Physics in medicine and biology最新文献

{"title":"Multi-channel MRI reconstruction using cascaded Swinμ transformers with overlapped attention.","authors":"Tahsin Rahman, Ali Bilgin, Sergio D Cabrera","doi":"10.1088/1361-6560/adb933","DOIUrl":"https://doi.org/10.1088/1361-6560/adb933","url":null,"abstract":"<p><p><i>Objective.</i>Deep neural networks have been shown to be very effective at artifact reduction tasks such as magnetic resonance imaging (MRI) reconstruction from undersampled k-space data. In recent years, attention-based vision transformer models have been shown to outperform purely convolutional models at a wide variety of tasks, including MRI reconstruction. Our objective is to investigate the use of different transformer architectures for multi-channel cascaded MRI reconstruction.<i>Approach.</i>In this work, we explore the effective use of cascades of small transformers in multi-channel undersampled MRI reconstruction. We introduce overlapped attention and compare it to hybrid attention in shifted-window (Swin) transformers. We also investigate the impact of the number of Swin transformer layers in each architecture. The proposed methods are compared to state-of-the-art MRI reconstruction methods for undersampled reconstruction on standard 3T and low-field (0.3T) T1-weighted MRI images at multiple acceleration rates.<i>Main results.</i>The models with overlapped attention achieve significantly higher or equivalent quantitative test metrics compared to state-of-the-art convolutional approaches. They also show more consistent reconstruction performance across different acceleration rates compared to their hybrid attention counterparts. We have also shown that transformer architectures with fewer layers can be as effective as those with more layers when used in cascaded MRI reconstruction problems.<i>Significance.</i>The feasibility and effectiveness of cascades of small transformers with overlapped attention for MRI reconstruction is demonstrated without incorporating pre-training of the transformer on ImageNet or other large-scale datasets.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":"70 7","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657431","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":"Dual photoacoustic/ultrasound technologies for preclinical research: current status and future trends.","authors":"Mailyn Pérez-Liva, María Alonso de Leciñana, María Gutiérrez-Fernández, Jorge Camacho Sosa Dias, Jorge F Cruza, Jorge Rodríguez-Pardo, Iván García-Suárez, Fernando Laso-García, Joaquin L Herraiz, Luis Elvira Segura","doi":"10.1088/1361-6560/adb368","DOIUrl":"10.1088/1361-6560/adb368","url":null,"abstract":"<p><p>Photoacoustic (PA) imaging, by integrating optical and ultrasound (US) modalities, combines high spatial resolution with deep tissue penetration, making it a transformative tool in biomedical research. This review presents a comprehensive analysis of the current status of dual PA/US imaging technologies, emphasising their applications in preclinical research. It details advancements in light excitation strategies, including tomographic and microscopic modalities, innovations in pulsed laser and alternative light sources, and US instrumentation. The review further explores preclinical methodologies, encompassing dedicated instrumentation, signal processing, and data analysis techniques essential for PA/US systems. Key applications discussed include the visualisation of blood vessels, micro-circulation, and tissue perfusion; diagnosis and monitoring of inflammation; evaluation of infections, atherosclerosis, burn injuries, healing, and scar formation; assessment of liver and renal diseases; monitoring of epilepsy and neurodegenerative conditions; studies on brain disorders and preeclampsia; cell therapy monitoring; and tumour detection, staging, and recurrence monitoring. Challenges related to imaging depth, resolution, cost, and the translation of contrast agents to clinical practice are analysed, alongside advancements in high-speed acquisition, artificial intelligence-driven reconstruction, and innovative light-delivery methods. While clinical translation remains complex, this review underscores the crucial role of preclinical studies in unravelling fundamental biomedical questions and assessing novel imaging strategies. Ultimately, this review delves into the future trends of dual PA/US imaging, highlighting its potential to bridge preclinical discoveries with clinical applications and drive advances in diagnostics, therapeutic monitoring, and personalised medicine.