Literature DB >> 23993172

Automated skin segmentation in ultrasonic evaluation of skin toxicity in breast cancer radiotherapy.

Yi Gao1, Allen Tannenbaum, Hao Chen, Mylin Torres, Emi Yoshida, Xiaofeng Yang, Yuefeng Wang, Walter Curran, Tian Liu.   

Abstract

Skin toxicity is the most common side effect of breast cancer radiotherapy and impairs the quality of life of many breast cancer survivors. We, along with other researchers, have recently found quantitative ultrasound to be effective as a skin toxicity assessment tool. Although more reliable than standard clinical evaluations (visual observation and palpation), the current procedure for ultrasound-based skin toxicity measurements requires manual delineation of the skin layers (i.e., epidermis-dermis and dermis-hypodermis interfaces) on each ultrasound B-mode image. Manual skin segmentation is time consuming and subjective. Moreover, radiation-induced skin injury may decrease image contrast between the dermis and hypodermis, which increases the difficulty of delineation. Therefore, we have developed an automatic skin segmentation tool (ASST) based on the active contour model with two significant modifications: (i) The proposed algorithm introduces a novel dual-curve scheme for the double skin layer extraction, as opposed to the original single active contour method. (ii) The proposed algorithm is based on a geometric contour framework as opposed to the previous parametric algorithm. This ASST algorithm was tested on a breast cancer image database of 730 ultrasound breast images (73 ultrasound studies of 23 patients). We compared skin segmentation results obtained with the ASST with manual contours performed by two physicians. The average percentage differences in skin thickness between the ASST measurement and that of each physician were less than 5% (4.8 ± 17.8% and -3.8 ± 21.1%, respectively). In summary, we have developed an automatic skin segmentation method that ensures objective assessment of radiation-induced changes in skin thickness. Our ultrasound technology offers a unique opportunity to quantify tissue injury in a more meaningful and reproducible manner than the subjective assessments currently employed in the clinic.
Copyright © 2013 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Breast cancer radiotherapy; Breast ultrasound; Radiation toxicity; Skin segmentation

Mesh:

Year:  2013        PMID: 23993172      PMCID: PMC3913784          DOI: 10.1016/j.ultrasmedbio.2013.04.006

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  22 in total

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Review 4.  Ultrasound image segmentation: a survey.

Authors:  J Alison Noble; Djamal Boukerroui
Journal:  IEEE Trans Med Imaging       Date:  2006-08       Impact factor: 10.048

5.  Deformable segmentation of 3-D ultrasound prostate images using statistical texture matching method.

Authors:  Yiqiang Zhan; Dinggang Shen
Journal:  IEEE Trans Med Imaging       Date:  2006-03       Impact factor: 10.048

6.  Active contours without edges.

Authors:  T F Chan; L A Vese
Journal:  IEEE Trans Image Process       Date:  2001       Impact factor: 10.856

7.  Speckle reducing anisotropic diffusion.

Authors:  Yongjian Yu; Scott T Acton
Journal:  IEEE Trans Image Process       Date:  2002       Impact factor: 10.856

8.  20 MHz ultrasonic imaging for quantitative assessment and documentation of early and late postradiation skin reactions in breast cancer patients.

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Journal:  Radiother Oncol       Date:  1998-06       Impact factor: 6.280

Review 9.  Pathophysiology of irradiated skin and breast.

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Journal:  Int J Radiat Oncol Biol Phys       Date:  1995-03-30       Impact factor: 7.038

10.  Reliability of quantitative ultrasonic assessment of normal-tissue toxicity in breast cancer radiotherapy.

Authors:  Emi J Yoshida; Hao Chen; Mylin Torres; Fundagul Andic; Hao-Yang Liu; Zhengjia Chen; Xiaoyan Sun; Walter J Curran; Tian Liu
Journal:  Int J Radiat Oncol Biol Phys       Date:  2011-03-23       Impact factor: 7.038

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  6 in total

1.  The Impact of Axillary Lymph Node Surgery on Breast Skin Thickening During and After Radiation Therapy for Breast Cancer.

Authors:  Mylin A Torres; Xiaofeng Yang; Samantha Noreen; Hao Chen; Tatiana Han; Simone Henry; Donna Mister; Fundagal Andic; Qi Long; Tian Liu
Journal:  Int J Radiat Oncol Biol Phys       Date:  2016-01-23       Impact factor: 7.038

2.  Full axillary lymph node dissection and increased breast epidermal thickness 1 year after radiation therapy for breast cancer.

Authors:  Jolinta Y Lin; Xiaofeng Yang; Monica Serra; Andrew H Miller; Karen D Godette; Shannon T Kahn; Simone Henry; Gabrielle Brown; Tian Liu; Mylin A Torres
Journal:  J Surg Oncol       Date:  2019-11-08       Impact factor: 3.454

Review 3.  An Assessment of Imaging Informatics for Precision Medicine in Cancer.

Authors:  C Chennubhotla; L P Clarke; A Fedorov; D Foran; G Harris; E Helton; R Nordstrom; F Prior; D Rubin; J H Saltz; E Shalley; A Sharma
Journal:  Yearb Med Inform       Date:  2017-09-11

4.  Deformable registration for quantifying longitudinal tumor changes during neoadjuvant chemotherapy.

Authors:  Yangming Ou; Susan P Weinstein; Emily F Conant; Sarah Englander; Xiao Da; Bilwaj Gaonkar; Meng-Kang Hsieh; Mark Rosen; Angela DeMichele; Christos Davatzikos; Despina Kontos
Journal:  Magn Reson Med       Date:  2014-07-15       Impact factor: 4.668

5.  Objective breast tissue image classification using Quantitative Transmission ultrasound tomography.

Authors:  Bilal Malik; John Klock; James Wiskin; Mark Lenox
Journal:  Sci Rep       Date:  2016-12-09       Impact factor: 4.379

6.  High-Frequency Ultrasound Dataset for Deep Learning-Based Image Quality Assessment.

Authors:  Joanna Czajkowska; Jan Juszczyk; Laura Piejko; Małgorzata Glenc-Ambroży
Journal:  Sensors (Basel)       Date:  2022-02-14       Impact factor: 3.576

  6 in total

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