Skip to main content

Advertisement

SpringerLink
Log in

Artificial Intelligence Based Framework to Quantify the Cardiomyocyte Structural Integrity in Heart Slices

  • Original Article
  • Published:
Cardiovascular Engineering and Technology Aims and scope Submit manuscript

Abstract

Purpose

Drug induced cardiac toxicity is a disruption of the functionality of cardiomyocytes which is highly correlated to the organization of the subcellular structures. We can analyze cellular structures by utilizing microscopy imaging data. However, conventional image analysis methods might miss structural deteriorations that are difficult to perceive. Here, we propose an image-based deep learning pipeline for the automated quantification of drug induced structural deteriorations using a 3D heart slice culture model.

Methods

In our deep learning pipeline, we quantify the induced structural deterioration from three anticancer drugs (doxorubicin, sunitinib, and herceptin) with known adverse cardiac effects. The proposed deep learning framework is composed of three convolutional neural networks that process three different image sizes. The results of the three networks are combined to produce a classification map that shows the locations of the structural deteriorations in the input cardiac image.

Results

The result of our technique is the capability of producing classification maps that accurately detect drug induced structural deterioration on the pixel level.

Conclusion

This technology could be widely applied to perform unbiased quantification of the structural effect of the cardiotoxins on heart slices.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9

Similar content being viewed by others

References

  1. Abadi, M., A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, and M. Devin, et al. Tensorflow: large-scale machine learning on heterogeneous distributed systems, 2016. arXiv:1603.04467

  2. Barpe, D. R., D. D. Rosa, and P. E. Froehlich. Pharmacokinetic evaluation of doxorubicin plasma levels in normal and overweight patients with breast cancer and simulation of dose adjustment by different indexes of body mass. Eur. J. Pharma. Sci. 41(3–4):458–463, 2010.

    Article  CAS  Google Scholar 

  3. Fermini, B., and A. A. Fossa. The impact of drug-induced qt interval prolongation on drug discovery and development. Nat. Rev. Drug Discov. 2(6):439–447, 2003.

    Article  CAS  PubMed  Google Scholar 

  4. Fischer, C., H. Milting, E. Fein, E. Reiser, K. Lu, T. Seidel, C. Schinner, T. Schwarzmayr, R. Schramm, R. Tomasi, et al. Long-term functional and structural preservation of precision-cut human myocardium under continuous electromechanical stimulation in vitro. Nat. Commun. 10(1):1–12, 2019.

    Article  CAS  Google Scholar 

  5. Fu, X., H. Khalil, O. Kanisicak, J. G. Boyer, R. J. Vagnozzi, B. D. Maliken, M. A. Sargent, V. Prasad, I. Valiente-Alandi, B. C. Blaxall, et al.: Specialized fibroblast differentiated states underlie scar formation in the infarcted mouse heart. J. Clin. Invest. 128(5):2127–2143, 2018.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Hammouda, K., F. Khalifa, H. Abdeltawab, A. Elnakib, G. Giridharan, M. Zhu, C. Ng, S. Dassanayaka, M. Kong, H. Darwish, et al.: A new framework for performing cardiac strain analysis from cine mri imaging in mice. Sci. Rep. 10(1):1–15, 2020.

    Article  Google Scholar 

  7. Hammouda, K., F. Khalifa, A. Soliman, H. Abdeltawab, M. Ghazal, M. Abou El-Ghar, A. Haddad, H. E. Darwish, R. Keynton, and A. El-Baz: A 3d cnn with a learnable adaptive shape prior for accurate segmentation of bladder wall using mr images. In: 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), pp. 935–938. IEEE, 2020.

  8. Hammouda, K., F. Khalifa, A. Soliman, M. Ghazal, M. Abou El-Ghar, A. Haddad, M. Elmogy, H. Darwish, R. Keynton, and A. El-Baz: A deep learning-based approach for accurate segmentation of bladder wall using mr images. In: 2019 IEEE International Conference on Imaging Systems and Techniques (IST), pp. 1–6. IEEE, 2019.

  9. He, K., X. Zhang, S. Ren, and J. Sun. Delving deep into rectifiers: Surpassing human-level performance on imagenet classification. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1026–1034, 2015.

