Radiotherapy Planning Research Articles

Optimising PTV margins in oesophageal cancer radiotherapy: Amodern radiotherapy planning, treatment delivery and verification approach - A single institutional analysis.

Radiotherapy plays a key role in the multidisciplinary management of oesophageal cancers across neoadjuvant, definitive and palliative settings. Improved precision in radiotherapy planning and delivery techniques have allowed treating disease with tighter margins reducing toxicity. In this study, we examine the appropriateness of current practice in defining the planning target volume (PTV). This is a single institutional retrospective study of patients who received radiotherapy for oesophageal cancers using volumetric modulated arc therapy (VMAT) during 2020. All cone-beam computerised tomography (CBCT) scans were reviewed to assess whether PTV expansions appropriately accounted for tumour motion and interfractional variation. Of the 27 patients, 2 (7%), 5 (19%) and 20 (74%) had cervical, thoracic and distal/gastro-oesophageal junction (GOJ) disease, respectively. 16 (59%) had adenocarcinoma and 9 (33%) had squamous cell carcinoma. 9 of 20 distal/GOJ patients were planned and treated according to the institutional stomach filling protocol. 521/528 (98.7%) CBCTs demonstrated adequate target coverage. Cervical, thoracic and GOJ regions demonstrated adequate target coverage in 57/58, 96/97 and 368/373 CBCTs with median PTV expansions of 5, 7 and 7 mm, respectively. In four patients with GOJ disease, CBCT review identified five episodes where the target volume was insufficiently covered during the treatment course. In this single institutional retrospective study, for the vast majority of patients, our institutional practice of defining PTV margins achieved satisfactory target treatment. The interfractional variations observed in patients with GOJ tumours due to target motion and variable gastric volume, highlights the role of further refinements to motion management techniques in this cohort.

Dual convolution-transformer UNet (DCT-UNet) for organs at risk and clinical target volume segmentation in MRI for cervical cancer brachytherapy

Objective. MRI is the standard imaging modality for high-dose-rate brachytherapy of cervical cancer. Precise contouring of organs at risk (OARs) and high-risk clinical target volume (HR-CTV) from MRI is a crucial step for radiotherapy planning and treatment. However, conventional manual contouring has limitations in terms of accuracy as well as procedural time. To overcome these, we propose a deep learning approach to automatically segment OARs (bladder, rectum, and sigmoid colon) and HR-CTV from female pelvic MRI.Approach. In the proposed pipeline, a coarse multi-organ segmentation model first segments all structures, from which a region of interest is computed for each structure. Then, each organ is segmented using an organ-specific fine segmentation model separately trained for each organ. To account for variable sizes of HR-CTV, a size-adaptive multi-model approach was employed. For coarse and fine segmentations, we designed a dual convolution-transformer UNet (DCT-UNet) which uses dual-path encoder consisting of convolution and transformer blocks. To evaluate our model, OAR segmentations were compared to the clinical contours drawn by the attending radiation oncologist. For HR-CTV, four sets of contours (clinical + three additional sets) were obtained to produce a consensus ground truth as well as for inter/intra-observer variability analysis.Main results. DCT-UNet achieved dice similarity coefficient (mean ± SD) of 0.932 ± 0.032 (bladder), 0.786 ± 0.090 (rectum), 0.663 ± 0.180 (sigmoid colon), and 0.741 ± 0.076 (HR-CTV), outperforming other state-of-the-art models. Notably, the size-adaptive multi-model significantly improved HR-CTV segmentation compared to a single-model. Furthermore, significant inter/intra-observer variability was observed, and our model showed comparable performance to all observers. Computation time for the entire pipeline per subject was 12.59 ± 0.79 s, which is significantly shorter than the typical manual contouring time of >15 min.Significance. These experimental results demonstrate that our model has great utility in cervical cancer brachytherapy by enabling fast and accurate automatic segmentation, and has potential in improving consistency in contouring. DCT-UNet source code is available athttps://github.com/JHU-MICA/DCT-UNet.

Transformer-Integrated Hybrid Convolutional Neural Network for Dose Prediction in Nasopharyngeal Carcinoma Radiotherapy.

