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[This corrects the article DOI: 10.3389/fonc.2022.879167.].
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The rapid development of artificial intelligence (AI) has gained importance, with many tools already entering our daily lives. The medical field of radiation oncology is also subject to this development, with AI entering all steps of the patient journey. In this review article, we summarize contemporary AI techniques and explore the clinical applications of AI-based automated segmentation models in radiotherapy planning, focusing on delineation of organs at risk (OARs), the gross tumor volume (GTV), and the clinical target volume (CTV). Emphasizing the need for precise and individualized plans, we review various commercial and freeware segmentation tools and also state-of-the-art approaches. Through our own findings and based on the literature, we demonstrate improved efficiency and consistency as well as time savings in different clinical scenarios. Despite challenges in clinical implementation such as domain shifts, the potential benefits for personalized treatment planning are substantial. The integration of mathematical tumor growth models and AI-based tumor detection further enhances the possibilities for refining target volumes. As advancements continue, the prospect of one-stop-shop segmentation and radiotherapy planning represents an exciting frontier in radiotherapy, potentially enabling fast treatment with enhanced precision and individualization.
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PURPOSE: Radiotherapy treatment planning (RTP) using MR has been used increasingly for the abdominal site. Multiple contrast weightings and motion-resolved imaging are desired for accurate delineation of the target and various organs-at-risk and patient-tailored planning. Current MR protocols achieve these through multiple scans with distinct contrast and variable respiratory motion management strategies and acquisition parameters, leading to a complex and inaccurate planning process. This study presents a standalone MR Multitasking (MT)-based technique to produce volumetric, motion-resolved, multicontrast images for abdominal radiotherapy treatment planning. METHODS: The MT technique resolves motion and provides a wide range of contrast weightings by repeating a magnetization-prepared (saturation recovery and T2 preparations) spoiled gradient-echo readout series and adopting the MT image reconstruction framework. The performance of the technique was assessed through digital phantom simulations and in vivo studies of both healthy volunteers and patients with liver tumors. RESULTS: In the digital phantom study, the MT technique presented structural details and motion in excellent agreement with the digital ground truth. The in vivo studies showed that the motion range was highly correlated (R2 = 0.82) between MT and 2D cine imaging. MT allowed for a flexible contrast-weighting selection for better visualization. Initial clinical testing with interobserver analysis demonstrated acceptable target delineation quality (Dice coefficient = 0.85 ± 0.05, Hausdorff distance = 3.3 ± 0.72 mm). CONCLUSION: The developed MT-based, abdomen-dedicated technique is capable of providing motion-resolved, multicontrast volumetric images in a single scan, which may facilitate abdominal radiotherapy treatment planning.
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Background: Electronic portal imaging devices (EPIDs) are applied to measure the dose and verify patients' position. Objective: The present study aims to evaluate the performance of EPID for measuring dosimetric parameters in small photon fields. Material and Methods: In this experimental study, the output factors and beam profiles were obtained using the amorphous silicon (a-Si) EPID for square field sizes ranging from 1×1 to 10×10 cm2 at energies 6 and 18 mega-voltage (MV). For comparison, the dosimetric parameters were measured with the pinpoint, diode, and Semiflex dosimeters. Additionally, the Monaco treatment planning system was selected to calculate the output factors and beam profiles. Results: There was a significant difference between the output factors measured using the EPID and that measured with the other dosimeters for field sizes lower than 8×8 cm2. In the energy of 6 MV, the gamma passing rates (3%/3 mm) between EPID and diode profile were 98%, 98%, 95%, 94%, 93%, and 94% for 1×1, 2×2, 3×3, 4×4, 5×5, and 10×10 cm2, respectively. The measured penumbra width with EPID was higher compared to that measured by the diode dosimeter for both energies. Conclusion: The EPID can measure the dosimetric parameters in small photon fields, especially for beam profiles and penumbra measurements.
