Physics and Imaging in Radiation Oncology最新文献_第7页

Risk of genitourinary late effects after radiotherapy for prostate cancer associated with early changes in bladder shape 前列腺癌放疗后泌尿生殖系统晚期效应与早期膀胱形状改变的风险

IF 3.3 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2025-10-01 DOI: 10.1016/j.phro.2025.100855

Oscar Casares-Magaz , Renata G. Raidou , Katarina Furmanová , Niclas Pettersson , Vitali Moiseenko , John Einck , Austin Hopper , Rick Knopp , Ludvig P. Muren

Background and purpose

The risk of genitourinary late effects is a major dose-limiting factor in radiotherapy for prostate cancer. By using shape analysis and machine learning, the aim of this study was to evaluate whether bladder shape descriptors from the first week of treatment could identify patients experiencing genitourinary late effects.

Material and methods

From a cohort of 258 prostate cancer patients treated with daily cone-beam computed tomography (CBCT)-guided radiotherapy (prescription doses of 77.4–81.0 Gy), 7 pre-treatment asymptomatic cases experiencing RTOG genitourinary late effects ≥Grade 2 and 21 matched controls were selected. The bladder was manually contoured on each CBCT, and a 17-D vector comprising shape descriptors was used for patient clustering, focusing on bladder contours from the first week of treatment. ANOVA was used to test statistical significance of descriptors across and within clusters.

Results

Of the contours from the first week of treatment, 84 % could be classified in two main clusters with distinct bladder shape characteristics. This cluster stratification remained identical when bladder contours from the entire course of treatment were used. Convexity, elliptic variance and compactness were significantly different between patients with vs. without genitourinary late effects ≥Grade 2 (p < 0.05). Dice Coefficients between predictive models using descriptors of the first week and the voxels’ probability of belonging to the bladder were above 93 ± 6 % (median ± interquartile range).

Conclusion

Bladder shape descriptors in the first week of treatment showed potential to predict the risk of developing genitourinary late effects after radiotherapy for prostate cancer.

背景与目的泌尿生殖系统晚期效应的风险是前列腺癌放疗的一个主要剂量限制因素。通过使用形状分析和机器学习，本研究的目的是评估从治疗第一周开始的膀胱形状描述符是否可以识别患有泌尿生殖系统晚期效应的患者。材料与方法258例接受每日锥束计算机断层扫描（CBCT）引导放射治疗（处方剂量77.4-81.0 Gy）的前列腺癌患者中，选择7例治疗前出现RTOG晚期效应≥2级的无症状患者和21例匹配对照。在每个CBCT上手动绘制膀胱轮廓，并使用包含形状描述符的17-D向量进行患者聚类，重点关注治疗第一周的膀胱轮廓。方差分析用于检验描述符在集群间和集群内的统计显著性。结果治疗后第一周的膀胱外形特征中，有84%的患者可分为两类。当使用整个治疗过程的膀胱轮廓时，这种簇状分层保持相同。泌尿生殖系统晚期效应≥2级患者与非泌尿生殖系统晚期效应患者的凸度、椭圆方差和致密度差异有统计学意义（p < 0.05）。使用第一周描述符的预测模型与属于膀胱的体素概率之间的骰子系数大于93±6%（中位数±四分位数范围）。结论前列腺癌放疗后第一周膀胱形态描述符可预测患者发生泌尿生殖系统晚期反应的风险。

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引用次数: 0

Time-saving potential of daily online adaptive proton therapy for head and neck cancers by reducing number of beams 通过减少光束数量，每日在线自适应质子治疗头颈癌节省时间的潜力

IF 3.3 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2025-10-01 DOI: 10.1016/j.phro.2025.100853

Evangelia Choulilitsa , Katarzyna Czerska , Barbara Bachtiary , Damien Charles Weber , Antony John Lomax , Francesca Albertini

Background and purpose

Standard care for head and neck cancer (HNC) treatment with proton therapy typically involves a 4–6 field Intensity Modulated Proton Therapy plan to enhance robustness towards anatomical changes and patient misalignments. This study aimed to evaluate whether a more efficient plan with fewer beams, designed for faster delivery, can be combined with online daily adaptation (DAPT) to provide treatment of comparable quality, and improve treatment outcomes.

