Volume 1 Issue 2 | Biophotonics Discovery

Biophotonics Discovery

VOL. 1 · NO. 2 | July 2024

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IN PROGRESS

SPIE publishes accepted journal articles as soon as they are approved for publication. Journal issues are considered In Progress until all articles for an issue have been published. Articles published ahead of the completed issue are fully citable.

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Review Paper (1)

Research (2)

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Review Paper

Review of Cherenkov imaging technology advances in radiotherapy: single-photon-level imaging in high ambient light and radiation backgrounds

Aubrey Parks, Jeremy Hallett, Alexander Niver, Rongxiao Zhang, Petr Bruza, Brian Pogue

Biophotonics Discovery, Vol. 1, Issue 02, 020901, (July 2024) https://doi.org/10.1117/1.BIOS.1.2.020901

TOPICS: Radiotherapy, Cameras, Tissues, Scintillators, Signal detection, Interference (communication), Tunable filters, Optical filters, Imaging technologies, Biomedical optics

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Significance

Single-photon-level imaging has been utilized for decades in closed dark environments; however, the utility for macroscopic imaging is more limited because it involves time-gating, filtering, and processing to view signals of interest. In radiation therapy delivery, a low-level signal called Cherenkov emission occurs from patients’ bodies, which is imaged with single-photon level sensitivity, mapping radiation dose deposition in tissue. Several key technological advances have been leveraged to make this extremely low-light signal overcome high background and noise in clinical settings.

Aim

Our review summarizes specific technological advances that have led to a single-photon imaging in high radiation noise and high optical background environments possible. Our work discusses applications and future opportunities.

Approach

Physical fundamentals of Cherenkov light, ambient room light, optical filtering, time-gating, and image processing are reviewed with key technological camera choices. This is followed by discussion of image quality, noise, and postprocessing, with current and future applications.

Results

Invention and optimization of time-gating techniques and cameras with a single-photon capability were required to achieve real-time Cherenkov imaging. Requirements of video frame rate (≈10 to 30 fps), fast triggering (≈μs), clinically relevant spatial resolution (≈mm), single-photon/pixel sensitivity, and large field of view all led to intensified complementary metal-oxide-semiconductor cameras. Additional innovations in wavelength filtering, lens choices, and spatial and temporal postprocessing have allowed imaging that is not overwhelmed by ambient radiation noise or room lights. The current use provides real-time visualization of external beam radiotherapy on patient’s skin. Several emerging research areas may improve image quality and provide additional capabilities in biochemical sensing and quantification of delivery.

Conclusion

The technical inventions and discoveries on how this light signal is sampled have led to real-time beam observation for dose delivery verification in settings where single-photon sensitive imaging is seemingly implausible while also opening the door to additional research applications.

Research

Computer-assisted discrimination of cancerous and pre-cancerous from benign oral lesions based on multispectral autofluorescence imaging endoscopy

Elvis de Jesus Duran Sierra, Shuna Cheng, Rodrigo Cuenca Martinez, Beena Ahmed, Jim Ji, Vladislav Yakovlev, Mathias Martinez, Moustafa Al-Khalil, Hussain Al-Enazi, Carlos Busso, Javier Jo

Biophotonics Discovery, Vol. 1, Issue 02, 025001, (July 2024) https://doi.org/10.1117/1.BIOS.1.2.025001

TOPICS: Autofluorescence, Tumor growth modeling, Multispectral imaging, Endoscopy, Cancer, Image classification, Autofluorescence imaging, Cancer detection, Tissues, Diagnostics

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Significance

Diagnosis of cancerous and pre-cancerous oral lesions at early stages is critical for the improvement of patient care, to increase survival rates and minimize the invasiveness of tumor resection surgery. Unfortunately, oral precancerous and early-stage cancerous lesions are often difficult to distinguish from oral benign lesions with the existing diagnostic tools used during standard clinical oral examination. In consequence, early diagnosis of oral cancer can be achieved in only about 30% of patients. Therefore, clinical diagnostic technologies for fast, minimally invasive, and accurate oral cancer screening are urgently needed.

Aim

This study investigated the use of multispectral autofluorescence imaging endoscopy for the automated and noninvasive discrimination of cancerous and precancerous from benign oral epithelial lesions.

Approach

In vivo multispectral autofluorescence endoscopic images of clinically suspicious oral lesions were acquired from 67 patients undergoing tissue biopsy examination. The imaged lesions were classified as precancerous (n=4), cancerous (n=29), and benign (n=34) lesions based on histopathology diagnosis. Multispectral autofluorescence intensity feature maps were generated for each oral lesion and used to train and optimize support vector machine (SVM) models for automated discrimination of cancerous and precancerous from benign oral lesions.

Results

After a leave-one-patient-out cross-validation strategy, an optimized SVM model developed with four multispectral autofluorescence features yielded levels of sensitivity and specificity of 85% and 71%, respectively and overall accuracy of 78% in the discrimination of cancerous/precancerous versus benign oral lesions.

Conclusion

This study demonstrates the potentials of a computer-assisted detection system based on multispectral autofluorescence imaging endoscopy for the early detection of cancerous and precancerous oral lesions.

In vivo spectroscopy to concurrently characterize five metabolic and vascular endpoints relevant to aggressive breast cancer

Victoria D’Agostino, Riley Deutsch, Michelle Kwan, Enakshi Sunassee, Megan Madonna, Gregory Palmer, Brian Crouch, Nirmala Ramanujam

Biophotonics Discovery, Vol. 1, Issue 02, 025002, (July 2024) https://doi.org/10.1117/1.BIOS.1.2.025002

TOPICS: Tumors, Fluorophores, Tissues, In vivo imaging, Monte Carlo methods, Spectroscopy, Fluorescence, Crosstalk, Biomedical optics, Glucose

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