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PURPOSE: In radiotherapy of the head and neck (H&N) it is common for the clinical target volume (CTV) to extend to the patient's skin. Adding a margin for set-up uncertainty and delivery creates a planning target volume (PTV) that extends beyond the patient surface. This can result in excessive fluence being delivered to the build-up region and therefore the skin. This study evaluates four different planning methods used when inverse-planning H&N radiotherapy treatments with CTV extending to the skin. The aim of the study was to determine which planning method gives superior plan quality. METHOD: Ten H&N cancer patients with a CTV contoured to the skin were inverse-planned using four planning methods. The planning methods compared were: cropping the optimization PTV back from the skin surface by 5.0, 3.0, and 0.0 mm and a virtual bolus method. For each planning method, the increased fluence at the skin surface was analyzed. The CTV coverage and skin doses were compared. Plan robustness was evaluated by applying an isocenter shift of ±3.0 mm in the major axes. RESULTS: The planning method cropping the PTV 0.0 mm from the skin surface results in an increased fluence in the build-up region. The average volume of CTV receiving 98% of the prescription dose was 89.6% ± 3.4%, 91.6% ± 2.4%, and 93.5% ± 1.7% when cropped 5.0, 3.0, and 0.0 mm, respectively, and 93.4% ± 2.1% for the virtual bolus method. Introducing plan uncertainty affects CTV coverage the most when cropping 5.0 mm. When plan uncertainties are considered the methods of cropping 5.0, 3.0 mm, and the virtual bolus method have the same average skin dose within ±0.3%. CONCLUSION: This study shows that a virtual bolus planning method results in no increased fluence at the patient's surface, improves CTV coverage, and is the most robust to changes in setup and patient anatomy.
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PURPOSE: This study aimed to develop an automated Tomotherapy (TOMO) planning method for cervical cancer treatment, and to validate its feasibility and effectiveness. MATERIALS AND METHODS: The study enrolled 30 cervical cancer patients treated with TOMO at our center. Utilizing scripting and Python environment within the RayStation (RaySearch Labs, Sweden) treatment planning system (TPS), we developed automated planning methods for TOMO and volumetric modulated arc therapy (VMAT) techniques. The clinical manual TOMO (M-TOMO) plans for the 30 patients were re-optimized using automated planning scripts for both TOMO and VMAT, creating automated TOMO (A-TOMO) and automated VMAT (A-VMAT) plans. We compared A-TOMO with M-TOMO and A-VMAT plans. The primary evaluated relevant dosimetric parameters and treatment plan efficiency were assessed using the two-sided Wilcoxon signed-rank test for statistical analysis, with a P-value < 0.05 indicating statistical significance. RESULTS: A-TOMO plans maintained similar target dose uniformity compared to M-TOMO plans, with improvements in target conformity and faster dose drop-off outside the target, and demonstrated significant statistical differences (P+ < 0.01). A-TOMO plans also significantly outperformed M-TOMO plans in reducing V50Gy, V40Gy and Dmean for the bladder and rectum, as well as Dmean for the bowel bag, femoral heads, and kidneys (all P+ < 0.05). Additionally, A-TOMO plans demonstrated better consistency in plan quality. Furthermore, the quality of A-TOMO plans was comparable to or superior than A-VMAT plans. In terms of efficiency, A-TOMO significantly reduced the time required for treatment planning to approximately 20 min. CONCLUSION: We have successfully developed an A-TOMO planning method for cervical cancer. Compared to M-TOMO plans, A-TOMO plans improved target conformity and reduced radiation dose to OARs. Additionally, the quality of A-TOMO plans was on par with or surpasses that of A-VMAT plans. The A-TOMO planning method significantly improved the efficiency of treatment planning.
