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Purpose: The purpose of the study is to investigate the clinical application of deep learning (DL)-assisted automatic radiotherapy planning for lung cancer., Methods: A DL model was developed for predicting patient-specific doses, trained and validated on a dataset of 235 patients with diverse target volumes and prescriptions. The model was integrated into clinical workflow with DL-predicted objective functions. The automatic plans were retrospectively designed for additional 50 treated manual volumetric modulated arc therapy (VMAT) plans. A comparison was made between automatic and manual plans in terms of dosimetric indexes, monitor units (MUs) and planning time. Plan quality metric (PQM) encompassing these indexes was evaluated, with higher PQM values indicating superior plan quality. Qualitative evaluations of two plans were conducted by four reviewers., Results: The PQM score was 40.7 ± 13.1 for manual plans and 40.8 ± 13.5 for automatic plans (P = 0.75). Compared to manual plans, the targets coverage and homogeneity of automatic plans demonstrated no significant difference. Manual plans exhibited better sparing for lung in V5 (difference: 1.8 ± 4.2 %, P = 0.02), whereas automatic plans showed enhanced sparing for heart in V30 (difference: 1.4 ± 4.7 %, P = 0.02) and for spinal cord in Dmax (difference: 0.7 ± 4.7 Gy, P = 0.04). The planning time and MUs of automatic plans were significantly reduced by 70.5 ± 20.0 min and 97.4 ± 82.1. Automatic plans were deemed acceptable in 88 % of the reviews (176/200)., Conclusions: The DL-assisted approach for lung cancer notably decreased planning time and MUs, while demonstrating comparable or superior quality relative to manual plans. It has the potential to provide benefit to lung cancer patients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.)

Objective: Radiation pneumonitis (RP) is the major dose-limiting toxicity of thoracic radiotherapy. This study aimed to developed a dual-omics (single nucleotide polymorphisms, SNP and dosiomics) prediction model for symptomatic RP., Materials and Methods: The potential SNPs, which are of significant difference between the RP grade ≥ 3 group and the RP grade ≤ 1 group, were selected from the whole exome sequencing SNPs using the Fisher's exact test. Patients with lung cancer who received thoracic radiotherapy at our institution from 2009 to 2016 were enrolled for SNP selection and model construction. The factorization machine (FM) method was used to model the SNP epistasis effect, and to construct the RP prediction model (SNP-FM). The dosiomics features were extracted, and further selected using the minimum redundancy maximum relevance (mRMR) method. The selected dosiomics features were added to the SNP-FM model to construct the dual-omics model., Results: For SNP screening, peripheral blood samples of 28 patients with RP grade ≥ 3 and the matched 28 patients with RP grade ≤ 1 were sequenced. 81 SNPs were of significant difference (P < 0.015) and considered as potential SNPs. In addition, 21 radiation toxicity related SNPs were also included. For model construction, 400 eligible patients (including 108 RP grade ≥ 2) were enrolled. Single SNP showed no strong correlation with RP. On the other hand, the SNP-SNP interaction (epistasis effect) of 19 SNPs were modeled by the FM method, and achieved an area under the curve (AUC) of 0.76 in the testing group. In addition, 4 dosiomics features were selected and added to the model, and increased the AUC to 0.81., Conclusions: A novel dual-omics model by synergizing the SNP epistasis effect with dosiomics features was developed. The enhanced the RP prediction suggested its promising clinical utility in identifying the patients with severe RP during thoracic radiotherapy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Radiotherapy-induced esophagitis (RE) diminishes the quality of life and interrupts treatment in patients with non-small cell lung cancer (NSCLC) undergoing postoperative radiotherapy. Dosimetric models showed limited capability in predicting RE. We aimed to develop dosiomic models to predict RE., Methods: Models were trained with a real-world cohort and validated with PORT-C randomized controlled trial cohort. Patients with NSCLC undergoing resection followed by postoperative radiotherapy between 2004 and 2015 were enrolled. The endpoint was grade ≥2 RE. Esophageal three-dimensional dose distribution features were extracted using handcrafted and convolutional neural network (CNN) methods, screened using an entropy-based method, and selected using minimum redundancy and maximum relevance. Prediction models were built using logistic regression. The areas under the receiver operating characteristic curve (AUC) and precision-recall curve were used to evaluate prediction model performance. A dosimetric model was built for comparison., Results: A total of 190 and 103 patients were enrolled in the training and validation sets, respectively. Using handcrafted and CNN methods, 107 and 4096 features were derived, respectively. Three handcrafted, four CNN-extracted and three dosimetric features were selected. AUCs of training and validation sets were 0.737 and 0.655 for the dosimetric features, 0.730 and 0.724 for handcrafted features, and 0.812 and 0.785 for CNN-extracted features, respectively. Precision-recall curves revealed that CNN-extracted features outperformed dosimetric and handcrafted features., Conclusions: Prediction models may identify patients at high risk of developing RE. Dosiomic models outperformed the dosimetric-feature model in predicting RE. CNN-extracted features were more predictive but less interpretable than handcrafted features., (© 2023 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.)