Materials and methods

We retrospectively analyzed five HNC patients with available daily 3D imaging treated at our institution. To simulate DAPT, synthetic Computed Tomography (CT) images were generated by deforming planning CT to each daily Cone-Beam CT with targets and organs-at-risk (OARs) propagated to daily images. Three plans were created per-patient: Offline_SBC and DAPT_SBC with standard, and DAPT_RBC with reduced, beam configuration. DAPT_SBC and DAPT_RBC were reoptimized on daily synCTs, while Offline_SBC followed clinical workflow, with offline replanning as needed.

Results

Offline_SBC showed >5% target underdosage in 15% of fractions, with both adaptive approaches significantly improving coverage. Although DAPT_RBC outperformed Offline_SBC for target coverage, its advantage in OARs sparing was less definitive. DAPT_SBC reduced pooled average normal tissue dose across patients and fractions by 13% and pooled average normal tissue complication probability for xerostomia by 7%. Delivery of DAPT_RBC with fewer beams was 24% faster than plans with conventional arrangement.

Conclusions

Our delivery efficiency study shows that DAPT can allow fewer beams to achieve faster delivery, as shown in case of DAPT_RBC workflow, and a reduction in the dose to normal tissue.

背景和目的质子治疗头颈癌（HNC）的标准护理通常包括4-6场强度调制质子治疗计划，以增强对解剖改变和患者错位的稳健性。本研究旨在评估一种更有效的方案，采用更少的光束，设计更快的交付，是否可以与在线每日适应（DAPT）相结合，提供同等质量的治疗，并改善治疗结果。材料和方法我们回顾性分析了5例在我院接受每日3D成像治疗的HNC患者。为了模拟DAPT，通过将规划CT变形为每个日常锥束CT生成合成计算机断层扫描（CT）图像，并将目标和危险器官（OARs）传播到日常图像中。为每位患者创建了三种方案：标准的OfflineSBC和DAPTSBC，以及减少光束配置的DAPTRBC。在每日同步ct上重新优化DAPTSBC和DAPTRBC，而OfflineSBC则遵循临床工作流程，并根据需要进行离线重新规划。结果sofflinesbc在15%的分数中显示5%的目标剂量不足，两种适应性方法均显著提高了覆盖率。尽管DAPTRBC在目标覆盖方面优于OfflineSBC，但其在桨叶保护方面的优势并不确定。DAPTSBC将患者和部分患者的正常组织总平均剂量降低了13%，口干症的正常组织并发症总平均发生率降低了7%。采用较少光束的DAPTRBC比采用常规布置的方案快24%。结论DAPT的递送效率研究表明，在DAPTRBC的工作流程中，DAPT可以使更少的光束实现更快的递送，并且可以减少对正常组织的剂量。

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引用次数: 0

Using three-dimensional equieffective dose mapping to audit a methodology for calculating permitted doses for head and neck reirradiation 使用三维等有效剂量图审核头颈部再照射允许剂量的计算方法

IF 3.3 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2025-10-01 DOI: 10.1016/j.phro.2025.100867

David Nash , Sarah Muscat , Chelmis M. Thiong’o , Eliana Vasquez Osorio , Antony L. Palmer

Background and purpose

Reirradiation is increasingly common, but accounting for prior dose to the spinal cord and brainstem is challenging. This study compares a simple isodose-based method of previous dose compensation with voxel-wise equivalent dose in 2 Gy fractions (EQD_2/2) dose mapping to assess accuracy and safety.

Materials and methods

Ten head and neck reirradiation cases were retrospectively reviewed. During planning, original dose distributions were mapped onto the reirradiation computed tomography scan. Isodoses within the cord and brainstem were used to segment dose-level substructures, with cumulative doses kept within defined tolerances. Following 3D EQD_2/2 mapping, the same cases were audited by recalculating cumulative maximum doses. Cumulative doses from both methods were compared.

Results

Retrospective EQD_2/2 analysis confirmed all cumulative doses were within tolerance, with up to 9.7 Gy difference between the two methods. In two cases, cord and brainstem doses approached tolerance.

