We report a coregistered ultrasound and photoacoustic imaging protocol for the transvaginal imaging of ovarian/adnexal lesions. The protocol may be valuable to other translational photoacoustic imaging studies, especially those using commercial ultrasound arrays for the detection of photoacoustic signals and standard delay-and-sum beamforming algorithms for imaging.
Ovarian cancer remains the deadliest of all the gynecological malignancies due to the lack of reliable screening tools for early detection and diagnosis. Photoacoustic imaging or tomography (PAT) is an emerging imaging modality that can provide the total hemoglobin concentration (relative scale, rHbT) and blood oxygen saturation (%sO2) of ovarian/adnexal lesions, which are important parameters for cancer diagnosis. Combined with coregistered ultrasound (US), PAT has demonstrated great potential for detecting ovarian cancers and for accurately diagnosing ovarian lesions for effective risk assessment and the reduction of unnecessary surgeries of benign lesions. However, PAT imaging protocols in clinical applications, to our knowledge, largely vary among different studies. Here, we report a transvaginal ovarian cancer imaging protocol that can be beneficial to other clinical studies, especially those using commercial ultrasound arrays for the detection of photoacoustic signals and standard delay-and-sum beamforming algorithms for imaging.
Photoacoustic imaging or tomography (PAT) is a hybrid imaging modality that measures the optical absorption distribution at US resolution and depths far beyond the tissue optical diffusion limit (~1 mm). In PAT, a nanosecond laser pulse is used to excite biological tissue, causing a transient temperature rise due to optical absorption. This leads to an initial pressure rise, and the resultant photoacoustic waves are measured by US transducers. Multispectral PAT involves the use of either a tunable laser or multiple lasers operating at different wavelengths to illuminate the tissue, thereby enabling the reconstruction of optical absorption maps at multiple wavelengths. Based on the differential absorption of oxygenated and deoxygenated hemoglobin in the near-infrared (NIR) window, multispectral PAT can compute the distributions of oxygenated and deoxygenated hemoglobin concentrations, the total hemoglobin concentration, and the blood oxygen saturation, which are all functional biomarkers related to tumor angiogenesis and blood oxygenation consumption or tumor metabolism. PAT has demonstrated success in many oncology applications, such as ovarian cancer1,2, breast cancer3,4,5, skin cancer6, thyroid cancer7,8, cervical cancer9, prostate cancer10,11, and colorectal cancer12.
Ovarian cancer is the deadliest of all gynecological malignancies. Only 38% of ovarian cancers are diagnosed at an early (localized or regional) stage, where the 5 year survival rate is 74.2% to 93.1%. Most are diagnosed at a late stage, for which the 5 year survival rate is 30.8% or less13. Current clinical diagnosis methods, including transvaginal ultrasonography (TUS), Doppler US, serum cancer antigen 125 (CA 125), and human epididymis protein 4 (HE4), are shown to lack sensitivity and specificity for early ovarian cancer diagnosis14,15,16. Additionally, a large portion of benign ovarian lesions may be difficult to diagnose accurately with current imaging technologies, which leads to unnecessary surgeries with increased healthcare costs and surgical complications. Thus, additional accurate non-invasive methods for the risk stratification of adnexal masses are needed to optimize the management and outcomes. Clearly, a technique that is sensitive and specific to early-stage ovarian cancer and more accurate in identifying malignant from benign lesions is needed.
Our group has developed a coregistered transvaginal US and PAT system (USPAT) for ovarian cancer diagnosis by combining a clinical US system, a custom-made probe sheath to house the optical fibers for light delivery, and a tunable laser1. The total hemoglobin concentration (relative scale, rHbT) and the blood oxygen saturation (%sO2) derived from the USPAT system have demonstrated great potential for the detection of early-stage ovarian cancers and for accurately diagnosing ovarian lesions for effective risk assessment and the reduction of unnecessary benign lesion surgeries1,2. The current system schematic is shown in Figure 1, and the control block diagram is shown in Figure 2. This strategy has the potential to be integrated into existing TUS protocols for ovarian cancer diagnosis while providing functional parameters (rHbT, %sO2) to improve the sensitivity and specificity of TUS.
