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Abstract
Intraoperative imaging has been studied using conventional devices such as near infrared (NIR) optical probes and gamma probes. However, these devices have limited depth penetration and spatial resolution. In a previous study, we realized a multi-modal endoscopic system. However, charge-coupled device (CCD)-based gamma imaging required long acquisition times and lacked gamma energy information. A silicon photomultiplier (SiPM)-based gamma detector is implemented in a multi-modal laparoscope herein. A gradient index (GRIN) lens and CCD are used to transfer and readout visible and NIR photons. The feasibility of in-vivo sentinel lymph node (SLN) mapping was successfully performed with the proposed system.
© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
Image-guided surgery has been playing an important role in cancer surgery to improve the patient outcome significantly by detecting the tumor and sentinel lymph node (SLN) [1,2]. In particular, near-infrared fluorescence (NIRF) image-guided surgery [3] has been adopted rapidly into clinical practice in last two decades with the development of fluorescent agents such as methylene blue and indocyanine green (ICG) [4,5]. The NIRF image-guided surgery can visualize the tumor margin with high-resolution (∼1 mm) in real-time so as to help surgeon to remove the tumor tissues with precision while minimizing the unnecessary resection of normal tissue surrounding the tumor tissues. In the early 2000s, the NIRF image-guided surgery was first translated into clinical procedure for breast cancer surgery in which the cancer surgery can be performed with open surgery which does not demand miniaturized medical imaging systems [6]. Hence, the early stage of the NIRF imaging systems employed bulky charge-coupled device (CCD) cameras and illumination systems [1].
Recently, minimally invasive surgery which uses the limited size and number of incisions on the patient body, has been widely used for cancer surgery to reduce the patient recovery time significantly as compared to that of traditional open surgery which requires a long recovery time in the hospital [7,8]. The minimal invasive surgery includes an endoscopic surgery for gastric cancers [9], laparoscopic surgery for prostate cancers [10], and robot-assisted laparoscopic cancer surgery using the Da Vinci system [11]. Hence, NIRF imaging systems have been evolved toward minimally invasive surgery. As a result, various endoscopic and laparoscopic NIRF imaging systems have been developed with compact size to fit inside the laparoscopic port diameter of 12 mm [12–14].
NIRF image-guided surgery has transformed the cancer surgery procedure in clinical practice by providing real-time images and good spatial resolution of tumor margins [15,16]. However, tissue depth penetration using NIRF is limited to less than 10 mm because of significant optical scattering and absorption inside the tissues [3,17]. Therefore, tumors or SLNs located at deep tissue region are barely identified thereby increasing the false-positive rate on the detection of tumor tissues which may lead to a recurrence of cancer.
In order to solve the depth penetration issue of NIRF, a novel hybrid imaging system combining ultrasound, photoacoustic, and fluorescence device was proposed [18]. The handheld hybrid imaging system can provide real-time images with good spatial resolution for the detection of SLN. However, it is difficult to realize superficially located target images, and ultrasound probes need to make contact with the tissue for observation. Moreover, the size of the hybrid imaging system is bulky which is not applicable for minimal invasive surgery.
The depth penetration issue can also be solved by using gamma probes [19] or gamma cameras [20,21] which detect high-energy gamma photons emitted from radiopharmaceuticals such as 99mTc-nanocolloid [19]. Therefore, radionuclide surgery has been widely used for intraoperative cancer detection in clinical practice since the early 2000s [22]. Recently, a hybrid intraoperative surgery technique was proposed in which the standalone gamma probe and NIRF imaging system were used separately during robot-assisted laparoscopic cancer surgery [23–26]. The hybrid intraoperative cancer surgery technique could enhance the detection accuracy of SLN during prostate cancer surgery as compared to that of using only NIRF image guided surgery [27,28]. However, the gamma probe and NIRF imaging systems were physically separated thereby resulting in the potential mismatch on the information obtained from the two independent modalities. In order to address this issue, a novel hybrid optical/gamma probe was developed for SLN detection during laparosopic surgery [29]. The NIRF and gamma signals were detected simultaneously using an integrated probe system and the beep signals were generated in proportional to the number of detected NIRF and gamma signals. However, the hybrid optical/gamma probe cannot provide the images of SLN which are crucial for image-guided cancer surgery.
