Characterizing muscle components in intestinal strictures using spectroscopic photoacoustic imaging

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Data may be preliminary. 19 September 2025 V1 Latest version Share on Characterizing muscle components in intestinal strictures using spectroscopic photoacoustic imaging Authors : Xiaorui Peng [email protected] , Linyu Ni , Laura Johnson , Yaocai Huang , Wei Zhang , Xueding Wang , Peter D.R. Higgins , and Guan Xu 0000-0002-5942-7987 Authors Info & Affiliations https://doi.org/10.22541/au.175827451.12997054/v1 Published Journal of Biophotonics Version of record Peer review timeline 302 views 149 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Inflammatory bowel disease is a chronic autoimmune disease that causes obstructive intestinal strictures, characterized by inflammation, fibrosis, and muscular hypertrophy. Accurately characterizing the stricture pathology for therapeutic planning remains challenging. In our previous study, using multispectral photoacoustic (PA) imaging, we investigated the feasibility of quantifying the hemoglobin and collagen components, corresponding to the inflammation and fibrosis, respectively, in animals in vivo and human subjects. In this study, we investigated resolving the myoglobin component that is associated with muscular hypertrophy with PA imaging. We quantified the hemoglobin and myoglobin ratios in a controlled phantom. We visualized the distribution of the tissue components in porcine tissue samples ex vivo. We also examined PA imaging in quantifying tissue components in human intestinal strictures and unstrictured margin ex vivo and in rabbits in vivo . The results show that PA imaging is a promising tool for characterizing the pathology of intestinal strictures. Article type: Research Articles Title: Characterizing muscle components in intestinal strictures using spectroscopic photoacoustic imaging Xiaorui Peng 1 ; Linyu Ni 1 ; Laura Johnson 2,3 ; Yaocai Huang 1 ; Wei Zhang 1 ; Xueding Wang 1,4,* ; Peter D.R. Higgins 2,3* ; Guan Xu 1,5,* 1. Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States. 2. Department of Internal Medicine, Michigan Medicine, Ann Arbor, MI, United States. 3. Division of Gastroenterology and Hepatology, Michigan Medicine, Ann Arbor, MI, United States. 4. Department of Radiology, University of Michigan, Ann Arbor, MI, United States. 5. Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, United States. *Correspondence Email: [email protected] Abstract Inflammatory bowel disease is a chronic autoimmune disease that causes obstructive intestinal strictures, characterized by inflammation, fibrosis, and muscular hypertrophy. Accurately characterizing the stricture pathology for therapeutic planning remains challenging. In our previous study, using multispectral photoacoustic (PA) imaging, we investigated the feasibility of quantifying the hemoglobin and collagen components, corresponding to the inflammation and fibrosis, respectively, in animals in vivo and human subjects. In this study, we investigated resolving the myoglobin component that is associated with muscular hypertrophy with PA imaging. We quantified the hemoglobin and myoglobin ratios in a controlled phantom. We visualized the distribution of the tissue components in porcine tissue samples ex vivo. We also examined PA imaging in quantifying tissue components in human intestinal strictures and unstrictured margin ex vivo and in rabbits in vivo . The results show that PA imaging is a promising tool for characterizing the pathology of intestinal strictures. Keywords: argon plasma coagulation; inflammatory bowel disease; photoacoustic/ultrasound imaging; spectral unmixing Abbreviations: IBD, Inflammatory bowel disease; PA, photoacoustic; Hb, hemoglobin; Mb, myoglobin; APC, argon plasma coagulation; CD, Crohn’s disease; US, ultrasound; MRI, magnetic resonance imaging; CT, computed tomography; TNBS, trinitrobenzene sulfonic acid; OPO, optical parametric oscillator; PAM, photoacoustic microscopy; FOV, field of view; MAP, maximum amplitude projection; PACT, photoacoustic computed tomography; ROI, region of interest; 1 INTRODUCTION Crohn’s disease (CD) is a chronic autoimmune condition affecting approximately 700,000 people in the United States[1]. A majority of CD patients develop intestinal strictures within 10 years of diagnosis [2]. Initially triggered by inflammation, intestinal strictures contain both inflammation and fibrosis, as well as muscular hypertrophy [3]. While acute inflammatory strictures can be treated medically, chronic fibromuscular strictures, driven by irreversible fibrosis and muscle hypertrophy, require surgical intervention [4, 5]. Chronic inflammation results in a combination of fibrosis and expansion of smooth muscle layers, leading to bowel narrowing and stiffening[6, 7]. Clinicians are interested in the correlation between the progression of fibrosis and muscular hypertrophy, which is critical for selecting appropriately targeted treatment approaches and gaining a better mechanistic understanding of the disease [3, 8-10]. The current practice of CD stricture management often involves repeated trials of anti-inflammatory therapies such as corticosteroids, leading to therapeutic delays, hospitalizations, and adverse side effects before surgery becomes inevitable [11-13]. Therefore, a non-invasive method to assess fibrosis and muscular hypertrophy in intestinal strictures could significantly enhance timely therapeutic decisions and improve patient outcomes [14-18]. The current diagnostic approach for CD involves endoscopic biopsy [19], where small pieces of mucosa are taken from the inner lining of the intestine for histopathological analysis [20-22]. Although this method can identify intestinal inflammation [23], it is limited in assessing intestinal fibrosis and muscular hypertrophy, which occur in the lamina propria and muscularis [20, 24-26]. Since biopsies typically do not reach these deeper tissues, they may not detect fibrosis and muscular hypertrophy, while inflammation, detected in superficial layers, often leads to corticosteroid treatment, which is ineffective for chronic fibromuscular strictures [27-30]. Conventional non-invasive imaging modalities such as