Categorisation of tibial artery disease on computer tomography angiography according to the TASC II classification. (August 2017)

• Record Type: Journal Article
• Authors: Rehman, Adeeb; Antonietti, Alberto; Burnside, Girvan; Torella, Francesco
• Is Part Of: Vascular. Volume 25:Number 4(2017)
• Page Start: 402
• Page End: 405
• Publication Date: 2017-08
• Subjects: TASC II -- computer tomography angiography -- below the knee -- infra-popliteal -- peripheral vascular disease -- interobserver agreement; 616.13
• DOI: 10.1177/1708538116689176
• Languages: English
• ISSNs: 1708-5381

Abstract

Purpose: Computer tomography angiography is used to assess peripheral arterial disease. Its preference over other imaging modalities is based upon its rapid acquisition and high spatial resolution, along with ease of access. TASC II have recently updated their vascular lesion classification to include infrapopliteal lesions, and our aim is to assess the reproducibility of TASC II on infrapopliteal disease when using computer tomography angiography. Methods: A retrospective analysis of a series of consecutive computer tomography angiographies was performed by seven assessors (three consultant radiologists, two consultant vascular surgeons and two vascular specialty trainees). Each assessor was asked to classify the target vessel based on the TASC II classification. Statistical analysis was performed using Cohen's weighted kappa. Results: Seven assessors analysed 48 target vessels in 25 patients (20 men), with a mean age of 72.9 years. Twenty posterior tibial, 27 anterior tibial and one peroneal artery were analysed. Poor agreement was demonstrated between the two vascular consultants, with a kappa of 0.094. Weak agreement was demonstrated among the radiologists, with a kappa of 0.547. The total group of assessors had a kappa of 0.176. Conclusion: This study showed poor agreement between assessors when applying the TASC II classification to infrapopliteal lesions on computer tomography angiography. TASC II should not be used to classify lesions, for clinical or research purposes, with this image modality.