Low cost, high temporal resolution optical fiber-based γ-photon sensor for real-time pre-clinical evaluation of cancer-targeting radiopharmaceuticals.

Cancer radiopharmaceutical therapies (RPTs) have demonstrated great promise in the treatment of neuroendocrine and prostate cancer, giving hope to late-stage metastatic cancer patients with currently very few treatment options. These therapies have sparked a large amount of interest in pre-clinical research due to their ability to target metastatic disease, with many research efforts focused towards developing and evaluating targeted RPTs for different cancer types in in vivo models. Here we describe a method for monitoring real-time in vivo binding kinetics for the pre-clinical evaluation of cancer RPTs. Recognizing the significant heterogeneity in biodistribution of RPTs among even genetically identical animal models, this approach offers long-term monitoring of the same in vivo organism without euthanasia in contrast to ex vivo tissue dosimetry, while providing high temporal resolution with a low-cost, easily assembled platform, that is not present in small-animal SPECT/CTs. The method utilizes the developed optical fiber-based γ-photon biosensor, characterized to have a wide linear dynamic range with Lutetium-177 (177Lu) activity (0.5-500 µCi/mL), a common radioisotope used in cancer RPT. The probe's ability to track in vivo uptake relative to SPECT/CT and ex vivo dosimetry techniques was verified by administering 177Lu-PSMA-617 to mouse models bearing human prostate cancer tumors (PC3-PIP, PC3-flu). With this method for monitoring RPT uptake, it is possible to evaluate changes in tissue uptake at temporal resolutions <1 min to determine RPT biodistribution in pre-clinical models and better understand dose relationships with tumor ablation, toxicity, and recurrence when attempting to move therapies towards clinical trial validation.

Signal to Noise Ratio as a Cross-Platform Metric for Intraoperative Fluorescence Imaging.

Real-time molecular imaging to guide curative cancer surgeries is critical to ensure removal of all tumor cells; however, visualization of microscopic tumor foci remains challenging. Wide variation in both imager instrumentation and molecular labeling agents demands a common metric conveying the ability of a system to identify tumor cells. Microscopic disease, comprised of a small number of tumor cells, has a signal on par with the background, making the use of signal (or tumor) to background ratio inapplicable in this critical regime. Therefore, a metric that incorporates the ability to subtract out background, evaluating the signal itself relative to the sources of uncertainty, or noise is required. Here we introduce the signal to noise ratio (SNR) to characterize the ultimate sensitivity of an imaging system and optimize factors such as pixel size. Variation in the background (noise) is due to electronic sources, optical sources, and spatial sources (heterogeneity in tumor marker expression, fluorophore binding, and diffusion). Here, we investigate the impact of these noise sources and ways to limit its effect on SNR. We use empirical tumor and noise measurements to procedurally generate tumor images and run a Monte Carlo simulation of microscopic disease imaging to optimize parameters such as pixel size.

Socioeconomic disparities in timeliness of care and outcomes for anal cancer patients.

BACKGROUND: Socioeconomic status (SES) is associated with diagnostic and treatment delays and survival in multiple cancers, but less data exist for anal squamous cell carcinoma (ASCC). This study investigated the association between SES and outcomes for patients undergoing definitive chemoradiation therapy for ASCC. METHODS: One hundred and eleven patients diagnosed with nonmetastatic ASCC between 2005 and 2018 were retrospectively reviewed. Socioeconomic predictor variables included primary payer, race, income, employment, and partnership status. Outcomes included the tumor-node (TN) stage at diagnosis, the duration from diagnosis to treatment initiation, relapse-free survival (RFS), and overall survival (OS). Age, gender, TN stage, and HIV status were analyzed as covariates in survival analysis. RESULTS: SES was not associated with the TN stage at diagnosis. SES factors associated with treatment initiation delays were Medicaid payer (P = .016) and single partnership status (P = .016). Compared to privately insured patients, Medicaid patients had lower 2-year RFS (64.4% vs 93.8%, P = .021) and OS (82.9% vs 93.5%, P = .038). Similarly, relative to patients in the racial majority, racial minority patients had lower 2-year RFS (53.3% vs 93.5%, P = .001) and OS (73.7% vs 92.6%, P = .008). Race was an independent predictor for both RFS (P = .027) and OS (P = .047). CONCLUSIONS: These results highlight the impact of social contextual factors on health. Interventions targeted at socioeconomically vulnerable populations are needed to reduce disparities in ASCC outcomes.