TY - JOUR
T1 - Co-registered photoacoustic and ultrasound imaging of human colorectal cancer
AU - Yang, Guang
AU - Amidi, Eghbal
AU - Chapman, William C.
AU - Nandy, Sreyankar
AU - Mostafa, Atahar
AU - Abdelal, Heba
AU - Alipour, Zahra
AU - Chatterjee, Deyali
AU - Mutch, Matthew
AU - Zhu, Quing
N1 - Funding Information:
Research in this publication was partially funded by R01CA151570 and R01EB002136, and supported by the Washington University School of Medicine Surgical Oncology Basic Science and Translational Research Training Program Grant No. T32CA009621 from the National Cancer Institute. Partial results were presented at SPIE Photonics West 2019 and were also included in the SPIE 2019 proceedings.
Publisher Copyright:
© The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
PY - 2019/12/1
Y1 - 2019/12/1
N2 - Colorectal cancer is the second most common malignancy diagnosed globally. Critical gaps exist in diagnostic and surveillance imaging modalities for colorectal neoplasia. Although prior studies have demonstrated the capability of photoacoustic imaging techniques to differentiate normal from neoplastic tissue in the gastrointestinal tract, evaluation of deep tissue with a fast speed and a large field of view remains limited. To investigate the ability of photoacoustic technology to image deeper tissue, we conducted a pilot study using a real-time co-registered photoacoustic tomography (PAT) and ultrasound (US) system. A total of 23 ex vivo human colorectal tissue samples were imaged immediately after surgical resection. Co-registered photoacoustic images of malignancies showed significantly increased PAT signal compared to normal regions of the same sample. The quantitative relative total hemoglobin (rHbT) concentration computed from four optical wavelengths, the spectral features, such as the mean spectral slope, and 0.5-MHz intercept extracted from PAT and US spectral data, and image features, such as the first-and second-order statistics along with the standard deviation of the mean radon transform of PAT images, have shown statistical significance between untreated colorectal tumors and the normal tissue. Using either a logistic regression model or a support vector machine, the best set of parameters of rHbT and PAT intercept has achieved area-under-the-curve (AUC) values of 0.97 and 0.95 for both training and testing data sets, respectively, for prediction of histologically confirmed invasive carcinoma.
AB - Colorectal cancer is the second most common malignancy diagnosed globally. Critical gaps exist in diagnostic and surveillance imaging modalities for colorectal neoplasia. Although prior studies have demonstrated the capability of photoacoustic imaging techniques to differentiate normal from neoplastic tissue in the gastrointestinal tract, evaluation of deep tissue with a fast speed and a large field of view remains limited. To investigate the ability of photoacoustic technology to image deeper tissue, we conducted a pilot study using a real-time co-registered photoacoustic tomography (PAT) and ultrasound (US) system. A total of 23 ex vivo human colorectal tissue samples were imaged immediately after surgical resection. Co-registered photoacoustic images of malignancies showed significantly increased PAT signal compared to normal regions of the same sample. The quantitative relative total hemoglobin (rHbT) concentration computed from four optical wavelengths, the spectral features, such as the mean spectral slope, and 0.5-MHz intercept extracted from PAT and US spectral data, and image features, such as the first-and second-order statistics along with the standard deviation of the mean radon transform of PAT images, have shown statistical significance between untreated colorectal tumors and the normal tissue. Using either a logistic regression model or a support vector machine, the best set of parameters of rHbT and PAT intercept has achieved area-under-the-curve (AUC) values of 0.97 and 0.95 for both training and testing data sets, respectively, for prediction of histologically confirmed invasive carcinoma.
KW - human colorectal cancer
KW - photoacoustic imaging
KW - prediction models
UR - http://www.scopus.com/inward/record.url?scp=85075305310&partnerID=8YFLogxK
U2 - 10.1117/1.JBO.24.12.121913
DO - 10.1117/1.JBO.24.12.121913
M3 - Article
C2 - 31746155
AN - SCOPUS:85075305310
SN - 1083-3668
VL - 24
JO - Journal of Biomedical Optics
JF - Journal of Biomedical Optics
IS - 12
M1 - 121913
ER -