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Non-invasive monitoring of blood oxygenation in human placentas via concurrent diffuse optical spectroscopy and ultrasound imaging

Abstract

Direct assessment of blood oxygenation in the human placenta can provide information about placental function. However, the monitoring of placental oxygenation involves invasive sampling or imaging techniques that are poorly suited for bedside use. Here we show that placental oxygen haemodynamics can be non-invasively probed in real time and up to 4.2 cm below the body surface via concurrent frequency-domain diffuse optical spectroscopy and ultrasound imaging. We developed a multimodal instrument to facilitate the assessment of the properties of the anterior placenta by leveraging image-reconstruction algorithms that integrate ultrasound information about the morphology of tissue layers with optical information on haemodynamics. In a pilot investigation involving placentas with normal function (15 women) or abnormal function (9 women) from pregnancies in the third trimester, we found no significant differences in baseline haemoglobin properties, but statistically significant differences in the haemodynamic responses to maternal hyperoxia. Our findings suggest that the non-invasive monitoring of placental oxygenation may aid the early detection of placenta-related adverse pregnancy outcomes and maternal vascular malperfusion.

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Fig. 1: Integrated FD-DOS/US placenta instrumentation and three-layer modelling.
Fig. 2: Three-layer model reconstruction algorithm and phantom-validation experiments.
Fig. 3: Placental haemoglobin properties during stability test measurements and the maternal left-tilt experiment.
Fig. 4: Continuous monitoring of placental haemoglobin properties during maternal hyperoxia.
Fig. 5: Static (baseline) and dynamic (during maternal hyperoxia) placental haemoglobin properties for participants with NPO or APO.
Fig. 6: Static (baseline) and dynamic (during maternal hyperoxia) placental haemoglobin properties for participants with NPP or MVM.

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Data availability

The main data supporting the results in this study are available within the paper and its supplementary information. All optical data generated in this study, including source data and the data used to make the figures, are available from figshare with identifiers at https://doi.org/10.6084/m9.figshare.19451882, https://doi.org/10.6084/m9.figshare.19451879 and https://doi.org/10.6084/m9.figshare.19451876. The raw clinical and ultrasound data are available from the corresponding author, subject to approval from the Institutional Review Board of the University of Pennsylvania.

Code availability

The custom code employed for processing the optical data and for performing the statistical analysis are available from figshare with identifiers at https://doi.org/10.6084/m9.figshare.19451882, https://doi.org/10.6084/m9.figshare.19451879 and https://doi.org/10.6084/m9.figshare.19451876. The LabVIEW code and simulation code are also available from the corresponding author on request.

References

  1. Burton, G. J., Fowden, A. L. & Thornburg, K. L. Placental origins of chronic disease. Physiol. Rev. 96, 1509–1565 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Thornburg, K. L., O’Tierney, P. F. & Louey, S. Review: the placenta is a programming agent for cardiovascular disease. Placenta 31, S54–S59 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Hodyl, N. A. et al. Child neurodevelopmental outcomes following preterm and term birth: what can the placenta tell us? Placenta 57, 79–86 (2017).

    Article  CAS  PubMed  Google Scholar 

  4. AIUM-ACR-ACOG-SMFM-SRU practice parameter for the performance of standard diagnostic obstetric ultrasound examinations. J. Ultrasound Med. 37, E13–E24 (2018).

  5. Turco, M. Y. et al. Trophoblast organoids as a model for maternal–fetal interactions during human placentation. Nature 564, 263–281 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Hemberger, M., Hanna, C. W. & Dean, W. Mechanisms of early placental development in mouse and humans. Nat. Rev. Genet. 21, 27–43 (2020).

    Article  CAS  PubMed  Google Scholar 

  7. Carter, A. M. Animal models of human placentation – a review. Placenta 28, S41–S47 (2007).

    Article  PubMed  Google Scholar 

  8. Schmidt, A., Morales-Prieto, D. M., Pastuschek, J., Fröhlich, K. & Markert, U. R. Only humans have human placentas: molecular differences between mice and humans. J. Reprod. Immunol. 108, 65–71 (2015).

