional connectivity. The journal of headache and pain. 2024 May 28;25(1):88. PMID: 38807070