Toward the hybrid intraoperative imaging system combining gamma camera and NIRF devices for SLN mapping, our group has proposed several prototype hybrid laparoscopic imaging systems. A novel multi-modal laparoscopic system, realizing simultaneous annihilation-gamma (511 keV), NIRF, and visible images, has been developed [30]. However, the target radiopharmaceutical is [18F]-FDG; hence, the system cannot be used for SLN mapping using ICG-99mTc-nanocolloid, which emits relatively low-energy gamma photons (140 keV). In previous studies, we developed multi-modal laparoscopic systems to realize gamma, NIRF, and visible images [30–32]. The gamma images were obtained using a combination of a scintillation crystal, optical fiber bundles, and a charge-coupled device (CCD). However, CCD-based gamma imaging required long acquisition times, owing to light loss during transmission through the optical fiber bundle. Image acquisition times of more than 30 s were required to yield sufficiently high contrast-to-noise ratios (CNRs). Moreover, CCD-based gamma imaging is affected by scattering, which deteriorates the CNR. The long gamma acquisition time can be reduced substantially by coupling the scintillation crystal array to the photo-sensor. Furthermore, the gamma energy information can be recorded using a silicon photomultiplier (SiPM), thereby enabling the rejection of scattering events. In this study, we propose a novel intraoperative multi-modal imaging system comprised a SiPM-based gamma detector and NIRF/visible optical systems for image-guided laparoscopic surgery using ICG-99mTc-nanocolloid. The performance of the proposed multi-modal imaging system was evaluated using phantom studies, and the feasibility of in-vivo SLN imaging is discussed.
2. Methods
2.1 Overview of the multi-modal laparoscope system
The proposed visible/NIRF/gamma multi-modal system consists of a laparoscope tube, a beam splitter module, illumination components, and imaging devices, as shown in Fig. 1. When ICG-99mTc-nanocolloid hybrid tracer accumulates in tumors, the tracer emits NIRF and gamma (140 keV) signals, which are collected at the front of the laparoscope tube, along with visible photons from the surgical region. The beam splitter module was used to separate visible and NIRF photons using a dichroic long-pass filter. The illumination components illuminate the imaging object with white light and NIR excitation light simultaneously. The visible/NIRF/gamma multi-modal system acquires individual visible, NIRF, and gamma images to produce the comprehensive image of the lesion. The NIRF CCD band pass filter and illumination light source in Fig. 1 can be easily changed to match the optical properties of different fluorophores if different fluorophores are used.
Fig. 1. Schematic of the visible/NIRF/gamma multi-modal laparoscope imaging system using SiPM-based gamma detector.
2.2 Optical readout devices of the multi-modal laparoscope system
Visible and NIRF photons were collected using a gradient index (GRIN) objective lens (GT-IFRL-100-020-50-NC, GRINTECH, Germany) located at the center of the laparoscopic tube. The GRIN lens has a diameter of 1 mm and length of 2 mm. The collected optical photons were transferred from the GRIN lens to the beam splitter module using a GRIN relay lens (GT-IFRL-100-150-10-NC, GRINTECH, Germany) with a diameter of 1 mm and length of 67 mm. In the beam splitter module, transmitted visible and NIRF photons were collected separately by the dichroic long-pass filter, as shown in Fig. 1. The dichroic long-pass filter (750 nm, Edmund Optics, USA) reflects light of wavelengths 565-715 nm, such that visible light was reflected by a dichroic long-pass filter and NIRF light was transmitted to an optical fiber (OD = 1.00 mm, length = 840.8 mm, Schott, Germany). The transmitted NIRF light was filtered using a band-pass filter (832/37 nm, Edmund Optics, USA). The visible and NIRF photons were focused by an aspherized achromatic lens (f = 25 mm, Edmund Optics, USA). Subsequently, the images were acquired by a Basler CCD (acA1300-30uc, Basler, USA) for the visible photons and an Andor CCD (iKon-M 934, Andor Technology Ltd, Northern Ireland) for NIRF image photons.
The illumination light sources were a fiber optic illuminator LED (G180P-6500 K, ScopeLED, USA) for white light and an NIR light diode (M780LP1, Thorlabs, USA) for NIR excitation. Each light source was focused on the illumination fiber bundle in the multi-modal system.
