Journal of Biomedical Optics最新文献

{"title":"Multi-spectral laser speckle contrast imaging for depth-resolved blood perfusion assessment.","authors":"Liban Hussein, Sajjad Moazeni","doi":"10.1117/1.JBO.30.2.023517","DOIUrl":"10.1117/1.JBO.30.2.023517","url":null,"abstract":"<p><strong>Significance: </strong>Laser speckle contrast imaging (LSCI) is a widely used tool in biomedical imaging that leverages the interactions between coherent laser light and tissue to assess blood perfusion. Although effective for 2D imaging applications such as skin burn assessment and wound healing, conventional LSCI lacks depth-resolved capabilities, limiting its potential for deeper perfusion analysis. Enhancing LSCI for depth profiling would significantly expand its utility in applications such as vascular imaging and burn diagnostics.</p><p><strong>Aim: </strong>We investigate the use of multi-spectral laser speckle contrast imaging (MS-LSCI) for assessing blood perfusion at multiple depths, utilizing multiple laser wavelengths and advanced correlation techniques to improve depth localization.</p><p><strong>Approach: </strong>Two tissue phantom molds were fabricated to simulate blood vessels at varying depths. Laser wavelengths from blue to near-infrared (NIR) were used to perform controlled experiments. The visibility parameter, <math> <mrow><msub><mi>V</mi> <mi>r</mi></msub> </mrow> </math> , was employed to correlate and estimate the depth between the phantoms. In addition, a spectral wavelength mapping technique was implemented to enhance signal quality. Validation was conducted by imaging a human hand using the MS-LSCI setup.</p><p><strong>Results: </strong>MS-LSCI demonstrated improved depth profiling accuracy across varying laser wavelengths. The spectral wavelength mapping technique enhanced signal quality for wavelengths with limited penetration. The visibility parameter, <math> <mrow><msub><mi>V</mi> <mi>r</mi></msub> </mrow> </math> , provided consistent depth correlations across phantom models, with results validated through successful imaging of blood perfusion in a human hand.</p><p><strong>Conclusions: </strong>We highlight the potential of MS-LSCI for depth-resolved blood perfusion imaging using multi-wavelength approaches. The findings emphasize the technique's feasibility for non-invasive biomedical applications, including burn wound assessment and vascular imaging.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"30 2","pages":"023517"},"PeriodicalIF":3.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11853228/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143501468","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":"Complex conjugate removal in optical coherence tomography using phase aware generative adversarial network.","authors":"Valentina Bellemo, Richard Haindl, Manojit Pramanik, Linbo Liu, Leopold Schmetterer, Xinyu Liu","doi":"10.1117/1.JBO.30.2.026001","DOIUrl":"10.1117/1.JBO.30.2.026001","url":null,"abstract":"<p><strong>Significance: </strong>Current methods for complex conjugate removal (CCR) in frequency-domain optical coherence tomography (FD-OCT) often require additional hardware components, which increase system complexity and cost. A software-based solution would provide a more efficient and cost-effective alternative.</p><p><strong>Aim: </strong>We aim to develop a deep learning approach to effectively remove complex conjugate artifacts (CCAs) from OCT scans without the need for extra hardware components.</p><p><strong>Approach: </strong>We introduce a deep learning method that employs generative adversarial networks to eliminate CCAs from OCT scans. Our model leverages both conventional intensity images and phase images from the OCT scans to enhance the artifact removal process.</p><p><strong>Results: </strong>Our CCR-generative adversarial network models successfully converted conventional OCT scans with CCAs into artifact-free scans across various samples, including phantoms, human skin, and mouse eyes imaged <i>in vivo</i> with a phase-stable swept source-OCT prototype. The inclusion of phase images significantly improved the performance of the deep learning models in removing CCAs.</p><p><strong>Conclusions: </strong>Our method provides a low-cost, data-driven, and software-based solution to enhance FD-OCT imaging capabilities by the removal of CCAs.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"30 2","pages":"026001"},"PeriodicalIF":3.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11831228/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440983","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":"Assessment of ultraviolet radiation impact on human skin tissue using double-exposure digital holographic interferometry.","authors":"Gloria Frausto-Rea, María Del Socorro Hernández-Montes, Fernando Mendoza Santoyo, Noé Alcala Ochoa, Edgard Efrén Lozada Hernández","doi":"10.1117/1.JBO.30.2.025001","DOIUrl":"10.1117/1.JBO.30.2.025001","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Significance: &lt;/strong&gt;We are all exposed to ultraviolet (UV) radiation coming from the Sun, electronic devices, and artificial sources used in medicine, industry, cosmetics, and other fields, and as it can penetrate the skin, it poses a health risk. In this research, the effects of UV radiation on human skin exposed to different energy doses are evaluated using digital holographic interferometry (DHI), which is proposed as a useful tool to assess the changes caused by skin surface displacement and stiffness values. These two indicators, and their representation in pseudo-three-dimensional (3D) images, will be used as biomarkers, and their quantification will help to better understand the effects of UV rays on human skin.