Introduction: Dose reconstructed based on linear accelerator (linac) log-files is one of the widely used solutions to perform patient-specific quality assurance (QA). However, it has a drawback that the accuracy of log-file is highly dependent on the linac calibration. The objective of the current study is to represent a new practical approach for a patient-specific QA during Volumetric modulated arc therapy (VMAT) using both log-file and calibration errors of linac., Methods: A total of six cases, including two head and neck neoplasms, two lung cancers, and two rectal carcinomas, were selected. The VMAT-based delivery was optimized by the TPS of Pinnacle^3 subsequently, using Elekta Synergy VMAT linac (Elekta Oncology Systems, Crawley, UK), which was equipped with 80 Multi-leaf collimators (MLCs) and the energy of the ray selected at 6 MV. Clinical mode log-file of this linac was used in this study. A series of test fields validate the accuracy of log-file. Then, six plans of test cases were delivered and log-file of each was obtained. The log-file errors were added to the corresponding plans through the house script and the first reconstructed plan was obtained. Later, a series of tests were performed to evaluate the major calibration errors of the linac (dose-rate, gantry angle, MLC leaf position) and the errors were added to the first reconstruction plan to generate the second reconstruction plan. At last, all plans were imported to Pinnacle and recalculated dose distribution on patient CT and ArcCheck phantom (SUN Nuclear). For the former, both target and OAR dose differences between them were compared. For the latter, γ was evaluated by ArcCheck, and subsequently, the surface dose differences between them were performed., Results: Accuracy of log-file was validated. If error recordings in the log file were only considered, there were four arcs whose proportion of control points with gantry angle errors more than ± 1°larger than 35%. Errors of leaves within ± 0.5 mm were 95% for all arcs. The distinctness of a single control point MU was bigger, but the distinctness of cumulative MU was smaller. The maximum, minimum, and mean doses for all targets were distributed between -6.79E-02-0.42%, -0.38-0.4%, 2.69E-02-8.54E-02% respectively, whereas for all OAR, the maximum and mean dose were distributed between -1.16-2.51%, -1.21-3.12% respectively. For the second reconstructed dose: the maximum, minimum, and mean dose for all targets was distributed between 0.0995~5.7145%, 0.6892~4.4727%, 0.5829~1.8931% separately. Due to OAR, maximum and mean dose distribution was observed between -3.1462~6.8920%, -6.9899~1.9316%, respectively., Conclusion: Patient-specific QA based on the log-file could reflect the accuracy of the linac execution plan, which usually has a small influence on dose delivery. When the linac calibration errors were considered, the reconstructed dose was closer to the actual delivery and the developed method was accurate and practical., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Purpose: Radiotherapy plays an important role in the treatment of lung cancer, and both coplanar beam arrangements (CBA) and noncoplanar beam arrangements (NCBA) are adopted in clinic practice. The aim of this study is to answer the question whether NCBA are dosimetrically superior to CBA., Methods: Search of publications were performed in PubMed, Web of Science, and the Cochran Library till March 2020. The searching terms were as following: ((noncoplanar) or ("non coplanar") or ("4pi") or ("4π")) AND (("lung cancer") or ("lung tumor") or ("lung carcinoma")) AND ((radiotherapy) or ("radiation therapy")). The included studies and extracted data were manually screened. All forest and funnel plots were carried out with RevMan software, and the Egger's regression asymmetry tests were conducted with STATA software., Results: Nine studies were included and evaluated in the meta-analysis and treatment plans were designed with both CBA and NCBA. For the planning target volumes (PTV), D98%, D2%, the conformity index (CI), and the gradient index (GI) had no statistically significant difference. For organs-at-risk (OAR), V20 of the whole lung and the maximum dose of the spinal cord were significantly reduced in NCBA plans compared with CBA ones. But V10, V5, and mean dose of the whole lung, the maximum dose of the heart, and the maximum dose of the esophagus exhibited no significant difference when the two types of beam arrangements were compared., Conclusion: After combining multicenter results, NCBA plans have significant advantages in reducing V20 of the whole lung and max dose of spinal cord., (© 2021 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Purpose: To investigate planning time and number of optimizations in routine clinical lung cancer plans based on the plan quality improvements following each optimization., Materials and Method: We selected 40 patients with lung cancer who were treated with conventional fractionated radiotherapy (CFRT). The 40 plans (divided into two groups with one or two target volumes) were completed by 9 planners using volumetric modulated arc therapy (VMAT). A planning strategy, including technique script for each group and a planning process for data collection, was introduced. The total planning time, number of optimizations, and dose-volume parameters of each plan were recorded and analyzed. A plan quality metric (PQM) was defined according to the clinical constraints. Statistical analysis of parameters of each plan following each optimization was performed for evaluating improvements in plan quality., Results: According to the clinical plans generated by different planners, the median number of optimizations of each group was 4, and the median planning time was approximately 1 h (68.6 min and 62.0 min for plans with one or two target volumes, respectively). The dose deposited in organs at risk (OARs) gradually decreased, and the PQM values gradually improved following each optimization. The improvements were significant only between adjacent optimizations from the first optimization (Opt1) to the third optimization (Opt3)., Conclusion: Increasing the number of optimizations was associated with significantly improved sparing of OARs with slight effects on the dose coverage and homogeneity of target volume. Generally, based on the designed planning strategy, there was no significant improvement of the plan quality for more than three optimizations., (© 2020 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

