Background: Magnetic Particle Imaging (MPI) is an emerging imaging modality for quantitative direct imaging of superparamagnetic iron oxide nanoparticles (SPION or SPIO). With different physics from MRI, MPI benefits from ideal image contrast with zero background tissue signal. This enables clear visualization of cancer with image characteristics similar to PET or SPECT, but using radiation-free magnetic nanoparticles instead, with infinite-duration reporter persistence in vivo. MPI for cancer imaging: demonstrated months of quantitative imaging of the cancer-related immune response with in situ SPION-labelling of immune cells (e.g., neutrophils, CAR T-cells). Because MPI suffers absolutely no susceptibility artifacts in the lung, immuno-MPI could soon provide completely noninvasive early-stage diagnosis and treatment monitoring of lung cancers. MPI for magnetic steering: MPI gradients are ~150 × stronger than MRI, enabling remote magnetic steering of magneto-aerosol, nanoparticles, and catheter tips, enhancing therapeutic delivery by magnetic means. MPI for precision therapy: gradients enable focusing of magnetic hyperthermia and magnetic-actuated drug release with up to 2 mm precision. The extent of drug release from the magnetic nanocarrier can be quantitatively monitored by MPI of SPION’s MPS spectral changes within the nanocarrier. Conclusion: MPI is a promising new magnetic modality spanning cancer imaging to guided-therapy.

Biosensing and bioimaging are essential in understanding biological and pathological processes in a living system, for example, in detecting and understanding certain diseases. Optical fiber has made remarkable contributions to the biosensing and bioimaging areas due to its unique advantages of compact size, immunity to electromagnetic interference, biocompatibility, fast response, etc. This review paper will present an overview of seven common types of optical fiber biosensors and optical fiber-based ultrasound detection in photoacoustic imaging (PAI) and the applications of these technologies in biosensing and bioimaging areas. Of course, there are many types of optical fiber biosensors. Still, this paper will review the most common ones: optical fiber grating, surface plasmon resonance, Sagnac interferometer, Mach–Zehnder interferometer, Michelson interferometer, Fabry–Perot Interferometer, lossy mode resonance, and surface-enhanced Raman scattering. Furthermore, different optical fiber techniques for detecting ultrasound in PAI are summarized. Finally, the main challenges and future development direction are briefly discussed.

Atopic dermatitis (AD) is a chronic and pruritic skin inflammatory disease causing a significant burden to health care management and patient’s quality of life. Seemingly healthy skin or non-lesional sites on AD patients still presents skin barrier defects and immune response, which can develop to AD at a later stage. To investigate further the balance between the epidermal barrier impairment and intrinsic immune dysregulation in AD, we exploited multispectral Raster-Scanning Optoacoustic Mesoscopy (ms-RSOM) to image lesional and non-lesional skin areas on AD patients of different severities non-invasively to elucidate their structural features and functional information. Herein, we demonstrate the objective assessment of AD severity using relative changes in oxygen saturation (δsO₂) levels in microvasculature along with other structural parameters such as relative changes in epidermis thickness (δET) and total blood volume (δTBV) between the lesional and non-lesional areas of the skin. We could observe an increasing trend for δsO₂ and δTBV, which correlated well with the subjective clinical Scoring Atopic Dermatitis (SCORAD) for evaluating the severity. Notably, δET showed a decreasing trend with AD severity, indicating that the difference in epidermal thickness between lesional and non-lesional area of the skin decreases with AD severity. Our results also correlated well with conventional metrics such as trans-epidermal water loss (TEWL) and erythrosine sedimentation rate (ESR). We quantified the δsO₂ and δET changes to objectively evaluate the treatment response before and four months after treatment using topical steroids and cyclosporine in one severe AD patient. We observed reduced δsO₂ and δET post treatment. We envision that in future, functional and structural imaging metrics derived from ms-RSOM can be translated as objective markers to assess and stratify the severity of AD and understand the function of skin barrier dysfunctions and immune dysregulation. It could also be employed to monitor the treatment response of AD in regular clinical settings.

Atopic dermatitis (AD) is a common chronic inflammatory skin dermatosis condition due to skin barrier dysfunction that causes itchy, red, swollen, and cracked skin. Currently, AD severity clinical scores are subjected to intra- and inter-observer differences. There is a need for an objective scoring method that is sensitive to skin barrier differences. The aim of this study was to evaluate the relevant skin chemical biomarkers in AD patients. We used confocal Raman micro-spectroscopy and advanced machine learning methods as means to classify eczema patients and healthy controls with sufficient sensitivity and specificity. Raman spectra at different skin depths were acquired from subjects’ lower volar forearm location using an in-house developed handheld confocal Raman micro-spectroscopy system. The Raman spectra corresponding to the skin surface from all the subjects were further analyzed through partial least squares discriminant analysis, a binary classification model allowing the classification between eczema and healthy subjects with a sensitivity and specificity of 0.94 and 0.85, respectively, using stratified K-fold (K = 10) cross-validation. The variable importance in the projection score from the partial least squares discriminant analysis classification model further elucidated the role of important stratum corneum proteins and lipids in distinguishing two subject groups.

More than half of all pleural effusions are due to malignancy of which lung cancer is the main cause. Pleural effusions can complicate the course of pneumonia, pulmonary tuberculosis, or underlying systemic disease. We explore the application of label-free surface-enhanced Raman spectroscopy (SERS) as a point of care (POC) diagnostic tool to identify if pleural effusions are due to lung cancer or to other causes (controls). Lung cancer samples showed specific SERS spectral signatures such as the position and intensity of the Raman band in different wave number region using a novel silver coated silicon nanopillar (SCSNP) as a SERS substrate. We report a classification accuracy of 85% along with a sensitivity and specificity of 87% and 83%, respectively, for the detection of lung cancer over control pleural fluid samples with a receiver operating characteristics (ROC) area under curve value of 0.93 using a PLS-DA binary classifier to distinguish between lung cancer over control subjects. We have also evaluated discriminative wavenumber bands responsible for the distinction between the two classes with the help of a variable importance in projection (VIP) score. We found that our label-free SERS platform was able to distinguish lung cancer from pleural effusions due to other causes (controls) with higher diagnostic accuracy.

Fluorescence imaging has shown great potential in non-invasive plant monitoring and analysis. However, current systems have several limitations, such as bulky size, high cost, contact measurement, and lack of multifunctionality, which may hinder its applications in a wide range of settings including indoor vertical farming. Herein, we developed a compact handheld fluorescence imager enabling multipurpose plant phenotyping, such as continuous photosynthetic activity monitoring and non-destructive anthocyanin quantification. The compact imager comprises of pulse-amplitude-modulated multi-color light emitting diodes (LEDs), optimized light illumination and collection, dedicated driver circuit board, miniaturized charge-coupled device camera, and associated image analytics. Experiments conducted in drought stressed lettuce proved that the novel imager could quantitatively evaluate the plant stress by the non-invasive measurement of photosynthetic activity efficiency. Moreover, a non-invasive and fast quantification of anthocyanins in green and red Batavia lettuce leaves had excellent correlation (>84%) with conventional destructive biochemical analysis. Preliminary experimental results emphasize the high throughput monitoring capability and multifunctionality of our novel handheld fluorescence imager, indicating its tremendous potential in modern agriculture.