Optimized Coherence Masking Improves Ultrasound Imaging of Kidney Cysts.
TL;DR
A 2-stage image-correction algorithm that combines sound speed correction for beamforming with masking based on the spatial coherence of the beamformed signals has translational potential to improve US image quality and enhance clinical confidence in managing the common and clinically important challenge of renal cysts.
Abstract
Objectives
Renal cystic lesions are exceedingly common and typically benign, though accurate diagnostic techniques are required to recognize the subset of malignant lesions that require timely intervention. Ultrasound (US) is the preferred first line test for renal cyst evaluation because it is safe, widely accessible, and low cost. US imaging, however, is limited in individuals with obesity, as subcutaneous fat introduces imaging artifacts (eg, aberration) that obscure features critical for assessing a cyst's malignant potential.
Methods
In this work, we propose a 2-stage image-correction algorithm to improve the resolution, contrast, and potential diagnostic utility of US images of renal cysts. The method combines sound speed correction for beamforming with masking based on the spatial coherence of the beamformed signals.
Results
In a pilot cohort of 10 subjects, we observed improved image sharpness and contrast-to-noise ratio in nearly all cases compared to baseline images (mean improvements of approximately 5 and 10%, respectively). Additionally, 2 expert readers preferred nearly universally the corrected images in a blinded review.
Conclusion
Together, the results from this pilot study suggest that our method has translational potential to improve US image quality and enhance clinical confidence in managing the common and clinically important challenge of renal cysts.