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1.
Radiat Environ Biophys ; 63(2): 297-306, 2024 May.
Article in English | MEDLINE | ID: mdl-38722389

ABSTRACT

For locally advanced cervical cancer, the standard therapeutic approach involves concomitant chemoradiation therapy, supplemented by a brachytherapy boost. Moreover, an external beam radiotherapy (RT) boost should be considered for treating gross lymph node (LN) volumes. Two boost approaches exist with Volumetric Intensity Modulated Arc Therapy (VMAT): Sequential (SEQ) and Simultaneous Integrated Boost (SIB). This study undertakes a comprehensive dosimetric and radiobiological comparison between these two boost strategies. The study encompassed ten patients who underwent RT for cervical cancer with node-positive disease. Two sets of treatment plans were generated for each patient: SIB-VMAT and SEQ-VMAT. Dosimetric as well as radiobiological parameters including tumour control probability (TCP) and normal tissue complication probability (NTCP) were compared. Both techniques were analyzed for two different levels of LN involvement - only pelvic LNs and pelvic with para-aortic LNs. Statistical analysis was performed using SPSS software version 25.0. SIB-VMAT exhibited superior target coverage, yielding improved doses to the planning target volume (PTV) and gross tumour volume (GTV). Notably, SIB-VMAT plans displayed markedly superior dose conformity. While SEQ-VMAT displayed favorable organ sparing for femoral heads, SIB-VMAT appeared as the more efficient approach for mitigating bladder and bowel doses. TCP was significantly higher with SIB-VMAT, suggesting a higher likelihood of successful tumour control. Conversely, no statistically significant difference in NTCP was observed between the two techniques. This study's findings underscore the advantages of SIB-VMAT over SEQ-VMAT in terms of improved target coverage, dose conformity, and tumour control probability. In particular, SIB-VMAT demonstrated potential benefits for cases involving para-aortic nodes. It is concluded that SIB-VMAT should be the preferred approach in all cases of locally advanced cervical cancer.


Subject(s)
Radiotherapy Dosage , Radiotherapy, Intensity-Modulated , Uterine Cervical Neoplasms , Humans , Uterine Cervical Neoplasms/radiotherapy , Uterine Cervical Neoplasms/pathology , Female , Radiotherapy, Intensity-Modulated/methods , Radiotherapy Planning, Computer-Assisted/methods , Radiometry , Middle Aged , Organs at Risk/radiation effects , Lymphatic Metastasis/radiotherapy
2.
Biomed Phys Eng Express ; 10(4)2024 May 10.
Article in English | MEDLINE | ID: mdl-38697044

ABSTRACT

Objective.The aim of this work was to develop a Phase I control chart framework for the recently proposed multivariate risk-adjusted Hotelling'sT2chart. Although this control chart alone can identify most patients receiving extreme organ-at-risk (OAR) dose, it is restricted by underlying distributional assumptions, making it sensitive to extreme observations in the sample, as is typically found in radiotherapy plan quality data such as dose-volume histogram (DVH) points. This can lead to slightly poor-quality plans that should have been identified as out-of-control (OC) to be signaled in-control (IC).Approach. We develop a robust iterative control chart framework to identify all OC patients with abnormally high OAR dose and improve them via re-optimization to achieve an IC sample prior to establishing the Phase I control chart, which can be used to monitor future treatment plans.Main Results. Eighty head-and-neck patients were used in this study. After the first iteration, P14, P67, and P68 were detected as OC for high brainstem dose, warranting re-optimization aimed to reduce brainstem dose without worsening other planning criteria. The DVH and control chart were updated after re-optimization. On the second iteration, P14, P67, and P68 were IC, but P40 was identified as OC. After re-optimizing P40's plan and updating the DVH and control chart, P40 was IC, but P14* (P14's re-optimized plan) and P62 were flagged as OC. P14* could not be re-optimized without worsening target coverage, so only P62 was re-optimized. Ultimately, a fully IC sample was achieved. Multiple iterations were needed to identify and improve all OC patients, and to establish a more robust control limit to monitor future treatment plans.Significance. The iterative procedure resulted in a fully IC sample of patients. With this sample, a more robust Phase I control chart that can monitor OAR doses of new plans was established.


Subject(s)
Organs at Risk , Quality Control , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Humans , Organs at Risk/radiation effects , Radiotherapy Planning, Computer-Assisted/methods , Head and Neck Neoplasms/radiotherapy , Algorithms
3.
Radiat Oncol ; 19(1): 54, 2024 May 03.
Article in English | MEDLINE | ID: mdl-38702761

