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Optical coherence tomography (OCT), a three-dimensional imaging technology, was used to monitor and characterize the growth kinetics of multicellular tumor spheroids. Precise volumetric quantification of tumor spheroids using a voxel counting approach, and label-free dead tissue detection in the spheroids based on intrinsic optical attenuation contrast, were demonstrated.
Tumor spheroids have been developed as a three-dimensional (3D) cell culture model in cancer research and anti-cancer drug discovery. However, currently, high-throughput imaging modalities utilizing bright field or fluorescence detection, are unable to resolve the overall 3D structure of the tumor spheroid due to limited light penetration, diffusion of fluorescent dyes and depth-resolvability. Recently, our lab demonstrated the use of optical coherence tomography (OCT), a label-free and non-destructive 3D imaging modality, to perform longitudinal characterization of multicellular tumor spheroids in a 96-well plate. OCT was capable of obtaining 3D morphological and physiological information of tumor spheroids growing up to about 600 µm in height. In this article, we demonstrate a high-throughput OCT (HT-OCT) imaging system that scans the whole multi-well plate and obtains 3D OCT data of tumor spheroids automatically. We describe the details of the HT-OCT system and construction guidelines in the protocol. From the 3D OCT data, one can visualize the overall structure of the spheroid with 3D rendered and orthogonal slices, characterize the longitudinal growth curve of the tumor spheroid based on the morphological information of size and volume, and monitor the growth of the dead-cell regions in the tumor spheroid based on optical intrinsic attenuation contrast. We show that HT-OCT can be used as a high-throughput imaging modality for drug screening as well as characterizing biofabricated samples.
Cancer is the second leading cause of death in the world1. Developing drugs targeting cancer is of crucial importance for patients. However, it is estimated that more than 90% of new anti-cancer drugs fail in the development phase because of a lack of efficacy and unexpected toxicity in clinical trials2. Part of the reason can be attributed to the use of simple two-dimensional (2D) cell culture models for compound screening, which provide results with limited predictive values of compound efficacy and toxicity for the following stages of drug discovery2,3,4. Recently, three-dimensional (3D) tumor spheroid models have been developed to provide clinically relevant physiological and pharmacological data for anti-cancer drug discovery3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25. Since these spheroids can mimic tissue-specific properties of tumors in vivo, such as nutrient and oxygen gradient, hypoxic core as well as drug resistance19, the use of these models can potentially shorten drug discovery timelines, reduce costs of investment, and bring new medicines to patients more effectively. One critical approach to evaluating compound efficacy in 3D tumor spheroid development is to monitor the spheroid growth and recurrence under treatments9,26. To do this, quantitative characterizations of the tumor morphology, involving its diameter and volume, with high-resolution imaging modalities, are imperative.
Conventional imaging modalities, such as bright-field, phase contrast7,9,22,24, and fluorescence microscopy8,9,16,18,22 can provide a measurement of the spheroid's diameter but cannot resolve the overall structure of the spheroid in 3D space. Many factors contribute to these limitations, including penetration of the probing light in the spheroid; diffusion of the fluorescent dyes into the spheroid; emitting fluorescent signals from excited fluorescent dyes inside or on the opposite surface of the spheroid due to strong absorption and scattering; and depth-resolvability of these imaging modalities. This often leads to an inaccurate volume measurement. Development of the necrotic core in spheroids mimics necrosis in in vivo tumors6,10,15,19,25. This pathological feature is unlikely reproduced in 2D cell cultures19,25,27,28. With a spheroid size larger than 500 µm in diameter, a three-layer concentric structure, including an outer layer of proliferating cells, a middle layer of quiescent cells, and a necrotic core, can be observed in the spheroid6,10,15,19,25, due to lack of oxygen and nutrients. Live and dead cell fluorescence imaging is the standard approach to label the boundary of the necrotic core. However, again, penetrations of both these fluorescent dyes and visible light hinder the potential to probe into the necrotic core to monitor its development in its actual shape.