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143365689","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":"Bowel tracking for MR-guided radiotherapy: simultaneous optimization of small bowel imaging and tracking.","authors":"S L C Damen, A L H M W van Lier, C Zachiu, B W Raaymakers","doi":"10.1088/1361-6560/adbbac","DOIUrl":"10.1088/1361-6560/adbbac","url":null,"abstract":"<p><p><i>Objective</i>. The small bowel is one of the most radiosensitive organs-at-risk during radiotherapy in the pelvis. This is further complicated due to anatomical and physiological motion. Thus, its accurate tracking becomes of particular importance during therapy delivery, to obtain better dose-toxicity relations and/or to perform safe adaptive treatments. The aim of this work is to simultaneously optimize the MR imaging sequence and motion estimation solution towards improved small bowel tracking precision during radiotherapy delivery.<i>Approach</i>. An MRI sequence was optimized, to adhere to the respiratory and peristaltic motion frequencies, by assesing the performance of an image registration algorithm on data acquired on volunteers and patients. In terms of tracking, three registration algorithms, previously-employed in the scope of image-guided radiotherapy, were investigated and optimized. The optimized scan was acquired for 7.5 min, in 18 patients and for 15 min, in 10 volunteers at a 1.5 T MRL (Unity, Elekta AB). The tracking precision was evaluated and validated by means of three different quality assurance criteria: Structural Similarity Index Measure (SSIM), Inverse Consistency (IC) and Absolute Intensity Difference.<i>Main results</i>. The optimal sequence was a balanced Fast Field Echo, which acquired a 3D volume of the abdomen, with a dynamic scan time of 1.8 s. An optical flow algorithm performed best and which was able to resolve most of the motion. This was shown by mean IC values of<1 mm and a mean SSIM>0.9for the majority of the cases. A strong positive correlation (<i>p</i> <0.001) between the registration performance and visceral fat percentage was found, where a higher visceral fat percentage gave a better registration due to the better image contrast.<i>Significance</i>. A method for simultaneous optimization of imaging and tracking was presented, which derived an imaging and registration procedure for accurate small bowel tracking on the MR-Linac.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143531839","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":"Modelling occult lymph node metastases in HNSCC patients with a trinary state hidden Markov model.","authors":"Yoel Samuel Pérez Haas, Roman Ludwig, Esmée Lauren Looman, Vincent Grégoire, Panagiotis Balermpas, Jan Unkelbach","doi":"10.1088/1361-6560/adc235","DOIUrl":"10.1088/1361-6560/adc235","url":null,"abstract":"<p><strong>Objective: </strong>Head-and-neck squamous cell carcinoma frequently metastasize through lymphatic system. Occult metastases are challenging for designing radiotherapy treatment volumes. Literature values indicate that around 20% of lymph node metastases are clinically undetected. However, recent data suggest that this value is only representative for level II whereas the rate of occult metastases is substantially higher in levels III and IV. , while occult metastases are more common in levels III and IV.</p><p><strong>Approach: </strong>We propose a trinary-state Hidden Markov Model to describe ipsilateral lymphatic tumor progression over time. Each lymph node level (LNL) can be in one of three states: healthy, microscopically (pathologically) involved, or macroscopically (clinically) involved. In each time step, a healthy LNL may become microscopically involved due to spread from the primary tumor or an involved upstream LNL. In addition, a microscopically involved LNL may transition to macroscop- ically involved. The probability of occult metastases is obtained as the conditional probability of being in the microscopically involved state given the individual patient's macroscopic involvement. Model parameters are learned from a dataset of 550 patients, including 263 with both pathological and clinical LNL involvement reported.</p><p><strong>Main results: </strong>For oropharyngeal SCC, the model estimates an occult metastases probability below 5% in LNL IV unless LNL III is clinically positive, suggesting potential for reducing elective clinical target volumes. The model's estimated rate of clinically undetected metastases is 82%, 41%, and 34% for LNL II, III, and IV, respectively, which agrees with the data.</p><p><strong>Significance: </strong>The proposed trinary-state HMM represents a methodological extension to a previ- ously published binary-state HMM. The binary HMM distinguished the microscopic and macroscopic involvement via the concept of sensitivity, which may underestimate the risk of occult metastases. The trinary HMM addresses this problem and represents a more natural description of tumor progression.