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

External validation of a multimodality deep-learning normal tissue complication probability model for mandibular osteoradionecrosis trained on 3D radiation distribution maps and clinical variables 根据三维辐射分布图和临床变量训练的下颌骨骨坏死多模态深度学习正常组织并发症概率模型的外部验证

IF 3.4 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100668

Laia Humbert-Vidan , Christian R. Hansen , Vinod Patel , Jørgen Johansen , Andrew P. King , Teresa Guerrero Urbano

Background and purpose

While the inclusion of spatial dose information in deep learning (DL)-based normal-tissue complication probability (NTCP) models has been the focus of recent research studies, external validation is still lacking. This study aimed to externally validate a DL-based NTCP model for mandibular osteoradionecrosis (ORN) trained on 3D radiation dose distribution maps and clinical variables.

Methods and materials

A 3D DenseNet-40 convolutional neural network (3D-mDN40) was trained on clinical and radiation dose distribution maps on a retrospective class-balanced matched cohort of 184 subjects. A second model (3D-DN40) was trained on dose maps only and both DL models were compared to a logistic regression (LR) model trained on DVH metrics and clinical variables. All models were externally validated by means of their discriminative ability and calibration on an independent dataset of 82 subjects.

Results

No significant difference in performance was observed between models. In internal validation, these exhibited similar Brier scores around 0.2, Log Loss values of 0.6–0.7 and ROC AUC values around 0.7 (internal) and 0.6 (external). Differences in clinical variable distributions and their effect sizes were observed between internal and external cohorts, such as smoking status (0.6 vs. 0.1) and chemotherapy (0.1 vs. −0.5), respectively.

Conclusion

To our knowledge, this is the first study to externally validate a multimodality DL-based ORN NTCP model. Utilising mandible dose distribution maps, these models show promise for enhancing spatial risk assessment and guiding dental and oncological decision-making, though further research is essential to address overfitting and domain shift for reliable clinical use.

背景和目的虽然将空间剂量信息纳入基于深度学习（DL）的正常组织并发症概率（NTCP）模型是近期研究的重点，但仍缺乏外部验证。本研究旨在从外部验证基于三维辐射剂量分布图和临床变量训练的下颌骨骨坏死（ORN）深度学习并发症概率（NTCP）模型。方法和材料在184名受试者的回顾性类平衡匹配队列中，根据临床和辐射剂量分布图训练了一个三维DenseNet-40卷积神经网络（3D-mDN40）。第二个模型（3D-DN40）仅在剂量分布图上进行了训练，两个 DL 模型都与在 DVH 指标和临床变量上训练的逻辑回归 (LR) 模型进行了比较。所有模型都在一个由 82 名受试者组成的独立数据集上通过判别能力和校准进行了外部验证。在内部验证中，这些模型表现出相似的 Brier 分数（0.2 左右）、Log Loss 值（0.6-0.7）和 ROC AUC 值（0.7（内部）和 0.6（外部））。内部和外部队列之间的临床变量分布及其效应大小存在差异，如吸烟状态（0.6 vs. 0.1）和化疗（0.1 vs. -0.5）。利用下颌骨剂量分布图，这些模型有望加强空间风险评估，并指导牙科和肿瘤决策，但为了可靠地应用于临床，解决过拟合和域偏移问题还需要进一步的研究。

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引用次数: 0

Accuracy, repeatability, and reproducibility of water-fat magnetic resonance imaging in a phantom and healthy volunteer 模型和健康志愿者的水脂磁共振成像的准确性、可重复性和再现性

IF 3.4 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100651

Anouk Corbeau , Pien van Gastel , Piotr A. Wielopolski , Nick de Jong , Carien L. Creutzberg , Uulke A. van der Heide , Stephanie M. de Boer , Eleftheria Astreinidou

Bone marrow (BM) damage due to chemoradiotherapy can increase BM fat in cervical cancer patients. Water-fat magnetic resonance (MR) scans were performed on a phantom and a healthy female volunteer to validate proton density fat fraction accuracy, reproducibility, and repeatability across different vendors, field strengths, and protocols. Phantom measurements showed a high accuracy, high repeatability, and excellent reproducibility. Volunteer measurements had an excellent intra- and interreader reliability, good repeatability, and moderate to good reproducibility. Water-fat MRI show potential for quantification of longitudinal vertebral BM fat changes. Further studies are needed to validate and extend these findings for broader clinical applicability.