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Aim: &lt;/strong&gt;This research is centered on studying human skin tissue samples (HSTs) with double-exposure DHI; this non-invasive optical technique is able to detect alterations in its mechanical response as it changes caused by UV radiation falling on the skin surface, and such response is compared with the one of non-irradiated samples allowing us to correlate the changes in displacement and stiffness resulting from exposure to different doses of UV radiation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Approach: &lt;/strong&gt;Acoustic waves are sent to the HST to induce vibrations and displacements on their surface; the resulting vibration patterns are monitored through an out-of-plane sensitive DHI setup. The full-field-of-view quantification of the displacements in the &lt;math&gt;&lt;mrow&gt;&lt;mi&gt;z&lt;/mi&gt;&lt;/mrow&gt; &lt;/math&gt; -direction (normal to the surface) is quickly determined by processing the digital holograms, and with the amplitude of the displacements, skin stiffness is calculated. Both the surface displacements and their corresponding stiffness values correctly reveal the effects caused by the different UV radiation doses falling on the HST surface, a matter discussed in detail.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The resonant frequencies and the 3D shape of the vibration showing the displacement and stiffness of human skin with and without radiation were found, and graphs were constructed using those data. A negative correlation is observed between the amount of UV energy applied and the changes in displacements, whereas a positive correlation is observed between stiffness and UV dose. The plot serves as a calibration plot and thus can be used to predict, from the optical data, the displacement and stiffness as a function of the UV dose. In addition, some critical changes in skin stiffness may indicate aging or dehydration in the skin, and this may be useful to achieve better skin care. These data indicate that UV light induces skin stiffening. The amplitude variation in displacement/strain and stiffness allows differentiation between skin tissues without and with UV radiation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The optical non-invasive DHI technique offers a whole field of view assessment of the UV effects on the HST without touching the skin. ","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"30 2","pages":"025001"},"PeriodicalIF":3.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11817812/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143407981","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":"Hyperspectral analysis to assess gametocytogenesis stage progression in malaria-infected human erythrocytes.","authors":"Ik Hwan Kwon, Ji Youn Lee, Fuyuki Tokumasu, Sang-Won Lee, Jeeseong Hwang","doi":"10.1117/1.JBO.30.2.023516","DOIUrl":"10.1117/1.JBO.30.2.023516","url":null,"abstract":"<p><strong>Significance: </strong>Developments of anti-gametocyte drugs have been delayed due to insufficient understanding of gametocyte biology. We report a systematic workflow of data processing algorithms to quantify changes in the absorption spectrum and cell morphology of single malaria-infected erythrocytes. These changes may serve as biomarkers instrumental for the future development of antimalarial strategies, especially for anti-gametocyte drug design and testing. Image-based biomarkers may also be useful for nondestructive, label-free malaria detection and drug efficacy evaluation in resource-limited communities.</p><p><strong>Aim: </strong>We extend the application of hyperspectral microscopy to provide detailed insights into gametocyte stage progression through the quantitative analysis of absorbance spectra and cell morphology in malaria-infected erythrocytes.</p><p><strong>Approach: </strong>Malaria-infected erythrocytes at asexual and different gametocytogenesis stages were imaged through hyperspectral confocal microscopy. The preprocessing of the hyperspectral data cubes to transform them to color images and spectral angle mapper (SAM) analysis were first used to segment hemoglobin (Hb)- and hemozoin (Hz)-abundant areas within the host erythrocytes. Correlations between changes in cell morphology and increasing Hz-abundant areas of the infected erythrocytes were then examined to test their potential as optical biomarkers to determine the progression of infection, involving transitions from asexual to various gametocytogenesis stages.