New Approach could help Preoperative Differentiation of Endometriosis and Cancer

New set of radiological parameters identified that could distinguish between ovarian cancer and benign ovarian endometriosis

Key Points

Highlights:

• Researchers identified a new set of radiological parameters that could help differentiate between endometriosis-associated ovarian cancer and benign ovarian endometriosis.

Importance:

• This finding could help to diagnose ovarian cancer pre-operatively and offer the right treatment to only those women who need it.

What’s done here?

• 82 women treated at the Nara Medical University Hospital between January 2008 and January 2015, were analyzed using contrast-enhanced magnetic resonance imaging (MRI) before surgery.
• A total of 42 of the women with ovarian endometriosis with benign mural nodules compared to those 40 patients with endometriosis-associated ovarian cancer. 
• Researchers analyzed the size and location of the solid nodular and cystic part, as well as the age of two groups.

Key results:

• A mural nodule height of more than 1.5 cm, height and weight ratio of mural nodules of more than 0.9, a maximum cyst diameter of more than 7.9 cm and being older than 43 years of age were identified as independent factors that differentiate between endometriosis-associated ovarian cancer and benign ovarian endometriosis with mural nodules.

Limitations of the study:

• The mural nodules in women with ovarian endometriosis were small leading to significant measurement errors. 
• This was a retrospective study, meaning that history was collected about the present condition, so there may have been some bias in the selection of data to be analyzed. 
• Researchers mainly focused on imaging findings such as the shape and location of the mural nodules and no other techniques that could differentiate between benign and malignant growths were used.

Lay Summary

Researchers in Japan identified some radiological parameters that could be used to differentiate between endometriosis-associated ovarian cancer (EAOC) and a particular type of benign ovarian endometriosis (OE), making it easier for doctors to offer the right treatment to women who need it.

In a research article published in the scientific journal Magnetic Resonance in Medical Sciences, a team of researchers led by Dr. Hiroshi Kobayashi reported that the height and height-width ration (HWR) of the mural nodules, or cysts found in the walls of ovarian tumors, may help to differentiate between these two conditions. 

The team analyzed 82 women who were treated at the Nara Medical University Hospital between January 2008 and January 2015, using a technique called contrast-enhanced magnetic resonance imaging (MRI) before surgery. A total of 42 of the women were diagnosed with ovarian endometriosis with mural nodules and 40 with endometriosis-associated ovarian cancer. 

The researchers found that most of the mural nodules were retracted blood clots. They also found that women with cancerous mural nodules were older, had larger cysts, and larger mural nodules than those with non-cancerous nodules. The nodules were also more likely to be taller rather than wider. Finally, imaging findings such as signal intensities and shading as measured by MRI were more likely to be varied, and the cysts were more likely to be located towards the front of the ovary. 

Using statistical analyses, the researchers identified four different parameters as independent factors that can help distinguish between EAOC and OE. These were:

• A mural nodule height of more than 1.5 cm
• An HWR of the mural nodule of more than 0.9 
• A maximum cyst diameter of more than 7.9 cm
• Being older than 43 years of age

 “The height and HWR of the mural nodules in the cyst may yield a novel potential diagnostic factor for differentiating EAOC from benign OE with mural nodules," the researchers concluded.

Mural nodules are found both in non-cancerous ovarian endometriosis and endometriosis-associated ovarian cancer, making it difficult for doctors to diagnose these conditions.

Research Source: https://www.ncbi.nlm.nih.gov/pubmed/28824051