化放疗导致的骨髓（BM）损伤会增加宫颈癌患者的骨髓脂肪。为了验证质子密度脂肪分数的准确性、可重复性以及在不同供应商、场强和方案下的可重复性，我们在一个模型和一名健康女性志愿者身上进行了水脂肪磁共振（MR）扫描。模型测量结果显示了高准确性、高重复性和出色的再现性。志愿者的测量结果在读取器内部和读取器之间具有极佳的可靠性、良好的可重复性和中等至良好的再现性。水脂磁共振成像显示出量化椎体基质脂肪纵向变化的潜力。还需要进一步的研究来验证和扩展这些发现的临床适用性。

引用次数: 0

Comparing robust proton versus online adaptive photon radiotherapy for short-course treatment of rectal cancer 比较用于直肠癌短程治疗的强质子放疗和在线自适应光子放疗

IF 3.4 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100663

Johanna A. Hundvin , Unn Hege Lilleøren , Alexander Valdman , Bruno Sorcini , John Alfred Brennsæter , Camilla G. Boer , Helge E.S. Pettersen , Kathrine R. Redalen , Inger Marie Løes , Sara Pilskog

Background and purpose

Image-guided proton beam therapy (IG-PBT) and cone-beam CT (CBCT)-based online adaptive photon radiotherapy (oART) have potentials to restrict radiation toxicity. They are both hypothesised to reduce therapy limiting bowel toxicity in the multimodality treatment of locally advanced rectal cancer (LARC). This study aimed to quantify the difference in relevant dose-volume metrics for these modalities.

Material and Methods

Six-degrees-of-freedom IG-PBT and oART short-course radiotherapy (SCRT) were simulated for 18 LARC patients. Relative biological effectiveness (RBE) was 1.1 for IG-PBT. Delivered dose was evaluated using post-CBCTs. Target coverage was considered robust if average dose to 99% of the clinical target volume was

\geq

95% of the prescription. Organ at risk (OAR) doses were compared using dose-volume histograms and severe bowel toxicity estimated using dose–response modelling.

Results

Target coverage was robust in all patients for oART and all but one patient for IG-PBT. For the main OARs, IG-PBT increased the volume exposed to

\geq

15 Gy (RBE), but reduced volumes exposed to lower doses. Both low- and high-dose exposure to bowel loops were significantly different between the modalities (median (interquartile range) IG-PBT-V_8.9Gy(RBE) = 92 (51–156) cm³, oART-V_8.9Gy(RBE) = 166 (107–234) cm³, p < 0.001; IG-PBT-V_23Gy(RBE) = 62 (25–106) cm³, oART-V_23Gy(RBE) = 38 (18–75) cm³, p < 0.001), translating into similar total grade ≥ 3 bowel toxicity risk.

Conclusion

IG-PBT and oART delivered comparable and satisfying target coverage in SCRT for LARC with similar estimated risk of severe bowel toxicity. Volumes of OAR exposed to 15 Gy (RBE) or more were reduced by oART, while IG-PBT reduced the volumes receiving doses below this level.

背景和目的图像引导质子束疗法（IG-PBT）和基于锥束 CT（CBCT）的在线自适应光子放疗（oART）具有限制放射毒性的潜力。在局部晚期直肠癌（LARC）的多模态治疗中，这两种疗法都被假定能减少限制性肠毒性。本研究旨在量化这些模式的相关剂量-体积指标的差异。材料与方法模拟 18 名 LARC 患者的六自由度 IG-PBT 和 oART 短程放疗（SCRT）。IG-PBT 的相对生物有效性 (RBE) 为 1.1。使用后 CBCT 对投放剂量进行评估。如果 99% 临床靶体积的平均剂量≥处方剂量的 95%，则认为目标覆盖稳健。使用剂量-体积直方图比较风险器官（OAR）剂量，并使用剂量-反应模型估计严重肠毒性。对于主要的 OARs，IG-PBT 增加了≥ 15 Gy（RBE）的暴露量，但减少了较低剂量的暴露量。低剂量和高剂量暴露于肠道襻的情况在不同模式之间有显著差异（中位数（四分位数间距）IG-PBT-V8.9Gy(RBE) = 92 (51-156) cm3，oART-V8.9Gy(RBE) = 166 (107-234) cm3，p < 0.001；IG-PBT-V23Gy(RBE) = 62 (25-106) cm3，oART-V23Gy(RBE) = 38 (18-75) cm3，p < 0.001），转化为相似的总≥3级肠毒性风险。oART 减少了暴露于 15 Gy（RBE）或更高剂量的 OAR 的体积，而 IG-PBT 则减少了低于此剂量的体积。