</p><p><strong>Results: </strong>Following successful segmentation of Hb- and Hz-abundant areas in malaria-infected erythrocytes through SAM analysis, a modest correlation between the segmented Hz-abundant area and cell shape changes over time was observed. A significant increase in both the areal fraction of Hz and the ellipticity of the cell confirms that the Hz fraction change correlates with the progression of gametocytogenesis.</p><p><strong>Conclusions: </strong>Our workflow enables the quantification of changes in host cell morphology and the relative contents of Hb and Hz at various parasite growth stages. The quantified results exhibit a trend that both the segmented areal fraction of intracellular Hz and the ellipticity of the host cell increase as gametocytogenesis progresses, suggesting that these two metrics may serve as useful biomarkers to determine the stage of gametocytogenesis.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"30 2","pages":"023516"},"PeriodicalIF":3.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11757776/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143046965","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":"Personal identification using a cross-sectional hyperspectral image of a hand.","authors":"Takashi Suzuki","doi":"10.1117/1.JBO.30.2.023514","DOIUrl":"10.1117/1.JBO.30.2.023514","url":null,"abstract":"<p><strong>Significance: </strong>I explore hyperspectral imaging, a rapid and noninvasive technique with significant potential in biometrics and medical diagnosis. Personal identification was performed using cross-sectional hyperspectral images of palms, offering a simpler and more robust method than conventional vascular pattern identification methods.</p><p><strong>Aim: </strong>I aim to demonstrate the potential of local cross-sectional hyperspectral palm images to identify individuals with high accuracy.</p><p><strong>Approach: </strong>Hyperspectral imaging of palms, artificial intelligence (AI)-based region of interest (ROI) detection, feature vector extraction, and dimensionality reduction were utilized to validate personal identification accuracy using the area under the curve (AUC) and equal error rate (EER).</p><p><strong>Results: </strong>The feature vectors extracted by the proposed method demonstrated higher intra-cluster similarity when the clustering data were reduced through uniform manifold approximation and projection compared with principal component analysis and <math><mrow><mi>t</mi></mrow> </math> -distributed stochastic neighbor embedding. A maximum AUC of 0.98 and an EER of 0.04% were observed.</p><p><strong>Conclusions: </strong>I proposed a biometric method using cross-sectional hyperspectral imaging of human palms. The procedure includes AI-based ROI detection, feature extraction, dimension reduction, and intra- and inter-subject matching using Euclidean distances as a discriminant function. The proposed method has the potential to identify individuals with high accuracy.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"30 2","pages":"023514"},"PeriodicalIF":3.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11649094/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142836611","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":"Special Section Guest Editorial: JBO Special Section on Hyperspectral Imaging.","authors":"Baowei Fei, Jeeseong Hwang, Matija Milanič","doi":"10.1117/1.JBO.30.2.023501","DOIUrl":"10.1117/1.JBO.30.2.023501","url":null,"abstract":"<p><p>The editors introduce a Journal of Biomedical Optics (JBO) special section on Hyperspectral Imaging. The 2-part special section features a number of important research and review papers on new hyperspectral imaging and detection devices and associated technologies, for application in the areas of translational research and clinical studies.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"30 2","pages":"023501"},"PeriodicalIF":3.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11877005/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143557092","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":"Digital instrument simulator to optimize the development of hyperspectral systems: application for intraoperative functional brain mapping.","authors":"Charly Caredda, Frédéric Lange, Luca Giannoni, Ivan Ezhov, Thiébaud Picart, Jacques Guyotat, Ilias Tachtsidis, Bruno Montcel","doi":"10.1117/1.JBO.30.2.023513","DOIUrl":"https://doi.org/10.1117/1.JBO.30.2.023513","url":null,"abstract":"<p><strong>Significance: </strong>Intraoperative optical imaging is a localization technique for the functional areas of the human brain cortex during neurosurgical procedures. These areas can be assessed by monitoring cerebral hemodynamics and metabolism. Robust quantification of these biomarkers is complicated to perform during neurosurgery due to the critical context of the operating room. In actual devices, the inhomogeneities of the optical properties of the exposed brain cortex are poorly taken into consideration, which introduce quantification errors of biomarkers of brain functionality. Moreover, the best choice of spectral configuration is still based on an empirical approach.