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Hou H, Mitbander R, Tang Y, Azimuddin A, Carns J, Schwarz RA, Richards-Kortum RR. Optical imaging technologies for in vivo cancer detection in low-resource settings. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2023; 28:100495. [PMID: 38406798 PMCID: PMC10883072 DOI: 10.1016/j.cobme.2023.100495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Cancer continues to affect underserved populations disproportionately. Novel optical imaging technologies, which can provide rapid, non-invasive, and accurate cancer detection at the point of care, have great potential to improve global cancer care. This article reviews the recent technical innovations and clinical translation of low-cost optical imaging technologies, highlighting the advances in both hardware and software, especially the integration of artificial intelligence, to improve in vivo cancer detection in low-resource settings. Additionally, this article provides an overview of existing challenges and future perspectives of adapting optical imaging technologies into clinical practice, which can potentially contribute to novel insights and programs that effectively improve cancer detection in low-resource settings.
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Affiliation(s)
- Huayu Hou
- Department of Bioengineering, Rice University, Houston, TX 77005, USA
| | - Ruchika Mitbander
- Department of Bioengineering, Rice University, Houston, TX 77005, USA
| | - Yubo Tang
- Department of Bioengineering, Rice University, Houston, TX 77005, USA
| | - Ahad Azimuddin
- School of Medicine, Texas A&M University, Houston, TX 77030, USA
| | - Jennifer Carns
- Department of Bioengineering, Rice University, Houston, TX 77005, USA
| | - Richard A Schwarz
- Department of Bioengineering, Rice University, Houston, TX 77005, USA
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Luo N, Zhong X, Su L, Cheng Z, Ma W, Hao P. Artificial intelligence-assisted dermatology diagnosis: From unimodal to multimodal. Comput Biol Med 2023; 165:107413. [PMID: 37703714 DOI: 10.1016/j.compbiomed.2023.107413] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 08/02/2023] [Accepted: 08/28/2023] [Indexed: 09/15/2023]
Abstract
Artificial Intelligence (AI) is progressively permeating medicine, notably in the realm of assisted diagnosis. However, the traditional unimodal AI models, reliant on large volumes of accurately labeled data and single data type usage, prove insufficient to assist dermatological diagnosis. Augmenting these models with text data from patient narratives, laboratory reports, and image data from skin lesions, dermoscopy, and pathologies could significantly enhance their diagnostic capacity. Large-scale pre-training multimodal models offer a promising solution, exploiting the burgeoning reservoir of clinical data and amalgamating various data types. This paper delves into unimodal models' methodologies, applications, and shortcomings while exploring how multimodal models can enhance accuracy and reliability. Furthermore, integrating cutting-edge technologies like federated learning and multi-party privacy computing with AI can substantially mitigate patient privacy concerns in dermatological datasets and further fosters a move towards high-precision self-diagnosis. Diagnostic systems underpinned by large-scale pre-training multimodal models can facilitate dermatology physicians in formulating effective diagnostic and treatment strategies and herald a transformative era in healthcare.
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Affiliation(s)
- Nan Luo
- Hospital of Chengdu University of Traditional Chinese Medicine, No. 39 Shi-er-qiao Road, Chengdu, 610075, Sichuan, China.
| | - Xiaojing Zhong
- Hospital of Chengdu University of Traditional Chinese Medicine, No. 39 Shi-er-qiao Road, Chengdu, 610075, Sichuan, China.
| | - Luxin Su
- Hospital of Chengdu University of Traditional Chinese Medicine, No. 39 Shi-er-qiao Road, Chengdu, 610075, Sichuan, China.
| | - Zilin Cheng
- Hospital of Chengdu University of Traditional Chinese Medicine, No. 39 Shi-er-qiao Road, Chengdu, 610075, Sichuan, China.
| | - Wenyi Ma
- Hospital of Chengdu University of Traditional Chinese Medicine, No. 39 Shi-er-qiao Road, Chengdu, 610075, Sichuan, China.
| | - Pingsheng Hao
- Hospital of Chengdu University of Traditional Chinese Medicine, No. 39 Shi-er-qiao Road, Chengdu, 610075, Sichuan, China.
