Journal of Biomedical Optics最新文献

{"title":"Macroscopic inelastic scattering imaging using a hyperspectral line-scanning system identifies invasive breast cancer in lumpectomy and mastectomy specimens.","authors":"Sandryne David, Hugo Tavera, Tran Trang, Frédérick Dallaire, François Daoust, Francine Tremblay, Lara Richer, Sarkis Meterissian, Frédéric Leblond","doi":"10.1117/1.JBO.29.6.065004","DOIUrl":"10.1117/1.JBO.29.6.065004","url":null,"abstract":"<p><strong>Significance: </strong>Of patients with early-stage breast cancer, 60% to 75% undergo breast-conserving surgery. Of those, 20% or more need a second surgery because of an incomplete tumor resection only discovered days after surgery. An intraoperative imaging technology allowing cancer detection on the margins of breast specimens could reduce re-excision procedure rates and improve patient survival.</p><p><strong>Aim: </strong>We aimed to develop an experimental protocol using hyperspectral line-scanning Raman spectroscopy to image fresh breast specimens from cancer patients. Our objective was to determine whether macroscopic specimen images could be produced to distinguish invasive breast cancer from normal tissue structures.</p><p><strong>Approach: </strong>A hyperspectral inelastic scattering imaging instrument was used to interrogate eight specimens from six patients undergoing breast cancer surgery. Machine learning models trained with a different system to distinguish cancer from normal breast structures were used to produce tissue maps with a field-of-view of <math><mrow><mn>1</mn> <mtext>  </mtext> <msup><mrow><mi>cm</mi></mrow> <mrow><mn>2</mn></mrow> </msup> </mrow> </math> classifying each pixel as either cancer, adipose, or other normal tissues. The predictive model results were compared with spatially correlated histology maps of the specimens.</p><p><strong>Results: </strong>A total of eight specimens from six patients were imaged. Four of the hyperspectral images were associated with specimens containing cancer cells that were correctly identified by the new <i>ex vivo</i> pathology technique. The images associated with the remaining four specimens had no histologically detectable cancer cells, and this was also correctly predicted by the instrument.</p><p><strong>Conclusions: </strong>We showed the potential of hyperspectral Raman imaging as an intraoperative breast cancer margin assessment technique that could help surgeons improve cosmesis and reduce the number of repeat procedures in breast cancer surgery.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 6","pages":"065004"},"PeriodicalIF":3.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11155388/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283838","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":"Deformable multi-modal image registration for the correlation between optical measurements and histology images.","authors":"Lianne Feenstra, Maud Lambregts, Theo J M Ruers, Behdad Dashtbozorg","doi":"10.1117/1.JBO.29.6.066007","DOIUrl":"10.1117/1.JBO.29.6.066007","url":null,"abstract":"<p><strong>Significance: </strong>The accurate correlation between optical measurements and pathology relies on precise image registration, often hindered by deformations in histology images. We investigate an automated multi-modal image registration method using deep learning to align breast specimen images with corresponding histology images.</p><p><strong>Aim: </strong>We aim to explore the effectiveness of an automated image registration technique based on deep learning principles for aligning breast specimen images with histology images acquired through different modalities, addressing challenges posed by intensity variations and structural differences.</p><p><strong>Approach: </strong>Unsupervised and supervised learning approaches, employing the VoxelMorph model, were examined using a dataset featuring manually registered images as ground truth.</p><p><strong>Results: </strong>Evaluation metrics, including Dice scores and mutual information, demonstrate that the unsupervised model exceeds the supervised (and manual) approaches significantly, achieving superior image alignment. The findings highlight the efficacy of automated registration in enhancing the validation of optical technologies by reducing human errors associated with manual registration processes.</p><p><strong>Conclusions: </strong>This automated registration technique offers promising potential to enhance the validation of optical technologies by minimizing human-induced errors and inconsistencies associated with manual image registration processes, thereby improving the accuracy of correlating optical measurements with pathology labels.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 6","pages":"066007"},"PeriodicalIF":3.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11167953/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141310766","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":"Off-axis digital lensless holographic microscopy based on spatially multiplexed interferometry.","authors":"José Ángel Picazo-Bueno, Steffi Ketelhut, Jürgen Schnekenburger, Vicente Micó, Björn Kemper","doi":"10.1117/1.JBO.29.S2.S22715","DOIUrl":"10.1117/1.JBO.29.S2.S22715","url":null,"abstract":"<p><strong>Significance: </strong>Digital holographic microscopy (DHM) is a label-free microscopy technique that provides time-resolved quantitative phase imaging (QPI) by measuring the optical path delay of light induced by transparent biological samples. DHM has been utilized for various biomedical applications, such as cancer research and sperm cell assessment, as well as for <i>in vitro</i> drug or toxicity testing. Its lensless version, digital lensless holographic microscopy (DLHM), is an emerging technology that offers size-reduced, lightweight, and cost-effective imaging systems. These features make DLHM applicable, for example, in limited resource laboratories, remote areas, and point-of-care applications.