Optimized Coherence Masking Improves Ultrasound Imaging of Kidney Cysts

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.

Authors

Institutions

Publication Details

Journal
Journal of Ultrasound in Medicine
Published
2026-07-24
DOI
https://doi.org/10.1002/jum.70380
Primary Topic
Renal cell carcinoma treatment
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimized Coherence Masking Improves Ultrasound Imaging of Kidney Cysts

Theodore T. Pierce, David Hunt, Abder-Rahman Ali, Mike Washburn et al.
Journal of Ultrasound in Medicine
Renal cell carcinoma treatment
article

Optimized Coherence Masking Improves Ultrasound Imaging of Kidney Cysts

Theodore T. Pierce, David Hunt, Abder-Rahman Ali, Mike Washburn, Scott Schoen, Kai E. Thomenius, Anthony E. Samir, Rimon Tadross, Mary K. Peters, Sai Dhanush Reddy Jeggari, Brian Lause, Michael Wang, Kathleen Pope
article en

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.

Journal of Ultrasound in Medicine
Georgia Institute of Technology (US), Harvard University (US), Massachusetts General Hospital (US)
GE Healthcare
Good health and well-being
Openalex Percentile: Top 9%
Renal cell carcinoma treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.