2.3 Gamma detection of the multi-modal laparoscope system
2.3.1 SiPM-based gamma detector module
The SiPM-based gamma detector is shown in Fig. 1. A multi-modal gamma detector of 13 mm diameter was built for insertion into the laparoscope tip. To obtain the maximum effective area within a small diameter, SiPMs of areas 2 ${\times} $ 2 mm2 (S13360-2050VE, Hamamatsu, Japan) and 1 ${\times} $ 1 mm2 (S13615-1050, Hamamatsu Photonics, Japan) were used to cover the scintillation crystals. A cerium-doped gadolinium aluminum gallium garnet (Gd3Al2Ga3O12: Ce, GAGG: Ce; Furukawa Scintitech Corporation, Japan) of size of 1.4 ${\times} $ 1.4 ${\times} $ 4 mm3 was used as the scintillation crystal. All GAGG crystals were polished chemically, and barium sulfate (BaSO4) reflectors of thickness 100 µm were used to optically isolate each GAGG pixel. This resulted in a crystal pitch of 1.5 mm. The scintillation crystal array was coupled with the SiPM using a polyvinyl chloride (PVC) light guide as compensation. The PVC was used to compensate for the height difference between the two SiPM detectors, and spread the scintillation light effectively. The SiPM detector and crystal array have a hole in the center for inserting the GRIN lens, and the pinhole collimator of the gamma detector was designed by the Monte-Carlo simulation to obtain a gamma image that was the same as the optical focal plane. The field of views (FOVs) of the gamma, NIRF, and visible images are aligned in the identical optical axis. Consequently, image registration between the visible, NIRF, and gamma images can be performed, while minimizing any potential image registration errors. The bias voltage of the gamma detector was selected as an overvoltage of 5.6 V to acquire gamma events, and the threshold of the discriminator cut was 0.9 V.
2.3.2 Signal processing circuit and data analysis of the multi-modal gamma detector
Four position signals (A, B, C, and D) of the gamma detector were obtained using a discretized positioning circuit for each SiPM output signal, amplified by an amplifier board (BASP-10005, Brightonics Imaging, South Korea), and read out to a DRS4 waveform digitizer (DT5742B, Caen, Italy). The sampling rate of DT5742B is 5 GSa/s, and the sampling resolution is 12-bit for each channel. The position signals were used to calculate the gamma photon interaction position within the GAGG crystal array using the following equation [33]:
where X and Y are the x-axis and y-axis positions at the gamma detector, respectively. To reject gamma scattering events, an energy window amounting to 20% of the 140 keV photo-peak was used.To evaluate the performance of the gamma detector, the Voronoi diagram [34] was used to segment the crystal map so as to extract the energy information of individual crystal pixel. The photo-peak value in ADC unit for each crystal pixel was obtained and then normalized to compensate the non-uniformity of detection efficiency as well as light output variation over the crystal array. After the photo-peak normalization and detection efficiency compensation, a 2D gamma event map which represents the number of events per crystal pixel was generated to visualize the radiopharmaceutical inside the imaging object. In the gamma event map, a GRIN lens was placed at the center of the crystal array to acquire the visible and NIRF images. The gamma events at the central crystal were calculated from neighboring crystal events in the gamma event map, as shown in Fig. 2, using the following equation:
Fig. 2. Gamma detector acquisition flow and gamma image inpainting method of the visible/NIRF/gamma multi-modal laparoscope system using SiPM-based gamma detector. (a) Gamma detector image acquisition diagram, (b) gamma image center hole inpainting method.
2.4 Image matching of the multi-modal laparoscope imaging system
The multi-modal laparoscope was designed for easy matching using the same FOV in the visible and NIRF imaging lenses and the gamma detector. The image fusion flow in the multi-modal imaging system is shown in Fig. 3. The gamma image was acquired based on the analog gamma signal at a 1 s interval. The 7 ${\times} $ 7 gamma event map was reshaped into an image of resolution 480 ${\times} $ 480 pixels using bicubic interpolation to match the image size of the visible CCD image. The 120 ${\times} $ 120 NIRF images were also reshaped to images of resolution 480 ${\times} $ 480 pixels image. The resized gamma and NIRF images were used to obtain fusion images with the visible image.
In the fusion images, the gamma and NIRF signals were pseudo-colored in the hot color map and green hot, respectively. The NIRF signal was filtered using a kernel with 11 ${\times} $ 11 median filters in the fusion visible/NIRF/gamma image. For the visible image, flat-field correction was employed to compensate for the non-uniformity in intensity across the FOV.