Subscription Required. Please recommend JoVE to your librarian.
All the research performed was approved by the Washington University Institutional Review Board.
1. System configuration: Optical illumination (Figure 1)
- Use an Nd:YAG laser pumping a pulsed, tunable (690-890 nm) Ti-sapphire laser at 10 Hz.
- Expand the laser beam by first diverging the beam with a plano-concave lens and then collimating the beam with a plano-convex lens. Use two mirrors to direct the beam onto a beam splitter (described below).
- Split the expanded laser beam into four beams with equal energy by splitting the original beam into two with a polarizing beam splitter and then splitting the two beams with two more second-stage beam splitters.
- Mount four multi-mode optical fibers with fiber chucks.
- Use four plano-convex lenses to focus the four laser beams into the four fibers.
- Due to laser safety considerations, cover all the optical components under a metal box to ensure that the optical path is not exposed.
- Attach the other ends of the four fibers to the transvaginal ultrasound probe, and enclose the probe and the fibers in a protective sheath.
NOTE: The sheath and the acoustic window of the transducer are coated with highly reflective white paint to improve the illumination uniformity. This setup, including the use of four fibers for light delivery, was previously shown to be optimal for transvaginal applications17. See the discussion for more information.
2. System configuration: Ultrasonic detection and scanning scheme
- Use a programmable clinical US system.
NOTE: A programmable system means the raw ultrasound data is accessible, and custom data acquisition protocols and processing algorithms can be programmed.
- Connect an additional monitor to the US system to run the USPAT display software for the real-time visualization of the rHbT, %sO2 maps, and other functional parameters.
- Connect the internal trigger of the laser to the external trigger of the US system.
- Use a time-division multiplexing approach during coregistered mode; specifically, for each wavelength, sequentially acquire five consecutive PAT frames and one coregistered US frame. Average the PAT frames to improve the signal-to-noise ratio. The total data acquisition time for four wavelengths is around 15 s.
3. System calibration
- Set the laser pump energy to a fixed level.
- For each wavelength (750 nm, 780 nm, 800 nm, and 830 nm), check the per pulse energy output at each fiber tip to make sure the calculated energy density at each selected wavelength is at the expected value given in Table 1.
- If energy output is lower than expected, fine-tune the optical alignment by adjusting the mirror and beam splitter angles. This step is not always needed.
- Repeat steps 3.2-3.4 until the energy is satisfactory.
- Record the four fibers' energy output at each wavelength, and enter the values in the USPAT display software.
NOTE: These values are used to calibrate the calculation of the rHbT. The laser energy fluctuates over time, and calibration ensures that the quantitative parameters computed from the multispectral PAT data are as accurate as possible.
4. A sample experimental procedure: Transvaginal USPAT imaging of the human ovary
- Preparation of the USPAT imaging system
- Disinfect the endocavity US probe and the cover sheath with the standard ultrasound probe cleaning protocol at the institution.
- Turn on the clinical US system, start the US system software, and select the correct US transducer.
- Calibrate the laser system as in step 3.
- Enter the total pulse energy for each wavelength into the USPAT display software.
- Assemble the USPAT probe by enclosing the fibers and the probe inside the probe sheath.
- Preparation of the patient
- Follow the institution-specific protocol to obtain informed consent and prepare the patient.
- Locate the target ovary using pulse-echo US.
NOTE: This step is done by the study physician, who is free to adjust the imaging parameters on the clinical US machine, such as the depth, the dynamic range, and the TGC.
- Select the desired depth in the USPAT control software.
- Click Scan in the control software to start the coregistered USPAT B-mode data acquisition. Watch the USPAT image display software to review the coregistered US and PAT B-mode images and reconstructed functional maps in real time.
- Repeat steps 4.3.1-4.3.3 to acquire more images and (if necessary) image the second lesion.
- Locate the target ovary using pulse-echo US.