</p><p><strong>Aim: </strong>In addition to the abovementioned advantages, in-line arrangements for DLHM also include the limitation of the twin-image presence, which can restrict accurate QPI. We therefore propose a compact lensless common-path interferometric off-axis approach that is capable of quantitative imaging of fast-moving biological specimens, such as living cells in flow.</p><p><strong>Approach: </strong>We suggest lensless spatially multiplexed interferometric microscopy (LESSMIM) as a lens-free variant of the previously reported spatially multiplexed interferometric microscopy (SMIM) concept. LESSMIM comprises a common-path interferometric architecture that is based on a single diffraction grating to achieve digital off-axis holography. From a series of single-shot off-axis holograms, twin-image free and time-resolved QPI is achieved by commonly used methods for Fourier filtering-based reconstruction, aberration compensation, and numerical propagation.</p><p><strong>Results: </strong>Initially, the LESSMIM concept is experimentally demonstrated by results from a resolution test chart and investigations on temporal stability. Then, the accuracy of QPI and capabilities for imaging of living adherent cell cultures is characterized. Finally, utilizing a microfluidic channel, the cytometry of suspended cells in flow is evaluated.</p><p><strong>Conclusions: </strong>LESSMIM overcomes several limitations of in-line DLHM and provides fast time-resolved QPI in a compact optical arrangement. In summary, LESSMIM represents a promising technique with potential biomedical applications for fast imaging such as in imaging flow cytometry or sperm cell analysis.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 Suppl 2","pages":"S22715"},"PeriodicalIF":3.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11331263/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142004330","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 characterization of cardiac tissue: the potential of light scattering spectroscopy.","authors":"Brian Cottle, Sarthak Tiwari, Aditya Kaza, Frank B Sachse, Robert Hitchcock","doi":"10.1117/1.JBO.29.6.066005","DOIUrl":"10.1117/1.JBO.29.6.066005","url":null,"abstract":"<p><strong>Significance: </strong>Damage to the cardiac conduction system remains one of the most significant risks associated with surgical interventions to correct congenital heart disease. This work demonstrates how light-scattering spectroscopy (LSS) can be used to non-destructively characterize cardiac tissue regions.</p><p><strong>Aim: </strong>To present an approach for associating tissue composition information with location-specific LSS data and further evaluate an LSS and machine learning system as a method for non-destructive tissue characterization.</p><p><strong>Approach: </strong>A custom LSS probe was used to gather spectral data from locations across 14 excised human pediatric nodal tissue samples (8 sinus nodes, 6 atrioventricular nodes). The LSS spectra were used to train linear and neural-network-based regressor models to predict tissue composition characteristics derived from the 3D models.</p><p><strong>Results: </strong>Nodal tissue region nuclear densities were reported. A linear model trained to regress nuclear density from spectra achieved a prediction r-squared of 0.64 and a concordance correlation coefficient of 0.78.</p><p><strong>Conclusions: </strong>These methods build on previous studies suggesting that LSS measurements combined with machine learning signal processing can provide clinically relevant cardiac tissue composition.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 6","pages":"066005"},"PeriodicalIF":3.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11152447/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141263701","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":"Vibrational imaging of metabolites for improved microbial cell strains.","authors":"Adam Hanninen","doi":"10.1117/1.JBO.29.S2.S22711","DOIUrl":"10.1117/1.JBO.29.S2.S22711","url":null,"abstract":"<p><strong>Significance: </strong>Biomanufacturing utilizes modified microbial systems to sustainably produce commercially important biomolecules for use in agricultural, energy, food, material, and pharmaceutical industries. However, technological challenges related to non-destructive and high-throughput metabolite screening need to be addressed to fully unlock the potential of synthetic biology and sustainable biomanufacturing.</p><p><strong>Aim: </strong>This perspective outlines current analytical screening tools used in industrial cell strain development programs and introduces label-free vibrational spectro-microscopy as an alternative contrast mechanism.</p><p><strong>Approach: </strong>We provide an overview of the analytical instrumentation currently used in the \"test\" portion of the design, build, test, and learn cycle of synthetic biology. We then highlight recent progress in Raman scattering and infrared absorption imaging techniques, which have enabled improved molecular specificity and sensitivity.</p><p><strong>Results: </strong>Recent developments in high-resolution chemical imaging methods allow for greater throughput without compromising the image contrast. We provide a roadmap of future work needed to support integration with microfluidics for rapid screening at the single-cell level.