Journal of Biomedical Optics最新文献

{"title":"Superconducting nanowire single-photon detectors for enhanced biomedical imaging.","authors":"Emi Cora Valmai Hughes, Avinash Upadhya, Kishan Dholakia","doi":"10.1117/1.JBO.31.11.113502","DOIUrl":"10.1117/1.JBO.31.11.113502","url":null,"abstract":"<p><strong>Significance: </strong>Superconducting nanowire single-photon detectors (SNSPDs; also known as SSPDs) show enormous promise for low-light biomedical imaging by offering exceptional sensitivity, picosecond timing resolution, and broad spectral coverage.</p><p><strong>Aim: </strong>This perspective evaluates the role of SNSPDs by comparing their performance with other photon-counting detectors for emerging biomedical imaging applications.</p><p><strong>Approach: </strong>We describe the need for ultrasensitive detectors for biophotonics, summarize SNSPD operating principles, and compare their performance with established photon-counting devices. We highlight applications where SNSPDs make previously unattainable imaging capabilities possible and discuss system-level challenges and technological developments that are critical to future applications, including clinical translation.</p><p><strong>Results: </strong>SNSPDs offer advantages in signal-to-noise ratio, temporal precision, and detection bandwidth, enabling deep tissue imaging, high-precision fluorescence lifetime measurements, and quantum-enhanced imaging modalities. Advances in scalable arrays, cryogenic miniaturization, and improved signal collection are reducing barriers to widespread adoption.</p><p><strong>Conclusions: </strong>SNSPDs are poised to transform photon-limited biomedical imaging. As device performance and system integration continue to advance, their adoption in imaging platforms is expected to accelerate. Combining SNSPDs with advancements in the excitation pathway, such as structured-light excitation with Bessel beams, aberration correction, and wavefront shaping, shows promise for delivering unprecedented imaging capabilities and broadening both the preclinical and clinical utility of these detectors.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"31 11","pages":"113502"},"PeriodicalIF":3.3,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13012184/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147512268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biophotonics point-of-care diagnostics in low-resource settings: a South African perspective.","authors":"Patience Mthunzi-Kufa, Morongwa Mary Mathipa, Tendai Makwikwi, Mellisa Brenda Sagandira, Moses Wabwile Juma, Degratious Kgoale, Nkgaphe Tsebesebe","doi":"10.1117/1.JBO.31.11.113506","DOIUrl":"10.1117/1.JBO.31.11.113506","url":null,"abstract":"<p><strong>Significance: </strong>Point-of-care (POC) diagnostics based on photonics and biophotonics technologies hold transformative potential for healthcare delivery in peri-urban and underdeveloped settings, combining optical sensitivity with portability, rapid readout, and minimal consumable requirements.</p><p><strong>Aim: </strong>We aim to synthesize design considerations and recent advances that align photonics-based POC devices with the World Health Organization's ASSURED/REASSURED framework, emphasizing affordability, sensitivity, ease of use, rapidity, robustness, equipment-free operation where possible, deliverability, and the added priorities of real-time connectivity and environmental sustainability.</p><p><strong>Approach: </strong>We examine implementation evidence from sub-Saharan Africa, highlighting gaps in field validation, quality assurance, and sustainability identified by recent scoping reviews, as well as the persistent need for context-adapted usability and training strategies. Advances covered include miniaturized optical biosensors (fluorescence, Raman, and photothermal modalities), smartphone-integrated microscopy and spectroscopy, low-cost LASER/LED illumination systems, and multiplexed lateral-flow/optical hybrids, all tailored for low-resource constraints.</p><p><strong>Results: </strong>We discuss how digitization and connected diagnostics (including data standards, mobile health integration, and secure cloud reporting) amplify clinical impact, enable surveillance, and support task-shifting in primary care, aligning with South Africa's National Digital Health Strategy. We also survey regional innovation capacity, with examples of locally focused development and prototyping that demonstrate pathways to regional manufacturing and deployment.</p><p><strong>Conclusions: </strong>We conclude with recommendations for regulatory-science partnerships, human-centred design, interoperable digital pipelines, and investment in field-based validation and manufacturing to translate photonics innovations into resilient, equitable POC solutions across South Africa and the wider sub-Saharan context.