Subscription Required. Please recommend JoVE to your librarian.
Here, we show examples of malignant and normal ovarian lesions imaged by USPAT. Figure 3 shows a 50 year old premenopausal woman with bilateral multicystic adnexal masses revealed by contrast-enhanced CT. Figure 3A shows the US image of the left adnexa with the ROI marking the suspicious solid nodule inside the cystic lesion. Figure 3B shows the PAT rHbT map superimposed onto the US and shown in red. The rHbT showed extensive diffused vascular distribution in the depth range of 1 cm to 5 cm and the level was high at 17.1 (a.u.). Figure 3C shows the %sO2 distribution superimposed onto the US, and the level was low at a mean value of 46.4%. The histograms of rHbT and %sO2 in the ROI are shown in the right corner of the rHbT and %sO2 maps. Surgical pathology revealed well-differentiated endometrioid adenocarcinoma of both the right and left ovaries.
Figure 4 shows a 46 year old woman with bilateral cystic lesions. Figure 4A shows the US image of the right ovary with a simple cyst measuring 4.2 cm in maximum diameter. Figure 4B shows the PAT rHbT map superimposed onto the coregistered US showing scattering signals on the left side of the lesion with a low average level of 4.8 (a.u). Figure 4C shows the %sO2 map, which revealed a higher %sO2 content of 67.5%. The surgical pathology revealed a normal right ovary with follicular cysts.
Based on the pilot data, malignant ovarian lesions revealed 1.9 times higher rHbT and 9% lower %sO2 on average as compared with benign lesions1. These two representative examples highlight the importance of the functional parameters provided by PAT in the diagnosis of US-detected lesions.
|Wavelengths||750 nm||780 nm||800 nm||830 nm|
|Fiber 1||4.79 mJ/cm2||6.16 mJ/cm2||6.59 mJ/cm2||6.33 mJ/cm2|
|Fiber 2||4.62 mJ/cm2||5.39 mJ/cm2||5.99 mJ/cm2||6.50 mJ/cm2|
|Fiber 3||4.79 mJ/cm2||6.07 mJ/cm2||6.76 mJ/cm2||6.84 mJ/cm2|
|Fiber 4||4.70 mJ/cm2||6.07 mJ/cm2||6.67 mJ/cm2||6.50 mJ/cm2|
|Total||18.90 mJ/cm2||23.69 mJ/cm2||26.01 mJ/cm2||26.17 mJ/cm2|
|MPE (ANSI)||25.2 mJ/cm2||28.9 mJ/cm2||31.7 mJ/cm2||36.4 mJ/cm2|
Table 1: Representative laser energy density measurements in units of mJ/cm2 coupled to the four fiber tips for four wavelengths along with their corresponding MPE values.
Figure 1: The coregistered US and PAT system and probe. The US system is extended with another monitor for the USPAT display software, and it receives laser triggers to synchronize the US acquisition. The laser beam is expanded by a plano-convex lens (L1), collimated by a plano-concave lens (L2), split into four beams with two stages of beam splitters (BS), and coupled into multi-mode fibers (MMF) with four plano-convex lenses (L3-6) and fiber couplers (FC1-4). The fibers are attached to the endocavity US probe through a custom probe sheath. Mirrors (M) are used to redirect light in the confined space when necessary. The control computer is not shown. Please click here to view a larger version of this figure.
Figure 2: Block diagram of the USPAT control software. The control software automates the imaging process by changing the laser wavelength, sending data acquisition commands to the clinical US system, and signaling the display software to process and visualize the data. The clinical US system receives triggers from the laser directly to synchronize the laser excitation with the US detection. The display software reads the RF data from the file system. Please click here to view a larger version of this figure.
