Physics in medicine and biology最新文献

{"title":"Ultra-high energy spectral prompt PET.","authors":"Satyajit Ghosh, Valerio Cosmi, Ruud M Ramakers, Freek J Beekman, Marlies C Goorden","doi":"10.1088/1361-6560/adbfd7","DOIUrl":"10.1088/1361-6560/adbfd7","url":null,"abstract":"<p><p><i>Objective.</i>Utilizing prompt gammas in preclinical pinhole-collimated positron emission tomography (PET) avoids image degradation due to positron range blurring and photon down scatter, enables multi-isotope PET and can improve counting statistics for low-abundance positron emitters. This was earlier reported for¹²⁴I,⁸⁹Zr and simultaneous¹²⁴I -¹⁸F PET using the VECTor scanner (MILabs, The Netherlands), demonstrating sub-mm resolution despite long positron ranges. The aim of the present study is to investigate if such sub-mm PET imaging is also feasible for a large variety of other isotopes including those with extremely high energy prompt gammas (>1 MeV) or with complex emission spectra of prompt gammas.<i>Approach.</i>We use Monte Carlo simulations to assess achievable image resolutions and uniformity across a broad range of spectrum types and emitted prompt gamma energies (603 keV-2.2 MeV), using⁵²Mn,⁹⁴Tc,⁸⁹Zr,⁴⁴Sc,⁸⁶Y,⁷²As,¹²⁴I,³⁸K, and⁶⁶Ga.<i>Main results.</i>Our results indicate that sub-millimeter resolution imaging may be feasible for almost all isotopes investigated, with the currently used cluster pinhole collimators. At prompt gamma energies of 603 keV of¹²⁴I, an image resolution of ∼0.65 mm was achieved, while for emissions at 703, 744, 834, and 909 keV of⁹⁴Tc,⁵²Mn,⁷²As, and⁸⁹Zr, respectively, ∼0.7 mm resolution was obtained. Finally, at ultra-high energies of 1.2 (⁴⁴Sc) and 1.4 MeV (⁵²Mn) resolutions of ∼0.75 mm and ∼0.8 mm could still be achieved although ring artifacts were observed at the highest energies (1.4 MeV). For³⁸K (2.2 MeV), an image resolution of 1.2 mm was achieved utilizing its 2.2 MeV prompt emission.<i>Significance.</i>This work shows that current cluster pinhole collimators are suitable for sub-mm resolution prompt PET up till at least 1.4 MeV. This may open up new avenues to developing new tracer applications and therapies utilizing these PET isotopes.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143616775","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":"Optimisation of magnetic field sensing with optically pumped magnetometers for magnetic detection electrical impedance tomography.","authors":"Kai Mason, Florencia Maurino-Alperovich, Kirill Aristovich, David Holder","doi":"10.1088/1361-6560/adc0df","DOIUrl":"10.1088/1361-6560/adc0df","url":null,"abstract":"<p><p><i>Objective.</i>Magnetic detection electrical impedance tomography (MDEIT) is a novel technique that could enable non-invasive imaging of fast neural activity in the brain. However, commercial magnetometers are not suited to its technical requirements. The purpose of this work was to optimise the number, orientation and size of optically pumped magnetometers (OPMs) for MDEIT and inform the future development of MDEIT-specific magnetometers.<i>Approach.</i>Computational modelling was used to perform forward and inverse MDEIT modelling. Images were reconstructed using three sensing axes, arrays of 16 to 160 magnetometers, and cell sizes ranging from 1 to 18 mm. Image quality was evaluated visually and with the weighted spatial variance.<i>Main results.</i>Single-axis measurements normal to the surface provided the best image quality, and image quality increased with an increase in sensor number and size. The optimal sensing arrangement balancing image quality and practical implementation was measurement normal to the surface of the scalp using between 48 and 96 magnetometers with a cubic cell with an 18 mm side length.<i>Significance.</i>This study can inform future OPM design, showing the size of the vapour cell need not be constrained to that of commercially available OPMs, and that the development of a small array of single-axis, highly sensitive, high-bandwidth OPMs should be prioritised for fast neural MDEIT.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630840","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":"Development and dosimetric evaluation of a modulated intraoperative radiotherapy (mIORT) system using the Zeiss intrabeam device.","authors":"Xavier Jones, Gabor Neveri, Marsha Chin, Pejman Rowshanfarzad","doi":"10.1088/1361-6560/adc06f","DOIUrl":"10.1088/1361-6560/adc06f","url":null,"abstract":"<p><p><i>Objective.