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"31 11","pages":"113506"},"PeriodicalIF":3.3,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13618995/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149074860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatio-temporally modulated fluorescence imager for intraoperative nerve identification.","authors":"Jesung Park, Hyejin Yoo, Samuel S Streeter, John Grimble, Mark T Scimone, Gopi Maguluri, Jeffrey L Campbell, Madelyn O'Shaughnessy, Nicusor Iftimia, Eric R Henderson, Brian W Pogue, Youbo Zhao","doi":"10.1117/1.JBO.31.10.106001","DOIUrl":"https://doi.org/10.1117/1.JBO.31.10.106001","url":null,"abstract":"<p><strong>Significance: </strong>Fluorescence-guided surgery (FGS) based on nerve-labeling agents has the potential to enhance nerve identification during various operational procedures including orthopedic, craniofacial, and otolaryngological surgeries that involve complex and delicate nerve structures. A major challenge in FGS is the adverse impact of strong ambient light, which interferes with weak fluorescence signals, especially at visible wavelengths. Currently, this issue is mitigated by dimming or turning off the operating room (OR) lights during the fluorescence imaging procedure. However, this causes substantial disruption to the surgical workflow and reduces the potential for clinical adoption of FGS technologies.</p><p><strong>Aim: </strong>In this work, we develop a novel intraoperative fluorescence imager that is based on a spatio-temporal modulation (STM) approach to suppress interference from strong OR lights.</p><p><strong>Approach: </strong>The STM technology employed a line-scan imaging scheme that encodes the fluorescence signal into a distinctive spatial frequency within a narrow time window. By applying spatial frequency demodulation and time-gating methods, the imager effectively extracted the fluorescence signals by rejecting temporally constant and spatially uniform background OR lights.</p><p><strong>Results: </strong>The performance of the imager in detecting nerve structures in realistic OR lighting conditions was validated during <i>in vivo</i> animal studies. Additional evaluation using <i>ex vivo</i> human nerve tissue specimens and perfused amputated human limbs further supported the clinical suitability and readiness.</p><p><strong>Conclusions: </strong>This innovative imaging technology enables high-contrast fluorescence visualization of nerve tissue under standard OR lighting and represents a significant step toward practical clinical implementation of FGS for enhanced nerve identification.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"31 10","pages":"106001"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13630344/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149110266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SEFCA-Net: a semantic-edge-frequency cross-attention network for diabetic retinopathy lesion segmentation.","authors":"Jin Xie, Jingtao Wang, Duo Xu, Yuzhong Peng, Kunlong Wu, Fangning Gu, Xue Zhang, Zhizhong Zhang, Xinjian Chen, Jianping Liao","doi":"10.1117/1.JBO.31.10.106002","DOIUrl":"10.1117/1.JBO.31.10.106002","url":null,"abstract":"<p><strong>Significance: </strong>Diabetic retinopathy (DR) lesion segmentation provides pixel-level lesion localization in fundus images. However, such lesions are often tiny, sparsely distributed, low-contrast, morphologically diverse, and visually similar to vessels or surrounding retinal structures, making accurate localization difficult. Many existing methods emphasize multi-scale spatial representation learning and handle boundary ambiguity and subtle texture differences mainly through encoder-decoder fusion. We therefore examine boundary and frequency representations as explicit, complementary inputs to semantic decoding.</p><p><strong>Aim: </strong>We aim to develop SEFCA-Net, a semantic-edge-frequency cross-attention network for diabetic retinopathy lesion segmentation. The main objective is to examine whether semantic, edge, and frequency-domain representations can be fused under semantic guidance to improve pixel-level lesion localization without compromising the semantic decoding stream. The evaluation focuses on four lesion categories, including hard exudates, hemorrhages, soft exudates, and microaneurysms, using public benchmarks and a DDR-to-IDRiD cross-dataset setting.</p><p><strong>Approach: </strong>SEFCA-Net uses HRNet-W48 as the semantic backbone to extract multi-scale semantic features and explicitly constructs edge and frequency-domain representations from input fundus images. The learnable multi-scale edge branch extracts boundary-sensitive features, while the all-channel multi-scale discrete cosine transform (DCT) frequency-domain branch generates texture-sensitive responses to low-contrast lesions. The semantic-edge-frequency cross-attention decoder uses the semantic representation as the primary stream and injects edge and frequency-domain features through semantic-guided window-based cross-attention. Performance is evaluated using the area under the precision-recall curve (AUPR), Dice, and Intersection-over-Union (IoU).</p><p><strong>Results: </strong>On DDR, SEFCA-Net achieves 47.85% mean AUPR (mAUPR), 46.76% mean Dice, and 31.22% mean IoU. On IDRiD, it reaches 69.74% mAUPR; when trained on DDR and tested on IDRiD, it obtains 59.83% mAUPR. Ablation studies show that either auxiliary branch improves the semantic-only baseline and that the complete configuration gives the highest mAUPR. Multi-scale Sobel modeling and DCT outperform the tested single-scale and wavelet alternatives, respectively.