2.5 Phantom test of the proposed system
Figure 4 shows the experimental setup for the quantitative evaluation of gamma images. To mimic a patient’s abdominal cavity during laparoscopic surgery, the multi-modal system and the solution of mixed 99mTc isotope and ICG NIR dye phantom source were placed in a dark box. A tungsten pinhole collimator of diameter 1.5 mm was used to acquire the gamma image. The distances from the phantom source to the pinhole collimator and that from the pinhole collimator to the GAGG crystals were 50 and 10 mm on the z-axis, respectively. The FOV of the visible, NIRF, and gamma images was 50 ${\times} $ 50 mm2. The 99mTc gamma source activity was 1.1 MBq, and the ICG dye volume was 0.1 mL with a concentration of 10 µM (Cardiogreen, Sigma Aldrich, USA). The gamma images were acquired with an acquisition time of 1 s, and then, the signal intensities in the gamma images were accumulated. The visible and NIRF images were obtained with acquisition times of 50 and 200 ms, respectively, and updated at the start of each acquisition. The CNR of the gamma image was calculated using the following equation [35]:
where ${I_{sig}}$ and ${I_{bkg}}$ are the average pixel intensities of the region of interest (ROI) of the signal and background, respectively.Fig. 4. Phantom test for gamma image acquisition time and tissue-equivalent phantom depth penetration test. (a) ICG-99mTc mixture phantom, (b) gelatin tissue-equivalent phantoms with different thicknesses, (c) phantom test setup.
To characterize the NIRF image for human tissue, tissue-equivalent phantoms were fabricated with 89% water, 10% gelatin from porcine skin (Sigma Aldrich, USA), and 20% weight of intralipid 1% (JW Pharmaceutical, Korea). The tissue-equivalent phantoms were molded into custom-made plastic frames of thicknesses 2, 4, 6, 8, and 10 mm. All images were acquired with the same FOV, and the signal-to-noise ratio (SNR) and CNR were calculated using the following equations [35]:
2.6 Testing with a rat model
Figure 5 shows photographs of the visible/NIRF/gamma multi-modal imaging system and a Sprague Dawley rat model, which was used to identify the SLN. To prevent motion artifacts in the rat model during in-vivo imaging, inhalation anesthetizing was maintained with Isoflurane 2%. The ICG-99mTc-nanocolloid (human serum albumin) source was used as the hybrid tracer. The injection radiation dose was 81.77 MBq of 99mTc, and ICG labeling was performed with a commercial kit-NH2 (Dojindo Laboratories, Japan). After the multi-modal images were acquired, the rat model was sacrificed to dissect the SLN. All rat model studies were approved by the Institutional Animal Care and Use Committee at Seoul National University Bundang Hospital. Imaging was performed 3 h after tracer injection for the axillary point image, and 4 h after tracer injection for the resected lymph node multi-modal images.
Fig. 5. Rat model test. (a) Setup, (b) injection position, (c) image acquisition from the axillary position.
3. Results
3.1 Performance of the gamma detector
Figure 6 shows the performance of the proposed gamma detector for the multi-modal laparoscope system. Individual crystals were clearly resolved in the segmentation map (Fig. 6(a)), and the average energy resolution of the normalized gamma event map was 18.7 ± 1.4%, as shown in Fig. 6(c). The distance between the laparoscopic tip and source was 50 mm. As shown in Fig. 6(d), the signal was calculated from the ROI (white line), and the background (white dotted line) was calculated for the opposite side of the gamma image. Figure 6(e) shows the signal and noise intensity and CNR obtained for the gamma images of the 99mTc radioactive source (4.3 MBq/300 µL) for different acquisition times. The gamma signal increased linearly with the acquisition time, and the CNR increased with the acquisition time of the gamma detector. A gamma detector sensitivity of 0.035 cps/kBq was acquired for the 99mTc source.
Fig. 6. Intrinsic performance of the SiPM-based gamma detector. (a) Flood map of the detector, (b) raw energy spectra, (c) normalized energy spectra (W/ Gaussian fitting), (d) acquired gamma detector event map, (e) net count and CNR of the detector.