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657062","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 semi-supervised prototypical network for prostate lesion segmentation from multimodality MRI.","authors":"Wen Yan, Yipeng Hu, Qianye Yang, Yunguan Fu, Tom Syer, Zhe Min, Shonit Punwani, Mark Emberton, Dean C Barratt, Carmen C M Cho, Bernard Chiu","doi":"10.1088/1361-6560/adc182","DOIUrl":"https://doi.org/10.1088/1361-6560/adc182","url":null,"abstract":"<p><strong>Objective: </strong>Prostate lesion segmentation from multiparametric MR images is particularly challenging due to the limited availability of labeled data. This scarcity of annotated images makes it difficult for supervised models to learn the complex features necessary for accurate lesion detection and segmentation. &#xD; &#xD;Approach: We proposed a novel semi-supervised algorithm that embeds prototype learning into mean-teacher training to improve the feature representation for unlabeled data. In this method, pseudo-labels generated by the teacher network simultaneously serve as supervision for unlabeled prototype-based segmentation. By enabling prototype segmentation to operate across labeled and unlabeled data, the network enriches the pool of \"lesion representative prototypes\", and allows prototypes to flow bidirectionally-from support-to-query and query-to-support paths. This intersected, bidirectional information flow strengthens the model's generalization ability. This approach is distinct from the mean-teacher algorithm as it involves few-shot training and differs from prototypical learning for adopting unlabeled data for training. &#xD;&#xD;Main results: This study evaluated multiple datasets with 767 patients from three different institutions, including the publicly available PROSTATEx/PROSTATEx2 datasets as the holdout institute for reproducibility. The experimental results showed that the proposed algorithm outperformed state-of-the-art semi-supervised methods with limited labeled data, observing an improvement in Dice similarity coefficient (DSC) with increasing labeled data, ranging from 0.04 to 0.09.&#xD;&#xD;Significance: Our method shows promise in improving segmentation outcomes with limited labeled data and potentially aiding clinicians in making informed patient treatment and management decisions.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143649520","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":"Reference dosimetry for MRI-Linacs: an addendum to the 2020 IPEM code of practice for high-energy photon therapy dosimetry.","authors":"Ilias Billas, Geoff J Budgell, Ben George, Russell A S Thomas, Simon Duane, David J Eaton","doi":"10.1088/1361-6560/adc0e0","DOIUrl":"https://doi.org/10.1088/1361-6560/adc0e0","url":null,"abstract":"<p><p>The 2020 Institute of Physics and Engineering in Medicine code of practice (COP) for megavoltage dosimetry (Eaton et al 2020, Phys. Med. Biol. 65(19): 195006) provides standardised and practical methods for measurement of absorbed dose to water, linked to calibration by the National Physical Laboratory. This report extends the use of that COP to MRI-Linacs through the addition of two correction factors: (1) to account for the influence of the magnetic field on the absorbed dose and model-specific chamber response; and (2) to account for differences in chamber response in the beam spectrum of the MRI-Linac and the Linac where the cross-calibration is performed. Guidance is provided on practical aspects of chamber calibration and dose measurement in MRI-Linac beams, including the use of liquid water, consistent chamber orientation and corrections for other influence quantities. Using this approach uncertainties are similar to other applications of the COP.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630849","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":"Role of modeled high-grade glioma cell invasion and survival on the prediction of tumor progression after radiotherapy.","authors":"Wille Häger, Iuliana Toma-Dașu, Mehdi Astaraki, Marta Lazzeroni","doi":"10.1088/1361-6560/adbcf4","DOIUrl":"10.1088/1361-6560/adbcf4","url":null,"abstract":"<p><p><i>Objective.</i>Glioblastoma (GBM) prognosis remains poor despite progress in radiotherapy and imaging techniques. Tumor recurrence has been attributed to the widespread tumor invasion of normal tissue. Since the complete extension of invasion is undetectable on imaging, it is not deliberately treated. To improve the treatment outcome, models have been developed to predict tumor invasion based standard imaging data. This study aimed to investigate whether a tumor invasion model, together with the predicted number of surviving cells after radiotherapy, could predict tumor progression post-treatment.