An alternative 3D imaging modality, optical coherence tomography (OCT) is introduced to characterize the tumor spheroids. OCT is a biomedical imaging technique that is capable of acquiring label-free, non-destructive 3D data from up to 1-2 mm depths in biological tissues29,30,31,32,33,34. OCT employs low-coherence interferometry to detect back-scattered signals from different depths of the sample and provides reconstructed depth-resolved images at micron-level spatial resolutions in both lateral and vertical directions. OCT has been widely adopted in ophthalmology35,36,37 and angiography38,39. Previous studies have used OCT to observe the morphology of in vitro tumor spheroids in basement membrane matrix (e.g., Matrigel) and evaluate their responses to photodynamic therapy40,41. Recently, our group established a high-throughput OCT imaging platform to systematically monitor and quantify the growth kinetics of 3D tumor spheroids in multi-well plates42. Precise volumetric quantification of 3D tumor spheroids using a voxel counting approach and label-free necrotic tissue detection in the spheroids based on intrinsic optical attenuation contrast were demonstrated. This paper describes the details of how the OCT imaging platform was constructed and employed to obtain high-resolution 3D images of tumor spheroids. The step-by-step quantitative analyses of the growth kinetics of 3D tumor spheroids, including accurate measurements of spheroid diameter and volumes, is described. Also, the method of the non-destructive detection of necrotic tissue regions using OCT, based on the intrinsic optical attenuation contrast is presented.
1. Preparation of Cells
2. High-throughput OCT Imaging Platform
NOTE: See referenced work29,30,31,32,33,34 for a thorough review of principles and applications of OCT. See Figure 1 and Huang et al.42 for details of the custom OCT imaging system used in this study.
3. OCT Scanning and Processing of Tumor Spheroids
4. Morphological Quantification of 3D Tumor Spheroids
NOTE: A custom written code in MATLAB processes this quantification. Click the Run button to initiate the process. See Figure 2B for the flowchart of the steps of morphological quantification of spheroids.
5. Dead-Cell Region Detection of 3D Tumor Spheroids
NOTE: In a homogeneous medium, OCT back-scattered intensity detected as a function of depth (I(z)) can be described by the Beer-Lambert Law49: , where z represents the depth, μ is the optical attenuation coefficient, and I0 is the incident intensity to the sample. Hence the derived optical attenuation coefficient can be expressed as:
. Since OCT images are often plotted on a logarithmic scale, the slope of the OCT intensity profile can be retrieved to derive the optical attenuation coefficient. See Figure 2C for a flowchart of the generation of the optical attenuation maps.
6. Histology and Immunohistochemistry
NOTE: Histology and immunohistochemistry (IHC) stained images of tumor spheroids are obtained to correlate with the corresponding OCT results.
High Throughput Optical Coherence Tomography Imaging of Spheroids in a 96-well Plate
Figure 3 exhibits the result of HT-OCT scanning of a 96-well plate with HCT 116 tumor spheroids on Day 3. The sequential scan of the whole plate starts from the bottom-right well (H12). Figure 3B shows the flow chart of the software implementation of the HT-OCT system. After one spheroid d...
Tumor activity is highly relevant to its morphological structure. Similar to monitoring characteristic growth curve for 2D cell cultures, tracking the growth curve for 3D tumor spheroids is also a conventional approach to characterize the long-term spheroid growth behavior for different cell lines. Notably, we can characterize the drug response by analyzing tumor degradation or tumor regrowth directly reflected in the growth curve. Therefore, quantitative assessment of 3D tumor spheroids, including the size and volume, t...
The authors disclose no competing interest.
This work was supported by NSF grants IDBR (DBI-1455613), PFI:AIR-TT (IIP-1640707), NIH grants R21EY026380, R15EB019704 and R01EB025209, and Lehigh University startup fund.
