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Anticipating potential bottlenecks in adaptive proton FLASH therapy: a ridge filter reuse strategy.
IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2025-03-05 DOI: 10.1088/1361-6560/adb9b2
Benjamin Roberfroid, Macarena S Chocan Vera, Camille Draguet, John A Lee, Ana M Barragán-Montero, Edmond Sterpin

Objective.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.Approach.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.Main results.Fractions with SAO showed a median decrease of 0.05 Gy forD98% and a median increase of 0.03 Gy forD2% 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.Significance.Proposed SAO workflow showed that for most of our evaluated plans, daily reprinting of RF was not necessary.

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引用次数: 0
Multi-task interaction learning for accurate segmentation and classification of breast tumors in ultrasound images.
IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2025-03-05 DOI: 10.1088/1361-6560/adae4d
Shenhai Zheng, Jianfei Li, Lihong Qiao, Xi Gao

Objective.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.Approach.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.Main results.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.Significance.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.

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引用次数: 0
A validated Monte Carlo model for a CdTe-based photon-counting detector at higher flux rates.
IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2025-03-04 DOI: 10.1088/1361-6560/adb89d
Sebastian Konrad, Timo Klemm, Martin Hupfer, Karl Stierstorfer, Thorsten M Buzug, Andreas Maier

Objective.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.Approach.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.Main Results.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.Significance.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.

目的:使用包含空间和光谱相关性的专用蒙特卡洛模型模拟碲化镉光子计数探测器的统计特性。对相同特性进行测量,以验证模拟结果并进一步了解探测器:使用蒙特卡罗 X 射线模拟程序计算光子历史,该程序使用了与能量相关的入射光子相互作用概率。从预先计算的脉冲形状查找表中提取与光子相互作用位置相对应的脉冲形式,并将其插入模拟脉冲串中。对这些脉冲串进行了评估。测量是在装有光子计数探测器的临床 CT 扫描仪上进行的。检测器的性能包括检测到的计数、方差、方差-均值比,以及连接相邻像素不同阈值的各种光谱-空间相关性:模拟数据再现了探测器统计中观察到的所有趋势。一个像素中不同阈值之间的光谱相关性显示,无论是低通量还是高通量,模拟和测量结果都非常吻合。模拟结果略微高估了较低阈值之间的空间相关性:测量数据和模拟数据的比较表明,模拟结果很好地模拟了探测器的统计数据。这样就可以在模拟的基础上对探测器进行进一步研究,并利用模拟进一步优化探测器的设计 关键词:光子计数探测器、光谱响应、探测器统计、蒙特卡罗模拟 .
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引用次数: 0
Acoustic holography in biomedical applications.
IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2025-03-03 DOI: 10.1088/1361-6560/adb89a
Rachel Burstow, Diana Andrés, Noé Jiménez, Francisco Camarena, Maya Thanou, Antonios N Pouliopoulos

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.

声全息技术可通过对发射场进行波束赋形,在所需的二维平面或三维体积上构建所需的波阵面,是生物医学应用领域一项相对较新的技术。继 Gabor 在 20 世纪 40 年代创造出光学全息图之后,声全息技术于 1985 年首次被理论化,而 3D 打印技术的最新发展则为制造单片声全息透镜提供了更简便、更快捷的方法,这种透镜可连接到单元素传感器上。当超声波通过透镜材料时,会对其进行相移,从而在二维图像平面上产生干涉图案,形成所需的压力场。这项技术已经有许多应用,并越来越受到医学界的关注,尤其是在治疗众所周知难以操作的区域(如大脑)方面。声学全息图可以提供一种非侵入性、精确和针对特定病人的方式来给药、诱导热疗、创建组织细胞模式,并对许多其他医学领域有所帮助。然而,声全息影像仍存在一些局限性,如创建三维全息图的困难和单片透镜的被动性。本综述旨在概述迄今为止所报道的声全息图在生物医学方面的应用,并讨论其目前的局限性以及为充分发挥其在生物医学界的潜力而需要开展的未来工作。
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引用次数: 0
Alleviating the trade-off between coincidence time resolution and sensitivity using scalable TOF-DOI detectors.
IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2025-03-03 DOI: 10.1088/1361-6560/adb936
Yuya Onishi, Ryosuke Ota

Objective. 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.Approach. 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.Main results. 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 ofxy-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.Significance. 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.

