Design and clinical validation of a point-of-care device for the diagnosis of lymphoma via contrast-enhanced microholography and machine learning.

The identification of patients with aggressive cancer who require immediate therapy is a health challenge in low-income and middle-income countries. Limited pathology resources, high healthcare costs and large-case loads call for the development of advanced standalone diagnostics. Here, we report and validate an automated, low-cost point-of-care device for the molecular diagnosis of aggressive lymphomas.

Holographic Assessment of Lymphoma Tissue (HALT) for Global Oncology Field Applications.

Low-cost, rapid and accurate detection technologies are key requisites to cope with the growing global cancer challenges. The need is particularly pronounced in resource-limited settings where treatment opportunities are often missed due to the absence of timely diagnoses. We herein describe a Holographic Assessment of Lymphoma Tissue (HALT) system that adopts a smartphone as the basis for molecular cancer diagnostics.

Digital diffraction analysis enables low-cost molecular diagnostics on a smartphone.

The widespread distribution of smartphones, with their integrated sensors and communication capabilities, makes them an ideal platform for point-of-care (POC) diagnosis, especially in resource-limited settings. Molecular diagnostics, however, have been difficult to implement in smartphones. We herein report a diffraction-based approach that enables molecular and cellular diagnostics.

Noise suppressed, multifocus image fusion for enhanced intraoperative navigation.

Current intraoperative imaging systems are typically not able to provide 'sharp' images over entire large areas or entire organs. Distinct structures such as tissue margins or groups of malignant cells are therefore often difficult to detect, especially under low signal-to-noise-ratio conditions. In this report, we introduce a noise suppressed multifocus image fusion algorithm, that provides detailed reconstructions even when images are acquired under sub-optimal conditions, such is the case for real time fluorescence intraoperative surgery.

Hybrid PET-optical imaging using targeted probes.

Fusion imaging of radionuclide-based molecular (PET) and structural data [x-ray computed tomography (CT)] has been firmly established. Here we show that optical measurements [fluorescence-mediated tomography (FMT)] show exquisite congruence to radionuclide measurements and that information can be seamlessly integrated and visualized. Using biocompatible nanoparticles as a generic platform (containing a (18)F isotope and a far red fluorochrome), we show good correlations between FMT and PET in probe concentration (r(2) > 0.