Biomarker Imaging for Preclinical Cancer Research

Scientific article by Nina Culum, MSc

Despite advances in diagnostics and treatment, cancer remains a leading cause of death worldwide [1]. Many cancers are already metastatic at presentation due to limited options for early cancer screening, many of which involve invasive physical exams, tissue biopsies, or radiation for imaging [2]. A major challenge in effective cancer treatment is therefore early disease diagnosis, which would greatly improve patient survival. Current and emerging molecular biomarkers for cancer detection and progression monitoring are vital to cancer management, but the challenge remains to identify those with adequate sensitivity and specificity for accurate diagnosis and prognosis [3].

Preclinical and Clinical Applications of Cancer Biomarker Imaging

Biospecimen-derived and imaging biomarkers are both widely used in oncology research and practice. In healthcare settings, biomarker imaging applications include diagnosing and staging cancer, targeting treatments, and predicting and monitoring therapeutic efficacy and/or toxicity, while research applications include guiding drug development and tracking drug efficacy and resistance [4]. Although biomarkers are useful for clinical practice, those that do not cross the translational gap can still further research and drug discovery. For example, left ventricular ejection fraction, a safety biomarker, can guide recruitment and continuation in many clinical trials through scintigraphy or ultrasound imaging [5]. In this article, we review several modalities commonly used for cancer biomarker imaging at preclinical stages, as well as recent technological advances.

WEBINAR: Improving Sleep to Slow the Progression of Alzheimer’s Disease

An in-depth review and discussion on the value of imaging the mouse right ventricle and lungs using high-frequency ultrasound for models of cardiopulmonary physiology and associated diseases. WATCH NOW

Common Techniques for Cancer Biomarker Imaging in Preclinical Research

Noninvasive preclinical cancer imaging enables the study of proliferation, metabolism, apoptosis, angiogenesis, and gene expression, and can be used to evaluate the therapeutic effects of drug candidates and guide surgical approaches [6]. The choice of imaging technique depends on device availability, accessibility, and contrast that allows for best tumor imaging [7]. Common biomarker imaging methods include fluorescence, bioluminescence, ultrasound, photoacoustic, positron emission tomography (PET), computed tomography (CT), and magnetic resonance imaging (MRI), though this article will focus on optical and acoustic preclinical imaging techniques.

Fluorescence and Bioluminescence Biomarker Imaging

Fluorescence imaging requires an external light source to excite a fluorophore which, on decay, releases low energy light [7]. Although much of fluorescence imaging is done in 2D, 3D imaging is possible with fluorescence molecular tomography, which can visualize tissue with a penetration depth of several centimeters in the red to near-infrared (NIR) region [8]. Traditional fluorescence relies on fluorophores excited by light in the 650-950 nm region (NIR-I), but this intrinsically suffers from strong light attenuation in tissues as well as high autofluorescence that leads to shallow tissue penetration depth, low sensitivity, and high background signals [9]. Imaging at the 1000-1700 nm range (NIR-II), however, minimizes photon scattering and tissue autofluorescence, thereby increasing tissue penetration depth, sensitivity, and resolution [9].

A great number of novel probes for improved fluorescence imaging have been reported in recent years, such as enzyme-activated NIR-II probes [10, 11] and plasmonic-fluorescent nanoparticles [12]. A smart nanoprobe consisting of a self-assembling cyclopeptide-dye has been investigated, which responds to pH decreases in the tumor microenvironment by aggregating from small (80 nm) to large (500 nm) nanoparticles, allowing for high contrast and resolution tumor imaging in mice [13]. Rare earth-doped nanoparticles have also allowed for the visualization of tiny (2 mm) metastatic lesions in mice [14], while targeted heptamethine cyanine-based fluorophores have been used to target a diverse range of tumors [15]. First described in 2022, neodymium (3+)-coordinated black phosphorus quantum dots have been used for efficient glioblastoma imaging in mice as well as synergistic x-ray-induced photodynamic chemotherapy [16], while gadolinium-based virus-like nanoparticles have been shown to intraoperatively recognize residual tumors in a mouse model of breast cancer (Figure 1) [17].