ABSTRACT

BACKGROUND: Stereotactic ablative body radiotherapy (SABR) is an emerging treatment alternative for patients with localized low and intermediate risk prostate cancer patients. As already explored by some authors in the context of conventional moderate hypofractionated radiotherapy, focal boost of the index lesion defined by magnetic resonance imaging (MRI) is associated with an improved biochemical outcome. The objective of this phase II trial is to determine the effectiveness (in terms of biochemical, morphological and functional control), the safety and impact on quality of life, of prostate SABR with MRI guided focal dose intensification in males with intermediate and high-risk localized prostate cancer. METHODS: Patients with intermediate and high-risk prostate cancer according to NCCN definition will be treated with SABR 36.25 Gy in 5 fractions to the whole prostate gland with MRI guided simultaneous integrated focal boost (SIB) to the index lesion (IL) up to 50 Gy in 5 fractions, using a protocol of bladder trigone and urethra sparing. Intra-fractional motion will be monitored with daily cone beam computed tomography (CBCT) and intra-fractional tracking with intraprostatic gold fiducials. Androgen deprivation therapy (ADT) will be allowed. The primary endpoint will be efficacy in terms of biochemical and local control assessed by Phoenix criteria and post-treatment MRI respectively. The secondary endpoints will encompass acute and late toxicity, quality of life (QoL) and progression-free survival. Finally, the subgroup of high-risk patients will be involved in a prospective study focused on immuno-phenotyping. DISCUSSION: To the best of our knowledge, this is the first trial to evaluate the impact of post-treatment MRI on local control among patients with intermediate and high-risk prostate cancer undergoing SABR and MRI guided focal intensification. The results of this trial will enhance our understanding of treatment focal intensification through the employment of the SABR technique within this specific patient subgroup, particularly among those with high-risk disease, and will help to clarify the significance of MRI in monitoring local responses. Hopefully will also help to design more personalized biomarker-based phase III trials in this specific context. Additionally, this trial is expected to be incorporated into a prospective radiomics study focused on localized prostate cancer treated with radiotherapy. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT05919524; Registered 17 July 2023. TRIAL SPONSOR: IRAD/SEOR (Instituto de Investigación de Oncología Radioterápica / Sociedad Española de Oncología Radioterápica). STUDY SETTING: Clinicaltrials.gov identifier: NCT05919524; Registered 17 July 2023. TRIAL STATUS: Protocol version number and date: v. 5/ 17 May-2023. Date of recruitment start: August 8, 2023. Date of recruitment completion: July 1, 2024.


Subject(s)
Prostatic Neoplasms , Radiosurgery , Radiotherapy, Image-Guided , Humans , Male , Prostatic Neoplasms/radiotherapy , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/surgery , Prostatic Neoplasms/pathology , Radiosurgery/methods , Radiotherapy, Image-Guided/methods , Urinary Bladder/radiation effects , Organs at Risk/radiation effects , Organ Sparing Treatments/methods , Magnetic Resonance Imaging/methods , Prospective Studies , Quality of Life , Radiotherapy Dosage , Aged , Radiotherapy Planning, Computer-Assisted/methods , Middle Aged
4.
J Appl Clin Med Phys ; 25(5): e14361, 2024 May.
Article in English | MEDLINE | ID: mdl-38642406

ABSTRACT

PURPOSES: This study aimed to develop and validate algorithms for automating intensity modulated radiation therapy (IMRT) planning in breast cancer patients, with a focus on patient anatomical characteristics. MATERIAL AND METHODS: We retrospectively selected 400 breast cancer patients without lymph node involvement for automated treatment planning. Automation was achieved using the Eclipse Scripting Application Programming Interface (ESAPI) integrated into the Eclipse Treatment Planning System. We employed three beam insertion geometries and three optimization strategies, resulting in 3600 plans, each delivering a 40.05 Gy dose in 15 fractions. Gantry angles in the tangent fields were selected based on a criterion involving the minimum intersection area between the Planning Target Volume (PTV) and the ipsilateral lung in the Beam's Eye View projection. ESAPI was also used to gather patient anatomical data, serving as input for Random Forest models to select the optimal plan. The Random Forest classification considered both beam insertion geometry and optimization strategy. Dosimetric data were evaluated in accordance with the Radiation Therapy Oncology Group (RTOG) 1005 protocol. RESULTS: Overall, all approaches generated high-quality plans, with approximately 94% meeting the acceptable dose criteria for organs at risk and/or target coverage as defined by RTOG guidelines. Average automated plan generation time ranged from 6 min and 37 s to 9 min and 22 s, with the mean time increasing with additional fields. The Random Forest approach did not successfully enable automatic planning strategy selection. Instead, our automated planning system allows users to choose from the tested geometry and strategy options. CONCLUSIONS: Although our attempt to correlate patient anatomical features with planning strategy using machine learning tools was unsuccessful, the resulting dosimetric outcomes proved satisfactory. Our algorithm consistently produced high-quality plans, offering significant time and efficiency advantages.


Subject(s)
Algorithms , Breast Neoplasms , Organs at Risk , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Radiotherapy, Intensity-Modulated , Humans , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy, Intensity-Modulated/methods , Female , Breast Neoplasms/radiotherapy , Organs at Risk/radiation effects , Retrospective Studies , Automation , Prognosis
5.
J Appl Clin Med Phys ; 25(5): e14345, 2024 May.
Article in English | MEDLINE | ID: mdl-38664894

ABSTRACT

PURPOSE: To establish the clinical applicability of deep-learning organ-at-risk autocontouring models (DL-AC) for brain radiotherapy. The dosimetric impact of contour editing, prior to model training, on performance was evaluated for both CT and MRI-based models. The correlation between geometric and dosimetric measures was also investigated to establish whether dosimetric assessment is required for clinical validation. METHOD: CT and MRI-based deep learning autosegmentation models were trained using edited and unedited clinical contours. Autosegmentations were dosimetrically compared to gold standard contours for a test cohort. D1%, D5%, D50%, and maximum dose were used as clinically relevant dosimetric measures. The statistical significance of dosimetric differences between the gold standard and autocontours was established using paired Student's t-tests. Clinically significant cases were identified via dosimetric headroom to the OAR tolerance. Pearson's Correlations were used to investigate the relationship between geometric measures and absolute percentage dose changes for each autosegmentation model. RESULTS: Except for the right orbit, when delineated using MRI models, the dosimetric statistical analysis revealed no superior model in terms of the dosimetric accuracy between the CT DL-AC models or between the MRI DL-AC for any investigated brain OARs. The number of patients where the clinical significance threshold was exceeded was higher for the optic chiasm D1% than other OARs, for all autosegmentation models. A weak correlation was consistently observed between the outcomes of dosimetric and geometric evaluations. CONCLUSIONS: Editing contours before training the DL-AC model had no significant impact on dosimetry. The geometric test metrics were inadequate to estimate the impact of contour inaccuracies on dose. Accordingly, dosimetric analysis is needed to evaluate the clinical applicability of DL-AC models in the brain.


