EP4658993A2 - System and method for identifying nanoparticles volumetrically via interferometric scattering hyperspectral microscopy - Google Patents

Abstract

Disclosed herein are hyperspectral acquisition systems for generating and recording hyperspectral profiles of nanoparticles and methods of using the systems. The hyperspectral acquisition systems include two systems: (1) a hyperspectral acquisition system (e.g., hyperspectral imaging system) for generating and recording the hyperspectral profiles and (2) a hyperspectral analysis system for assigning identifications using spectral features.

Description

SYSTEM AND METHOD FOR IDENTIFYING NANOPARTICLES VOLUMETRIC ALLY VIA INTERFEROMETRIC SCATTERING HYPERSPECTRAL MICROSCOPY

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application No. 63/442,266 filed on January 31, 2023, which the entire content is hereby incorporated by reference.

BACKGROUND OF THE DISCLOSURE

[0002] Nanomedicine and nanotechnology' are currently in a state of rapid advancement, with numerous potential applications in medicine and biology’. The COVID-19 pandemic has highlighted the importance of these technologies, particularly in developing mRNA vaccines utilizing lipid nanoparticle (LNP) delivery methods. In the last decade, the US FDA has approved over 100 nanomedicines for commercial use, demonstrating the significant impact these technologies have on our daily lives.

[0003] In discovering and developing new nanomedicines, it is important to characterize the NPs and the associated NP-cell interactions to test their effectiveness. The common characterization methods rely on the visualization of particles and cells, where fluorescent labels are assigned to NPs and cells by dye conjugation.

[0004] Despite the specificity, fluorescent labeling mainly has the following disadvantages:

(1) fluorescence dyes are prone to photobleaching, finite fluorescence rate, and photo-blinking;

(2) labeling the nanoparticles alters their intrinsic properties and disturbs particle-cell interactions; (3) fluorescence dyes are subject to dissociation from NPs/cells; and (4) difficulty' in distinguishing each individual particle from a group of particles sharing similar chemical properties. These limitations can impede continuous measurements and observations of a group of NPs.

[0005] Referring to FIGS. 1 A-1C, as it has been identified by many studies, interferometric scattering microscopy iSCAT technique provides nanometer-scale spatial resolution. The intensity of the pure scattering signal from a nanoparticle is proportional to 1/r⁶, where r is the radius of the scatter, making the signal too weak to be detectable down to the nanometer scale through conventional imaging. The interferometric scattering technique preserves the scattering information by interfering with a reference light, such as the one reflected by a glass slide, amplifying the signal intensity to 1/r³ proportionality. Thanks to this, it is feasible to detect particles down to a few nanometers, such as individual proteins.

[0006] The iSCAT illumination system, using a single wavelength (FIG. 1 A), can only generate intensity profiles of the particles. The difficulty' of practically using iSCAT having a single wavelength to isolate a single motion is that the scattered light intensity is not sufficient to distinguish between optically similar particles. Three aspects can contribute to the problem: (1) the intensity of each particle can be greatly affected by the relative position of the focal plane;

(2) the complexity of scattering on the nanometer scale (spectral intensity might vary but give similar intensity at a single wavelength); and (3) diffraction-limited optics. Darkfield (DF) arrangements can provide spectral information by illuminating a sample with a multi-wavelength light source and spectrally decomposing each pixel. However, the signal to noise ratio (SNR) suffers greatly, as there is no interference amplification. Additionally, current DF setups are not able to incorporate real-time volumetric spectral decomposition from a single image for dynamic samples.

[0007 j Based on the foregoing, it would be beneficial to have a method that identifies nanoparticles without fluorescent labeling, while having the capacity for volumetric, single-shot, spectral fingerprinting.

BRIEF DESCRIPTION

[0008] The present disclosure is directed to a hyperspectral acquisition system that generates and records hyperspectral profiles of nanoparticles.

[0009] Particularly, in one aspect, the present disclosure is directed to a hyperspectral acquisition system having a multiwavelength light source that emits an illuminating light having a spectrum of wavelengths and a primary beam splitter that splits the illuminating light to direct a portion of the illuminating light through an objective lens towards a sample location and an output light towards a focusing imaging lens. The system further includes a spectral separation module that receives the output light from the focusing imaging lens and transmits light in a plurality of ranges. Sensors of the system are each configured to capture images of the light received from the spectral separation module at different ranges.

[0010] Another aspect of the present disclosure is directed to a hyperspectral acquisition system that includes a multi wavelength light source configured to emit an illuminating light having a spectrum of w avelengths onto a sample location, an objective lens that receives the illuminating light from the sample location, and a focusing imaging lens that receives the illuminating light from the objective lens. The system further includes a spectral separation module for receiving the illuminating light from the focusing imaging lens and transmits light in a plurality of ranges. Sensors of the system are each able to capture images of the light received from the spectral separation module at different ranges.

[001 1 ] Another aspect of the present disclosure is directed to a method for identifying a sample. The method includes steps of providing a plurality of bandpass filters each directing output light to a sensor, producing a broadband spectrum of wavelengths directed to the sample, imaging hyperspectral data of the sample with the sensors, generating a spectral profile of the sample with the hyperspectral data imaged by the sensors, extracting intensities of the spectral profile using spectral decomposition, and comparing intensities to a hyperspectral library to identify the sample.

