Physics in medicine and biology最新文献

{"title":"Determination of output correction factors in magnetic fields using two methods for two detectors at the central axis.","authors":"Stephan Frick, Moritz Schneider, Daniela Thorwarth, Ralf-Peter Kapsch","doi":"10.1088/1361-6560/adb934","DOIUrl":"10.1088/1361-6560/adb934","url":null,"abstract":"<p><p><i>Objective.</i>Commissioning an MR-linac treatment planning system requires output correction factors,kB→,Qclin,Qmsrfclin,fmsr, for detectors to accurately measure the linac's output at various field sizes. In this study,kB→,Qclin,Qmsrfclin,fmsrwas determined at the central axis using two methods: one that combines the corrections for the influence of the magnetic field and the small field in a single factor (kB→,Qclin,Qmsrfclin,fmsr), and a second that isolates the magnetic field's influence, allowing the use of output correction factors without a magnetic field,kQclin,Qmsrfclin,fmsr, from literature for determiningkB→,Qclin,Qmsrfclin,fmsr.<i>Approach.</i>To determinekB→,Qclin,Qmsrfclin,fmsrand examine its behaviour across different photon energies and magnetic flux densitiesBin small fields, measurements with an ionization chamber (0.07 cm³sensitive volume) and a solid-state detector were carried out at an experimental facility for both approaches. Changes in absorbed dose to water with field size were determined via Monte Carlo simulations. To evaluate clinical applicability, additional measurements were conducted on a 1.5 T MR-linac.<i>Main results.</i>Both methods determined comparablekB→,Qclin,Qmsrfclin,fmsrresults. For field sizes >3 × 3 cm²,Branging from -1.5 to 1.5 T and photon energies of 6 and 8 MV, no change ofkQclin,Qmsrfclin,fmsras a function of the magnetic field was observed. Comparison with measurement results from the 1.5 T MR-linac confirm this. For ⩽3 × 3 cm²,kB→,Qclin,Qmsrfclin,fmsrdepends on photon energy andB. For 1.5 T and 6 MV,BreduceskQclin,Qmsrfclin,fmsrup to 3% for the ionization chamber and up to 7% for the solid-state detector.<i>Significance.</i>kB→,Qclin,Qmsrfclin,fmsrwere successfully determined for two detectors, enabling their use at a 1.5 T MR-linac. For field sizes of >3 × 3 cm²,kB→,Qclin,Qmsrfclin,fmsris one for most detectors suitable for small field dosimetry for all available perpendicular MR-linac systems, as confirmed in the literature. For these field sizes and detectors, the correction factor accounting for the dosimeter response change in the reference field due to the magnetic field,kB→,Qmsrfmsr, can be used for cross-calibration. Therefore, future research may only focus on small field sizes.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143472827","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":"Guided synthesis of annotated lung CT images with pathologies using a multi-conditioned denoising diffusion probabilistic model (mDDPM).","authors":"Arjun Krishna, Ge Wang, Klaus Mueller","doi":"10.1088/1361-6560/adb9b3","DOIUrl":"10.1088/1361-6560/adb9b3","url":null,"abstract":"<p><p><i>Objective</i>. The training of AI models for medical image diagnostics requires highly accurate, diverse, and large training datasets with annotations and pathologies. Unfortunately, due to privacy and other constraints the amount of medical image data available for AI training remains limited, and this scarcity is exacerbated by the high overhead required for annotation. We address this challenge by introducing a new controlled framework for the generation of synthetic images complete with annotations, incorporating multiple conditional specifications as inputs.<i>Approach</i>. Using lung CT as a case study, we employ a denoising diffusion probabilistic model to train an unconditional large-scale generative model. We extend this with a classifier-free sampling strategy to develop a robust generation framework. This approach enables the generation of constrained and annotated lung CT images that accurately depict anatomy, successfully deceiving experts into perceiving them as real. Most notably, we demonstrate the generalizability of our multi-conditioned sampling approach by producing images with specific pathologies, such as lung nodules at designated locations, within the constrained anatomy.<i>Main results</i>. Our experiments reveal that our proposed approach can effectively produce constrained, annotated and diverse lung CT images that maintain anatomical consistency and fidelity, even for annotations not present in the training datasets. Moreover, our results highlight the superior performance of controlled generative frameworks of this nature compared to nearly every state-of-the-art image generative model when trained on comparable large medical datasets. Finally, we highlight how our approach can be extended to other medical imaging domains, further underscoring the versatility of our method.<i>Significance</i>. The significance of our work lies in its robust approach for generating synthetic images with annotations, facilitating the creation of highly accurate and diverse training datasets for AI applications and its wider applicability to other imaging modalities in medical domains. Our demonstrated capability to faithfully represent anatomy and pathology in generated medical images holds significant potential for various medical imaging applications, with high promise to lead to improved diagnostic accuracy and patient care.