<i>Approach.</i>A tumor invasion model was applied to 56 cases of GBMs treated with radiotherapy. The invasion was quantified as the volume encompassed by the 100 cells mm^-3isocontour (<i>V</i>₁₀₀). A new metric, cell-volume-product, was defined as the product of the volume with cell density greater than a threshold value (in cells mm^-3), and the number of surviving cells within that volume, post-treatment. Tumor progression was assessed at 20 ± 10 d and 90 ± 20 d after treatment. Correlations between the disease progression and the gross tumor volume (GTV),<i>V</i>₁₀₀, and cell-volume-product, were determined using receiver operating characteristic curves.<i>Main results.</i>For the early follow-up time, the correlation between GTV and tumor progression was not statistically significant (<i>p</i>= 0.684). However, statistically significant correlations with progression were found between<i>V</i>₁₀₀and cell-volume-product with a cell threshold of 10^-6cells mm^-3with areas-under-the-curve of 0.69 (<i>p</i>= 0.023) and 0.66 (<i>p</i>= 0.045), respectively. No significant correlations were found for the late follow-up time.<i>Significance.</i>Modeling tumor spread otherwise undetectable on conventional imaging, as well as radiobiological model predictions of cell survival after treatment, may provide useful information regarding the likelihood of tumor progression at an early follow-up time point, which could potentially lead to improved treatment decisions for patients with GBMs.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143567956","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":"3D<i>π</i>: three-dimensional positron imaging, a novel total-body PET scanner using xenon-doped liquid argon scintillator.","authors":"Azam Zabihi, Xinran Li, Alejandro Ramirez, Iftikhar Ahmad, Manuel D Da Rocha Rolo, Davide Franco, Federico Gabriele, Cristiano Galbiati, Michela Lai, Daniel R Marlow, Andrew Renshaw, Shawn Westerdale, Masayuki Wada","doi":"10.1088/1361-6560/adbaac","DOIUrl":"10.1088/1361-6560/adbaac","url":null,"abstract":"<p><p><i>Objective.</i>This paper introduces a novel PET imaging methodology called 3-dimensional positron imaging (3D<i>π</i>), which integrates total-body coverage, time-of-flight (TOF) technology, ultra-low dose imaging capabilities, and ultra-fast readout electronics inspired by emerging technology from the DarkSide collaboration.<i>Approach.</i>The study evaluates the performance of 3D<i>π</i>using Monte Carlo simulations based on NEMA NU 2-2018 protocols. The methodology employs a homogenous, monolithic scintillator composed of liquid argon (LAr) doped with xenon (Xe) with silicon photomultipliers (SiPMs) operating at cryogenic temperatures.<i>Main results.</i>Substantial improvements in system performance are observed, with the 3D<i>π</i>system achieving a noise equivalent count rate of 3.2 Mcps at 17.3 kBq ml^-1, continuing to increase up to 4.3 Mcps at 40 kBq ml^-1. Spatial resolution measurements show an average FWHM of 2.7 mm across both axial positions. The system exhibits superior sensitivity, with values reaching 373 kcps MBq^-1with a line source at the center of the field of view. Additionally, 3D<i>π</i>achieves a TOF resolution of 151 ps at 5.3 kBq ml^-1, highlighting its potential to produce high-quality images with reduced noise levels.<i>Significance.</i>The study underscores the potential of 3D<i>π</i>in improving PET imaging performance, offering the potential for shorter scan times and reduced radiation exposure for patients. The Xe-doped LAr offers advantages such as fast scintillation, enhanced light yield, and cost-effectiveness. Future research will focus on optimizing system geometry and further refining reconstruction algorithms to exploit the strengths of 3D<i>π</i>for clinical applications.