Preclinical cancer biomarker imaging with fluorescence imaging

Figure 1: Preoperative, intraoperative, and postoperative images taken during white light (WL) only and NIR-II fluorescence (FL)-guided tumor resection surgeries in a mouse. Presence and absence of residual tumors were confirmed with bioluminescence (BL) imaging, while NIR-II fluorescence tumor recognition was confirmed with hematoxylin and eosin staining. © 2022 Yang et al., licensed under CC BY 4.0.

Bioluminescence imaging relies on the oxidation of a substrate (i.e., luciferin) by an enzyme (i.e., luciferase) to produce light, and has been used to monitor expression systems, visualize tumor growth, detect metastasis, and assess viral and gene therapies [7, 18]. However, genetic engineering is required to express luciferase in mammalian cells. Current research efforts are focused on developing luciferin-luciferase systems that are shifted towards the NIR region for brighter and more sustained signals compared to naturally occurring systems [18]. For example, red-shifted luciferins based on synthetic coelenterazine analogs and corresponding NanoLuc mutants have recently been used to develop a bioluminescence resonance energy-based Antares reporter for increased signal intensity and tissue penetration in vivo [19].

Ultrasound and Photoacoustic Biomarker Imaging

Ultrasound imaging relies on a transducer to generate sound pulses that propagate through tissue and are reflected back based on tissue density, and has been shown to closely monitor cancer development and metastasis in animals [7]. Microbubble contrast agents have expanded the utility of preclinical ultrasound imaging to allow for detailed interrogation of the cancer microvasculature, a technique referred to as contrast-enhanced ultrasound (CEUS) imaging [7, 20, 21]. For example, gemcitabine-loaded microbubbles have been used to substantially enhance tumor image quality in a murine pancreatic cancer model [22]. Additionally, microbubbles that target the breast cancer marker B7-H3 have been shown to differentiate normal mammary glands from those containing ductal carcinoma in situ (DCIS) in mice (Figure 2) [23].

Preclinical cancer biomarker imaging with ultrasound imaging

Figure 2: Ultrasound and CEUS images of murine mammary glands with normal or DCIS tissue (scale bar = 2 mm). © 2020 Bachawal et al., licensed under CC BY 4.0.

Photoacoustic imaging lies at the bridge of optical and acoustic imaging; by detecting optical absorption characteristics of biological tissue with ultrasound resolution, it can visualize molecular functional information in deep tissue better than pure optical imaging techniques [24]. In this method, molecular vibration and small pressure waves caused by light absorption generate thermoelastic expansion, and the resulting acoustic waves are detected by ultrasound transducers [18]. Whole body photoacoustic imaging of small animals has been widely applied in preclinical biomedical research to guide therapies and monitor drug delivery to tumors [24, 25].

Ultrasound and Photoacoustic Biomarker Imaging Solutions by FUJIFILM VisualSonics

Preclinical imaging data in rodents

Figure 3: Example Vevo images showcasing anatomical, functional, and molecular data across the whole rodent body.

FUJIFILM VisualSonics has specialized in ultra-high frequency ultrasound and photoacoustic imaging for more than 20 years. Ultra-high frequency ultrasound (up to 70 MHz) provides the resolution necessary to detect sub-millimeter tumors in preclinical cancer research models [26, 27]. Additionally, researchers can acquire functional data on blood flow, perfusion, and molecular expression with Doppler-based and contrast-enhanced imaging modes (Figure 3). When ultra-high frequency ultrasound is paired with the Vevo LAZR-X for photoacoustic imaging, anatomical and functional information can be co-registered with maps of oxygenation and biomarker distribution. Photoacoustic imaging with Vevo systems has been proven to be a valuable tool in assessing animal models of breast, [23], liver [26], and brain [28] tumors, as well as bacterial infections [29] and many other diseases. This multi-modal imaging allows for tumor detection in a myriad of ways, from tumor volume and vascularization to oxygenation and molecular expression [26, 28].

Visualsonics’ newest flagship platform, the Vevo F2, is the “world’s first” ultra-high to low frequency ultrasound system (Figure 4). The expanded bandwidth of this platform and the addition of new transducers provides increased penetration depth, allowing researchers to image a variety of animal models on the same system. The Vevo F2 features improve signal processing for faster image acquisition and include a triple transducer port for ease of switching between transducers and a new data acquisition mode (called VADA, or Vevo Advanced Data Acquisition), allowing researchers to configure custom image sequences for advanced applications such as ultrafast plane wave imaging. Together, the Vevo F2 and LAZR-X create a multi-modal, hybrid system that can provide researchers with anatomical, functional, and molecular data across different animal models like no other commercially available system.