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143493230","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":"Anticipating potential bottlenecks in adaptive proton FLASH therapy: a ridge filter reuse strategy.","authors":"Benjamin Roberfroid, Macarena S Chocan Vera, Camille Draguet, John A Lee, Ana M Barragán-Montero, Edmond Sterpin","doi":"10.1088/1361-6560/adb9b2","DOIUrl":"10.1088/1361-6560/adb9b2","url":null,"abstract":"<p><p><i>Objective.</i>Achieving FLASH dose rate with pencil beam scanning intensity modulated proton therapy is challenging. However, utilizing a single energy layer with a ridge filter (RF) can maintain dose rate and conformality. Yet, changes in patient anatomy over the treatment course can render the RF obsolete. Unfortunately, creating a new RF is time-consuming, thus, incompatible with online adaptation. To address this, we propose to re-optimize the spot weights while keeping the same initial RF.<i>Approach.</i>Data from six head and neck cancer patients with a repeated computed tomography (CT₂) were used. FLASH treatment plans were generated with three methods on CT₂: 'full-adaptation' (FA), optimized from scratch with a new RF; 'spot-adaptation only' (SAO), re-using initial RF but adjusting plan spot weights; and 'no adaptation' (NoA) where the dose from initial plans on initial CT (CT₁) was recomputed on CT₂. The prescribed dose per fraction was 9 Gy. Different beam angles were tested for each CT₂(1 beam per fraction). The FA, SAO and NoA plans were then compared on CT₂.<i>Main results.</i>Fractions with SAO showed a median decrease of 0.05 Gy for<i>D</i>98% and a median increase of 0.03 Gy for<i>D</i>2% of CTV when compared to their homologous FA plans on nominal case. Median conformity number decreased by 0.03. Median max dose to spinal cord increased by 0.09 Gy. The largest median increase in mean dose to organs was 0.03 Gy to the mandible. The largest observed median difference in organs receiving a minimal dose rate of 40 Gy s^-1was 0.5% for the mandible. Up to 16 of the 20 evaluated SAO fractions were thus deemed clinically acceptable, with up to 8 NoA plans already acceptable before adaptation.<i>Significance.</i>Proposed SAO workflow showed that for most of our evaluated plans, daily reprinting of RF was not necessary.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143493222","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-Dasu, Mehdi Astaraki, Marta Lazzeroni","doi":"10.1088/1361-6560/adbcf4","DOIUrl":"https://doi.org/10.1088/1361-6560/adbcf4","url":null,"abstract":"<p><strong>Objective: </strong>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.&#xD;&#xD;Approach: 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/mm³isocontour (V₁₀₀). A new metric, cell-volume-product, was defined as the product of the volume with cell density greater than a threshold value (in cells/mm³), and the number of surviving cells within that volume, post-treatment. Tumor progression was assessed at 20±10 days and 90±20 days after treatment. Correlations between the disease progression and the gross tumor volume (GTV), V₁₀₀, and cell-volume-product, were determined using Receiver Operating Characteristic curves.&#xD;&#xD;Main results: For the early follow-up time, the correlation between GTV and tumor progression was not statistically significant (p = 0.684). However, statistically significant correlations with progression were found between V₁₀₀and cell-volume-product with a cell threshold of 10^-6cells/mm³with areas-under-the-curve of 0.69 (p = 0.023) and 0.66 (p = 0.045), respectively. No significant correlations were found for the late follow-up time.&#xD;&#xD;Significance: 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":"2025-03-05","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":"Multi-task interaction learning for accurate segmentation and classification of breast tumors in ultrasound images.","authors":"Shenhai Zheng, Jianfei Li, Lihong Qiao, Xi Gao","doi":"10.1088/1361-6560/adae4d","DOIUrl":"10.1088/1361-6560/adae4d","url":null,"abstract":"<p><p><i>Objective.</i>In breast diagnostic imaging, the morphological variability of breast tumors and the inherent ambiguity of ultrasound images pose significant challenges. Moreover, multi-task computer-aided diagnosis systems in breast imaging may overlook inherent relationships between pixel-wise segmentation and categorical classification tasks.<i>Approach.</i>In this paper, we propose a multi-task learning network with deep inter-task interactions that exploits the inherently relations between two tasks. First, we fuse self-task attention and cross-task attention mechanisms to explore the two types of interaction information, location and semantic, between tasks. In addition, a feature aggregation block is developed based on the channel attention mechanism, which reduces the semantic differences between the decoder and the encoder. To exploit inter-task further, our network uses an circle training strategy to refine heterogeneous feature with the help of segmentation maps obtained from previous training.