ultrasound (US), magnetic resonance imaging (MRI), and computed tomography (CT) have demonstrated their ability to identify and locate intestinal strictures and measure bowel wall thickness [31-33]. However, these structural imaging techniques cannot assess strictures at the molecular level [34]. As a result, a prognostic gap remains, often filled by repeated empirical courses of corticosteroids, leading to significant adverse events and delays in timely surgical treatment [35]. Spectroscopic photoacoustic (PA) imaging is an emerging non-radiative and non-ionizing technology that combines the advantages of optical spectroscopy and ultrasonography [36, 37]. It offers high sensitivity to molecular components, decent spatial resolution and penetration depth, making it an ideal candidate for characterizing intestinal strictures [38]. In our previous research, we validated the feasibility of characterizing intestinal inflammation and fibrosis by quantifying hemoglobin and collagen content in animal and human samples ex vivo, animals in vivo , and human subjects [39-42]. The purpose of this study is to validate the ability of PA imaging to quantitatively measure the myoglobin (Mb) content, which is rich in muscle tissue, through studies with phantoms, animals in vivo and ex vivo human tissue samples. In addition, we introduced argon plasma coagulation (APC) [43] treatment to reliably generate fibrosis at intestinal locations with rich muscle components in animals. PA images of resolved biological contents were compared to histological results. Statistically significant differences were observed consistent with the histology. 2 METHODS AND MATERIALS 2.1 Spectral Unmixing Method In spectroscopic PA imaging, in order to resolve different biological contents, we can use the spectral unmixing method [44] based on Beer-Lambert law [45] in equation (1), \(A=\text{ϵbC}\) (1) where \(A\) is the optical absorbance, \(\epsilon\) is the molar attenuation coefficient, \(b\) is the optical path length and \(C\) is the concentration. To resolve the concentrations of multiple chromophores (e.g., hemoglobin (Hb), myoglobin (Mb), collagen, and lipid), PA signals can be acquired at multiple wavelengths (\(\lambda_{1}\), \(\lambda_{2}\),\(\lambda_{3}\), \(\lambda_{4}\)) of light and formulated as a linear inverse problem in the matrix form as in equation (2): \(\par\begin{bmatrix}C_{\text{Hb}}\\ C_{\text{Mb}}\\ C_{\text{collagen}}\\ C_{\text{lipid}}\\ \end{bmatrix}=\par\begin{bmatrix}\begin{matrix}\end{matrix}\text{\ \ \ \ \ }\par\begin{matrix}\end{matrix}\\ \begin{matrix}\end{matrix}\text{\ \ \ \ \ }\par\begin{matrix}\end{matrix}\\ \end{bmatrix}^{-1}\times\par\begin{bmatrix}A_{\lambda_{1}}\\ A_{\lambda_{2}}\\ A_{\lambda_{3}}\\ A_{\lambda_{4}}\\ \end{bmatrix}\) (2) Here, \(\mu_{i}\lambda_{j}\) denotes the known molar attenuation coefficient of chromophore \(i\) at wavelength \(\lambda_{j}\) used in the previous studies by our and other groups [44, 46, 47], and\(A_{\lambda_{j}}\) is the measured PA signal (proportional to optical absorbance) at that wavelength. 2.2 Phantom Study We conducted a phantom study to verify the feasibility of resolving hemoglobin and myoglobin contents, which are surrogates for detecting inflammation and muscular hyperplasia, respectively. The system setup is shown in Figure 1(a) . We used a tunable optical parametric oscillator (OPO) laser (Phocus Mobile, OPOTEK, CA) and a fiber bundle (P/N PP-FI-BDL, OPOTEK, CA) to deliver the laser emission from the top of a 1mm-diameter tube. We used a hydrophone (bandwidth: 1-28MHz, Onda HNC series, CA) with an amplifier (10 dB gain, Model 5072PR pulser/receiver, Olympus) as PA signal receiver and an oscilloscope (MDO3054, Tektronix, OR) to monitor the PA signals. We used phantom samples made from lyophilized myoglobin powder from equine heart (M1882, Sigma-Aldrich, MO) and hemoglobin powder from bovine blood (H2500, Sigma-Aldrich, MO) [44]. We measured the absorbance of Mb, Hb, and water using a spectrometer (SpectraMax M2, Molecular Devices, CA), as shown in Figure 1(b) . Our phantom samples were prepared at controlled myoglobin/hemoglobin (Mb/Hb) concentrations: Mb/Hb=2.5/0.5, Mb/Hb=2/1, Mb/Hb=1.5/1.5, Mb/Hb=1/2, Mb/Hb=0.5/2.5. The mixed solutions were injected into the tubing in Figure 1(a), and examined with PA measurements at 690nm, 700nm, 734nm, 757nm, 767nm, 800nm with the averages of 128 measurements. Figure 1(c) illustrates an example of A-line signals from 690nm, 734nm, 757nm and 800nm for a sample with Mb:Hb = 1:1. Figure 1(d) shows the relative Mb:Hb ratio calculated from the maximum signal intensities using the spectral unmixing method in equation (2) and normalized by the maximum calculated ratio. Figure 1(d) shows the correlation with an R-squared value of 0.868 between the true Mb:Hb ratios and the relative Mb:Hb ratios derived from the PA measurements. Figure 1. (a) System setup of phantom study with controlled myoglobin/hemoglobin (Mb/Hb) concentrations. The system consists of a hydrophone with an amplifier, an OPO tunable laser with a fiber bundle, and an oscilloscope. (b) Absorption spectra of myoglobin (Mb), hemoglobin (Hb) and water measured by a spectrometer. (c) Representative A-line photoacoustic signals acquired at 690 nm, 734 nm, 757nm and 800 nm. (Mb:Hb = 1:1) (d) Boxplot of relative Mb/Hb derived from PA measurement versus the actual Mb/Hb ratios. 2.3 Resolving Tissue Components in porcine esophageal samples ex vivo To determine the feasibility of resolving tissue components in the gastrointestinal tract, we performed optical resolution PA microscopy (PAM) on ex vivo porcine esophagus. We used the multispectral PAM system as shown in Figure 2(a) . The system features a tunable laser (SpitLight EVO II OPO, wavelengths: 680 –2400 nm, InnoLas Laser GmbH) with a repetition rate of 500 Hz as the illumination source. The emission beams at the signal and idler wavelengths were collimated to a diameter of 7 mm and aligned coaxially. A scanning lens (focal length 36 mm, LSM03-BB, Thorlabs, NJ) focused the collimated beams at the sample surface. The optical energy at the sample surface was maintained at 0.03 mJ per pulse at the signal wavelengths (680-950 nm) and 0.06 mJ per pulse at the idler wavelengths (1200-2400 nm). PA signals are detected by a needle hydrophone (Optosonic, CA) with 27 MHz center frequency, which was positioned 1 mm from the sample and amplified by 50 dB (Pasternack, CA). The data acquisition card (CSE161G4, Gage, Vitrek, IL) digitized signals at 250 MHz sampling rate. Synchronization of lasers, scanning galvonometer mirrors, and data acquisition is managed by a digital delay generator (DG535, Stanford Research Systems, CA). Imaging was conducted with a field of view (FOV) of 2 mm × 2 mm, using a step size of 20 μm in both lateral directions. To cover the entire specimen, four scans were performed. 