Vevo F2 and LAZR-X for ultrasound imaging and photoacoustic imaging

Figure 4: The hybrid Vevo F2 and LAZR-X system for ultrasound and photoacoustic preclinical imaging (click to enlarge).

Several approaches for monitoring drug delivery and treatment response in animals through photoacoustic imaging have been described in recent years. For example, nanocarrier drug release has been monitored in a murine colon cancer model through a paclitaxel-methylene blue conjugate with redox activity; during release, this conjugate spontaneously oxidizes to produce a concentration-dependent photoacoustic signal with up to 649% signal enhancement after 10 hours [30]. Optical-resolution photoacoustic microscopy imaging has also been used to track vascular changes in a mouse model of prostate cancer, and was shown to be a promising method for elucidating drug mechanisms in vivo and for monitoring and guiding cancer therapy [31].

More recently, efforts in developing dual-mode imaging modalities have been published. For instance, a cyanine-based photocage has been described under hypoxic conditions, whose photolysis simultaneously produces fluorescence and photoacoustic signals for dual-mode tumor imaging [32]. The combination of ultrasound and photoacoustic imaging has also been shown to reliably assess differences in tissue oxygenation between control and pancreatic tumor-bearing mice, which holds promise in assessing treatment responses in longitudinal preclinical studies [33].

WEBINAR: Measuring EEG in vivo for Preclinical Evaluation of Sleep and Alzheimer’s Disease

Join Dr. Sicard for an examination of the systemic effects of myocardial infarction using high-frequency ultrasound and photoacoustics. WATCH NOW

Conclusions and Future Perspectives

Imaging biomarkers are essential to both routine cancer patient care and in research stages when investigating underlying mechanisms and potential therapies. Furthermore, noninvasive in vivo approaches for imaging animal models of cancer facilitate longitudinal treatment studies, which can recapitulate therapeutic effects in human cancers [7]. Many preclinical imaging options are available to researchers, each with their own benefits and limitations (Figure 5).

Comparison of techniques for preclinical cancer biomarker imaging

Figure 5: Summary of the preclinical applications, advantages, and disadvantages of each preclinical imaging technique discussed. Created with information from refs. 7, 18, and 24.

While each imaging modality has its own advantages and disadvantages, the shortcomings of each method can be overcome with the use of multimodal scanners. Dual-mode systems, such as the combination of ultrasound and photoacoustic imaging, could become an integral component of preclinical cancer imaging, enabling the assessment of tumor structure and function, and even facilitate the development of personalized medicine [7]. For more insights into preclinical cancer research and methods, browse our latest webinars here.

Share This Story!

About the Author

About the Author

Nina Culum, MSc

Nina Culum graduated from the University of Western Ontario with a Master of Science in physical and analytical chemistry. During her graduate studies, she fabricated plasmonic nanohole arrays to capture extracellular vesicles and detect cancer by surface-enhanced Raman spectroscopy. Prior to attending UWO, Nina completed her Bachelor of Science in chemistry at the University of Waterloo.