Figure 3: A 50 year old premenopausal woman with bilateral multicystic adnexal masses revealed by contrast-enhanced CT. (A) US image of the left adnexa with the ROI marking the suspicious solid nodule inside the cystic lesion. (B) The PAT rHbT map superimposed onto the US and shown in red. The rHbT showed extensive diffused vascular distribution in the depth range of 1 cm to 5 cm, and the level was high at 17.1 (a.u.). (C) The %sO2 distribution superimposed onto the US. The level was low at a mean value of 46.4%. Surgical pathology revealed well-differentiated endometrioid adenocarcinoma of both the right and left ovaries. The depth was marked on the right side of the B-scan images. Please click here to view a larger version of this figure.
Figure 4: A 46 year old woman with bilateral cystic lesions. (A) US of the right ovary with a simple cyst measuring 4.2 cm in maximum diameter. (B) The PAT rHbT map superimposed onto the coregistered US showing scattering signals on the left side of the lesion with a low average level of 4.8 (a.u). (C) The %sO2 map revealed a higher %sO2 content of 67.5%. The surgical pathology revealed a normal right ovary with follicular cysts. The depth was marked on the right side of the B-scan images. Please click here to view a larger version of this figure.
Supplementary File 1: Probe sheath. Please click here to download this File.
Subscription Required. Please recommend JoVE to your librarian.
The number of fibers used is based on two factors: light illumination uniformity and system complexity. It is critical to have a uniform light illumination pattern at the skin surface to avoid hot spots. It is also important to keep the system simple and robust with a minimal number of fibers. The use of four separate fibers has previously been shown to be optimal for creating uniform illumination at depths of several millimeters and beyond. Additionally, the light coupling to four optical fibers is relatively simple and robust, as needed for patient studies. We have previously shown that the use of four 1 mm core multi-mode optical fibers, with the fiber tips approximately 10 mm away from the tissue, housed in a highly reflective probe sheath (refer to Supplementary File 1 for the design) are optimal for transvaginal photoacoustic imaging17.
USPAT display software
The clinical US system we use can be programmed for the real-time display of single-wavelength PAT21. However, our method requires custom post processing of multispectral PAT data to compute functional parameters, so we chose to implement our own USPAT display software in C++ to compute and visualize functional maps and parameters. US and PAT B-mode images are computed from the RF data using standard delay-and-sum beamforming, log compression, and dynamic range and are then interpolated into a fan shape. The rHbT and %sO2 maps computed from the multispectral PAT data (see "Computation of the rHbT and %sO2" later in the discussion) are displayed on the coregistered image or, optionally, in a user-defined region of interest (ROI). The mean and maximum of the %sO2 and rHbT are displayed on the screen for reference. During imaging, the display software is used in server mode to listen for remote procedure calls (RPCs) over TCP/IP from the USPAT control software for online processing and real-time visualization. It can also be used for offline processing and visualization.
Image processing algorithms are best implemented on specialized graphics hardware, such as the GPU, but in this study, we were able to achieve satisfactory performance with an optimized CPU implementation. The biggest performance gains came from substituting spatial domain algorithms with their frequency domain equivalents. Taking advantage of the Fast Fourier Transform, we can trivially improve the computational complexity of spatial filtering operations, which often have O(n2 ), time complexity, to O(n logn), which in practice is very close to linear time. Furthermore, for the filtering of raw RF data, we implemented fast discrete convolution with the Overlap-Add method18, which excels at finite impulse response (FIR) filtering.
Computation of the rHbT and %sO2
The computation of the functional parameters derived from the multispectral PAT data is implemented in the USPAT display software, and the functional parameters are automatically computed and visualized in real time. Briefly, we computed the oxy-hemoglobin and deoxy-hemoglobin (relative scale, rHbO and rHbR) concentration at every pixel by solving a non-negative linear least squares problem:
where g represents the measurements at four wavelengths, H represents the matrix of extinction coefficients of oxy-hemoglobin and deoxy-hemoglobin at each wavelength, and f represents the rHbO and rHbR. The rHbT is simply the sum of rHbO and rHbR, and the %sO2 can be computed from the ratio of rHbO:rHbT2. The computation of these parameters is implemented in the USPAT display software and is completely automated. This method with the system is validated through measuring the calibrated blood tube phantoms suspended in intralipid solution2.