</p><p><strong>Conclusions: </strong>Quantifying the net expression of metabolites allows for the identification of cells with metabolic pathways that result in increased biomolecule production, which is essential for improving the yield and reducing the cost of industrial biomanufacturing. Technological advancements in vibrational microscopy instrumentation will greatly benefit biofoundries as a complementary approach for non-destructive cell screening.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 Suppl 2","pages":"S22711"},"PeriodicalIF":3.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11216725/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141476667","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":"Utilizing convolutional neural networks for discriminating cancer and stromal cells in three-dimensional cell culture images with nuclei counterstain.","authors":"Huu Tuan Nguyen, Nicholas Pietraszek, Sarah E Shelton, Kwabena Arthur, Roger D Kamm","doi":"10.1117/1.JBO.29.S2.S22710","DOIUrl":"10.1117/1.JBO.29.S2.S22710","url":null,"abstract":"<p><strong>Significance: </strong>Accurate cell segmentation and classification in three-dimensional (3D) images are vital for studying live cell behavior and drug responses in 3D tissue culture. Evaluating diverse cell populations in 3D cell culture over time necessitates non-toxic staining methods, as specific fluorescent tags may not be suitable, and immunofluorescence staining can be cytotoxic for prolonged live cell cultures.</p><p><strong>Aim: </strong>We aim to perform machine learning-based cell classification within a live heterogeneous cell culture population grown in a 3D tissue culture relying only on reflectance, transmittance, and nuclei counterstained images obtained by confocal microscopy.</p><p><strong>Approach: </strong>In this study, we employed a supervised convolutional neural network (CNN) to classify tumor cells and fibroblasts within 3D-grown spheroids. These cells are first segmented using the marker-controlled watershed image processing method. Training data included nuclei counterstaining, reflectance, and transmitted light images, with stained fibroblast and tumor cells as ground-truth labels.</p><p><strong>Results: </strong>Our results demonstrate the successful marker-controlled watershed segmentation of 84% of spheroid cells into single cells. We achieved a median accuracy of 67% (95% confidence interval of the median is 65-71%) in identifying cell types. We also recapitulate the original 3D images using the CNN-classified cells to visualize the original 3D-stained image's cell distribution.</p><p><strong>Conclusion: </strong>This study introduces a non-invasive toxicity-free approach to 3D cell culture evaluation, combining machine learning with confocal microscopy, opening avenues for advanced cell studies.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 Suppl 2","pages":"S22710"},"PeriodicalIF":3.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11344342/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142055707","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":"Two-color diffuse <i>in vivo</i> flow cytometer.","authors":"Amber L Williams, Augustino V Scorzo, Rendall R Strawbridge, Scott C Davis, Mark Niedre","doi":"10.1117/1.JBO.29.6.065003","DOIUrl":"10.1117/1.JBO.29.6.065003","url":null,"abstract":"<p><strong>Significance: </strong>Hematogenous metastasis is mediated by circulating tumor cells (CTCs) and CTC clusters (CTCCs). We recently developed \"diffuse <i>in vivo</i> flow cytometry\" (DiFC) to detect fluorescent protein (FP) expressing CTCs in small animals. Extending DiFC to allow detection of two FPs simultaneously would allow concurrent study of different CTC sub-populations or heterogeneous CTCCs in the same animal.</p><p><strong>Aim: </strong>The goal of this work was to develop and validate a two-color DiFC system capable of non-invasively detecting circulating cells expressing two distinct FPs.</p><p><strong>Approach: </strong>A DiFC instrument was designed and built to detect cells expressing either green FP (GFP) or tdTomato. We tested the instrument in tissue-mimicking flow phantoms <i>in vitro</i> and in multiple myeloma bearing mice <i>in vivo</i>.</p><p><strong>Results: </strong>In phantoms, we could accurately differentiate GFP+ and tdTomato+ CTCs and CTCCs. In tumor-bearing mice, CTC numbers expressing both FPs increased during disease. Most CTCCs (86.5%) expressed single FPs with the remainder both FPs. These data were supported by whole-body hyperspectral fluorescence cryo-imaging of the mice.</p><p><strong>Conclusions: </strong>We showed that two-color DiFC can detect two populations of CTCs and CTCCs concurrently. This instrument could allow study of tumor development and response to therapies for different sub-populations in the same animal.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 6","pages":"065003"},"PeriodicalIF":3.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11138342/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141179414","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":"Erratum: Model for the diffuse reflectance in spatial frequency domain imaging (Erratum).","authors":"Anouk L Post, Dirk J Faber, Ton G van Leeuwen","doi":"10.1117/1.JBO.29.6.069801","DOIUrl":"https://doi.org/10.1117/1.JBO.29.6.069801","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1117/1.JBO.28.4.046002.].