  10. Kang, C., Y. Qiao, G. Li, K. Baechle, P. Camelliti, S. Rentschler, I. Efimov: Human organotypic cultured cardiac slices: new platform for high throughput preclinical human trials. Sci. Rep. 6:28798, 2016.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kanisicak, O., H. Khalil, M. J. Ivey, J. Karch, B. D. Maliken, R. N. Correll, M. J. Brody, S. C. J. Lin, B. J. Aronow, M. D. Tallquist, et al. Genetic lineage tracing defines myofibroblast origin and function in the injured heart. Nat. Commun. 7(1):1–14, 2016.

    Article  Google Scholar 

  12. Kretzschmar, K., Y. Post, M. Bannier-Hélaouët, A. Mattiotti, J. Drost, O. Basak, V. S. Li, M. van den Born, Q. D. Gunst, D. Versteeg, et al. Profiling proliferative cells and their progeny in damaged murine hearts. Proc. Natl. Acad. Sci. 115(52):E12245–E12254, 2018.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Maillet, A., K. Tan, X. Chai, S. N. Sadananda, A. Mehta, J. Ooi, M. R. Hayden, M. A. Pouladi, S. Ghosh, W. Shim, et al.: Modeling doxorubicin-induced cardiotoxicity in human pluripotent stem cell derived-cardiomyocytes. Sci. Rep. 6(1):1–13, 2016.

    Article  Google Scholar 

  14. Miller, J. M., M. H. Meki, Q. Ou, S. A. George, A. Gams, R. R. Abouleisa, X. L. Tang, B. M. Ahern, G. A. Giridharan, A. El-Baz, et al. Heart slice culture system reliably demonstrates clinical drug-related cardiotoxicity. Toxicol. Appl. Pharmacol. 406:115213, 2020.

  15. Mohan, N., Y. Shen, Y. Endo, M. K. ElZarrad, and W. J. Wu. Trastuzumab, but not pertuzumab, dysregulates her2 signaling to mediate inhibition of autophagy and increase in reactive oxygen species production in human cardiomyocytes. Mol. Cancer Therap. 15(6):1321–1331, 2016.

    Article  CAS  Google Scholar 

  16. Moslehi, J. J. Cardiovascular toxic effects of targeted cancer therapies. N. Engl. J. Med. 375(15):1457–1467, 2016.

    Article  CAS  PubMed  Google Scholar 

  17. Onakpoya, I. J., C. J. Heneghan, and J. K. Aronson. Post-marketing withdrawal of 462 medicinal products because of adverse drug reactions: a systematic review of the world literature. BMC Med. 14(1):10, 2016.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Ou, Q., R. R. Abouleisa, X. L. Tang, H. R. Juhardeen, M. H. Meki, J. M. Miller, G. Giridharan, A. El-Baz, R. Bolli, and T. M. Mohamed. Slicing and culturing pig hearts under physiological conditions. J. Visual. Exp. Jove, 2020. https://doi.org/10.3791/60913

  19. Ou, Q., Z. Jacobson, R. R. Abouleisa, X. L. Tang, S. M. Hindi, A. Kumar, K. N. Ivey, G. Giridharan, A. El-Baz, K. Brittian, et al. Physiological biomimetic culture system for pig and human heart slices. Circ. Res. 125(6):628–642, 2019.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Perbellini, F., S. A. Watson, M. Scigliano, S. Alayoubi, S. Tkach, I. Bardi, N. Quaife, C. Kane, N. P. Dufton, A. Simon, et al. Investigation of cardiac fibroblasts using myocardial slices. Circ. Res. 114(1):77–89, 2018.

    CAS  Google Scholar 

  21. Pinto, A. R., A. Ilinykh, M. J. Ivey, J. T. Kuwabara, M. L. D’antoni, R. Debuque, A. Chandran, L. Wang, K. Arora, N. A. Rosenthal, et al. Revisiting cardiac cellular composition. Circ. Res. 118(3):400–409, 2016.

  22. Rawat, W., and Z. Wang. Deep convolutional neural networks for image classification: a comprehensive review. Neu. Comput. 29(9):2352–2449, 2017.

    Article  Google Scholar 

  23. Robertson, C., D. D. Tran, and S. C. George. Concise review: Maturation phases of human pluripotent stem cell-derived cardiomyocytes. Stem Cells 31(5):829–837, 2013.

    Article  CAS  PubMed  Google Scholar 

  24. Stemmler, H. J., M. Schmitt, A. Willems, H. Bernhard, N. Harbeck, and V. Heinemann. Ratio of trastuzumab levels in serum and cerebrospinal fluid is altered in her2-positive breast cancer patients with brain metastases and impairment of blood-brain barrier. Anti-Cancer Drugs 18(1):23–28, 2007.

