Open Access
1 November 2009 Quantitative three-dimensional photoacoustic tomography of the finger joints: an in vivo study
Yao Sun, Eric S. Sobel, Huabei Jiang
Author Affiliations +
Abstract
We present for the first time in vivo full three-dimensional (3-D) photoacoustic tomography (PAT) of the distal interphalangeal joint in a human subject. Both absorbed energy density and absorption coefficient images of the joint are quantitatively obtained using our finite-element-based photoacoustic image reconstruction algorithm coupled with the photon diffusion equation. The results show that major anatomical features in the joint along with the side arteries can be imaged with a 1-MHz transducer in a spherical scanning geometry. In addition, the cartilages associated with the joint can be quantitatively differentiated from the phalanx. This in vivo study suggests that the 3-D PAT method described has the potential to be used for early diagnosis of joint diseases such as osteoarthritis and rheumatoid arthritis.

1.

Introduction

Photoacoustic tomography (PAT), also referred as optoacoustic tomography (OAT), is an emerging nonionizing, noninvasive imaging modality, which combines both high optical contrast and high ultrasound resolution in a single modality.1, 2, 3 Thus far, PAT has shown its potential to detect breast cancer, to assess vascular and skin diseases, and to image epilepsy in small animals.4, 5, 6, 7, 8, 9, 10, 11, 12, 13 By combining a light transport model with conventional PAT method,14, 15, 16, 17, 18 the utility of PAT has now been extended significantly to provide quantitative tissue absorption coefficient and physiological/functional information including hemoglobin concentration, blood oxygenation, and water content. These intrinsic tissue properties may be important for accurate diagnostic decision-making.

Diseases related to bones and joints are a major cause of morbidity in the population over 50year old and affect millions of people over the world, early detection of which is infeasible with traditional methods such as x-ray radiography, computed tomography (CT), and ultrasonography. Magnetic resonance imaging (MRI) represents a powerful tool for imaging joint diseases, but it is costly and cannot be used for frequent monitoring of the progressive joint diseases. Diffuse optical tomography (DOT), an emerging all-optical imaging modality, has been studied for joint imaging.19, 20, 21 Significant absorption contrast between diseased and normal joints has been observed in the hand with osteoarthritis22, 23 and rheumatoid arthritis.24, 25 For example, for an osteoarthritic joint, the ratio of its cartilage absorption coefficient to that of the associated bone is increased by 40% relative to the healthy joints.22 Since the same high absorption contrast is available to PAT, we expect that PAT may represent another optical-based modality for joint imaging with improved spatial resolution.

Wang 26 have recently presented high-resolution two-dimensional (2-D) photoacoustic images of the proximal interphalangeal (PIP) and distal interphalangeal (DIP) joints from a cadaver human finger. In vivo joint imaging represents a challenge because unlike the joint from a cadaver finger, an in vivo joint has abundant blood vessels located along the skin that strongly absorb light. The strong absorption from the blood vessels and bones give rise to significantly reduced signal-to-noise ratio (SNR) in an in vivo setting. In addition, both light and acoustic propagation in tissue are 3-D in nature. In particular, the joint structures are highly heterogeneous, which makes a full 3-D volumetric image reconstruction necessary.

Herein, in this study, we present an in vivo full 3-D PAT study of the DIP joint in a human subject using a Ti:Sapphire laser–based photoacoustic system in a spherical scanning geometry. Photoacoustic images containing major features/components in the finger joint as well as the absorption coefficient profiles of these joint structures are successfully achieved.

2.

Methods

The finite-element-based 3-D PAT reconstruction algorithm and its enhancement for extracting quantitative absorption coefficient used in this study have been described in detail previously and validated using considerable phantom experiments.15, 27, 28 (We found that the accuracy for obtaining absorption coefficient from the phantom experiments is typically within 20% relative to the exact values.) Basically, the reconstruction method includes two steps. The first step is to obtain the 3-D images of absorbed optical energy density through the conventional 3-D PAT reconstruction algorithm that is based on finite element solution to the photoacoustic wave equation in the frequency-domain subject to the second-order absorption boundary conditions:27

Eq. 1

2P(r,ω)+k02P(r,ω)=ik0c0βϕ(r)Cp,

Eq. 2

Pn̂=MP,
where P is the pressure wave; k0=ωc0 is the wave number described by the angular frequency, ω and the average speed of acoustic wave in the tissue, c0 ; β is the thermal expansion coefficient; Cp is the specific heat at constant pressure; and ϕ is the absorbed light energy density. M is a differential operator defined as the function of the mean and Gaussian curvatures at a point along the boundary surface.

