Diagnosis of Adnexal Masses—Do we Really Need Computed Tomography?

Abklärung von Adnextumoren – ist die Computertomographie unumgänglich?

Over the past decades ultrasound has become an indispensable extension of the gynecologist’s hands and eyes. It provides the examiner with all the necessary proxies to assess tissue texture, vascularization, mobility and tenderness. The complementary information generated from this low-cost, dynamic examination in addition to static imaging modalities is undisputed. Moreover it may serve on multiple tiers, ranging from a diagnostic triaging tool, over a stereotactic guide for representative tru-cut biopsies, to a guidance for therapeutic punctures.

Adequately discriminating benign adnexal lesions from their malignant counterparts is of paramount importance, as this allows to select the most appropriate treatment effectuated by the most appropriate physician, guided by the most appropriate second-stage examinations. Making an optimal pre-operative risk estimation has always been the main pursuit of the International Ovarian Tumor Analysis (IOTA) consortium, propelling multicentric prospective observational research, by use of standardized terms and definitions [1]. Through this uniformly gathered data, risk prediction models have been constructed. Initially these models—such as the Logistic Regression 1 (LR1), LR2, and IOTA Simple Rules (SR) and Simple Rules Risk (SRR) model—only allowed for dichotomous (benign vs malignant) risk estimation or calculation [2,3,4]. After appropriate training these models already enhanced the assessment by less-experienced examiners to a similar diagnostic performance as expert sonographers. The main prerequisite for a reliable result is that of correct adherence to the predefined IOTA terminology.

It wasn’t however until the advent of the Assessment of Different NEoplasias in the AdneXa (ADNEX) model that the deepest insight could be obtained from a thorough pelvic scan [5]. The ADNEX model is a multiclass or polytomous risk prediction model developed on IOTA phases 1, 1b and 2, temporally validated on phase 3 and ultimately retrained using the total dataset of 5909 patients. This polytomous modelling in masses was novel in that it allowed not only to distinguish between benign and malignant masses, but also allowed subdividing perceived malignancies in borderline tumors, primary International Federation of Gynecology and Obstetrics (FIGO) stage I ovarian cancer, primary FIGO stage II–IV ovarian cancer or secondary metastases to the ovary, respectively. The model requires only basic variables as input. Calculations are based on three clinical factors, consisting of age, whether you are scanning in an oncology center or not and the serum level of biomarker CA-125. Six highly reproducible, low-cost ultrasound variables will complete the assessment and these consist of the maximal lesion diameter, maximal diameter of the largest solid part, the number of papillary projections, presence of more or less than ten cyst locules, presence of acoustic shadows and presence of ascites. This model has shown to uphold high sensitivity and specificity values and an area under the curve (AUC) of 0.954 of the Receiver Operating Characteristic (ROC) plot, thereby outperforming previous IOTA models and paralleling expert sonography. It has subsequently been validated in repetitive external validation rounds, also providing insight in its calibration, and has been subjected to several meta-analyses containing cost-effectiveness calculations [6].

Not only have the aforementioned prediction models and consensuses aided in attaining a broader consensus and unified reporting among gynecologists globally, they have also intertwined with radiologists’ practice. Efforts have been made to move towards a global consensus on reporting risks associated with ovarian cysts together with the American College of Radiology (ACR) in a classification known as the Ovarian-Adnexal Reporting and Data System (O‑RADS) [7]. These guidelines specify all risk categories, based on arbitrarily selected risks of malignancy as indicated by the ADNEX model, with their appropriate management strategies. This O‑RADS classification model however still requires extensive internal and external validation in the years to come. From gradually merging insights with radiologists, sprouted also add-on approaches such as magnetic resonance imaging(MRI)-based stratification charts, such as O‑RADS MRI as second stage mass characterization [8].

With respect to staging as opposed to characterization, despite reports having been published in which diffuse intra-abdominal spread and distant metastases were appreciable on ultrasound, evidence is in favor of static imaging modalities [9]. When comparing computed tomography (CT) to MRI, notwithstanding the good spatial resolution of the former, it has repetitively shown inferior to the latter in contrast resolution, thereby being inferior in site-based lesion detection and not allowing for as adequate an estimation of intestinal disease and distant (nodal) metastasis [10,11,12].

It is therefore audacious yet not inconceivable to say that the decades to come might surprise us with a paradigm shift away from CT and towards ultrasound supplemented with MRI in second stage, be it for further characterization or defining disease extent.


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Correspondence to Ruben Heremans.

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For this article no studies with human participants or animals were performed by any of the authors. All studies performed were in accordance with the ethical standards indicated in each case.

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Lecture manuscript on the occasion of the XXIX Scientific Meeting of the Working Group for Gynaecological Oncology (AGO) of the Austrian Society of Gynaecology and Obstetrics (OEGGG) 2020, 18th Austrian Congress “Cancer in Women”, April 22–25, 2020, Salzburg. The meeting was cancelled due to the Sars-CoV‑2 pandemic.

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Heremans, R. Diagnosis of Adnexal Masses—Do we Really Need Computed Tomography?. J. Gynäkol. Endokrinol. AT 30, 67–68 (2020). https://doi.org/10.1007/s41974-020-00134-y

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