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Kang D. Low-Cost, In Vivo Optical Microscopy Methods for Examining Cellular Details at the Point of Care. MICROSCOPY AND MICROANALYSIS : THE OFFICIAL JOURNAL OF MICROSCOPY SOCIETY OF AMERICA, MICROBEAM ANALYSIS SOCIETY, MICROSCOPICAL SOCIETY OF CANADA 2023; 29:1100. [PMID: 37613206 DOI: 10.1093/micmic/ozad067.566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Affiliation(s)
- Dongkyun Kang
- College of Optical Sciences, University of Arizona, Tucson, AZ, USA
- Department of Biomedical Engineering, University of Arizona, Tucson, AZ, USA
- University of Arizona Cancer Center, University of Arizona, Tucson, AZ, USA
- Bio5 Institute, University of Arizona, Tucson, AZ, USA
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Atak MF, Farabi B, Navarrete-Dechent C, Rubinstein G, Rajadhyaksha M, Jain M. Confocal Microscopy for Diagnosis and Management of Cutaneous Malignancies: Clinical Impacts and Innovation. Diagnostics (Basel) 2023; 13:diagnostics13050854. [PMID: 36899999 PMCID: PMC10001140 DOI: 10.3390/diagnostics13050854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 02/10/2023] [Accepted: 02/20/2023] [Indexed: 02/25/2023] Open
Abstract
Cutaneous malignancies are common malignancies worldwide, with rising incidence. Most skin cancers, including melanoma, can be cured if diagnosed correctly at an early stage. Thus, millions of biopsies are performed annually, posing a major economic burden. Non-invasive skin imaging techniques can aid in early diagnosis and save unnecessary benign biopsies. In this review article, we will discuss in vivo and ex vivo confocal microscopy (CM) techniques that are currently being utilized in dermatology clinics for skin cancer diagnosis. We will discuss their current applications and clinical impact. Additionally, we will provide a comprehensive review of the advances in the field of CM, including multi-modal approaches, the integration of fluorescent targeted dyes, and the role of artificial intelligence for improved diagnosis and management.
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Affiliation(s)
- Mehmet Fatih Atak
- Department of Dermatology, New York Medical College, Metropolitan Hospital, New York, NY 10029, USA
| | - Banu Farabi
- Department of Dermatology, New York Medical College, Metropolitan Hospital, New York, NY 10029, USA
| | - Cristian Navarrete-Dechent
- Department of Dermatology, Escuela de Medicina, Pontificia Universidad Catolica de Chile, Santiago 8331150, Chile
| | | | - Milind Rajadhyaksha
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Manu Jain
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Dermatology Service, Department of Medicine, Weill Cornell Medicine, New York, NY 10021, USA
- Correspondence: ; Tel.: +1-(646)-608-3562
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Bishop KW, Maitland KC, Rajadhyaksha M, Liu JTC. In vivo microscopy as an adjunctive tool to guide detection, diagnosis, and treatment. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-220032-PER. [PMID: 35478042 PMCID: PMC9043840 DOI: 10.1117/1.jbo.27.4.040601] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 04/05/2022] [Indexed: 05/05/2023]
Abstract
SIGNIFICANCE There have been numerous academic and commercial efforts to develop high-resolution in vivo microscopes for a variety of clinical use cases, including early disease detection and surgical guidance. While many high-profile studies, commercialized products, and publications have resulted from these efforts, mainstream clinical adoption has been relatively slow other than for a few clinical applications (e.g., dermatology). AIM Here, our goals are threefold: (1) to introduce and motivate the need for in vivo microscopy (IVM) as an adjunctive tool for clinical detection, diagnosis, and treatment, (2) to discuss the key translational challenges facing the field, and (3) to propose best practices and recommendations to facilitate clinical adoption. APPROACH We will provide concrete examples from various clinical domains, such as dermatology, oral/gastrointestinal oncology, and neurosurgery, to reinforce our observations and recommendations. RESULTS While the incremental improvement and optimization of IVM technologies should and will continue to occur, future translational efforts would benefit from the following: (1) integrating clinical and industry partners upfront to define and maintain a compelling value proposition, (2) identifying multimodal/multiscale imaging workflows, which are necessary for success in most clinical scenarios, and (3) developing effective artificial intelligence tools for clinical decision support, tempered by a realization that complete adoption of such tools will be slow. CONCLUSIONS The convergence of imaging modalities, academic-industry-clinician partnerships, and new computational capabilities has the potential to catalyze rapid progress and adoption of IVM in the next few decades.
