Proof of concept of a multimodal intravital molecular imaging system for tumour transpathology investigation.
Fiducial marker
Glycolysis imaging
Intravital imaging
Multimodal imaging
Positron imaging
Transpathology
Tumour microenvironment
Window chamber
Journal
European journal of nuclear medicine and molecular imaging
ISSN: 1619-7089
Titre abrégé: Eur J Nucl Med Mol Imaging
Pays: Germany
ID NLM: 101140988
Informations de publication
Date de publication:
03 2022
03 2022
Historique:
received:
13
05
2021
accepted:
22
09
2021
pubmed:
16
10
2021
medline:
27
4
2022
entrez:
15
10
2021
Statut:
ppublish
Résumé
Transpathology highlights the interpretation of the underlying physiology behind molecular imaging. However, it remains challenging due to the discrepancies between in vivo and in vitro measurements and difficulties of precise co-registration between trans-scaled images. This study aims to develop a multimodal intravital molecular imaging (MIMI) system as a tool for in vivo tumour transpathology investigation. The proposed MIMI system integrates high-resolution positron imaging, magnetic resonance imaging (MRI) and microscopic imaging on a dorsal skin window chamber on an athymic nude rat. The window chamber frame was designed to be compatible with multimodal imaging and its fiducial markers were customized for precise physical alignment among modalities. The co-registration accuracy was evaluated based on phantoms with thin catheters. For proof of concept, tumour models of the human colorectal adenocarcinoma cell line HT-29 were imaged. The tissue within the window chamber was sectioned, fixed and haematoxylin-eosin (HE) stained for comparison with multimodal in vivo imaging. The final MIMI system had a maximum field of view (FOV) of 18 mm × 18 mm. Using the fiducial markers and the tubing phantom, the co-registration errors are 0.18 ± 0.27 mm between MRI and positron imaging, 0.19 ± 0.22 mm between positron imaging and microscopic imaging and 0.15 ± 0.27 mm between MRI and microscopic imaging. A pilot test demonstrated that the MIMI system provides an integrative visualization of the tumour anatomy, vasculatures and metabolism of the in vivo tumour microenvironment, which was consistent with ex vivo pathology. The established multimodal intravital imaging system provided a co-registered in vivo platform for trans-scale and transparent investigation of the underlying pathology behind imaging, which has the potential to enhance the translation of molecular imaging.
Sections du résumé
BACKGROUND
Transpathology highlights the interpretation of the underlying physiology behind molecular imaging. However, it remains challenging due to the discrepancies between in vivo and in vitro measurements and difficulties of precise co-registration between trans-scaled images. This study aims to develop a multimodal intravital molecular imaging (MIMI) system as a tool for in vivo tumour transpathology investigation.
METHODS
The proposed MIMI system integrates high-resolution positron imaging, magnetic resonance imaging (MRI) and microscopic imaging on a dorsal skin window chamber on an athymic nude rat. The window chamber frame was designed to be compatible with multimodal imaging and its fiducial markers were customized for precise physical alignment among modalities. The co-registration accuracy was evaluated based on phantoms with thin catheters. For proof of concept, tumour models of the human colorectal adenocarcinoma cell line HT-29 were imaged. The tissue within the window chamber was sectioned, fixed and haematoxylin-eosin (HE) stained for comparison with multimodal in vivo imaging.
RESULTS
The final MIMI system had a maximum field of view (FOV) of 18 mm × 18 mm. Using the fiducial markers and the tubing phantom, the co-registration errors are 0.18 ± 0.27 mm between MRI and positron imaging, 0.19 ± 0.22 mm between positron imaging and microscopic imaging and 0.15 ± 0.27 mm between MRI and microscopic imaging. A pilot test demonstrated that the MIMI system provides an integrative visualization of the tumour anatomy, vasculatures and metabolism of the in vivo tumour microenvironment, which was consistent with ex vivo pathology.
CONCLUSIONS
The established multimodal intravital imaging system provided a co-registered in vivo platform for trans-scale and transparent investigation of the underlying pathology behind imaging, which has the potential to enhance the translation of molecular imaging.
Identifiants
pubmed: 34651225
doi: 10.1007/s00259-021-05574-y
pii: 10.1007/s00259-021-05574-y
pmc: PMC8921117
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1157-1165Informations de copyright
© 2021. The Author(s).
