Journal of Biomedical Optics最新文献

{"title":"Ultrasound and diffuse optical tomography-transformer model for assessing pathological complete response to neoadjuvant chemotherapy in breast cancer.","authors":"Yun Zou, Minghao Xue, Md Iqbal Hossain, Quing Zhu","doi":"10.1117/1.JBO.29.7.076007","DOIUrl":"https://doi.org/10.1117/1.JBO.29.7.076007","url":null,"abstract":"<p><strong>Significance: </strong>We evaluate the efficiency of integrating ultrasound (US) and diffuse optical tomography (DOT) images for predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients. The ultrasound-diffuse optical tomography (USDOT)-Transformer model represents a significant step toward accurate prediction of pCR, which is critical for personalized treatment planning.</p><p><strong>Aim: </strong>We aim to develop and assess the performance of the USDOT-Transformer model, which combines US and DOT images with tumor receptor biomarkers to predict the pCR of breast cancer patients under NAC.</p><p><strong>Approach: </strong>We developed the USDOT-Transformer model using a dual-input transformer to process co-registered US and DOT images along with tumor receptor biomarkers. Our dataset comprised imaging data from 60 patients at multiple time points during their chemotherapy treatment. We used fivefold cross-validation to assess the model's performance, comparing its results against a single modality of US or DOT.</p><p><strong>Results: </strong>The USDOT-Transformer model demonstrated excellent predictive performance, with a mean area under the receiving characteristic curve of 0.96 (95%CI: 0.93 to 0.99) across the fivefold cross-validation. The integration of US and DOT images significantly enhanced the model's ability to predict pCR, outperforming models that relied on a single imaging modality (0.87 for US and 0.82 for DOT). This performance indicates the potential of advanced deep learning techniques and multimodal imaging data for improving the accuracy (ACC) of pCR prediction.</p><p><strong>Conclusion: </strong>The USDOT-Transformer model offers a promising non-invasive approach for predicting pCR to NAC in breast cancer patients. By leveraging the structural and functional information from US and DOT images, the model offers a faster and more reliable tool for personalized treatment planning. Future work will focus on expanding the dataset and refining the model to further improve its accuracy and generalizability.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 7","pages":"076007"},"PeriodicalIF":3.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11268382/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141758978","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":"Compressed intracellular motility via non-uniform temporal sampling in dynamic optical coherence tomography.","authors":"Amy L Oldenburg, Pan Ji, Xiao Yu, Lin Yang","doi":"10.1117/1.JBO.29.7.076002","DOIUrl":"10.1117/1.JBO.29.7.076002","url":null,"abstract":"<p><strong>Significance: </strong>Optical coherence tomography has great utility for capturing dynamic processes, but such applications are particularly data-intensive. Samples such as biological tissues exhibit temporal features at varying time scales, which makes data reduction challenging.</p><p><strong>Aim: </strong>We propose a method for capturing short- and long-term correlations of a sample in a compressed way using non-uniform temporal sampling to reduce scan time and memory overhead.</p><p><strong>Approach: </strong>The proposed method separates the relative contributions of white noise, fluctuating features, and stationary features. The method is demonstrated on mammary epithelial cell spheroids in three-dimensional culture for capturing intracellular motility without loss of signal integrity.</p><p><strong>Results: </strong>Results show that the spatial patterns of motility are preserved and that hypothesis tests of spheroids treated with blebbistatin, a motor protein inhibitor, are unchanged with up to eightfold compression.</p><p><strong>Conclusions: </strong>The ability to measure short- and long-term correlations compressively will enable new applications in (3+1)D imaging and high-throughput screening.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 7","pages":"076002"},"PeriodicalIF":3.