Ovarian tumors in pediatric population are uncommon compared to adult females, but not rare, only with a different incidence profile. Most tumors found under the age of 18 years are benign, with origin from germ cell line.

Tumors of the ovary can be placed into one of three major categories (Fig. 1) —according to the anatomic structures from which the tumors presumably originate:

1. surface epithelial-stromal tumors;
2. sex cord-stromal tumors;
3. germ cell tumors.

Ovarian tumors have similar clinical and imaging features, but specific key characteristics may be present in some types of tumors and provide the criteria for making a specific diagnose or substantially narrowing the differential diagnosis:

1. epithelial tumors - primarily cystic, with varying proportions of a solid component when malignant;
2. sex cord-stromal tumors - usually large solid or multicystic masses with solid components;
3. germ cell tumors - a large, complex abdominal mass that contains both solid and cystic components.

The diagnosis of ovarian tumors is based on pelvic ultrasound and abdominal-pelvic MRI because of its excellent visualization and absence of ionizing radiation on children. CT is reserved primarly for tumor staging and follow-up.

In most cases, a multimodality approach is preffered for diagnostic accuracy considering each imaging tehnique sensitivity for tissue components. For example, presence of fat in a lesion:

• on ultrasound images, fat tissues usually appear hyperechoic, although there are exceptions; 
  

  Fig. 2: Ultrasound ecogenity of tissues
  References: https://radiopaedia.org/cases/subcutaneous-fat-contusion-of-thigh-ultrasound
   
• on CT, fat appears to have low attenuation with a range of -10 to -100 Hounsfield units (HUs). If the proportion of fat within a voxel is small, then the mean CT number will increase and fat may be difficult to reliably identify; 
  

  Fig. 3: Plain CT shows hypodensity of entire pancreatic parenchyma with CT value of fat density (-117 HU) (white arrows)
  References: https://www.opensciencepublications.com/fulltextarticles/IJAR-2581-3919-3-116.html
  
  
  

  Fig. 4: The Hounsfield scale for radiodensity
  References: https://www.startradiology.com/internships/neurology/brain/ct-brain-hemorrhage/
   
• magnetic resonance imaging (MRI) can reveal small quantities of macroscopic fat and intracellular fat in a lesion being a helpful imaging finding that can potentially narrow the differential diagnosis and may significantly help the imaging specialist to reach the correct diagnosis. 
  

  Fig. 5: MRI T1 sequence intensity of structures
  References: https://www.startradiology.com/the-basics/mri-technique/index.html