Program Information

Semi-Automatic Segmentation of Skin Cancer in High-Frequency Ultrasound Images: Initial Comparison with Histology

X Yang

Y Gao¹ , X Li² , K Fishman³ , X Yang⁴*, T Liu⁵ , (1) Univ. Alabama at Birmingham, Birmingham, AL,(2) Medical College of Wisconsin, Milwaukee, WI, (3) Sensus Healthcare, Boca Raton, FL, (4) Department of Radiation Oncology and Winship Cancer Institute, Emory Univ., Atlanta, GA, (5) Emory Univ, Atlanta, GA

Presentations

TU-A-9A-6 Tuesday 7:30AM - 9:30AM Room: 9A

Purpose: In skin-cancer radiotherapy, the assessment of skin lesion is challenging, particularly with important features such as the depth and width hard to determine. The aim of this study is to develop interative segmentation method to delineate tumor boundary using high-frequency ultrasound images and to correlate the segmentation results with the histopathological tumor dimensions.

Methods: We analyzed 6 patients who comprised a total of 10 skin lesions involving the face, scalp, and hand. The patient’s various skin lesions were scanned using a high-frequency ultrasound system (Episcan, LONGPORT, INC., PA, U.S.A), with a 30-MHz single-element transducer. The lateral resolution was 14.6 micron and the axial resolution was 3.85 micron for the ultrasound image. Semi-automatic image segmentation was performed to extract the cancer region, using a robust statistics driven active contour algorithm. The corresponding histology images were also obtained after tumor resection and served as the reference standards in this study.

Results: Eight out of the 10 lesions are successfully segmented. The ultrasound tumor delineation correlates well with the histology assessment, in all the measurements such as depth, size, and shape. The depths measured by the ultrasound have an average of 9.3% difference comparing with that in the histology images. The remaining 2 cases suffered from the situation of mismatching between pathology and ultrasound images.

Conclusion: High-frequency ultrasound is a non-invasive, accurate and easy-accessible modality to image skin cancer. Our segmentation method, combined with high-frequency ultrasound technology, provides a promising tool to estimate the extent of the tumor to guide the radiotherapy procedure and monitor treatment response.



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