The reconstruction algorithm assumes a homogeneous acoustic speed c0 , which is an approximation to the possible heterogeneous acoustic media seen in the experiments. Newton method combined with Marquardt and Tikhonov regularizations is used to iteratively update an initial (guess) absorbed optical energy density distribution so that an object function composed of a weighted sum of the squared difference between computed and measured acoustic pressures for all acoustic frequencies can be minimized.

The second step is to recover the optical absorption coefficient using the absorbed optical energy density, ϕ reconstructed in the first step and the following photon diffusion equation as along with the Robin boundary conditions:15

Eq. 3

D(r)[Ψ(r)]μa(r)Ψ(r)=S(r),

Eq. 4

DΨ(r)n̂=αΨ(r),
where Ψ(r) is the photon density, Ψ(r)=ϕ(r)μa(r) , μa(r) is the optical absorption coefficient, D(r) is the diffusion coefficient, D=1[3(μa+μs)] and μs is the reduced scattering coefficients, α is a boundary condition coefficient related to the internal reflection at the boundary, and S(r) is the incident point or distributed source term.

To recover the optical absorption coefficient from the reconstructed absorbed optical energy density ϕ from an initial distribution of μa(r) , the optical fluence Ψ(r) and the absorbed energy density ϕ(c) are iteratively calculated through the photon diffusion equation and ϕ(c)=μa(r)Ψ , respectively. If the error between ϕ and ϕ(c) is not small, then μa(r) is updated by μa(r)=ϕΨ , and the preceding procedure is repeated until a small error between ϕ and ϕ(c) is reached, resulting in a stable quantitative distribution of μa(r) .

3.

System and Experiments

The in vivo finger joint experiment was conducted with our 3-D PAT imaging system, as shown in Fig. 1 . The Ti:Sapphire laser (LOTIS, Minsk, Belarus) generates a pulsed beam with a repetition rate of 10Hz and a pulse width <10ns . The wavelength of the laser is tunable from 600to950nm and was locked at 820nm in this study for deep tissue penetration. The light beam is delivered via an optical fiber to the bottom of the water tank and expanded by a lens and a ground glass before reaching the finger so that the DIP joint can be uniformly illuminated by an area source of light. The laser energy at the DIP joint was controlled around 10mJcm2 , which is far below the safety standard of 22mJcm2 .

Fig. 1

Schematic of the 3-D spherical scanning PAT system for finger joint imaging. L: lens; T: detector/transducer; R1/R2: rotary stages.

064002_1_003906jbo1.jpg

The DIP joint of the left index finger from a female healthy volunteer was photoacoustically examined, and the palmar side of the finger faced up during the examination, allowing the finger joint to be illuminated from the dorsal side of the finger. Our experience indicates that this way of light illumination can give us maximized tissue penetration. To secure the position of the finger, rubber bands were applied to the distal tip and the proximal end of the examined finger.

To detect the acoustic field generated by the pulsed laser, 1-MHz transducer (Valpey Fisher, Hopkinton, Massachusetts) was optimally chosen based on considerable phantom experiments. 28 The transducer has a bandwidth of 80% at 6dB and an aperture size of 6mm . To overcome the directivity limitation and aperture size effect of transducer, we adopted a spherical scanning configuration. Both the transducer and the finger were immersed in the water tank for minimized ultrasound attenuation. As can be seen from Fig. 1, the transducer was attached to the rotary stage R2 whose position was controlled by the rotary stage R1. During the examination, the finger was placed at the center of the two rotary stages. The detected acoustic signals were amplified and filtered by a Pulser/Receiver 5058PR (Panametrics, Waltham, Massachusetts). Labview software was used to control the entire data acquisition procedure.