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引用次数: 0
Evaluation of motion mitigation strategies for carbon ion therapy of abdominal tumors based on non-periodic imaging data.
IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2025-03-03 DOI: 10.1088/1361-6560/adb89b
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

Objective.To identify suitable combination strategies for treatment planning and beam delivery in scanned carbon ion therapy of moving tumors.Approach. 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.Main results. Breath-sampled treatments using the MP4D and MP4DRT delivery techniques were the only to achieveD95> 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.Significance. 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.

目标:确定移动肿瘤扫描碳离子疗法的治疗计划和射束传输的合适组合策略:为移动肿瘤的扫描碳离子治疗确定合适的治疗计划和射束输送组合策略:使用以下方法对 4DCT 数据中的五个腹部肿瘤的碳离子治疗计划进行优化:在所有阶段和门窗内的 4DITV、单相均匀剂量 (SPUD) 和创新的 4D 跟踪 ITV 策略。使用可变形图像注册管道,在由二维 cine-MRI 系列重建的时间分辨虚拟 CT 图像上计算出单分量的给药剂量。治疗计划与各种射束输送技术相结合:三维(无运动缓解)、重扫描、门控、光束跟踪以及带或不带残余跟踪(MP4D 和 MP4DRT)的多相 4D 传输,共形成 11 种治疗模式。累积单次分次剂量以模拟分次治疗:使用 MP4D 和 MP4DRT 输送技术的呼吸采样治疗是唯一能使低分次治疗的 D95 > 95 % 的方法,而且与分次数量的关系不大。将 MP4DRT 与新的 4D 跟踪 ITV 方法相结合,可实现适形剂量分布,并对不规则运动和解剖变化表现出最大的稳健性:这项研究表明,实时自适应射束传输策略可以在单次分次治疗中提供适形剂量,从而实现传统策略无法实现的低分次治疗方案。
{"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><sub>95</sub>> 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}
引用次数: 0
Bowel tracking for MR-guided radiotherapy: simultaneous optimization of small bowel imaging and tracking.
IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2025-02-28 DOI: 10.1088/1361-6560/adbbac
Saskia Laura Corry Damen, Astrid L H M W van Lier, Cornel Zachiu, Bas W Raaymakers

Background and purpose 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. Materials and methods 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. 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). Results 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. 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. Conclusions 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.

{"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}
引用次数: 0
Multi-institution investigations of online daily adaptive proton strategies for head and neck cancer patients.
IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2025-02-27 DOI: 10.1088/1361-6560/adbb51
Evangelia Choulilitsa, Mislav Bobić, Brian A Winey, Harald Paganetti, Antony John Lomax, Francesca Albertini

Objective: 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 MGH's online dose reoptimization approach, PSI's online replanning workflow and a full reoptimization adaptive workflow for head and neck cancer (H&N) patients. Approach:10 H&N patients (PSI:5, MGH:5) with daily CBCTs were included. Synthetic CTs were created by deforming the planning CT to each CBCT. Targets and 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 NAMGH and raycasting algorithm for NAPSI. Main results:All adaptive scenarios from both institutions achieved the prescribed daily target dose, with further improvements from online replanning. For all patients, low-dose CTV D98% 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 minutes for iii) and 2.4 for i) while the full dose reoptimization requires 72 minutes. The OAMGH20% 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 D98% occurred. Significance: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. .