</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 6","pages":"069801"},"PeriodicalIF":3.5,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11166170/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141306037","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 polystyrene and hydrogel microcarriers for optical imaging of adherent cells.","authors":"Oscar R Benavides, Berkley P White, Holly C Gibbs, Roland Kaunas, Carl A Gregory, Kristen C Maitland, Alex J Walsh","doi":"10.1117/1.JBO.29.S2.S22708","DOIUrl":"10.1117/1.JBO.29.S2.S22708","url":null,"abstract":"<p><strong>Significance: </strong>The ability to observe and monitor cell density and morphology has been imperative for assessing the health of a cell culture and for producing high quality, high yield cell cultures for decades. Microcarrier-based cultures, used for large-scale cellular expansion processes, are not compatible with traditional visualization-based methods, such as widefield microscopy, due to their thickness and material composition.</p><p><strong>Aim: </strong>Here, we assess the optical imaging compatibilities of commercial polystyrene microcarriers versus custom-fabricated gelatin methacryloyl (gelMA) microcarriers for non-destructive and non-invasive visualization of the entire microcarrier surface, direct cell enumeration, and sub-cellular visualization of mesenchymal stem/stromal cells.</p><p><strong>Approach: </strong>Mie scattering and wavefront error simulations of the polystyrene and gelMA microcarriers were performed to assess the potential for elastic scattering-based imaging of adherent cells. A Zeiss Z.1 light-sheet microscope was adapted to perform light-sheet tomography using label-free elastic scattering contrast from planar side illumination to achieve optical sectioning and permit non-invasive and non-destructive, <i>in toto</i>, three-dimensional, high-resolution visualization of cells cultured on microcarriers.</p><p><strong>Results: </strong>The polystyrene microcarrier prevents visualization of cells on the distal half of the microcarrier using either fluorescence or elastic scattering contrast, whereas the gelMA microcarrier allows for high fidelity visualization of cell morphology and quantification of cell density using light-sheet fluorescence microscopy and tomography.</p><p><strong>Conclusions: </strong>The combination of optical-quality gelMA microcarriers and label-free light-sheet tomography will facilitate enhanced control of bioreactor-microcarrier cell culture processes.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 Suppl 2","pages":"S22708"},"PeriodicalIF":3.5,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11175462/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141317374","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":"Functional hemodynamic imaging markers for the prediction of pathological outcomes in breast cancer patients treated with neoadjuvant chemotherapy.","authors":"Bin Deng, Ailis Muldoon, Jayne Cormier, Nathaniel D Mercaldo, Elizabeth Niehoff, Natalie Moffett, Mansi A Saksena, Steven J Isakoff, Stefan A Carp","doi":"10.1117/1.JBO.29.6.066001","DOIUrl":"10.1117/1.JBO.29.6.066001","url":null,"abstract":"<p><strong>Significance: </strong>Achieving pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is a significant predictor of increased likelihood of survival in breast cancer patients. Early prediction of pCR is of high clinical value as it could allow personalized adjustment of treatment regimens in non-responding patients for improved outcomes.</p><p><strong>Aim: </strong>We aim to assess the association between hemoglobin-based functional imaging biomarkers derived from diffuse optical tomography (DOT) and the pathological outcome represented by pCR at different timepoints along the course of NACT.</p><p><strong>Approach: </strong>Twenty-two breast cancer patients undergoing NACT were enrolled in a multimodal DOT and X-ray digital breast tomosynthesis (DBT) imaging study in which their breasts were imaged at different compression levels. Logistic regressions were used to study the associations between DOT-derived imaging markers evaluated after the first and second cycles of chemotherapy, respectively, with pCR status determined after the conclusion of NACT at the time of surgery. Receiver operating characteristic curve analysis was also used to explore the predictive performance of selected DOT-derived markers.</p><p><strong>Results: </strong>Normalized tumor HbT under half compression was significantly lower in the pCR group compared to the non-pCR group after two chemotherapy cycles (<math><mrow><mi>p</mi><mo>=</mo><mn>0.042</mn></mrow></math>). In addition, the change in normalized tumor <math><mrow><msub><mi>StO</mi><mn>2</mn></msub></mrow></math> upon reducing compression from full to half mammographic force was identified as another potential indicator of pCR at an earlier time point, i.e., after the first chemo cycle (<math><mrow><mi>p</mi><mo>=</mo><mn>0.038</mn></mrow></math>). Exploratory predictive assessments showed that AUCs using DOT-derived functional imaging markers as predictors reach as high as 0.75 and 0.71, respectively, after the first and second chemo cycle, compared to AUCs of 0.50 and 0.53 using changes in tumor size measured on DBT and MRI.</p><p><strong>Conclusions: </strong>These findings suggest that breast DOT could be used to assist response assessment in women undergoing NACT, a critical but unmet clinical need, and potentially enable personalized adjustments of treatment regimens.</p>","PeriodicalId":15264,"journal":{"name":"Journal of Biomedical Optics","volume":"29 6","pages":"066001"},"PeriodicalIF":3.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11088438/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140911842","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}