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Órgãos em Risco , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador , Radioterapia de Intensidade Modulada , Neoplasias do Colo do Útero , Humanos , Neoplasias do Colo do Útero/radioterapia , Feminino , Planejamento da Radioterapia Assistida por Computador/métodos , Radioterapia de Intensidade Modulada/métodos , Órgãos em Risco/efeitos da radiaçãoRESUMO
Novel hybrid approaches for chest wall irradiation show promising outcomes regarding target coverage and sparing organs at risk (OARs). In this systematic review, we compared hybrid volumetric modulated arc therapy (H-VMAT) or hybrid intensity-modulated radiotherapy (H-IMRT) techniques with non-hybrid techniques, such as three-dimensional conformal radiation therapy (3DCRT), field-in-field (FIF), intensity-modulated arc therapy (IMRT), and volumetric modulated arc therapy (VMAT), for breast cancer patients with mastectomy. Our focus was the plan quality and dose distribution to the OARs. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist, we performed a systematic review and quality appraisal of primary studies evaluating hybrid therapy to the chest wall and the OARs. An extensive online search of PubMed and Scopus databases was conducted using appropriate keywords. The dose to the OARs (lung, heart, and contralateral breast), planning target volume (PTV), homogeneity index (HI), and conformity index (CI) were extracted. The data were then tabulated and compared for the outcomes between modalities among the studies. Nine studies that met the search criteria were selected to evaluate the PTV coverage and dosimetric results of hybrid and non-hybrid techniques. In terms of 95% PTV coverage, among nine reviewed studies, the largest difference between the two techniques was between VMAT (47.6 Gy) and H-VMAT (48.4 Gy); for the conformity index, the largest difference was noted between 3DCRT (0.58) and H-VMAT (0.79). In both cases, differences were statistically significant (P < 0.005). Two studies showed dose homogeneity improvement within the treatment target in H-VMAT (0.15 and 0.07) compared with 3DCRT (0.41 and 0.12), with a P value of <0.001. Two studies did not report on the homogeneity index, and three others observed no statistical difference. Regarding OARs, in the comparison of H-VMAT and VMAT, the largest significant change was in the volume receiving 5 Gy (V5Gy) of the ipsilateral lung and the V10Gy of the contralateral lung. For the ipsilateral lung, V5Gy was 90.7% with VMAT versus 51.45% with H-VMAT. For the contralateral lung, V10Gy was 54.9% with VMAT versus 50.5% with H-VMAT. In six studies, the mean dose of the contralateral breast was lower in hybrid techniques than in single modalities: VMAT (4.2%, 6.0%, 1.9%, 7.1%, 4.57%) versus H-VMAT (1.4%, 3.4%, 1.8%, 3.5%, 2.34%) and IMRT (9.1%) versus H-IMRT (4.69%). Although most studies did not report on monitor units and treatment time, those that included them showed that hybrids had lower monitor units and shorter treatment times. Hybrid techniques in radiotherapy, such as combining two modalities, can indeed facilitate lower doses to OARs for patients with a high risk of toxicities. Prospective clinical studies are needed to determine the outcomes of breast cancer treated with hybrid techniques.
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Delineation of cardiac substructures is crucial for a better understanding of radiation-related cardiotoxicities and to facilitate accurate and precise cardiac dose calculation for developing and applying risk models. This review examines recent advancements in cardiac substructure delineation in the radiation therapy (RT) context, aiming to provide a comprehensive overview of the current level of knowledge, challenges and future directions in this evolving field. Imaging used for RT planning presents challenges in reliably visualising cardiac anatomy. Although cardiac atlases and contouring guidelines aid in standardisation and reduction of variability, significant uncertainties remain in defining cardiac anatomy. Coupled with the inherent complexity of the heart, this necessitates auto-contouring for consistent large-scale data analysis and improved efficiency in prospective applications. Auto-contouring models, developed primarily for breast and lung cancer RT, have demonstrated performance comparable to manual contouring, marking a significant milestone in the evolution of cardiac delineation practices. Nevertheless, several key concerns require further investigation. There is an unmet need for expanding cardiac auto-contouring models to encompass a broader range of cancer sites. A shift in focus is needed from ensuring accuracy to enhancing the robustness and accessibility of auto-contouring models. Addressing these challenges is paramount for the integration of cardiac substructure delineation and associated risk models into routine clinical practice, thereby improving the safety of RT for future cancer patients.