{"title":"Multi-institution investigations of online daily adaptive proton strategies for head and neck cancer patients.","authors":"Evangelia Choulilitsa, Mislav Bobić, Brian A Winey, Harald Paganetti, Antony John Lomax, Francesca Albertini","doi":"10.1088/1361-6560/adbb51","DOIUrl":"https://doi.org/10.1088/1361-6560/adbb51","url":null,"abstract":"<p><strong>Objective: </strong>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 MGH's online dose reoptimization approach, PSI's online replanning workflow and a full reoptimization adaptive workflow for head and neck cancer (H&N) patients.&#xD;&#xD;Approach:10 H&N patients (PSI:5, MGH:5) with daily CBCTs were included. Synthetic CTs were created by deforming the planning CT to each CBCT. Targets and 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 NAMGH and raycasting algorithm for NAPSI.&#xD; &#xD;Main results:All adaptive scenarios from both institutions achieved the prescribed daily target dose, with further improvements from online replanning. For all patients, low-dose CTV D98% 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 minutes for iii) and 2.4 for i) while the full dose reoptimization requires 72 minutes. The OAMGH20% 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 D98% occurred.&#xD;&#xD;Significance: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.&#xD.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-02-27","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}
引用次数: 0
A comparative analysis of image harmonization techniques in mitigating differences in CT acquisition and reconstruction. 图像协调技术在减轻CT采集和重建差异中的比较分析。
IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2025-02-27 DOI: 10.1088/1361-6560/adabad
Anil Yadav, Spencer Welland, John M Hoffman, Grace Hyun J Kim, Matthew S Brown, Ashley E Prosper, Denise R Aberle, Michael F McNitt-Gray, William Hsu

Objective. The study aims to systematically characterize the effect of CT parameter variations on images and lung radiomic and deep features, and to evaluate the ability of different image harmonization methods to mitigate the observed variations.Approach. A retrospective in-house sinogram dataset of 100 low-dose chest CT scans was reconstructed by varying radiation dose (100%, 25%, 10%) and reconstruction kernels (smooth, medium, sharp). A set of image processing, convolutional neural network (CNNs), and generative adversarial network-based (GANs) methods were trained to harmonize all image conditions to a reference condition (100% dose, medium kernel). Harmonized scans were evaluated for image similarity using peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and learned perceptual image patch similarity (LPIPS), and for the reproducibility of radiomic and deep features using concordance correlation coefficient (CCC).Main Results. CNNs consistently yielded higher image similarity metrics amongst others; for Sharp/10%, which exhibited the poorest visual similarity, PSNR increased from a mean ± CI of 17.763 ± 0.492 to 31.925 ± 0.571, SSIM from 0.219 ± 0.009 to 0.754 ± 0.017, and LPIPS decreased from 0.490 ± 0.005 to 0.275 ± 0.016. Texture-based radiomic features exhibited a greater degree of variability across conditions, i.e. a CCC of 0.500 ± 0.332, compared to intensity-based features (0.972 ± 0.045). GANs achieved the highest CCC (0.969 ± 0.009 for radiomic and 0.841 ± 0.070 for deep features) amongst others. CNNs are suitable if downstream applications necessitate visual interpretation of images, whereas GANs are better alternatives for generating reproducible quantitative image features needed for machine learning applications.Significance. Understanding the efficacy of harmonization in addressing multi-parameter variability is crucial for optimizing diagnostic accuracy and a critical step toward building generalizable models suitable for clinical use.