3D data are converted to 2D maximum amplitude projection (MAP) images for visualization. Figure 2. Experiment setup. (a) PAM system for resolving tissue components in the porcine esophagus ex vivo . SL: scanning lens. Sync: synchronization. PH: pinhole. DM: dichroic mirror. (b) (Left) PA tomography of ex vivo human intestinal specimens. The specimen was placed in a sample holder cup and imaged using a 64-element linear US array. (Right) Top view of the setup. (c) A PA and US catheter system for imaging the rabbit colon and rectum in vivo . 2.4 Photoacoustic Imaging of ex vivo Human Intestinal Specimens Deidentified ex vivo tissue samples were acquired from the Tissue Procurement Core from human patients with ileocolonic resections at Michigan Medicine. For PA imaging, the system was set up as shown in Figure 2(b) . The intestine samples were flattened and cut into pieces with areas of around 15 mm by 15 mm and positioned at the bottom of a transparent gel cup made of 10% gelatin powder mixture with water. A small amount of water was added on top of the samples for acoustic coupling. Optical illumination at the wavelengths of 734 nm, 757 nm, 1220 nm, and 1310 nm was delivered from the top of the cup to avoid optical attenuation by water. We utilized a miniaturized US transducer array (Acunav, Siemens, Germany) and a Verasonics system (Vantage 256, Kirkland, CA) to acquire PA and US images. The US array was positioned approximately 20 mm away from the center of the sample holder. The imaging plane of the US array was aligned with the sample plane. 2.5 Photoacoustic Imaging of Rabbits in vivo All the in vivo animal imaging protocols in this study were approved by the Institutional Animal Care and Use Committee (IACUC) at the University of Michigan in accordance with the United States Department of Agriculture (USDA) Animal Welfare Act and Animal Welfare Regulations (AWAR). Rabbits (New Zealand white) of both sexes were obtained from the University of Michigan breeding colony. During all procedures, the animals were anesthetized by inhalation of isoflurane. At the end of the experiments, the animals were euthanized under anesthesia by barbiturate overdose. Tissues from all imaged sites were collected for histology. Figure 2 (c) illustrates the system setup for the rabbit experiments. 2.5.1 Photoacoustic Imaging in Healthy Rabbits To examine the feasibility of assessing myoglobin content with PA imaging, we compared the rectum with the distal colon in 10 normal (no colitis) rabbits in vivo . We utilized the intrinsic anatomical differences between the rectum and colon to validate PA imaging of Mb as the rectum is surrounded by additional musculature and is expected to have higher myoglobin content in the PA image. 2.5.2 Photoacoustic Imaging in a Rabbit Model of Inflammation and Fibrosis To evaluate whether PA imaging can resolve the molecular components of hemoglobin, collagen, and myoglobin, we used a mucosal ablation model using argon plasma coagulation (APC), originally described by Selaru [48]. Briefly, a clinical bronchoscope (BF-140, Olympus, Tokyo, Japan) was inserted into the rabbit rectum and advanced to a depth of approximately 13 cm from the anus into the colon. Baseline (day 0) endoscopy videos were recorded from the colon to the rectum. Baseline PA measurements were captured prior to mucosal ablation. Using an APC device (ERBE ICC-200) with a flow rate of 0.8 L/min and 30 watts, multiple small areas of the mucosa at 3 cm from the anus were ablated multiple times to encompass the full circumference of the bowel lumen, forming a 1cm long lesion at the imaged location. We expect APC treatment to induce inflammation and fibrosis at the location close to the rectum, therefore forming a scenario where hemoglobin, collagen, and myoglobin coexist. 2.5.3 Photoacoustic Imaging System and Balloon Catheter Probe Our endoscopic PA-US balloon catheter imaging system [41] was used to acquire all the images in the rabbit study in vivo . The customized probe integrates a 64-element linear US array (bandwidth 5-10 MHz, Acunav 8F, Siemens, Seattle, WA) and a side-firing optical fiber (0.39 NA, 800 μ m core, Thorlabs, NJ) inside a medical balloon catheter (10 mm diameter, 10002000BB, Nordson Medical, OH). The illumination source of PA imaging is an OPO laser (Phocus Mobile, OPOTEK, CA) with 8 ns pulse length and 10 Hz repetition rate. Optical energy of 1.5 mJ per pulse was coupled to the fiber optics in the probe at all optical wavelengths, forming an optical energy density of approximately 7 mJ/cm 2 at the dilated balloon surface, which is below the safety limit established by American National Standards Institute [39]. We implemented illumination at 734 nm, 757 nm, 1220 nm and 1310 nm for PA measurements, targeting the absorption profiles of hemoglobin, myoglobin, lipids and collagen content, respectively. US images were acquired alongside PA measurements to visualize anatomical structures. 2.5.4 Data Processing and Image Reconstruction Both US and PA images were reconstructed with the delay-and-sum method and displayed in parallel in real time. For each illumination wavelength, the reconstructed PA images are compensated by optical attenuation estimated with the averaged optical properties of the intestines [49]. The molecular contents were resolved using a spectral unmixing method pixel-wise. The pixel intensities in the contents-resolved PA images were averaged within the bowel wall region for later statistical analysis. 