HyU: Hybrid Unmixing for longitudinal in vivo imaging of low signal to noise fluorescence

The expanded application of fluorescence imaging in biomedical and biological research towards more complex systems and geometries requires tools that can analyze a multitude of components at widely varying time- and length-scales. The major challenge in such complex imaging experiments is to cleanly separate multiple fluorescent labels with overlapping spectra from one another and background autofluorescence, without perturbing the sample with high levels of light. Thus, there is a requirement for efficient and robust analysis tools capable of quantitatively separating these signals. In response, we have combined multispectral fluorescence microscopy with hyperspectral phasors and linear unmixing to create Hybrid Unmixing (HyU). Here we demonstrate its capabilities in the dynamic imaging of multiple fluorescent labels in live, developing zebrafish embryos. HyU is more sensitive to low light levels of fluorescence compared to conventional linear unmixing approaches, permitting better multiplexed volumetric imaging over time, with less bleaching. HyU can also simultaneously image both bright exogenous and dim endogenous labels because of its high dynamic range. This allows studies of cellular behaviors, tagged components, and cell metabolism within the same specimen, offering a powerful window into the orchestrated complexity of biological systems.

3D-Printed Cold Preservation Device in Renal Autotransplantation for the Treatment of a Patient With Renal Artery Stenosis

Percutaneous transluminal angioplasty (PTRA) is a common treatment method for renal vascular disease (RVD). However, PTRA may not be effective in patients with abnormal vascular disease. Renal autotransplantation (RAT) has been used as an alternative therapy for these diseases. Restrictions due to intracorporeal kidney cold preservation and the renal function of intracorporeal RAT were not as well protected compared with open operation. We developed this technique of 3D-printed polylactide (PLA) cold jackets for laparoscopic complete intracorporeal RAT for the purpose of better protecting the renal function and determining the feasibility of this novel procedure. The procedure was successfully applied to a 51-year-old woman with bilateral renal artery stenosis. The operation time was 5 hours, and blood loss was 200 ml. The patient’s blood pressure remained constant throughout the operation, and the pressure was maintained at 120-140/70–90 mmHg without antihypertensive drugs 1 week after the operation. B-ultrasound showed that the blood flow signal of the transplanted kidney was normal and the boundary between the skin and medulla was clear. The patient was discharged 2 weeks after surgery. One year postoperatively, Doppler ultrasound of the autotransplant showed that the transplanted kidney was normal in size and shape. Radionuclide renal dynamic imaging revealed that the glomerular filtration rate (GFR) of the transplanted kidney was 36.9 ml/min. 3D-printed polylactide (PLA) cold jackets for laparoscopic complete intracorporeal RAT are a safe and effective method for the treatment of renal artery stenosis and represent a feasible method for preserving the renal function of severe renal artery stenosis patients; however, the technology is still at the exploratory stage and has room for further improvements.

Nanosecond-resolution photothermal dynamic imaging via MHZ digitization and match filtering

Photothermal microscopy has enabled highly sensitive label-free imaging of absorbers, from metallic nanoparticles to chemical bonds. Photothermal signals are conventionally detected via modulation of excitation beam and demodulation of probe beam using lock-in amplifier. While convenient, the wealth of thermal dynamics is not revealed. Here, we present a lock-in free, mid-infrared photothermal dynamic imaging (PDI) system by MHz digitization and match filtering at harmonics of modulation frequency. Thermal-dynamic information is acquired at nanosecond resolution within single pulse excitation. Our method not only increases the imaging speed by two orders of magnitude but also obtains four-fold enhancement of signal-to-noise ratio over lock-in counterpart, enabling high-throughput metabolism analysis at single-cell level. Moreover, by harnessing the thermal decay difference between water and biomolecules, water background is effectively separated in mid-infrared PDI of living cells. This ability to nondestructively probe chemically specific photothermal dynamics offers a valuable tool to characterize biological and material specimens.

Myotendinous pseudomasses: an imaging review

A mass or a tumor may not always be an underlying cause for a clinically apparent swelling. A wide range of myotendinous disorders can present as pseudomasses. These include muscle/myofascial hernia, tendon tears, benign hypertrophy, accessory muscles, tendon xanthomas, diffuse myositis, and exertional compartment syndromes. We have briefly reviewed these lesions highlighting their typical radiological findings and have also highlighted the role of different imaging modalities and the role of dynamic imaging. Although rare, radiologists should be aware of these entities to avoid mislabeling a pseudomass as a mass or malignancy and to detect the abnormality in not-so-apparent masses.

Concept of 'Central' or 'Axial' Atlantoaxial Instability

The atlantoaxial joint is the most mobile joint of the spine and is most liable to develop instability. Atlantoaxial instability can be identified on observation of facetal alignment on lateral profile imaging, telltale clinical and radiological evidence and by direct observation of instability by manual manipulation of bones during surgery. Central or axial atlantoaxial instability is when there is no abnormal increase in atlantodental interval on dynamic imaging and there is no dural or neural compression by the odontoid process. Understanding and appropriately treating central or axial atlantoaxial instability can have clinical implications.

Cancer-Cell Deep-Learning Classification by Integrating Quantitative-Phase Spatial and Temporal Fluctuations

We present a new classification approach for live cells, integrating together the spatial and temporal fluctuation maps and the quantitative optical thickness map of the cell, as acquired by common-path quantitative-phase dynamic imaging and processed with a deep-learning framework. We demonstrate this approach by classifying between two types of cancer cell lines of different metastatic potential originating from the same patient. It is based on the fact that both the cancer-cell morphology and its mechanical properties, as indicated by the cell temporal and spatial fluctuations, change over the disease progression. We tested different fusion methods for inputting both the morphological optical thickness maps and the coinciding spatio-temporal fluctuation maps of the cells to the classifying network framework. We show that the proposed integrated triple-path deep-learning architecture improves over deep-learning classification that is based only on the cell morphological evaluation via its quantitative optical thickness map, demonstrating the benefit in the acquisition of the cells over time and in extracting their spatio-temporal fluctuation maps, to be used as an input to the classifying deep neural network.