E2400. Update on Ovarian Neoplasm: Clinical, Laboratory, and an Algorithmic Imaging Approach to Benign versus Malignant Neoplasms
  1. Margarita Revzin; Yale School of Medicine
  2. Douglas Katz; Winthrop University Hospital
  3. Mariam Moshiri; University of Washington
  4. Christine Menias; Mayo Clinic Arizona
Adnexal masses and cysts are commonly encountered in daily radiology practice and most cysts can be accurately characterized with ultrasonography as likely benign or malignant. Ovarian cancer is the leading cause of death from gynecologic malignancy and fifth overall cause of death among women. Effective screening method is necessary to accurately detect and diagnose adnexal pathology. Recently, much of research was done to unify our reporting system and diagnostic algorithm. Each has positive effects and some drawbacks. Several classification systems exist: IOTA classification and multi-class ADNEX model SRU consensus criteria O-Rads Lexicon and scoring system Primary goal: To create a unified list of terms used to ameliorate inconsistencies in descriptor terminology among reporting clinicians and provide systematic approach to diagnosis

Educational Goals / Teaching Points
Describe the natural history and pathophysiology of ovarian neoplasms. Briefly review the history and rationale of ovarian lexicon development. Review mainstay imaging modalities for the diagnosis of ovarian masses, with emphasis on new techniques for detection of tumor angiogenesis: dynamic MRI, diffusion-weighted imaging (DWI), and contrast-enhanced ultrasound (CEUS). Familiarize radiologists with differentiating imaging and clinical/laboratory markers which should increase overall accuracy and positive predictive value in the diagnosis of ovarian malignancy, with radiologic-pathologic correlation.

Key Anatomic/Physiologic Issues and Imaging Findings/Techniques
Theories suggest that epithelial tumors (70% of all ovarian tumors) arise from cancer cells that originate in the fallopian tube, and subsequently seed the ovary and peritoneum. Currently, there is no effective screening method. As radiologists, how can we provide value in evaluating patients with ovarian neoplasms? Ultimate Goals of radiologists are to discriminate between benign and malignant lesions and provide quantitative risk stratification for ovarian lesions that will guide patient management US, MRI, CT/PET CT

Ovarian neoplasms are difficult to detect early due to lack of early symptoms. Standardization of ovarian cyst/mass characterization can help minimize surgical intervention for non-malignant masses. In cases that baseline ultrasound is equivocal, MRI and other newer techniques such as contrast-enhanced ultrasound, diffusion-weighted imaging, and dynamic post-contrast MRI may prove to be useful.