  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-49. DOI: 10.3322/caac.21660.
  2. DeLouize AM, Eick G, Karam SD, Snodgrass J. Current and future applications of biomarkers in samples collected through minimally invasive methods for cancer medicine and population-based research. Am J Hum Biol. 2021;e23665. DOI: 10.1002/ajhb.23665.
  3. Pal M, Muinao T, Boruah HPD, Mahindroo N. Current advances in prognostic and diagnostic biomarkers for solid cancers: detection techniques and future challenges. Biomed Pharmacother. 2022;146:112488. DOI: 10.1016/j.biopha.2021.112488.
  4. O’Connor JPB, Aboagye EO, Adams JE, Aerts HJWL, Barrington SF, Beer AJ, et al. Imaging biomarker roadmap for cancer studies. Nat Rev Clin Oncol. 2017;14:169-86. DOI: 10.1038/nrclinonc.2016.162.
  5. Plana JC, Galderisi M, Barac A, Ewer MS, Ky B, Scherrer-Crosbie M, et al. Expert consensus for multimodality imaging evaluation of adult patients during and after cancer therapy: a report from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. J Am Soc Echocardiogr. 2014;27(9):911-39. DOI: 10.1016/j.echo.2014.07.012.
  6. Khan AQ, Siveen KS, Prabhu KS, Kuttikrishnan S, Akhtar S, et al. Role of animal research in human malignancies. In: Azmi A, Mohammad RM, editors. Animal models in cancer discovery [Internet]. Elsevier Inc.; 2019 [cited 2022 Jul 08]. pp. 1-29. DOI: 10.1016/B978-0-12-814704-7.00003-9.
  7. McHugh CI, Blocker SJ, Viola-Villegas N, Shields AF. Cancer imaging in preclinical models. In: Azmi A, Mohammad RM, editors. Animal models in cancer discovery [Internet]. Elsevier Inc.; 2019 [cited 2022 Jul 11]. pp. 373-400. DOI: 10.1016/B978-0-12-814704-7.00016-7.
  8. Stuker F, Ripoll J, Rudin M. Fluorescence molecular tomography: principles and potential for pharmaceutical research. Pharmaceutics. 2011;3(2):299-74. DOI: 10.3390/pharmaceutics3020229.
  9. Meng X, Pand X, Zhang K, Gong C, Yang J, Dong H, et al. Recent advances in near-infrared-II fluorescence imaging for deep-tissue molecular analysis and cancer diagnosis. Small. 2022;18:2202035. DOI: 10.1002/smll.202202035.
  10. Chen J-A, Pan H, Wang Z, Gao J, Tan J, Ouyang Z, et al. Imaging of ovarian cancers using enzyme activatable probes with second near-infrared window emission. Chem Commun. 2020;56:2731-4. DOI: 10.1039/C9CC09158K.
  11. Zhan Y, Huang H, Zhang Y, Chen G, Huang S, Li C, et al. Rapid unperturbed-tissue analysis for intraoperative cancer diagnosis using an enzyme-activated NIR-II nanoprobe. Angew Chem Int Ed Engl. 2021;60(5):2637-42. DOI: 10.1002/anie.202011903.
  12. Zhang X, Wang W, Su L, Ge X, Ye J, Zhao C, et al. Plasmonic-fluorescent Janus Ag/Ag2S nanoparticles for in situ H2O2-activated NIR-II fluorescence imaging. Nano Lett. 2021;21(6):2625-33. DOI: 10.1021/acs.nanolett.1c00197.
  13. Chen H, Shou K, Chen S, Qu C, Wang Z, Jiang L, et al. Smart self-assembly amphiphilic cyclopeptide-dye for near-infrared window-II imaging. Adv Mater. 2021;33(16):e2006902. DOI: 10.1002/adma.202006902.
  14. Ren Y, He S, Huttad L, Chua M-S, So SK, Guo Q, et al. An NIR-II/MR dual modal nanoprobe for liver cancer imaging. Nanoscale. 2020;12(21):11510-7. DOI: 10.1039/D0NR00075B.
  15. Kang H, Shamim M, Yin X, Adluru E, Fukuda T, Yokomizo S, et al. Tumor-associated immune-cell-mediated tumor-targeting mechanism with NIR-II fluorescence imaging. Adv Mater. 2022;34(8):e2106500. DOI: 10.1002/adma.202106500.
  16. Li Z, Zhao C, Fu Q, Ye J, Su L, Ge X, et al. Neodymium (3+)-coordinated black phosphorus quantum dots with retrievable NIR/x-ray optoelectronic switching effect with anti-glioblastoma. Small. 2022;18:2105160. DOI: 10.1002/smll.202105160.