Subject(s)
Brain Neoplasms , Deep Learning , Magnetic Resonance Imaging , Organs at Risk , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Tomography, X-Ray Computed , Humans , Organs at Risk/radiation effects , Magnetic Resonance Imaging/methods , Tomography, X-Ray Computed/methods , Brain Neoplasms/radiotherapy , Brain Neoplasms/diagnostic imaging , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy, Intensity-Modulated/methods , Radiometry/methods , Image Processing, Computer-Assisted/methods
6.
J Appl Clin Med Phys ; 25(5): e14366, 2024 May.
Article in English | MEDLINE | ID: mdl-38669190

ABSTRACT

PURPOSE: Skin collimation is a useful tool in electron beam therapy (EBT) to decrease the penumbra at the field edge and minimize dose to nearby superficial organs at risk (OARs), but manually fabricating these collimation devices in the clinic to conform to the patient's anatomy can be a difficult and time intensive process. This work compares two types of patient-specific skin collimation (in-house 3D printed and vendor-provided machined brass) using clinically relevant metrics. METHODS: Attenuation measurements were performed to determine the thickness of each material needed to adequately shield both 6 and 9 MeV electron beams. Relative and absolute dose planes at various depths were measured using radiochromic film to compare the surface dose, flatness, and penumbra of the different skin collimation materials. RESULTS: Clinically acceptable thicknesses of each material were determined for both 6 and 9 MeV electron beams. Field width, flatness, and penumbra results between the two systems were very similar and significantly improved compared to measurements performed with no surface collimation. CONCLUSION: Both skin collimation methods investigated in this work generate sharp penumbras at the field edge and can minimize dose to superficial OARs compared to treatment fields with no surface collimation. The benefits of skin collimation are greatest for lower energy electron beams, and the benefits decrease as the measurement depth increases. Using bolus with skin collimation is recommended to avoid surface dose enhancement seen with collimators placed on the skin surface. Ultimately, the appropriate choice of material will depend on the desire to create these devices in-house or outsource the fabrication to a vendor.


Subject(s)
Electrons , Organs at Risk , Printing, Three-Dimensional , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Skin , Humans , Electrons/therapeutic use , Radiotherapy Planning, Computer-Assisted/methods , Organs at Risk/radiation effects , Skin/radiation effects , Phantoms, Imaging , Neoplasms/radiotherapy , Particle Accelerators/instrumentation
7.
Asian Pac J Cancer Prev ; 25(4): 1383-1390, 2024 04 01.
Article in English | MEDLINE | ID: mdl-38680000

ABSTRACT

BACKGROUND: The study aims to investigate potential dosimetric benefits between non-coplanar and coplanar beam arrangements of Volumetric-Modulated Arc Therapy (VMAT) plans for liver stereotactic body radiotherapy (SBRT). METHODS: Thirteen patients who had undergone liver SBRT treatment in our department were chosen retrospectively for the study. Two sets of SBRT-VMAT plans namely, non-coplanar (NC-VMAT) and Coplanar (C-VMAT) were generated in Monaco(v5.11) planning system for Elekta Versa HD Linac using unflatten 6MV photon. The NC-VMAT plans were created by two/three non-coplanar partial arcs with couch rotation of ±150 and had an arc span of 1300 to 1600 whereas the C-VMAT plans consisted of a full arc. Both plans were compared by statistically analyzing various dosimetric and technical parameters. RESULTS: There is no statistically significant difference observed between the C-VMAT and NC-VMAT plans for planning target volume (PTV) coverage. However, the spine dose (D1cc) was much less in the NC-VMAT plan compared to the C-VMAT plan, with mean values of 6.127 ± 3.08Gy and 9.058 ± 4.76Gy, respectively (p-value=0.002). The low dose spillage to the healthy tissue was compared by the volume receiving 5Gy (V5Gy) and 10Gy (V10Gy). V5Gy of the NC-VMAT plan was 2399.23±1870.76cc while that of C-VMAT plans was 2835.36±1930.20cc with the p-value <0.001. Moreover, the monitor units(MU) were less with NC-VMAT than with C-VMAT SBRT plans (p=0.015). CONCLUSION: The plan quality of NC-VMAT plans was favorable compared to C-VMAT plans for liver SBRT especially in reducing spine dose, low dose spillage to healthy tissue, and MU.


