Physics in medicine and biology最新文献

{"title":"Diffusion prior-guided implicit neural representation for metal artifact reduction in sparse-view CT reconstruction.","authors":"Subong Hyun, Sungho Yun, Seoyoung Lee, Da-In Choi, Seungryong Cho","doi":"10.1088/1361-6560/ae6a5a","DOIUrl":"https://doi.org/10.1088/1361-6560/ae6a5a","url":null,"abstract":"<p><strong>Objective: </strong>Sparse-view computed tomography (SVCT) reduces radiation exposure, but it inevitably leads to severe streak artifacts, which become even more pronounced in the presence of metallic implants. Most existing methods address SVCT and metal artifact reduction (MAR) separately, making the joint SVCT and MAR (SVMAR) problem suboptimal. While a few methods have been proposed to tackle SVMAR jointly, most are supervised and require large paired datasets that are difficult to obtain in clinical practice. To overcome these limitations, we propose a self-supervised framework that leverages a denoising diffusion probabilistic model (DDPM) and implicit neural representation (INR) to address the SVMAR problem. &#xD;Approach. First, an INR is optimized to produce an initial reconstruction using sparse-view measurements by sampling only rays outside the metal trace. This initial estimate is then used to accelerate the reverse diffusion process. During reverse diffusion, we alternately perform: (i) a MAR step, where diffusion priors guide the inpainting of metal-trace regions in the measurements using Poisson blending; and (ii) an SVCT step, where data fidelity is enforced by refining the INR with both diffusion priors and the MAR-corrected sinograms obtained from the MAR step.&#xD;Main result. Experiments on both simulation and clinical datasets show that the proposed method reconstructs high-quality images without requiring large paired datasets. Quantitative evaluations demonstrated that the proposed method outperformed existing methods including IndudoNet+ on the out-of-distribution dataset across 160-, 80-, and 40-view settings, with PSNR improving from 36.28 to 45.39 dB, 32.69 to 44.22 dB, and 31.37 to 41.90 dB, and SSIM increasing from 0.955 to 0.988, 0.920 to 0.983, and 0.906 to 0.973, respectively.&#xD;Significance. By leveraging diffusion priors within a self-supervised INR framework, the method provides a practical and generalizable solution for real-world SVMAR scenarios where ground-truth images are unavailable.&#xD.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147841381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A fast dosimetric optimization method of intensity modulated brachytherapy (IMBT) treatment plans for cervical cancer.","authors":"Miao Qi, Junyi Liu, Shijun Li, Yankui Chang, Jieping Zhou, Yong Cheng, Bing Yan, Yunqin Liu, Aidong Wu, Pei Xi, X George Xu","doi":"10.1088/1361-6560/ae63a2","DOIUrl":"10.1088/1361-6560/ae63a2","url":null,"abstract":"<p><p><i>Objective.</i>Intensity-modulated brachytherapy (IMBT) is an innovative technique aimed at achieving anisotropic dose distributions in brachytherapy. This study develops a fast dosimetric optimization method specifically for IMBT plans in cervical cancer.<i>Approach.</i>ARCHER-IMBT was validated against TOPAS in both water phantoms and clinical geometries. Optimization was performed for six intracavitary (IC-BT) cases and one intracavitary/interstitial (IC/IS-BT) case, comparing 50 kVp x-ray and Ir-192 sources. The study also explored the potential of IMBT to achieve comparable dosimetry to IC/IS-BT using only intracavitary applicators. Furthermore, a stochastic uncertainty analysis (200 Monte Carlo scenarios) was conducted to evaluate plan robustness against positional (0.3 mm) and angular (0.2°) perturbations.<i>Main results.</i>ARCHER-IMBT achieved speedup factors exceeding 50× for water phantoms and 350× for clinical cases, with gamma passing rates >98%. The entire optimization process was completed within one minute. Compared to IC-BT, IMBT plans reduced bladder and rectum<i>D</i>_2ccby 3.1% and 15.1% for Ir-192, and by 23.4% and 22.8% for 50 kVp x-rays, respectively. In the IC/IS-BT case, IMBT plans achieved comparable target coverage while potentially eliminating the need for invasive needles. However, uncertainty analysis revealed that the 50 kVp source is highly sensitive to sub-millimeter translational errors (0.3 mm) due to its steep dose gradients, whereas Ir-192 exhibited greater robustness.<i>Significance.