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143516494","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":"IPEM code of practice for proton therapy dosimetry based on the NPL primary standard proton calorimeter calibration service.","authors":"Stuart Green, Ana Lourenço, Hugo Palmans, Nigel Lee, Richard A Amos, Derek D' Souza, Francesca Fiorini, Frank Van Den Heuvel, Andrzej Kacperek, Ranald Mackay, John Pettingell, Russell Thomas","doi":"10.1088/1361-6560/adad2e","DOIUrl":"10.1088/1361-6560/adad2e","url":null,"abstract":"<p><p>Internationally, reference dosimetry for clinical proton beams largely follows the guidelines published by the International Atomic Energy Agency (IAEA TRS-398 Rev. 1 (2024). This approach yields a relative standard uncertainty of 1.7% (<i>k</i>= 1) on the absorbed dose to water determined under reference conditions. The new IPEM code of practice presented here, enables the relative standard uncertainty on the absorbed dose to water measured under reference conditions to be reduced to 1.0% (<i>k</i>= 1). This improvement is based on the absorbed dose to water calibration service for proton beams provided by the National Physical Laboratory (NPL), the UK's primary standards laboratory. This significantly reduced uncertainty is achieved through the use of a primary standard level graphite calorimeter to derive absorbed dose to water directly in the clinical department's beam. This eliminates the need for beam quality correction factors (kQ,Q0) as required by the IAEA TRS-398 approach. The portable primary standard level graphite calorimeter, developed over a number of years at the NPL, is sufficiently robust to be useable in the proton beams of clinical facilities both in the UK and overseas. The new code of practice involves performing reference dosimetry measurements directly traceable to the primary standard level graphite calorimeter in a clinical proton beam. Calibration of an ionisation chamber is performed in the centre of a standard test volume (STV) of dose, defined here to be a 10 × 10 × 10 cm volume in water, centred at a depth of 15 cm. Further STVs at reduced and increased depths are also utilised. The designated ionisation chambers are Roos-type plane-parallel chambers. This article provides all the necessary background material, formalism, and specifications of reference conditions required to implement reference dosimetry according to this new code of practice. The Annexes provide a detailed review of ion recombination and how this should be assessed (Annex A1) and detailed work instructions for creating and delivering the STVs (Annex A2).</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143023993","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-institution investigations of online daily adaptive proton strategies for head and neck cancer patients.","authors":"Evangelia Choulilitsa, Mislav Bobić, Brian Winey, Harald Paganetti, Antony J Lomax, Francesca Albertini","doi":"10.1088/1361-6560/adbb51","DOIUrl":"10.1088/1361-6560/adbb51","url":null,"abstract":"<p><p><i>Objective.</i>Fast computation of daily reoptimization is key for an efficient online adaptive proton therapy workflow. Various approaches aim to expedite this process, often compromising daily dose. This study compares Massachusetts General Hospital's (MGH's) online dose reoptimization approach, Paul Scherrer Institute's (PSI's) online replanning workflow and a full reoptimization adaptive workflow for head and neck cancer (H&N) patients.<i>Approach.</i>Ten H&N patients (PSI:5, MGH:5) with daily cone beam computed tomographys (CBCTs) were included. Synthetic CTs were created by deforming the planning CT to each CBCT. Targets and organs at risk (OARs) were deformed on daily images. Three adaptive approaches were investigated: (i) an online dose reoptimization approach modifying the fluence of a subset of beamlets, (ii) full reoptimization adaptive workflow modifying the fluence of all beamlets, and (iii) a full online replanning approach, allowing the optimizer to modify both fluence and position of all beamlets. Two non-adapted (NA) scenarios were simulated by recalculating the original plan on the daily image using: Monte Carlo for NA_MGHand raycasting algorithm for NA_PSI.<i>Main results.</i>All adaptive scenarios from both institutions achieved the prescribed daily target dose, with further improvements from online replanning. For all patients, low-dose CTV D_98%shows mean daily deviations of -2.2%, -1.1%, and 0.4% for workflows (i), (ii), and (iii), respectively. For the online adaptive scenarios, plan optimization averages 2.2 min for (iii) and 2.4 for (i) while the full dose reoptimization requires 72 min. The OA_MGH20%dose reoptimization approach produced results comparable to online replanning for most patients and fractions. However, for one patient, differences up to 11% in low-dose CTV D_98%occurred.<i>Significance.</i>Despite significant anatomical changes, all three adaptive approaches ensure target coverage without compromising OAR sparing. Our data suggests 20% dose reoptimization suffices, for most cases, yielding comparable results to online replanning with a marginal time increase due to Monte Carlo. For optimal daily adaptation, a rapid online replanning is preferable.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143524138","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}