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Oscillating-gradient diffusion-weighted MRI provides accurate cell radii in tumor spheroids
Marcel Kettelmann1, Stephan Niland2, Mirjam Gerwing1, Markus Wick3, Sascha Koehler3, Lydia Wachsmuth1, Moritz Wildgruber1, Johannes A Eble2, and Cornelius Faber1

1Translational Research Imaging Center (TRIC), University Hospital Muenster, Muenster, Germany, 2Institute of Physiological Chemistry and Pathobiochemistry, University Hospital Muenster, Muenster, Germany, 3Bruker BioSpin, Ettlingen, Germany

Synopsis

Diffusion weighted MRI using oscillating gradients has previously been shown to provide microstructural information on celllularity in tumors, which may serve as marker for monitoring therapy response. Which geometrical model for analysis of such data provides most reliable results, is, however, a matter of debate. Here, we used the IMPULSED approach, and show that cell radii in tumor spheroids of three different cell lines can be determined with high accuracy. In an in vivo model, however, deviations from radii determined by laser scanning microscopy were found.

Intrduction

DW-MRI has been shown to provide a sensitive early marker for therapy response in tumor treatment. Changes in tissue density, cellularity, or vascularization are reflected in diffusion parameters. How exactly structural and physiological parameters influence diffusion parameters, is currently a matter of debate. MRI sequences using oscillating instead of constant pulsed gradients, have been shown to provide more detailed insight into the microstructure of tumors. Three different geometrical models dubbed IMPULSED, POMACE and VERDICT have previously been described, as reviewed in (1). Here, we have used oscillating gradient DWI and the IMPULSED approach to calculate diameters of cells in spheroids of three different cancer cell lines, and in vivo in human xenograft mouse model, and we compared those to laser scanning microscopy data.

Methods

Tumor spheroids of SK-Mel-30, MG63 and A375 cells, respectively, were grown in 96 well plates to a diameter of 500-700 µm. For this purpose, 3000 or 6000 cells were initially seeded in methylcellulose containing medium, grown overnight and stained with wheat germ agglutinin, tetramethylrhodamine conjugate (WGA-TRITC) and Hoechst 33342. Spheroids were transferred to PCR tubes and embedded in Iow-melting agarose for MRI (Fig. 1). For the in vivo model 106 4T1 cells were injected into the mammary fat pad of balb-c mice and grown for three to six days (n=3). Scanning was performed at 9.4 T on a 94/20 BioSpec (Bruker BioSpin) using a CryoProbe and a 0.7 mT/m gradient system. Images were acquired with a spin echo gradient sequence using oscillating gradients with the following parameter for spheroids: (TR/TE:2000/89.4 ms; 2 segments, matrix 128x128, FOV: 8x8 mm2, resulting in a resolution of 63 µm and a scan time of 1:59 min). Modulation frequencies of the 20 ms gradients (5 ms separation) were 200 Hz, 150 Hz, 100 Hz and 50 Hz. For each frequency nine b-values were used: 1000, 875, 750, 625, 500, 375, 250, 125, 0 s/mm2. Four repetitions were performed for each set of scan parameters. Parameters for in vivo scans were TR/TE:3000/21.5 ms; 2 segments, matrix 108x96, FOV: 18x15 mm2) For analysis according to the IMPULSED approach, perfectly spherical cells with impermeable, infinitesimal walls were assumed. Tumors were manually segmented in the images and intensities fitted with the equation given by Jiang et al (2,3), yielding five parameters including average cell radius. Laser scanning microscopy was performed with a LSM 800 (Zeiss) (Fig. 2). Cell radii and eccentricity were determined manually using ImageJ.

Results

SNR values ranged between 30 and 70, and allowed for clearly delineating the spheroids and successful fitting of the data. For A375, SK-Mel-30, and MG-63 cells average radii of 11.1±0.9 µm (n=6 spheroids), 11.7±1.3 µm (n=9), and 13.9±1.4 µm (n=7) were calculated from the DWI data. These agreed well with the values obtained for the different cell lines by laser scanning microscopy of 8.7±2.4 µm (n=41 cells), 11.5±3.0 µm (n=91), and 13.6±2.1 µm (n=50). Eccentricity values were determined as 0.34, 0.42, and 0.34, respectively. Radii obtained by MRI for each individual spheroid and average values from microscopy are summarized in Fig. 3. For in vivo experiments, MR analysis of the 4T1 cells yielded an average radius of 9.9±1.9 µm, which exceeded the radius obtained from laser scanning microscopy of 6.4±1.0 µm (Fig. 4). The eccentricity was determined as 0.72.

Discussion

Determining cell radii from oscillating gradient DW-MRI is based on assumptions about geometry and exchange between compartments. Tumor spheroids very closely reproduce the assumption of spherical cells with no other disturbing structures, such as vessels or necrotic tumor regions. For these conditions the IMPULSED approach is capable to determine cell radii with high accuracy, as shown here for three different tumor cell lines. For tumors in vivo, MRI results deviated from microscopy data. This mismatch may be explained in part by the larger eccentricity of the 4T1 cells, but is most likely also due to the presence of vessels and small areas with beginning necrosis.

Conclusion

The IMPULSED approach provides highly accurate radii for spherical cells in tumor spheroids. For in vivo tumors however, more complex geometrical assumptions, such as for example the VERDICT model (4), may be required to provide correct estimates of the cellular microstructure, a potentially reliable marker for treatment response in cancer.

Acknowledgements

This work was supported by the DFG SFB1009, Z02 and A09

References

1. Reynaud O. Time-dependent diffusion MRI in cancer: Tissue modeling and applications. Front Phys. 2017; 5:1-16.

2. Jiang X, Li H, Xie J, et al. Quantification of cell size using temporal diffusion spectroscopy. Magn Reson Med. 2016; 75:1076-1085.

3. Jiang X, Li H, Xie J, et al. In vivo imaging of cancer cell size and cellularity using temporal diffusion spectroscopy. Magn Reson Med. 2017; 78:156-164.

4. Panagiotaki E, Walker-Samuel S, Siow B, et al. Noninvasive quantification of solid tumor microstructure using VERDICT MRI. Cancer Res. 2014; 74:1902–12.

Figures

Figure 1: Schematic of sample preparation for MRI of tumor spheroids, and representative DWI obtained with b=1000.

Figure 2: Laser scanning microscopy of a representative A375 spheroid (A), and enlarged detail of one exemplary Sk-Mel-30 spheroid (B). Cell membranes are labeled in red by WGA-TRTC. Hoechst 33342 staining shows nuclei in blue.

Figure 3: Cell radii obtained from each single spheroid, averaged over four repetitions of DWI. Averages for each cell line are indicated by horizontal lines, shaded areas indicate standard deviations (purple, A375, green, Sk-Mel-30, red, MG-63). Blue lines and shaded areas indicate microscopically determined averages and standard deviations.

Figure 4: T2w MRI showing an exemplary 4T1-tumor in the mammary fat pad. (B,C) Representative laser scanning microscopy of 4T1 tumor tissue. Cell membranes are labeled in red by WGA-TRTC. Hoechst 33342 staining shows nuclei in blue. In (B) vessels inside tumor tissue are visible.

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)
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