Conclusions

A simple, isodose-based approach to spinal cord and brainstem reirradiation tolerance calculation has been shown to be safe when retrospectively compared with voxel-wise EQD_2/2 mapping. This method can be implemented in any planning system capable of generating contours from isodose lines, offering a practical alternative where advanced EQD_2/2 dose accumulation software is unavailable.

背景和目的放射治疗越来越普遍，但对脊髓和脑干的先前剂量的解释是具有挑战性的。本研究比较了一种简单的基于异剂量的先前剂量补偿方法与2 Gy分数（EQD2/2）剂量测绘的体素等效剂量，以评估准确性和安全性。材料与方法对10例头颈部再照射病例进行回顾性分析。在计划期间，将原始剂量分布映射到再照射计算机断层扫描上。脊髓和脑干内的等剂量用于分割剂量水平的亚结构，累积剂量保持在规定的耐受范围内。在3D EQD2/2制图后，通过重新计算累积最大剂量对相同病例进行审计。比较了两种方法的累积剂量。结果回顾性EQD2/2分析证实所有累积剂量均在耐受范围内，两种方法之间的差异高达9.7 Gy。在两个病例中，脊髓和脑干剂量接近耐受。结论与EQD2/2体素制图相比，一种简单的、基于异剂量的脊髓和脑干再照射耐受计算方法是安全的。该方法可以在任何能够从等剂量线生成等高线的规划系统中实施，在没有先进的EQD2/2剂量累积软件的情况下提供实用的替代方案。

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引用次数: 0

Improving reirradiation of recurrent non-small cell lung cancer through non-coplanar beam arrangements 通过非共面光束排列改善复发性非小细胞肺癌的再照射

IF 3.3 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2025-10-01 DOI: 10.1016/j.phro.2025.100874

Nathan Torelli , Jonas Willmann , Katja Dähler , Madalyne Day , Nicolaus Andratschke , Jan Unkelbach

Background and purpose

Reirradiation for non-small cell lung cancer (NSCLC) is commonly delivered using coplanar techniques. In this study, we investigated whether the selection of favorable non-coplanar beam orientations may limit cumulative doses to critical organs-at-risk (OARs) and thus improve the therapeutic window.

Materials and methods

Fifteen cases of challenging high-dose reirradiation for locoregionally recurrent NSCLC were included in this in-silico study. For each patient, the dose distribution from the previous treatment was first mapped to the new patient anatomy using rigid dose registration, and subsequently converted to equivalent dose in 2 Gy fractions (EQD2). A two-arc non-coplanar reirradiation plan was then generated using an EQD2-based direct aperture optimization algorithm, which allows for the simultaneous optimization of dynamic gantry-couch paths and the cumulative EQD2 distribution. Non-coplanar reirradiation plans were benchmarked against two-arc coplanar plans.

Results

Considerable reductions of at least 5 Gy in the maximum cumulative EQD2 to critical organs were achieved in 6 out of 15 patients using non-coplanar versus coplanar arcs. In particular, the maximum cumulative EQD2 was reduced by up to −9.0 Gy for the bronchial tree, −5.8 Gy for the esophagus, −5.3 Gy for the trachea and −5.6 Gy for the great vessel. At the same time, target coverage and lung EQD2 metrics were comparable for both methods.

Conclusions

The automated selection of favorable non-coplanar beam orientations may reduce the maximum cumulative EQD2 to critical OARs in challenging thoracic reirradiation cases. This allows to explore either better OAR sparing or dose-escalation in future clinical studies.

背景与目的非小细胞肺癌（NSCLC）的放射治疗通常采用共面技术。在这项研究中，我们研究了选择有利的非共面光束方向是否可以限制关键危险器官（OARs）的累积剂量，从而改善治疗窗口。材料和方法本计算机研究纳入了15例局部复发性非小细胞肺癌的高剂量再照射治疗。对于每个患者，先前治疗的剂量分布首先使用严格的剂量登记映射到新的患者解剖结构，随后转换为2 Gy分数的等效剂量（EQD2）。采用基于EQD2的直接孔径优化算法生成两弧非共面再照射方案，同时优化动态龙台路径和累积EQD2分布。非共面再照射计划以两弧共面计划为基准。结果15例患者中有6例采用非共面弧线与共面弧线相比，对关键器官的最大累积EQD2减少了至少5 Gy。特别是，支气管树的最大累积EQD2减少了- 9.0 Gy，食道减少了- 5.8 Gy，气管减少了- 5.3 Gy，大血管减少了- 5.6 Gy。同时，两种方法的靶覆盖率和肺EQD2指标具有可比性。结论在具有挑战性的胸部再照射病例中，自动选择有利的非共面光束方向可将最大累积EQD2降低到临界OARs。这允许在未来的临床研究中探索更好的OAR保留或剂量递增。