BRIEF DESCRIPTION OF THE DRAWINGS

[ 0012 j FIG. 1A is a schematic illustration of a single wavelength iSCAT system, including a non-polarizing beam-splitter and an objective lens used on sub-diffractive nanoparticle detection; [0013] FIG. IB is an isometric view of the iSCAT system of FIG. 1 A;

[0014] FIG. 1C is a display of interferometric images of extracellular vesicles (4T1

EVs~100nm diameter) detected from the system of FIG. 1A;

[0015] FIG. ID is a display of interferometric images of 44 nm diameter polystyrene NPs detected from the system of FIG. 1 A;

[0016] FIG. 2 is a schematic illustration of a spectral acquisition system of the present disclosure;

[0017] FIG. 3A is a display of an experimental image of 100 nm polystyrene particles imaged at 405 nm wavelength using the system of FIG. 2;

[0018] FIG. 3B is a display of an experimental image of 100 nm polystyrene particles imaged at 632 nm wavelength using the system of FIG. 2;

[0019] FIG. 4 is a schematic illustration of a second embodiment of the spectral acquisition system of the present disclosure;

[0020] FIG. 5 is an alternative schematic illustration of the second embodiment of the spectral acquisition system of the present disclosure of FIG. 4;

[0021] FIG. 6 is a schematic illustration of a third embodiment of the spectral acquisition system of the present disclosure; [0022] FIG. 7 is an alternative schematic illustration of the of the third embodiment of the spectral acquisition system of the present disclosure of FIG. 6;

[0023] FIG. 8 is a display of a reflection phase of a sample utilizing the second embodiment of the spectral acquisition system;

[0024] FIG. 9 is a display of a reflection phase of a sample monitored with the third embodiment of the spectral acquisition system;

[0025] FIG. 10 is a display of hyperspectral data of a sample monitored with the third embodiment of the spectral acquisition system;

[0026] FIG. 11 A is a display of a raw image for image processing of interferograms from

100 nm polystyrene NPs. imaged at 632 nm wavelength using the system of FIG. 2;

[0027] FIG. 1 IB is a display of a background image depiction during image processing of

FIG. 11 A;

[0028] FIG. 11C is a display of a normalized image after image processing of FIG. 11 A;

[0029] FIG. 12A is a display of an example hyper-tesseract volume;

[0030] FIG. 12B is a display of axial (z-axis) spectral intensities of FIG. 12A corresponding to propagation kernel operation at respective wavelengths;

[0031] FIG. 13 A is a display of an example experimental hyperspectral profile of a NP;

[0032] FIG. 13B is a display of intensities at the NP location for a simulated 100 nm polystyrene (PS) NP of FIG. 13A;

[0033] FIG. 14 is a schematic diagram of a method for spectral acquisition system of the present disclosure.

DETAILED DESCRIPTION

[0034] The present disclosure is generally directed to a hyperspectral imaging and analysis (HSIA) system that provides a solution to the problems of utilizing a traditional iSCAT illumination system for identifying a nanoparticle in dynamic settings. Referring to FIG. 2, an exemplary embodiment of a system for HSIA for a sample (e.g., nanoparticles) is generally indicated at reference number 100. The HSIA system 100 includes two systems: (1) a hyperspectral acquisition system (e.g., hyperspectral imaging system), generally indicated at reference number 200, and (2) a hyperspectral analysis system, generally indicated at reference number 300. The acquisition system 200 generates and records the hyperspectral profiles, and the analysis system 300 assigns identifications using spectral features. Using this system 100, the present disclosure enables label-free identification of a group of nanoparticles in dynamic settings, such as, but not limited to, flow cells, nanoparticles and biological samples, extracellular vesicles, viruses, vaccines, proteins, by determining the spectral features of individual particles. Throughout this application, each change in embodiment will have corresponding reference numbers to the HSIA system 100 plus 1000 for similar features (e.g., the HSIA system 1100 in FIGS. 4-5, the HSIA system 2100 in FIGS. 6-7. and the like).

[0035] The present disclosure relates generally to scattering signals to assigning identifications to a group of optically similar nanoparticles (NPs). Methods in the present disclosure show strength in cases that traditionally require fluorescence labeling, including measuring diffusivity, size, mass, conformational state, and particle-cell association.

[0036] The disclosure develops a hyperspectral imaging and analysis (HSIA) system and method to characterize the interferometric scattering (iSCAT) signal to achieve this goal. The HSIA system 100 determines and records the spectral features of nanoparticles, for example bio- nanoparticles, in a group of optically similar specimens. The spectral features are used to identify and distinguish NPs regardless of the existence of surface plasmon resonances, working with dielectric materials. A detectable radius of NPs by the HSIA system 100 disclosure is between 5- 1000 nm, which covers the size range from single proteins to Chylomicrons. The HSIA system 100 has the potential to replace fluorescent labeling in the applications of specific particle identification. Therefore, the technique benefits biomedical research, for example particle characterization and cell-particle interactions.

[0037] To produce a spectral hypercube (e.g., two spatial dimensions and one spectral), complex image processing of each pixel is needed. The hyperspectral acquisition system 200 addresses the challenge of not being able to incorporate real-time spectral decomposition of the image for dynamic samples with traditional DF systems (FIG. 1 A). Specifically, referring to FIG. 2, the acquisition system 200 setup alters the traditional iSCAT setup. For example, the acquisition system 200 utilizes a multiwavelength light source 210 (e.g., a super-continuum laser, a frequency comb, or a combined set of lasers at different wavelengths) and captures images at narrow wavelength bands by utilizing one or multiple sensors (e.g.. cameras) 212, 214, 216, resulting in spectral information of the sample and an extended depth of focus. When the images are reconstructed in 3D and merged by the analysis system 300, the spectral hypercube’s spatial dimensions are extended, providing a new hyper-tesseract (e.g., three spatial and one spectral dimension). [0038] The hyperspectral analysis system 300 component of the HSIA system 100 relies on principles of the nature of light- matter interactions. For example, for nanoparticles, the hyperspectral analysis system 300 is governed by the nanoparticles’ polarizability, which depends on the nanoparticles' electronic structure at an atomic level and atomic arrangement at a molecular level.

Embodiment One of the Hyperspectral Acquisition System:

[0039] Referring to FIG. 2, the acquisition system 200 within the scope of this disclosure may broadly include a multi wav elength light source (e.g., a laser 210), a plurality⁷ of sensors (e.g., three sensors 212, 214, 216), a sample stage 218, an objective lens 220, a primary beam splitter 222, and a spectral separation module 224. The spectral separation module 224 of the acquisition system 200 further includes a first beam splitter 226 and at least one subsequent beam splitter (e.g., one subsequent beam splitter 228), a plurality⁷ of bandpass filters (e.g., bandpass filters 230, 232, 234), and a primary mirror 246 (e.g., a reflection mirror), and at least one lens (e.g., three lenses 240, 242, 244). In a reflection embodiment of the acquisition system 200, light from the laser 210 is directed to the reflection mirror 246 before reaching the primary beam splitter 222. The reflection mirror 246 is positioned to define a comer between the multiwavelength light source 210 and the primary beam splitter 222 such that the reflection mirror directs the illuminating light of the laser to the primary beam splitter.