    Article  CAS  PubMed  Google Scholar 

  25. Sze, V., Y. H. Chen, T. J. Yang, and J. S. Emer. Efficient processing of deep neural networks: a tutorial and survey. Proc. IEEE 105(12):2295–2329, 2017.

    Article  Google Scholar 

  26. Takasaki, S., Y. Kawasaki, M. Kikuchi, M. Tanaka, M. Suzuka, A. Noda, Y. Sato, S. Yamashita, K. Mitsuzuka, H. Saito, et al. Relationships between sunitinib plasma concentration and clinical outcomes in japanese patients with metastatic renal cell carcinoma. Int. J. Clin. Oncol. 23(5):936–943, 2018.

    Article  CAS  PubMed  Google Scholar 

  27. Wang, H., R. P. Sheehan, A. C. Palmer, R. A. Everley, S. A. Boswell, N. Ron-Harel, A. E. Ringel, K. M. Holton, C. A. Jacobson, A. R. Erickson, et al. Adaptation of human ipsc-derived cardiomyocytes to tyrosine kinase inhibitors reduces acute cardiotoxicity via metabolic reprogramming. Cell Syst. 8(5):412–426, 2019.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Watson, S. A., J. Duff, I. Bardi, M. Zabielska, S. S. Atanur, R. J. Jabbour, A. Simon, A. Tomas, R. T. Smolenski, S. E. Harding, et al. Biomimetic electromechanical stimulation to maintain adult myocardial slices in vitro. Nat. Commun. 10(1):1–15, 2019.

    Article  CAS  Google Scholar 

  29. Watson, S. A., M. Scigliano, I. Bardi, R. Ascione, C. M. Terracciano, and F. Perbellini. Preparation of viable adult ventricular myocardial slices from large and small mammals. Nat. Protoc. 12(12):2623–2639, 2017.

  30. Zhao, L., and B. Zhang. Doxorubicin induces cardiotoxicity through upregulation of death receptors mediated apoptosis in cardiomyocytes. Sci. Rep. 7(1):1–11, 2017.

    Article  Google Scholar 

Download references

Author Contribution

HA: designed the algorithm and performed the CNN validation and testing. FK and KH: designed the algorithm and the methods of analysis. HA and FK: provided writting the initial manuscript draft. JMM, MMM, and QO: performed heart slice culture, staining and imaging of the slides. AE and TMAM: conceived the idea and provided funding. All authors have read and commented on the manuscript.

Funding

TMAM is supported by NIH Grants R01HL147921 and P30GM127607 and American Heart Association Grant 16SDG29950012.

Data Availability

No high throughput sequencing data are generated in this work. All algorithms and calculations are described within the manuscript.

Conflict of interest

Authors HA, FK, KH, JMM, MMM, QO, and AE declare that they have no conflict of interest. TMAM, holds equities in Tenaya Therapeutics.

Ethics Approval

All institutional and national guidelines for the care and use of laboratory animals were followed and approved by the University of Louisville Institutional Animal Care and Use Committee.

Author information

Authors and Affiliations

  1. BioImaging Laboratory, Department of Bioengineering, University of Louisville, Louisville, KY, USA

    Hisham Abdeltawab, Fahmi Khalifa, Kamal Hammouda & Ayman El-Baz

  2. Division of Cardiovascular Medicine, Department of Medicine, University of Louisville, Louisville, KY, USA

    Jessica M. Miller, Moustafa M. Meki, Qinghui Ou & Tamer M. A. Mohamed

Authors
  1. Hisham Abdeltawab
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fahmi Khalifa
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kamal Hammouda
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jessica M. Miller
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Moustafa M. Meki
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Qinghui Ou
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ayman El-Baz
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Tamer M. A. Mohamed
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Ayman El-Baz or Tamer M. A. Mohamed.

Additional information

Associate Editor Igor Efimov oversaw the review of this article.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abdeltawab, H., Khalifa, F., Hammouda, K. et al. Artificial Intelligence Based Framework to Quantify the Cardiomyocyte Structural Integrity in Heart Slices. Cardiovasc Eng Tech 13, 170–180 (2022). https://doi.org/10.1007/s13239-021-00571-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13239-021-00571-6

Keywords

Search

Navigation