</i>This study demonstrates a computationally efficient IMBT optimization platform. The findings highlight the dosimetric benefits of IMBT and its potential to simplify complex IC/IS-BT procedures, while underscoring the stringent mechanical precision required for clinical implementation.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147778531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MRI-guided radiotherapy: is the best still to come?","authors":"David E J Waddington, Paul J Keall, Bas W Raaymakers","doi":"10.1088/1361-6560/ae63a0","DOIUrl":"10.1088/1361-6560/ae63a0","url":null,"abstract":"","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147778636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-model study of fast VMAT segment dose calculation with deep learning.","authors":"Fan Xiao, Niklas Wahl, Claus Belka, Christopher Kurz, George Dedes, Guillaume Landry","doi":"10.1088/1361-6560/ae6413","DOIUrl":"10.1088/1361-6560/ae6413","url":null,"abstract":"<p><p><i>Objective.</i>Deep learning (DL) methods enable photon dose calculation under two main coordinate representations: Beam's Eye View (BEV) and patient coordinates. We evaluate dose calculation accuracy and speed under these coordinate paradigms and with representative DL models within a unified dataset and pipeline, and introduce two lightweight models for fast photon dose calculation.<i>Approach.</i>Planning computed tomography (CT) scans and volumetric modulated arc therapy plans from 24 prostate cancer patients were used. Monte Carlo simulation generated 5940, 540, and 3053 segment doses for training (11 patients), validation (3), and testing (10), respectively. For BEV, we used a combination of convolutional neural network (CNN) and convolutional long short-term memory network (ConvLSTM) called CNN-ConvLSTM, a CNN-Mamba combination (CNN-Mamba), a transformer-based architecture (DoTA), and a cascaded 3D UNet (C3D). These were trained on CT and segment-projection BEV cuboids. For patient coordinates, the DeepDose individual segment dose prediction framework implemented with C3D (DeepDose-C3D) was trained on cropped CT volumes with four physical inputs. Segment and plan dose accuracy were assessed using local gamma passing ratesγPR(2%/3 mm and 1%/3 mm) and dose-volume histogram metrics. Dose calculation times (inference plus pre/post-processing) were measured on three different graphics processing unit (GPUs).<i>Results.</i>All five models achieved mean localγPRvalues⩾91.0% (2%/3 mm) for segment doses and⩾99.0% (1%/3 mm) for plan doses. Mean per-segment dose calculation times were 79, 67, 298, 490, 356 ms for CNN-ConvLSTM, CNN-Mamba, DoTA, C3D, and DeepDose-C3D, respectively. On the latest-generation GPU available, the corresponding per-plan (average 305 segments) dose calculation times were 5.5, 6.2, 33.6, 38.7, 35.4 s.<i>Significance.</i>Both BEV- and patient-coordinate DL methods achieved accurate photon plan dose calculation, with BEV-based approaches showing more robust segment performance. CNN-ConvLSTM and CNN-Mamba retain comparable accuracy at lower computational cost, enabling fast photon dose calculation.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147778604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sparse probabilistic evaluation for treatment planning: a feasibility study in IMPT head and neck patients.","authors":"Jenneke I de Jong, Steven J M Habraken, Albin Fredriksson, Johan Sundström, Erik Engwall, Sebastiaan Breedveld, Mischa S Hoogeman","doi":"10.1088/1361-6560/ae6223","DOIUrl":"10.1088/1361-6560/ae6223","url":null,"abstract":"<p><p><i>Objective.</i>Probabilistic evaluation improves the trade-off between target coverage and OAR sparing in IMPT but remains computationally demanding. This study proposes sparse probabilistic evaluation (SPE), a computationally efficient approach integrated into a clinical treatment planning system.<i>Approach.</i>Clinical plans of 20 IMPT head and neck cancer patients treated in 2024 were included. SPE used a predefined setup and range error grid with Monte Carlo (MC) computed dose distributions. Two grid settings were evaluated: the maximum error<i>E</i>_max(3<i>σ</i>or 4<i>σ</i>), withσ=(σrandomerror)2+(σsystematicerror)2, and the number of setup error points<i>n</i>_setup(7, 33, 123). Accuracy and duration of SPE with each grid were evaluated in the calibration group (5 patients). A total of 1000 treatments with normally distributed random (<i>σ</i>= 1 mm) and systematic (<i>σ</i>= 0.92 mm) setup and range (<i>σ</i>= 1.5%) errors were simulated. The dose distribution of the nearest error point in the grid was assigned to each fraction. Probability distributions derived from SPE were compared with those from a reference based on 35 000 MC calculations. Agreement was quantified using the mean percentile error (MPE), the mean absolute difference across percentiles 0.01, 0.02, …, 1. The found optimal grid (<i>E</i>_max= 3<i>σ, n</i>_setup= 33) was applied to the validation group (15 patients).