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BACKGROUND: Fibroblast activation protein (FAP) is expressed in the tumor microenvironment (TME) of various cancers. In our analysis, we describe the impact of dual-tracer imaging with Gallium-68-radiolabeled inhibitors of FAP (FAPI-46-PET/CT) and fluorodeoxy-D-glucose (FDG-PET/CT) on the radiotherapeutic management of primary esophageal cancer (EC). METHODS: 32 patients with EC, who are scheduled for chemoradiation, received FDG and FAPI-46 PET/CT on the same day (dual-tracer protocol, 71%) or on two separate days (29%) We compared functional tumor volumes (FTVs), gross tumor volumes (GTVs) and tumor stages before and after PET-imaging. Changes in treatment were categorized as "minor" (adaption of radiation field) or "major" (change of treatment regimen). Immunohistochemistry (IHC) staining for FAP was performed in all patients with available tissue. RESULTS: Primary tumor was detected in all FAPI-46/dual-tracer scans and in 30/32 (93%) of FDG scans. Compared to the initial staging CT scan, 12/32 patients (38%) were upstaged in nodal status after the combination of FDG and FAPI-46 PET scans. Two lymph node metastases were only visible in FAPI-46/dual-tracer. New distant metastasis was observed in 2/32 (6%) patients following FAPI-4 -PET/CT. Our findings led to larger RT fields ("minor change") in 5/32 patients (16%) and changed treatment regimen ("major change") in 3/32 patients after FAPI-46/dual-tracer PET/CT. GTVs were larger in FAPI-46/dual-tracer scans compared to FDG-PET/CT (mean 99.0 vs. 80.3 ml, respectively (p < 0.001)) with similar results for nuclear medical FTVs. IHC revealed heterogenous FAP-expression in all specimens (mean H-score: 36.3 (SD 24.6)) without correlation between FAP expression in IHC and FAPI tracer uptake in PET/CT. CONCLUSION: We report first data on the use of PET with FAPI-46 for patients with EC, who are scheduled to receive RT. Tumor uptake was high and not depending on FAP expression in TME. Further, FAPI-46/dual-tracer PET had relevant impact on management in this setting. Our data calls for prospective evaluation of FAPI-46/dual-tracer PET to improve clinical outcomes of EC.
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Neoplasias Esofágicas , Quinolinas , Humanos , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Fluordesoxiglucose F18 , Neoplasias Esofágicas/diagnóstico por imagem , Neoplasias Esofágicas/radioterapia , Tomografia por Emissão de Pósitrons , Microambiente TumoralRESUMO
PURPOSE: Within a multi-institutional project, we aimed to assess the transferability of knowledge-based (KB) plan prediction models in the case of whole breast irradiation (WBI) for left-side breast irradiation with tangential fields (TF). METHODS: Eight institutions set KB models, following previously shared common criteria. Plan prediction performance was tested on 16 new patients (2 pts per centre) extracting dose-volume-histogram (DVH) prediction bands of heart, ipsilateral lung, contralateral lung and breast. The inter-institutional variability was quantified by the standard deviations (SDint) of predicted DVHs and mean-dose (Dmean). The transferability of models, for the heart and the ipsilateral lung, was evaluated by the range of geometric Principal Component (PC1) applicability of a model to test patients of the other 7 institutions. RESULTS: SDint of the DVH was 1.8â¯% and 1.6â¯% for the ipsilateral lung and the heart, respectively (20â¯%-80â¯% dose range); concerning Dmean, SDint was 0.9â¯Gy and 0.6â¯Gy for the ipsilateral lung and the heart, respectively (<0.2â¯Gy for contralateral organs). Mean predicted doses ranged between 4.3 and 5.9â¯Gy for the ipsilateral lung and 1.1-2.3â¯Gy for the heart. PC1 analysis suggested no relevant differences among models, except for one centre showing a systematic larger sparing of the heart, concomitant to a worse PTV coverage, due to high priority in sparing the left anterior descending coronary artery. CONCLUSIONS: Results showed high transferability among models and low inter-institutional variability of 2% for plan prediction. These findings encourage the building of benchmark models in the case of TF-WBI.
