There are an expanding number of contrast agents under development in the field of intraoperative fluorescence imaging. We demonstrate solid phantoms focused on addressing clinical and pre-clinical fluorophores while also incorporating tissue-mimicking optical properties. Characterization techniques and design considerations are discussed. Examples of OTL38-equivalent solid reference targets and dynamic flow phantoms are presented. Use cases are used to demonstrate how these tools reduce development time and accelerate the clinical adoption of new fluorescence imaging technologies.
The emerging clinical use of fluorescent agents has led to a shift in intraoperative imaging practices that overcome the limitations of human vision, thereby improving treatment outcomes in applications such as perfusion assessment and positive margins in tumor resection. As the field of fluorescence-guided surgery (FGS) expands, there is a wider range of imaging systems that are indicated for the same uses, such that there is a compelling need for standards and methods that enable system characterization and intersystem comparisons. Here we present methods for the radiometric characterization of FGS imaging systems using a calibrated solid-state emitter to enable the conversion of imager-specific responses to SI-traceable units.
According to the American Cancer Society, it is projected that 1.8 million new cancer cases will arise. Of these new cases, 15% are expected to be Breast Cancer related. For many subjects undergoing radiation therapy (RT), radiation dermatitis (RD) is an unavoidable adverse reaction to necessary treatment. As much as 95% of RT subjects will experience RD during or after their treatment plan which can range from mild erythema to full necrosis of the treated tissue. Further complicating matters, the standard assessment approach for RD, the Common Terminology Criteria for Adverse Events (CTCAE), is subjective and relies on the treating clinician’s visual assessment. Assessment of oxygenated blood flow changes holds potential as a means of assessing the severity of RD. In this study, spatial-temporal changes of tissue oxygenation, via a breath-hold paradigm, were monitored in breast cancer subjects across weeks of RT using a near infrared imaging approach. Subjects were imaged dynamically to acquire 2D spatial-temporal maps of tissue oxygenation. A Pearson’s correlation-based approach was applied to spatial-temporal oxygenation maps to determine the extent of symmetry or asymmetry in oxygenated blood flow patterns. Current results indicate that the oxygenated blood flow in tissue regions neighboring the irradiated site are affected by radiation dermatitis. These results are significant as they infer that RT induces altered oxygenated blood flow that could potentially be correlated to RD severity, apart from static tissue oxygenation measurements.
KEYWORDS: Biomedical optics and medical imaging, Medical imaging, Tissues, Chest, Tissue optics, Breast cancer, Skin, Cancer, Oxygen, Radiotherapy, Skin cancer
The American Cancer Society has estimated that a total of 1.8 million new cancer cases will arise in 2020, 15% percent of which are breast cancer. Radiation therapy (RT) is widely used post mastectomy or lumpectomy as a method of avoiding recurrence of disease in affected regions. Photon and proton therapy are among the main forms of RT currently applied to breast cancer patients. The effectiveness of photon vs proton therapy has been studied in various cancer models from differences in subjective clinical grading of radiation dermatitis (RD), a common side effect of RT. Herein, an objective physiological imaging approach using near-infrared optical techniques is implemented to quantitatively differentiate the effectiveness of proton vs photon therapy in breast cancer subjects undergoing RT. A 6-8 week longitudinal pilot study (WIRB approved) was carried out on 10 breast cancer subjects undergoing RT at Miami Cancer Institute (MCI). The chest wall, axilla, and lower neck were imaged on the irradiated and the non-irradiated (contralateral) sides of the torso to measure for tissue oxygenation changes. From preliminary analysis, it was observed that were distinct differences in tissue oxygenation and RD in the irradiated regions when compared to their contralateral nonirradiated tissue (reference). Changes in tissue oxygenation and skin toxicity (i.e. RD clinical grading) were more localized and less severe in subjects receiving proton therapy compared to photon therapy. Quantitative comparison of oxygenation changes and its correlation to the skin toxicity levels in photon vs proton therapy treated breast cancer subjects is currently carried out.
Near-infrared (NIR) spectroscopic imaging of wounds has been performed by past researchers to obtain tissue oxygenation at discrete point locations. We had developed a near-infrared optical scanner (NIROS) that performs noncontact NIR spectroscopic (NIRS) imaging to provide 2D tissue oxygenation maps of the entire wounds. Regions of changed oxygenation have to be demarcated and registered with respect to visual white light images of the wound. Herein, a semi-automatic image segmentation and co-registration approach using machine learning has been developed to differentiate regions of changed tissue oxygenation. A registration technique was applied using a transformation matrix approach using specific markers across the white light image and the NIR images (or tissue oxygenation maps). This allowed for physiological changes observed from hemodynamic changes to be observed in the RGB white light image as well. Semi-automated segmentation techniques employing graph cuts algorithms was implemented to demarcate the 2D tissue oxygenation maps depicting regions of increased or decreased oxygenation and further coregistered onto the white light images. The developed registration technique was validated via phantom studies (both flat and curved phantoms) and in-vivo studies on controls, demonstrating an accuracy >97%. The technique was further implemented on wounds (here, diabetic foot ulcers) across weeks of treatment. Regions of decreased oxygenation were demarcated, and its area estimated and co-registered in comparison to the clinically demarcated wound area. Future work involves the development of automated machine learning approaches of image analysis for clinicians to obtain real-time co-registered clinical and subclinical assessments of the wound.
Diabetic Foot Ulcers (DFUs) are responsible for 20% of diabetic-related hospitalization and 85% of diabetes related amputations. In DFUs the primary factor affecting healing is an adequate oxygen supply to the wound. However, the gold standard approach for assessing DFUs is by evaluating the reduction of wound size over a four-week period. In this study, we investigate the potential of altered breathing patterns as a technique to assess localized oxygenated perfusion in DFUs as a measure of healing potential. A continuous wave (CW), non-contact, near infrared optical scanner (NIROS) was used to conduct NIR based spectroscopic imaging at dual discrete wavelengths (729nm and 799nm) on DFUs with 7mW of maximum optical power. Subjects were imaged at discrete time points and dynamically utilizing an altered breathing paradigm (i.e. breath-hold) to measure the relative oxy- (ΔHbO) and deoxyhemoglobin (ΔHbR) changes in normal and DFU scenarios. Results show that in normal individuals, ΔHbO/ΔHbR changes at all points of the foot because of altered breathing patterns are synchronous; whereas in the DFU scenario changes in hemodynamic parameters are asynchronous. This indicates that under normal circumstances, oxygenated perfusion changes are consistent and uniform at all points of the foot as opposed to the DFU scenario’s inconsistent oxygenated perfusion. Altered breathing paradigms may serve as a useful tool in assessing localized sub-surface oxygenated perfusion in regions around the wound, and help clinicians better cater the treatment process.
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