<i>Main results.</i>The median MPE in the calibration group decreased significantly as the number of error points increased from 7 (<i>t</i>_avg= 2 min) to 33 (<i>t</i>_avg= 9 min), with no further improvement between 33 and 123 (<i>t</i>_avg= 27 min) error points. Increasing<i>E</i>_maxfrom 3<i>σ</i>to 4<i>σ</i>only improved accuracy for values above the 98th percentile. Applying SPE to the validation group resulted in median errors of 0.02 Gy RBE (range: -0.11-0.07) for the 10th percentile of the<i>D</i>_{99.8%, CTV}distribution and 0.0 Gy RBE (range: -0.14-0.23) for the 95th percentile of the<i>D</i>_{0.03cc,SpinalCord Core}distribution.<i>Significance.</i>SPE achieves sufficient accuracy while requiring clinically acceptable computation times, paving the way for probabilistic evaluation in clinical practice.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147729610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimations of lung structural properties from a single propagation-based dark-field x-ray image.","authors":"Dylan William O'Connell, Kaye S Morgan, Linda C P Croton, James A Pollock, Gary Ruben, Kelly J Crossley, Megan J Wallace, Erin McGillick, Stuart B Hooper, Marcus J Kitchen","doi":"10.1088/1361-6560/ae6966","DOIUrl":"https://doi.org/10.1088/1361-6560/ae6966","url":null,"abstract":"<p><p>In this investigation, we applied a single-projection dark-field imaging technique to gain statistical information on the smallest airway structures within the lung-the alveoli-focusing on their size and number as key indicators of lung health. The algorithm employed here retrieves the projected thickness of the sample from a propagation-based phase contrast image using the transport-of-intensity equation. The first Born approximation is then used to isolate the dark-field signal associated with edge scattering, which increases the visibility of microstructure boundaries. PMMA spheres of known sizes were imaged first as an idealised alveolar model. The dark-field signal was then recovered from propagation-based phase-contrast X-ray images of the lungs of small mammals using this method. The retrieved dark-field signal was found to be proportional to both the alveolar size (R 2 = 0.85) and the number in projection (R 2 = 0.69), and these measurements could be combined to provide an estimate of the total surface area of the alveolar interfaces (R 2 = 0.78). This demonstrates the approach's ability to indicate lung health using the dark-field signal retrieved from a single-phase-contrast X-ray image.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147841379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultra-high dose rate dependent modeling of plasmid DNA damage with TOPAS-nBio.","authors":"Thongchai A M Masilela, J Naoki D-Kondo, Wook-Geun Shin, Mohammad Rezaee, Jay A LaVerne, Harald Paganetti, Bruce Faddegon, Jan Schuemann, José Ramos-Méndez","doi":"10.1088/1361-6560/ae62c6","DOIUrl":"10.1088/1361-6560/ae62c6","url":null,"abstract":"<p><p><i>Objective.</i>FLASH radiotherapy (FLASH-RT) delivers radiation at ultra-high dose rates (UHDR) and has been shown to spare normal tissue while maintaining tumor control (FLASH effect). This could be due to a reduction in radiation-induced DNA damage in normal tissue. Consequently, plasmid assays have been proposed as a way to evaluate these potential differences. However, experimental results have been varied. Track-structure Monte Carlo (MC) simulations may offer a way to disentangle these differences. In this work, we propose a MC model of plasmid DNA damage at UHDR using TOPAS-nBio.<i>Approach</i>. The radiolysis of plasmids (pUC19, 50<i>μ</i>g ml^-1) in an oxygenated (21%) aqueous solution containing DMSO (0.01-100 mM) were modeled in-silico using TOPAS-nBio. 100 Gy was deposited in the solution by 225 kVp x-rays, delivered in a single pulse at conventional (CONV) dose rates (0.1 Gy s^-1) or UHDR (2 × 10⁷Gy s^-1). Two models were evaluated, model 1 in which there was no DNA repair, and model 2 in which oxygen competition was introduced in the form of WR-1065 to induce chemical repair. These models were compared against published experimental data.