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Neoplasias da Mama , Radioterapia de Intensidade Modulada , Parede Torácica , Humanos , Feminino , Radioterapia de Intensidade Modulada/métodos , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador/métodos , Mama , Órgãos em Risco/efeitos da radiaçãoRESUMO
Background and purpose: Glioblastoma is one of the most common and aggressive primary brain tumours in adults. Though radiation therapy (RT) techniques have progressed significantly in recent decades, patient survival has seen little improvement. However, an area of promise is the use of fluorine-18-fluoroethyltyrosine positron-emission-tomography (18F-FET PET) imaging to assist in RT target delineation. This retrospective study aims to assess the impact of 18F-FET PET scan timing on the resultant RT target volumes and subsequent RT plans in post-operative glioblastoma patients. Materials and Methods: The imaging and RT treatment data of eight patients diagnosed with glioblastoma and treated at a single institution were analysed. Before starting RT, each patient had two 18F-FET-PET scans acquired within seven days of each other. The information from these 18F-FET-PET scans aided in the creation of two novel target volume sets. The new volumes and plans were compared with each other and the originals. Results: The median clinical target volume (CTV) 1 was statistically smaller than CTV 2. The median Dice score for the CTV1/CTV2 was 0.98 and, of the voxels that differ (median 6.5 cc), 99.7% were covered with a 5 mm expansion. Overall organs at risk (OAR) and target dosimetry were similar in the PTV1 and PTV2 plans. Conclusion: Provided the 18F-FET PET scan is acquired within two weeks of the RT planning and a comprehensive approach is taken to CTV delineation, the timing of scan acquisition has minimal impact on the resulting RT plan.
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OBJECTIVE: To investigate differences in uptake regions between methyl-11C-L-methionine positron emission tomography (11C-MET PET) and gadolinium (Gd)-enhanced magnetic resonance imaging (MRI), and their impact on dose distribution, including changing of the threshold for tumor boundaries. METHODS: Twenty consecutive patients with grade 3 or 4 glioma who had recurrence after postoperative radiotherapy (RT) between April 2016 and October 2017 were examined. The study was performed using simulation with the assumption that all patients received RT. The clinical target volume (CTV) was contoured using the Gd-enhanced region (CTV(Gd)), the tumor/normal tissue (T/N) ratios of 11C-MET PET of 1.3 and 2.0 (CTV (T/N 1.3), CTV (T/N 2.0)), and the PET-edge method (CTV(P-E)) for stereotactic RT planning. Differences among CTVs were evaluated. The brain dose at each CTV and the dose at each CTV defined by 11C-MET PET using MRI as the reference were evaluated. RESULTS: The Jaccard index (JI) for concordance of CTV (Gd) with CTVs using 11C-MET PET was highest for CTV (T/N 2.0), with a value of 0.7. In a comparison of pixel values of MRI and PET, the correlation coefficient for cases with higher JI was significantly greater than that for lower JI cases (0.37 vs. 0.20, P = 0.007). D50% of the brain in RT planning using each CTV differed significantly (P = 0.03) and that using CTV (T/N 1.3) were higher than with use of CTV (Gd). V90% and V95% for each CTV differed in a simulation study for actual treatment using CTV (Gd) (P = 1.0 × 10-7 and 3.0 × 10-9, respectively) and those using CTV (T/N 1.3) and CTV (P-E) were lower than with CTV (Gd). CONCLUSIONS: The region of 11C-MET accumulation is not necessarily consistent with and larger than the Gd-enhanced region. A change of the tumor boundary using 11C-MET PET can cause significant changes in doses to the brain and the CTV.