</i>Intraoperative radiotherapy (IORT) is a specialised radiotherapy technique that delivers a precise, single high-dose fraction to the tumour bed after surgical removal of the tumour, aiming to eliminate residual cancer cells. This study investigates the incorporation of novel applicators into an existing IORT system to enable dose modulation, performing Monte Carlo (MC) simulations, 3D printing, and experimental validation. The Zeiss Intrabeam IORT device, a low-kV IORT system capable of delivering x-rays nearly isotropically, with energies up to 50 kV, was used in this study.<i>Approach.</i>Applicators were modified to alter dose distributions, incorporating features such as shielding or changes to an ellipsoid shape. The EGSnrc MC code was employed to simulate the dose distributions of each applicator design, generating data such as dose maps, percentage depth dose (PDD) curves, per cent difference maps between shielded and unshielded regions, and energy spectra to characterise each applicator. Gafchromic EBT3 film measurements were performed on select 3D printed applicators, to verify the MC simulations, with dose distribution data extracted for comparison.<i>Main Results.</i>Visual comparisons of dose and percentage different maps indicate a high correlation between the MC simulations and film measurements. Most PDD points for spherical applicators showed deviations within 4%, while ellipsoid applicators had deviations of 14% for the unshielded and 5% for the shielded applicators. All Root Mean Square Error (RMSEs) were below 0.05 for spherical and 0.18 for ellipsoid designs. Based on film data, shielded ellipsoid applicators reduced the dose by ∼99%, 48%, 22%, and 8% at 0.3, 1, 2, and 3 cm, respectively, while shielded spherical applicators achieved ∼83%, 35%, 14%, and 7% reductions at the same distances. Energy spectra for photons exiting shielded regions were also generated.<i>Significance.</i>Results of this study may be used in the development of patient-specific IORT techniques, or the development of a treatment planning system involving mIORT.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143625260","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":"Regularized origin ensemble with a beam prior for range verification in particle therapy with Compton-camera data.","authors":"Jona Kasprzak, Jorge Roser, Julius Werner, Nadja Kohlhase, Andreas Bolke, Lisa-Marie Kaufmann, Magdalena Rafecas","doi":"10.1088/1361-6560/adbfd8","DOIUrl":"10.1088/1361-6560/adbfd8","url":null,"abstract":"<p><p><i>Objective</i>. In particle therapy (PT), several methods are being investigated to help reduce range margins and identify deviations from the original treatment plan, such as prompt-gamma imaging with Compton cameras (CC). To reconstruct the images, the Origin Ensemble (OE) algorithm is commonly used. In the context of PT, artifacts and strong noise often affect CC images. To improve the ability of OE to identify range shifts, and also to enhance image quality, we propose to regularize OE using beam a-priori knowledge (<i>beam prior</i>).<i>Approach</i>. We implemented the beam prior to OE using the class of Gibbs' distribution functions. For evaluation, Monte-Carlo simulations of centered and off-center beams with therapeutic energies impinging on a PMMA target were conducted in GATE. To introduce range shifts, air layers were introduced into the target. In addition, the effect of a bone layer, closer to a realistic scenario, was investigated. OE with the beam prior (BP-OE) and conventional OE (reference) were compared using the spill-over-ratio (SOR) as well as shifts in the distal falloff in projections using cubic splines with Chebyshev nodes.<i>Main results</i>. BP-OE improved the shift estimates by up to 11% compared to conventional OE for centered and up to 250% with off-centered beams. BP-OE decreased the image noise level, improving the SOR significantly by up to 96%.<i>Significance</i>. BP-OE applied to CC data can improve shift estimations compared to conventional OE. The developed Gibbs-based regularization framework also allows further prior functions to be included into OE, for instance, smoothing or edge-preserving priors. BP-OE could be extended to PET-based range verification or multiple-beam scenarios.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143616773","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-short time-echo based ray tracing for transcranial focused ultrasound aberration correction in human calvaria.","authors":"Thomas J Manuel, Thomas Bancel, Thomas Tiennot, Mélanie Didier, Mathieu Santin, Maxime Daniel, David Attali, Mickael Tanter, Stéphane Lehéricy, Nadya Pyatigorskaya, Jean-François Aubry","doi":"10.1088/1361-6560/ad4f44","DOIUrl":"10.1088/1361-6560/ad4f44","url":null,"abstract":"<p><p><i>Objective.