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Affiliation(s)
- Kevin W. Bishop
- University of Washington, Department of Bioengineering, Seattle, Washington, United States
- University of Washington, Department of Mechanical Engineering, Seattle, Washington, United States
| | - Kristen C. Maitland
- Texas A&M University, Department of Biomedical Engineering, College Station, Texas, United States
| | - Milind Rajadhyaksha
- Memorial Sloan Kettering Cancer Center, Dermatology Service, New York, New York, United States
| | - Jonathan T. C. Liu
- University of Washington, Department of Bioengineering, Seattle, Washington, United States
- University of Washington, Department of Mechanical Engineering, Seattle, Washington, United States
- University of Washington, Department of Laboratory Medicine and Pathology, Seattle, Washington, United States
- Address all correspondence to Jonathan T.C. Liu,
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Kulkarni N, Masciola A, Nishant A, Kim KJ, Choi H, Gmitro A, Freeman EE, Semeere A, Nakalembe M, Kang D. Low-cost, chromatic confocal endomicroscope for cellular imaging in vivo. BIOMEDICAL OPTICS EXPRESS 2021; 12:5629-5643. [PMID: 34692205 PMCID: PMC8515984 DOI: 10.1364/boe.434892] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 07/29/2021] [Accepted: 08/01/2021] [Indexed: 05/06/2023]
Abstract
We have developed a low-cost, chromatic confocal endomicroscope (CCE) that can image a cross-section of the tissue at cellular resolution. In CCE, a custom miniature objective lens was used to focus different wavelengths into different tissue depths. Therefore, each tissue depth was encoded with the wavelength. A custom miniature spectrometer was used to spectrally-disperse light reflected from the tissue and generate cross-sectional confocal images. The CCE prototype had a diameter of 9.5 mm and a length of 68 mm. Measured resolution was high, 2 µm and 4 µm for lateral and axial directions, respectively. Effective field size was 468 µm. Preliminary results showed that CCE can visualize cellular details from cross-sections of the tissue in vivo down to the tissue depth of 100 µm.
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Affiliation(s)
- Nachiket Kulkarni
- James C. Wyant College of Optical Sciences, University of Arizona, Tucson, Arizona 85721, USA
| | - Andrew Masciola
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona 85721, USA
| | - Abhinav Nishant
- James C. Wyant College of Optical Sciences, University of Arizona, Tucson, Arizona 85721, USA
| | - Kyung-Jo Kim
- James C. Wyant College of Optical Sciences, University of Arizona, Tucson, Arizona 85721, USA
| | - Heejoo Choi
- James C. Wyant College of Optical Sciences, University of Arizona, Tucson, Arizona 85721, USA
| | - Arthur Gmitro
- James C. Wyant College of Optical Sciences, University of Arizona, Tucson, Arizona 85721, USA
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona 85721, USA
| | - Esther E. Freeman
- Department of Dermatology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Aggrey Semeere
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
- Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA 94143, USA
| | - Miriam Nakalembe
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
| | - Dongkyun Kang
- James C. Wyant College of Optical Sciences, University of Arizona, Tucson, Arizona 85721, USA
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona 85721, USA
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