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11223688/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141534529","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":"iStent insertion orientation and impact on trabecular meshwork motion resolved by optical coherence tomography imaging.","authors":"Zhaoyu Gong, Murray A Johnstone, Ruikang K Wang","doi":"10.1117/1.JBO.29.7.076008","DOIUrl":"10.1117/1.JBO.29.7.076008","url":null,"abstract":"<p><strong>Significance: </strong>The iStent is a popular device designed for glaucoma treatment, functioning by creating an artificial fluid pathway in the trabecular meshwork (TM) to drain aqueous humor. The assessment of iStent implantation surgery is clinically important. However, current tools offer limited information.</p><p><strong>Aim: </strong>We aim to develop innovative assessment strategies for iStent implantation using optical coherence tomography (OCT) to evaluate the position and orientation of the iStent and its biomechanical impact on outflow system dynamics.</p><p><strong>Approach: </strong>We examined four iStents in the two eyes of a glaucoma patient. Three-dimensional (3D) OCT structural imaging was conducted for each iStent, and a semi-automated algorithm was developed for iStent segmentation and visualization, allowing precise measurement of position and orientation. In addition, phase-sensitive OCT (PhS-OCT) imaging was introduced to measure the biomechanical impact of the iStent on the outflow system quantified by cumulative displacement (CDisp) of pulse-dependent trabecular TM motion.</p><p><strong>Results: </strong>The 3D structural image processed by our algorithm definitively resolved the position and orientation of the iStent in the anterior segment, revealing substantial variations in relevant parameters. PhS-OCT imaging demonstrated significantly higher CDisp in the regions between two iStents compared to locations distant from the iStents in both OD ( <math><mrow><mi>p</mi> <mo>=</mo> <mn>0.0075</mn></mrow> </math> ) and OS ( <math><mrow><mi>p</mi> <mo>=</mo> <mn>0.0437</mn></mrow> </math> ).</p><p><strong>Conclusions: </strong>Our proposed structural imaging technique improved the characterization of the iStent's placement. The imaging results revealed inherent challenges in achieving precise control of iStent insertion. Furthermore, PhS-OCT imaging unveiled potential biomechanical alterations induced by the iStent. This unique methodology shows potential as a valuable clinical tool for evaluating iStent implantation.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 7","pages":"076008"},"PeriodicalIF":3.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11283271/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141788060","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":"Convolutional neural network advances in demosaicing for fluorescent cancer imaging with color-near-infrared sensors.","authors":"Yifei Jin, Borislav Kondov, Goran Kondov, Sunil Singhal, Shuming Nie, Viktor Gruev","doi":"10.1117/1.JBO.29.7.076005","DOIUrl":"10.1117/1.JBO.29.7.076005","url":null,"abstract":"<p><strong>Significance: </strong>Single-chip imaging devices featuring vertically stacked photodiodes and pixelated spectral filters are advancing multi-dye imaging methods for cancer surgeries, though this innovation comes with a compromise in spatial resolution. To mitigate this drawback, we developed a deep convolutional neural network (CNN) aimed at demosaicing the color and near-infrared (NIR) channels, with its performance validated on both pre-clinical and clinical datasets.</p><p><strong>Aim: </strong>We introduce an optimized deep CNN designed for demosaicing both color and NIR images obtained using a hexachromatic imaging sensor.</p><p><strong>Approach: </strong>A residual CNN was fine-tuned and trained on a dataset of color images and subsequently assessed on a series of dual-channel, color, and NIR images to demonstrate its enhanced performance compared with traditional bilinear interpolation.</p><p><strong>Results: </strong>Our optimized CNN for demosaicing color and NIR images achieves a reduction in the mean square error by 37% for color and 40% for NIR, respectively, and enhances the structural dissimilarity index by 37% across both imaging modalities in pre-clinical data. In clinical datasets, the network improves the mean square error by 35% in color images and 42% in NIR images while enhancing the structural dissimilarity index by 39% in both imaging modalities.</p><p><strong>Conclusions: </strong>We showcase enhancements in image resolution for both color and NIR modalities through the use of an optimized CNN tailored for a hexachromatic image sensor. With the ongoing advancements in graphics card computational power, our approach delivers significant improvements in resolution that are feasible for real-time execution in surgical environments.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 7","pages":"076005"},"PeriodicalIF":3.