# CT Imaging Biomarkers in Rhinogenic Contact Point Headache: Quantitative Phenotyping and Diagnostic Correlations

**Authors:** Salvatore Lavalle, Salvatore Ferlito, Jerome Rene Lechien, Mario Lentini, Placido Romeo, Alberto Maria Saibene, Gian Luca Fadda, Antonino Maniaci

PMC · DOI: 10.3390/jimaging11100362 · Journal of Imaging · 2025-10-14

## TL;DR

This study develops a CT imaging framework to diagnose rhinogenic contact point headache by identifying key anatomical markers and their correlation with pain severity.

## Contribution

A novel CT-based imaging framework for RCPH diagnosis with validated biomarkers and strong interobserver reliability.

## Key findings

- CP-I and CP-II are the most common contact point patterns in RCPH patients.
- Moderate CI, focal ME, and specific septal deviation patterns predict higher pain scores.
- The framework shows strong interobserver reliability (κ = 0.76–0.91).

## Abstract

Rhinogenic contact point headache (RCPH) represents a diagnostic challenge due to different anatomical presentations and unstandardized imaging markers. This prospective multicenter study involving 120 patients aimed to develop and validate a CT-based imaging framework for RCPH diagnosis. High-resolution CT scans were systematically assessed for seven parameters: contact point (CP) type, contact intensity (CI), septal deviation, concha bullosa (CB) morphology, mucosal edema (ME), turbinate hypertrophy (TH), and associated anatomical variants. Results revealed CP-I (37.5%) and CP-II (22.5%) as predominant patterns, with moderate CI (45.8%) and septal deviation > 15° (71.7%) commonly observed. CB was found in 54.2% of patients, primarily bulbous type (26.7%). Interestingly, focal ME at CP was independently associated with greater pain severity in the multivariate model (p = 0.003). The framework demonstrated substantial to excellent interobserver reliability (κ = 0.76–0.91), with multivariate analysis identifying moderate–severe CI, focal ME, and specific septal deviation patterns as independent predictors of higher pain scores. Our imaging classification system highlights key radiological biomarkers associated with symptom severity and may facilitate future applications in quantitative imaging, automated phenotyping, and personalized treatment approaches.

## Full-text entities

- **Diseases:** ME (MESH:D004487), TH (MESH:D006984), RCPH (MESH:D006261), pain (MESH:D010146), CB (MESH:D004820)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

16 references — full list in the complete paper: https://tomesphere.com/paper/PMC12565281/full.md

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Source: https://tomesphere.com/paper/PMC12565281