Subject(s)
Liver Neoplasms , Organs at Risk , Radiosurgery , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Radiotherapy, Intensity-Modulated , Humans , Radiosurgery/methods , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy, Intensity-Modulated/methods , Liver Neoplasms/radiotherapy , Liver Neoplasms/surgery , Retrospective Studies , Organs at Risk/radiation effects , Prognosis , Male , Female , Follow-Up Studies , Aged , Middle Aged
8.
J Egypt Natl Canc Inst ; 36(1): 11, 2024 Apr 08.
Article in English | MEDLINE | ID: mdl-38584227

ABSTRACT

BACKGROUND: The moderate deep inspiratory breath hold (mDIBH) is a modality famed for cardiac sparing. Prospective studies based on this are few from the eastern part of the world and India. We intend to compare the dosimetry between mDIBH and free-breathing (FB) plans. METHODS: Thirty-two locally advanced left breast cancer patients were taken up for the study. All patients received a dose of 50 Gy in 25 fractions to the chest wall/intact breast, followed by a 10-Gy boost to the lumpectomy cavity in the case of breast conservation surgery. All the patients were treated in mDIBH using active breath coordinator (ABC). The data from the two dose volume histograms were compared regarding plan quality and the doses received by the organs at risk. Paired t-test was used for data analysis. RESULTS: The dose received by the heart in terms of V5, V10, and V30 (4.55% vs 8.39%) and mean dose (4.73 Gy vs 6.74 Gy) were statistically significant in the ABC group than that in the FB group (all p-values < 0.001). Also, the dose received by the LADA in terms of V30 (19.32% vs 24.87%) and mean dose (32.99 Gy vs 46.65 Gy) were significantly less in the ABC group. The mean treatment time for the ABC group was 20 min, while that for the free-breathing group was 10 min. CONCLUSIONS: Incorporating ABC-mDIBH for left-sided breast cancer radiotherapy significantly reduces the doses received by the heart, LADA, and left and right lung, with no compromise in plan quality but with an increase in treatment time.


Subject(s)
Breast Neoplasms , Unilateral Breast Neoplasms , Humans , Female , Breath Holding , Unilateral Breast Neoplasms/radiotherapy , Breast Neoplasms/radiotherapy , Prospective Studies , Heart , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Organs at Risk
9.
Technol Cancer Res Treat ; 23: 15330338241242654, 2024.
Article in English | MEDLINE | ID: mdl-38584413

ABSTRACT

Purpose: Deep learning (DL) is widely used in dose prediction for radiation oncology, multiple DL techniques comparison is often lacking in the literature. To compare the performance of 4 state-of-the-art DL models in predicting the voxel-level dose distribution for cervical cancer volumetric modulated arc therapy (VMAT). Methods and Materials: A total of 261 patients' plans for cervical cancer were retrieved in this retrospective study. A three-channel feature map, consisting of a planning target volume (PTV) mask, organs at risk (OARs) mask, and CT image was fed into the three-dimensional (3D) U-Net and its 3 variants models. The data set was randomly divided into 80% as training-validation and 20% as testing set, respectively. The model performance was evaluated on the 52 testing patients by comparing the generated dose distributions against the clinical approved ground truth (GT) using mean absolute error (MAE), dose map difference (GT-predicted), clinical dosimetric indices, and dice similarity coefficients (DSC). Results: The 3D U-Net and its 3 variants DL models exhibited promising performance with a maximum MAE within the PTV 0.83% ± 0.67% in the UNETR model. The maximum MAE among the OARs is the left femoral head, which reached 6.95% ± 6.55%. For the body, the maximum MAE was observed in UNETR, which is 1.19 ± 0.86%, and the minimum MAE was 0.94 ± 0.85% for 3D U-Net. The average error of the Dmean difference for different OARs is within 2.5 Gy. The average error of V40 difference for the bladder and rectum is about 5%. The mean DSC under different isodose volumes was above 90%. Conclusions: DL models can predict the voxel-level dose distribution accurately for cervical cancer VMAT treatment plans. All models demonstrated almost analogous performance for voxel-wise dose prediction maps. Considering all voxels within the body, 3D U-Net showed the best performance. The state-of-the-art DL models are of great significance for further clinical applications of cervical cancer VMAT.


Subject(s)
Deep Learning , Radiotherapy, Intensity-Modulated , Uterine Cervical Neoplasms , Female , Humans , Radiotherapy, Intensity-Modulated/methods , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy Dosage , Uterine Cervical Neoplasms/diagnostic imaging , Uterine Cervical Neoplasms/radiotherapy , Retrospective Studies , Organs at Risk
10.
Technol Cancer Res Treat ; 23: 15330338241241898, 2024.
Article in English | MEDLINE | ID: mdl-38557213

ABSTRACT

Introduction: In this study, we sought to develop a thermoplastic patient-specific helmet bolus that could deliver a uniform therapeutic dose to the target and minimize the dose to the normal brain during whole-scalp treatment with a humanoid head phantom. Methods: The bolus material was a commercial thermoplastic used for patient immobilization, and the holes in the netting were filled with melted paraffin. We compared volumetric-modulated arc therapy treatment plans with and without the bolus for quantitative dose distribution analysis. We analyzed the dose distribution in the region of interest to compare dose differences between target and normal organs. For quantitative analysis of treatment dose, OSLD chips were attached at the vertex (VX), posterior occipital (PO), right (RT), and left temporal (LT) locations. Results: The average dose in the clinical target volume was 6553.8 cGy (99.3%) with bolus and 5874 cGy (89%) without bolus, differing by more than 10% from the prescribed dose (6600 cGy) to the scalp target. For the normal brain, it was 3747.8 cGy (56.8%) with bolus and 5484.6 cGy (83.1%) without bolus. These results show that while the dose to the treatment target decreased, the average dose to the normal brain, which is mostly inside the treatment target, increased by more than 25%. With the bolus, the OSLD measured dose was 102.5 ± 1.2% for VX and 101.5 ± 1.9%, 95.9 ± 1.9%, and 81.8 ± 2.1% for PO, RT, and LT, respectively. In addition, the average dose in the treatment plan was 102%, 101%, 93.6%, and 80.7% for VX, PO, RT, and LT. When no bolus was administered, 59.6 ± 2.4%, 112.6 ± 1.8%, 47.1 ± 1.6%, and 53.1 ± 2.3% were assessed as OSLD doses for VX, PO, RT, and LT, respectively. Conclusion: This study proposed a method to fabricate patient-specific boluses that are highly reproducible, accessible, and easy to fabricate for radiotherapy to the entire scalp and can effectively spare normal tissue while delivering sufficient surface dose.


