High‐Frequency Ultrasonography Evaluation of Acne by Thickness and Power Doppler Vascular Analysis

医学 痤疮 病变 超声科 功率多普勒 超声波 核医学 皮肤病科 放射科 外科
作者
Xuanyin Wu,Tianan Jiang
出处
期刊:Journal of Ultrasound in Medicine [Wiley]
卷期号:41 (10): 2517-2525 被引量:3
标识
DOI:10.1002/jum.15941
摘要

Objectives To assess acne vulgaris quantitatively using high‐frequency ultrasonography (HF‐USG) and power Doppler (PD), and investigate the feasibility and application value of HF‐USG and PD in acne vulgaris. Methods A total of 105 patients with the diagnosis of acne vulgaris in the face referred by a dermatologist were studied prospectively. All the acne patients enrolled were clinically classified by two attending dermatologists independently using three degrees with four levels of classification evaluating only the severest lesion. Gray‐scale ultrasound was used to assess the thickness of the lesion, and the thickness ratio was calculated. PD equipped with Qpack semi‐quantitative analysis software was used to assess blood signals of the lesion, and Qpack ratio, Qpack peak were calculated. Ten level‐4 acne patients were re‐evaluated after 2 weeks' treatment, and the results were compared with those before treatment. Results A total of 105 patients were categorized into four groups by dermatologists, 23 cases were comedones, 33 were papules, 26 were pustules, and 23 were nodules/cysts. There were significant differences in thickness ratio ( P < .001), Qpack ratio ( P < .001), and Qpack peak ( P < .001) among the four groups. For the 10 level‐4 acne patients treated 2 weeks by the dermatologist, the difference in thickness ratio between pre‐treatment and post‐treatment showed no significance ( P = .06). However, Qpack ratio and Qpack peak were significantly decreased between pre‐treatment and post‐treatment (both P = .01). Conclusions HF‐USG and PD equipped with semi‐quantitative analysis software can assess acne vulgaris quantitatively, which provides a good basis for the classification and treatment of acne. Their features include thickness ratio, Qpack ratio, and Qpack peak, with Qpack ratio and Qpack peak being the sensitive features for the early efficacy evaluation.
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