</p><p><strong>Conclusions: </strong>SEFCA-Net shows that semantic features can remain the main decoding stream while boundary-sensitive features and texture-sensitive responses are integrated in a controlled manner. Under the evaluated protocols, the model shows competitive in-domain performance and records the highest DDR-to-IDRiD mAUPR among the reproduced methods.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"31 10","pages":"106002"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13649286/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149136914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intraoperative margin assessment in colorectal cancer via AI-enhanced multiphoton microscopy.","authors":"Qiaoyu Lai, Zilu Lin, Gangqin Xi, Jiajia He, Guangxing Wang, Jun Zhang, Shuangmu Zhuo, Jian Sui","doi":"10.1117/1.JBO.31.10.106501","DOIUrl":"https://doi.org/10.1117/1.JBO.31.10.106501","url":null,"abstract":"<p><strong>Significance: </strong>Identifying residual tumors at the resection margins is crucial for individuals undergoing colorectal cancer (CRC) surgery. Accurate margin assessment can help minimize residual tumor while avoiding unnecessary removal of healthy tissue.</p><p><strong>Aim: </strong>This study uses label-free multiphoton microscopy to visualize collagen architecture and develops a feature-enhanced deep-learning model to distinguish CRC from margin-adjacent normal tissue.</p><p><strong>Approach: </strong>Margin-adjacent normal and carcinoma tissues were imaged using multiphoton microscopy, and 142 quantitative collagen features were extracted from SHG images. We propose PVT-Enhanced, a feature-fusion model that integrates handcrafted collagen features with deep image features derived from PVTv2-b5 through an attention-based fusion strategy. Its performance was compared with LASSO-LR, three convolutional neural networks, and image-only PVTv2-b5.</p><p><strong>Results: </strong>SHG imaging showed relatively coherent fiber orientation, longer and more continuous collagen fibers, and higher fiber density in margin-adjacent normal tissue, whereas carcinoma tissue showed more disorganized orientation, shorter and more fragmented fibers, and lower fiber density. The PVT-Enhanced model achieved an accuracy of 86.9%, an AUC of 0.923, and a specificity of 96.4%. Only 5 of 137 margin-adjacent normal images were misclassified as CRC.</p><p><strong>Conclusions: </strong>Our findings suggest that the PVT-Enhanced framework combined with SHG imaging allows accurate, rapid, and label-free tissue characterization that may support intraoperative margin assessment in CRC surgery.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"31 10","pages":"106501"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13652112/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149166327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phase-aberration-corrected coherence factor beamforming for photoacoustic computed tomography.","authors":"Xiali Gao, Zhichao Zheng, Zhibo Xiao, Xu Sun, Nuomin Zhang, Yang Xiao, Hao Huang, Xuran Zhou, Fan Meng, Xuanhao Wang, Ruimin Chen, Junhui Shi","doi":"10.1117/1.JBO.31.10.106003","DOIUrl":"https://doi.org/10.1117/1.JBO.31.10.106003","url":null,"abstract":"<p><strong>Significance: </strong>Coherence factor (CF) beamforming can suppress sidelobes in photoacoustic computed tomography, but phase aberration can make genuine absorbers appear incoherent and cause conventional CF to downweight real signals.</p><p><strong>Aim: </strong>We aim to reduce photoacoustic volume tomography phase-aberration-induced loss of true signals in conventional coherence-factor reconstruction and validate the method using phantom and <i>in vivo</i> experiments.</p><p><strong>Approach: </strong>PAC-CF extends an ellipsoidal two-region time-of-flight correction to the angle-weighted channel contributions used for both coherent backprojection and final conventional energy-ratio CF evaluation. The ROI-optimized effective internal sound speed is selected from multiframe PA receive data by maximizing the mean CF within a fixed region of interest.</p><p><strong>Results: </strong>Simulations showed that conventional CF at the true source dropped to 0.00794 at a <math><mrow><mn>170</mn> <mtext>  </mtext> <mi>m</mi> <mo>/</mo> <mi>s</mi></mrow> </math> sound-speed difference and to <math><mrow><mo>∼</mo> <mn>0.00039</mn></mrow> </math> to 0.00042 at larger sound-speed differences, whereas PAC-CF preserved coherence and localization. The four-method phantom ablation showed that combining two-region TOF correction with final CF weighting produced the most concentrated wire responses and strongest background suppression, whereas mouse experiments showed recovery of vascular features suppressed by conventional CF.</p><p><strong>Conclusions: </strong>By extending two-region time-of-flight correction to the channel contributions evaluated by the final CF weight, PAC-CF reduces the erroneous suppression of true signals caused by propagation-model mismatch and provides a practical PA-only approach for coherence-weighted three-dimensional PACT.