Références
Tian M, He X, Jin C, He X, Wu S, Zhou R, et al. Transpathology: molecular imaging-based pathology. Eur J Nucl Med Mol Imaging. 2021. https://doi.org/10.1007/s00259-021-05234-1 .
doi: 10.1007/s00259-021-05234-1
pubmed: 34893920
pmcid: 8440289
Phelps M, Schwaiger M, Chiti A. Multi-scale imaging as an essential tool for precision medicine. Eur J Nucl Med Mol Imaging. 2021. https://doi.org/10.1007/s00259-021-05367-3 .
doi: 10.1007/s00259-021-05367-3
pubmed: 33974092
Cho H, Ackerstaff E, Carlin S, Lupu ME, Wang Y, Rizwan A, et al. Noninvasive multimodality imaging of the tumor microenvironment: registered dynamic magnetic resonance imaging and positron emission tomography studies of a preclinical tumor model of tumor hypoxia. Neoplasia. 2009;11:247–59.
doi: 10.1593/neo.81360
Bali MA, Metens T, Denolin V, Delhaye M, Demetter P, Closset J, et al. Tumoral and nontumoral pancreas: correlation between quantitative dynamic contrast-enhanced MR imaging and histopathologic parameters. Radiology. 2011;261:456–66. https://doi.org/10.1148/radiol.11103515 .
doi: 10.1148/radiol.11103515
pubmed: 21852570
Hu S, Balakrishnan A, Bok RA, Anderton B, Larson PE, Nelson SJ, et al. 13C-pyruvate imaging reveals alterations in glycolysis that precede c-Myc-induced tumor formation and regression. Cell Metab. 2011;14:131–42. https://doi.org/10.1016/j.cmet.2011.04.012 .
doi: 10.1016/j.cmet.2011.04.012
pubmed: 21723511
Viel T, Talasila KM, Monfared P, Wang J, Jikeli JF, Waerzeggers Y, et al. Analysis of the growth dynamics of angiogenesis-dependent and -independent experimental glioblastomas by multimodal small-animal PET and MRI. J Nucl Med. 2012;53:1135–45. https://doi.org/10.2967/jnumed.111.101659 .
doi: 10.2967/jnumed.111.101659
pubmed: 22689925
Jain RK. The next frontier of molecular medicine: delivery of therapeutics. Nat Med. 1998;4:655–7.
doi: 10.1038/nm0698-655
Puri T, Chalkidou A, Henley-Smith R, Roy A, Barber PR, Guerrero-Urbano T, et al. A method for accurate spatial registration of PET images and histopathology slices. EJNMMI Res. 2015;5:64. https://doi.org/10.1186/s13550-015-0138-7 .
doi: 10.1186/s13550-015-0138-7
pubmed: 26576995
pmcid: 4648832
Jain RK, Munn LL, Fukumura D. Transparent window models and intravital microscopy: imaging gene expression, physiological function and therapeutic effects in tumors. In: Teicher BA, editor. Tumor Models in Cancer Research: Springer; 2011.
Pittet MJ, Weissleder R. Intravital imaging. Cell. 2011;147:983–91. https://doi.org/10.1016/j.cell.2011.11.004 .
doi: 10.1016/j.cell.2011.11.004
pubmed: 22118457
Oishi H, Sunamura M, Egawa S, Motoi F, Unno M, Furukawa T, et al. Blockade of delta-like ligand 4 signaling inhibits both growth and angiogenesis of pancreatic cancer. Pancreas. 2010;39:897–903. https://doi.org/10.1097/MPA.0b013e3181ce7185 .
doi: 10.1097/MPA.0b013e3181ce7185
pubmed: 20182391
Chen X, Leischner U, Rochefort NL, Nelken I, Konnerth A. Functional mapping of single spines in cortical neurons in vivo. Nature. 2011;475:501–5. https://doi.org/10.1038/nature10193 .
doi: 10.1038/nature10193
pubmed: 21706031
Jain RK, Munn LL, Fukumura D. Dissecting tumour pathophysiology using intravital microscopy. Nat Rev Cancer. 2002;2:266–76. https://doi.org/10.1038/nrc778 .
doi: 10.1038/nrc778
pubmed: 12001988
Vajkoczy P, Ullrich A, Menger MD. Intravital fluorescence videomicroscopy to study tumor angiogenesis and microcirculation. Neoplasia. 2000;2:53–61. https://doi.org/10.1038/sj.neo.7900062 .
