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Eminaga O, Lee TJ, Ge J, Shkolyar E, Laurie M, Long J, Hockman LG, Liao JC. Conceptual framework and documentation standards of cystoscopic media content for artificial intelligence. J Biomed Inform 2023; 142:104369. [PMID: 37088456 PMCID: PMC10643098 DOI: 10.1016/j.jbi.2023.104369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 04/03/2023] [Accepted: 04/18/2023] [Indexed: 04/25/2023]
Abstract
BACKGROUND The clinical documentation of cystoscopy includes visual and textual materials. However, the secondary use of visual cystoscopic data for educational and research purposes remains limited due to inefficient data management in routine clinical practice. METHODS A conceptual framework was designed to document cystoscopy in a standardized manner with three major sections: data management, annotation management, and utilization management. A Swiss-cheese model was proposed for quality control and root cause analyses. We defined the infrastructure required to implement the framework with respect to FAIR (findable, accessible, interoperable, reusable) principles. We applied two scenarios exemplifying data sharing for research and educational projects to ensure compliance with FAIR principles. RESULTS The framework was successfully implemented while following FAIR principles. The cystoscopy atlas produced from the framework could be presented in an educational web portal; a total of 68 full-length qualitative videos and corresponding annotation data were sharable for artificial intelligence projects covering frame classification and segmentation problems at case, lesion, and frame levels. CONCLUSION Our study shows that the proposed framework facilitates the storage of visual documentation in a standardized manner and enables FAIR data for education and artificial intelligence research.
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Affiliation(s)
- Okyaz Eminaga
- Department of Urology, Stanford University School of Medicine, Stanford, USA; Center for Artificial Intelligence and Medical Imaging, Stanford University School of Medicine, Stanford, CA, USA.
| | - Timothy Jiyong Lee
- Department of Urology, Stanford University School of Medicine, Stanford, USA
| | - Jessie Ge
- Department of Urology, Stanford University School of Medicine, Stanford, USA
| | - Eugene Shkolyar
- Department of Urology, Stanford University School of Medicine, Stanford, USA
| | - Mark Laurie
- Department of Urology, Stanford University School of Medicine, Stanford, USA
| | - Jin Long
- Center for Artificial Intelligence and Medical Imaging, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Joseph C Liao
- Department of Urology, Stanford University School of Medicine, Stanford, USA; Center for Artificial Intelligence and Medical Imaging, Stanford University School of Medicine, Stanford, CA, USA.
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Masuoka S, Miyazaki O, Imai A, Okamoto R, Tsutsumi Y, Miyasaka M, Hasegawa Y, Yoshioka T, Nosaka S. "Another inchworm sign" on dynamic contrast-enhanced magnetic resonance imaging in pediatric patients with cystitis cystica and glandularis: Radiologic-pathologic correlation. Radiol Case Rep 2022; 18:840-843. [PMID: 36589501 PMCID: PMC9800242 DOI: 10.1016/j.radcr.2022.11.069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 11/27/2022] [Indexed: 12/24/2022] Open
Abstract
Cystitis cystica and glandularis is a hyperproliferative disease of the urothelium, and may form a papillary or polypoid mass. Clinically, these mass lesions are often difficult to distinguish from malignant tumors. We present a pediatric patient of cystitis cystica and glandularis with a bladder mass and discuss dynamic contrast-enhanced magnetic resonance imaging (MRI) findings and histopathological profiles, which have not been previously explored in the literature. Dynamic contrast-enhanced MRI showed unique, superficial, strong enhancement that resembles an inchworm in appearance. The term "inchworm sign" is a characteristic finding on diffusion-weighted MRI, proposed as a criterion for T-staging in non-muscle-invasive bladder cancer. We would like to propose another "inchworm sign" on dynamic contrast-enhanced MRI as a new hallmark of cystitis cystica and glandularis, which may differentiate it from a malignant tumor.
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Affiliation(s)
- Sota Masuoka
- Department of Radiology, National Center for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, 157-8535, Japan,Department of Diagnostic and Interventional Radiology, University of Tsukuba, Faculty of Medicine, 1-1-1, Tennoudai, Tsukuba, Ibaraki, 305-8575, Japan
| | - Osamu Miyazaki
- Department of Radiology, National Center for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, 157-8535, Japan,Corresponding author.
| | - Ayako Imai
- Department of Radiology, National Center for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, 157-8535, Japan
| | - Reiko Okamoto
- Department of Radiology, National Center for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, 157-8535, Japan
| | - Yoshiyuki Tsutsumi
- Department of Radiology, National Center for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, 157-8535, Japan
| | - Mikiko Miyasaka
- Department of Radiology, National Center for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, 157-8535, Japan
| | - Yuichi Hasegawa
- Department of Urology, National Center for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, 157-8535, Japan
| | - Takako Yoshioka
- Department of Pathology, National Center for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, 157-8535, Japan
| | - Shunsuke Nosaka
- Department of Radiology, National Center for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, 157-8535, Japan
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Eminaga O, Ge TJ, Shkolyar E, Laurie MA, Lee TJ, Hockman L, Jia X, Xing L, Liao JC. An Efficient Framework for Video Documentation of Bladder Lesions for Cystoscopy: A Proof-of-Concept Study. J Med Syst 2022; 46:73. [PMID: 36190581 PMCID: PMC10751224 DOI: 10.1007/s10916-022-01862-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 09/07/2022] [Indexed: 10/10/2022]
Abstract
Processing full-length cystoscopy videos is challenging for documentation and research purposes. We therefore designed a surgeon-guided framework to extract short video clips with bladder lesions for more efficient content navigation and extraction. Screenshots of bladder lesions were captured during transurethral resection of bladder tumor, then manually labeled according to case identification, date, lesion location, imaging modality, and pathology. The framework used the screenshot to search for and extract a corresponding 10-seconds video clip. Each video clip included a one-second space holder with a QR barcode informing the video content. The success of the framework was measured by the secondary use of these short clips and the reduction of storage volume required for video materials. From 86 cases, the framework successfully generated 249 video clips from 230 screenshots, with 14 erroneous video clips from 8 screenshots excluded. The HIPPA-compliant barcodes provided information of video contents with a 100% data completeness. A web-based educational gallery was curated with various diagnostic categories and annotated frame sequences. Compared with the unedited videos, the informative short video clips reduced the storage volume by 99.5%. In conclusion, our framework expedites the generation of visual contents with surgeon's instruction for cystoscopy and potential incorporation of video data towards applications including clinical documentation, education, and research.
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Affiliation(s)
- Okyaz Eminaga
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA, 94304, USA.
| | - T Jessie Ge
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Eugene Shkolyar
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Mark A Laurie
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Timothy J Lee
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Lukas Hockman
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Xiao Jia
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA
| | - Lei Xing
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA
| | - Joseph C Liao
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA, 94304, USA.
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