[0040] The sample stage 218 stores a sample (e.g., a Nanoparticle NP) at a sample location. The laser 210 emits illuminating light LI having a spectrum of wavelengths. For example, the spectrum of wavelengths may be between or includes 450 nm and 2000 nm. Referring to FIGS. 2, 3A-3B, the plurality of sensors 212, 214, 216 captures images at ranges of wavelength bands such that each sensor defines an output location. The primary beam splitter 222 splits the illuminating light LI of the laser 212 to direct a portion L2 of the illuminating light towards the sample location and directs a portion L3 of the illuminating light (e.g., output light such as a reflected portion of the illuminating light or a transmitted portion of the illuminating light) towards a subsequent beam splitter 226. The subsequent beam splitter 226 receives the portion L3 of the illuminating light from the primary⁷ beam splitter 222. Once the subsequent beam splitter 226 receives the output light L3, the subsequent beam splitter splits the output light to direct a portion L4 of the output light towards either another subsequent beam splitter (e.g., 228) or a sensor mirror 236 and directs a reflected portion L5 of the output light L3 towards a sensor of the plurality of sensors 212. 214, 216. [0041] In the HSIA system setup in FIG. 2, the laser 210 emits the illuminating light LI having the spectrum of wavelengths ranging between 450 nm and 2000 nm. The illuminating light LI is reflected on the reflection mirror 246 that directs the illuminating light towards a widefield lens 248 as the widefield lens is arranged between the primary beam splitter and reflection mirror. After the primary' beam splitter 222 splits the illuminating light LI, the widefield lens 248 focuses the light L2 on the back focal plane of the objective lens (OL) 220. Before reaching the objective lens 220 and the sample stage 218, the light L2 reaches an achromatic quarter wave plate 250 that circularly polarizes the light L2 to improve signal decay. In a preferred embodiment, the super-achromatic quarter w ave plate 250 polarizes the light L2 by a fourth cycle (e.g., X/4). After being circularly polarized by the super-achromatic quarter wave plate 250, the light L2 enters the objective lens 220 of the sample stage 218, where the transmitted portion of the light L2 is collimated, illuminating the glass slide microchannel 252 containing the sample NP (e.g., nanoparticle solution). A scattered light L2 then interferes with a reflected light portion L3 of the illuminating light, w hich is then recorded by the imaging sensors 212, 214, 216 at specific wavelength bands, yielding a different interferometric point spread function pattern for analysis, as explained in further detail below. For example, once the illuminating light has been scattered from the nanoparticle and interacts with reflected light from a portion of the sample stage 218 (e.g., a microchannel coverslip), it is guided with the primary beam splitter 222 to be imaged. Imaging lenses 240. 242, 244 collimate the reflected light and focus an interferometric signal on the camera sensors 212, 214, 216. Before reaching the sensors 212, 214, 216, a bandpass fdter (e.g., a spectral filter 230, 232, 234) in the desired wavelength captures the light at a narrow specific broadband, as explained in more detail below'. Referring to FIGS. 2 and 3A-3B, the setup is an RGB spectral mode iSCAT. As shown, interferometric function varies at different wavelengths. By way of particularly suitable examples, FIG. 3A shows imaged wavelengths of 405 nm and FIG. 3B shows imaged wavelengths at 632 nm. [0042] Referring to FIG. 2, the illuminating light LI has a reflected light portion L3 that is directed to a first imaging lens 240, then a first subsequent beam splitter 226 that divides the reflected light portion L3 of the illuminating light LI by 25:75 such that a reflected light portion L5 is directed to and received by a first spectral filter 230. As one w ith ordinary' skill in the art would understand, the illuminating light LI can be divided into any' arbitrary ratio without departing from the scope of the present disclosure, such as for example 10:90 to 90: 10, and particularly, 25:75 or 75:25 or 50:50. The first spectral filter 230 may selectively transmit light within a predetermined range. For example, in one suitable embodiment, the predetermined range for the first spectral filter 230 transmits light having a wavelength of 632 nm. Once filtered, a first sensor 212 collects images of the light received through the first spectral filter 230. In an embodiment, the first sensor 212 is an sCMOS sensor; however, as one with ordinary skill in the art would understand, types of sensors may vary without departing from the present disclosure. For example, referring to FIG. 3B, the first sensor 212 captures an experimental image of 100 nm polystyrene particles imaged at a 632 nm wavelength.

[ 0043] Referring to FIG. 2, a transmitted light portion L4 from the first subsequent beam splitter 226 is directed to a second imaging lens 242, then a second subsequent beam splitter 228. The second subsequent beam splitter 228 divides the transmitted light portion L4 from the first subsequent beam splitter 272 by 50:50 such that a transmitted light portion L6 is directed to a sensor mirror 236 and a reflected light portion L7 is directed to and received by a second spectral filter 232. The second spectral filter 232 may selectively transmit light within a predetermined range. For example, in an embodiment, a predetermined range for the second spectral filter 232 transmits light having a wavelength of 532 nm. Once filtered, a second sensor 214 collects images of the light received through the second spectral filter 232. In an embodiment, the second sensor 214 is an sCMOS sensor; however, as one with ordinary skill in the art would understand, types of sensors may vary without departing from the present disclosure.

[0044] Referring to FIG. 2, a transmitted light portion L6 from the second subsequent beam splitter 228 is directed to a third imaging lens 244 then the sensor mirror 236. The sensor mirror 236 directs the transmitted light portion L6 from the second subsequent beam splitter 228 towards a third spectral filter 234. The third spectral filter 234 may selectively transmit light within a predetermined range. For example, in an embodiment, a predetermined range for the third spectral filter 234 transmits light having a wavelength of 402 nm. Once filtered, a third sensor 216 collects images (FIG. 3A) of the light received through the third spectral filter 234. In an embodiment, the third sensor 216 is an sCMOS sensor; however, as one with ordinary skill in the art would understand, types of sensors may vary without departing from the present disclosure. For example, referring to FIG. 3A, the third sensor 216 captures an experimental image of 100 nm polystyrene particles imaged at 405 nm wavelength.