<i>Main results</i>. At CONV dose rates, the model reproduced published experimental single strand break (SSB) yields across a range of scavenging capacities, with statistical uncertainties within 2% (one standard deviation). At low scavenging capacities, there was a 54.7% reduction in SSBs and a 73.5% reduction in double strand breaks at UHDR compared to CONV. At biologically relevant scavenging capacities this difference was within the statistical uncertainty, and there were no observed differences in chemical repair by WR-1065 between UHDR and CONV.<i>Significance</i>. These results suggest that the reduction in DNA damage observed experimentally at low DNA concentrations and low scavenging capacities is due to the intertrack effect, with no difference predicted at low DNA concentrations and cell-like scavenging capacities.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147778405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design, development and characterization of pregnant anthropomorphic phantoms for fetal dose measurements in proton therapy.","authors":"Marijke De Saint-Hubert, Jana Hohmann, Werner Schoonjans, Dries Colson, Pasquale Lombardo, Olivier Van Hoey, Vjekoslav Kopacin, Hrvoje Brkić, Bertrand Dewit, Charlotte Lejeune, Frédéric Amant, Maarten Lambrecht, Tom Depuydt, Lara Struelens","doi":"10.1088/1361-6560/ae6967","DOIUrl":"https://doi.org/10.1088/1361-6560/ae6967","url":null,"abstract":"<p><strong>Objective: </strong>&#xD;Radiotherapy during pregnancy is clinically challenging due to concerns about fetal radiation exposure. Proton therapy (PT) with pencil beam scanning can reduce out-of-field dose compared with photon therapy; however, secondary neutron production requires accurate fetal dosimetry.&#xD;Approach:&#xD;This study presents the design, material characterization, and computational modeling of two anatomically realistic pregnant anthropomorphic phantoms, MaTORI10 and MaTORI30, representing 10 and 30 weeks of gestation and developed for fetal dose assessment in PT. Candidate materials for lung, soft tissue, and bone-including commercial phantom materials, QA materials, and novel 3D-printed or castable polymers-were evaluated using MCNP 6.2 Monte Carlo simulations and compared with reference pregnant-tissue compositions. Depth-dose distributions, neutron yields, and out-of-field neutron spectra were analyzed to characterize radiological behavior. Suitable materials were implemented in physical phantoms constructed by integrating 3D-printed components and cast bone into an ATOM® female phantom. Pregnancy geometries from the University of Florida pregnant phantom library were merged with ATOM CT and surface scans to generate anatomically realistic models with detector inserts. Voxelized computational versions were generated from CT and surface scans and implemented in TOPAS 3.8. A virtual PT brain irradiation plan (78-116 MeV, 10 cm range SOBP, 5 cm modulation, 3 cm radius), with and without a range shifter (RS), was used to quantify in-field and fetal doses.&#xD;Main Results:&#xD;Material testing showed substantial variability, primarily driven by differences in hydrogen content and density. Both phantoms were successfully constructed and validated by CT imaging. For MaTORI30, modeled fetal dose was on average 29% higher without RS and 21% higher with RS compared to reference materials; for MaTORI10, increases of 10% and 18% were observed.&#xD;Significance:&#xD;The MaTORI10 and MaTORI30 phantoms provide the first anatomically detailed, pregnant anthropomorphic phantoms whose tissue-equivalent properties were computationally characterized for fetal dose assessment in PT. These phantoms provide a platform for experimental and Monte Carlo-based assessment of fetal dose, facilitating safer radiotherapy and optimal planning for pregnant patients.&#xD.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147841377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A beam model and Boltzmann solver for radiotherapy treatment planning of superficial brain metastases using a scanned electron beam at ultra-high (FLASH) dose rate.","authors":"J Bedford, M Gross, F Riemer, Z Amirkhanyan, F Stephan, U Oelfke","doi":"10.1088/1361-6560/ae6225","DOIUrl":"10.1088/1361-6560/ae6225","url":null,"abstract":"<p><p><i>Objective.