Purpose: Cone-beam computerized tomography (CBCT) is routinely performed for verification of patient position in radiotherapy. It produced a large amount of data which require a method to compress them for efficient storage. In this study three video compression algorithms were introduced and their performance was evaluated based on real patient data., Materials and Methods: At first CBCT images in multiple sets of a patient were transferred from reconstruction workstation or exported from treatment planning system. Then CBCT images were sorted according to imaging time (time-prioritized sequence) or imaging location (location-prioritized sequence). Next, this sequence was processed by a video compression algorithm and resulted in a movie. Three representative video compression algorithms (Motion JPEG 2000, Motion JPEG AVI, and MPEG-4) were employed and their compression performance was evaluated based on the CBCT data of 30 patients., Results: Among three video compression algorithms, Motion JPEG 2000 has the least compression ratio since it is a lossless compression algorithm. Motion JPEG AVI and MPEG-4 have higher compression ratios than Motion JPEG 2000 but come with certain image losses. For MPEG-4, location-prioritized sequences show higher compression ratio than time-prioritized sequences. Based on the results achieved on the clinical target verification application, the registration accuracy of CBCT after decompression was comparable to that of the original CBCT., Conclusions: Video compression algorithms could provide a higher compression ratio comparing to static image compression algorithm. Although the loss of CBCT image due to compression its impact on registration accuracy of patient positioning is almost negligible. Video compression method is an effective way to substantially reduce the size of CBCT images for storage., (© 2019 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

Purpose: To investigate the dosimetric impact of hysteresis on lung cancer tomotherapy., Methods: Measurements were acquired using MapCheck with an XY4D motion simulation table. Six hysteresis states (0, π/32, π/16, π/8, 3π/16, and π/4) were considered with sinusoidal motions in the superior-inferior and left-right orientations. The measured data were analyzed both globally (from all detectors) and structure-by-structure in the measurement plane. The dose difference (DD) analysis method with local normalization in the absolute dose mode with a DD threshold of 6 cGy was adopted to analyze each hysteresis vs. static state (H(∗)S) and nonzero vs. zero hysteresis (H(∗)0). The threshold was 10% for all analyses. Wilcoxon signed rank tests with significance level p = 0.05 were used for statistical analysis., Results: The DD analysis of each H(∗)S mostly indicated that the passing rate differed between structures but was similar between hysteresis states. The DD analysis of H(∗)0 showed that the passing rate decreased with increasing hysteresis. The differences between larger hysteresis (≥3π/16) and other states were significant for comparisons between global, left lung, chest wall, and target. Both analyses showed that the DD distribution changed with hysteresis., Conclusions: Hysteresis difference causes the DD distribution to change. Structural difference had more impact than hysteresis state difference on hysteresis motion vs. static comparisons. Remarkable effects on nonzero vs. zero hysteresis comparisons were only seen for structures closely related to the target at large hysteresis. Small organs at risk that are close to the target need to be considered further., (Copyright © 2018. Published by Elsevier Ltd.)