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引用次数: 0

Magnetic resonance-guided stereotactic body radiation therapy for pancreatic oligometastases from renal cell carcinoma 磁共振引导下的立体定向体放射治疗肾细胞癌胰腺寡转移瘤。

IF 3.4 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100683

Jonna K. van Vulpen , Hidde Eijkelenkamp , Guus Grimbergen , Frank J. Wessels , Sasja F. Mulder , Gert J. Meijer , Martijn P.W. Intven

Stereotactic body radiation therapy (SBRT) may be a non-invasive strategy to treat patients with pancreatic oligometastases from renal cell carcinoma (RCC). We analyzed 11 patients treated with MR-guided SBRT to 31 pancreatic oligometastases. At a median follow-up of 31.6 months, 1-year and 2-year freedom from local progression was 100 % and 95 % (95 % CI 86–100 %), respectively. Moreover, 1-year and 2-year freedom from systemic therapy was 91 % (95 %CI 75–100 %) and 82 % (95 % CI 62–100 %), respectively. MR-guided SBRT may be a safe and effective treatment option for pancreatic oligometastases from RCC.

立体定向全身放射治疗（SBRT）可能是治疗肾细胞癌（RCC）胰腺少转移患者的一种非侵入性策略。我们分析了11例接受mr引导的SBRT治疗的31例胰腺少转移灶。在中位31.6个月的随访中，1年和2年的局部进展自由度分别为100%和95% （95% CI 86- 100%）。此外，1年和2年的全身治疗自由度分别为91% （95% CI 75- 100%）和82% （95% CI 62- 100%）。mr引导下的SBRT可能是一种安全有效的治疗RCC胰腺少转移的选择。

引用次数: 0

The influence of cardiac substructure dose on survival in a large lung cancer stereotactic radiotherapy cohort using a robust personalized contour analysis 在一个大型肺癌立体定向放疗队列中，心脏亚结构剂量对生存的影响采用了稳健的个性化轮廓分析。

IF 3.4 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100686

Luuk H.G. van der Pol , Jacquelien Pomp , Firdaus A.A. Mohamed Hoesein , Bas W. Raaymakers , Joost J.C. Verhoeff , Martin F. Fast

Background/Purpose: Radiation-induced cardiac toxicity in lung cancer patients has received increased attention since RTOG 0617. However, large cohort studies with accurate cardiac substructure (CS) contours are lacking, limiting our understanding of the potential influence of individual CSs. Here, we analyse the correlation between CS dose and overall survival (OS) while accounting for deep learning (DL) contouring uncertainty,

α / β

uncertainty and different modelling approaches. Materials/Methods: This single institution, retrospective cohort study includes 730 patients (early-stage tumours (I or II). All treated: 2009–2019), who received stereotactic body radiotherapy (≥ 5 Gy per fraction). A DL model was trained on 70 manually contoured patients to create 12 cardio-vascular structures. Structures with median dice score above 0.8 and mean surface distance (MSD) <2 mm during testing, were further analysed. Patientspecific CS dose was used to find the correlation between CS dose and OS with elastic net and random survival forest models (with and without confounding clinical factors). The influence of delineation-induced dose uncertainty on OS was investigated by expanding/contracting the DL-created contours using the MSD ± 2 standard deviations. Results: Eight CS contours met the required performance level. The left atrium (LA) mean dose was significant for OS and an LA mean dose of 3.3 Gy (in EQD2) was found as a significant dose stratum. Conclusion: Explicitly accounting for input parameter uncertainty in lung cancer survival modelling was crucial in robustly identifying critical CS dose parameters. Using this robust methodology, LA mean dose was revealed as the most influential CS dose parameter.

