Structured Vascular Segment Analysis for Giant Cell Arteritis: A Proposed Scoring System for CT Angiography-Based...

Area of Science:

• Vascular Imaging
• Rheumatology
• Diagnostic Radiology

Background:

• Giant cell arteritis (GCA) diagnosis traditionally uses ultrasound, MRI, and nuclear medicine.
• Computed tomographic angiography (CTA) offers rapid, comprehensive assessment of neck vessels but lacks systematic evaluation for GCA.
• This study investigates CTA's utility in differentiating GCA patients from controls.

Purpose of the Study:

• To evaluate the diagnostic capability of CTA in distinguishing biopsy-proven GCA patients from age- and sex-matched controls.
• To assess cervical arterial abnormalities across multiple segments using CTA.
• To determine if CTA can serve as a valuable tool in GCA diagnosis.

Main Methods:

• Retrospective single-center study of 20 GCA patients and 20 controls.
• Two neuroradiologists independently assessed 21 arterial segments for abnormalities (wall thickening, stenosis, fat-stranding).
• Receiver operating characteristic (ROC) analysis and McNemar testing were used to evaluate performance.

Main Results:

• CTA demonstrated excellent discrimination between GCA patients and controls (AUC 0.971).
• High sensitivity (90%) and specificity (100%) were achieved at a total score threshold of ≥3.
• Maxillary, facial, and superficial temporal arteries showed the most frequent involvement in GCA patients.

Conclusions:

• Structured multi-segment CTA scoring effectively differentiates biopsy-proven GCA from controls.
• CTA is a promising and useful imaging modality for diagnosing GCA.
• Further validation supports CTA's role in the diagnostic workup of GCA.