The collection of acoustic signals along a spherical scanning surface was realized through the combined rotations of rotary stages R1 and R2. (Note that R1 and R2 were attached to the same L-shape arm; see Fig. 1.) As shown in Fig. 2, the examined finger joint was aligned in the direction of y axis, and located at the rotation center, O. In the scanning, the transducer was first rotated by R1 to a position along the circular locus L1 and then rotated by R2 along the circular locus L2 [Fig. 2a]. This process was repeated until the spherical scanning was completed. Since the finger/hand blocked the scanning of the transducer in certain angles, the scanning along L1 and L2 covered only 240deg and 252deg , respectively [Figs. 2b and 2c]. A complete scanning allowed the collection of signals at 387 positions along the spherical surface which took about 40min .

Fig. 2

Schematic of the spherical scanning geometry (a), circular locus L1 (b), and L2 (c).

064002_1_003906jbo2.jpg

4.

Results and Discussion

In this section, we present the in vivo 3-D reconstruction results and make observations based on these results. The 3-D images were reconstructed using a finite element mesh of 41,323 tetrahedral elements and 7519 nodes, which required 120min per iteration, for a total of 10 iterations on a parallel computer with 10 processors. Each of the processors worked at 2.2GHz with 2-GB memory.

A coronal section of the reconstructed 3-D image (absorbed energy density) is shown in Fig. 3a, while a similar section of the DIP joint from a typical human finger by MRI is given in Fig. 3b for comparison. As can be observed from Fig. 3a, the cartilage/joint space is well differentiated from the adjacent distal phalanx (DP) and intermediate phalanx (IP). The recovered absorption coefficient image and the absorption coefficient profile along a transect x=2mm corresponding to the coronal slice shown in Fig. 3a are displayed in Figs. 4a and 4b, respectively. We see that the absorption coefficient values of the phalanxes and cartilage/joint space are quantitatively consistent with that reported in the literature.22, 23 By estimating the full width at half maximum (FWHM) of the absorption coefficient profiles, the recovered thickness of cartilage/joint space was found to be 1.6mm , which is in agreement with the actual size.

Fig. 3

Selected coronal section from the reconstructed 3-D image (absorbed energy density) at z=5mm (a), and MRI (coronal section) from a similar joint (b). DP: distal phalanx; IP: intermediate phalanx; DIP: distal interphalangeal joint.

064002_1_003906jbo3.jpg

Fig. 4

Selected coronal section from the recovered absorption coefficient image at z=5mm (a), and its profile along the cut line x=2mm (b).

064002_1_003906jbo4.jpg

Figure 5a presents a cross section of the reconstructed 3-D image (absorbed energy density). Again, a similar cross section of the DIP joint from a typical human finger by MRI is shown in Fig. 5b for comparison. Comparing both Figs. 5a and 5b, it appears that several joint tissue types are visible including phalanx (PX), lateral artery (LA), median artery (MA), and tendon (TE). The recovered absorption coefficient image and the absorption coefficient profiles along two transects are displayed in Figs. 6a, 6b, 6c . The first transect [line 1 in Fig. 6a] goes through the phalanx and tendon, while the second one [line 2 in Fig. 6a] crosses the tendon and two arteries. The recovered absorption coefficients of the phalanx, tendon, median and lateral arteries were found to be 0.07mm1 , 0.074mm1 , 0.064mm1 , and 0.058mm1 , respectively. Again, these values are generally consistent with that reported in the literature.21, 22 We note that blurs around the two blood vessels are noticeable [Fig. 5a] largely due to the relatively low-frequency (1MHz) transducer used in this study. We believe the resolution can be enhanced with a wideband transducer having higher frequency (e.g., 5to10MHz ), which will make the millimeter- to submillimeter-sized arteries accurately imaged.

Fig. 5

Selected cross section from the reconstructed 3-D image (absorbed energy density) at y=7mm (a), and MRI (cross section) from a similar joint (b). PX: phalanx; MA: median artery; TE: tendon; LA: lateral artery.

064002_1_003906jbo5.jpg

Fig. 6

Selected cross section from the recovered absorption coefficient image at y=7mm (a), and its profile along cut lines 1 (b) and 2 (c), respectively.