[0045] By utilizing the first, second, and third spectral filters 230, 232, 234 and the first, second, and third sensors 212, 214, 216, images from each sensor can be added to create a RGB spectral. By having each sensor filter different wavelength ranges, each wavelength range detected by the first, second, and third sensors 212, 214. 234 can be superposed in space to create a full spectrum for the sample NP. [0046] The sample stage 218 with micro/nanometric precision holds the sample NP, which defines the sample location for the acquisition system 200. In an embodiment, the sample stage 218 in the piezo stage has the objective lens 220 and a microchannel 252. In an embodiment, the objective lens 220 may be a high numerical aperture (NA) objective lens. The microchannel 252 is configured to hold the sample NP to define the sample location.

[0047] The primary beam splitter 222 divides the illuminating light of the laser 210 into any desired proportions. The subsequent beam splitters 226, 228 divide the output light L3 of the primary beam splitter 222 into any desired proportions, for example, but not limited to, 25:75, 50:50. For example, the first subsequent beam splitter 226 receives a reflected light portion L3 of the illuminating light LI and divides the reflected light portion into a desired portion of 25:75, to produce a first subsequent transmitted light portion L4 and a first subsequent reflected light portion L5. The second subsequent beam splitter 228 receives the first subsequent transmitted light portion L4 and divides the first subsequent transmitted light portion L4 into a desired portion of 50:50, to produce a second subsequent transmitted light portion L6 and a second subsequent reflected light portion L7.

Embodiment Two of the Hyperspectral Acquisition System:

[0048] Referring to FIGS. 4-5. the acquisition system 1200 within the scope of this disclosure may broadly comprise a multiwavelength light source (e.g., a laser 1210), a plurality of sensors (e.g., three sensors 1212, 1214, 1216), a sample stage 1218, an objective lens 1220, a primary beam splitter 1222, a spectral separation module 1224. The spectral separation module 1224 of the acquisition system 1200 further comprises a first beam splitter 1226 and at least one subsequent beam splitter (e.g., one subsequent beam splitter 1228), a plurality of bandpass filters (e.g., bandpass filters 1230, 1232, 1234), and a primary mirror 1246 (e.g., reflection mirror, and at least one lens (e.g., one lens 1240). As one with ordinary⁷ skill in the art would understand, the number of lens may vary without departing from the scope of the present disclosure. For example, other lenses can be added to compensate for chromatic aberrations after spectral separation if needed. In the present embodiment, the lens 1240 is a single achromatic lens. In comparison to the reflection embodiment of the acquisition system 200 of FIG. 2 where light from the laser 210 reaches the reflection mirror 246 before reaching the primary beam splitter 222, in this reflection embodiment of the acquisition system 1200 light from the laser 1210 is directed to the reflection mirror 1246 after reaching the primary beam splitter 1222. In this embodiment, light LI is directed to an optical lens 1254, a pinhole 1256, and a collimating lens 1258 before reaching the primary beam splitter 1222.

[0049] The sample stage 1218 stores a sample (e g., ananoparticle NP) at a sample location. The laser 1210 emits illuminating light having a spectrum of wavelengths. The plurality of sensors 1212, 1214, 1216 captures images at ranges of wavelength bands, wherein each sensor defines an output location. The light LI from the laser 1210 is first received by the optical lens 1254, the pinhole 1256, and the collimating lens 1258 before reaching the primary beam splitter 1222. The primary beam splitter 1222 splits the illuminating light LI of the laser 1212 to direct the illuminating light L2 towards the sample location and an output light L3 (e.g., a reflected portion of the illuminating light or a transmitted portion of the illuminating light) towards an imaging lens 1240 then the first beam splitter 1226. The first beam splitter 1226 receives the light L3 and splits the light to direct the light L4 towards either another subsequent beam splitter (e.g., 1228) or a sensor mirror 1236 and directs a reflected portion L5 of the output light L3 towards a sensor of the plurality of sensors 1212, 1214, 1216. Specifically, the reflected portion L5 is directed to a first spectral filter 1230 then the first sensor 1212, and the transmitted portion L4 is directed towards a second subsequent beam splitter 1228. The second subsequent beam splitter 1228 divides the transmitted light portion L4 from the first subsequent beam splitter 1226 such that a transmitted light portion L6 is directed to a sensor mirror 1236 and a reflected light portion L7 is directed to and received by a second spectral filter 1232 then the second sensor 1214. The sensor mirror 1236 directs the transmitted light portion L6 from the second subsequent beam splitter 1228 towards a third spectral filter 1234 then the third sensor 1216.

[0050] Before reaching the objective lens 1220 and the sample stage 1218, the light L2 reaches an achromatic quarter wave plate 1250 that circularly polarizes the illuminating light L2 to improve signal decay. In a preferred embodiment, the super-achromatic quarter wave plate 1250 polarizes the light L2 by a fourth cycle (e.g., X/4). After being circularly polarized by the super-achromatic quarter wave plate 1250, the light L2 enters the objective lens 1220 of the sample stage 1218, where the transmitted portion L2 of the illuminating light LI is collimated, illuminating a glass slide or microchannel (not shown) containing the sample NP (e.g., nanoparticle solution). The scattered light L2 then interferes with a reflected light portion L3 of the illuminating light LI, which is then recorded by the imaging sensors 1212, 1214, 1216 at specific wavelength bands, yielding a different interferometric point spread function pattern for analysis, as explained in further detail below. For example, once the illuminating light has been scattered from the nanoparticle and interacts with reflected light from a portion of the sample stage 1218 (e.g., a microchannel coverslip), it is guided with the primary beam splitter 1222 to be imaged. Imaging lens 1240 collimate the reflected light and focus an interferometric signal on the camera sensors 1212, 1214, 1216. Before reaching the sensors 1212, 1214, 1216, a bandpass filter (e.g., a spectral filter 1230, 1232, 1234) in the desired wavelength captures the light at a narrow specific broadband. By utilizing the first, second, and third spectral filters 1230, 1232, 1234 and the first, second, and third sensors 1212. 1214, 1216, images from each sensor can be added to create a RGB spectral. By having each sensor filter different wavelength ranges, each wavelength range detected by the first, second, and third sensors 1212, 1214, 1234 can be superposed in space to create a full spectrum for the sample NP.

