Detection of collagens by multispectral optoacoustic tomography as an imaging biomarker for Duchenne muscular dystrophy

Abstract

Biomarkers for monitoring of disease progression and response to therapy are lacking for muscle diseases such as Duchenne muscular dystrophy. Noninvasive in vivo molecular imaging with multispectral optoacoustic tomography (MSOT) uses pulsed laser light to induce acoustic pressure waves, enabling the visualization of endogenous chromophores. Here we describe an application of MSOT, in which illumination in the near- and extended near-infrared ranges from 680–1,100 nm enables the visualization and quantification of collagen content. We first demonstrated the feasibility of this approach to noninvasive quantification of tissue fibrosis in longitudinal studies in a large-animal Duchenne muscular dystrophy model in pigs, and then applied this approach to pediatric patients. MSOT-derived collagen content measurements in skeletal muscle were highly correlated to the functional status of the patients and provided additional information on molecular features as compared to magnetic resonance imaging. This study highlights the potential of MSOT imaging as a noninvasive, age-independent biomarker for the implementation and monitoring of newly developed therapies in muscular diseases.

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Fig. 1: exNIR MSOT can detect collagen.
Fig. 2: In vivo 2D MSOT imaging of newborn piglets.
Fig. 3: In vivo 2D MSOT imaging of healthy volunteers and patients with DMD.
Fig. 4: In vivo 3D MSOT imaging of healthy volunteers and patients with DMD.
Fig. 5: Correlation of MSOT imaging and clinical standard assessments.
Fig. 6: Quantitative visualization by MSOT of early-stage disease progression over time.

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. Restrictions may apply due to patient privacy and the General Data Protection Regulation.

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Acknowledgements

F.K. acknowledges founding from Else Kröner–Fresenius–Stiftung (Else Kröner-Memorial-Stipendium, no. 2018_EKMS.03). A.P.R. received support from the ELAN Fond at the University Hospital of Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg. F.K. and A.P.R. acknowledge support by the Interdisciplinary Center for Clinical Research at the University Hospital of FAU Erlangen-Nürnberg. R.T. and A.M.N. acknowledge funding from the Johannes and Frieda Marohn Foundation. M.J.W. received support from the Graduate School in Advanced Optical Technologies of FAU Erlangen-Nürnberg. M.F.N. acknowledges funding from the Emerging Fields Initiative of FAU Erlangen-Nürnberg. M.J.W and M.F.N. acknowledge founding from the German Research Foundation (nos. FOR2438 and TRR241). E.W. acknowledges funding from the Else Kröner–Fresenius Foundation (nos. 2015_180 and 2018_T20), the Bayerische Forschungsstiftung (no. AZ 802/08) and the German Research Foundation (no. TRR127). M.F.N., M.J.W. and F.K. received funding from the European Union’s Horizon 2020 research and innovation program (grant agreement no. 830965). We thank the Imaging Science Institute (Erlangen, Germany) for providing us with measurement facilities for the 3 T MRI system. The present work was performed in partial fulfillment of the requirements for obtaining the degree ‘Dr med. vet.’ (L.M.F.). We thank the patients and healthy volunteers who provided their time and effort. We gratefully acknowledge our physiotherapists J. Tolks, M. Müller-Allissat and P. Poepperl for excellent assistance and physical testing of the participants. We thank the administrative staff at the Center for Social Pediatrics and the Center for Rare Neuromuscular Diseases within the Center for Rare Disease at University Hospital Erlangen, with special thanks to S. Schuessler for help during patient recruitment; G. Boie and I. Allabauer for performing histological techniques; C. Blechinger for exceptional help during animal husbandry and histological preparations; B. Marty for fruitful discussions about MRI in muscular diseases; G. Poland for language editing; and M. Englbrecht for statistical review of the manuscript.

Author information

R.T. and F.K. conceived the idea of the study. Phantom imaging was performed by A.P.R., A.L.W. and F.K. A.P.R., R.T., M.J.W. and F.K. designed the study and recruited the pediatric participants. R.T., M.J.W. and F.K. were the principal investigators of the pediatric study. Ultrasound imaging was performed by J.J. M.Q. provided device support. The animal model was designed by E.W. and N.K. The animal studies were designed by A.P.R., L.M.F., E.W., M.J.W. and F.K. E.W. was the principal investigator of the animal study. A.P.R., L.M.F., A.L.W. and F.K. performed the imaging studies. Pediatric MSOT imaging was performed by A.P.R. and F.K. Human MRI imaging was performed and analyzed by T.G., A.M.N., R.H., A.P.R. and M.U. Ex vivo tissue analyses were performed by L.M.F., E.K., A.P.R. and F.K. T.F. and F.F. performed mass spectrometry. Data collection was completed and analyzed by A.P.R. and F.K. A.P.R., L.M.F., M.F.N., E.W., T.G., W.R., J.W., M.J.W. and F.K. interpreted the data. A.P.R. and F.K. wrote the first draft of the manuscript. The manuscript was critically reviewed by all authors.

Correspondence to Ferdinand Knieling.

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Competing interests

A.P.R., M.J.W. and F.K. are co-inventors, together with iThera Medical GmbH, Germany on an EU patent application (no. EP 19 163 304.9) relating to a device and a method for analysis of optoacoustic data, an optoacoustic system and a computer program. A.P.R., M.J.W. and F.K. received travel support by iThera Medical GmbH, Germany. F.K. reports lecture fees from Siemens Healthcare GmbH outside the submitted work. All other authors declare no competing interests.

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Peer review information Michael Basson was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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

Extended data

Extended Data Fig. 1 Correlation between transversal and longitudinal MSOT collagenmean/max signals.