doi: 10.1038/sj.neo.7900062
pubmed: 10933068
pmcid: 1531866
Guba M, von Breitenbuch P, Steinbauer M, Koehl G, Flegel S, Hornung M, et al. Rapamycin inhibits primary and metastatic tumor growth by antiangiogenesis: involvement of vascular endothelial growth factor. Nat Med. 2002;8:128–35. https://doi.org/10.1038/nm0202-128 .
doi: 10.1038/nm0202-128
pubmed: 11821896
Dewhirst MW, Ong ET, Braun RD, Smith B, Klitzman B, Evans SM, et al. Quantification of longitudinal tissue pO2 gradients in window chamber tumours: impact on tumour hypoxia. Brit J Cancer. 1999;79:1717–22.
doi: 10.1038/sj.bjc.6690273
Cardenas-Navia LI, Mace D, Richardson RA, Wilson DF, Shan S, Dewhirst MW. The pervasive presence of fluctuating oxygenation in tumors. Can Res. 2008;68:5812–9. https://doi.org/10.1158/0008-5472.CAN-07-6387 .
doi: 10.1158/0008-5472.CAN-07-6387
Gaustad JV, Brurberg KG, Simonsen TG, Mollatt CS, Rofstad EK. Tumor vascularity assessed by magnetic resonance imaging and intravital microscopy imaging. Neoplasia. 2008;10:354–62. https://doi.org/10.1593/neo.08162 .
doi: 10.1593/neo.08162
pubmed: 18392132
pmcid: 2288537
Schafer R, Leung HM, Gmitro AF. Multi-modality imaging of a murine mammary window chamber for breast cancer research. Biotechniques. 2014;57:45–50. https://doi.org/10.2144/000114191 .
doi: 10.2144/000114191
pubmed: 25005693
pmcid: 4136411
Laschke MW, Vollmar B, Menger MD. The dorsal skinfold chamber: window into the dynamic interaction of biomaterials with their surrounding host tissue. Eur Cell Mater. 2011;22:147–64.
doi: 10.22203/eCM.v022a12
Gregory MP, Andrew NF, Siqing S, Gabi H, Guoqing Z, Cassandra LF, et al. In vivo optical molecular imaging and analysis in mice using dorsal window chamber models applied to hypoxia, vasculature and fluorescent reporters. Nat Protoc. 2011;6:1355–66. https://doi.org/10.1038/nprot.2011.349 .
doi: 10.1038/nprot.2011.349
Wang Q, Tous J, Liu Z, Ziegler S, Shi K. Evaluation of Timepix silicon detector for the detection of 18F positrons. J Instrument. 2014;9:C05067.
doi: 10.1088/1748-0221/9/05/C05067
Wang Q, Liu Z, Ziegler SI, Shi K. Enhancing spatial resolution of (18)F positron imaging with the Timepix detector by classification of primary fired pixels using support vector machine. Phys Med Biol. 2015;60:5261–78. https://doi.org/10.1088/0031-9155/60/13/5261 .
doi: 10.1088/0031-9155/60/13/5261
pubmed: 26086805
Romano A, Tavanti F, Rossi Espagnet MC, Terenzi V, Cassoni A, Suma G, et al. The role of time-resolved imaging of contrast kinetics (TRICKS) magnetic resonance angiography (MRA) in the evaluation of head-neck vascular anomalies: a preliminary experience. Dentomaxillofac Radiol. 2015;44:20140302. https://doi.org/10.1259/dmfr.20140302 .
doi: 10.1259/dmfr.20140302
pubmed: 25410709
Damon J. Properties of ridges and cores for two-dimensional images. J Math Imaging Vis. 1999;10:163–74. https://doi.org/10.1023/A:1008379107611 .
doi: 10.1023/A:1008379107611
Wehrl HF, Sauter AW, Divine MR, Pichler BJ. Combined PET/MR: a technology becomes mature. J Nucl Med. 2015;56:165–8. https://doi.org/10.2967/jnumed.114.150318 .
doi: 10.2967/jnumed.114.150318
pubmed: 25593114
Hundshammer C, Braeuer M, Muller CA, Hansen AE, Schillmaier M, Duwel S, et al. Simultaneous characterization of tumor cellularity and the Warburg effect with PET, MRI and hyperpolarized (13)C-MRSI. Theranostics. 2018;8:4765–80. https://doi.org/10.7150/thno.25162 .