Subject(s)
Organothiophosphorus Compounds , Radiotherapy, Intensity-Modulated , Humans , Radiotherapy, Intensity-Modulated/methods , Scalp , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted/methods , Feasibility Studies , Head Protective Devices , Organs at Risk/radiation effects
11.
Acta Oncol ; 63: 240-247, 2024 Apr 29.
Article in English | MEDLINE | ID: mdl-38682458

ABSTRACT

BACKGROUND AND PURPOSE: Doses to the coronary arteries in breast cancer (BC) radiotherapy (RT) have been suggested to be a risk predictor of long-term cardiac toxicity after BC treatment. We investigated the dose-risk relationships between near maximum doses (Dmax) to the right coronary artery (RCA) and left anterior descending coronary artery (LAD) and ischemic heart disease (IHD) mortality after BC RT. PATIENTS AND METHODS: In a cohort of 2,813 women diagnosed with BC between 1958 and 1992 with a follow-up of at least 10 years, we identified 134 cases of death due to IHD 10-19 years after BC diagnosis. For each case, one control was selected within the cohort matched for age at diagnosis. 3D-volume and 3D-dose reconstructions were obtained from individual RT charts. We estimated the Dmax to the RCA and the LAD and the mean heart dose (MHD). We performed conditional logistic regression analysis comparing piecewise spline transformation and simple linear modeling for best fit. RESULTS: There was a linear dose-risk relationship for both the Dmax to the RCA (odds ratio [OR]/Gray [Gy] 1.03 [1.01-1.05]) and the LAD (OR/Gy 1.04 [1.02-1.06]) in a multivariable model. For MHD there was a linear dose-risk relationship (1,14 OR/Gy [1.08-1.19]. For all relationships, simple linear modelling was superior to spline transformations. INTERPRETATION: Doses to both the RCA and LAD are independent risk predictors of long-term cardiotoxicity after RT for BC In addition to the LAD, the RCA should be regarded as an organ at risk in RT planning.


Subject(s)
Breast Neoplasms , Coronary Vessels , Myocardial Ischemia , Humans , Female , Breast Neoplasms/radiotherapy , Breast Neoplasms/mortality , Case-Control Studies , Middle Aged , Coronary Vessels/radiation effects , Coronary Vessels/pathology , Myocardial Ischemia/etiology , Myocardial Ischemia/mortality , Aged , Adult , Radiation Injuries/etiology , Radiation Injuries/epidemiology , Radiation Injuries/mortality , Radiotherapy Dosage , Dose-Response Relationship, Radiation , Organs at Risk/radiation effects , Follow-Up Studies , Cohort Studies
12.
Radiat Oncol ; 19(1): 45, 2024 Apr 08.
Article in English | MEDLINE | ID: mdl-38589961

ABSTRACT

BACKGROUND: Current automated planning solutions are calibrated using trial and error or machine learning on historical datasets. Neither method allows for the intuitive exploration of differing trade-off options during calibration, which may aid in ensuring automated solutions align with clinical preference. Pareto navigation provides this functionality and offers a potential calibration alternative. The purpose of this study was to validate an automated radiotherapy planning solution with a novel multi-dimensional Pareto navigation calibration interface across two external institutions for prostate cancer. METHODS: The implemented 'Pareto Guided Automated Planning' (PGAP) methodology was developed in RayStation using scripting and consisted of a Pareto navigation calibration interface built upon a 'Protocol Based Automatic Iterative Optimisation' planning framework. 30 previous patients were randomly selected by each institution (IA and IB), 10 for calibration and 20 for validation. Utilising the Pareto navigation interface automated protocols were calibrated to the institutions' clinical preferences. A single automated plan (VMATAuto) was generated for each validation patient with plan quality compared against the previously treated clinical plan (VMATClinical) both quantitatively, using a range of DVH metrics, and qualitatively through blind review at the external institution. RESULTS: PGAP led to marked improvements across the majority of rectal dose metrics, with Dmean reduced by 3.7 Gy and 1.8 Gy for IA and IB respectively (p < 0.001). For bladder, results were mixed with low and intermediate dose metrics reduced for IB but increased for IA. Differences, whilst statistically significant (p < 0.05) were small and not considered clinically relevant. The reduction in rectum dose was not at the expense of PTV coverage (D98% was generally improved with VMATAuto), but was somewhat detrimental to PTV conformality. The prioritisation of rectum over conformality was however aligned with preferences expressed during calibration and was a key driver in both institutions demonstrating a clear preference towards VMATAuto, with 31/40 considered superior to VMATClinical upon blind review. CONCLUSIONS: PGAP enabled intuitive adaptation of automated protocols to an institution's planning aims and yielded plans more congruent with the institution's clinical preference than the locally produced manual clinical plans.