</p><p><strong>Aim: </strong>We propose a digital instrument simulator to optimize the development of hyperspectral systems for intraoperative brain mapping studies. This simulator can provide realistic modeling of the cerebral cortex and the identification of the optimal wavelengths to monitor cerebral hemodynamics (oxygenated <math> <mrow><msub><mi>HbO</mi> <mn>2</mn></msub> </mrow> </math> and deoxygenated hemoglobin Hb) and metabolism (oxidized state of cytochromes <math><mrow><mi>b</mi></mrow> </math> and <math><mrow><mi>c</mi></mrow> </math> and cytochrome-c-oxidase oxCytb, oxCytc, and oxCCO).</p><p><strong>Approach: </strong>The digital instrument simulator is computed with white Monte Carlo simulations of a volume created from a real image of exposed cortex. We developed an optimization procedure based on a genetic algorithm to identify the best wavelength combinations in the visible and near-infrared range to quantify concentration changes in <math> <mrow><msub><mi>HbO</mi> <mn>2</mn></msub> </mrow> </math> , Hb, oxCCO, and the oxidized state of cytochrome <math><mrow><mi>b</mi></mrow> </math> and <math><mrow><mi>c</mi></mrow> </math> (oxCytb and oxCytc).</p><p><strong>Results: </strong>The digital instrument allows the modeling of intensity maps collected by a camera sensor as well as images of path length to take into account the inhomogeneities of the optical properties. The optimization procedure helps to identify the best wavelength combination of 18 wavelengths that reduces the quantification errors in <math> <mrow><msub><mi>HbO</mi> <mn>2</mn></msub> </mrow> </math> , Hb, and oxCCO by 47%, 57%, and 57%, respectively, compared with the gold standard of 121 wavelengths between 780 and 900 nm. The optimization procedure does not help to resolve changes in cytochrome <math><mrow><mi>b</mi></mrow> </math> and <math><mrow><mi>c</mi></mrow> </math> in a significant way but helps to better resolve oxCCO changes.</p><p><strong>Conclusions: </strong>We proposed a digital instrument simulator to optimize the development of hyperspectral systems for intraoperative brain mapping studies. This digital instrument simulator and this optimization framework could be used to optimize the design of hyperspectral imaging devices.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"30 2","pages":"023513"},"PeriodicalIF":3.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11610766/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142769418","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":"Photoacoustic imaging of rat kidney tissue oxygenation using second near-infrared wavelengths.","authors":"Vinoin Devpaul Vincely, Carolyn L Bayer","doi":"10.1117/1.JBO.30.2.026002","DOIUrl":"10.1117/1.JBO.30.2.026002","url":null,"abstract":"<p><strong>Significance: </strong>Conventionally, spectral photoacoustic imaging (sPAI) to assess tissue oxygenation ( <math> <mrow><msub><mi>sO</mi> <mn>2</mn></msub> </mrow> </math> ) uses optical wavelengths in the first near-infrared (NIR-I) window. This limits the maximum photoacoustic imaging depth due to the high spectral coloring of biological tissues and has been a major barrier to the clinical translation of the technique.</p><p><strong>Aim: </strong>We demonstrate the second near-infrared (NIR-II) tissue optical window (950 to 1400 nm) for the assessment of blood and tissue <math> <mrow><msub><mi>sO</mi> <mn>2</mn></msub> </mrow> </math> .</p><p><strong>Approach: </strong>The NIR-II PA spectra of oxygenated and deoxygenated hemoglobin were first characterized using a phantom. Optimal wavelengths to minimize spectral coloring were identified. The resulting NIR-II PA imaging methods were then validated <i>in vivo</i> by measuring kidney <math> <mrow><msub><mi>sO</mi> <mn>2</mn></msub> </mrow> </math> in adult female rats.</p><p><strong>Results: </strong>sPAI of whole blood, in a phantom, and of blood in kidneys <i>in vivo</i> produced PA spectra proportional to wavelength-dependent optical absorption. Using the NIR-II wavelengths for spectral unmixing resulted in a <math><mrow><mo>∼</mo> <mn>50</mn> <mo>%</mo></mrow> </math> decrease in the error of the estimated blood <math> <mrow><msub><mi>sO</mi> <mn>2</mn></msub> </mrow> </math> , compared with conventional NIR-I wavelengths. <i>In vivo</i> measurements of kidney <math> <mrow><msub><mi>sO</mi> <mn>2</mn></msub> </mrow> </math> validated these findings, with a similar 50% reduction in error when using NIR-II wavelengths versus NIR-I wavelengths at larger illumination depths.</p><p><strong>Conclusions: </strong>sPAI using NIR-II wavelengths improved the accuracy of tissue <math> <mrow><msub><mi>sO</mi> <mn>2</mn></msub> </mrow> </math> measurements. This is likely due to reduced scattering, which reduces the attenuation and, therefore, the impact of spectral coloring in this wavelength range. Combined with the increased safe skin exposure fluence limits in this wavelength range, these results demonstrate the potential to use NIR-II wavelengths for quantitative sPAI of <math> <mrow><msub><mi>sO</mi> <mn>2</mn></msub> </mrow> </math> from deep heterogeneous tissues.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"30 2","pages":"026002"},"PeriodicalIF":3.