  17. Yang R-Q, Wang P-Y, Lou K-L, Dang Y-Y, Tian H-N, Li Y, et al. Biodegradable nanoprobe for NIR-II fluorescence image-guided surgery and enhanced breast cancer radiotherapy efficacy. Adv Sci. 2022;9(12):2104728. DOI: 10.1002/advs.202104728.
  18. Pirovano G, Roberts S, Kossatz S, Reiner T. Optical imaging modalities: principles and applications in preclinical research and clinical settings. J Nucl Med. 2020;61(10):1419–27. DOI: 10.2967/jnumed.119.238279.
  19. Yeh H-W, Karmach O, Ji A, Carter D, Martins-Green MM, Ai H-w. Red-shifted luciferase–luciferin pairs for enhanced bioluminescence imaging. Nat Methods. 2017;14:971-4. DOI:10.1038/nmeth.4400.
  20. Diakova GB, Du Z, Klibanov AL. Targeted ultrasound contrast imaging of tumor vasculature with positively charged microbubbles. Invest Radiol. 2020;55(11):736-40. DOI: 10.1097/RLI.0000000000000699.
  21. Liu Y, Lai X, Zhu Y, Guo F, Su L, Arkin G, et al. Contrast-enhanced ultrasound imaging using long-circulating cationic magnetic microbubbles in vitro and in vivo validations. Int J Pharm. 2022;616:121299. DOI: 10.1016/j.ijpharm.2021.121299.
  22. Delaney LJ, Eisenbrey JR, Brown D, Brody JR, Jimbo M, Oeffinger BE. Gemcitabine-loaded microbubble system for ultrasound imaging and therapy. Acta Biomater. 2021;130:385-94. DOI: 10.1016/j.actbio.2021.05.046.
  23. Bachawal S, Bean GR, Krings G, Wilson KE. Evaluation of ductal carcinoma in situ grade via triple-modal molecular imaging of B7-H3 expression. NPJ Breast Cancer. 2020;6:14. DOI: 10.1038/s41523-020-0158-y.
  24. Kye H, Song Y, Ninjbadgar T, Kim C, Kim J. Whole-body photoacoustic imaging techniques for preclinical small animal studies. Sensors. 2022;(14):5130. DOI: 10.3390/s22145130.
  25. Park B, Park S, Kim J, Kim C. Listening to drug delivery and responses via photoacoustic imaging. Adv Drug Deliv Rev. 2022;184:114235. DOI: 10.1016/j.addr.2022.114235.
  26. Yu Q, Huang S, Wu Z, Zheng J, Chen X, Nie L. Label-free visualization of early cancer hepatic micrometastasis and intraoperative image-guided surgery by photoacoustic imaging. J Nucl Med. 2020;61(7):1079-85. DOI: 10.2967/jnumed.119.233155.
  27. Sastra SA, Olive KP. Quantification of murine pancreatic tumors by high-resolution ultrasound. Methods Mol Biol. 2013;980:249-66. DOI: 10.1007/978-1-62703-287-2_13.
  28. Lavaud J, Henry M, Coll JL, Josserand V. Exploration of melanoma metastases in mice brains using endogenous contrast photoacoustic imaging. Int J Pharm. 20175;532(2):704-9. DOI: 10.1016/j.ijpharm.2017.08.104.
  29. Zlitni A, Gowrishankar G, Steinberg I, Haywood T, Gambhir SS. Maltotriose-based probes for fluorescence and photoacoustic imaging of bacterial infections. Nat Commun. 2020;11:1250. DOI: 10.1038/s41467-020-14985-8.
  30. Jeevarathinam AS, Lemaster JE, Chen F, Zhao E, Jokerst JV. Photoacoustic imaging quantifies drug release from nanocarriers via redox chemistry of dye-labeled cargo. Angew Chem Int Ed Engl. 2020;59(12):4678-83. DOI: 10.1002/anie.201914120.
  31. Zhou H-C, Chen N, Zhao H, Yin T, Zhang J, Zheng W, et al. Optical-resolution photoacoustic microscopy for monitoring vascular normalization during anti-angiogenic therapy. Photoacoustics. 2019;15:100143. DOI: 10.1016/j.pacs.2019.100143.
  32. Zhang Y, Yan C, Zheng Q, Jia Q, Wang Z, Shi P, et al. Harnessing hypoxia-dependent cyanine photocages for in vivo precision drug release. Angew Chem Int Ed Engl. 2021;60(17):9553-61. DOI: 10.1002/anie.202017349.
  33. Wang Y, Jhang D-F, Tsai C-H, Chiang N-J, Tsao C-H, Chuang C-C. In vivo assessment of hypoxia levels in pancreatic tumors using a dual-modality ultrasound/photoacoustic imaging system. Micromachines. 2021;12(6):668. DOI: 10.3390/mi12060668.