<i>Main results.</i>The experimental results show that our method achieved excellent performance on the BUSI and BUS-B datasets, with DSCs of 81.95% and 86.41% for segmentation tasks, and F1 scores of 82.13% and 69.01% for classification tasks, respectively.<i>Significance.</i>The proposed multi-task interaction learning not only enhances the performance of all tasks related to breast tumor segmentation and classification but also promotes research in multi-task learning, providing further insights for clinical applications.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143041066","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 validated Monte Carlo model for a CdTe-based photon-counting detector at higher flux rates.","authors":"Sebastian Konrad, Timo Klemm, Martin Hupfer, Karl Stierstorfer, Thorsten M Buzug, Andreas Maier","doi":"10.1088/1361-6560/adb89d","DOIUrl":"10.1088/1361-6560/adb89d","url":null,"abstract":"<p><p><i>Objective.</i>Statistical properties of a CdTe photon-counting detector were simulated using a dedicated Monte Carlo model that includes spatial and spectral correlations. A measurement of the same properties was done to validate the simulation and gain further understanding of the detector.<i>Approach.</i>Photon histories were calculated using a Monte Carlo x-ray simulation program using energy dependent interaction probabilities of the incoming photons. Pulse forms corresponding to photon interaction locations were taken from a pre-calculated pulse shape lookup table and were inserted into simulated pulse trains. These pulse trains were evaluated. Measurements were done on a clinical CT scanner equipped with photon-counting detectors. The examined properties of the detector are detected counts, variances, variance-to-mean-ratios, as well as various spectral-spatial correlations connecting different thresholds in neighboring pixels.<i>Main Results.</i>The simulated data reproduced all trends observed in the statistics of the detector. Spectral correlations between threshold in one pixel showed an excellent agreement between simulation and measurement, both for low and higher fluxes. Spatial correlations between lower thresholds were slightly overestimated in simulations.<i>Significance.</i>The comparison of measured and simulated data shows that the simulation models the statistics of the detector well. This allows further investigation of the detector on a simulated basis and allows using the simulation to further optimize the detector design.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143468457","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":"Acoustic holography in biomedical applications.","authors":"Rachel Burstow, Diana Andrés, Noé Jiménez, Francisco Camarena, Maya Thanou, Antonios N Pouliopoulos","doi":"10.1088/1361-6560/adb89a","DOIUrl":"10.1088/1361-6560/adb89a","url":null,"abstract":"<p><p>Acoustic holography can be used to construct an arbitrary wavefront at a desired 2D plane or 3D volume by beam shaping an emitted field and is a relatively new technique in the field of biomedical applications. Acoustic holography was first theorized in 1985 following Gabor's work in creating optical holograms in the 1940s. Recent developments in 3D printing have led to an easier and faster way to manufacture monolithic acoustic holographic lenses that can be attached to single-element transducers. As ultrasound passes through the lens material, a phase shift is applied to the waves, causing an interference pattern at the 2D image plane or 3D volume, which forms the desired pressure field. This technology has many applications already in use and has become of increasing interest for the biomedical community, particularly for treating regions that are notoriously difficult to operate on, such as the brain. Acoustic holograms could provide a non-invasive, precise, and patient specific way to deliver drugs, induce hyperthermia, or create tissue cell patterns. However, there are still limitations in acoustic holography, such as the difficulties in creating 3D holograms and the passivity of monolithic lenses. This review aims to outline the biomedical applications of acoustic holograms reported to date and discuss their current limitations and the future work that is needed for them to reach their full potential in the biomedical community.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143468470","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":"Alleviating the trade-off between coincidence time resolution and sensitivity using scalable TOF-DOI detectors.","authors":"Yuya Onishi, Ryosuke Ota","doi":"10.1088/1361-6560/adb936","DOIUrl":"10.1088/1361-6560/adb936","url":null,"abstract":"<p><p><i>Objective</i>. Coincidence time resolution (CTR) in time-of-flight positron emission tomography (TOF-PET) has significantly improved with advancements in scintillators, photodetectors, and readout electronics. Achieving a CTR of 100 ps remains challenging due to the need for sufficiently thick scintillators-typically 20 mm-to ensure adequate sensitivity because the photon transit time spread within these thick scintillators impedes achieving 100 ps CTR. Therefore thinner scintillators are preferable for CTR better than 100 ps. To address the trade-off between TOF capability and sensitivity, we propose a readout scheme of PET detectors.