The association between sonographic features and clinical symptoms of adenomyosis

Author:

Maldutytė Gailė1ORCID,Opolskienė Gina23ORCID,Rudaitis Vilius23ORCID,Ramašauskaitė Diana23ORCID

Affiliation:

1. Department of Gynecology Republican Vilnius University Hospital Vilnius Lithuania

2. Clinic of Obstetrics and Gynecology, Institute of Clinical Medicine, Faculty of Medicine Vilnius University Vilnius Lithuania

3. Center of Obstetrics and Gynecology Vilnius University Hospital Santaros Clinics Vilnius Lithuania

Abstract

AbstractPurposeTo investigate the association of sonographic features and clinical symptoms of adenomyosis.MethodsThis was a prospective observational study. Only reproductive age women who underwent standardized transvaginal ultrasound examination were included. The diagnosis of adenomyosis was based on sonographic features proposed by Morphological Uterus Sonographic Assessment (MUSA) group. Pictorial blood loss assessment chart (PBAC) and numerical rating scale (NRS) were respectively used for the evaluation of menstrual bleeding and pain.ResultsFifty‐three women were recruited. Adenomyosis group consisted of 33 (62.3%) representative cases, whereas control group consisted of 20 (37.7%). Women with adenomyosis experienced significantly heavier menstrual bleeding (p = 0.008) and more painful menstrual periods (p = 0.003). Significant positive correlation between the number of sonographic adenomyosis features and both PBAC (r = 0.613, p < 0.001) and NRS scores (r = 0.402, p = 0.022) was found. PBAC score was significantly higher if either fan‐shaped shadowing (r = 0.548, p = 0.001), interrupted junctional zone (JZ) (r = 0.548, p = 0.001) or globular uterus (r = 0.445, p = 0.011) was detected. Interrupted JZ (r = 0.440, p = 0.012) was associated with higher NRS score. Significant positive correlation between PBAC score and adenomyosis spread in uterine layers (r = 0.495, p = 0.004) was established.ConclusionCertain sonographic features of adenomyosis and assessment of its involvement in uterine layers may predict the severity of adenomyosis symptoms.

Publisher

Wiley

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