</i>Magnetic resonance guided transcranial focused ultrasound holds great promises for treating neurological disorders. This technique relies on skull aberration correction which requires computed tomography (CT) scans of the skull of the patients. Recently, ultra-short time-echo (UTE) magnetic resonance (MR) sequences have unleashed the MRI potential to reveal internal bone structures. In this study, we measure the efficacy of transcranial aberration correction using UTE images.<i>Approach.</i>We compare the efficacy of transcranial aberration correction using UTE scans to CT based correction on four skulls and two targets using a clinical device (Exablate Neuro, Insightec, Israel). We also evaluate the performance of a custom ray tracing algorithm using both UTE and CT estimates of acoustic properties and compare these against the performance of the manufacturer's proprietary aberration correction software.<i>Main results<u>.</u></i>UTE estimated skull maps in Hounsfield units (HU) had a mean absolute error of 242 ± 20 HU (<i>n</i>= 4). The UTE skull maps were sufficiently accurate to improve pressure at the target (no correction: 0.44 ± 0.10, UTE correction: 0.79 ± 0.05, manufacturer CT: 0.80 ± 0.05), pressure confinement ratios (no correction: 0.45 ± 0.10, UTE correction: 0.80 ± 0.05, manufacturer CT: 0.81 ± 0.05), and targeting error (no correction: 1.06 ± 0.42 mm, UTE correction 0.30 ± 0.23 mm, manufacturer CT: 0.32 ± 0.22) (<i>n</i>= 8 for all values). When using CT, our ray tracing algorithm performed slightly better than UTE based correction with pressure at the target (UTE: 0.79 ± 0.05, CT: 0.84 ± 0.04), pressure confinement ratios (UTE: 0.80 ± 0.05, CT: 0.84 ± 0.04), and targeting error (UTE: 0.30 ± 0.23 mm, CT: 0.17 ± 0.15).<i>Significance.</i>These 3D transcranial measurements suggest that UTE sequences could replace CT scans in the case of MR guided focused ultrasound with minimal reduction in performance which will avoid ionizing radiation exposure to the patients and reduce procedure time and cost.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141082130","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":"Real-time dose reconstruction in proton therapy from in-beam PET measurements.","authors":"V V Onecha, A Espinosa-Rodriguez, C Soneira-Landín, F Arias-Valcayo, S Gaitán-Dominguez, V Martinez-Nouvilas, M García-Díez, P Ibáñez, S España, D Sanchez-Parcerisa, F Cerrón-Campoo, J A Vera-Sánchez, A Mazal, J M Udias, L M Fraile","doi":"10.1088/1361-6560/adbfd9","DOIUrl":"10.1088/1361-6560/adbfd9","url":null,"abstract":"<p><p><i>Objective</i>. Clinical implementation of in-beam positron emission tomography (PET) monitoring in proton therapy (PT) requires the integration of an online fast and reliable dose calculation engine. This manuscript reports on the achievement of real-time reconstruction of 3D dose and activity maps with proton range verification from experimental in-beam PET measurements.<i>Approach</i>. Several cylindrical homogeneous PMMA phantoms were irradiated with a monoenergetic 70 MeV proton beam in a clinical facility. Additionally, PMMA range-shifting foils of varying thicknesses were placed at the proximal surface of the phantom to investigate range shift prediction capabilities. PET activity was measured using a state-of-the-art in-house developed six-module PET scanner equipped with online PET reconstruction capabilities. For real-time dose estimation, we integrated this system with an in-beam dose estimation algorithm, which combines a graphical processing unit-based 3D reconstruction algorithm with a dictionary-based software, capable of estimating deposited doses from the 3D PET activity images. The range shift prediction performance has been quantitatively studied in terms of the minimum dose to be delivered and the maximum acquisition time.<i>Main results</i>. With this framework, 3D dose maps were accurately reconstructed and displayed with a delay as short as one second. For a dose fraction of 8.4 Gy at the Bragg peak maximum, range shifts as small as 1 mm could be detected. The quantitative analysis shows that accumulating 20 s of statistics from the start of the irradiation, doses down to 1 Gy could be estimated online with total uncertainties smaller than 2 mm.<i>Significance</i>. The hardware and software combination employed in this work can deliver dose maps and accurately predict range shifts after short acquisition times and small doses, suggesting that real-time monitoring and dose reconstruction during PT are within reach. Future work will focus on testing the methodology in more complex clinical scenarios and on upgrading the PET prototype for increased sensitivity.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143616770","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 feasibility study of automating radiotherapy planning with large language model agents.","authors":"Qingxin Wang, Zhongqiu Wang, Minghua Li, Xinye Ni, Rong Tan, Wenwen Zhang, Maitudi Wubulaishan, Wei Wang, Zhiyong Yuan, Zhen Zhang, Cong Liu","doi":"10.1088/1361-6560/adbff1","DOIUrl":"10.1088/1361-6560/adbff1","url":null,"abstract":"<p><p><i>Objective.