3.2 Evaluation of the multi-modal laparoscope system with a phantom test
Figure 7 shows the multi-modal visible, NIRF, and gamma images with different image acquisition times. The visible, NIRF, and gamma images shown in Fig. 7(a), (b), and (c) were acquired with acquisition times of 50 ms, 200 ms, and 30 s, respectively. The spatial resolution of the NIRF image was acquired at 5.4 mm in Fig. 7(d), and the gamma image spatial resolution was 8.2 mm, as shown in Fig. 7(e). The fusion images of visible, NIRF, and gamma images shown in Fig. 7(f) were obtained by combining Fig. 7(a) and (b) with gamma images obtained for 1, 5, 10, and 20 s.
Fig. 7. Phantom test images. (a) Visible image, (b) NIRF image, (c) gamma image, (d) NIRF image phantom spatial resolution plot (W/ Gaussian fitting), (e) gamma image phantom spatial resolution plot (W/ Gaussian fitting), (f) multi-modal fusion image different of gamma acquisition times.
Figure 8 shows the multi-modal laparoscope images of the 99mTc isotope and ICG dye mixture at 0, 4, 6, and 10 mm thicknesses of the tissue-equivalent gelatin phantom. All gamma images required an acquisition time of 10 s. The images in Fig. 8(a) were obtained by adjusting the contrast, while the images in Fig. 8(b) were obtained using the median filter. The scattered NIRF signals are shown in Fig. 8(b).
Fig. 8. Tissue-equivalent phantom depth penetration test images. (a) Multi-modal laparoscope fusion image of the tissue-equivalent phantom image in different depths (W/O histogram stretch), (b) tissue-equivalent phantom image (W/ histogram stretch and median filter).
Figure 9 shows the NIRF and gamma signal intensities at different depths of tissue-equivalent phantoms. As the depth of the phantom increases, the gamma and NIRF signals deteriorate by 13% and 80% at 10 mm, respectively.
3.3 Evaluation of the multi-modal laparoscope system with the small animal test
Figure 10 shows the visible images of the ICG-99mTc-nanocolloid tracer injection points (paw and palm), axillary area, and resected lymph node. The images clearly show the characteristics of NIRF and gamma imaging, such as the limited depth penetration of NIR and poor spatial resolution of gamma. Immediately after injection, the gamma image was obtained with an acquisition time of 2 s, because the injection point radiation dose was high. The axillary gamma image acquired 3 h after injection was obtained with a 90 s acquisition time, because the distance from the multi-modal laparoscope to the rat model was increased from 50 mm to 100 mm. The resected lymph node gamma image acquired after 4 h of injection took 30 s. The NIRF image of the resected lymph node took 5 s, since the NIRF signal of the lymph node was very low.
Fig. 10. In-vivo imaging results of a rat with the proposed multi-modal laparoscope imaging system small animal image: (a) visible/NIRF image at paw (left), palm (middle), and axillary area (right), (b) visible/gamma image at paw (left), palm (middle), and axillary area (right), (c) visible/NIRF/gamma image at paw (left), palm (middle), and axillary area (right), (d) resected lymph node image of visible/NIRF, visible/gamma, and visible/NIRF/gamma.
Figure 10(a) shows the visible/NIRF images, and it can be seen that NIRF realizes good spatial resolution, but cannot penetrate the rat model’s hand, as shown in the palm image. The yellow line in the palm image was caused by the NIRF concentration at the paw side. As shown in Fig. 10(b) of the visible and gamma image, the gamma signal can penetrate the rat model; however, this results in poor spatial resolution. Figure 10(c) shows the visible/NIRF/gamma fusion image, overcoming the weaknesses of each imaging modality. Figure 10(d) shows the lymph node image shown in Fig. 10(c), where the axillary area gamma hot spot region shows the detection ability of the multi-modal laparoscope image system.
4. Discussion
Recently, intraoperative imaging methods have been studied using NIRF, ultrasound, and gamma probes to provide images and signals for surgeons. However, each imaging method has problems such as the penetration depth problem of NIRF, poor resolution of superficial regions in ultrasound, image acquisition time, and poor spatial resolution of the gamma probe. In addition, the existing imaging method can result in a high false-negative rate for lesions. The SLN biopsy using both 99mTc-nanocolloid and vital dye resulted in the greater detection ability than using separate markers [36]. Currently, the dual technique of using NIRF and gamma signal is the gold standard for SLN biopsy.
For the image guided surgery, the hybrid tracer study has been also increasing as the multi-modal system research. Even though there are some challenges generating the hybrid tracers, but the hybrid tracers showed better results than monomodal tracers [23,24,27,28].
