Optical Mapping Methods for Treating Cancer in Low- and Middle-Income Countries like India

Authors

  • Soumya Mazumdar Indian Institute of Technology Madras, Gargi Memorial Institute of Technology [JIS Group], West Bengal

DOI:

https://doi.org/10.37506/qranvz77

Keywords:

optical imaging, cancer treatment, flurorescence imaging, bioluminescence imaging, raman spectroscopy, optical coherence tomography, cancer surgery, treatment monitoring

Abstract

Cancer presents substantial challenges globally, particularly in low- and middle-income countries (LMICs) such as India, where resources are limited. This study explores the potential of optical imaging technologies for cancer diagnosis in low-resource settings (LRS) within India. It assesses the benefits, prospects, and obstacles associated with their adoption. Optical imaging offers advantages including non-invasiveness, automated diagnosis, and cost-effectiveness; however, its widespread implementation faces constraints such as high initial costs, inadequate infrastructure, a shortage of skilled personnel, and integration challenges with existing healthcare systems. Addressing these challenges necessitates strategies involving capital investments, skill enhancement, and infrastructure development. Affordable and user-friendly optical imaging systems tailored for LRS have been developed, and the
application of artificial intelligence (AI) shows promise for improving cancer diagnosis in LMICs like India. This study reviews the latest advancements in optical imaging technology and underscores the need for further research and collaboration to enhance cancer treatment in India and other LMICs.

References

dos-Santos-Silva I, Gupta S, Orem J, Shulman LN. Global disparities in access to cancer care. Commun Med. 2022;2(1). https://doi.org/10.1038/s43856-022-00097-5

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49. https://doi.org/10.3322/caac.21660

Pierce MC, Richards-Kortum R. Low-cost, portable optical imaging systems for cancer diagnosis. IEEE Eng Med Biol Soc. 2010. https://doi.org/10.1109/iembs.2010.5627330

Zhang Y, Wu X, He L, Meng C, Du S, Bao J, et al. Applications of hyperspectral imaging in the detection and diagnosis of solid tumors. Transl Cancer Res. 2020;9(2):1265–77. https://doi.org/10.21037/tcr.2019.12.53

Shao C, Li Z, Zhang C, Zhang W, He R, Cai Y, et al. Optical diagnostic imaging and therapy for thyroid cancer. Mater Today Bio. 2022;17:100441. https://doi.org/10.1016/j.mtbio.2022.100441

Lin L, Jiang P, Bao Z, Pang W, Ding S, Yin M, et al. Fundamentals of Optical Imaging. In: Advances in Experimental Medicine and Biology. 2021. p. 1–22. https://doi.org/10.1007/978-981-15-7627-0_1

Williams D, Hornung H, Nadimpalli A, Peery A. Deep Learning and its Application for Healthcare Delivery in Low and Middle Income Countries. Front Artif Intell. 2021;4. https://doi.org/10.3389/frai.2021.553987

Mueller JL, Lam CT, Dahl DK, Asiedu MN, Krieger M, Fuentes YMB, et al. Portable Pocket colposcopy performs comparably to standard-of-care clinical colposcopy using acetic acid and Lugol’s iodine as contrast mediators: an investigational study in Peru. BJOG. 2018;125(10):1321–

https://doi.org/10.1111/1471-0528.15326

Taghavi K, Banerjee D, Mandal R, Kallner HK, Thorsell M, Friis T, et al. Colposcopy telemedicine: live versus static swede score and accuracy in detecting CIN2+, a cross-sectional pilot study. BMC Womens Health. 2018;18(1). https://doi.org/10.1186/s12905-018-0569-1

Mueller JL, Lam CT, Dahl DK, Asiedu MN, Krieger M, Fuentes YMB, et al. Portable Pocket colposcopy performs comparably to standard-of-care clinical colposcopy using acetic acid and Lugol’s iodine as contrast mediators: an investigational study in Peru. BJOG. 2018;125(10):1321–9. https://doi.org/10.1111/1471-0528.15326