2.6 Histology All tissue samples were fixed in 10% neutral buffered formalin. Tissue processing, hematoxylin and eosin (H&E) staining and Masson’s trichrome staining was performed by the University of Michigan Cancer Center Histology and Immunoperoxidase Lab (Ann Arbor, MI, USA) and McClinchey Histology Lab (Stockbridge, MI, USA), respectively. Digital photomicrographs of colon sections were captured using an Olympus BX51 microscope at the University of Michigan Microscopy and Image Analysis Laboratory (Ann Arbor, MI, USA). 2.7 Quantifications and Statistics The pig esophageal sample study was a proof-of-concept study to examine whether PA imaging can resolve the layered structures in the gastrointestinal tract, therefore no quantitative analysis was performed. PA measurements from diseased human stricture samples and normal margins were compared using t-tests with the null hypothesis that the PA measurements could not be differentiated between the two groups. For the healthy rabbit study, t-tests were performed between the colon and rectum with the null hypothesis that the two groups cannot be differentiated by the tissue components derived from PA imaging. For the APC model study, t-tests were performed between the tissue components measured at the baseline and endpoint, with a null hypothesis stating that PA imaging cannot detect the histopathological changes induced by the APC treatments. 3 RESULTS 3.1 Spatially resolving Tissue Components in Pig Esophagus Specimens Using Photoacoustic Microscopy Figure 3. Microscopic PA images showing the molecular tissue components of the upper gastrointestinal tract. (a) Photo of a swine esophageal sample. (b) Magnified view of the red box in (a), borders of the tissue layers (epithelium, submucosa, and the deeper muscle layers are denoted by yellow dashed lines. (c) PA molecular component pseudo-color images with Hb (red), Mb (pink), collagen (green), and lipid (blue). (d) Trichrome staining of the swine esophagus illustrates the normal tissue architecture and collagen (blue staining). Arrows in (c-d) denote areas of collagen accumulation. Epithelium (E), submucosa (S), and muscularis layers (M). Scalebar: 500 µm. Figure 3 shows a strong morphological correlation between the PA imaging and histological appearance. Exact registration between the PA imaging and the histology was not possible due to the sample processing. The distribution of molecular components and the tissue architecture are consistent between the PA and histological images. 3.2 Quantitative Photoacoustic Imaging of Human Intestinal Stricture Specimens Figure 4. PA imaging of ex vivo human Crohn’s disease intestinal tissue (a-b). Representative histology of Trichome-stained stricture and normal margins, respectively, illustrating a dramatic increase in collagen (blue staining). (c-d) Contents-resolved pseudo-color images of the stricture and normal specimen, respectively with (Hb (red), Mb (pink), lipid (green), and collagen (blue). The image was taken with the setup in Fig. 2(b). (e) Comparison of relative tissue components derived from normal tissue (N = 4) and strictured tissue (N = 7). Histological images in Figure 4(a-b) show that the stricture tissue has increased muscle, lipid, and collagen content compared to the normal margin. As illustrated in Figure 2(b) and described in the method section, the intestine samples were flattened, and the PA image was taken parallel to the sample plane. PA signals from multiple layers in the samples were captured, and the molecular components overlap. Figure 4(c-d) are the PA images showing the molecular components in pseudocolor, demonstrating increased collagen and myoglobin content. Due to the optical penetration and elevational receiving angle of the US array, direct registration to the histological samples was not possible. Figure 4(e) shows the statistics of the average molecular components in the strictures and normal margins. Significant differences in collagen (0.75 vs 1.1 vs arbitrary units, p<0.01) and lipid (0.6 vs 1.4 arbitrary units, p<0.05) content are found before and after the APC treatment due to the lipid deposition and fibrosis in the stricture sample. Muscle content also increased in the strictured tissue compared to the unstructured margin. However, due to the large standard deviation within the strictured samples, no statistically significant difference in muscle content was found between the normal and stricture samples. Hemoglobin content is difficult to compare due to the inherent lack of blood flow in ex vivo tissue. 3.3 Photoacoustic Imaging of Rectum and Distal Colon in Healthy Rabbits Figure 5(a) shows the example images of US B-mode images and PA images at different wavelengths acquired at the rectum and the colon 7cm from the rectum in a healthy rabbit. Figure 5(b) shows the pseudo color images combining the Hb, Mb, lipid, and collagen contents and histology. Figure 5(c) showed that the muscle content in the rectum is higher than that in the colon (n=10, p<0.001), which agrees with the histology in Figure 5(b) . Figure 5. US and PA images of healthy rabbit rectum and colon in vivo . (a) US and PA images at the optical wavelengths of 734 nm, 757 nm, 1200 nm, and 1310 nm at the rectum and the colon 7cm proximal to the rectum. (b) Pseudocolor imaging showing the molecular components with (Hb (red), Mb (pink), lipid (blue), and collagen (green) compared to histology at the same locations. (c) Statistics of the relative content of molecular components measured at the two locations (n=10). Scalebars in PA and US images: 1 mm. Scalebars in histology, 500 µ m. 3.4 Photoacoustic Imaging Results in the Rabbit APC Model of Colitis Figure 6. PA images of a location close to the rectum at baseline (Day 0) and after APC treatment (Day 51) in a rabbit. (a) US and pseudo-color PA images of the tissue components (Hb (red), Mb (pink), and collagen (green). (b) Histology of the APC-treated colon at the end of the experiment. The histology demonstrates collagen staining (Yellow arrows are collagen deposition due to APC treatment; blue arrow is normal structural collagen.) and distribution of the muscularis mucosa and deeper circular and longitudinal muscle layers (pink, brackets). Scalebars in PA and US images: 1 mm. Scalebars in histology, 500 µ m. Figure 6(a) shows the representative US and PA images at the baseline, i.e. before APC treatment, and at the end of the experiment. Hemoglobin and myoglobin content were captured both before and after the treatment. Collagen content (blue staining) increased due to the APC treatment. This agrees with the histology in Figure 6(b) . In Figure 7 , statistics derived from measurements in 3 rabbits before and after APC treatment confirm the rich hemoglobin and myoglobin content at the intestinal location close to the rectum. Despite strong background PA signals generated by the hemoglobin and myoglobin content, our imaging system can measure an increase in collagen content of 3.8 arbitrary units due to the fibrosis induced by APC treatment (p < 0.05). Figure 7. Statistical analysis of APC-treated rectal tissue in rabbits in vivo . Hb: Hemoglobin. Mb: Myoglobin. Col: Collagen. 