The purpose of this paper was to evaluate the impact of leaf treatment of multileaf collimator (MLC) in plan quality of intensity-modulated radiotherapy (IMRT) of patients with advanced lung cancer. Five MLCs with different leaf transmissions (0.01%, 0.5%, 1.2%, 1.8%, and 3%) were configured for an accelerator in a treatment planning system. Correspondingly, 5 treatment plans with the same optimization setting were created and evaluated quantitatively for each patient (11 patients total) who was diagnosed with advanced lung cancer. All of the 5 plans for each patient met the dose requirement for the planning treatment volumes (PTVs) and had similar target dose homogeneity and conformity. On average, the doses to selected organs were as follows: (1) V 5 , V 20 , and the mean dose of total lung; (2) the maximum and mean dose to spinal cord planning organ-at-risk volume (PRV); and (3) V 30 and V 40 of heart, decreased slightly when MLC transmission was decreased, but with no statistical differences. There is a clear grouping of plans having total quality score (S D ) value, which is used to evaluate plan quality: (1) more than 1 (patient nos. 1 to 3, 5, and 8), and more than 2.5 (patient no. 6); (2) less than 1 (patient nos. 7 and 10); (3) around 1 (patient nos. 4, 9, and 11). As MLC transmission increased, overall S D values increased as well and plan dose requirement was harder to meet. The clinical requirements were violated increasingly as MLC transmission became large. Total S D with and without normal tissue (NT) showed similar results, with no statistically significant differences. Therefore, decrease of MLC transmission did have minimum impact on plan, and it improved target coverage and reduced normal tissue radiation slightly, with no statistical significance. Plan quality could not be significantly improved by MLC transmission reduction. However, lower MLC transmission may have advantages on lung sparing to low- and intermediate-dose exposure. Besides conventional fraction, hyperfraction, or stereotactic body radiotherapy (SBRT), the reduction on lung sparing is still essential because it is highly relevant to radiation pneumonitis (RP). It has potential to diminish incidence of RP and improve patient's quality of life after irradiation with lowered MLC transmission., (Copyright © 2017 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.)

It is important to minimize lung dose during intensity-modulated radiation therapy (IMRT) of nonsmall cell lung cancer (NSCLC). In this study, an approach was proposed to reduce lung dose by relaxing the constraint of target dose homogeneity during treatment planning of IMRT. Ten NSCLC patients with lung tumor on the right side were selected. The total dose for planning target volume (PTV) was 60 Gy (2 Gy/fraction). For each patient, two IMRT plans with six beams were created in Pinnacle treatment planning system. The dose homogeneity of target was controlled by constraints on the maximum and uniform doses of target volume. One IMRT plan was made with homogeneous target dose (the resulting target dose was within 95%-107% of the prescribed dose), while another IMRT plan was made with inhomogeneous target dose (the resulting target dose was more than 95% of the prescribed dose). During plan optimization, the dose of cord and heart in two types of IMRT plans were kept nearly the same. The doses of lungs, PTV and organs at risk (OARs) between two types of IMRT plans were compared and analyzed quantitatively. For all patients, the lung dose was decreased in the IMRT plans with inhomogeneous target dose. On average, the mean dose, V5, V20, and V30 of lung were reduced by 1.4 Gy, 4.8%, 3.7%, and 1.7%, respectively, and the dose to normal tissue was also reduced. These reductions in DVH values were all statistically significant (P < 0.05). There were no significant differences between the two IMRT plans on V25, V30, V40, V50 and mean dose for heart. The maximum doses of cords in two type IMRT plans were nearly the same. IMRT plans with inhomogeneous target dose could protect lungs better and may be considered as a choice for treating NSCLC., (© 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