[0051] Referring to FIG. 5, a simplified working mechanism of the system 1100 is shown. A multiwav elength light source £_inc (e.g., laser 1210 of FIG. 4) focuses on the back focal plane of the objective lens OL (e g., objective lens 1220 of FIG. 4) and becomes collimated. A suspended nanoparticle SNP (e.g., sample NP of FIG. 2) scatters the collimated light E_sca and interferes with the light from the glass slide GS interface (e.g.. sample stage 1218 of FIG. 4). After passing through a beam splitter BS (e.g.. primary’ beam splitter 1222 of FIG. 4) and a focusing imaging lens IL (e.g., imaging lens 1240 of FIG. 4), a spectral separation SS module (e g., spectral separation module 1224 of FIG. 4) separates the multiple wavelengths intensities /_det to be captured by the detectors D (e.g., sensors 1212, 1214, 1216 of FIG. 4).

Embodiment Three of the Hyperspectral Acquisition System:

[0052] Referring to FIGS. 6-7, the acquisition system 2200 within the scope of this disclosure may broadly comprise a multiwavelength light source (e.g., a laser 2210), a plurality’ of sensors (e.g., three sensors 2212, 2214, 221 ), a sample stage 2218, an objective lens 2220, a focusing imaging lens 2248, and a spectral separation module 2224. The spectral separation module 2224 of the acquisition system 2200 further comprises a first beam splitter 2226 and at least one subsequent beam splitter (e.g., one subsequent beam splitter 2228), a plurality of bandpass filters (e.g., bandpass filters 2230, 2232, 2234), and at least one lens (e.g., one lens 2240). As one with ordinary skill in the art would understand, the number of lens may vary’ without departing from the scope of the present disclosure. In comparison to the reflection embodiment of the acquisition system 200 of FIG. 2 where light from the laser 2210 reaches the reflection mirror 246 before reaching the primary beam splitter 222, in this reflection embodiment of the acquisition system 2200 light from the laser 2210 is directed from a first reflection mirror 2246A to a second reflection mirror 2246B. Further, in this embodiment, light LI is directed to an optical lens 2254, a pinhole 2256, and a collimating lens 2258 before reaching the sample stage 2218 and the light LI is directed to the sample stage 2218 before reaching the first reflection mirror 2246A. As one with ordinary skill in the art would understand, number of reflection mirrors may vary' without departing from the scope of the present disclosure.

[0053] The sample stage 2218 stores a sample (e.g., a nanoparticle NP) at a sample location. The laser 2210 emits illuminating light having a spectrum of wavelengths. The plurality of sensors 2212, 2214, 2216 captures images at ranges of wavelength bands, wherein each sensor defines an output location. The light LI from the laser 2210 is first received by the optical lens 2254, the pinhole 2256, and the collimating lens 2258 before reaching the sample stage 2218. From the sample stage 2218. the light LI passes through the objective lens 2220 before reaching the first reflection mirror 2246 A then the second reflection mirror 2246B. The light LI from the laser 2210 enters the objective lens 2220 of the sample stage 2218, where the transmitted portion of the illuminating light L2 is collimated, illuminating a glass slide or microchannel (not shown) containing the sample NP (e.g., nanoparticle solution). In this embodiment, the objective lens 2220 includes an attenuator positioned in the back focal plane of the objective lens. Once the illuminating light has been scattered from the nanoparticle and interacts with reflected light from a portion of the sample stage 2218 (e.g., a microchannel coverslip), it is guided with the first and second reflection mirrors 2246 A, 2246B to be imaged. In this embodiment, the light LI is forward scattering, as opposed to the backwards scattering of light in reflection embodiments (FIGS. 2 and 4-5). Since incoming light and reference light are the same due to the forward scattering, the attenuator positioned in the back focal plane of the objective lens 2220 can lead to a better image contrast in cases with weak scattering nanoparticles.

[0054] The imaging lens 2240 collimate the reflected light and focus an interferometric signal on the camera sensors 2212, 2214, 221 . Before reaching the sensors 2212, 2214, 2216, a bandpass filter (e.g., a spectral filter 2230, 2232, 2234) in the desired wavelength captures the light at a narrow specific broadband. By utilizing the first, second, and third spectral filters 2230. 2232, 2234 and the first, second, and third sensors 2212, 2214, 2216, images from each sensor can be added to create a RGB spectral. By having each sensor filter different wavelength ranges, each wavelength range detected by the first, second, and third sensors 2212, 2214, 2234 can be superposed in space to create a full spectrum for the sample NP.

[0055] From the second reflection mirror 2246B, the illuminating light LI of the laser 2212 is directed towards the imaging lens 2240 then the beam splitter 2226 that divides the light LI such that an output light L2 is either directed to another subsequent beam splitter (e.g., 2228) or a sensor mirror 2236 and a reflected portion L3 of the light LI is directed towards a sensor of the plurality of sensors 2212, 2214, 2216. Specifically, the reflected portion L3 is directed to a first spectral filter 2230 then the first sensor sensors 2212, and the transmitted portion L2 is directed towards a second beam splitter 2228. The second beam splitter 2228 divides the transmitted light portion L2 from the first beam splitter 2272 such that a transmitted light portion L4 is directed to a sensor mirror 2236 and a reflected light portion L5 is directed to and received by a second spectral filter 2232 then the second sensor 2214. The sensor mirror 2236 directs the transmitted light portion L4 from the second beam splitter 2228 towards a third spectral filter 2234 then the third sensor 2216.