4 DISCUSSION This study explored the feasibility of using PA imaging to quantitatively resolve intestinal tissue components, including myoglobin, hemoglobin, collagen, and lipid. Our spectral unmixing method successfully characterized the myoglobin content, in addition to hemoglobin and collagen content, within phantoms and in vivo animal models, as well as human ex vivo tissue. The PA findings were validated by histology. These outcomes demonstrate that PA imaging is a promising tool to quantitatively evaluate muscle content in intestines, and PA imaging is a promising non-invasive diagnostic tool for assessing structural changes associated with gastrointestinal diseases. PA imaging of ex vivo human intestinal strictures showed higher collagen and myoglobin content than normal margin tissue, although the difference in myoglobin content was not statistically significant due to high variability in the strictured samples. This observation is consistent with the histology. Based on our PA imaging studies in healthy rabbits which characterized the rich muscle component near the rectum, we generated APC lesions in a location close to the rectum to create a scenario where fibrosis, muscle components and hemoglobin are present at the same time. In the rabbit APC model, intestinal fibrosis was generated at locations with rich muscle components, as confirmed by histology. PA imaging showed similar findings of increased collagen content. Myoglobin content was observed by PA imaging at both the baseline and the endpoint with no significant change. The PA observations of collagen and hemoglobin are consistent with histology. In our previous studies, we demonstrated that PA imaging can differentiate inflammation from fibrosis in the TNBS rabbit colitis model [40]. However, the TNBS model has limitations, including the distribution and severity of tissue injury. In this study, we refined a porcine APC (argon plasma coagulation) model [43] to create a pre-clinical rabbit model that replicates intestinal injury, wound healing, and fibrosis observed in human inflammatory bowel disease. In this study, we utilized APC to induce targeted mucosal injuries at multiple, anatomically distinct sites (rectum vs. colon), while preserving the normal colon between sites. The changes in wavelength selection reflect the iterative process of optimizing parameters throughout the study. While the wavelengths varied across the phantom, animal in vivo , and ex vivo tissue studies, the absorption coefficients at the specific wavelength were used to ensure accurate quantitative measurements. Within each experimental phase, the same set of wavelengths was consistently applied to maintain consistency. Moving forward, the optimal wavelength selections identified during this study will be standardized to enhance consistency across future investigations. 5 CONCLUSIONS This study investigated resolving muscle components in the gastrointestinal tract using PA imaging. Studies with phantoms, animal and human tissue samples ex vivo and animals in vivo validated our approach in quantitatively assessing myoglobin content as a measure of muscular hypertrophy. By accurately characterizing the composition of strictures, our approach has the potential to improve treatment strategies, minimize unnecessary surgeries, and enhance monitoring of disease progression. ACKNOWLEDGMENTS This research is supported by the National Institute of Health under grants R37CA222829 and R01DK125687. CONFLICT OF INTEREST The authors declare no financial or commercial conflict of interest. DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request. REFERENCES [1] S. B. Hanauer, ”Inflammatory bowel disease: epidemiology, pathogenesis, and therapeutic opportunities,” Inflammatory bowel diseases, vol. 12, pp. S3-S9, 2006.[2] X. X. Lin, Y. Qiu, X. J. Zhuang, F. Liu, X. M. Wu, M. H. Chen , et al. , ”Intestinal stricture in Crohn’s disease: A 2020 update,” Journal of Digestive Diseases, vol. 22, pp. 390-398, 2021.[3] W. Chen, C. Lu, C. Hirota, M. Iacucci, S. Ghosh, and X. Gui, ”Smooth muscle hyperplasia/hypertrophy is the most prominent histological change in Crohn’s fibrostenosing bowel strictures: a semiquantitative analysis by using a novel histological grading scheme,” Journal of Crohn’s and Colitis, vol. 11, pp. 92-104, 2017.[4] J. H. Yoo, S. Holubar, and F. Rieder, ”Fibrostenotic strictures in Crohn’s disease,” Intest Res, vol. 18, pp. 379-401, 2020.[5] B. Shen, ”Interventional IBD: The Role of Endoscopist in the Multidisciplinary Team Management of IBD,” Inflammatory Bowel Diseases, vol. 24, pp. 298-309, 2018.[6] J. Alfredsson and M. J. Wick, ”Mechanism of fibrosis and stricture formation in Crohn’s disease,” Scandinavian Journal of Immunology, vol. 92, p. e12990, 2020.[7] G. Shelley‐Fraser, N. R. Borley, B. F. Warren, and N. A. Shepherd, ”The connective tissue changes of Crohn’s disease,” Histopathology, vol. 60, pp. 1034-1044, 2012.[8] W. Verla, W. Oosterlinck, A.-F. Spinoit, and M. Waterloos, ”A comprehensive review emphasizing anatomy, etiology, diagnosis, and treatment of male urethral stricture disease,” BioMed research international, vol. 2019, p. 9046430, 2019.[9] X. Lin, Y. Wang, Z. Liu, S. Lin, J. Tan, J. He , et al. , ”Intestinal strictures in Crohn’s disease: a 2021 update,” Therapeutic Advances in Gastroenterology, vol. 15, p. 17562848221104951, 2022.[10] V. Solitano, A. Dal Buono, R. Gabbiadini, M. Wozny, A. Repici, A. Spinelli , et al. , ”Fibro-stenosing Crohn’s disease: what is new and what is next?,” Journal of Clinical Medicine, vol. 12, p. 3052, 2023.