目的:本研究旨在系统表征CT参数变化对图像及肺放射学和深部特征的影响,并评估不同图像协调方法减轻观察到的变化的能力。方法:通过不同的辐射剂量(100%,25%,10%)和重建核(平滑,中等,锐利)重建100个低剂量胸部CT扫描的回顾性内部sinogram数据集。训练了一组图像处理、卷积神经网络(cnn)和基于生成对抗网络(gan)的方法,以协调所有图像条件到参考条件(100%剂量,中等核)。利用峰值信噪比(PSNR)、结构相似指数(SSIM)和学习感知图像斑块相似度(LPIPS)评估协调扫描图像的相似性,并利用一致性相关系数(CCC)评估放射学和深度特征的再现性。主要结果:cnn在其他图像中始终获得更高的图像相似度指标;视觉相似性最差的Sharp/10%的PSNR从平均±CI(17.763±0.492)上升到31.925±0.571,SSIM从0.219±0.009上升到0.754±0.017,LPIPS从0.490±0.005下降到0.275±0.016。与基于强度的特征(0.972±0.045)相比,基于纹理的放射学特征在不同条件下表现出更大程度的可变性,即CCC为0.500±0.332。其中,gan的CCC最高(放射性特征为0.969±0.009,深层特征为0.841±0.070)。如果下游应用需要图像的视觉解释,那么卷积神经网络是合适的,而生成对抗网络是生成机器学习应用所需的可重复定量图像特征的更好选择。意义:了解协调在解决多参数变异性方面的功效对于优化诊断准确性至关重要,也是构建适合临床使用的可推广模型的关键一步。
{"title":"A comparative analysis of image harmonization techniques in mitigating differences in CT acquisition and reconstruction.","authors":"Anil Yadav, Spencer Welland, John M Hoffman, Grace Hyun J Kim, Matthew S Brown, Ashley E Prosper, Denise R Aberle, Michael F McNitt-Gray, William Hsu","doi":"10.1088/1361-6560/adabad","DOIUrl":"10.1088/1361-6560/adabad","url":null,"abstract":"<p><p><i>Objective</i>. The study aims to systematically characterize the effect of CT parameter variations on images and lung radiomic and deep features, and to evaluate the ability of different image harmonization methods to mitigate the observed variations.<i>Approach</i>. A retrospective in-house sinogram dataset of 100 low-dose chest CT scans was reconstructed by varying radiation dose (100%, 25%, 10%) and reconstruction kernels (smooth, medium, sharp). A set of image processing, convolutional neural network (CNNs), and generative adversarial network-based (GANs) methods were trained to harmonize all image conditions to a reference condition (100% dose, medium kernel). Harmonized scans were evaluated for image similarity using peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and learned perceptual image patch similarity (LPIPS), and for the reproducibility of radiomic and deep features using concordance correlation coefficient (CCC).<i>Main Results</i>. CNNs consistently yielded higher image similarity metrics amongst others; for Sharp/10%, which exhibited the poorest visual similarity, PSNR increased from a mean ± CI of 17.763 ± 0.492 to 31.925 ± 0.571, SSIM from 0.219 ± 0.009 to 0.754 ± 0.017, and LPIPS decreased from 0.490 ± 0.005 to 0.275 ± 0.016. Texture-based radiomic features exhibited a greater degree of variability across conditions, i.e. a CCC of 0.500 ± 0.332, compared to intensity-based features (0.972 ± 0.045). GANs achieved the highest CCC (0.969 ± 0.009 for radiomic and 0.841 ± 0.070 for deep features) amongst others. CNNs are suitable if downstream applications necessitate visual interpretation of images, whereas GANs are better alternatives for generating reproducible quantitative image features needed for machine learning applications.<i>Significance</i>. Understanding the efficacy of harmonization in addressing multi-parameter variability is crucial for optimizing diagnostic accuracy and a critical step toward building generalizable models suitable for clinical use.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11866762/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143009972","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}
引用次数: 0
DRACO: differentiable reconstruction for arbitrary CBCT orbits.
IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2025-02-27 DOI: 10.1088/1361-6560/adbb50
Chengze Ye, Linda-Sophie Schneider, Yipeng Sun, Mareike Thies, Siyuan Mei, Andreas Maier

Objective: 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.

Approach: 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.

Main results: 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.

Significance: 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. Code Availability: Code is available at https://github.com/ChengzeYe/Defrise-and-Clack-reconstruction.

{"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":"https://doi.org/10.1088/1361-6560/adbb50","url":null,"abstract":"<p><strong>Objective: </strong>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.</p><p><strong>Approach: </strong>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.</p><p><strong>Main results: </strong>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.</p><p><strong>Significance: </strong>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. Code Availability: Code is available at https://github.com/ChengzeYe/Defrise-and-Clack-reconstruction.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-02-27","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}
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