</i>Contemporary particle accelerators allow for the generation of a narrow pencil beam of electrons which can be scanned to deliver a clinical dose distribution at an ultra-high (FLASH) dose rate. This study develops a radiotherapy beam model and discrete ordinates Boltzmann solver for such an accelerator and then applies the method to treatment planning for superficial brain metastases.<i>Approach.</i>Beam profiles for the quasi-monoenergetic 17.5 MeV electron beam from the Photo Injector Test facility at Deutsches Elektronen-Synchrotron laboratory in Zeuthen (PITZ) were measured at various depths in a water tank using radiochromic film. The incident radiation was modelled as a Gaussian source and the electron distribution in the patient was modelled using classical observations with continuous slowing down approximation (CSDA). This distribution then formed the fixed source component in a discrete ordinates Boltzmann solver. The dose calculation method was then applied to a retrospective study of six patients with superficial brain metastases. The dose due to scanned electrons was compared with that from a single passively scattered proton beam at ultra-high dose rate (UHDR), a proton arc, and a robotic photon treatment.<i>Main results.</i>The calculated dose distribution in a homogeneous water phantom agreed with the measured data to within the 3% experimental uncertainty at all depths. Scanned electron beams were able to provide dose distributions for superficial brain metastases that had a better conformity index than either passively scattered protons or robotic photon treatment (1.02 ± 0.13 versus 1.54 ± 0.13 and 1.35 ± 0.26 respectively; median ± hemi-range; p < 0.05). Brain V_12Gyand skin dose were acceptable for all treatments.<i>Significance.</i>The dose calculation provides a fast and efficient method for inverse planning in the potential clinical application of a scanned electron beam at UHDR. The results show that such an approach could be useful in the treatment of superficial target volumes.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13145812/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147729624","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":"Recent near-infrared approaches to cytochrome-c-oxidase monitoring: a systematic review of instruments and algorithms.","authors":"Robert Ward, Mamadou Diop, Ilias Tachtsidis, Felipe Orihuela-Espina","doi":"10.1088/1361-6560/ae62f3","DOIUrl":"10.1088/1361-6560/ae62f3","url":null,"abstract":"<p><p>Broadband near-infrared spectroscopy (bNIRS) has emerged as a promising technique for non-invasive monitoring of the redox state of cytochrome-c-oxidase (CCO), a key enzyme in cellular energy production. While early work focused on linear approaches based on the modified Beer-Lambert law (MBLL), recent decades have seen substantial diversification in both instrumentation and computational strategies. To capture this evolution, we conducted a systematic review following preferred reporting items for systematic reviews and meta-analyses guidelines across PubMed, Web of Science, ScienceDirect (limited to the journal<i>NeuroImage</i>), and IEEE Xplore, identifying 35 studies that reported novel hardware or algorithmic approaches to CCO reconstruction. Hardware developments ranged from broadband lamps and supercontinuum lasers to light emitting diode and complementary metal-oxide-semiconductor-based miniaturised systems, reflecting a trade-off between spectral coverage, portability, and sensitivity. Algorithmic innovations encompassed refinements of MBLL, diffusion theory, stochastic Monte Carlo modelling, and emerging machine learning methods, each addressing challenges of scattering, spectral overlap, and low signal-to-noise. Despite progress, the field remains limited by variability in instrumentation, standardised validation protocols, and the inherent weakness of the CCO signal relative to haemoglobin. We conclude that advancing bNIRS toward robust, clinically relevant metabolic monitoring will require integration of wearable system design, high-performance computational modelling, and shared benchmarking datasets. This review provides a structured synthesis of hardware and algorithmic advances, highlighting the underlying physics that govern light-tissue interaction and reconstruction, and identifying key directions for future research at the intersection of optical modelling, biomedical engineering, and translational neuroscience.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147778596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}