[11] D. Bettenworth and F. Rieder, ”Medical therapy of stricturing Crohn’s disease: what the gut can learn from other organs-a systematic review,” Fibrogenesis & tissue repair, vol. 7, pp. 1-16, 2014.[12] S.-N. Lin, R. Mao, C. Qian, D. Bettenworth, J. Wang, J. Li , et al. , ”Development of antifibrotic therapy for stricturing Crohn’s disease: lessons from randomized trials in other fibrotic diseases,” Physiological Reviews, vol. 102, pp. 605-652, 2022.[13] F. Rieder, C. Fiocchi, and G. Rogler, ”Mechanisms, management, and treatment of fibrosis in patients with inflammatory bowel diseases,” Gastroenterology, vol. 152, pp. 340-350. e6, 2017.[14] M. Allocca, G. Fiorino, C. Bonifacio, L. Peyrin-Biroulet, and S. Danese, ”Noninvasive multimodal methods to differentiate inflamed vs fibrotic strictures in patients with Crohn’s disease,” Clinical gastroenterology and hepatology, vol. 17, pp. 2397-2415, 2019.[15] Z. Liu, Z. Huang, Y. Wang, S. Xiong, S. Lin, J. He , et al. , ”Intestinal strictures in Crohn’s disease: An update from 2023,” United European Gastroenterology Journal, 2024.[16] G. Santacroce, M. V. Lenti, and A. Di Sabatino, ”Therapeutic targeting of intestinal fibrosis in Crohn’s disease,” Cells, vol. 11, p. 429, 2022.[17] S. Jarmakiewicz-Czaja, J. Gruszecka, and R. Filip, ”The Diagnosis of Intestinal Fibrosis in Crohn’s Disease—Present and Future,” International Journal of Molecular Sciences, vol. 25, p. 6935, 2024.[18] P. Kathuria, P. D. Higgins, and J. A. Berinstein, ”Timing is everything: The lifesaving potential of early medical therapy in acute severe ulcerative colitis,” Official journal of the American College of Gastroenterology| ACG, vol. 119, pp. 2139-2140, 2024.[19] S. Dandalides, W. Carey, R. Petras, and E. Achkar, ”Endoscopic small bowel mucosal biopsy: a controlled trial evaluating forceps size and biopsy location in the diagnosis of normal and abnormal mucosal architecture,” Gastrointestinal Endoscopy, vol. 35, pp. 197-200, 1989.[20] K. Geboes, ”Histopathology of Crohn’s disease and ulcerative colitis,” Inflammatory bowel disease, vol. 4, pp. 210-28, 2003.[21] S. M. Hong and D. H. Baek, ”Diagnostic Procedures for Inflammatory Bowel Disease: Laboratory, Endoscopy, Pathology, Imaging, and Beyond,” Diagnostics, vol. 14, p. 1384, 2024.[22] B. Kővári, Á. Báthori, M. S. Friedman, and G. Y. Lauwers, ”Histologic diagnosis of inflammatory bowel diseases,” Advances in Anatomic Pathology, vol. 29, pp. 48-61, 2022.[23] K. Kim, L. A. Johnson, C. Jia, J. C. Joyce, S. Rangwalla, P. D. Higgins , et al. , ”Noninvasive ultrasound elasticity imaging (UEI) of Crohn’s disease: animal model,” Ultrasound in medicine & biology, vol. 34, pp. 902-912, 2008.[24] H. Tavares de Sousa and F. Magro, ”How to evaluate fibrosis in IBD?,” Diagnostics, vol. 13, p. 2188, 2023.[25] M. H. P. T. de Sousa, ”Are Crohn’s disease phenotypes a myth? A histopathological and molecular study on transmural fibrosis and inflammation in ileal Crohn’s disease,” 2024.[26] L. Golusda, A. A. Kühl, B. Siegmund, and D. Paclik, ”Extracellular matrix components as diagnostic tools in inflammatory bowel disease,” Biology, vol. 10, p. 1024, 2021.[27] G. K. Makharia, S. Srivastava, P. Das, P. Goswami, U. Singh, M. Tripathi , et al. , ”Clinical, endoscopic, and histological differentiations between Crohn’s disease and intestinal tuberculosis,” Official journal of the American College of Gastroenterology| ACG, vol. 105, pp. 642-651, 2010.[28] T. S. Khor, T. S. Claudtiz, B. Kővári, G. Y. Lauwers, M. B. Wallace, and P. Kumarasinghe, ”Inflammatory Conditions of the Colon,” Gastrointestinal Pathology: Correlative Endoscopic and Histologic Assessment, pp. 235-305, 2021.[29] D. Jenkins, M. Balsitis, S. Gallivan, M. Dixon, H. Gilmour, N. Shepherd , et al. , ”Guidelines for the initial biopsy diagnosis of suspected chronic idiopathic inflammatory bowel disease. The British Society of Gastroenterology Initiative,” Journal of clinical pathology, vol. 50, p. 93, 1997.[30] G. E. Tontini, M. Vecchi, L. Pastorelli, M. F. Neurath, and H. Neumann, ”Differential diagnosis in inflammatory bowel disease colitis: state of the art and future perspectives,” World journal of gastroenterology: WJG, vol. 21, p. 21, 2015.[31] Z. Tarján, G. Tóth, T. Györke, Á. Mester, K. Karlinger, and E. K. Makó, ”Ultrasound in Crohn’s disease of the small bowel,” European Journal of Radiology, vol. 35, pp. 176-182, 2000.[32] M. Boudiaf, P. Soyer, C. Terem, J. P. Pelage, E. Maissiat, and R. Rymer, ”CT Evaluation of Small Bowel Obstruction,” RadioGraphics, vol. 21, pp. 613-624, 2001/05/01 2001.[33] P. Paolantonio, R. Ferrari, F. Vecchietti, S. Cucchiara, and A. Laghi, ”Current status of MR imaging in the evaluation of IBD in a pediatric population of patients,” European Journal of Radiology, vol. 69, pp. 418-424, 2009.[34] A.-J. Greenup, B. Bressler, and G. Rosenfeld, ”Medical imaging in small bowel Crohn’s disease—computer tomography enterography, magnetic resonance enterography, and ultrasound:“which one is the best for what?”,” Inflammatory bowel diseases, vol. 22, pp. 1246-1261, 2016.[35] W. A. Faubion Jr, E. V. Loftus Jr, W. S. Harmsen, A. R. Zinsmeister, and W. J. Sandborn, ”The natural history of corticosteroid therapy for inflammatory bowel disease: a population-based study,” Gastroenterology, vol. 121, pp. 255-260, 2001.[36] 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,” Nature biotechnology, vol. 21, pp. 803-806, 2003.[37] B. Cox, J. G. Laufer, S. R. Arridge, and P. C. Beard, ”Quantitative spectroscopic photoacoustic imaging: a review,” Journal of biomedical optics, vol. 17, pp. 061202-061202, 2012.[38] L. V. Wang and S. Hu, ”Photoacoustic tomography: in vivo imaging from organelles to organs,” science, vol. 335, pp. 1458-1462, 2012.[39] H. Lei, L. A. Johnson, S. Liu, D. S. Moons, T. Ma, Q. Zhou , et al. , ”Characterizing intestinal inflammation and fibrosis in Crohn’s disease by photoacoustic imaging: feasibility study,” Biomedical optics express, vol. 7, pp. 2837-2848, 2016.[40] H. Lei, L. A. Johnson, K. A. Eaton, S. Liu, J. Ni, X. Wang , et al. , ”Characterizing intestinal strictures of Crohn’s disease in vivo by endoscopic photoacoustic imaging,” Biomedical optics express, vol. 10, pp. 2542-2555, 2019.