064002_1_003906jbo6.jpg

To view the volumetric structures of the tissues around the joint, a series of cross- and coronal-section images are displayed in Figs. 7 and 8 , respectively. As shown in Figs. 7a, 7b, 7c, 7d, 7e, 7f, the phalanx is clearly visible in all the cross-section images from the proximal end (y=2.5mm) to the distal end (y=9mm) . The tendon is differentiated from the phalanx [Figs. 7a, 7e, 7f]. The lateral artery is visible almost in all the cross section images except for that shown in Fig. 7f at the distal end of the finger. The median artery is seen in Figs. 7e and 7f and weakly visible in Fig. 7d. Other joint structures including the phalanges (DP and IP) and the cartilage (CL) are clearly imaged from the coronal section images close to the dorsal side of the finger [Figs. 8a and 8b]. Close to the palmar side of the finger, the tendon and two arteries begin to show up [Fig. 8c], and the two arteries become clearly visible eventually [Fig. 8d]. Negative values are also observed in the reconstructed absorbed energy density images. This is likely due to the homogenous acoustic approximation (constant acoustic speed) to the actual heterogeneous acoustic media of the finger joints and limited signal-to-noise ratio because of the strong light scattering of joint tissues.

Fig. 7

Cross-section images (absorbed energy density) at y=2.5mm (a), y=0mm (b), y=3mm (c), y=5mm (d), y=7mm (e), and y=9mm (f). PX: phalanx; MA: median artery; TE: tendon; LA: lateral artery.

064002_1_003906jbo7.jpg

Fig. 8

Coronal-section images (absorbed energy density) at z=5mm (a), z=3.5mm (b), z=1mm (c), and z=4.5mm (d). DP: distal phalanx; IP: intermediate phalanx; CL: cartilage; PX: phalanx; MA: median artery; TE: tendon; LA: lateral artery.

064002_1_003906jbo8.jpg

In summary, we have presented a 3-D PAT technique that is able to image finger joints in vivo. Although it seems impossible for PAT to provide image quality (in terms of spatial resolution) comparable to MRI for joint or breast imaging, PAT is capable of obtaining absorption coefficient or functional information. In addition, PAT is portable and low in cost. While our current experimental setup is not optimized, it allows us to demonstrate the possibility of 3-D in vivo joint imaging for the first time. The results obtained indicate that major joint structures and their absorption coefficients can be quantitatively reconstructed using our 3-D PAT approach. We plan to improve our imaging system for optimized performance. For example, we will implement an excitation configuration that allows light illumination of the entire finger joint, which would then permit the use of higher frequency transducers for enhanced resolution due to the significantly improved signal-to-noise ratio. We also plan to perform in vivo 3-D PAT studies in human subjects with hand osteoarthritis or rheumatoid arthritis in the near future.

References

1. 

A. A. Oraevsky and A. A. Karabutov, “Optoacoustic tomography,” Biomedical Photonics Handbook, PM125 34/1 –34/34 CRC Press, Boca Raton, FL (2003). Google Scholar

2. 

A. A. Oraevsky, S. L. Jacques, R. O. Esenaliev, and F. K. Tittel, “Laser based optoacoustic imaging in biological tissues,” Proc. SPIE, 2134A 122 –128 (1994). 0277-786X Google Scholar

3. 

R. A. Kruger and P. Liu, “Photoacoustic ultrasound reconstruction tomography,” Med. Phys., 22 (10), 1605 –1609 (1995). https://doi.org/10.1118/1.597429 0094-2405 Google Scholar

4. 

A. A. Oraevsky, A. A. Karabutov, and S. V. Solomatin, “Laser optoacoustic imaging of breast cancer in vivo,” Proc. SPIE, 4256 6 –11 (2001). https://doi.org/10.1117/12.429300 0277-786X Google Scholar

5. 

S. Manohar, A. Kharine, J. C. G. van Hespen, W. Steenbergen, and T. G. van Leeuwen, “Photoacoustic mammography laboratory prototype: imaging of breast tissue phantoms,” Phys. Med. Biol., 50 2543 –2557 (2005). https://doi.org/10.1088/0031-9155/50/11/007 0031-9155 Google Scholar

6. 

