Differentiating solid, non-macroscopic fat containing, enhancing renal masses using fast Fourier transform analysis...

Area of Science:

• Radiology and Medical Imaging
• Biomedical Engineering
• Oncology

Background:

• Renal masses require accurate differentiation for appropriate patient management.
• Distinguishing benign from malignant renal tumors, particularly solid, enhancing masses, remains a clinical challenge.
• Intratumoral heterogeneity influences tumor behavior and can be assessed using imaging metrics.

Purpose of the Study:

• To evaluate the feasibility of two-dimensional fast Fourier transform (FFT)-based imaging metrics for differentiating solid, enhancing renal masses.
• To quantify intratumoral textural variations using frequency-based FFT metrics on contrast-enhanced CT images.
• To assess the diagnostic performance of FFT metrics in distinguishing benign from malignant renal masses and specific tumor subtypes.

Main Methods:

• A retrospective case-control study included 156 patients with solid, enhancing renal masses (110 malignant RCC, 46 benign).
• Whole lesions were manually segmented from multiphase contrast-enhanced CT acquisitions.
• The FFT2 function in Matlab was used for image-to-frequency transformation to derive textural metrics.

Main Results:

• FFT-based metrics showed significant differences (p < 0.005) between benign and malignant renal masses.
• Significant differentiation was also observed between oncocytoma vs. clear cell RCC and oncocytoma vs. lipid-poor angiomyolipoma.
• Receiver operator characteristics analysis indicated reasonable discrimination (AUC > 0.7, p < 0.05) in these comparisons.

Conclusions:

• FFT-based imaging metrics can differentiate between certain types of solid, enhancing renal masses using contrast-enhanced CT data.
• These metrics hold potential for improving patient management when used in conjunction with other diagnostic tools.
• This study represents the first report on the application of FFT metrics for differentiating specific renal tumors.