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11265532/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141751766","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":"Depolarization diagrams for circularly polarized light scattering for biological particle monitoring.","authors":"Nozomi Nishizawa, Asato Esumi, Yukito Ganko","doi":"10.1117/1.JBO.29.7.075001","DOIUrl":"10.1117/1.JBO.29.7.075001","url":null,"abstract":"<p><strong>Significance: </strong>The depolarization of circularly polarized light (CPL) caused by scattering in turbid media reveals structural information about the dispersed particles, such as their size, density, and distribution, which is useful for investigating the state of biological tissue. However, the correlation between depolarization strength and tissue parameters is unclear.</p><p><strong>Aim: </strong>We aimed to examine the generalized correlations of depolarization strength with the particle size and wavelength, yielding depolarization diagrams.</p><p><strong>Approach: </strong>The correlation between depolarization intensity and size parameter was examined for single and multiple scattering using the Monte Carlo simulation method. Expanding the wavelength width allows us to obtain depolarization distribution diagrams as functions of wavelength and particle diameter for reflection and transparent geometries.</p><p><strong>Results: </strong>CPL suffers intensive depolarization in a single scattering against particles of various specific sizes for its wavelength, which becomes more noticeable in the multiple scattering regime.</p><p><strong>Conclusions: </strong>The depolarization diagrams with particle size and wavelength as independent variables were obtained, which are particularly helpful for investigating the feasibility of various particle-monitoring methods. Based on the obtained diagrams, several applications have been proposed, including blood cell monitoring, early embryogenesis, and antigen-antibody interactions.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 7","pages":"075001"},"PeriodicalIF":3.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11191632/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141442765","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":"Single-beam digital holographic reconstruction: a phase-support enhanced complex wavefront on phase-only function for twin-image elimination.","authors":"Charlotte Kyeremah, Matthew Weiss, Dila Kandel, Daniel Haehn, Chandra Yelleswarapu","doi":"10.1117/1.JBO.29.7.076502","DOIUrl":"10.1117/1.JBO.29.7.076502","url":null,"abstract":"<p><strong>Significance: </strong>In in-line digital holographic microscopy (DHM), twin-image artifacts pose a significant challenge, and reduction or complete elimination is essential for object reconstruction.</p><p><strong>Aim: </strong>To facilitate object reconstruction using a single hologram, significantly reduce inaccuracies, and avoid iterative processing, a digital holographic reconstruction algorithm called phase-support constraint on phase-only function (PCOF) is presented.</p><p><strong>Approach: </strong>In-line DHM simulations and tabletop experiments employing the sliding-window approach are used to compute the arithmetic mean and variance of the phase values in the reconstructed image. A support constraint mask, through variance thresholding, effectively enabled twin-image artifacts.</p><p><strong>Results: </strong>Quantitative evaluations using metrics such as mean squared error, peak signal-to-noise ratio, and mean structural similarity index show PCOF's superior capability in eliminating twin-image artifacts and achieving high-fidelity reconstructions compared with conventional methods such as angular spectrum and iterative phase retrieval methods.</p><p><strong>Conclusions: </strong>PCOF stands as a promising approach to in-line digital holographic reconstruction, offering a robust solution to mitigate twin-image artifacts and enhance the fidelity of reconstructed objects.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 7","pages":"076502"},"PeriodicalIF":3.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11246103/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141616532","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":"Challenges and advances in two-dimensional photoacoustic computed tomography: a review.","authors":"Shunyao Zhang, Jingyi Miao, Lei S Li","doi":"10.1117/1.JBO.29.7.070901","DOIUrl":"10.1117/1.JBO.29.7.070901","url":null,"abstract":"<p><strong>Significance: </strong>Photoacoustic computed tomography (PACT), a hybrid imaging modality combining optical excitation with acoustic detection, has rapidly emerged as a prominent biomedical imaging technique.