USPAT control software
The USPAT control software automates the USPAT data acquisition process by communicating with the laser for wavelength tuning, the clinical US system for data acquisition, and the USPAT display software for data processing and visualization. After selecting the depth in the graphical user interface (GUI), the software sends a command to the US system (over TCP/IP through an ethernet cable) to load the correct sequence file. The Scan button begins the acquisition process of one set of coregistered multispectral PAT and US data. First, the control software sequentially tunes the laser wavelength (over USB) from the lowest to the highest, while the US system acquires the coregistered PAT and US frames. Finally, the control software triggers the USPAT display software (over TCP/IP) to compute the US and PAT B-mode images, reconstruct the functional maps, and display them in real time. At the same time, the laser is tuned back to the lowest wavelength.
Currently, there are several limitations of the USPAT technique. First, photoacoustic imaging can reach only about 5 cm deep with commercial US transducers of 4-10 MHz bandwidth. Thus, for ovaries deeper than 5 cm, or when the target pathologic process is more than 5 cm from the vaginal fornix within a large adnexal mass, PAT is limited. Second, the limited field of view of the US transducer requires scanning a larger lesion at multiple angles to obtain an average that is more representative of the lesion's rHbT and %sO2 contrast. Third, the relative total hemoglobin concentration has been reported because the PAT measurements are the product of the local fluence distribution and optical absorption profile. It is challenging to estimate the optical absorption profile from in vivo measurements. Recently, neural network-based approaches have been explored for the reconstruction of the absolute total hemoglobin concentration19, but these approaches remain to be validated. Finally, the frame rate of multispectral photoacoustic imaging is limited by the speed at which the laser can tune its wavelength. The laser operates at 10 Hz and is mechanically tuned, and the data acquisition for four wavelengths takes about 15 s, so this is the bottleneck in improving the frame rate.
Subscription Required. Please recommend JoVE to your librarian.
The authors have no relevant financial interests in the manuscript and no other potential conflicts of interest to disclose.
This work was supported by the NCI (R01CA151570, R01CA237664). The authors thank the entire GYN oncology group led by Dr. Mathew Powell for helping with recruiting patients, radiologists Drs. Cary Siegel, William Middleton, and Malak Itnai for helping with the US studies, and the pathologist Dr. Ian Hagemann for helping with the pathology interpretation of the data. The authors gratefully acknowledge the efforts of Megan Luther and the GYN study coordinators in coordinating the study schedules, identifying patients for the study, and obtaining informed consent.
|Clinical US imaging system||Alpinion Medical Systems||EC-12R||Fully programmable clinical US system|
|Dielectric mirror||Thorlabs||BB1-E03||Used to reflect light along the optical path|
|Endocavity US transducer||Alpinion Medical Systems||EC3-10||Transvaginal ultrasound probe|
|Laser power meter||Coherent||LabMax TOP||Used to measure laser energy|
|Multi-mode optical fiber||Thorlabs||FP1000ERT||Couple laser light to the endocavity ultrasound probe|
|Non-polarizing beam splitter plate||Thorlabs||BSW11||For splitting laser beam into sensors to measure energy|
|Plano-concave lens||Thorlabs||LC1715||For laser beam expansion|
|Plano-convex lens||Thorlabs||LA1484-B||For laser beam collimation|
|Plano-convex lens||Thorlabs||LA1433-B||Used to focus light into four optical fibers|
|Polarizing beam splitter cube||Thorlabs||PBS252||For splitting laser beam into four beams|
|Protective probe shealth||Custom 3D printed||Hold and protect the four optical fibers at the tip of the ultrasound probe|
|Right angle prism mirror||Thorlabs||MRA25-E03||Used to reflect light along the optical path|
|Tunable laser system||Symphotic TII||LS-2145-LT50PC||Light source for multispectral PAT|
|USPAT control software||Custom developed in C++||Controls acquisition parameters of the ultrasound machine and the laser wavelength|
|USPAT image display software||Custom developed in C++||Displays the US/PAT B-scans and sO2/rHbT maps in real time|
- Nandy, S., et al. Evaluation of ovarian cancer: Initial application of coregistered photoacoustic tomography and US. Radiology. 289 (3), 740-747 (2018).
