Histogram Feature Analysis of Tumor Body on Diffusion-weighted MR Imaging in Differentiation between Granulosa Cell Tumors and Other Sex-cord Tumors in Ovary: Comparison with Histological Results

Minjie Wu ¹, Tianping Wang ¹, Feiran Zhang ²

⁰Department of Radiology, Obstetrics and Gynecology Hospital, Fudan University, P.R. China.

Current Medical Imaging +

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February 28, 2024

View abstract on PubMed

Summary

Feature analysis of MR imaging tumor body features effectively differentiates granulosa cell tumors (GCT) from other ovarian sex-cord tumors (OSCs). This advanced MRI technique offers superior diagnostic performance compared to conventional apparent diffusion coefficient (ADC) measurements.

Area Of Science

Radiology
Oncology
Pathology

Background

Ovarian sex-cord tumors (OSCs) encompass a diverse group of neoplasms.
Granulosa cell tumors (GCTs) are a significant subtype of OSCs requiring accurate differentiation.
Distinguishing GCTs from other OSCs is crucial for appropriate clinical management.

Purpose Of The Study

To evaluate the efficacy of MR imaging feature analysis of the tumor body in differentiating GCTs from other OSCs.
To compare the diagnostic performance of MR imaging features with conventional apparent diffusion coefficient (ADC) measurements.

Main Methods

Retrospective analysis of 27 patients with pathologically confirmed sex-cord tumors (14 GCTs, 8 fibromas, 4 fibrothecomas, 1 sclerosing stromal tumor).
MR imaging feature analysis, including histogram analysis of diffusion-weighted imaging (DWI) and T2-weighted imaging (T2WI).
Comparison of histogram parameters and ADC values between GCTs and other OSCs, with cellular-type myomas as a control group.

Main Results

Histogram variance on DWI, histogram percentage on T2WI, and ADC min demonstrated significant discriminative performance.
Histogram variance on DWI achieved an area under the receiver operator curve (AUC) of 0.997, with 92.3% sensitivity, 100% specificity, and 96.6% accuracy for GCT differentiation.
Conventional ADC measurements showed good repeatability, but feature analysis provided superior diagnostic performance.

Conclusions

MR imaging feature analysis of the tumor body is a highly effective method for differentiating GCTs from other OSCs.
This advanced imaging approach surpasses the diagnostic capabilities of conventional ADC measurements.
Feature analysis offers a promising non-invasive tool for improved diagnosis of GCTs.

Keywords:

diffusion weighted imaging granulosa cell tumor magnetic resonance imaging ovarian neoplasm