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Related Experiment Video

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Patterning via Optical Saturable Transitions - Fabrication and Characterization
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Characterizing the Structural Pattern Predicting Medication Response in Herpes Zoster Patients Using Multivoxel

Ping Zeng1,2, Jiabin Huang3, Songxiong Wu1,2

  • 1School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.

Frontiers in Neuroscience
|June 14, 2019
PubMed
Summary
This summary is machine-generated.

Brain imaging can predict how well Herpes zoster (HZ) patients respond to medication. Structural MRI and pattern analysis identified brain regions associated with poor treatment outcomes, aiding personalized pain management.

Keywords:
herpes zostermedication responsemultivoxel pattern analysispredictionstructural MRI

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Area of Science:

  • Neuroimaging
  • Neurology
  • Pain Medicine

Background:

  • Herpes zoster (HZ) causes neuropathic pain, often in elderly or immunocompromised individuals.
  • Current pharmacotherapy for HZ can lead to side effects or intractable post-herpetic neuralgia (PHN).
  • Predicting medication response in HZ patients is challenging due to limited understanding of underlying neurological factors.

Purpose of the Study:

  • To characterize brain structural patterns in HZ patients before treatment.
  • To identify neuroanatomical biomarkers that predict medication response in HZ.
  • To explore the utility of structural MRI and MVPA for HZ pain management.

Main Methods:

  • Structural MRI scans were acquired from HZ patients with poor and good medication responses.
  • Multivoxel pattern analysis (MVPA) with a searchlight algorithm and SVM identified gray matter (GM) volume patterns.
  • Analysis focused on identifying predictive regions with accuracy exceeding 79%.

Main Results:

  • Predictive regions included the cerebellum, posterior insular cortex (pIC), frontal lobes (mFC, OFC), cingulum (ACC, MCC), precuneus (PCu), and cuneus.
  • Increased GM volumes in mFC, pIC, and MCC were associated with poor medication response.
  • High predictive accuracy ( >79%) was achieved in identifying these brain regions.

Conclusions:

  • Structural MRI combined with MVPA can identify neuroanatomical biomarkers for HZ-related pain.
  • These biomarkers may help predict patient response to pharmacotherapy.
  • This approach could aid in tailoring HZ treatment and improving patient outcomes.