R. G. M. Kollkman, J. H. G. M. Klaessens, E. Hondebrink, J. C. W. Hopman, F. F. M. de Mul, W. Steenbergen, J. M. Thijssen, and T. G. V. Leeuwen, “Photoacoustic determination of blood vessel diameter,” Phys. Med. Biol., 49 4745 –4756 (2004). https://doi.org/10.1088/0031-9155/49/20/006 0031-9155 Google Scholar

7. 

R. I. Siphanto, K. K. Thumma, R. G. M. Kolkman, T. G. van Leeuwen, F. F. M. de Mul, J. W. van Neck, L. N. A. van Adrichem, and W. Steenbergen, “Serial noninvasive photoacoustic imaging of neovascularization in tumor angiogenesis,” Opt. Express, 13 89 –95 (2005). https://doi.org/10.1364/OPEX.13.000089 1094-4087 Google Scholar

8. 

S. Yang, D. Xing, Q. Zhou, L. Xiang, and Y. Lao, “Functional imaging of cerebrovascular activities in small animals using high-resolution photoacoustic tomography,” Med. Phys., 34 3294 –3301 (2007). https://doi.org/10.1118/1.2757088 0094-2405 Google Scholar

9. 

X. Wang, Y. Pang, G. Ku, X. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol., 21 803 –806 (2003). https://doi.org/10.1038/nbt839 1087-0156 Google Scholar

10. 

E. Z. Zhang, J. Laufer, and P. Beard, “Three-dimensional photoacoustic imaging of vascular anatomy in small animals using an optical detection system,” Proc. SPIE, 6437 643710 (2007). https://doi.org/10.1117/12.701740 0277-786X Google Scholar

11. 

A. A. Karabutov, E. Savateeva, and A. Oraevsky, “Imaging of layered structures in biological tissues with opto-acoustic front surface transducer,” Proc. SPIE, 3601 284 –295 (1999). https://doi.org/10.1117/12.350011 0277-786X Google Scholar

12. 

J. A. Viator, G. Au, G. Paltauf, S. Jacques, S. Prahl, H. Ren, Z. Chen, and J. Nelson, “Clinical testing of a photoacoustic probe for port wine stain depth determination,” Lasers Surg. Med., 30 141 –148 (2002). https://doi.org/10.1002/lsm.10015 0196-8092 Google Scholar

13. 

Q. Zhang, Z. Liu, P. R. Carney, Z. Yuan, H. Chen, S. N. Roper, and H. Jiang, “Non-invasive imaging of epileptic seizures in vivo using photoacoustic tomography,” Phys. Med. Biol., 53 1921 –1931 (2008). https://doi.org/10.1088/0031-9155/53/7/008 0031-9155 Google Scholar

14. 

J. Ripoll and V. Ntziachristos, “Quantitative point source photoacoustic inversion formulas for scattering and absorbing medium,” Phys. Rev. E, 71 031912 (2005). https://doi.org/10.1103/PhysRevE.71.031912 1063-651X Google Scholar

15. 

Z. Yuan and H. Jiang, “Quantitative photoacoustic tomography: recovery of optical absorption coefficient map of heterogeneous medium,” Appl. Phys. Lett., 88 231101 (2006). https://doi.org/10.1063/1.2209883 0003-6951 Google Scholar

16. 

B. Cox, S. Arridge, K. Kostli, and P. Beard, “2D quantitative photoacoustic image reconstruction of absorption distributions in scattering medium using a simple iterative method,” Appl. Opt., 45 1866 –1875 (2006). https://doi.org/10.1364/AO.45.001866 0003-6935 Google Scholar

17. 

L. Yin, Q. Wang, Q. Zhang, and H. Jiang, “Tomographic imaging of absolute optical absorption coefficient in turbid medium using combing photoacoustic and diffusing light measurements,” Opt. Lett., 32 2556 –2558 (2007). https://doi.org/10.1364/OL.32.002556 0146-9592 Google Scholar

18. 