[0056] Referring to FIG. 7, a simplified working mechanism of the system 2100 is shown. A collimated multiwavelength light source fine (e.g., laser 2210 of FIG. 6) impinges on a suspended nanoparticle SNP (e.g., sample NP of FIG. 2) resulting in scattering E_SCa and interference. A reference light Eref can be attenuated by a neutral density filter at the objective lens OL (e.g., objective lens 2220 of FIG. 6) focal point. After passing through a focusing imaging lens IL (e.g., imaging lens 2226 of FIG. 6), a spectral separation SS module (spectral separation module 2224 of FIG. 6) separates the multiple w avelengths intensities /det to be captured by the detectors D (e.g., sensors 2212, 2214, 2216 of FIG. 6).

Hyperspectral Analysis System:

[0057] The spatial resolution of the iSCAT used in the spectral acquisition systems 200, 1200, 2200 is sufficient to detect the 4T1-EV and PS samples with nanometer-level resolution. For example, 4T1 EVs were purified using ultra-centrifugation and characterized with Nanosight NTA. PS samples were assumed to follow the size distribution from the manufacturer. The samples were placed on a cover slip before data acquisition. Using this system 200 sensitivity of scattering signals to the wavelength of the incident light can be identified. For example, laser 210 emitting illumining light with 405 nm and 632 nm wavelengths is used. The same particle's point spread function (PSF) shows distinguishable spectral features (FIGS. 3A-3B).

[0058] The hyperspectral analysis system 300 aims to analyze the spectral line of individual particles of the sample NP (FIG. 2). This function can be achieved through two steps: (1) acquire a particle hyperspectral library with respect to initial particle status and (2) identify particles of the sample by matching an instantaneous spectral line associated with the sample NP with the library identity as explained in further detail below. [0059] Referring to FIG. 2 the hyperspectral analysis system 300 utilized hyperspectral data of the sample NP imaged by the sensors 212, 214. 216. Once the hyperspectral data of the sample NP is acquired, the hyperspectral analysis system 300 generates a spectral profile of the sample using the hyperspectral data imaged by the sensors. For example, while the sensors (e.g., 212, 214, 216) are imaging the hyperspectral data, a background illumination image is produced by scanning the sample stage 218 (FIG. 2 and FIG. 1 IB). With the background illumination image, the hyperspectral analysis system 300, subtracts and normalizes the hyperspectral data with the background illumination image (FIG. 11C). Further, the hyperspectral analysis system 300 extracts intensities of the spectral profile using spectral decomposition that compares the intensities to the hyperspectral library to identify the sample NP. To compare the intensities of the sample with the hyperspectral library for identifying the sample, the hyperspectral analysis system 300 matches the intensity of the instantaneous spectral line of the sample NP with a library identity within the hyperspectral I ibrary .

[0060] Referring to FIGS. 8-9, using coherent brightfield microscopy, particle location can be shown graphically by displaying axial intensity profiles at different wavelengths by showing the effect of the iSCAT reflection phase difference for the reflection HSIA system 1100 (FIG. 8) and the transmission HSIA system 2100 (FIG. 9). Further, referring to FIG. 10, which displays hyperspectral data of a sample NP monitored with the transmission HSIA system 2100, contrast acquisition for different particles sizes and wavelengths can be displayed. The contrast acquisition can show the relationship between particle size and contrast, as well as the variation with respect to the wavelength can be shown using the equation: C^1/3 ex 4nty³ ( -rip+ —2n_m-/ ) = a, where n_p = N (A) + i/c(A).

[0061] Referring to FIGS. 11 A- 1 IB, to produce spatial resolution enhancement of the sample, background noise, which hinders the information substantiation, is minimized by a subtraction and normalization method applied to reduce a negative impact on determining the origin of spectral information for the sample. With normalization, the image reveals otherwise hidden features (FIG. 11C). Briefly, the sample stage is scanned throughout the sample’s surface while acquiring images of the samples' hyperspectral data by the sensors. The hyperspectral data images and the scanned sample stage image are averaged to produce a representative “background” illumination. By normalizing images with respect to this, terms originating from interactions of the illuminating light with analytes can be segregated and enhanced. This process becomes simpler with dynamic samples, as particles would be moving; thus, scanning the sample stage would be neglected. [0062] Owing to the nature of the interferograms’ slowly decaying signal, the weakly- scattered light by the NPs can be captured. Compared to other interferometric techniques, such as off-axis holography, iSCAT has exquisite resistance to vibrations due to the shared optical axis between the scattered and reference fields, outlining NPs that would otherwise be lost to image noise.

[0063] To build the hyperspectral library-, unique spectral features of nanoparticles in the system must be extracted from the raw spectral image data (e.g., hyperspectral data). To build a hyper-tesseract volume of the sample NP (e.g., FIG. 12A), an effective method utilizes Fourier convolution processing. Computational backpropagation using Fourier convolution reconstructs an electromagnetic field numerically to contain information of the location of the sample NP, as well as the spectral distribution of the sample defined by- the spectral module’s capability. The spectral information is then collected and restored in the hyperspectral library-. Interferometric point-spread functions, utilized in FIGS. 2 and 12A, are solved through vector representations of electromagnetic field and propagated through convolution theory. The Fourier convolution method employs a kernel representing a light source to emulate reversal of electromagnetic waves, thus leading to a spatial reconstruction of a light path.

[0064] Construction of the spectral features is critical to assign an ID to particles. Spectral features of a nanoparticle are acquired and generated from a group of particles. The sample NP is diluted, dried on the surface of the slide, and placed into the hyperspectral analyzer to provide the spectral distribution of the analytes (FIG. 13A). By comparing an instantaneous spectral shape profile of the sample NP to the previously- acquired hyperspectral library information, identification of the sample is possible. Some critical wavelengths will be selected to reconstruct a smooth and continuous spectral line for fitting acceleration. With further spectral decomposition, the spectral profile of the sample at each voxel can be extracted and linked to the hyperspectral library. Therefore, by comparing these respective intensities to the previously acquired hyperspectral library information, identifying the NP is possible (e.g., FIG. 13B).