</i>Radiotherapy planning requires significant expertise to balance tumor control and organ-at-risk (OAR) sparing. Automated planning can improve both efficiency and quality. This study introduces GPT-Plan, a novel multi-agent system powered by the GPT-4 family of large language models (LLMs), for automating the iterative radiotherapy plan optimization.<i>Approach.</i>GPT-Plan uses LLM-driven agents, mimicking the collaborative clinical workflow of a dosimetrist and physicist, to iteratively generate and evaluate text-based radiotherapy plans based on predefined criteria. Supporting tools assist the agents by leveraging historical plans, mitigating LLM hallucinations, and balancing exploration and exploitation. Performance was evaluated on 12 lung (IMRT) and 5 cervical (VMAT) cancer cases, benchmarked against the ECHO auto-planning method and manual plans. The impact of historical plan retrieval on efficiency was also assessed.<i>Results.</i>For IMRT lung cancer cases, GPT-Plan generated high-quality plans, demonstrating superior target coverage and homogeneity compared to ECHO while maintaining comparable or better OAR sparing. For VMAT cervical cancer cases, plan quality was comparable to a senior physicist and consistently superior to a junior physicist, particularly for OAR sparing. Retrieving historical plans significantly reduced the number of required optimization iterations for lung cases (<i>p</i> < 0.01) and yielded iteration counts comparable to those of the senior physicist for cervical cases (<i>p</i> = 0.313). Occasional LLM hallucinations have been mitigated by self-reflection mechanisms. One limitation was the inaccuracy of vision-based LLMs in interpreting dose images.<i>Significance.</i>This pioneering study demonstrates the feasibility of automating radiotherapy planning using LLM-powered agents for complex treatment decision-making tasks. While challenges remain in addressing LLM limitations, ongoing advancements hold potential for further refining and expanding GPT-Plan's capabilities.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143616768","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":"Real-time 3D synthetic MRI based on kV imaging for motion monitoring of abdominal radiotherapy in a conventional LINAC.","authors":"Paulo Quintero, Can Wu, Hao Zhang, Ricardo Otazo, Laura Cerviño, Wendy Harrys","doi":"10.1088/1361-6560/adbeb5","DOIUrl":"10.1088/1361-6560/adbeb5","url":null,"abstract":"<p><p><i>Introduction.</i>Real-time 2D-kV-triggered images used to evaluate intra-fraction motion during abdominal radiotherapy only provides 2D information with poor soft-tissue contrast. The main goal of this research is to evaluate a novel method that generates synthetic 3D-MRI from single 2D-kV images for online motion monitoring in abdominal radiotherapy.<i>Methods.</i>Deformable image registration (DIR) is performed between one 4D-MRI reference phase and all other phases, and principal-component-analysis (PCA) is implemented on their respective deformation vectors. By sampling 1000 times the PCA eigenvalues and applying the new deformations over a reference CT, 1000 digital reconstructed radiographs (DRRs) were generated to train a convolutional neural network to predict their respective eigenvalues. The method was implemented and tested using a digital phantom (XCAT) and an MRI-compatible phantom (ZEUS) with five DRR angles (0°, 45°, 90°, 135°, 180°). Seven motion scenarios were tested. For model performance, mean absolute error (MAE) and root mean square error (RMSE) were reported. Image quality was evaluated with structure similarity index (SSIM) and normalized RMSE (nRMSE), and target-volume variations were evaluated with volumetric dice coefficient (VDC) and Hausdorff-distance (HD).<i>Results.</i>The model performance across the evaluated angles were MAE_{(XCAT, ZEUS)}= (0.053 ± 0.003, 0.094 ± 0.003), and RMSE_{(XCAT, ZEUS)}= (0.054 ± 0.007, 0.103 ± 0.002). Similarly, SSIM_{(XCAT, ZEUS)}= (0.994 ± 0.001, 0.96 ± 0.02), and nRMSE_{(XCAT, ZEUS)}= (0.13 ± 0.01, 0.17 ± 0.03). For all motion scenarios for XCAT and ZEUS, SSIM were 0.98 ± 0.01 and 0.84 ± 0.02, nRMSE were 0.14 ± 0.01 and 0.27 ± 0.02, VDC were 0.98 ± 0.01 and 0.90 ± 0.01, and HD were 0.24 ± 0.02 mm and 2.3 ± 0.8 mm, respectively, averaged across all angles. Finally, SSIM, nRMSE, VDC and HU values for ZEUS using the^deformedimages as ground truth, presented an improvement of 13%, 28%, 4%, and 76%, respectively.<i>Conclusions</i>. Results from a digital and physical phantom demonstrate a novel approach to generate real-time 3D synthetic MRI from onboard kV images on a conventional LINAC for intra-fraction monitoring in abdominal radiotherapy.