    Article  CAS  PubMed  Google Scholar 

  9. Nye, G. A. et al. Human placental oxygenation in late gestation: experimental and theoretical approaches. J. Physiol. 596, 5523–5534 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Horsman, M. R., Mortensen, L. S., Petersen, J. B., Busk, M. & Overgaard, J. Imaging hypoxia to improve radiotherapy outcome. Nat. Rev. Clin. Oncol. 9, 674–687 (2012).

    Article  CAS  PubMed  Google Scholar 

  11. You, W. et al. Hemodynamic responses of the placenta and brain to maternal hyperoxia in fetuses with congenital heart disease by using blood oxygen-level dependent MRI. Radiology 294, 141–148 (2020).

    Article  PubMed  Google Scholar 

  12. Logothetis, N. K. What we can do and what we cannot do with fMRI. Nature 453, 869–878 (2008).

    Article  CAS  PubMed  Google Scholar 

  13. Durduran, T., Choe, R., Yodh, A. G. & Baker, W. B. Diffuse optics for tissue monitoring and tomography. Rep. Prog. Phys. 73, 076701 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Yodh, A. G. & Boas, D. A. in Biomedical Photonics Handbook: Biomedical Diagnostics (ed Vo-Dinh, Tuan) Ch. 21 (2014).

  15. Boas, D. A., O’Leary, M. A., Chance, B. & Yodh, A. G. Scattering of diffuse photon density waves by spherical inhomogeneities within turbid media: analytic solution and applications. Proc. Natl Acad. Sci. USA 91, 4887–4891 (1994).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Waterhouse, D. J., Fitzpatrick, C. R. M., Pogue, B. W., O’Connor, J. P. B. & Bohndiek, S. E. A roadmap for the clinical implementation of optical-imaging biomarkers. Nat. Biomed. Eng. 3, 339–353 (2019).

    Article  CAS  PubMed  Google Scholar 

  17. Baker, W. B. et al. Continuous non-invasive optical monitoring of cerebral blood flow and oxidative metabolism after acute brain injury. J. Cereb. Blood Flow Metab. 39, 1469–1485 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Choe, R. et al. Transabdominal near infrared oximetry of hypoxic stress in fetal sheep brain in utero. Proc. Natl Acad. Sci. USA 100, 12950–12954 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Tromberg, B. J. et al. Predicting responses to neoadjuvant chemotherapy in breast cancer: ACRIN 6691 trial of diffuse optical spectroscopic imaging. Cancer Res. 76, 5933–5944 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Boas, D. A., Elwell, C. E., Ferrari, M. & Taga, G. Twenty years of functional near-infrared spectroscopy: introduction for the special issue. Neuroimage 85, 1–5 (2014).

    Article  PubMed  Google Scholar 

  21. Yun, S. H. & Kwok, S. J. J. Light in diagnosis, therapy and surgery. Nat. Biomed. Eng. 1, 8 (2017).

    Article  CAS  Google Scholar 

  22. Zhu, Q. et al. Breast cancer: assessing response to neoadjuvant chemotherapy by using US-guided near-infrared tomography. Radiology 266, 433–442 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Eggebrecht, A. T. et al. Mapping distributed brain function and networks with diffuse optical tomography. Nat. Photonics 8, 448–454 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Konecky, S. D. et al. Imaging complex structures with diffuse light. Opt. Express 16, 5048–5060 (2008).

    Article  PubMed  Google Scholar 

  25. Ntziachristos, V. Going deeper than microscopy: the optical imaging frontier in biology. Nat. Methods 7, 603–614 (2010).

    Article  CAS  PubMed  Google Scholar 

  26. Kakogawa, J., Sumimoto, K., Kawamura, T., Minoura, S. & Kanayama, N. Noninvasive monitoring of placental oxygenation by near-infrared spectroscopy. Am. J. Perinatol. 27, 463–468 (2010).

    Article  PubMed  Google Scholar 

  27. Hasegawa, J. et al. Evaluation of placental function using near infrared spectroscopy during fetal growth restriction. J. Perinat. Med. 38, 29–32 (2010).

    Article  PubMed  Google Scholar 

  28. Kawamura, T. et al. Measurement of placental oxygenation by transabdominal near-infrared spectroscopy. Am. J. Perinatol. 24, 161–166 (2007).