Subject(s)
Prostatic Neoplasms , Radiotherapy, Intensity-Modulated , Male , Humans , Radiotherapy, Intensity-Modulated/methods , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted/methods , Urinary Bladder , Prostatic Neoplasms/radiotherapy , Organs at Risk
13.
Phys Med ; 121: 103346, 2024 May.
Article in English | MEDLINE | ID: mdl-38608421

ABSTRACT

Partial breast irradiation for the treatment of early-stage breast cancer patients can be performed by means of Intra Operative electron Radiation Therapy (IOeRT). One of the main limitations of this technique is the absence of a treatment planning system (TPS) that could greatly help in ensuring a proper coverage of the target volume during irradiation. An IOeRT TPS has been developed using a fast Monte Carlo (MC) and an ultrasound imaging system to provide the best irradiation strategy (electron beam energy, applicator position and bevel angle) and to facilitate the optimisation of dose prescription and delivery to the target volume while maximising the organs at risk sparing. The study has been performed in silico, exploiting MC simulations of a breast cancer treatment. Ultrasound-based input has been used to compute the absorbed dose maps in different irradiation strategies and a quantitative comparison between the different options was carried out using Dose Volume Histograms. The system was capable of exploring different beam energies and applicator positions in few minutes, identifying the best strategy with an overall computation time that was found to be completely compatible with clinical implementation. The systematic uncertainty related to tissue deformation during treatment delivery with respect to imaging acquisition was taken into account. The potential and feasibility of a GPU based full MC TPS implementation of IOeRT breast cancer treatments has been demonstrated in-silico. This long awaited tool will greatly improve the treatment safety and efficacy, overcoming the limits identified within the clinical trials carried out so far.


Subject(s)
Breast Neoplasms , Monte Carlo Method , Radiotherapy Planning, Computer-Assisted , Breast Neoplasms/radiotherapy , Breast Neoplasms/diagnostic imaging , Humans , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy Dosage , Electrons/therapeutic use , Time Factors , Computer Graphics , Female , Organs at Risk/radiation effects
14.
Phys Med ; 121: 103369, 2024 May.
Article in English | MEDLINE | ID: mdl-38669811

ABSTRACT

PURPOSE: In radiotherapy it is often necessary to transfer a patient's DICOM (Digital Imaging and COmmunications in Medicine) dataset from one system to another for re-treatment, plan-summation or registration purposes. The aim of the study is to evaluate effects of dataset transfer between treatment planning systems. MATERIALS AND METHODS: Twenty-five patients treated in a 0.35T MR-Linac (MRidian, ViewRay) for locally-advanced pancreatic cancer were enrolled. For each patient, a nominal dose distribution was optimized on the planning MRI. Each plan was daily re-optimized if needed to match the anatomy and exported from MRIdian-TPS (ViewRay Inc.) to Eclipse-TPS (Siemens-Varian). A comparison between the two TPSs was performed considering the PTV and OARs volumes (cc), as well as dose coverages and clinical constraints. RESULTS: From the twenty-five enrolled patients, 139 plans were included in the data comparison. The median values of percentage PTV volume variation are 10.8 % for each fraction, while percentage differences of PTV coverage have a mean value of -1.4 %. The median values of the percentage OARs volume variation are 16.0 %, 7.0 %, 10.4 % and 8.5 % for duodenum, stomach, small and large bowel, respectively. The percentage variations of the dose constraints are 41.0 %, 52.7 % and 49.8 % for duodenum, stomach and small bowel, respectively. CONCLUSIONS: This study has demonstrated a non-negligible variation in size and dosimetric parameters when datasets are transferred between TPSs. Such variations should be clinically considered. Investigations are focused on DICOM structure algorithm employed by the TPSs during the transfer to understand the cause of such variations.


Subject(s)
Pancreatic Neoplasms , Radiometry , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Radiotherapy Planning, Computer-Assisted/methods , Humans , Pancreatic Neoplasms/radiotherapy , Pancreatic Neoplasms/diagnostic imaging , Organs at Risk/radiation effects , Magnetic Resonance Imaging
15.
In Vivo ; 38(3): 1412-1420, 2024.
Article in English | MEDLINE | ID: mdl-38688603

ABSTRACT

BACKGROUND/AIM: To compare implant sparing irradiation with conventional radiotherapy (RT) using helical (H) and TomoDirect (TD) techniques in breast cancer patients undergoing immediate breast reconstruction (IBR). PATIENTS AND METHODS: The dosimetric parameters of 40 patients with retropectoral implants receiving 50.4 Gy delivered in 28 fractions were analyzed. Three plans were created: H plan using conventional planning target volume (PTV) that included the chest wall, skin, and implant; TD plan using conventional PTV; and Hs plan using implant-sparing PTV. The H, TD, and Hs plans were compared for PTV doses, organ-at-risk (OAR) doses, and treatment times. RESULTS: Dose distribution in the Hs plan was less homogeneous and uniform than that in the H and TD plans. The TD plan had lower lung, heart, contralateral breast, spinal cord, liver, and esophagus doses than the Hs plan. Compared to the Hs plan, the H plan had lower lung volume receiving 5Gy (V5) (39.1±3.9 vs. 41.2±3.9 Gy; p<0.001), higher V20 (12.3±1.3 vs. 11.5±2.6 Gy; p=0.02), and higher V30 (7.5±1.6 vs. 4.4±1.7 Gy; p<0.001). H plan outperformed Hs plan in heart dosimetric parameters except V20. The Hs plan had significantly lower mean implant doses (43.4±2.1 Gy) than the H plan (51.4±0.5 Gy; p<0.001) and the TD plan (51.9±0.6 Gy; p<0.001). Implementing an implant sparing technique for silicone dose reduction decreases lung doses. CONCLUSION: Conventional H and TD plans outperform the implant sparing helical plan dosimetrically. Because capsular contracture during RT is unpredictable, long-term clinical outcomes are required to determine whether silicon should be spared.


