DISCUSSION:
Main Findings:
We assessed clinical and MRI parameters for their potential to predict
histopathological adenomyosis diagnosis prior to hysterectomy. The
resultant multivariate prediction model discriminates well between
patients with and without adenomyosis (AUC 0.776). Five clinical
characteristics: age at MRI, BMI, history of curettage, dysmenorrhoea,
and AUB, and four primary MRI parameters: mean JZ thickness, JZ Diff ≥5
mm, JZ/MYO >.40, and the presence of HSI foci are included.
Strengths and Limitations:
This study has several strengths and limitations that merit
consideration. A strength of our study is that two researchers
independently reviewed all pelvic MRIs blinded to the histopathology
outcome. Furthermore, the proposed model was built on data of 296
patients and data driven variable selection was avoided, along with
corrections for potential overfitting. Additionally, the combination of
both clinical and MRI parameters makes this model easily implementable
into daily clinical practise.
The present study used broad inclusion criteria, which could be
interpreted as both a strength and limitation. On the one hand,
inclusion of patients with comorbidities like uterine fibroids might
have prevented an overestimation of diagnostic performance of the
individual potential predictors. Alternatively, severe distortion of the
uterus due to fibroids or endometriosis can limit the ability for
objective assessment of all MRI parameters.
One limitation of the current study is that it was not possible to
correct for the influence of the menstrual cycle on MRI parameters.
Although it is known that JZ thickness changes during the menstrual
cycle 25, cycle phase at time of MRI was not reported
for most of our patients. Furthermore, the choice for histopathology
after hysterectomy as a reference standard introduces an element of
selection bias. Potentially, our group consisted of women with more
severe adenomyosis and thus may have affected the general phenotype. The
present study did not conduct a central review of pathology however, and
(histological) adenomyosis severity was generally not reported in
pathology reports. Therefore this remains hypothetical.
Interpretation of findings:
To the best of our knowledge, no comparable models for histopathological
adenomyosis diagnosis based on MRI exist. Previous studies have
investigated prediction of adenomyosis diagnosis based on ultrasound,
with comparable accuracy 9,11,26. However, it is known
that ultrasound diagnosis is highly operator dependent, with varying
inter- and intra-observer variability 8,27,28. An MRI
prediction model such as developed in our study thus has clinical value
especially in cases where adenomyosis co-exists with other pathology (as
was the case in the majority of our included patients), or is mild, or
atypical.
The parameters ultimately included in this model are unsurprising when
considering reported adenomyosis clinical presentation and aetiology.
Dysmenorrhoea and AUB are the most frequently reported symptoms of
adenomyosis 4,29 and were thus logical (and
statistically significant) additions to the model. Age at MRI was
further included in the model due to the known physiological increase in
JZ thickness with age 25,30,31. BMI was also manually
entered into the model as, despite univariate analysis showing no
significant association, increased body weight and obesity have been
reported as strong risk factors for adenomyosis 32.
History of curettage (after miscarriage) established itself to be an
important predictor and was thus included in our model. It is debatable
as to if curettage is a cause or a consequence of adenomyosis, as
adenomyosis is often associated with risk of miscarriage5. Conversely, curettage as a risk factor for the
development of adenomyosis could potentially be explained by iatrogenic
trauma leading to the mechanical transport of endometrial cells into the
myometrium 33,34.
None of the primary MRI parameters alone were sufficient to diagnose
adenomyosis conclusively, which is in line with the literature (11) .
The presence of HSI foci emerged as the strongest predictor of the
assessed MRI parameters (p <.001). Bazot et al. indeed
described these foci as the only direct diagnostic criterion and almost
pathognomonic for adenomyosis on MRI, although they are detected in only
about half the cases (11).
In clinical practice, our model could be used to calculate the risk of
adenomyosis in individual patients. For example, in a 31-year-old woman
with a BMI of 19 kg/m2, without history of curettage,
with complaints of both dysmenorrhoea and AUB, and an MRI with mean JZ
thickness of 8.3 millimetres, a JZ Diff <5 mm, a JZ/MYO
>.40, but HSI Foci (Figure 1A), the probability of
adenomyosis is 14.9%. In a 35-year-old woman with a BMI of 24
kg/m2, without history of curettage, with complaints
of both dysmenorrhoea and AUB, and an MRI with a mean JZ thickness of
24.6 millimetres, a JZ Diff ≥5 mm, a JZ/MYO >.40 and HSI
Foci (Figure 1B), this probability increases to 90.3%.