背景/目的：自RTOG 0617以来，肺癌患者的辐射诱发心脏毒性受到越来越多的关注。然而，缺乏具有准确心脏亚结构（CS）轮廓的大型队列研究，限制了我们对个体CS潜在影响的理解。在这里，我们分析了CS剂量与总生存（OS）之间的相关性，同时考虑了深度学习（DL）轮廓不确定性、α / β不确定性和不同的建模方法。材料/方法：这项单机构、回顾性队列研究包括730例患者（早期肿瘤（I或II），所有治疗时间：2009-2019年），接受立体定向全身放疗（≥5 Gy / fraction）。在70例人工轮廓患者上训练DL模型以创建12个心血管结构。骰子中位数评分大于0.8，平均表面距离（MSD）的结构。结果：8个CS轮廓达到要求的性能水平。左心房（LA）平均剂量对OS有显著性意义，其中3.3 Gy的LA平均剂量（EQD2）为显著剂量层。结论：明确考虑肺癌生存模型中输入参数的不确定性对于确定关键CS剂量参数至关重要。使用这种稳健的方法，LA平均剂量被揭示为最具影响力的CS剂量参数。

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引用次数: 0

Development and international multicentre pilot testing of a postal dosimetry audit methodology for high dose rate brachytherapy 高剂量率近距离放射治疗邮寄剂量测量审计方法的开发和国际多中心试点测试

IF 3.4 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100665

Alexis Dimitriadis, Anna Becker, Krzysztof Chelminski, Pavel Kazantsev, Egor Titovich, Godfrey Azangwe, Liset de la Fuente Rosales, Benjamin Kellogg, Mauro Carrara, Jamema Swamidas

Background and Purpose

Dosimetry audits are essential for reducing errors in brachytherapy. A postal dosimetry audit methodology was developed and tested in an international multicentre pilot, to assess the accuracy of the Reference Air Kerma Rate of ¹⁹²Ir and ⁶⁰Co brachytherapy sources.

Materials and Methods

A compact phantom made of polymethyl methacrylate was developed to accommodate two catheters, a radiophotoluminescence dosimeter (RPLD) for dose measurements and a Gafchromic (RTQA2) film strip for source position verification. Deviations of the audit setup from TG-43 conditions were quantified experimentally and compared to previous Monte Carlo (MC) simulations. A measurement uncertainty budget was estimated for the RPLD analysis. The methodology was tested in an international pilot study consisting of 59 dosimeter sets among 48 centres from 11 countries.

Results

The experimental correction factors showed good agreement with previous MC simulations, and the total correction factor accounting for non-water equivalence, lack of scatter and beam quality was found to be 1.029 ± 0.009 for ¹⁹²Ir and 1.059 ± 0.007 for ⁶⁰Co sources, to be employed in audit measurement. The total uncertainty budget was estimated to be 2.24 % (k = 1). In the multicentre study, the ratio between measured and reported user dose ranged from 0.968 to 1.049, with all irradiated dosimeter sets within ± 5 %, and 54 out of 59 within ± 3 %.

Conclusions

The methodology was tested in an international multicentre pilot study and has shown good performance validating the uncertainty budget.

背景和目的剂量测定审核对于减少近距离放射治疗中的误差至关重要。我们开发了一种邮政剂量测定审核方法，并在一个国际多中心试点中进行了测试，以评估 192Ir 和 60Co 近距离放射源的参考空气柯玛率的准确性。材料和方法我们开发了一个由聚甲基丙烯酸甲酯制成的紧凑型模型，可容纳两个导管、一个用于剂量测量的放射光致发光剂量计 (RPLD) 和一个用于放射源位置验证的 Gafchromic (RTQA2) 胶片条。对审计设置与 TG-43 条件的偏差进行了实验量化，并与之前的蒙特卡罗（MC）模拟进行了比较。为 RPLD 分析估算了测量不确定性预算。结果实验校正因子与之前的蒙特卡洛模拟结果显示出良好的一致性，并发现 192Ir 和 60Co 辐射源的总校正因子分别为 1.029 ± 0.009 和 1.059 ± 0.007（考虑到非水等效、缺乏散射和光束质量），可用于审核测量。总不确定性预算估计为 2.24 %（k = 1）。在多中心研究中，用户剂量的测量值与报告值之间的比率介于 0.968 至 1.049 之间，所有辐照剂量计的测量值均在± 5 %以内，59 个剂量计中有 54 个剂量计的测量值在± 3 %以内。

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引用次数: 0

Multi-institutional experience treating patients with cardiac devices on a 1.5 Tesla magnetic resonance-linear accelerator and workflow development for thoracic treatments 在 1.5 特斯拉磁共振线性加速器上治疗心脏装置患者的多机构经验，以及胸腔治疗工作流程的开发