Z. Yuan, Q. Wang, and H. Jiang, “Reconstruction of optical absorption coefficient maps of heterogeneous media by photoacoustic tomography coupled with diffusion equation based regularized Newton method,” Opt. Express, 15 18076 –18081 (2007). https://doi.org/10.1364/OE.15.018076 1094-4087 Google Scholar

19. 

A. Klose, A. Hielscher, K. Hanson, and J. Beuthan, “Two- and three-dimensional optical tomography of finger joints for diagnostics of rheumatoid arthritis,” Proc. SPIE, 3566 151 –159 (1998). https://doi.org/10.1117/12.334363 0277-786X Google Scholar

20. 

Y. Xu, N. Iftimia, and H. Jiang, “Imaging of in vitro and in vivo bones and joints with continuous-wave diffusion optical tomography,” Opt. Express, 8 447 –451 (2001). https://doi.org/10.1364/OE.8.000447 1094-4087 Google Scholar

21. 

Y. Xu, W. Iftimia, H. Jiang, L. L. Key, and M. B. Bolster, “Three-dimensional diffuse optical tomography of bones and joints,” J. Biomed. Opt., 7 88 –92 (2002). https://doi.org/10.1117/1.1427336 1083-3668 Google Scholar

22. 

Z. Yuan, Q. Zhang, E. Sobel, and H. Jiang, “Three-dimensional diffuse optical tomography of osteoarthritis: initial results in the finger joints,” J. Biomed. Opt., 12 034001-1 –11 (2007). https://doi.org/10.1117/1.2737420 1083-3668 Google Scholar

23. 

Z. Yuan, Q. Zhang, E. S. Sobel, and H. Jiang, “Tomographic x-ray guided three-dimensional diffuse optical tomography of osteoarthritis in the finger joints,” J. Biomed. Opt., 13 044006-1 –10 (2008). https://doi.org/10.1117/1.2965547 1083-3668 Google Scholar

24. 

A. H. Hielscher, A. D. Klose, A. K. Scheel, B. Moa-Anderson, M. Backhaus, U. Netz, and J. Beuthan, “Sagittal laser optical tomography for imaging of rheumatoid finger joints,” Phys. Med. Biol., 49 1147 –1163 (2004). https://doi.org/10.1088/0031-9155/49/7/005 0031-9155 Google Scholar

25. 

A. K. Scheel, M. Backhaus, A. Klose, B. Moa-Anderson, U. Netz, K. Hermann, J. Beauthan, G. Muller, G. Brrmester, and A. Hielscher, “First clinical evaluation of sagittal laser optical tomography for detection of synovitis in arthritic finger joints,” Ann. Rheum. Dis., 64 239 –245 (2005). https://doi.org/10.1136/ard.2004.024224 0003-4967 Google Scholar

26. 

X. Wang, D. L. Chamberland, and D. A. Jamadar, “Noninvasive photoacoustic tomography of human peripheral joints toward diagnosis of inflammatory arthritis,” Opt. Lett., 32 3002 –3004 (2007). https://doi.org/10.1364/OL.32.003002 0146-9592 Google Scholar

27. 

Z. Yuan and H. Jiang, “Three-dimensional finite-element-based photoacoustic tomography: reconstruction algorithm and simulations,” Med. Phys., 34 538 –546 (2007). https://doi.org/10.1118/1.2409234 0094-2405 Google Scholar

28. 

Y. Sun and H. Jiang, “Quantitative three-dimensional photoacoustic tomography of the finger joints: phantom studies in a spherical scanning geometry,” Phys. Med. Biol., 54 5457 –5467 (2009). https://doi.org/10.1088/0031-9155/54/18/007 0031-9155 Google Scholar
©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)
Yao Sun, Eric S. Sobel, and Huabei Jiang "Quantitative three-dimensional photoacoustic tomography of the finger joints: an in vivo study," Journal of Biomedical Optics 14(6), 064002 (1 November 2009). https://doi.org/10.1117/1.3257246
Published: 1 November 2009
Lens.org Logo
CITATIONS
Cited by 44 scholarly publications and 1 patent.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Absorption

In vivo imaging

Acquisition tracking and pointing

Arteries

3D image processing

Acoustics

Photoacoustic tomography

Back to Top