Subject(s)
Breast Neoplasms , Mammaplasty , Organs at Risk , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Radiotherapy, Intensity-Modulated , Humans , Female , Breast Neoplasms/radiotherapy , Breast Neoplasms/surgery , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy, Intensity-Modulated/methods , Middle Aged , Mammaplasty/methods , Adult , Breast Implants , Radiometry , Aged
16.
Radiat Oncol ; 19(1): 53, 2024 Apr 30.
Article in English | MEDLINE | ID: mdl-38689338

ABSTRACT

PURPOSE: The number of older adults with head and neck squamous cell carcinoma (HNSCC) is continuously increasing. Older HNSCC patients may be more vulnerable to radiotherapy-related toxicities, so that extrapolation of available normal tissue complication probability (NTCP) models to this population may not be appropriate. Hence, we aimed to investigate the correlation between organ at risk (OAR) doses and chronic toxicities in older patients with HNSCC undergoing definitive radiotherapy. METHODS: Patients treated with definitive radiotherapy, either alone or with concomitant systemic treatment, between 2009 and 2019 in a large tertiary cancer center were eligible for this analysis. OARs were contoured based on international consensus guidelines, and EQD2 doses using α/ß values of 3 Gy for late effects were calculated based on the radiation treatment plans. Treatment-related toxicities were graded according to Common Terminology Criteria for Adverse Events version 5.0. Logistic regression analyses were carried out, and NTCP models were developed and internally validated using the bootstrapping method. RESULTS: A total of 180 patients with a median age of 73 years fulfilled the inclusion criteria and were analyzed. Seventy-three patients developed chronic moderate xerostomia (grade 2), 34 moderate dysgeusia (grade 2), and 59 moderate-to-severe (grade 2-3) dysphagia after definitive radiotherapy. The soft palate dose was significantly associated with all analyzed toxicities (xerostomia: OR = 1.028, dysgeusia: OR = 1.022, dysphagia: OR = 1.027) in the multivariable regression. The superior pharyngeal constrictor muscle was also significantly related to chronic dysphagia (OR = 1.030). Consecutively developed and internally validated NTCP models were predictive for the analyzed toxicities (optimism-corrected AUCs after bootstrapping: AUCxerostomia=0.64, AUCdysgeusia=0.60, AUCdysphagia=0.64). CONCLUSIONS: Our data suggest that the dose to the soft palate is associated with chronic moderate xerostomia, moderate dysgeusia and moderate-to-severe dysphagia in older HNSCC patients undergoing definitive radiotherapy. If validated in external studies, efforts should be undertaken to reduce the soft palate dose in these patients.


Subject(s)
Head and Neck Neoplasms , Organs at Risk , Palate, Soft , Radiation Injuries , Radiotherapy Dosage , Squamous Cell Carcinoma of Head and Neck , Humans , Aged , Female , Male , Head and Neck Neoplasms/radiotherapy , Organs at Risk/radiation effects , Palate, Soft/radiation effects , Radiation Injuries/etiology , Aged, 80 and over , Middle Aged , Squamous Cell Carcinoma of Head and Neck/radiotherapy , Retrospective Studies , Radiotherapy Planning, Computer-Assisted/methods
17.
J Appl Clin Med Phys ; 25(5): e14318, 2024 May.
Article in English | MEDLINE | ID: mdl-38427776

ABSTRACT

PURPOSE: To quantify the impact of treatment planning system beam model parameters, based on the actual spread in radiotherapy community data, on clinical treatment plans and determine which complexity metrics best describe the impact beam modeling errors have on dose accuracy. METHODS: Ten beam modeling parameters for a Varian accelerator were modified in RayStation to match radiotherapy community data at the 2.5, 25, 50, 75, and 97.5 percentile levels. These modifications were evaluated on 25 patient cases, including prostate, non-small cell lung, H&N, brain, and mesothelioma, generating 1,000 plan perturbations. Differences in the mean planned dose to clinical target volumes (CTV) and organs at risk (OAR) were evaluated with respect to the planned dose using the reference (50th-percentile) parameter values. Correlation between CTV dose differences, and 18 different complexity metrics were evaluated using linear regression; R-squared values were used to determine the best metric. RESULTS: Perturbations to MLC offset and transmission parameters demonstrated the greatest changes in dose: up to 5.7% in CTVs and 16.7% for OARs. More complex clinical plans showed greater dose perturbation with atypical beam model parameters. The mean MLC Gap and Tongue & Groove index (TGi) complexity metrics best described the impact of TPS beam modeling variations on clinical dose delivery across all anatomical sites; similar, though not identical, trends between complexity and dose perturbation were observed among all sites. CONCLUSION: Extreme values for MLC offset and MLC transmission beam modeling parameters were found to most substantially impact the dose distribution of clinical plans and careful attention should be given to these beam modeling parameters. The mean MLC Gap and TGi complexity metrics were best suited to identifying clinical plans most sensitive to beam modeling errors; this could help provide focus for clinical QA in identifying unacceptable plans.