- Amidi, E., et al. Role of blood oxygenation saturation in ovarian cancer diagnosis using multi-spectral photoacoustic tomography. Journal of Biophotonics. 14 (4), 202000368 (2021).
- Dogan, B. E., et al. Optoacoustic imaging and gray-scale US features of breast cancers: Correlation with molecular subtypes. Radiology. 292 (3), 564-572 (2019).
- Menezes, G. L. G., et al. Downgrading of breast masses suspicious for cancer by using optoacoustic breast imaging. Radiology. 288 (2), 355-365 (2018).
- Neuschler, E. I., et al. A pivotal study of optoacoustic imaging to diagnose benign and malignant breast masses: A new evaluation tool for radiologists. Radiology. 287 (2), 398-412 (2018).
- von Knorring, T., Mogensen, M. Photoacoustic tomography for assessment and quantification of cutaneous and metastatic malignant melanoma - A systematic review. Photodiagnosis and Photodynamic Therapy. 33, 102095 (2021).
- Han, S., Lee, H., Kim, C., Kim, J. Review on multispectral photoacoustic analysis of cancer: Thyroid and breast. Metabolites. 12 (5), 382 (2022).
- Kim, J., et al. Multiparametric photoacoustic analysis of human thyroid cancers in vivo. Cancer Research. 81 (18), 4849-4860 (2021).
- Basij, M., Karpiouk, A., Winer, I., Emelianov, S., Mehrmohammadi, M. Dual-illumination ultrasound/photoacoustic system for cervical cancer imaging. IEEE Photonics Journal. 13 (1), 6900310 (2021).
- Agrawal, S., et al. development, and multi-characterization of an integrated clinical transrectal ultrasound and photoacoustic device for human prostate imaging. Diagnostics. 10 (8), 566 (2020).
- Kothapalli, S. -R., et al. Simultaneous transrectal ultrasound and photoacoustic human prostate imaging. Science Translational Medicine. 11 (507), 2169 (2019).
- Leng, X., et al. Assessing rectal cancer treatment response using coregistered endorectal photoacoustic and US imaging paired with deep learning. Radiology. 299 (2), 349-358 (2021).
- Surveillance, Epidemiology, and End Results Program. Cancer of the Ovary - Cancer Stat Facts. National Cancer Institute. , Available from: https://seer.cancer.gov/statfacts/html/ovary.html (2022).
- Temkin, S. M., et al. Outcomes from ovarian cancer screening in the PLCO trial: Histologic heterogeneity impacts detection, overdiagnosis and survival. European Journal of Cancer. 87, 182-188 (2017).
- Kobayashi, H., et al. A randomized study of screening for ovarian cancer: A multicenter study in Japan. International Journal of Gynecological Cancer. 18 (3), 414-420 (2008).
- Andreotti, R. F., et al. O-RADS US risk stratification and management system: A consensus guideline from the ACR ovarian-adnexal reporting and data system committee. Radiology. 294 (1), 168-185 (2020).
- Salehi, H. S., et al. Design of optimal light delivery system for coregistered transvaginal ultrasound and photoacoustic imaging of ovarian tissue. Photoacoustics. 3 (3), 114-122 (2015).
- Oppenheim, A. V., Schafer, R. W. Digital Signal Processing. , Prentice-Hall. Upper Saddle River, NJ. (1975).
- Zou, Y., Amidi, E., Luo, H., Zhu, Q. Ultrasound-enhanced Unet model for quantitative photoacoustic tomography of ovarian lesions. Photoacoustics. 28, 100420 (2022).
- Prince, J. L., Links, J. M. Medical Imaging Signals and Systems. , Prentice-Hall. Upper Saddle River, NJ. (2006).
- Kim, J., et al. Programmable Real-time Clinical Photoacoustic and Ultrasound Imaging System. Scientific Reports. 6, 35137 (2016).