Purpose: Poor pulmonary function (PF) is often considered a contraindication to definitive radiation therapy for lung cancer. This study investigated whether baseline PF was associated with radiation-induced lung toxicity (RILT) in patients with non-small cell lung cancer (NSCLC) receiving conformal radiation therapy (CRT)., Methods and Materials: NSCLC patients treated with CRT and tested for PF at baseline were eligible. Baseline predicted values of forced expiratory volume in 1 sec (FEV1), forced vital capacity (FVC), and diffusion capacity of lung for carbon monoxide (DLCO) were analyzed. Additional factors included age, gender, smoking status, Karnofsky performance status, coexisting chronic obstructive pulmonary disease (COPD), tumor location, histology, concurrent chemotherapy, radiation dose, and mean lung dose (MLD) were evaluated for RILT. The primary endpoint was symptomatic RILT (SRILT), including grade ≥2 radiation pneumonitis and fibrosis., Results: There was a total of 260 patients, and SRILT occurred in 58 (22.3%) of them. Mean FEV1 values for SRILT and non-SRILT patients were 71.7% and 65.9% (P=.077). Under univariate analysis, risk of SRILT increased with MLD (P=.008), the absence of COPD (P=.047), and FEV1 (P=.077). Age (65 split) and MLD were significantly associated with SRILT in multivariate analysis. The addition of FEV1 and age with the MLD-based model slightly improved the predictability of SRILT (area under curve from 0.63-0.70, P=.088)., Conclusions: Poor baseline PF does not increase the risk of SRILT, and combining FEV1, age, and MLD may improve the predictive ability., (Published by Elsevier Inc.)

The purpose of this study was to compare setup errors obtained with kilovoltage cone-beam computed tomography (CBCT) and 2 different kinds of reference images, free-breathing 3D localization CT images (FB-CT) and the average images of 4-D localization CT images (AVG-CT) for phantom and lung cancer patients. This study also explored the correlation between the difference of translational setup errors and the gross tumor volume (GTV) motion. A respiratory phantom and 14 patients were enrolled in this study. For phantom and each patient, 3D helical CT and 4D CT images were acquired, and AVG-CT images were generated from the 4D CT. The setup errors were determined based on the image registration between the CBCT and the 2 different reference images, respectively. The data for both translational and rotational setup errors were analyzed and compared. The GTV centroid movement as well as its correlation with the translational setup error differences was also evaluated. In the phantom study, the AVG-CT method was more accurate than the FB-CT method. For patients, the translational setup errors based on FB-CT were significantly larger than those from AVG-CT in the left-right (LR), superior-inferior (SI), and anterior-posterior (AP) directions (p < 0.05). Translational setup errors differed by >1 mm in 32.6% and >2 mm in 12.9% of CBCT scans. The rotational setup errors from FB-CT were significantly different from those from AVG-CT in the LR and AP directions (p < 0.05). The correlation coefficient of the translational setup error differences and the GTV centroid movement in the LR, SI, and AP directions was 0.515 (p = 0.060), 0.902 (p < 0.001), and 0.510 (p = 0.062), respectively. For lung cancer patients, respiration may affect the on-line target position location. AVG-CT provides different reference information than FB-CT. The difference in SI direction caused by the 2 methods increases with the GTV movement. Therefore, AVG-CT should be the prefered choice of reference images., (Copyright © 2012 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.)

Using higher energy photons can obtain better target dose uniformity and skin sparing for treating deep lesions, but the effect of lacking lateral scattering in the low-density lung may degrade the target coverage. To analyze the influence of lateral electronic disequilibrium on the radiation treatment planning for lung cancer, three dimension conformal treatment (3D-CRT) plans of using 6 MV and 18 MV X-ray respectively for a lung cancer case have been worked out by using pencil beam algorithm and collapsed cone algorithm provided by Helax-TMS treatment planning system for the same radiation field arrangement for both energies. Dose volume histogram (DVH) in target and organs at risk (OARs) are used for comparison of different plans. The study shows that using pencil beam algorithm, the target DVH are similar for 6 MV and 18 MV plan. However, using collapsed cone algorithm that can make account of lateral electron scattering, the target is underdosed. The change is even more pronounced for 18 MV plan. The doses for lung and spinal cord are similar for these two energies and two algorithms. Therefore, for lung cancer, dose calculation algorithm should have the ability of handling accurately the effect of the tissue density heterogeneity. It is better to use the lower-energy photons (6 MV) than to use the higher-energy photons (18 MV).