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11833698/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143449143","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":"Exploring near-infrared autofluorescence properties in parathyroid tissue: an analysis of fresh and paraffin-embedded thyroidectomy specimens.","authors":"Bo Wang, Chi-Peng Zhou, Wei Ao, Shao-Jun Cai, Zhi-Wen Ge, Jun Wang, Wen-Yu Huang, Jia-Fan Yu, Si-Bin Wu, Shou-Yi Yan, Li-Yong Zhang, Si-Si Wang, Zhi-Hong Wang, Surong Hua, Amr H Abdelhamid Ahmed, Gregory W Randolph, Wen-Xin Zhao","doi":"10.1117/1.JBO.30.S1.S13702","DOIUrl":"10.1117/1.JBO.30.S1.S13702","url":null,"abstract":"<p><strong>Significance: </strong>Near-infrared autofluorescence (NIRAF) utilizes the natural autofluorescence of parathyroid glands (PGs) to improve their identification during thyroid surgeries, reducing the risk of inadvertent removal and subsequent complications such as hypoparathyroidism. This study evaluates NIRAF's effectiveness in real-world surgical settings, highlighting its potential to enhance surgical outcomes and patient safety.</p><p><strong>Aim: </strong>We evaluate the effectiveness of NIRAF in detecting PGs during thyroidectomy and central neck dissection and investigate autofluorescence characteristics in both fresh and paraffin-embedded tissues.</p><p><strong>Approach: </strong>We included 101 patients diagnosed with papillary thyroid cancer who underwent surgeries in 2022 and 2023. We assessed NIRAF's ability to locate PGs, confirmed via parathyroid hormone assays, and involved both junior and senior surgeons. We measured the accuracy, speed, and agreement levels of each method and analyzed autofluorescence persistence and variation over 10 years, alongside the expression of calcium-sensing receptor (CaSR) and vitamin D.</p><p><strong>Results: </strong>NIRAF demonstrated a sensitivity of 89.5% and a negative predictive value of 89.1%. However, its specificity and positive predictive value (PPV) were 61.2% and 62.3%, respectively, which are considered lower. The kappa statistic indicated moderate to substantial agreement (kappa = 0.478; <math><mrow><mi>P</mi> <mo><</mo> <mn>0.001</mn></mrow> </math> ). Senior surgeons achieved high specificity (86.2%) and PPV (85.3%), with substantial agreement (kappa = 0.847; <math><mrow><mi>P</mi> <mo><</mo> <mn>0.001</mn></mrow> </math> ). In contrast, junior surgeons displayed the lowest kappa statistic among the groups, indicating minimal agreement (kappa = 0.381; <math><mrow><mi>P</mi> <mo><</mo> <mn>0.001</mn></mrow> </math> ). Common errors in NIRAF included interference from brown fat and eschar. In addition, paraffin-embedded samples retained stable autofluorescence over 10 years, showing no significant correlation with CaSR and vitamin D levels.</p><p><strong>Conclusions: </strong>NIRAF is useful for PG identification in thyroid and neck surgeries, enhancing efficiency and reducing inadvertent PG removals. The stability of autofluorescence in paraffin samples suggests its long-term viability, with false positives providing insights for further improvements in NIRAF technology.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"30 Suppl 1","pages":"S13702"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11256002/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141734166","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":"Robust estimation of skin physiological parameters from hyperspectral images using Bayesian neural networks.","authors":"Teo Manojlović, Tadej Tomanič, Ivan Štajduhar, Matija Milanič","doi":"10.1117/1.JBO.30.1.016004","DOIUrl":"10.1117/1.JBO.30.1.016004","url":null,"abstract":"<p><strong>Significance: </strong>Machine learning models for the direct extraction of tissue parameters from hyperspectral images have been extensively researched recently, as they represent a faster alternative to the well-known iterative methods such as inverse Monte Carlo and inverse adding-doubling (IAD).</p><p><strong>Aim: </strong>We aim to develop a Bayesian neural network model for robust prediction of physiological parameters from hyperspectral images.</p><p><strong>Approach: </strong>We propose a two-component system for extracting physiological parameters from hyperspectral images. First, our system models the relationship between the measured spectra and the tissue parameters as a distribution rather than a point estimate and is thus able to generate multiple possible solutions. Second, the proposed tissue parameters are then refined using the neural network that approximates the biological tissue model.</p><p><strong>Results: </strong>The proposed model was tested on simulated and <i>in vivo</i> data. It outperformed current models with an overall mean absolute error of 0.0141 and can be used as a faster alternative to the IAD algorithm.</p><p><strong>Conclusions: </strong>Results suggest that Bayesian neural networks coupled with the approximation of a biological tissue model can be used to reliably and accurately extract tissue properties from hyperspectral images on the fly.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"30 1","pages":"016004"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11737236/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143006170","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}