Diffusion-weighted and diffusion-tensor imaging of normal and diseased uterus

Bozkurt, Duygu Kara; Bozkurt, Murat; Nazli, Mehmet Ali; Mutlu, İlhan Nahit; Kılıçkesmez, Özgür

doi:10.4329/wjr.v7.i7.149

Cited by 10 publications

(1 citation statement)

References 38 publications

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“…[54][55][56] More recently, the use of diffusion tensor imaging has also been explored in uterine and gynecological disorders like endometriosis, malignancies, and uterine fibroids, suggesting great potential in the use of these techniques in gynecological conditions. 57,58 Their diagnostic potential remains to be definitively evaluated; however, the one study that investigated diffusion tensor imaging for its diagnostic potential showed superior accuracy over conventional MRI. 16 There are several limitations which may impact our results.…”

Section: Correlation With Clinical Outcomesmentioning

confidence: 99%

Objective measures of adenomyosis on MRI and their diagnostic accuracy—a systematic review & meta‐analysis

Rees

Mischi

Vliet

et al. 2021

Acta Obstet Gynecol Scand

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Introduction: Magnetic resonance imaging (MRI) diagnosis of adenomyosis is considered the most accurate non-invasive technique, but remains subjective, with no consensus on which diagnostic parameters are most accurate. We aimed to systematically review the literature on how adenomyosis can be objectively quantified on MRI in a scoping manner, to review the diagnostic performance of these characteristics compared with histopathological diagnosis, and to summarize correlations between measures of adenomyosis on MRI and clinical outcomes. Material and methods:We searched databases Pubmed, Embase, and Cochrane for relevant literature up to April 2020 according to PRISMA guidelines. We included studies that objectively assessed adenomyosis on MRI, and separately assessed studies investigating the diagnostic performance of MRI vs histopathology for inclusion in a meta-analysis. The QUADAS-2 tool was used for risk of bias, with many studies showing an unclear or high risk of bias.Results: Eighty studies were included, of which 14 assessed the diagnostic performance of individual MRI parameters, with four included in the meta-analysis of diagnostic accuracy. Common MRI parameters were: junctional zone (JZ) characteristics, such as maximum JZ thickness-pooled sensitivity 71.6% (95% CI 46.0%-88.2%), specificity 85.5% (52.3%-97.0%); JZ differential-pooled sensitivity 58.9% (95% CI 44.3%-72.1%), specificity 83.2% (95% CI 71.3%-90.8%); and JZ to myometrial ratiopooled sensitivity 63.3% (95% CI 51.9%-73.4%), specificity 79.4% (95% CI 42.0%-95.4%); adenomyosis lesion size, uterine morphology (pooled sensitivity 42.9% (95% CI 15.9%-74.9%), specificity 87.7%, (95% CI 37.9-98.8) and changes in signal intensity-eg, presence of myometrium cysts; pooled 59.6% (95% CI 41.6%-75.4%) and specificity of 96.1% (95% CI 80.7%-99.3%). Other MRI parameters have been used for adenomyosis diagnosis, but their diagnostic performance is unknown. Few studies attempted to correlate adenomyosis MRI phenotype to clinical outcomes. Conclusions:A wide range of objective parameters for adenomyosis exist on MRI; however, in many cases their individual diagnostic performance remains uncertain.We included studies investigating the diagnosis, evaluation or classification of adenomyosis objectively based on MRI. Studies were included regardless of study design, use of hormonal therapy, age, or clinical manifestation. Studies written in English, Dutch or French were considered for inclusion, published up to April 7, 2020.Data reported in secondary analysis (reviews), case reports, letters to editors, conference abstracts, and protocols for ongoing JZ characteristics remain the most widely used and investigated with acceptable diagnostic accuracy. Specific research is needed into how these objective measures of adenomyosis can be correlated to clinical outcomes.

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