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Neoplasias Encefálicas , Glioma , Humanos , Metionina , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/radioterapia , Neoplasias Encefálicas/patologia , Glioma/diagnóstico por imagem , Glioma/radioterapia , Glioma/patologia , Tomografia por Emissão de Pósitrons/métodos , Racemetionina , Imageamento por Ressonância Magnética/métodosRESUMO
BACKGROUND: Uncertainties in radiotherapy cause deviation from the planned dose distribution and may result in delivering a treatment that fails to meet clinical objectives. The impact of uncertainties is unique to the patient anatomy and the needle locations in HDR prostate brachytherapy. Evaluating this impact during treatment planning is not common practice, relying on margins around the target or organs-at-risk to account for uncertainties. PURPOSE: A robust evaluation framework for HDR prostate brachytherapy treatment plans was evaluated on 49 patient plans, measuring the range of possible dosimetric outcomes to the patient due to 14 major uncertainties. METHODS: Patient plans were evaluated for their robustness to uncertainties by simulating probable uncertainty scenarios. Five-thousand probabilistic and 1943 worst-case scenarios per patient were simulated by changing the position and size of structures and length of dwell times from their nominal values. For each uncertainty scenario, the prostate D90 and maximum doses to the urethra, D0.01cc , and rectum, D0.1cc , were calculated. RESULTS: The D90 was an average 1.16 ± 0.51% (mean ± SD) below nominal values for the probabilistic scenarios; the D0.01cc metric was 2.24 ± 0.90% higher; and D0.1cc was greater by 0.48 ± 0.30%. The D0.01cc and D90 metrics were more sensitive to uncertainties than D0.1cc , with a median of 79.0% and 84.9% of probabilistic scenarios passing the constraints, compared to 96.5%. The median pass-rate for scenarios that passed all three metrics simultaneously was 63.4%. CONCLUSIONS: Assessing treatment plan robustness improves plan quality assurance, is achievable in less than 1-min, and identifies treatment plans with poor robustness, allowing re-optimization before delivery.
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Braquiterapia , Neoplasias da Próstata , Masculino , Humanos , Próstata , Incerteza , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador , Neoplasias da Próstata/radioterapiaRESUMO
Objective:To investigate the effects of temozolomide combined with γ-fractional stereotactic radiotherapy on the expression of S100B and exosomal microRNA-330(miR-330) in the treatment of non-small cell lung cancer (NSCLC) patients with brain metastases.Methods:A total of 82 patients with NSCLC brain metastases from February 2018 to October 2020 were selected prospectively, and they were divided into the control group and the observation group by the random number table method, each with 41 patients. The control group received γ-fractional stereotactic radiotherapy, and the observation group received temozolomide on the basis of the control group. The therapeutic efficacy and prognosis of the two groups were compared, and the levels of serum myelin basic protein (MBP), neuron-specific enolase (NSE), glial fibrillary acidic protein (GFAP) levels, liver and kidney function indexes, serum S100B, carcinoembryonic antigen (CEA), exosomal miR-330 were compared between the two groups before and after the treatment. The neurologic function of the patients were evaluated by Mini Mental State Examination (MMSE) and National Institutes Health Stroke Scale (NIHSS).Results:The total remission rate in the observation group was higher than that in the control group: 65.85%(27/41) vs. 34.15%(14/41), there was statistical differences ( χ2 = 8.24, P<0.05), but the disease control rate between the two groups had no significant difference ( P>0.05). After the treatment, the levels of serum MBP, GFAP and NSE in the observation group were lower than those in the control group: (10.13 ± 2.07) μg/L vs. (14.39 ± 2.58) μg/L, (0.57 ± 0.12) μg/L vs. (0.75 ± 0.16) μg/L, (5.09 ± 1.16) μg/L vs. (7.17 ± 1.35) μg/L, there were statistical differences ( P<0.05). The levels alanine aminotransferase, blood urea nitrogen and serum creatinine after treatment between the two groups had no significant differences ( P>0.05). After the treatment, the NIHSS scores in the observation group was lower than that in the control group, MMSE scores was higher than that in the control group: (4.16 ± 0.52) scores vs. (4.73 ± 0.44) scores, (22.07 ± 2.51) scores vs. (20.68 ± 2.19) scores, there were statistical differences ( P<0.05). After treatment, the serum levels of S100B and CEA in the observation group were lower than those in the control group, and the expression of exosomal miR-330 was higher than that in the control group: (62.37 ± 10.54) mg/L vs. (68.05 ± 9.39) mg/L, (12.61 ± 2.05) μg/L vs.(14.08 ± 1.97) μg/L, 0.49 ± 0.12 vs. 0.42 ± 0.05, there were statistical differences ( P<0.05). The median survival time in the observation group was 14.6 months, while that in the control group was 11.50 months. There were no significant differences in the incidence of adverse reactions between the two groups ( P>0.05). Conclusions:Treatment with temozolomide combined with γ-fractional stereotactic radiotherapy for NSCLC patients with brain metastases can improve the therapeutic efficacy, neurological function, inhibit the expression of serum S100B, CEA and exosomal miR-330, and prolong the survival time of patients.