To overcome the limitations of using a single imaging modality, the hand-held tri-modal probe was proposed using ultrasound, photoacoustic, and fluorescence. The tri-modal imaging method can show the obstructed SLNs and metastatic involvement [18]. In this study, we investigated a multi-modal laparoscope imaging system acquiring simultaneous visible, NIRF, and gamma images. The phantom study with the 99mTc isotope and ICG dye mixture showed that the fusion image was not affected by the depth penetration problem of the NIRF signal and the poor spatial resolution of the gamma signal. In addition, the small animal test demonstrated the detection ability of the proposed system in lymph node resection. The proposed system was focused on imaging the ICG-99mTc-nanocolloid hybrid tracer with a single system which is able to obtain visible, NIRF, gamma and hybrid images. The ICG fluorophore does not accumulate in the lymph node, while the ICG-99mTc-nanocolloid hybrid tracer is accumulated so that the lymph node could be located with the smaller false-positive rate using the multi-modal imaging than the ICG or 99mTc-nanocolloid alone imaging [20,23,24,27,28]. The single system which we proposed occupies less space in the laparoscopic surgery cavity than two imaging devices, one for ICG and the other for 99mTc-nanocolloid, something which could be quite convenient for surgeons considering that many devices compete for the laparoscopic surgery cavity. Moreover, it can be easily applied to other fluorophores by changing the NIR CCD bandpass filter and illumination NIR light diode.
The limitations of the multi-modal laparoscope imaging system are the central dead region of the gamma detector and the low sensitivity of NIRF and gamma signals. In the multi-modal system, the gamma detector was designed to acquire the optical and gamma images in the same FOV, owing to which the gamma detector has a central dead region for the optical GRIN lens system. To address this issue, inpainting of the center hole gamma event was implemented. In the phantom study, all the images matched well in the fusion image, and the gamma event center hole effect was not significant. However, the small animal test exposed the weakness of the large image defect at the central region, resulting in difficult interpretation of the gamma image. In addition, the central dead region caused worse gamma event defects as the FOV increased.
Gamma images were acquired at 1 s intervals (i.e., frame rate of 1 fps), and accumulated to produce the final image at the desired time. Visible and NIRF images were acquired at each acquisition time of the CCD camera single image and flushed. The gamma image was acquired for 30 s at a distance of 50 mm, and 90 s at a distance of 100 mm in the small animal test axillary image. As resection of the lymph nodes was performed 4 h after injecting the ICG-99mTc-nanocolloid, the concentration of lymph nodes was low, resulting in poor NIRF signal intensity in the resected lymph node image. The lymph node NIRF image also required an additional acquisition time of 5 s. The proposed multi-modal laparoscope system can provide visible, NIRF, and gamma image simultaneously. In surgical environment where the SLN is located under the tissue or fat, it can provide the rough SLN location with the gamma image which, with surgical tools, can be exposed to acquire the visible/NIRF image for the precise SLN location.
In future studies, we plan to investigate a multi-modal imaging system without a central dead region, assuming gamma detectors improve the source detection ability and reduces the gamma image acquisition time. The usefulness of the scattered NIRF signals at a thickness of 10 mm in tissue-equivalent phantoms will be also studied in future works.
5. Conclusion
We developed a novel prototype multi-modal laparoscope system for simultaneous NIRF/gamma/visible imaging, containing a gamma detector with a central dead region to accommodate the GRIN lens for visible and NIRF images. The feasibility of in-vivo SLN mapping was successfully performed with the proposed system, using the ICG-99mTc-nanocolloid. In the future, the laparoscopic system will be further optimized for a pilot clinical study.
Funding
National Research Foundation of Korea (NRF-2017M2A2A4A01071175, NRF-2020R1F1A1054317); Korea Medical Device Development Fund (202011D24).
Acknowledgments
National Research Foundation (NRF) of Korea of the Ministry of Science, ICT & Future Planning, Nuclear R&D Program (NRF-2017M2A2A4A01071175); National Research Foundation of Korea (NRF) grant funded by the Korea government Ministry of Science and ICT (MSIT) (NRF-2020R1F1A1054317); Korea Medical Device Development Fund grant funded by the Korea government R&D Program (202011D24).
Disclosures
The authors declare no conflicts of interest.
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