IF 3.4 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100680

Rick Keesman , Erik van der Bijl , Linda G.W. Kerkmeijer , Neelam Tyagi , Osman Akdag , Jochem W.H. Wolthaus , Sandrine M.G. van de Pol , Juus L. Noteboom , Martijn P.W. Intven , Martin F. Fast , Astrid L.H.M.W. van Lier

Background and purpose

Patients with cardiac implantable electronic devices (CIED patients) are often ineligible for online magnetic resonance-guided radiotherapy (MRgRT), most likely due to the absence of established guidelines. Existing radiotherapy (RT) and magnetic resonance imaging (MRI) guidelines offer an opportunity to construct MRgRT protocols, promoting equitable access. Our objective was to present such a workflow, share multi-institutional experiences treating CIED patients with MRgRT on a 1.5 T magnetic resonance-linear accelerator (MR-linac), and investigate geometric accuracy and electrocardiogram (ECG) monitoring for thoracic treatment.

Materials and methods

A risk analysis identified strategies for safe MRgRT for CIED patients. At three institutions, 21 pelvic and abdominal patients were treated. Patient records were analyzed for adverse events. Geometric accuracy was investigated using B₀-mapping with a phantom simulating moving lung and cardiac lesions near a CIED. Volunteer measurements evaluated the effects of patient positioning and MRI sequences on ECG signal distortion.

Results

MRI and RT workflows were adaptable to MRgRT. No adverse events were recorded. B₀-maps showed a maximum mean difference between static and dynamic phantom configurations of 0.1 mm, increasing to 0.4 mm distortion in the presence of a CIED. ECG readings exhibited severe distortions during scanning, hampering heart rhythm detection for most MRI sequences.

Conclusions

CIED patients can safely undergo treatment on a 1.5 T MR-linac following RT and MRI guidelines. For targets near CIEDs, a B₀-mapping procedure was considered accurate enough to determine MRgRT eligibility. Pulse oximetry is recommended for cardiac monitoring during MRI scanning due to ECG signal distortion.

背景和目的心脏植入式电子装置患者（CIED 患者）通常不符合在线磁共振引导放射治疗（MRgRT）的条件，这很可能是因为缺乏既定的指南。现有的放射治疗（RT）和磁共振成像（MRI）指南为构建磁共振引导放疗方案提供了机会，从而促进了公平的治疗。我们的目标是介绍这样一种工作流程，分享在1.5 T磁共振直线加速器（MR-linac）上用MRgRT治疗CIED患者的多机构经验，并研究胸部治疗的几何精度和心电图（ECG）监测。三家机构共治疗了21名盆腔和腹腔患者。对患者记录进行了不良事件分析。使用B0映射模型模拟CIED附近移动的肺部和心脏病灶，对几何精度进行了研究。志愿者测量评估了患者定位和 MRI 序列对心电图信号失真的影响。无不良事件记录。B0 地图显示静态和动态模型配置之间的最大平均差异为 0.1 毫米，在有 CIED 的情况下，失真增加到 0.4 毫米。心电图读数在扫描过程中出现严重失真，妨碍了大多数磁共振成像序列的心律检测。对于CIED附近的目标，B0映射程序被认为足够精确，足以确定是否符合MRgRT条件。由于心电图信号失真，建议在磁共振成像扫描期间使用脉搏血氧仪进行心脏监测。

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引用次数: 0

Palliative radiotherapy of soft tissue tumoral masses based on diagnostic instead of planning computed tomography scans 基于诊断而非计划计算机断层扫描的软组织肿瘤肿块的姑息性放疗

IF 3.4 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100682

Satu Strengell , Suvi Larjavaara , Mikko Tenhunen, Anu Anttonen

Background and purpose

Radiotherapy (RT) treatment planning is based on a planning computed tomography scan (pCT), while the decision to treat is often already established on a diagnostic CT scan (dCT). The objective of this study was to evaluate the usage of dCT for palliative radiation planning of soft tissue tumoral masses (STTMs), removing the need for a pCT scan and associated attendances.

Materials and methods

RT planning was performed retrospectively to 38 STTMs of 7 anatomical sites using volumetric modulated arc therapy techniques in dCT and transferred to pCT. The dose of clinical target volumes (CTV), D(95 %,50 %), were compared between the plans. The patient setup was assessed in cone-beam CT scans.