Each independent muscle was analyzed for its transversal and longitudinal MSOT collagenmean (a) and collagenmax (b) signal. Correlations between longitudinal and transversal MSOT collagenmean/max signals are given by Spearman correlation coefficient (rs). Two-tailed test. Linear regression lines are in black. P values ≤0.05 were considered statistically significant. n = 316 muscle regions (n = 159 transversal/n = 157 longitudinal independent muscle regions) in n = 20 biologically independent subjects (n = 10 HV/n = 10 DMD patients). Source data

Extended Data Fig. 2 Standard B-mode ultrasound imaging.

Representative examples of transversal and longitudinal B-mode ultrasound imaging of quadriceps femoris muscles in a HV and in a patient with DMD. A representative result for a HV and a DMD from n = 160 independent muscle regions (n = 80 HV/n = 80 DMD) of n = 20 biologically independent subjects (n = 10 HV/n = 10 DMD patients) with similar results is shown. Scale bars, 1 cm.

Extended Data Fig. 3 Quantification of 2D and 3D MSOT collagenmax signals in WT and DMD muscles over time.

Quantification of 2D (a) and 3D (b) MSOT collagenmax signals in WT and DMD piglet muscles over time. WT and DMD MSOT collagenmax signals of independent piglet muscles of all animals were compared with each other at weeks 1, 2, 3, and 4 of age. Each filled circle represents one MSOT signal per independent muscle region (n = 24 WT/n = 20 DMD). Two-tailed independent samples t-tests (with Welch’s correction in cases of unequal variances) was used for statistical analysis. If the assumption of normal distribution was violated, a Mann-Whitney U-test was used. P values ≤ 0.05 were considered statistically significant. Bonferroni-Holm adjustment was used to control type I error, due to four comparisons (week 1 - 4) per parameter (e.g. 2D collagenmean). Confidence intervals (95% CI), effect size (R2), coefficients (t(df)/U) and exact p values are noted in the main text and/or Supplementary Tables. Data are shown as mean ± s.d. n = 44 independent muscle regions (n = 24 WT/n = 20 DMD) in n = 11 biologically independent animals (n = 6 WT/n = 5 DMD piglets) from n = 2 litters are shown. Source data

Extended Data Fig. 4 Quantification of 2D and 3D MSOT collagenmax signals in WT and DMD piglet muscles over time.

2D (a) and 3D (b) MSOT collagenmax signals of independent piglet muscles of surviving animals were compared with each other at weeks 1, 2, 3, and 4 of age. Each filled circle/square represents the mean ± s.d. MSOT signal of independent muscle regions over the course of the experiment (n = 12 WT/n = 8 DMD). 2D MSOT parameters were analyzed by post-hoc Tukey’s HSD following a mixed-effects models due to missing values in week 1 (litter 1). p values ≤ 0.05 were considered statistically significant. 3D MSOT collagen parameters were analyzed by Tukey’s honestly significant difference tests following a two-way (mixed design) ANOVA; Data are shown as mean ± s.d. n = 20 independent muscle regions (n = 12 WT/n = 8 DMD) in n = 5 biologically independent animals (n = 3 WT/n = 2 DMD piglets) from n = 2 litters are shown. Source data

Extended Data Fig. 5 Overview of the mean MSOT collagenmean/max signals per individual piglet over time.

Mean 2D (a, b) and mean 3D (c, d) MSOT collagenmean/max signals per individual piglet over time (weeks 1, 2, 3 and 4 of age). Each filled circle represents the mean ± s.d. MSOT signal of an independent piglet over the course of the experiment (n = 6 WT/n = 5 DMD). n = 11 biologically independent animals (n = 6 WT/n = 5 DMD piglets) from n = 2 litters are shown. Source data

Extended Data Fig. 6 Overview of independent muscle regions in each DMD piglet over time.

2D (a, b) and 3D (c, d) MSOT collagenmean/max signals of each independent muscle region of all surviving DMD piglets over the course of the experiment. Each icon represents one independent muscle over the time period, connected by a colored line (weeks 1, 2, 3, and 4 of age). SR, shoulder right (yellow line); LR, leg right (blue line); SL, shoulder left (purple line); LL, leg left (green line). n = 8 independent muscle regions (n = 4 in DMD-number-2/n = 4 in DMD-number-5) of n = 2 biologically independent animals (n = 2 DMD piglets) from n = 2 litters are shown. Source data

Extended Data Fig. 7 Standardization and positioning of the detector probe.

Examples of detector probe positioning and MSOT scanning. Exact positioning of the MSOT detector was standardized for each anatomical region (Supplementary Table 23) and marked with small labels (e.g. red dots). Scanning of a 3-year-old volunteer with the 2D MSOT detector is presented.

Supplementary information

Supplementary Information

Supplementary Tables 1–23.

Reporting Summary

Supplementary Video

Real-time 2D MSOT imaging in newborn piglets. The video shows a split screen. On the left, live imaging of a piglet is presented. The detector was placed on the thigh (biceps femoris muscle) of the piglet. On the right, simultaneous MSOT imaging is shown. Spectral unmixing for collagen (turquoise) and lipids (yellow) is overlaid on RUCT images. A representative video for MSOT real-time imaging from n = 58 independent muscle regions (n = 34 WT/n = 24 DMD) in n = 17 biologically independent animals (n = 10 WT/n = 7 DMD piglets) from n = 3 litters with similar results is shown.

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Regensburger, A.P., Fonteyne, L.M., Jüngert, J. et al. Detection of collagens by multispectral optoacoustic tomography as an imaging biomarker for Duchenne muscular dystrophy. Nat Med 25, 1905–1915 (2019). https://doi.org/10.1038/s41591-019-0669-y

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