[0065] Referring to FIG. 14, aspects of the HSIA systems 100, 1100, 2100 may be embodied as a method 400 without departing from the present disclosure. For example, the method 400 of utilizing the HSIA systems 100, 1100, 2100 may include step 410 of providing a plurality of bandpass filters each directing output light to a sensor (e.g., by the spectral separation modules 224, 1224, 2224). As explained in the present disclosure, each bandpass filter filters a different wavelength range including one of: (i) 632 nm, (ii) 532 nm, or (iii) 405 nm to create a RGB spectral. For example, a wavelength range could be 600-700 nm to encompass 632 nm. representing red, 500-560 nm to encompass 532 nm, representing green, or 400-475 nm to encompass 405 nm, representing blue. As one with ordinary skill in the art would understand, the range and representative wavelength for red, green, and blue may vary without departing from the scope of the present disclosure. Next, the method 400 of utilizing the HSIA systems 100, 1100, 2100 includes step 412 of producing a broadband spectrum of wavelengths directed to the sample (e.g., by the multiwavelength light source 210, 1210, 2210). Next, the method 400 includes step 414 of imaging hyperspectral data of the sample with the sensor (e.g., by the sensors 212, 214, 216, 1212, 1214, 1216, 2212, 2214, 2216). After imaging, step 416 of the method includes generating a spectral profile of the sample with the hyperspectral data imaged by the sensors (e.g., by the acquisition system 200, 1200, 2200). Once a spectral profile is created, step 418 includes extracting intensities of the spectral profile using spectral decomposition. Once the intensities are extracted, the method finishes with step 420 of comparing intensities to a hyperspectral library to identify the sample. The hyperspectral library may be acquired in step 422, which can be completed before step 420. In an embodiment, the method 400 may further include step 424 of scanning a sample stage (e.g., the sample stage 218, 1218, 2218) that defines a location of the sample to produce a sample stage image (FIG. 11B). With the sample stage image, step 416 of generating the spectral profile further includes step 426 of normalizing the hyperspectral data with the sample stage image to produce a background illumination image (FIG. 11C).

[0066] In summary, the HSIA system of the present disclosure has the capacity to measure spectral lines and determine the unique features of nanoparticles in dynamic samples and flowing samples. The HSIA system may be used for any nanoparticle and approaches a true label-free tracking and identification technique.

[ 0067] The present disclosure has identified the existence of non-linear terms in the scattering signal and utilizes them to distinguish the NPs. The origin of the non-linear terms can be: (1) nanoparticles have a very⁷ high surface-to-volume ratio; (2) conformational change; and/or (3) intrinsic status of chemical/physical properties (e.g., mass, shape, surface decoration, density of pi electrons).

[ 0068] The partition of three contributions to the non-linear terms is difficult, but identifying the NPs only needs a certain number of spectral features, associated with specific refraction/ absorption bands of the NPs material properties.

[0069] The function of assigning an identity to NPs relies on the analysis of spectral line shape variations, for example, but not limited to using a dark-field hyperspectral acquisition system. The spectral line shape isn’t influenced by axial position of the particles relative to a focal plane. Even though intensity of scattering signals would decay, normalized shape at each wavelength does not. This offers the proposed HSIA system advantages of marking NPs in 3D space.

[0070] Features of the sample NP can be obtained by comparing an intensity ratio between two randomly selected wavelengths and an intensity of a dominating frequency of the sample after transferring spectral lines into k-space. Then, a feature matrix is generated to assign an identity to individual particles. For example, the feature matrix is a particularly useful technique for separating single particle motion from a group of NPs.

[0071] As will be appreciated by one skilled in the art, aspects of the embodiments disclosed herein may be embodied as a system, method, computer program product or any combination thereof. Accordingly, embodiments of the disclosure may take the form of an entire hardware embodiment, an entire software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the disclosure may take the form of a computer program product embodied in any tangible medium having computer usable program code embodied in the medium.

[0072] Aspects of the disclosure may be described in the general context of computerexecutable or processor-executable instructions, such as program modules, being executed by a computer or processor. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Aspects of the disclosure may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media, including memory storage devices. [0073] Any combination of one or more computer-usable or computer-readable medium(s) may be utilized, including machine learning and artificial intelligence (Al) algorithms. The computer-usable or computer-readable medium may be. for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium. More specific examples (a non-exhaustive list) of the computer- readable medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CDROM), an optical storage device, a transmission media such as those supporting the Internet or an intranet, or a magnetic storage device. Note that the computer-usable or computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory. In the context of this document, a computer-usable or computer-readable medium may be any medium that can contain or store the program for use by or in connection with the instruction execution system, apparatus, or device.

[0074] Computer program code for carrying out operations of the present disclosure may be written in any combination of one or more programming languages, including, but not limited to, an object oriented programming language such as Java, Smalltalk, C++, C#, Pythonor the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on the portable electronic device, partly on the portable electronic device, as a stand-alone software package, partly on the portable electronic device and partly on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the portable electronic device through any ty pe of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0075] When introducing elements of the present disclosure or the preferred embodiment(s) thereof, the articles "a", "an", "the" and "said" are intended to mean that there are one or more of the elements. The terms "comprising", "including" and "having" are intended to be inclusive and mean that there may be additional elements other than the listed elements.

[0076] In view of the above, it will be seen that the several objects of the disclosure are achieved and other advantageous results attained.

[0077] As various changes could be made in the above products and methods without departing from the scope of the disclosure, it is intended that all matter contained in the above description shall be interpreted as illustrative and not in a limiting sense.

Claims

CLAIMS What is claimed is:

1. A hyperspectral acquisition system for generating and recording hyperspectral profiles of nanoparticles, the system comprising: a sample stage being configured to store a sample and define a sample location; a multiwav elength light source configured to emit an illuminating light comprising a spectrum of wavelengths; an objective lens arranged between the sample stage and the multiwav elength light source; a primary beam splitter configured to split the illuminating light of the multiwavelength light source to direct a portion of the illuminating light, through the objective lens towards the sample location and an output light towards a focusing imaging lens; a spectral separation module configured to receive the output light from the focusing imaging lens and transmit light in a plurality of ranges; and a plurality of sensors, each configured to capture images of the light received from the spectral separation module at different ranges.