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143597638","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":"Joint estimation of activity, attenuation and motion in respiratory-self-gated time-of-flight PET.","authors":"Masoud Elhamiasl, Frederic Jolivet, Ahmadreza Rezaei, Michael Fieseler, Klaus Schäfers, Johan Nuyts, Georg Schramm, Fernando Boada","doi":"10.1088/1361-6560/adbed5","DOIUrl":"10.1088/1361-6560/adbed5","url":null,"abstract":"<p><p><i>Objective</i>. Whole-body positron emission tomography (PET) imaging is often hindered by respiratory motion during acquisition, causing significant degradation in the quality of reconstructed activity images. An additional challenge in PET/CT imaging arises from the respiratory phase mismatch between CT-based attenuation correction and PET acquisition, leading to attenuation artifacts. To address these issues, we propose two new, purely data-driven methods for the joint estimation of activity, attenuation, and motion in respiratory self-gated time-of-flight PET. These methods enable the reconstruction of a single activity image free from motion and attenuation artifacts.<i>Approach</i>. The proposed methods were evaluated using data from the anthropomorphic Wilhelm phantom acquired on a Siemens mCT PET/CT system, as well as three clinical [¹⁸F]FDG PET/CT datasets acquired on a GE DMI PET/CT system. Image quality was assessed visually to identify motion and attenuation artifacts. Lesion uptake values were quantitatively compared across reconstructions without motion modeling, with motion modeling but 'static' attenuation correction, and with our proposed methods.<i>Main results</i>. For the Wilhelm phantom, the proposed methods delivered image quality closely matching the reference reconstruction from a static acquisition. The lesion-to-background contrast for a liver dome lesion improved from 2.0 (no motion correction) to 5.2 (using our proposed methods), matching the contrast from the static acquisition (5.2). In contrast, motion modeling with 'static' attenuation correction yielded a lower contrast of 3.5. In patient datasets, the proposed methods successfully reduced motion artifacts in lung and liver lesions and mitigated attenuation artifacts, demonstrating superior lesion to background separation.<i>Significance</i>. Our proposed methods enable the reconstruction of a single, high-quality activity image that is motion-corrected and free from attenuation artifacts, without the need for external hardware.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143597601","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":"DRACO: differentiable reconstruction for arbitrary CBCT orbits.","authors":"Chengze Ye, Linda-Sophie Schneider, Yipeng Sun, Mareike Thies, Siyuan Mei, Andreas Maier","doi":"10.1088/1361-6560/adbb50","DOIUrl":"10.1088/1361-6560/adbb50","url":null,"abstract":"<p><p><i>Objective</i>. This study introduces a novel method for reconstructing cone beam computed tomography (CBCT) images for arbitrary orbits, addressing the computational and memory challenges associated with traditional iterative reconstruction algorithms.<i>Approach</i>. The proposed method employs a differentiable shift-variant filtered backprojection neural network, optimized for arbitrary trajectories. By integrating known operators into the learning model, the approach minimizes the number of trainable parameters while enhancing model interpretability. This framework adapts seamlessly to specific orbit geometries, including non-continuous trajectories such as circular-plus-arc or sinusoidal paths, enabling faster and more accurate CBCT reconstructions.<i>Main results</i>. Experimental validation demonstrates that the method significantly accelerates reconstruction, reducing computation time by over 97% compared to conventional iterative algorithms. It achieves superior or comparable image quality with reduced noise, as evidenced by a 38.6% reduction in mean squared error, a 7.7% increase in peak signal-to-noise ratio, and a 5.0% improvement in the structural similarity index measure. The flexibility and robustness of the approach are confirmed through its ability to handle data from diverse scan geometries.<i>Significance</i>. This method represents a significant advancement in interventional medical imaging, particularly for robotic C-arm CT systems, enabling real-time, high-quality CBCT reconstructions for customized orbits. It offers a transformative solution for clinical applications requiring computational efficiency and precision in imaging.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143524137","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}