    Article  PubMed  Google Scholar 

  29. Scholkmann, F. et al. A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology. NeuroImage 85, 6–27 (2014).

    Article  PubMed  Google Scholar 

  30. Boas, D. A., Pitris, C. & Ramanujam, N. (eds) Handbook of biomedical optics (CRC Press, 2016). https://doi.org/10.1201/b10951

  31. Fantini, S. & Sassaroli, A. in Handbook of Optical Biomedical Diagnostics 2nd edn (ed Valery V. Tuchin) Ch. 7. (SPIE Press, 2016). https://doi.org/10.1117/3.2219603.ch7

  32. Choi, J. et al. Noninvasive determination of the optical properties of adult brain: near-infrared spectroscopy approach. J. Biomed. Opt. 9, 221–229 (2004).

    Article  PubMed  Google Scholar 

  33. Liebert, A. et al. Assessment of inflow and washout of indocyanine green in the adult human brain by monitoring of diffuse reflectance at large source-detector separation. J. Biomed. Opt. 16, 046011 (2011).

    Article  PubMed  CAS  Google Scholar 

  34. Pifferi, A. et al. New frontiers in time-domain diffuse optics, a review. J. Biomed. Opt. 21, 091310 (2016).

    Article  PubMed  Google Scholar 

  35. Wright, E. et al. Maternal vascular malperfusion and adverse perinatal outcomes in low-risk nulliparous women. Obstet. Gynecol. 130, 1112–1120 (2017).

    Article  PubMed  Google Scholar 

  36. Ernst, L. M. Maternal vascular malperfusion of the placental bed. APMIS 126, 551–560 (2018).

    Article  PubMed  Google Scholar 

  37. Hallacoglu, B., Sassaroli, A. & Fantini, S. Optical characterization of two-layered turbid media for non-invasive, absolute oximetry in cerebral and extracerebral tissue. PLoS ONE 8, E64095 (2013).

    Article  Google Scholar 

  38. Liemert, A. & Kienle, A. Light diffusion in N-layered turbid media: frequency and time domains. J. Biomed. Opt. 15, 025002 (2010).

    Article  PubMed  Google Scholar 

  39. Ripoll, J. et al. Recovery of optical parameters in multiple-layered diffusive media: theory and experiments. J. Opt. Soc. Am. A 18, 821–830 (2001).

    Article  CAS  Google Scholar 

  40. Corlu, A. et al. Diffuse optical tomography with spectral constraints and wavelength optimization. Appl. Opt. 44, 2082–2093 (2005).

    Article  PubMed  Google Scholar 

  41. Pogue, B. W. & Patterson, M. S. Review of tissue simulating phantoms for optical spectroscopy, imaging and dosimetry. J. Biomed. Opt. 11, 041102 (2006).

    Article  PubMed  Google Scholar 

  42. Schweiger, M. & Arridge, S. The Toast++ software suite for forward and inverse modeling in optical tomography. J. Biomed. Opt. 19, 040801 (2014).

    Article  PubMed  Google Scholar 

  43. Lee, S. W. Y., Khaw, K. S., Kee, W. D. N., Leung, T. Y. & Critchley, L. A. H. Haemodynamic effects from aortocaval compression at different angles of lateral tilt in non-labouring term pregnant women. Br. J. Anaesth. 109, 950–956 (2012).

    Article  CAS  PubMed  Google Scholar 

  44. O’Gorman, N., Tampakoudis, G., Wright, A., Wright, D. & Nicolaides, K. H. Uterine artery pulsatility index at 12, 22, 32 and 36 weeks’ gestation in screening for pre-eclampsia. Ultrasound Obstet. Gynecol. 47, 565–572 (2016).

    Article  PubMed  Google Scholar 

  45. Nguyen, T. et al. Non-invasive transabdominal measurement of placental oxygenation: a step toward continuous monitoring. Biomed. Opt. Express 12, 4119–4130 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  46. American College of Obstetricians and Gynecologists. Management of intrapartum fetal heart rate tracings. Obstet. Gynecol. 116, 1232–1240 (2010).

  47. Luo, J. et al. In vivo quantification of placental insufficiency by BOLD MRI: a human study. Sci. Rep. 7, 3713 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Catov, J. M. et al. Neonatal outcomes following preterm birth classified according to placental features. Am. J. Obstet. Gynecol. 216, 411.e1–411.e14 (2017).

