Abstract

The heterogeneity in the pathological and clinical manifestations of ovarian cancer is a major hurdle impeding early and accurate diagnosis. A host of imaging modalities, including Doppler ultrasound, MRI, and CT, have been investigated to improve the assessment of ovarian lesions. We hypothesized that pathologic conditions might affect the ovarian vasculature and that these changes might be detectable by optical-resolution photoacoustic microscopy (OR-PAM). In our previous work, we developed a benchtop OR-PAM and demonstrated it on a limited set of ovarian and fallopian tube specimens. In this study, we collected data from over 50 patients, supporting a more robust statistical analysis. We then developed an efficient custom analysis pipeline for characterizing the vascular features of the samples, including the mean vessel diameter, vascular density, global vascular directionality, local vascular definition, and local vascular tortuosity/branchedness. Phantom studies using carbon fibers showed that our algorithm was accurate within an acceptable error range. Between normal ovaries and normal fallopian tubes, we observed significant differences in five of six extracted vascular features. Further, we showed that distinct subsets of vascular features could distinguish normal ovaries from cystic, fibrous, and malignant ovarian lesions. In addition, a statistically significant difference was found in the mean vascular tortuosity/branchedness values of normal and abnormal tubes. The findings support the proposition that OR-PAM can help distinguish the severity of tubal and ovarian pathologies.

Details

Title
Quantification of ovarian lesion and fallopian tube vasculature using optical-resolution photoacoustic microscopy
Author
Leng, Xiandong 1 ; Kou, Sitai 1 ; Lin, Yixiao 1 ; Hagemann, Andrea R. 2 ; Hagemann, Ian S. 3 ; Thaker, Premal H. 2 ; Kuroki, Lindsay M. 2 ; McCourt, Carolyn K. 2 ; Mutch, David G. 2 ; Siegel, Cary 4 ; Powell, Matthew A. 2 ; Zhu, Quing 5 

 Washington University, Biomedical Engineering, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002) 
 Washington University School of Medicine, Department of Obstetrics and Gynecology, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002) 
 Washington University School of Medicine, Department of Obstetrics and Gynecology, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002); Washington University School of Medicine, Department of Pathology and Immunology, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002) 
 Washington University School of Medicine, Department of Radiology, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002) 
 Washington University, Biomedical Engineering, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002); Washington University School of Medicine, Department of Radiology, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2717204297
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.