[41] Y. Zhu, L. Ni, G. Hu, L. A. Johnson, K. A. Eaton, X. Wang , et al. , ”Prototype endoscopic photoacoustic-ultrasound balloon catheter for characterizing intestinal obstruction,” Biomedical Optics Express, vol. 13, pp. 3355-3365, 2022.[42] Y. Zhu, L. A. Johnson, J. M. Rubin, H. Appelman, L. Ni, J. Yuan , et al. , ”Strain-Photoacoustic Imaging as a Potential Tool for Characterizing Intestinal Fibrosis,” Gastroenterology, vol. 157, pp. 1196-1198, 2019.[43] L. Li, M. I. Itani, K. J. Salimian, Y. Li, O. B. Gutierrez, H. Hu , et al. , ”A patient-like swine model of gastrointestinal fibrotic strictures for advancing therapeutics,” Scientific reports, vol. 11, p. 13344, 2021.[44] L. Lin, J. Yao, L. Li, and L. Wang, ”In vivo photoacoustic tomography of myoglobin oxygen saturation,” Journal of Biomedical Optics, vol. 21, p. 061002, 2015.[45] D. F. Swinehart, ”The Beer-Lambert Law,” Journal of Chemical Education, vol. 39, p. 333, July 01, 1962 1962.[46] H. Lei, L. A. Johnson, S. Liu, D. S. Moons, T. Ma, Q. Zhou , et al. , ”Characterizing intestinal inflammation and fibrosis in Crohn’s disease by photoacoustic imaging: feasibility study,” Biomedical Optics Express, vol. 7, pp. 2837-2848, 2016/07/01 2016.[47] H.-W. Wang, N. Chai, P. Wang, S. Hu, W. Dou, D. Umulis , et al. , ”Label-Free Bond-Selective Imaging by Listening to Vibrationally Excited Molecules,” Physical Review Letters, vol. 106, p. 238106, 2011.[48] L. Li, M. I. Itani, K. J. Salimian, Y. Li, O. B. Gutierrez, H. Hu , et al. , ”A patient-like swine model of gastrointestinal fibrotic strictures for advancing therapeutics,” Sci Rep, vol. 11, p. 13344, Jun 25 2021.[49] Y. Zhu, L. Ni, G. Hu, L. A. Johnson, K. A. Eaton, X. Wang , et al. , ”Prototype endoscopic photoacoustic-ultrasound balloon catheter for characterizing intestinal obstruction,” Biomedical Optics Express, vol. 13, pp. 3355-3365, 2022/06/01 2022. [1] S. B. Hanauer, ”Inflammatory bowel disease: epidemiology, pathogenesis, and therapeutic opportunities,” Inflammatory bowel diseases, vol. 12, no. suppl_1, pp. S3-S9, 2006. [2] W. Chen, C. Lu, C. Hirota, M. Iacucci, S. Ghosh, and X. Gui, ”Smooth muscle hyperplasia/hypertrophy is the most prominent histological change in Crohn’s fibrostenosing bowel strictures: a semiquantitative analysis by using a novel histological grading scheme,” Journal of Crohn’s and Colitis, vol. 11, no. 1, pp. 92-104, 2017. [3] J. H. Yoo, S. Holubar, and F. Rieder, ”Fibrostenotic strictures in Crohn’s disease,” Intest Res, vol. 18, no. 4, pp. 379-401, 2020. [4] B. Shen, ”Interventional IBD: The Role of Endoscopist in the Multidisciplinary Team Management of IBD,” Inflammatory Bowel Diseases, vol. 24, no. 2, pp. 298-309, 2018, doi: 10.1093/ibd/izx058. [5] J. Alfredsson and M. J. Wick, ”Mechanism of fibrosis and stricture formation in Crohn’s disease,” Scandinavian Journal of Immunology, vol. 92, no. 6, p. e12990, 2020. [6] G. Shelley‐Fraser, N. R. Borley, B. F. Warren, and N. A. Shepherd, ”The connective tissue changes of Crohn’s disease,” Histopathology, vol. 60, no. 7, pp. 1034-1044, 2012. [7] W. Verla, W. Oosterlinck, A.-F. Spinoit, and M. Waterloos, ”A comprehensive review emphasizing anatomy, etiology, diagnosis, and treatment of male urethral stricture disease,” BioMed research international, vol. 2019, no. 1, p. 9046430, 2019. [8] X. Lin et al., ”Intestinal strictures in Crohn’s disease: a 2021 update,” Therapeutic Advances in Gastroenterology, vol. 15, p. 17562848221104951, 2022. [9] V. Solitano et al., ”Fibro-stenosing Crohn’s disease: what is new and what is next?,” Journal of Clinical Medicine, vol. 12, no. 9, p. 3052, 2023. [10] D. Bettenworth and F. Rieder, ”Medical therapy of stricturing Crohn’s disease: what the gut can learn from other organs-a systematic review,” Fibrogenesis & tissue repair, vol. 7, pp. 1-16, 2014. [11] S.-N. Lin et al., ”Development of antifibrotic therapy for stricturing Crohn’s disease: lessons from randomized trials in other fibrotic diseases,” Physiological Reviews, vol. 102, no. 2, pp. 605-652, 2022. [12] F. Rieder, C. Fiocchi, and G. Rogler, ”Mechanisms, management, and treatment of fibrosis in patients with inflammatory bowel diseases,” Gastroenterology, vol. 152, no. 2, pp. 340-350. e6, 2017. [13] M. Allocca, G. Fiorino, C. Bonifacio, L. Peyrin-Biroulet, and S. Danese, ”Noninvasive multimodal methods to differentiate inflamed vs fibrotic strictures in patients with Crohn’s disease,” Clinical gastroenterology and hepatology, vol. 17, no. 12, pp. 2397-2415, 2019. [14] Z. Liu et al., ”Intestinal strictures in Crohn’s disease: An update from 2023,” United European Gastroenterology Journal, 2024. [15] G. Santacroce, M. V. Lenti, and A. Di Sabatino, ”Therapeutic targeting of intestinal fibrosis in Crohn’s disease,” Cells, vol. 11, no. 3, p. 429, 2022. [16] S. Jarmakiewicz-Czaja, J. Gruszecka, and R. Filip, ”The Diagnosis of Intestinal Fibrosis in Crohn’s Disease—Present and Future,” International Journal of Molecular Sciences, vol. 25, no. 13, p. 6935, 2024. [17] P. Kathuria, P. D. Higgins, and J. A. Berinstein, ”Timing is everything: The lifesaving potential of early medical therapy in acute severe ulcerative colitis,” Official journal of the American College of Gastroenterology| ACG, vol. 119, no. 10, pp. 2139-2140, 2024. [18] S. Dandalides, W. Carey, R. Petras, and E. Achkar, ”Endoscopic small bowel mucosal biopsy: a controlled trial evaluating forceps size and biopsy location in the diagnosis of normal and abnormal mucosal architecture,” Gastrointestinal endoscopy, vol. 35, no. 3, pp. 197-200, 1989. [19] K. Geboes, ”Histopathology of Crohn’s disease and ulcerative colitis,” Inflammatory bowel disease, vol. 4, pp. 210-28, 2003. [20] S. M. Hong and D. H. Baek, ”Diagnostic Procedures for Inflammatory Bowel Disease: Laboratory, Endoscopy, Pathology, Imaging, and Beyond,” Diagnostics, vol. 14, no. 13, p. 1384, 2024. [21] B. Kővári, Á. Báthori, M. S. Friedman, and G. Y. Lauwers, ”Histologic diagnosis of inflammatory bowel diseases,” Advances in Anatomic Pathology, vol. 29, no. 1, pp. 48-61, 2022. [22] K. Kim et al., ”Noninvasive ultrasound elasticity imaging (UEI) of Crohn’s disease: animal model,” Ultrasound in medicine & biology, vol. 34, no. 