</p><p><strong>Aim: </strong>We review the challenges and advances of PACT, including (1) limited view, (2) anisotropy resolution, (3) spatial aliasing, (4) acoustic heterogeneity (speed of sound mismatch), and (5) fluence correction of spectral unmixing.</p><p><strong>Approach: </strong>We performed a comprehensive literature review to summarize the key challenges in PACT toward practical applications and discuss various solutions.</p><p><strong>Results: </strong>There is a wide range of contributions from both industry and academic spaces. Various approaches, including emerging deep learning methods, are proposed to improve the performance of PACT further.</p><p><strong>Conclusions: </strong>We outline contemporary technologies aimed at tackling the challenges in PACT applications.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 7","pages":"070901"},"PeriodicalIF":3.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11245175/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141616531","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":"Deep learning-enabled high-speed, multi-parameter diffuse optical tomography.","authors":"Robin Dale, Biao Zheng, Felipe Orihuela-Espina, Nicholas Ross, Thomas D O'Sullivan, Scott Howard, Hamid Dehghani","doi":"10.1117/1.JBO.29.7.076004","DOIUrl":"10.1117/1.JBO.29.7.076004","url":null,"abstract":"<p><strong>Significance: </strong>Frequency-domain diffuse optical tomography (FD-DOT) could enhance clinical breast tumor characterization. However, conventional diffuse optical tomography (DOT) image reconstruction algorithms require case-by-case expert tuning and are too computationally intensive to provide feedback during a scan. Deep learning (DL) algorithms front-load computational and tuning costs, enabling high-speed, high-fidelity FD-DOT.</p><p><strong>Aim: </strong>We aim to demonstrate a simultaneous reconstruction of three-dimensional absorption and reduced scattering coefficients using DL-FD-DOT, with a view toward real-time imaging with a handheld probe.</p><p><strong>Approach: </strong>A DL model was trained to solve the DOT inverse problem using a realistically simulated FD-DOT dataset emulating a handheld probe for human breast imaging and tested using both synthetic and experimental data.</p><p><strong>Results: </strong>Over a test set of 300 simulated tissue phantoms for absorption and scattering reconstructions, the DL-DOT model reduced the root mean square error by <math><mrow><mn>12</mn> <mo>%</mo> <mo>±</mo> <mn>40</mn> <mo>%</mo></mrow> </math> and <math><mrow><mn>23</mn> <mo>%</mo> <mo>±</mo> <mn>40</mn> <mo>%</mo></mrow> </math> , increased the spatial similarity by <math><mrow><mn>17</mn> <mo>%</mo> <mo>±</mo> <mn>17</mn> <mo>%</mo></mrow> </math> and <math><mrow><mn>9</mn> <mo>%</mo> <mo>±</mo> <mn>15</mn> <mo>%</mo></mrow> </math> , increased the anomaly contrast accuracy by <math><mrow><mn>9</mn> <mo>%</mo> <mo>±</mo> <mn>9</mn> <mo>%</mo></mrow> </math> ( <math> <mrow><msub><mi>μ</mi> <mi>a</mi></msub> </mrow> </math> ), and reduced the crosstalk by <math><mrow><mn>5</mn> <mo>%</mo> <mo>±</mo> <mn>18</mn> <mo>%</mo></mrow> </math> and <math><mrow><mn>7</mn> <mo>%</mo> <mo>±</mo> <mn>11</mn> <mo>%</mo></mrow> </math> , respectively, compared with model-based tomography. The average reconstruction time was reduced from 3.8 min to 0.02 s for a single reconstruction. The model was successfully verified using two tumor-emulating optical phantoms.</p><p><strong>Conclusions: </strong>There is clinical potential for real-time functional imaging of human breast tissue using DL and FD-DOT.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 7","pages":"076004"},"PeriodicalIF":3.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11259453/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141734165","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":"Distribution-informed and wavelength-flexible data-driven photoacoustic oximetry.","authors":"Janek Gröhl, Kylie Yeung, Kevin Gu, Thomas R Else, Monika Golinska, Ellie V Bunce, Lina Hacker, Sarah E Bohndiek","doi":"10.1117/1.JBO.29.S3.S33303","DOIUrl":"10.1117/1.JBO.29.S3.S33303","url":null,"abstract":"<p><strong>Significance: </strong>Photoacoustic imaging (PAI) promises to measure spatially resolved blood oxygen saturation but suffers from a lack of accurate and robust spectral unmixing methods to deliver on this promise. Accurate blood oxygenation estimation could have important clinical applications from cancer detection to quantifying inflammation.