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引用次数: 0

Impact of post-correction validation scans on intrafraction tumour misalignment in lung stereotactic body radiotherapy 校正后验证扫描对肺立体定向放射治疗中病灶内肿瘤错位的影响

IF 3.3 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2025-10-01 DOI: 10.1016/j.phro.2025.100868

Maddalena M.G. Rossi, Barbara Stam, Iris Walraven , Jose A. Belderbos, Jan-Jakob Sonke

Background and purpose

Tumour position may change after the acquisition of an initial cone-beam computed-tomography for setup correction (CBCT^PreCor). In this study, the impact of post-correction validation (CBCT^Val) and intra-arc scans (CBCT^IA) on intrafraction tumour misalignment during volumetric-modulated-arc-therapy (VMAT) lung stereotactic-body radiotherapy (SBRT) was evaluated.

Material and methods

Early stage lung cancer patients (n = 167) treated with VMAT SBRT had the following image guided (IG)RT protocol: (1) CBCT^PreCor, (2) CBCT^Val to verify tumour alignment, (3) an intra-arc scan (CBCT^IA) during both VMAT arcs. Additional corrections were made for residual misalignments ≥0.3 cm. The actual and two simulated protocols were analysed: (1) clinical (CBCT^Clin), (2) simulations without validation scans (CBCT^No_Val), (3) simulations without repeat CBCTs (CBCT^No_IFMM). Grand-mean (GM), systematic (∑) and random (σ) tumour misalignment in CBCT^IA-1 and CBCT^IA-2 were calculated. Patient characteristics were evaluated for association with extra validation scans.

Results

CBCT^Val triggered a second correction in 20.4 % of fractions in 47 % of patients and CBCT^IA-1 in 14.4 % of fractions in 40 % of patients. Omitting CBCT^Val increased ∑ and σ ranging from 27–30 % and 20–45 % for the different directions. Omitting also CBCT^IA further increased ∑ ranging from 55–90 %. Omitting CBCT^Val and CBCT^IA would require a 1–2 mm planning target volume margin increase. Respiratory amplitude and body mass index (BMI) were significantly associated with extra corrections (area under the curve: 0.75).

Conclusion

This study demonstrates that CBCT^Val and CBCT^IA-1 reduce geometric uncertainties in VMAT lung SBRT. Respiratory amplitude and BMI were significantly associated with extra corrections but cannot reliably identify patients requiring extra validation scans.

背景和目的在获得初始锥形束计算机断层扫描进行设置校正（CBCTPreCor）后，肿瘤位置可能会发生变化。在这项研究中，评估了校正后验证（CBCTVal）和弧内扫描（CBCTIA）对体积调节弧治疗（VMAT）肺立体定向放射治疗（SBRT）期间病灶内肿瘤错位的影响。材料与方法接受VMAT SBRT治疗的早期肺癌患者（n = 167）采用以下图像引导（IG）RT方案：(1)CBCTPreCor, (2) CBCTVal验证肿瘤排列，(3)两次VMAT弧内扫描（CBCTIA）。对≥0.3 cm的剩余误差进行额外校正。分析了实际方案和两个模拟方案：(1)临床（cbctclinin），(2)没有验证扫描的模拟（CBCTNo_Val），(3)没有重复cbct的模拟（CBCTNo_IFMM）。计算CBCTIA-1和CBCTIA-2肿瘤偏差的均值（GM）、系统性（∑）和随机性（σ）。评估患者特征与额外验证扫描的关联。结果scbctval在47%的患者中有20.4%的分数触发了第二次校正，CBCTIA-1在40%的患者中有14.4%的分数触发了第二次校正。在不同方向上，忽略CBCTVal可使∑和σ分别增加27 ~ 30%和20 ~ 45%。忽略CBCTIA进一步提高了∑55 ~ 90%。忽略CBCTVal和CBCTIA将需要增加1-2毫米的规划目标体积余量。呼吸振幅和体重指数（BMI）与额外校正显著相关（曲线下面积：0.75）。结论CBCTVal和CBCTIA-1可降低VMAT肺SBRT的几何不确定性。呼吸振幅和BMI与额外校正显著相关，但不能可靠地识别需要额外验证扫描的患者。