Bae JK, Roh H, You JS, Kim K, Ahn Y, Askaruly S, et al. Quantitative Screening of cervical Cancers for Low-Resource Settings: Pilot study of Smartphone-Based Endoscopic Visual Inspection after acetic Acid using Machine learning techniques. JMIR Mhealth Uhealth. 2020;8(3)

. https://doi.org/10.2196/16467

Hou H, Mitbander R, Tang Y, Azimuddin A, Carns J, Schwarz RA, et al. Optical imaging technologies for in vivo cancer detection in low-resource settings. Curr Opin Biomed Eng. 2023;28:100495. https://doi.org/10.1016/j.cobme.2023.100495

Uthoff RD, Song B, Maarouf M, Shi VY, Liang R. Point-of-care, multispectral, smartphone-based dermascopes for dermal lesion screening and erythema monitoring. J Biomed Opt. 2020;25(06):1. https://doi.org/10.1117/1.jbo.25.6.066004

Gebru T, Morgenstern J, Vecchione B, Vaughan J, Wallach H, Daumé H, et al. Datasheets for datasets. Commun ACM. 2021;64(12):86–92. https://doi.org/10.1145/3458723

He QP, Wang K. Hyperspectral imaging enabled by an unmodified smartphone for analyzing skin morphological features and monitoring hemodynamics. Biomed Opt Express. 2020;11(2):895. https://doi.org/10.1364/boe.378470

Kuzmina I, Oshina I, Dambite L, Lukinsone V, Maslobojeva A, Berzina A, et al. Skin chromophore mapping by smartphone RGB camera under spectral band and spectral line illumination. J Biomed Opt. 2022;27(02). https://doi.org/10.1117/1.jbo.27.2.026004

Ding H, Chen C, Zhao H, Yue Y, Han C. Smartphone based multispectral imager and its potential for point-of-care testing. Analyst. 2019;144(14):4380–5. https://doi.org/10.1039/c9an00853e

Bishop MM. AccessNeurology Walkthrough. J Electron Resour Med Libr. 2022;19(1–2):27–36. https://doi.org/10.1080/15424065.2022.2046233

Baxi V, Edwards R, Montalto M, Saha S. Digital pathology and artificial intelligence in translational medicine and clinical practice. Mod Pathol. 2022;35(1):23–32. https://doi.org/10.1038/s41379-021-00919-2

Smith BL, Gadd MA, Lanahan CR, Rai U, Tang R, Rice-Stitt T, et al. Real-time, intraoperative detection of residual breast cancer in lumpectomy cavity walls using a novel cathepsin-activated fluorescent imaging system. Breast Cancer Res Treat. 2018;171(2):413–20.

https://doi.org/10.1007/s10549-018-4845-4

Miampamba M, Liu J, Harootunian A, Gale AJ, Baird SM, Chen SL, et al. Sensitive in vivo Visualization of Breast Cancer Using Ratiometric Protease-activatable Fluorescent Imaging Agent, AVB-620. Theranostics. 2017;7(13):3369–86. https://doi.org/10.7150/thno.20678

Bradbury MS, Pauliah M, Zanzonico P, Wiesner U, Patel SG. Intraoperative mapping of sentinel lymph node metastases using a clinically translated ultrasmall silica nanoparticle. WIREs Nanomed Nanobiotechnol. 2015;8(4):535–53. https://doi.org/10.1002/wnan.1380

Baik FM, Hansen S, Knoblaugh SE, Sahetya D, Mitchell RM, Xu C, et al. Fluorescence identification of head and neck squamous cell carcinoma and High-Risk oral dysplasia with BLZ- 100, a Chlorotoxin-Indocyanine green conjugate. JAMA Otolaryngol Head Neck Surg.

;142(4):330. https://doi.org/10.1001/jamaoto.2015.3617

Downloads

Published

2024-06-06

Similar Articles

1-10 of 41

You may also start an advanced similarity search for this article.