</p><p><strong>Aim: </strong>We address the inflexibility of existing data-driven methods for estimating blood oxygenation in PAI by introducing a recurrent neural network architecture.</p><p><strong>Approach: </strong>We created 25 simulated training dataset variations to assess neural network performance. We used a long short-term memory network to implement a wavelength-flexible network architecture and proposed the Jensen-Shannon divergence to predict the most suitable training dataset.</p><p><strong>Results: </strong>The network architecture can flexibly handle the input wavelengths and outperforms linear unmixing and the previously proposed learned spectral decoloring method. Small changes in the training data significantly affect the accuracy of our method, but we find that the Jensen-Shannon divergence correlates with the estimation error and is thus suitable for predicting the most appropriate training datasets for any given application.</p><p><strong>Conclusions: </strong>A flexible data-driven network architecture combined with the Jensen-Shannon divergence to predict the best training data set provides a promising direction that might enable robust data-driven photoacoustic oximetry for clinical use cases.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 Suppl 3","pages":"S33303"},"PeriodicalIF":3.5,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11151660/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141260266","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":"Capturing cell morphology dynamics with high temporal resolution using single-shot quantitative phase gradient imaging.","authors":"Sun Woong Hur, Minsung Kwon, Revathi Manoharaan, Melika Haji Mohammadi, Ashok Zachariah Samuel, Michael P Mulligan, Paul J Hergenrother, Rohit Bhargava","doi":"10.1117/1.JBO.29.S2.S22712","DOIUrl":"10.1117/1.JBO.29.S2.S22712","url":null,"abstract":"<p><strong>Significance: </strong>Label-free quantitative phase imaging can potentially measure cellular dynamics with minimal perturbation, motivating efforts to develop faster and more sensitive instrumentation. We characterize fast, single-shot quantitative phase gradient microscopy (ss-QPGM) that simultaneously acquires multiple polarization components required to reconstruct phase images. We integrate a computationally efficient least squares algorithm to provide real-time, video-rate imaging (up to <math><mrow><mn>75</mn> <mtext>  frames</mtext> <mo>/</mo> <mi>s</mi></mrow> </math> ). The developed instrument was used to observe changes in cellular morphology and correlate these to molecular measures commonly obtained by staining.</p><p><strong>Aim: </strong>We aim to characterize a fast approach to ss-QPGM and record morphological changes in single-cell phase images. We also correlate these with biochemical changes indicating cell death using concurrently acquired fluorescence images.</p><p><strong>Approach: </strong>Here, we examine nutrient deprivation and anticancer drug-induced cell death in two different breast cell lines, <i>viz.</i>, M2 and MCF7. Our approach involves in-line measurements of ss-QPGM and fluorescence imaging of the cells biochemically labeled for viability.</p><p><strong>Results: </strong>We validate the accuracy of the phase measurement using a USAF1951 pattern phase target. The ss-QPGM system resolves <math><mrow><mn>912.3</mn> <mtext>  </mtext> <mi>lp</mi> <mo>/</mo> <mi>mm</mi></mrow> </math> , and our analysis scheme accurately retrieves the phase with a high correlation coefficient ( <math><mrow><mo>∼</mo> <mn>0.99</mn></mrow> </math> ), as measured by calibrated sample thicknesses. Analyzing the contrast in phase, we estimate the spatial resolution achievable to be <math><mrow><mn>0.55</mn> <mtext>  </mtext> <mi>μ</mi> <mi>m</mi></mrow> </math> for this microscope. ss-QPGM time-lapse live-cell imaging reveals multiple intracellular and morphological changes during biochemically induced cell death. Inferences from co-registered images of quantitative phase and fluorescence suggest the possibility of necrosis, which agrees with previous findings.</p><p><strong>Conclusions: </strong>Label-free ss-QPGM with high-temporal resolution and high spatial fidelity is demonstrated. Its application for monitoring dynamic changes in live cells offers promising prospects.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 Suppl 2","pages":"S22712"},"PeriodicalIF":3.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11249975/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141626852","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}