{"title":"Impact of post-correction validation scans on intrafraction tumour misalignment in lung stereotactic body radiotherapy","authors":"Maddalena M.G. Rossi, Barbara Stam, Iris Walraven , Jose A. Belderbos, Jan-Jakob Sonke","doi":"10.1016/j.phro.2025.100868","DOIUrl":"10.1016/j.phro.2025.100868","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Tumour position may change after the acquisition of an initial cone-beam computed-tomography for setup correction (CBCT<sup>PreCor</sup>). In this study, the impact of post-correction validation (CBCT<sup>Val</sup>) and intra-arc scans (CBCT<sup>IA</sup>) on intrafraction tumour misalignment during volumetric-modulated-arc-therapy (VMAT) lung stereotactic-body radiotherapy (SBRT) was evaluated.</div></div><div><h3>Material and methods</h3><div>Early stage lung cancer patients (n = 167) treated with VMAT SBRT had the following image guided (IG)RT protocol: (1) CBCT<sup>PreCor</sup>, (2) CBCT<sup>Val</sup> to verify tumour alignment, (3) an intra-arc scan (CBCT<sup>IA</sup>) during both VMAT arcs. Additional corrections were made for residual misalignments ≥0.3 cm. The actual and two simulated protocols were analysed: (1) clinical (CBCT<sup>Clin</sup>), (2) simulations without validation scans (CBCT<sup>No_Val</sup>), (3) simulations without repeat CBCTs (CBCT<sup>No_IFMM</sup>). Grand-mean (GM), systematic (∑) and random (σ) tumour misalignment in CBCT<sup>IA-1</sup> and CBCT<sup>IA-2</sup> were calculated. Patient characteristics were evaluated for association with extra validation scans.</div></div><div><h3>Results</h3><div>CBCT<sup>Val</sup> triggered a second correction in 20.4 % of fractions in 47 % of patients and CBCT<sup>IA-1</sup> in 14.4 % of fractions in 40 % of patients. Omitting CBCT<sup>Val</sup> increased ∑ and σ ranging from 27–30 % and 20–45 % for the different directions. Omitting also CBCT<sup>IA</sup> further increased ∑ ranging from 55–90 %. Omitting CBCT<sup>Val</sup> and CBCT<sup>IA</sup> would require a 1–2 mm planning target volume margin increase. Respiratory amplitude and body mass index (BMI) were significantly associated with extra corrections (area under the curve: 0.75).</div></div><div><h3>Conclusion</h3><div>This study demonstrates that CBCT<sup>Val</sup> and CBCT<sup>IA-1</sup> reduce geometric uncertainties in VMAT lung SBRT. Respiratory amplitude and BMI were significantly associated with extra corrections but cannot reliably identify patients requiring extra validation scans.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100868"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145614361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automated target misalignment correction for cone beam computed tomography-based online adaptive radiotherapy of locally advanced lung cancer patients 锥形束ct在线自适应放疗对局部晚期肺癌患者靶位失调的自动校正

IF 3.3 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2025-10-01 DOI: 10.1016/j.phro.2025.100885

Carmen Seller-Oria, Suzanne van Beek, Suzan Gerrets, Sanne van Weerdenburg, Paula Bos, Simon van Kranen, Marloes Frantzen-Steneker, Zeno Gouw, Jan-Jakob Sonke, Peter Remeijer

Background and purpose

Locally advanced lung cancer patients are commonly treated with daily cone beam CT (CBCT) guided radiotherapy using one treatment isocenter. Due to differential motion between primary tumor (GTV_prim) and affected lymph nodes, a compromise needs to be made during daily patient alignment, requiring enlarged treatment margins. In this work, an online adaptive (OART) strategy was proposed to correct for residual target misalignments and enable treatment margin reduction.