6, pp. 902-912, 2008. [23] H. Tavares de Sousa and F. Magro, ”How to evaluate fibrosis in IBD?,” Diagnostics, vol. 13, no. 13, p. 2188, 2023. [24] M. H. P. T. de Sousa, ”Are Crohn’s disease phenotypes a myth? A histopathological and molecular study on transmural fibrosis and inflammation in ileal Crohn’s disease,” 2024. [25] L. Golusda, A. A. Kühl, B. Siegmund, and D. Paclik, ”Extracellular matrix components as diagnostic tools in inflammatory bowel disease,” Biology, vol. 10, no. 10, p. 1024, 2021. [26] G. K. Makharia et al., ”Clinical, endoscopic, and histological differentiations between Crohn’s disease and intestinal tuberculosis,” Official journal of the American College of Gastroenterology| ACG, vol. 105, no. 3, pp. 642-651, 2010. [27] T. S. Khor, T. S. Claudtiz, B. Kővári, G. Y. Lauwers, M. B. Wallace, and P. Kumarasinghe, ”Inflammatory Conditions of the Colon,” Gastrointestinal Pathology: Correlative Endoscopic and Histologic Assessment, pp. 235-305, 2021. [28] D. Jenkins et al., ”Guidelines for the initial biopsy diagnosis of suspected chronic idiopathic inflammatory bowel disease. The British Society of Gastroenterology Initiative,” Journal of clinical pathology, vol. 50, no. 2, p. 93, 1997. [29] G. E. Tontini, M. Vecchi, L. Pastorelli, M. F. Neurath, and H. Neumann, ”Differential diagnosis in inflammatory bowel disease colitis: state of the art and future perspectives,” World journal of gastroenterology: WJG, vol. 21, no. 1, p. 21, 2015. [30] Z. Tarján, G. Tóth, T. Györke, Á. Mester, K. Karlinger, and E. K. Makó, ”Ultrasound in Crohn’s disease of the small bowel,” European journal of radiology, vol. 35, no. 3, pp. 176-182, 2000. [31] M. Boudiaf, P. Soyer, C. Terem, J. P. Pelage, E. Maissiat, and R. Rymer, ”CT evaluation of small bowel obstruction,” Radiographics, vol. 21, no. 3, pp. 613-624, 2001. [32] P. Paolantonio, R. Ferrari, F. Vecchietti, S. Cucchiara, and A. Laghi, ”Current status of MR imaging in the evaluation of IBD in a pediatric population of patients,” European journal of radiology, vol. 69, no. 3, pp. 418-424, 2009. [33] A.-J. Greenup, B. Bressler, and G. Rosenfeld, ”Medical imaging in small bowel Crohn’s disease—computer tomography enterography, magnetic resonance enterography, and ultrasound:“which one is the best for what?”,” Inflammatory bowel diseases, vol. 22, no. 5, pp. 1246-1261, 2016. [34] W. A. Faubion Jr, E. V. Loftus Jr, W. S. Harmsen, A. R. Zinsmeister, and W. J. Sandborn, ”The natural history of corticosteroid therapy for inflammatory bowel disease: a population-based study,” Gastroenterology, vol. 121, no. 2, pp. 255-260, 2001. [35] 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,” Nature biotechnology, vol. 21, no. 7, pp. 803-806, 2003. [36] B. Cox, J. G. Laufer, S. R. Arridge, and P. C. Beard, ”Quantitative spectroscopic photoacoustic imaging: a review,” Journal of biomedical optics, vol. 17, no. 6, pp. 061202-061202, 2012. [37] L. V. Wang and S. Hu, ”Photoacoustic tomography: in vivo imaging from organelles to organs,” science, vol. 335, no. 6075, pp. 1458-1462, 2012. [38] H. Lei et al., ”Characterizing intestinal inflammation and fibrosis in Crohn’s disease by photoacoustic imaging: feasibility study,” Biomedical optics express, vol. 7, no. 7, pp. 2837-2848, 2016. [39] H. Lei et al., ”Characterizing intestinal strictures of Crohn’s disease in vivo by endoscopic photoacoustic imaging,” Biomedical optics express, vol. 10, no. 5, pp. 2542-2555, 2019. [40] Y. Zhu et al., ”Prototype endoscopic photoacoustic-ultrasound balloon catheter for characterizing intestinal obstruction,” Biomedical Optics Express, vol. 13, no. 6, pp. 3355-3365, 2022. [41] L. Li et al., ”A patient-like swine model of gastrointestinal fibrotic strictures for advancing therapeutics,” Scientific reports, vol. 11, no. 1, p. 13344, 2021. [42] L. Lin, J. Yao, L. Li, and L. Wang, ”In vivo photoacoustic tomography of myoglobin oxygen saturation,” Journal of Biomedical Optics, vol. 21, no. 6, p. 061002, 2015. [Online]. Available: https://doi.org/10.1117/1.JBO.21.6.061002. [43] D. F. Swinehart, ”The Beer-Lambert Law,” Journal of Chemical Education, vol. 39, p. 333, July 01, 1962 1962, doi: 10.1021/ed039p333. [44] L. Li et al., ”A patient-like swine model of gastrointestinal fibrotic strictures for advancing therapeutics,” (in eng), Sci Rep, vol. 11, no. 1, p. 13344, Jun 25 2021, doi: 10.1038/s41598-021-92628-8. [45] Y. Zhu et al., ”Prototype endoscopic photoacoustic-ultrasound balloon catheter for characterizing intestinal obstruction,” Biomedical Optics Express, vol. 13, no. 6, pp. 3355-3365, 2022/06/01 2022, doi: 10.1364/BOE.456672. Information & Authors Information Version history V1 Version 1 19 September 2025 Peer review timeline Published Journal of Biophotonics Version of Record 11 Feb 2026 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords argon plasma coagulation inflammatory bowel disease photoacoustic/ultrasound imaging spectral unmixing Authors Affiliations Xiaorui Peng [email protected] University of Michigan Department of Biomedical Engineering View all articles by this author Linyu Ni University of Michigan Department of Biomedical Engineering View all articles by this author Laura Johnson University of Michigan Department of Internal Medicine View all articles by this author Yaocai Huang University of Michigan Department of Biomedical Engineering View all articles by this author Wei Zhang University of Michigan Department of Biomedical Engineering View all articles by this author Xueding Wang University of Michigan Department of Biomedical Engineering View all articles by this author Peter D.R. Higgins University of Michigan Department of Internal Medicine View all articles by this author Guan Xu 0000-0002-5942-7987 University of Michigan Department of Biomedical Engineering View all articles by this author Metrics & Citations Metrics Article Usage 302 views 149 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Xiaorui Peng, Linyu Ni, Laura Johnson, et al. Characterizing muscle components in intestinal strictures using spectroscopic photoacoustic imaging. Authorea . 19 September 2025. DOI: https://doi.org/10.22541/au.175827451.12997054/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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