Results

The differences of D(95 %,50 %) between dCT and pCT plans were the lowest in the STTMs of the thoracic cage (0.9 %,0.9 %), STTMs in the inguinal area (0.8 %,1.3 %) and in mediastinal masses associated with superior vena cava syndrome (SVCS) (1.1 %,1.3 %), while the differences increased for other sites. The patient setup was acceptable for 88 % of mediastinal masses associated with SVCS and ≤ 60 % of cases in other sites comparing pCT and CBCT images with a strict margin of 6 mm, but all cases fitted to increased 2 cm margin.

Conclusions

This study demonstrated the possibility of using dCT scans for palliative RT planning of STTMs for mediastinal masses associated with SVCS and for STTMs in the thoracic cage and in the inguinal area, indicating the potential feasibility of this procedure for clinical use.

背景和目的放射治疗（RT）的治疗计划是基于计划的计算机断层扫描（pCT），而治疗的决定通常已经建立在诊断性CT扫描（dCT）上。本研究的目的是评估dCT在软组织肿瘤肿块（sttm）姑息性放疗计划中的应用，消除了对pCT扫描和相关就诊的需要。材料与方法回顾性地对7个解剖部位的38例STTMs采用体积调制弧线治疗技术在dCT和转移到pCT进行srt计划，比较两种计划的临床靶体积剂量（CTV）， D（95%, 50%）。在锥形束CT扫描中评估患者设置。结果dCT与pCT方案在胸廓STTMs（0.9%, 0.9%）、腹股沟STTMs（0.8%, 1.3%）和纵膈肿块合并上腔静脉综合征（SVCS）（1.1%, 1.3%）的D值差异最低（95%,50%），其他部位差异增大。在与SVCS相关的纵隔肿块中，88%的患者设置是可接受的，在其他部位，pCT和CBCT图像的严格边界为6mm的病例中，≤60%的病例设置是可接受的，但所有病例都适合增加2cm的边界。结论：本研究证明了使用dCT扫描对伴有SVCS的纵隔肿块以及胸廓和腹股沟区域的sttm进行姑息性放疗计划的可能性，表明该程序在临床应用的潜在可行性。

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引用次数: 0

Head and neck automatic multi-organ segmentation on Dual-Energy Computed Tomography 双能量计算机断层扫描的头颈部多器官自动分割功能

IF 3.4 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100654

Anh Thu Lê , Killian Sambourg , Roger Sun , Nicolas Deny , Vjona Cifliku , Rahimeh Rouhi , Eric Deutsch , Nathalie Fournier-Bidoz , Charlotte Robert

Background and purpose

Deep-learning-based automatic segmentation is widely used in radiation oncology to delineate organs-at-risk. Dual-energy CT (DECT) allows the reconstruction of enhanced contrast images that could help with manual and auto-delineation. This paper presents a performance evaluation of a commercial auto-segmentation software on image series generated by a DECT.

Material and methods

Different types of DECT images from seventy four head-and-neck (HN) patients were retrieved, including polyenergetic images at different voltages [80 kV reconstructed with a kernel corresponding to the commercial algorithm DirectDensity™ (PEI80-DD), 80 kV (PEI80), 120 kV-mixed (PEI120)] and a virtual-monoenergetic image at 40 keV (VMI40). Delineations used for treatment planning were considered as ground truth (GT) and were compared with the auto-segmentations performed on the 4 DECT images. A blinded qualitative evaluation of 3 structures (thyroid, left parotid, left nodes level II) was carried out. Performance metrics were calculated for thirteen HN structures to evaluate the auto-contours including dice similarity coefficient (DSC), 95th percentile Hausdorff distance (95HD) and mean surface distance (MSD).

Results

We observed a high rate of low scores for PEI80-DD and VMI40 auto-segmentations on the thyroid and for GT and VMI40 contours on the nodes level II. All images received excellent scores for the parotid glands. The metrics comparison between GT and auto-segmented contours revealed that PEI80-DD had the highest DSC scores, significantly outperforming other reconstructed images for all organs (p < 0.05).

Conclusions

The results indicate that the auto-contouring system cannot generalize to images derived from DECT acquisition. It is therefore crucial to identify which organs benefit from these acquisitions to adapt the training datasets accordingly.