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Purpose To evaluate the quality of fully automated stereotactic body radiation therapy (SBRT) planning based on volumetric modulated arc therapy, which can reduce the reliance on historical plans and the experience of dosimetrists. Methods Fully automated re-planning was performed on twenty liver cancer patients, automated plans based on automated SBRT planning (ASP) program and manual plans were conducted and compared. One patient was randomly selected and evaluate the repeatability of ASP, ten automated and ten manual SBRT plans were generated based on the same initial optimization objectives. Then, ten SBRT plans were generated for another selected randomly patient with different initial optimization objectives to assess the reproducibility. All plans were clinically evaluated in a double-blinded manner by five experienced radiation oncologists. Results Fully automated plans provided similar planning target volume dose coverage and statistically better organ at risk sparing compared to the manual plans. Notably, automated plans achieved significant dose reduction in spinal cord, stomach, kidney, duodenum, and colon, with a median dose of D2% reduction ranging from 0.64 to 2.85 Gy. R50% and Dmean of ten rings for automated plans were significantly lower than those of manual plans. The average planning time for automated and manual plans was 59.8 ± 7.9 min vs. 127.1 ± 16.8 min (− 67.3 min). Conclusion Automated planning for SBRT, without relying on historical data, can generate comparable or even better plan quality for liver cancer compared with manual planning, along with better reproducibility, and less clinically planning time (AU)
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Humanos , Neoplasias Hepáticas/radioterapia , Neoplasias Hepáticas/cirurgia , Radiocirurgia , Radioterapia de Intensidade Modulada , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador , Reprodutibilidade dos TestesRESUMO
[This corrects the article DOI: 10.3389/fonc.2022.879167.].
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PURPOSE: Development of a novel interactive visualization approach for the exploration of radiotherapy treatment plans with a focus on overlap volumes with the aim of healthy tissue sparing. METHODS: We propose a visualization approach to include overlap volumes in the radiotherapy treatment plan evaluation process. Quantitative properties can be interactively explored to identify critical regions and used to steer the visualization for a detailed inspection of candidates. We evaluated our approach with a user study covering the individual visualizations and their interactions regarding helpfulness, comprehensibility, intuitiveness, decision-making and speed. RESULTS: A user study with three domain experts was conducted using our software and evaluating five data sets each representing a different type of cancer and location by performing a set of tasks and filling out a questionnaire. The results show that the visualizations and interactions help to identify and evaluate overlap volumes according to their physical and dose properties. Furthermore, the task of finding dose hot spots can also benefit from our approach. CONCLUSIONS: The results indicate the potential to enhance the current treatment plan evaluation process in terms of healthy tissue sparing.