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"31 10","pages":"106003"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13652113/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149167352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial optimization of transthoracic diffuse optics for myocardial ischemia in mice: a Monte Carlo study.","authors":"Tao Yang, Guangqi Chen, Danni Wei, Yongle Wang, Sifan Chen, Jiayu Hu, Le Pan, Henggui Zhang, Li Wang, Jin Li, Weichao Liu","doi":"10.1117/1.JBO.31.10.105001","DOIUrl":"10.1117/1.JBO.31.10.105001","url":null,"abstract":"<p><strong>Significance: </strong>Continuous, noninvasive assessment of myocardial ischemia in intact mouse models poses a significant technical challenge. Conventional diffuse optical techniques are mostly limited to <i>ex vivo</i> hearts or open-chest animal models due to severe signal attenuation and tissue interference caused by the complex thoracic anatomy. Empirical placement of photoelectric probes over the cardiothorax further undermines the sensitivity and specificity of cardiac signal detection.</p><p><strong>Aim: </strong>This study aims to systematically characterize photon transport dynamics within the mouse thorax, determine the optimal light Source-Detector (S-D) spatial configuration, and quantitatively evaluate the theoretical feasibility of transthoracic diffuse optics for detecting varying degrees of myocardial ischemia.</p><p><strong>Approach: </strong>Using a high-fidelity 3D voxelized model derived from realistic mouse anatomical data, we performed Monte Carlo photon transport simulations at 800 nm. A high-density virtual array of sources and detectors was deployed on the body surface to determine the optimal S-D positions for cardiac signal extraction. Myocardial ischemia was simulated by modulating the optical coefficients of myocardial tissue, enabling the investigation of the relationship between surface-captured optical signals and ischemia severity.</p><p><strong>Results: </strong>The simulations identified an optimized S-D configuration that maximizes the detection sensitivity for deep myocardial signals while minimizing interference from overlying tissues. Notably, under this configuration, the diffuse optical signals collected at the body surface showed a strong linear correlation with the degree of myocardial ischemia.</p><p><strong>Conclusions: </strong>An optimized S-D configuration was demonstrated for establishing a linear correlation between optical signal variations and ischemic severity. This study provides a theoretical framework toward diffuse optics for <i>in vivo</i> assessment of cardiac hemodynamics and tissue oxygenation in murine models.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"31 10","pages":"105001"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13667762/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149194076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of volumetric dynamic optical coherence tomography with biological methods for evaluation of radiation effects in prostate tumor spheroids.","authors":"Steph Swanson, Keyu Chen, Elahe Cheraghi, Ernest Osei, Kostadinka Bizheva","doi":"10.1117/1.JBO.31.10.106004","DOIUrl":"https://doi.org/10.1117/1.JBO.31.10.106004","url":null,"abstract":"<p><strong>Significance: </strong>Three-dimensional (3D) tumor spheroids are more physiologically representative of <i>in vivo</i> patient tumors compared with two-dimensional monolayer culture. However, their 3D nature challenges the use of conventional biological techniques such as proliferation assays, fluorescence microscopy, and the clonogenic assay, which is the gold standard method for assessing cell survival following radiation. However, the clonogenic assay requires spheroid disaggregation.</p><p><strong>Aim: </strong>Non-invasive volumetric imaging with dynamic optical coherence tomography (dOCT) enables cellular activity to be visualized with spatial resolution within 3D tumor spheroids. Cellular activity observed via dOCT in irradiated prostate tumor spheroids was quantified for comparison with conventional biological techniques.</p><p><strong>Approach: </strong>A Varian TrueBeam linear accelerator was used to irradiate spheroid and monolayer cultures with a 6-MV beam. Cellular activity was estimated from dOCT images generated via frequency banding and compared with clonogenic assay, proliferation assay, fluorescence microscopy, and 3D cell simulation.</p><p><strong>Results: </strong>Prostate cancer cells cultured as spheroids demonstrated improved radio-resistance via clonogenic assay compared with monolayer culture. The dOCT method demonstrated quantitative and qualitative agreement with the proliferation assay and fluorescence microscopy, respectively.</p><p><strong>Conclusions: </strong>A longer duration of repeated dOCT measurement in tumor spheroids following radiation treatment could offer a non-invasive alternative to the clonogenic assay.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"31 10","pages":"106004"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13660629/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149182128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geometric decoupling of epidermal melanin and dermal hemoglobin signals using coaxial and spatially resolved NIRS.","authors":"Vedanshi Patel, Devang Vyas, John Hanks, Amir Tofighi Zavareh","doi":"10.1117/1.JBO.31.10.107001","DOIUrl":"10.1117/1.JBO.31.10.107001","url":null,"abstract":"<p><strong>Significance: </strong>Epidermal melanin can confound NIRS measurements of tissue oxygen saturation and reduce accuracy across skin tones.