Name | Company | Catalog Number | Comments |
Custom Spectral Domain OCT imaging system | Developed in our lab | ||
Superluminescent Diode (SLD) | Thorlabs | SLD1325 | light source |
2×2 single mode fused fiber coupler, 50:50 splitting ratio | AC Photonics | WP13500202B201 | |
Reference Arm | |||
Lens Tube | Thorlabs | ||
Adapter | Thorlabs | ||
Collimating Lens | Thorlabs | AC080-020-C | |
Focusing Lens | Thorlabs | ||
Kinematic Mirror Mount | Thorlabs | ||
Mirror | Thorlabs | ||
1D Translational Stage | Thorlabs | ||
Continuous neutral density filter | Thorlabs | ||
Pedestrial Post | Thorlabs | ||
Clamping Fork | Thorlabs | ||
Sample Arm | |||
Lens Tube | Thorlabs | ||
Adapter | Thorlabs | ||
Collimating Lens | Thorlabs | AC080-020-C | |
Galvanometer | Thorlabs | ||
Relay Lens | Thorlabs | AC254-100-C | two Relay lens to make a telescope setup |
Triangle Mirror Mount | Thorlabs | ||
Mirror | Thorlabs | ||
Objective | Mitutoyo | ||
Pedestrial Post | Thorlabs | ||
Clamping Fork | Thorlabs | ||
Polarization Controller | Thorlabs | ||
30mm Cage Mount | Thorlabs | ||
Cage Rod | Thorlabs | ||
Stage | |||
3D motorized translation stage | Beijing Mao Feng Optoelectronics Technology Co., Ltd. | JTH360XY | |
2D Tilting Stage | |||
Rotation Stage | |||
Plate Holder | 3D printed | ||
Spectrometer | |||
Lens Tube | Thorlabs | ||
Adapter | Thorlabs | ||
Collimating Lens | Thorlabs | AC080-020-C | |
Grating | Wasatch | G = 1145 lpmm | |
F-theta Lens | Thorlabs | FTH-1064-100 | |
InGaAs Line-scan Camera | Sensor Unlimited | SU1024-LDH2 | |
Name | Company | Catalog Number | Comments |
Cell Culture Component | |||
HCT 116 Cell line | ATCC | CCL-247 | |
Cell Culture Flask | SPL Life Sciences | 70025 | |
Pipette | Fisherbrand | 14388100 | |
Pipette tips | Sorenson Bioscience | 10340 | |
Gibco GlutaMax DMEM | Thermo Fisher Scientific | 10569044 | |
Fetal Bovine Serum, certified, US origin | Thermo Fisher Scientific | 16000044 | |
Antibiotic-Antimycotic (100X) | Thermo Fisher Scientific | 15240062 | |
Corning 96-well Clear Round Bottom Ultra-Low Attachment Microplate | Corning | 7007 | |
Gibco PBS, pH 7.4 | Thermo Fisher Scientific | 10010023 | |
Gibco Trypsin-EDTA (0.5%) | Thermo Fisher Scientific | 15400054 | |
Forma Series II 3110 Water-Jacketed CO2 Incubators | Thermo Fisher Scientific | 3120 | |
Gloves | VWR | 89428-750 | |
Parafilm | Sigma-Aldrich | P7793 | |
Transfer pipets | Globe Scientific | 138080 | |
Centrifuge | Eppendorf | 5702 R | To centrifuge the 15 mL tube |
Centrifuge | NUAIRE | AWEL CF 48-R | To centrifuge the 96-well plate |
Microscope | Olympus | ||
Name | Company | Catalog Number | Comments |
Histology & IHC | |||
Digital slide scanner | Leica | Aperio AT2 | Obtain high-resolution histological images |
Histology Service | Histowiz | Request service for histological and immunohistological staining of tumor spheroid | |
Name | Company | Catalog Number | Comments |
List of Commerical OCTs | |||
SD-OCT system | Thorlabs | Telesto Series | |
SD-OCT system | Wasatch Photonics | WP OCT 1300 nm | |
Name | Company | Catalog Number | Comments |
Software for Data Analyses | |||
Basic Image Analysis | NIH | ImageJ | Fiji also works. |
3D Rendering | Thermo Fisher Scientific | Amira | Commercial software. Option 1 |
3D Rendering | Bitplane | Imaris | Commercial software. Option 2. Used in the protocol |
OCT acquisition software | custom developed in C++. | ||
Stage Control | Beijing Mao Feng Optoelectronics Technology Co., Ltd. | MRC_3 | Incorporated into the custom OCT acquisition code |
OCT processing software | custom developed in C++. Utilize GPU. Incorporated into the custom OCT acquisition code. | ||
Morphological and Physiological Analysis | custom developed in MATLAB |
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