Subject(s)
Neoplasms , Organs at Risk , Particle Accelerators , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Radiotherapy, Intensity-Modulated , Humans , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy, Intensity-Modulated/methods , Organs at Risk/radiation effects , Neoplasms/radiotherapy , Particle Accelerators/instrumentation , Algorithms
18.
Radiat Oncol ; 19(1): 39, 2024 Mar 20.
Article in English | MEDLINE | ID: mdl-38509540

ABSTRACT

BACKGROUND: At present, the implementation of intensity-modulated radiation therapy (IMRT) treatment planning for geometrically complex nasopharyngeal carcinoma (NPC) through manual trial-and-error fashion presents challenges to the improvement of planning efficiency and the obtaining of high-consistency plan quality. This paper aims to propose an automatic IMRT plan generation method through fluence prediction and further plan fine-tuning for patients with NPC and evaluates the planning efficiency and plan quality. METHODS: A total of 38 patients with NPC treated with nine-beam IMRT were enrolled in this study and automatically re-planned with the proposed method. A trained deep learning model was employed to generate static field fluence maps for each patient with 3D computed tomography images and structure contours as input. Automatic IMRT treatment planning was achieved by using its generated dose with slight tightening for further plan fine-tuning. Lastly, the plan quality was compared between automatic plans and clinical plans. RESULTS: The average time for automatic plan generation was less than 4 min, including fluence maps prediction with a python script and automated plan tuning with a C# script. Compared with clinical plans, automatic plans showed better conformity and homogeneity for planning target volumes (PTVs) except for the conformity of PTV-1. Meanwhile, the dosimetric metrics for most organs at risk (OARs) were ameliorated in the automatic plan, especially Dmax of the brainstem and spinal cord, and Dmean of the left and right parotid glands significantly decreased (P < 0.05). CONCLUSION: We have successfully implemented an automatic IMRT plan generation method for patients with NPC. This method shows high planning efficiency and comparable or superior plan quality than clinical plans. The qualitative results before and after the plan fine-tuning indicates that further optimization using dose objectives generated by predicted fluence maps is crucial to obtain high-quality automatic plans.


Subject(s)
Nasopharyngeal Neoplasms , Radiotherapy, Intensity-Modulated , Humans , Nasopharyngeal Carcinoma/radiotherapy , Radiotherapy, Intensity-Modulated/methods , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted/methods , Organs at Risk , Nasopharyngeal Neoplasms/radiotherapy
19.
Radiat Prot Dosimetry ; 200(6): 538-543, 2024 Apr 20.
Article in English | MEDLINE | ID: mdl-38441907

ABSTRACT

The objective of this study is dosimetric comparison between the O-ring Halcyon and C-arm Clinac iX linac for volumetric modulated arc therapy (VMAT) plans for head & neck (H&N) cancer and carcinoma cervix patients. Total 60 patients of H&N cancer and carcinoma cervix were enrolled prospectively from March 2021 to March 2023. VMAT plans with 6 MV photons for Halcyon and Clinac iX were generated and compared for each patient by dose volume histogram for planning target volume coverage and organ at risk (OAR) sparing. There were no differences in between both the linacs for PTV D2% and D98%, homogeneity index, conformity index, Dmax (maximum dose) and Dmean (mean dose) of OAR. Halcyon had significantly shorter treatment time compared to Clinac iX. Halcyon delivered higher integral dose and monitor units. O-ring Halcyon produces VMAT plans comparable to other C-arm linacs for H&N and carcinoma cervix patients.


Subject(s)
Head and Neck Neoplasms , Organs at Risk , Particle Accelerators , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Radiotherapy, Intensity-Modulated , Uterine Cervical Neoplasms , Humans , Radiotherapy, Intensity-Modulated/methods , Female , Uterine Cervical Neoplasms/radiotherapy , Radiotherapy Planning, Computer-Assisted/methods , Particle Accelerators/instrumentation , Head and Neck Neoplasms/radiotherapy , Organs at Risk/radiation effects , Radiometry/methods , Prospective Studies , Middle Aged , Adult
20.
Phys Med Biol ; 69(9)2024 Apr 17.
Article in English | MEDLINE | ID: mdl-38537309

ABSTRACT

Objective.Predicting the probability of having the plan approved by the physician is important for automatic treatment planning. Driven by the mathematical foundation of deep learning that can use a deep neural network to represent functions accurately and flexibly, we developed a deep-learning framework that learns the probability of plan approval for cervical cancer high-dose-rate brachytherapy (HDRBT).Approach.The system consisted of a dose prediction network (DPN) and a plan-approval probability network (PPN). DPN predicts organs at risk (OAR)D2ccand CTVD90%of the current fraction from the patient's current anatomy and prescription dose of HDRBT. PPN outputs the probability of a given plan being acceptable to the physician based on the patients anatomy and the total dose combining HDRBT and external beam radiotherapy sessions. Training of the networks was achieved by first training them separately for a good initialization, and then jointly via an adversarial process. We collected approved treatment plans of 248 treatment fractions from 63 patients. Among them, 216 plans from 54 patients were employed in a four-fold cross validation study, and the remaining 32 plans from other 9 patients were saved for independent testing.Main results.DPN predicted equivalent dose of 2 Gy for bladder, rectum, sigmoidD2ccand CTVD90%with a relative error of 11.51% ± 6.92%, 8.23% ± 5.75%, 7.12% ± 6.00%, and 10.16% ± 10.42%, respectively. In a task that differentiates clinically approved plans and disapproved plans generated by perturbing doses in ground truth approved plans by 20%, PPN achieved accuracy, sensitivity, specificity, and area under the curve 0.70, 0.74, 0.65, and 0.74.Significance.We demonstrated the feasibility of developing a novel deep-learning framework that predicts a probability of plan approval for HDRBT of cervical cancer, which is an essential component in automatic treatment planning.


Subject(s)
Brachytherapy , Deep Learning , Uterine Cervical Neoplasms , Female , Humans , Radiotherapy Dosage , Brachytherapy/methods , Uterine Cervical Neoplasms/radiotherapy , Radiotherapy Planning, Computer-Assisted/methods , Organs at Risk
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