Material and methods

We developed in-house an application that produced a synthetic CT (sCT) and delineations to correct for residual target misalignments. A deformation vector field (DVF) was created by using conventional CBCT-to-CT rigid target registrations. The DVF was applied to the planning CT (pCT) and delineations to generate a sCT where GTV_prim was loco-rigidly shifted into the correct position. Twenty CBCTs of eight patients were selected to assess sCTs in terms of GTV_prim position (via CBCT-to-sCT and CBCT-to-pCT registration vector lengths), pixel-wise sCT-pCT Hounsfield unit (HU) errors inside GTV_prim, and sCT-pCT GTV_prim volume differences.

Results

Median vector lengths were 5.1 mm relative to pCTs, and 0.7 mm relative to sCTs, demonstrating the ability of the proposed tool to correct residual misalignments. Median HU errors across all scans were within 1 HU, and the median GTV_prim volume difference was −3.7 %.

Conclusions

A correction method for residual target misalignments in locally advanced lung cancer patients was proposed. It automatically produces sCTs and delineations, enabling OART implementation without the need for manual delineation corrections, and with potentially smaller treatment margins.

背景与目的局部晚期肺癌患者通常采用每日锥形束CT （CBCT）引导的单中心放射治疗。由于原发肿瘤（GTVprim）和受影响淋巴结之间的差异运动，需要在日常患者对齐时做出妥协，需要扩大治疗范围。在这项工作中，提出了一种在线自适应（OART）策略来纠正残留的靶标错位并使治疗余量减小。材料和方法我们在内部开发了一个应用程序，该应用程序产生合成CT （sCT）和圈定来纠正残留的目标错位。采用常规的cbct - ct刚性目标配准方法建立了变形向量场（DVF）。DVF应用于规划CT （pCT）和描绘生成sCT，其中GTVprim局部刚性移位到正确位置。选择8例患者的20个cbct来评估GTVprim位置（通过CBCT-to-sCT和CBCT-to-pCT注册向量长度）、GTVprim内像素级sCT-pCT Hounsfield单位（HU）误差以及sCT-pCT GTVprim体积差异。结果：相对于pct，中位矢量长度为5.1 mm，相对于sct，中位矢量长度为0.7 mm，表明所提出的工具有能力纠正剩余的不对中。所有扫描的HU误差中位数在1 HU以内，GTVprim体积差中位数为- 3.7%。结论提出了局部晚期肺癌患者残留靶位失调的校正方法。它可以自动生成sct和圈定，无需手动圈定校正就可以实现OART，并且潜在的处理余量更小。

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引用次数: 0

Imaging, automation and workflow challenges for online adaptive proton therapy 在线自适应质子治疗的成像、自动化和工作流程挑战

IF 3.3 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2025-10-01 DOI: 10.1016/j.phro.2025.100875

Dirk Wagenaar , Francesca Albertini , Ludvig P. Muren , Barbara Knäusl

引用次数: 0

A dual-layer quality assurance approach leveraging dose prediction for efficient review of automated contours of organs at risk in the brain in radiotherapy 一种双层质量保证方法，利用剂量预测对放射治疗中脑危险器官的自动轮廓进行有效审查

IF 3.3 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2025-10-01 DOI: 10.1016/j.phro.2025.100888

Robert Poel , Amith Kamath , Ekin Ermiş , Jonas Willmann , Elias Rüfenacht , Nicolaus Andratschke , Peter Manser , Daniel M. Aebersold , Mauricio Reyes

Background and Purpose

Despite widespread adaptation of automatic segmentation (AS), manual review and adjustment of generated contours are still essential. This process is time-consuming and identifying clinically relevant corrections remains challenging. Inter-observer variability and the risk of overlooking significant errors further complicate the workflow. A dedicated quality assurance tool is highly relevant to assure quality and speed up the manual review task. The primary aim of this work is to identify critical segmentation errors while reducing unnecessary manual review, enabling efficient integration of AS into routine radiotherapy.