    Article  Google Scholar 

  49. Liemert, A. Light diffusion in N-layered turbid media: steady-state domain. J. Biomed. Opt. 15, 025003 (2010).

    Article  PubMed  Google Scholar 

  50. Haskell, R. C. et al. Boundary conditions for the diffusion equation in radiative transfer. J. Opt. Soc. Am. A 11, 2727–2741 (1994).

    Article  CAS  Google Scholar 

  51. Jacques, S. L. Optical properties of biological tissues: a review. Phys. Med. Biol. 58, R37–R61 (2013).

    Article  PubMed  Google Scholar 

  52. Hansen, P. C. in Computational Inverse Problems in Electrocardiology Vol. 4 (ed P. Johnston, Advances in Computational Bioengineering) 119–142 (WIT Press, Southampton, 2000).

  53. Ugray, Z. et al. Scatter search and local NLP solvers: a multistart framework for global optimization. INFORMS J. Comput. 19, 328–340 (2007).

    Article  Google Scholar 

  54. Gestational hypertension and preeclampsia: ACOG practice bulletin, number 222. Obstet. Gynecol. 135, e237–e260 (2020).

  55. Fenton, T. R. & Kim, J. H. A systematic review and meta-analysis to revise the Fenton growth chart for preterm infants. BMC Pediatr. 13, 59 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Khong, T. Y. et al. Sampling and definitions of placental lesions: Amsterdam Placental Workshop Group Consensus Statement. Arch. Pathol. Lab. Med. 140, 698–713 (2016).

  57. Taroni, P. et al. Breast tissue composition and its dependence on demographic risk factors for breast cancer: non-invasive assessment by time domain diffuse optical spectroscopy. PLoS ONE 10, e0128941 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Henry, B. et al. Hybrid diffuse optical techniques for continuous hemodynamic measurement in gastrocnemius during plantar flexion exercise. J. Biomed. Opt. 20, 125006 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Khare, S. M. et al. Evaluation of the human placenta optical scattering properties using continuous wave and frequency-domain diffuse reflectance spectroscopy. J. Biomed. Opt. 25, 116001 (2020).

    Article  CAS  PubMed Central  Google Scholar 

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Acknowledgements

The work was supported by NIH U01HD087180. J.M.C. was partially supported by NIH P41EB015893. T.K. was partially supported by NIH F31HD085731 and NIH T32HL007915. W.B. was partially supported by R01NS113945. A.G.Y. acknowledges partial support from NIH R01NS060653 and NIH P41EB015893. We thank D. Licht, B. White, J. Strauss and Y. H. Ong for useful discussions, advice and support, as well as the clinic research coordinators of the Maternal and Child Health Research Center at Perelman School of Medicine, University of Pennsylvania.

Author information

Authors and Affiliations

Authors

Contributions

L.W., A.G.Y. and N.S. designed the study. L.W. and T.K. developed the instrument with assistance from W.B.B., K.A., L.H., D.R.B. and V.K. L.W. and J.M.C. developed the three-layer reconstruction algorithm and conducted the computer simulations. L.W. and T.K. performed phantom experiments with help from W.B.B. and L.H. K.A. designed the optical probe with input from L.W. and W.B.B. L.W. collected and analysed the optical data. S.P. and N.S. advised on human participant data interpretation. N.S. collected and analysed the ultrasound data. R.L.L. performed placental histopathologic analysis. L.W., A.G.Y. and N.S. wrote the paper with input from all authors.

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Correspondence to Lin Wang.

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Nature Biomedical Engineering thanks Carolyn Bayer, Christopher Contag and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1

Detailed schematic of the custom heterodyne FD-DOS instrument.

Supplementary information

Reporting Summary

Supplementary dataset 1

Optically measured placental data for the 24 participants.

Supplementary dataset 2

Clinically monitored variables for the 24 participants.

Supplementary tables

Supplementary Tables 1–6.

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Wang, L., Cochran, J.M., Ko, T. et al. Non-invasive monitoring of blood oxygenation in human placentas via concurrent diffuse optical spectroscopy and ultrasound imaging. Nat. Biomed. Eng 6, 1017–1030 (2022). https://doi.org/10.1038/s41551-022-00913-2

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