<i>Approach</i>. The proposed scheme utilizes two orthogonally stacked one-dimensional PET detectors, enabling the thickness of the scintillators to be reduced to approximately 13 mm without compromising sensitivity. This is achieved by stacking the detectors along the depth-of-interaction (DOI) axis of a PET scanner. We refer to this design as the cross-stacked detector, or xDetector. Furthermore, the xDetector inherently provides DOI information using the same readout scheme.<i>Main results</i>. Experimental evaluations demonstrated that the xDetector achieved the best CTR of 175 ps full width at half maximum (FWHM) and an energy resolution of 11% FWHM at 511 keV with 3 × 3 × 12.8 mm³lutetium oxyorthosilicate crystals, each coupled one-to-one with silicon photomultipliers. The CTRs are between the xDetector and reference detector with a single timing resolution of 111.2 ± 0.8 ps FWHM. In terms of<i>xy</i>-spatial resolution, the xDetector exhibited an asymmetric resolution due to its readout scheme: one resolution was defined by the 3.2 mm readout pitch, while the other was calculated using the center-of-gravity method.<i>Significance</i>. The xDetector effectively resolves the trade-off between TOF capability and sensitivity while offering scalability and DOI capability. By integrating state-of-the-art scintillators, photodetectors, and readout electronics with the xDetector scheme, achieving a CTR of 100 ps FWHM alongside high DOI resolution becomes a practical possibility.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143472825","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":"Evaluation of motion mitigation strategies for carbon ion therapy of abdominal tumors based on non-periodic imaging data.","authors":"Timo Steinsberger, Anestis Nakas, Alessandro Vai, Silvia Molinelli, Marco Donetti, Marco Pullia, Maria Chiara Martire, Cosimo Galeone, Mario Ciocca, Andrea Pella, Viviana Vitolo, Amelia Barcelini, Ester Orlandi, Sara Imparato, Lennart Volz, Guido Baroni, Chiara Paganelli, Marco Durante, Christian Graeff","doi":"10.1088/1361-6560/adb89b","DOIUrl":"10.1088/1361-6560/adb89b","url":null,"abstract":"<p><p><i>Objective.</i>To identify suitable combination strategies for treatment planning and beam delivery in scanned carbon ion therapy of moving tumors.<i>Approach</i>. Carbon ion treatment plans for five abdominal tumors were optimized on four-dimensional (4D) computed tomography (CT) data using the following approaches. 4DITV across all phases and within a gating window, single phase uniform dose, and an innovative 4D tracking internal target volume (ITV) strategy. Delivered single-fraction doses were calculated on time-resolved virtual CT images reconstructed from 2D cine-magnetic resonance imaging series, using a deformable image registration pipeline. Treatment plans were combined with various beam delivery techniques: three-dimensional (no motion mitigation), rescanning, gating, beam tracking, and multi-phase 4D delivery with and without residual tracking (MP4D and MP4DRT) to form in total 11 treatment modalities. Single fraction doses were accumulated to simulate a fractionated treatment.<i>Main results</i>. Breath-sampled treatments using the MP4D and MP4DRT delivery techniques were the only to achieve<i>D</i>₉₅> 95% for hypofractionated treatments, with little dependence on the number of fractions. A combination of MP4DRT with the new 4D tracking ITV approach resulting in conformal dose distributions and demonstrated the greatest robustness against irregular motion and anatomical changes.<i>Significance</i>. This study demonstrates, that real-time adaptive beam delivery strategies can deliver conformal doses within single fractions, thereby enabling hypofractionated treatment schemes that are not feasible with conventional strategies.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143468795","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":"Saskia Laura Corry Damen, Astrid L H M W van Lier, Cornel Zachiu, Bas W Raaymakers","doi":"10.1088/1361-6560/adbbac","DOIUrl":"https://doi.org/10.1088/1361-6560/adbbac","url":null,"abstract":"<p><p>Background and purpose&#xD;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. &#xD;&#xD;Materials and methods&#xD;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. &#xD;The optimized scan was acquired for 7.5 min., in 18 patients and for 15 min., in 10 volunteers at a 1.5T MRL (Unity, Elekta AB). The tracking precision was evaluated and validated by means of three different quality assurance criteria: Structural Similarity Index Metric (SSIM), Inverse Consistency (IC) and Absolute Intensity Difference (AID). &#xD;&#xD;Results&#xD;The optimal sequence was a balanced Fast Field Echo (FFE), which acquired a 3D volume of the abdomen, with a dynamic scan time of 1.8 seconds. 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 >0.9 for the majority of the cases.&#xD;A strong positive correlation (p<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. &#xD;&#xD;Conclusions&#xD;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":"2025-02-28","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}