Dual excitation spectral autofluorescence lifetime and reflectance imaging for fast macroscopic characterization of tissues.

Advancements in optical imaging techniques have revolutionized the field of biomedical research, allowing for the comprehensive characterization of tissues and their underlying biological processes. Yet, there is still a lack of tools to provide quantitative and objective characterization of tissues that can aid clinical assessment in vivo to enhance diagnostic and therapeutic interventions. Here, we present a clinically viable fiber-based imaging system combining time-resolved spectrofluorimetry and reflectance spectroscopy to achieve fast multiparametric macroscopic characterization of tissues. An essential feature of the setup is its ability to perform dual wavelength excitation in combination with recording time-resolved fluorescence data in several spectral intervals. Initial validation of this bimodal system was carried out in freshly resected human colorectal cancer specimens, where we demonstrated the ability of the system to differentiate normal from malignant tissues based on their autofluorescence and reflectance properties. To further highlight the complementarity of autofluorescence and reflectance measurements and demonstrate viability in a clinically relevant scenario, we also collected in vivo data from the skin of a volunteer. Altogether, integration of these modalities in a single platform can offer multidimensional characterization of tissues, thus facilitating a deeper understanding of biological processes and potentially advancing diagnostic and therapeutic approaches in various medical applications.

Zebrafish Avatar-test forecasts clinical response to chemotherapy in patients with colorectal cancer.

Cancer patients often undergo rounds of trial-and-error to find the most effective treatment because there is no test in the clinical practice for predicting therapy response. Here, we conduct a clinical study to validate the zebrafish patient-derived xenograft model (zAvatar) as a fast predictive platform for personalized treatment in colorectal cancer. zAvatars are generated with patient tumor cells, treated exactly with the same therapy as their corresponding patient and analyzed at single-cell resolution. By individually comparing the clinical responses of 55 patients with their zAvatar-test, we develop a decision tree model integrating tumor stage, zAvatar-apoptosis, and zAvatar-metastatic potential. This model accurately forecasts patient progression with 91% accuracy. Importantly, patients with a sensitive zAvatar-test exhibit longer progression-free survival compared to those with a resistant test. We propose the zAvatar-test as a rapid approach to guide clinical decisions, optimizing treatment options and improving the survival of cancer patients.

Systemic mastocytosis - a diagnostic challenge

Mastocytosis refers to a group of disorders characterized by the infiltration of clonally derived mast cells to the skin or extracutaneous tissues resulting in a heterogeneous clinical picture. It is a rare hematologic disorder in all its forms. The exact incidence is unknown; it affects patients of any age and males and females equally. Its molecular pathogenesis is incompletely understood. The clinical features of mastocytosis result from both chronic and episodic mast cell mediator release, signs and symptoms arising from diffuse or focal tissue infiltration, and, occasionally, the presence of an associated non-mast cell clonal hematologic disease. The histopathologic analysis is essential for definitive diagnosis but there is no curative treatment. The authors report a clinical case of a 72-year-old woman with no history of allergies, with bicytopenia, weight loss, and diffuse axial osteolytic lesions. This is a rare clinical case of aggressive systemic mastocytosis for which palliative treatment can improve survival and quality of life. A brief review of the literature about this pathology is also included.