背景和目的基于深度学习的自动分割被广泛应用于放射肿瘤学中，以划分高危器官。双能 CT（DECT）可重建增强对比度图像，有助于手动和自动划线。本文介绍了一款商用自动分割软件在 DECT 生成的图像序列上的性能评估。材料和方法检索了七十四名头颈部（HN）患者的不同类型的 DECT 图像，包括不同电压下的多能图像[使用与商业算法 DirectDensity™ (PEI80-DD)、80 kV (PEI80)、120 kV-混合 (PEI120) 相对应的核重建的 80 kV]和 40 kV (VMI40) 下的虚拟单能图像。用于治疗计划的划分被视为地面实况（GT），并与在 4 幅 DECT 图像上进行的自动分割进行比较。对 3 个结构（甲状腺、左腮腺、左侧结节 II 级）进行了盲法定性评估。对 13 个 HN 结构计算了性能指标，以评估自动轮廓，包括骰子相似系数 (DSC)、第 95 百分位数豪斯多夫距离 (95HD) 和平均表面距离 (MSD)。腮腺的所有图像都获得了极好的评分。GT 和自动分割轮廓之间的度量比较显示，PEI80-DD 的 DSC 分数最高，在所有器官上都明显优于其他重建图像（p < 0.05）。因此，确定哪些器官可从这些采集中获益，从而相应地调整训练数据集至关重要。

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引用次数: 0

Proton dose calculation on cone-beam computed tomography using unsupervised 3D deep learning networks 利用无监督三维深度学习网络计算锥形束计算机断层扫描的质子剂量

IF 3.4 Q2 ONCOLOGY

Physics and Imaging in Radiation Oncology

Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100658

Casper Dueholm Vestergaard , Ulrik Vindelev Elstrøm , Ludvig Paul Muren , Jintao Ren , Ole Nørrevang , Kenneth Jensen , Vicki Trier Taasti

Background and Purpose

Poor image quality of cone-beam computed tomography (CBCT) images can hinder proton dose calculation to assess the influence of anatomy changes. The aim of this study was to evaluate image quality and proton dose calculation accuracy of synthetic CTs generated from CBCT using unsupervised 3D deep-learning networks.

Materials and methods

A total of 102 head-and-neck cancer patients were used to train (N=82) and test (N=20) i) a cycle-consistent generative adversarial network, ii) a contrastive unpaired translation, and iii) a fusion of the two (CycleCUT). For patients in the test set, a repeat CT was deformably registered to a same-day CBCT to create a ground-truth CT for comparison. The proton plan was re-calculated on the ground-truth CT and synthetic CTs. The image quality of the synthetic CTs was evaluated using peak signal-to-noise ratio, structural similarity index measure, mean error, and mean absolute error (MAE). Proton dose calculation accuracy was assessed through 3D gamma analysis and dose-volume-histogram parameters.

Results

All synthetic CTs accurately preserved the CBCT anatomy (verified by visual inspection) while improving the image quality. The CycleCUT network had slightly improved image quality compared to the other networks (MAE in body: 53 Hounsfield units (HU) vs. 54/55 HU). All networks had similar proton dose calculation accuracy with gamma passing rate above 97%.

Conclusions

All three evaluated networks generated synthetic CT images with dose distributions comparable to those of conventional fan-beam CT. The synthetic CT generation was fast, making all networks feasible for adaptive proton therapy.

背景和目的锥束计算机断层扫描（CBCT）图像质量差会妨碍质子剂量计算，从而无法评估解剖结构变化的影响。本研究旨在评估使用无监督三维深度学习网络从 CBCT 生成的合成 CT 的图像质量和质子剂量计算的准确性。材料与方法共有 102 名头颈部癌症患者被用于训练（N=82）和测试（N=20）i) 循环一致性生成对抗网络，ii) 对比非配对翻译，iii) 两者的融合（CycleCUT）。对于测试集中的患者，将重复 CT 与当天的 CBCT 进行变形注册，以创建地面实况 CT 进行比较。在地面实况 CT 和合成 CT 上重新计算质子计划。合成 CT 的图像质量通过峰值信噪比、结构相似性指数测量、平均误差和平均绝对误差 (MAE) 进行评估。结果所有合成 CT 都准确保留了 CBCT 的解剖结构（通过目测验证），同时提高了图像质量。与其他网络相比，CycleCUT 网络的图像质量略有提高（体部 MAE：53 Hounsfield 单位 (HU) 对 54/55 HU）。所有网络的质子剂量计算准确度相似，伽马通过率均在 97% 以上。结论所有三个评估网络生成的合成 CT 图像的剂量分布与传统扇形束 CT 的剂量分布相当。合成 CT 生成速度快，使所有网络都能用于自适应质子治疗。

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