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Background and purpose: Magnetic Resonance Imaging (MRI)-only planning workflows offer many advantages but raises challenges regarding image guidance. The study aimed to assess the viability of MRI to Cone Beam Computed Tomography (CBCT) based image guidance for MRI-only planning treatment workflows. Materials and methods: An MRI matching training package was developed. Ten radiation therapists, with a range of clinical image guidance experience and experience with MRI, completed the training package prior to matching assessment. The matching assessment was performed on four match regions: prostate gold seed, prostate soft tissue, rectum/anal canal and gynaecological. Each match region consisted of five patients, with three CBCTs per patient, resulting in fifteen CBCTs for each match region. The ten radiation therapists performed the CBCT image matching to CT and to MRI for all regions and recorded the match values. Results: The median inter-observer variation for MRI-CBCT matching and CT-CBCT matching for all regions were within 2 mm and 1 degree. There was no statistically significant association in the inter-observer variation in mean match values and radiation therapist image guidance experience levels. There was no statistically significant association in inter-observer variation in mean match values for MRI experience levels for prostate soft tissue and gynaecological match regions, while there was a statistically significant difference for prostate gold seed and rectum match regions. Conclusion: The results of this study support the concept that with focussed training, an MRI to CBCT image guidance approach can be successfully implemented in a clinical planning workflow.
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Background and purpose: Radiotherapy (RT) treatment planning is as a standard based on a computed tomography (CT) scan obtained at the planning stage (pCT), while most of the decisions whether to treat by RT are based on diagnostic CT scans (dCT). Bone metastases (BM) are the most common palliative RT target. The objective of this study was to investigate if a palliative RT treatment plan of BMs could be made based on a dCT with sufficient accuracy and safety, without sacrificing any treatment quality. Materials and methods: A retrospective study with 60 BMs of 8 anatomical sites was performed. RT planning was performed using intensity-modulated radiation therapy/volumetric modulated arc therapy techniques in dCT and transferred to pCT. The dose of clinical target volumes (CTVs), D(CTVV95%, V50%), were compared between plans for dCT and pCT. Patient setup was investigated in cone-beam CT scans. Results: The differences of D(CTVV95%, V50%) between dCT and pCT plans were the lowest in the pelvis (1.0%, 1.1%), lumbar spine (0.6%, 0.7%) and thoracic spine (0.7%, 2.1%), while the differences were higher in cervical spine (3.7%, 1.9%), long bones (2.3%, 0.8%), and costae (1.6%, 1.4%). The patient set-up was acceptable for 100% of the pelvic and lumbar, for 92% of thoracic spine cases, and for <80% of cases in other sites. Conclusion: This study showed the feasibility of using dCT images in palliative RT planning of BMs in thoracic, lumbar spine and pelvic sites, indicating the potential suitability of this strategy for clinical use.
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Radiotherapy is one of the leading treatments for cancer. To accelerate the implementation of radiotherapy in clinic, various deep learning-based methods have been developed for automatic dose prediction. However, the effectiveness of these methods heavily relies on the availability of a substantial amount of data with labels, i.e. the dose distribution maps, which cost dosimetrists considerable time and effort to acquire. For cancers of low-incidence, such as cervical cancer, it is often a luxury to collect an adequate amount of labeled data to train a well-performing deep learning (DL) model. To mitigate this problem, in this paper, we resort to the unsupervised domain adaptation (UDA) strategy to achieve accurate dose prediction for cervical cancer (target domain) by leveraging the well-labeled high-incidence rectal cancer (source domain). Specifically, we introduce the cross-attention mechanism to learn the domain-invariant features and develop a cross-attention transformer-based encoder to align the two different cancer domains. Meanwhile, to preserve the target-specific knowledge, we employ multiple domain classifiers to enforce the network to extract more discriminative target features. In addition, we employ two independent convolutional neural network (CNN) decoders to compensate for the lack of spatial inductive bias in the pure transformer and generate accurate dose maps for both domains. Furthermore, to enhance the performance, two additional losses, i.e. a knowledge distillation loss (KDL) and a domain classification loss (DCL), are incorporated to transfer the domain-invariant features while preserving domain-specific information. Experimental results on a rectal cancer dataset and a cervical cancer dataset have demonstrated that our method achieves the best quantitative results with [Formula: see text], [Formula: see text], and HI of 1.446, 1.231, and 0.082, respectively, and outperforms other methods in terms of qualitative assessment.