Materials and Methods

We developed an evaluation assistant that assesses contour quality through the geometric measures Dice similarity coefficient and the Hausdorff distance. This was combined with a dose prediction model to determine the clinical relevance. The system was validated on 30 glioblastoma cases with ground truth and manually modified organ at risk (OAR) contours. A traffic light decision matrix classified contours based on geometric and dose parameters, flagging structures for human review.

Results

Out of 507 analyzed OARs, 180 were classified as critical. Our approach identified 173 of these critical structures (sensitivity: 0.96, specificity: 0.55). The system flagged 317 organs (61%) as critical, effectively ruling out 39% as non-critical with only 7 false negatives comprising structures.

Conclusions

Our dual-layer QA approach effectively identifies critical OAR segmentations with high sensitivity and acceptable specificity, potentially reducing manual review requirements significantly. By focusing on clinically relevant dose/volume metric endpoints, this method assures the quality of brain AS results in clinical radiotherapy practice.

背景和目的尽管自动分割（AS）已被广泛应用，但人工检查和调整生成的轮廓仍然是必要的。这个过程很耗时，而且确定临床相关的纠正方法仍然具有挑战性。观察者之间的可变性和忽略重大错误的风险进一步使工作流程复杂化。一个专门的质量保证工具是高度相关的，以确保质量和加快人工审查任务。这项工作的主要目的是识别关键的分割错误，同时减少不必要的人工审查，从而有效地将AS整合到常规放疗中。材料与方法我们开发了一个通过几何度量Dice相似系数和Hausdorff距离来评估轮廓质量的评价助手。这与剂量预测模型相结合，以确定临床相关性。该系统在30例胶质母细胞瘤病例中进行了验证，并使用了地面真相和人工修改的危险器官（OAR）轮廓。交通灯决策矩阵根据几何参数和剂量参数对轮廓进行分类，标记结构供人类审查。结果507例桨叶中，180例为危重桨叶。我们的方法确定了173个这样的关键结构（灵敏度：0.96，特异性：0.55）。该系统将317个器官（61%）标记为关键，有效地排除了39%的非关键，只有7个假阴性包含结构。结论双层QA方法可有效识别关键的声腔分割，灵敏度高，特异性可接受，可显著减少人工复核的需要。通过关注临床相关的剂量/体积度量终点，该方法保证了临床放疗实践中脑AS结果的质量。

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引用次数: 0

Dynamic proton arc treatment planning study for oesophageal cancer 食管癌动态质子弧治疗方案研究

IF 3.3 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2025-10-01 DOI: 10.1016/j.phro.2025.100837

Macarena Chocan Vera , Anne-Catherine Wéra , Hamdiye Ozan , Erik Engwall , Viktor Wase , Otte Marthin , Johan Sundström , Sophie Wuyckens , Karin Haustermans , Ana M. Barragán-Montero , Kevin Souris , John A. Lee , Edmond Sterpin

Particle Arc Therapy (PAT) is considered a promising technique to improve conformity and reduce toxicities. Robustly optimized PAT plans were evaluated versus Intensity Modulated Proton Therapy (IMPT) for oesophageal cancer in 17 patients. Impact of motion, setup and range uncertainties on target coverage, plan quality and Organs At Risk (OAR) doses were assessed. PAT (two 80°–200°arcs) reduced OAR doses (spinal canal

D_{0.05 {cm}^{3}}

: 5.12 Gy (12.8%), lungs and heart

D_{mean}

: 0.39 Gy (8.8%) and 0.83 Gy (10.5%)) while maintaining robustness. Similar toxicities were observed, but delivery time was doubled for PAT, indicating that further development is needed.