2. The system of claim 1, wherein the spectral separation module comprises a first beam splitter configured to receive light from the focusing imaging lens and (i) direct a portion of the light towards at least one subsequent beam splitter and (ii) direct a portion of the light tow ards one of a plurality of bandpass filters, w herein the plurality of bandpass filters is configured to transmit light within a predetermined range to one of the plurality of sensors, and wherein the at least one subsequent beam splitter is configured to (i) direct a portion of the light to another at least one subsequent beam splitter and (ii) direct a portion of the light towards one of the plurality of bandpass filters.

3. The system of claim 2, wherein one of the at least one subsequent beam splitter is configured to (i) direct a portion of the light towards a mirror and (ii) direct a portion of the light tow ards one of the plurality of bandpass filters, wherein the mirror is configured to transmit light towards one of the plurality⁷ of bandpass filters.

4. The system of claim 3, wherein a total quantity of beam splitters comprised of the first beam splitter and the at least one subsequent beam splitter is two, wherein a quantity of the plurality of bandpass filters is three, and wherein each of the plurality of bandpass filters is configured to transmit a different wavelength range including one of: (i) 632 nm, (ii) 532 nm, or (iii) 405 nm.

5. The system of claim 3, wherein a total quantity of beam splitters comprised of the first beam splitter and the at least one subsequent beam splitter is two, wherein a quantity of the plurality' of bandpass filters is three, and wherein each of the plurality of bandpass filters is configured to transmit a different wavelength range being one of 600-700 nm, 500-560 nm, or 400-475 nm.

6. The system of claim 1, wherein the multi wav elength light source is a super-continuum laser, a frequency comb, or a combined set of lasers at different wavelengths.

7. The system of claim 6, wherein the illuminating light of the super-continuum laser comprises wavelengths between or including 450 nm and 2000 nm.

8. The system of claim 1. further comprising a primary mirror positioned to define a comer between the multiwavelength light source and the primary beam splitter such that the primary mirror directs the illuminating light of the laser to the primary beam splitter.

9. The system of claim 8. further comprising a wide field lens arranged between the primary beam splitter and primary mirror.

10. The system of claim 1, further comprising a sample positioned on the sample stage, wherein the sample is a bio-nanoparticle with a radius between 5 to 1000 nm.

11. The system of claim 1 , wherein the primary beam splitter comprises an achromatic quarter wave plate configured to circularly polarize the illuminating light.

12. A hyperspectral acquisition system for generating and recording hyperspectral profiles of nanoparticles, the system comprising: a sample stage being configured to store a sample and define a sample location; a multiwavelength light source configured to emit an illuminating light comprising a spectrum of wavelengths onto the sample location; an objective lens configured to receive the illuminating light from the sample location; a focusing imaging lens configured to receive the illuminating light from the obj ective lens; a spectral separation module configured to receive the illuminating light from the focusing imaging lens and transmit light in a plurality of ranges; and a plurality of sensors, each configured to capture images of the light received from the spectral separation module at different ranges.

13. The system of claim 12. wherein the spectral separation module comprises a first beam splitter configured to receive light from the focusing imaging lens and (i) direct a portion of the light towards at least one subsequent beam splitter and (ii) direct a portion of the light towards one of a plurality of bandpass filters, wherein the plurality of bandpass filters is configured to transmit light within a predetermined range to one of the plurality of sensors, and wherein the at least one subsequent beam splitter is configured to (i) direct a portion of the light to another at least one subsequent beam splitter and (ii) direct a portion of the light towards one of the plurality of bandpass filters.

14. The system of claim 13, wherein one of the at least one subsequent beam splitter is configured to (i) direct a portion of the light towards a mirror and (ii) direct a portion of the light towards one of the plurality⁷ of bandpass filters, wherein the mirror is configured to transmit light towards one of the plurality⁷ of bandpass filters.

15. The system of claim 13, wherein a total quantity of beam splitters comprised of the first beam splitter and the at least one subsequent beam splitter is tyvo, wherein a quantity of the plurality of bandpass filters is three, and wherein each of the plurality of bandpass filters is configured to transmit a different wavelength range including one of: (i) 632 nm, (ii) 532 nm. or (iii) 405nm.

16. The system of claim 12, wherein the multiwavelength light source is a super-continuum laser, a frequency comb, or a combined set of lasers at different wavelengths.

17. The system of claim 16, wherein the illuminating light of the super-continuum laser comprises wavelengths between or including 450 nm and 2000 nm.

18. The system of claim 12, further comprising an attenuator positioned in the back focal plane of the objective lens.

19. The system of claim 12, further comprising a sample positioned on the sample stage, wherein the sample is a bio-nanoparticle with a radius between 5 to 1000 nm.

20. The system of claim 12, wherein the primary beam splitter comprises an achromatic quarter wave plate configured to circularly polarize the illuminating light.

21. A method for hyperspectral acquisition and identification of a nanoparticle sample, the method comprising: providing a plurality of bandpass filters each directing output light to a sensor, where each bandpass filter is configured to filter a different wavelength range; producing a broadband spectrum of wavelengths directed to the sample; imaging hyperspectral data of the sample with the sensors; generating a spectral profile of the sample with the hyperspectral data imaged by the sensors; extracting intensities of the spectral profile using spectral decomposition; comparing intensities to a hyperspectral library to identify the sample.

22. The method of claim 21 , further comprising acquiring the hyperspectral library wi th respect to an initial particle status, and wherein comparing intensities to a hyperspectral 1 ibrary to identify the sample comprises matching the instantaneous spectral line with a library identity within the hyperspectral library.

23. The method of claim 21 , further comprising scanning a sample stage that defines a location of the sample to produce a sample stage image.

24. The method of claim 23, wherein generating a spectral profile of the sample with the hyperspectral data imaged by the sensors further comprises normalizing the hyperspectral data with the sample stage image to produce a background illumination image. The method of claim 21, wherein the different wave length range includes one of: (i) 632 nm, (ii) 532 nm, or (iii) 405nm.

25. The method of claim 21, wherein the different wave length range is one of 600-700 nm, 500-560 nm, or 400-475 nm.

26. The method of claim 23, wherein generating a spectral profile of the sample with the hyperspectral data imaged by the sensors further comprises normalizing the hyperspectral data with the sample stage image to produce a background illumination image.