Imaging plays a central role in identifying ovarian masses that could be malignant and require a gynecological oncologist for treatment. Ultrasound has always been the first and most universally accepted imaging modality used to evaluate adnexal masses, although deciding whether a mass is malignant or benign is difficult at times and may require an imaging expert.

Multiple studies in the late 1990s and early 2000s attempted to include a large number of sonographic variables into complex algorithms, hoping to find the most predictive combinations of ultrasound findings that could predict malignant masses. Although the sensitivity for detecting ovarian cancer was fairly high, the specificity and positive predictive value remained low.

Most importantly, these attempts at scoring indices were cumbersome, proposed and studied by experts in the field, with small numbers of patients and often in a single center, often not undertaking independent validation. Unfortunately, the need for these examinations by far outstrips the few dedicated experts. Most of the radiologists and gynecologists that perform the majority of ultrasound studies lack specialized expertise in gynecological imaging.

In the real world, many ultrasound reports fall short of identifying confidently whether an adnexal mass is benign or malignant. Too many practitioners use the term, complex cyst, to describe such a mass without attempting to characterize it further. Admittedly, the few expert practitioners interpret these ultrasound examinations more accurately than the more numerous generalists who read the bulk of these studies.

Hence it is no wonder that the ability of ultrasound to distinguish benign from malignant adnexal masses reliably remains disappointing in the hands of many. The challenge has been to find an ultrasound algorithm sufficiently simple and robust to enable the generalist imager to achieve the accuracy of the expert in determining whether a mass is malignant. This task presents a tall order indeed. Timmerman et al attacked this problem as early as 1999.

Timmerman et al, in the landmark study published in this issue of the Journal, report the culmination of multiple consecutive multicenter studies involving 24 centers in 10 countries from 1999 to 2012 and reporting on more than 5000 patients with ovarian masses. Timmerman and his team have managed to take a very complex problem with many ultrasound features and parameters and produce a simplified instrument that requires input of only 5 straightforward rules.

This series of studies undertaken by the International Ovarian Tumor Analysis (IOTA) group starting in 1999 developed multiple complex regression models to evaluate a large number of ultrasound parameters that might aid in discriminating benign from malignant ovarian lesions. After several stages of the studies including independent validation sets, Timmerman and colleagues developed the 5 simple ultrasound rules that they further validated in their own subsequent studies.

As attested to by many, the IOTA regression models remain the most accurate and clinically useful method for determining the malignant status of a mass that can be used clinically by all practitioners. In his landmark study of 2008, Timmerman et al introduced these 5 simple ultrasound rules that were then tested and retested both in his own laboratory with new data sets as well as in other institutions, showing unprecedented accuracy and ease of use in multiple countries, settings, and with practitioners at different stages of training. Furthermore, based on data from the IOTA phase 1-3 data sets, the IOTA group is developing a risk prediction model (Assessment of Different Neoplasias in the Adnexa) that can discriminate between different pathological types of ovarian tumors, such as borderline, stage I cancer, stages II-IV cancer, and secondary metastatic cancer, a very promising tool for the future.

Most importantly, Timmerman et al have shown that application of this regression model yields an accuracy equivalent to that of an expert in evaluating ovarian masses. The investigators have finally been able to level and elevate the playing field so that everybody can practice with expert results in this regard. Not only have the 5 simple rules demonstrated that you do not have to be an expert to evaluate ovarian masses accurately but that one can do so simply, reproducibly, and reliably.

Initially, the 5 simple rules enabled Timmerman and his team to classify 77% of ovarian masses leaving 23% uncertain. The indeterminate examinations would require the opinion of an expert interpreter. Taking it a step further, Timmerman reassessed his regression models in an attempt to provide a simple technique that could be used for every mass.

The results described in this issue of the Journal show that by assigning a risk estimate to each of these simple rules, one can derive an actual score that reflects the risk that a mass is malignant or benign. This risk can be calculated by any practitioner for any and every mass (using a simple smart phone–based application) to assign to each patient an individual risk of the presence of a malignant adnexal mass.

Modern medicine relies extensively on percentage risk for adverse outcome. In our own field of prenatal diagnosis, we have evolved from scoring systems into obtaining a percentage risk estimate for whether a fetus has Down syndrome by integrating ultrasound and biochemistry. The evaluation of the ovarian masses is similarly complicated and critical and could benefit enormously from the availability of a simple to apply method to nonexpert practitioners in any center.

Ultrasound is indeed an art, and the experts have become artists not only in obtaining the images but in reading them. Timmerman et al have found a way to provide a tool that renders ultrasound more uniform in the hands of all clinicians. The general public lacks awareness of the variability of ultrasound results that depends so much on who acquires and reads the images.

Timmerman et al have developed an exceptional way to level as well as raise the playing field of using ultrasound to evaluate ovarian masses, providing results close to those of an expert imager, with proven validity and broad utility. The use of an individual percentage risk is already a well-accepted method used in many aspects of modern medicine and one that the imager, referring clinicians, and patients can all understand.

It is vexing to many ultrasound experts that an ultrasound interpreted as equivocal or as a complex ovarian mass of unknown etiology, too often triggers performance of magnetic resonance imaging (MRI) to supercede the ultrasound reading. Little if any evidence indicates that MRI is more sensitive and accurate than a properly performed and interpreted ultrasound. One systematic review summarizing the literature indicates that MRI used to evaluate ovarian masses has a sensitivity of 83% and specificity of 89% and claims that ultrasound has a sensitivity of only 63%. Timmerman et al have shown that the IOTA simple rules give far superior results to those reported for MRI (sensitivity 90%, specificity 93%).

Another study from 10 years ago compared gray-scale ultrasound with MRI and added color Doppler only as a secondary parameter. The sensitivity of ultrasound with color Doppler was 84% compared with 76% with MRI, although MRI had a higher specificity of 97% compared with ultrasound’s 82%. The last decade has seen significant advances in ultrasound sensitivity and specificity for diagnosing ovarian malignancies (including the IOTA series of studies); hence, this 10 year old study may not reflect current ultrasound capabilities.

So why do we resort to MRI when the ultrasound reading is unequivocal rather than to an ultrasound expert? Timmerman has shown here that if we use the simple rules with the scoring instrument that he has developed with his team, we will determine the correct diagnosis more readily than ever before and offers the advantage that most practitioners could adopt this approach successfully.

I applaud this group for grappling with and challenging the problem of the variability of ultrasound diagnoses of adnexal masses, depending on the expertise of acquisition and interpretation, and succeeding in developing a simple, standardized, and scalable solution. By at once leveling and elevating the playing field, application of this method places expert interpretation and improved diagnostic ability within reach of all practitioners.