粒子弧治疗（PAT）被认为是一种很有前途的改善依从性和减少毒性的技术。对17例食管癌患者进行了稳健优化的PAT方案与强度调节质子治疗（IMPT）的比较。评估运动、设置和范围不确定性对目标覆盖、计划质量和器官危险（OAR）剂量的影响。PAT（两个80°-200°弧）在保持稳健性的同时减少了桨叶剂量(椎管D0.05cm3: 5.12 Gy（12.8%)，肺和心脏Dmean: 0.39 Gy（8.8%）和0.83 Gy(10.5%)）。观察到类似的毒性，但PAT的给药时间增加了一倍，表明需要进一步开发。

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引用次数: 0

Integrating dose–volume histogram parameters and radiomics-based machine learning to identify carbon ion radiotherapy-induced acute oral mucositis in patients with head and neck cancer 整合剂量-体积直方图参数和基于放射组学的机器学习来识别碳离子放疗引起的头颈癌患者急性口腔黏膜炎

IF 3.3 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2025-10-01 DOI: 10.1016/j.phro.2025.100842

Xiangdi Meng , Zhuojun Ju , Makoto Sakai , Yang Li , Atsushi Musha , Nobuteru Kubo , Hidemasa Kawamura , Tatsuya Ohno

Background and purpose

Acute oral mucositis (AOM) is a critical adverse event in head and neck cancer (HNC) requiring early intervention during carbon ion radiotherapy (CIRT). Considering external irradiation and internal mucosal heterogeneity, this study developed a classification model integrating maximum dose (Dmax) and dose-volume-based radiomics (RaV_x) for early identification of grade ≥ 2 AOM.

Methods and materials

We retrospectively analyzed 190 HNC patients treated with CIRT (training: test = 7:3). Radiomic features were extracted from the entire oral mucosa and dose-specific subregions [RaV_x, 10–50 Gy(RBE) in 10-Gy increments]. Feature selection employed logistic regression, random forest, and XGBoost, followed by Spearman’s correlation test. Six two-stage models were developed: Stage 1 stratified patients into high- and low-dose groups using a Dmax threshold (Dmax model), while Stage 2 further classified high-dose patients using a support vector machine (SVM) with selected RaV_x features (RaV_x-SVM model). Classification performance was assessed in training and test sets using bootstrap validation.

Results

Grade ≥ 2 AOM occurred in 61.6 % of patients. The Dmax model with a 50 Gy(RBE) threshold achieved 87.2 % accuracy but had a high false-positive rate (FPR = 31.4 %). The RaV_x-SVM model reduced false positives, with the RaV_{40 Gy(RBE)}-SVM-model performing best. The integrated Dmax₅₀&RaV_{40 Gy(RBE)}-SVM model achieved 97.0 % accuracy (FPR 2.0 %) in training and 96.5 % mean accuracy (mean FPR 4.7 %) in the test.

Conclusions

Dose-volume radiomics effectively identified low-risk AOM patients in the high-dose group. The integrated model demonstrated high accuracy in identifying HNC patients with grade ≥ 2 AOM during CIRT.

背景与目的急性口腔黏膜炎（AOM）是头颈癌（HNC）患者的严重不良事件，需要在碳离子放射治疗（CIRT）中进行早期干预。考虑到外照射和内部粘膜的异质性，本研究建立了一种整合最大剂量（Dmax）和基于剂量-体积的放射组学（RaVx）的分类模型，用于早期识别≥2级AOM。方法与材料我们回顾性分析190例接受CIRT治疗的HNC患者（训练：测试= 7:3）。从整个口腔黏膜和剂量特异性亚区提取放射学特征[RaVx， 10-50 Gy(RBE)， 10-Gy增量]。特征选择采用logistic回归、随机森林和XGBoost，然后进行Spearman相关检验。开发了6个两阶段模型：第一阶段使用Dmax阈值（Dmax模型）将患者分层为高剂量组和低剂量组，而第二阶段使用具有选定RaVx特征的支持向量机（SVM）进一步对高剂量患者进行分类（RaVx-SVM模型）。使用自举验证在训练集和测试集上评估分类性能。结果61.6%的患者发生≥2级AOM。阈值为50 Gy（RBE）的Dmax模型准确率达到87.2%，但假阳性率较高（FPR = 31.4%）。RaVx-SVM模型减少了误报，其中RaV40 Gy(RBE)- svm模型表现最好。集成的Dmax50&；RaV40 Gy(RBE)-SVM模型在训练中达到97.0%的准确率（FPR 2.0%），在测试中达到96.5%的平均准确率（平均FPR 4.7%）。结论剂量-体积放射组学可有效鉴别高剂量组低危AOM患者。该综合模型在CIRT中识别≥2级AOM的HNC患者具有很高的准确性。

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