</p><p><strong>Aim: </strong>We evaluated whether a coaxial detector can provide a superficial reference that improves absolute <math> <mrow><msub><mi>StO</mi> <mn>2</mn></msub> </mrow> </math> estimation when combined with spatially resolved measurements.</p><p><strong>Approach: </strong>Monte Carlo simulations of multilayer skin were evaluated using mutual information and XGBoost regression, with entire melanin levels held out during validation. Three detector configurations were compared: coaxial only, surface only, and the combined geometry. A secondary experimental analysis examined absolute and baseline referenced oxygenation prediction using validation that excluded one recording at a time.</p><p><strong>Results: </strong>The combined coaxial plus surface detector configuration reduced average <math> <mrow><msub><mi>StO</mi> <mn>2</mn></msub> </mrow> </math> RMSE from 11.34 to 5.41 percentage points, corresponding to a 52.3% relative reduction based on the displayed fold results. Mutual information analysis showed that the coaxial detector carried substantial information about melanin while carrying negligible direct information about <math> <mrow><msub><mi>StO</mi> <mn>2</mn></msub> </mrow> </math> . In the experimental analysis, baseline-referenced features improved pooled agreement, but the recording-based validation did not establish generalization to entirely unseen participants.</p><p><strong>Conclusions: </strong>These findings support future experimental validation of integrated coaxial plus spatially resolved probes for melanin-robust absolute tissue oxygenation monitoring.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"31 10","pages":"107001"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13648949/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149136875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MLDT: an open-source multilayer diffusion theory Python implementation.","authors":"Thomas T Livecchi, Mark C Pierce, Steven L Jacques","doi":"10.1117/1.JBO.31.9.095006","DOIUrl":"10.1117/1.JBO.31.9.095006","url":null,"abstract":"<p><strong>Significance: </strong>Diffuse reflectance spectroscopy and imaging are powerful noninvasive tools for quantifying tissue biomarkers such as hemoglobin, melanin, and water. A theoretical model of light propagation is required to interpret these reflectance measurements and translate them into quantitative biomarker concentrations. Although Monte Carlo (MC) simulations offer the gold-standard in accuracy, their high computational burden renders them impractical for real-time iterative inverse solving. Conversely, standard analytical approximations can be efficient but often oversimplify tissue as a semi-infinite homogeneous medium, leading to significant errors when analyzing layered structures.</p><p><strong>Aim: </strong>We aim to develop a generalized, computationally efficient forward model capable of rapidly predicting light transport in complex, multilayered tissue structures.</p><p><strong>Approach: </strong>We present a generalized derivation and open-source Python implementation of the P1 diffusion approximation for predicting diffuse reflectance from tissue with an arbitrary number of layers. This framework utilizes a vectorized banded matrix approach to solve the fluence rate equations efficiently. The model was validated against 400 randomized MC simulations encompassing architectures ranging from one to eight layers.</p><p><strong>Results: </strong>Diffuse reflectance spectra predicted by the generalized multilayer diffusion theory model show strong agreement with MC simulations in the diffusion regime ( <math> <mrow> <msub><mrow><mi>μ</mi></mrow> <mrow><mi>a</mi></mrow> </msub> <mo>≪</mo> <msubsup><mrow><mi>μ</mi></mrow> <mrow><mi>s</mi></mrow> <mrow><mo>'</mo></mrow> </msubsup> </mrow> </math> ), achieving a median spectral root mean square error of 0.0145 across the validation set. Computation times were over 5 orders of magnitude faster than GPU-accelerated MC, yielding a mean calculation time of 0.0087 s to generate a single predicted diffuse reflectance spectrum given a set of input optical properties and a speedup of <math><mrow><mo>∼</mo> <mn>277</mn> <mo>,</mo> <mn>607</mn> <mo>×</mo></mrow> </math> . Notably, validation results demonstrated that numerical error does not scale with structural complexity, indicating that multilayer architectures maintained high stability.</p><p><strong>Conclusions: </strong>We provide an accurate, computationally efficient, and generalized tool for modeling light transport in stratified media. By combining the ability of MC modeling to simulate complex tissue structures, with the speed of analytical diffusion methods, this tool facilitates real-time, depth-resolved quantitative tissue profiling. The full source code is made freely available to the community.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"31 9","pages":"095006"},"PeriodicalIF":3.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13621390/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149080946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}