doi: 10.7150/thno.25162
pubmed: 30279736
pmcid: 6160766
Fanti S, Minozzi S, Antoch G, Banks I, Briganti A, Carrio I, et al. Consensus on molecular imaging and theranostics in prostate cancer. Lancet Oncol. 2018;19:e696–708. https://doi.org/10.1016/S1470-2045(18)30604-1 .
doi: 10.1016/S1470-2045(18)30604-1
pubmed: 30507436
Gennaro N, Marrari A, Renne SL, Cananzi FCM, Quagliuolo VL, Di Brina L, et al. Multimodality imaging of adult rhabdomyosarcoma: the added value of hybrid imaging. Br J Radiol. 2020;93:20200250. https://doi.org/10.1259/bjr.20200250 .
doi: 10.1259/bjr.20200250
pubmed: 32559113
pmcid: 7446015
Catalano OA, Horn GL, Signore A, Iannace C, Lepore M, Vangel M, et al. PET/MR in invasive ductal breast cancer: correlation between imaging markers and histological phenotype. Br J Cancer. 2017;116:893–902. https://doi.org/10.1038/bjc.2017.26 .
doi: 10.1038/bjc.2017.26
pubmed: 28208155
pmcid: 5379139
Preibisch C, Shi K, Kluge A, Lukas M, Wiestler B, Gottler J, et al. Characterizing hypoxia in human glioma: a simultaneous multimodal MRI and PET study. NMR in biomedicine. 2017;30. https://doi.org/10.1002/nbm.3775 .
Berker Y, Li Y. Attenuation correction in emission tomography using the emission data–a review. Med Phys. 2016;43:807–32. https://doi.org/10.1118/1.4938264 .
doi: 10.1118/1.4938264
pubmed: 26843243
pmcid: 4715007
Moses WW. Fundamental limits of spatial resolution in PET. Nucl Instrum Methods Phys Res A. 2011;648:S236–40. https://doi.org/10.1016/j.nima.2010.11.092 .
Liu Z, Zhang P, Ji H, Long Y, Jing B, Wan L, et al. A mini-panel PET scanner-based microfluidic radiobioassay system allowing high-throughput imaging of real-time cellular pharmacokinetics. Lab Chip. 2020;20:1110-23. https://doi.org/10.1039/C9LC01066A
Stickel JR, Cherry SR. High-resolution PET detector design: modelling components of intrinsic spatial resolution. Phys Med Biol. 2005;50:179-95
doi: 10.1088/0031-9155/50/2/001
pubmed: 15742938
Liu Z, Jian Z, Wang Q, Cheng T, Feuerecker B, Schwaiger M, et al. A continuously infused microfluidic radioassay system for the characterization of cellular pharmacokinetics. J Nucl Med. 2016;57:1548–55. https://doi.org/10.2967/jnumed.115.169151 .
doi: 10.2967/jnumed.115.169151
pubmed: 27363838
Hofheinz F, Langner J, Petr J, Beuthien-Baumann B, Oehme L, Steinbach J, et al. A method for model-free partial volume correction in oncological PET. EJNMMI Res. 2012;2:16. https://doi.org/10.1186/2191-219X-2-16 .
doi: 10.1186/2191-219X-2-16
pubmed: 22531468
pmcid: 3502253
Cysouw MCF, Golla SVS, Frings V, Smit EF, Hoekstra OS, Kramer GM, et al. Partial-volume correction in dynamic PET-CT: effect on tumor kinetic parameter estimation and validation of simplified metrics. EJNMMI Res. 2019;9:12. https://doi.org/10.1186/s13550-019-0483-z .
doi: 10.1186/s13550-019-0483-z
pubmed: 30715647
pmcid: 6362178
Sadeghi MM. (18)F-FDG PET and vascular inflammation: time to refine the paradigm? J Nucl Cardiol. 2015;22:319–24. https://doi.org/10.1007/s12350-014-9917-1 .
doi: 10.1007/s12350-014-9917-1
pubmed: 24925623
pmcid: 4265310
Kim M, Achmad A, Higuchi T, Arisaka Y, Yokoo H, Yokoo S, et al. Effects of intratumoral inflammatory process on 18F-FDG uptake: pathologic and comparative study with 18F-fluoro-α-methyltyrosine PET/CT in oral squamous cell carcinoma. J Nucl Med. 2015;56:16–21. https://doi.org/10.2967/jnumed.114.144014 .
doi: 10.2967/jnumed.114.144014
pubmed: 25476535