Radiotherapy is recognized as the major treatment of nasopharyngeal carcinoma. Rapid and accurate dose prediction can improve the efficiency of the treatment planning process and the quality of radiotherapy plans. Currently, deep learning-based methods have been widely applied to dose prediction for radiotherapy treatment planning. However, it is important to note that existing models based on Convolutional Neural Networks (CNN) often overlook long-distance information. Although some studies try to use Transformer to solve the problem, it lacks the ability of CNN to process the spatial information inherent in images. Therefore, we propose a novel CNN and Transformer hybrid dose prediction model. To enhance the transmission ability of features between CNN and Transformer, we design a hierarchical dense recurrent encoder with a channel attention mechanism. Additionally, we propose a progressive decoder that preserves richer texture information through layer-wise reconstruction of high-dimensional feature maps. The proposed model also introduces object-driven skip connections, which facilitate the flow of information between the encoder and decoder. Experiments are conducted on in-house datasets, and the results show that the proposed model is superior to baseline methods in most dosimetric criteria. In addition, the image analysis metrics including PSNR, SSIM, and NRMSE demonstrate that the proposed model is consistent with ground truth and produces promising visual effects compared to other advanced methods. The proposed method could be taken as a powerful clinical guidance tool for physicists, significantly enhancing the efficiency of radiotherapy planning. The source code is available at https://github.com/CDUTJ102/THCN-Net .

89Zr]Zr-PSMA-617 PET/CT in a Patient with Biochemical Recurrence of Prostate Cancer and Prior Indetermined Findings on [18F]PSMA-1007 Imaging.

We report a case of a 79-year-old male patient with a history of radical prostatectomy for prostate cancer. The patient presented with biochemical reoccurrence; however, previous conventional PSMA PET/CT using [18F]PSMA-1007 showed two indetermined findings with low uptake in the right iliac lymph nodes. Further MRI evaluation provided no additional information. A recently introduced PSMA tracer, [89Zr]Zr-PSMA-617 (half-life: 3.3 days), was administered in an attempt to confirm the diagnosis and aid in potential radiation planning. [89Zr]Zr-PSMA-617 PET/CT clearly revealed the previously indetermined right iliac lymph nodes as definitely metastatic and also identified additional lymph node metastases that were undetected in prior scans. This case highlights the potential superior sensitivity of [89Zr]Zr-PSMA-617 PET/CT in detecting recurrent disease, especially in unclear settings of [18F]PSMA-1007 PET/CT and demonstrates its potential for guiding targeted radiation therapy with curative intent.

P13.01.A 11C-METHIONIN PET FOR RADIOTHERAPY TREATMENT PLANNING IN PATIENTS WITH RAPID EARLY PROGRESSION AFTER GLIOBLASTOMA SURGERY: PROSPECTIVE PHASE II TRIAL

Abstract BACKGROUND Radiotherapy (RT) is a standard treatment for nearly all glioblastoma patients following initial surgery. Few retrospective studies indicate negative prognostic instances of progression during the planning magnetic resonance (MR) (up to 1 week before initiating RT), termed Rapid Early Progression (REP). The optimal RT management for REP patients remains uncertain. The objective of this prospective phase II trial (NCT05608395) is to assess impact of 11C-Methionine PET used for RT planning in REP glioblastoma patients. It is one of the first prospective clinical interventional trials focused on this specific cohort of patients. MATERIAL AND METHODS We enrolled glioblastoma, IDHwt, or Astrocytoma, IDHmt, WHO grade IV patients, who developed REP characterized by 1) increase in postoperative residuum by ≥ 25%, 2) appearance of new contras enhancing lesion, 3) unequivocal progression of the unresected satelite. Patients received treatment based on the Stupp or Perry protocol. Treatment response was evaluated using RANO criteria. RT target volumes were delineated as follows: Gross tumor volume included tumor cavity, enhancing lesion and 11C-MET PET (1.3 tumor-to-background ratio). The clinical target volume was GTV plus a modified 2cm margin reflecting surrounding organs at risk. Volumetric analyses of different radiotherapy target volume were performed using EclipseTM software including patterns of failure. RESULTS During 12/2020 - 12/2023, total of 31 patients were enrolled (16 treated via abbreviated RT course); median age 60 years, ECOG 0-1 in 28 patients, median follow up 20 months. No effect of 11C-MET PET - based radiotherapy treatment planning of GBM patients with REP was observed on PFS (median 3.4 months comparing to 4.9 in historical control cohort) and OS (12.3 months comparing to 15.7 months). Median MET volume was 7.3cm3 (43% of MRI volume), MET avidity was presented in 7 patients et least 1cm beyond MRI volume. Central recurrence was presented in 87% patients. CONCLUSION The optimal treatment of patients with REP is unknown and needs to be studied in more details including dose escalation studies with reduced target margins potentialy directed also by aminoacid PET examination. Adjustment of target radiotherapy volumes using 11C-MET PET did not lead to improved PFS or OS. Supported by NU20-03-00148.

Optimization of image reconstruction technique for respiratory-gated lung stereotactic body radiotherapy treatment planning using four-dimensional CT: a phantom study.

Patient respiration is characterized by respiratory parameters, such as cycle, amplitude, and baseline drift. In treatment planning using four-dimensional computed tomography (4DCT) images, the target dose may be affected by variations in image reconstruction techniques and respiratory parameters. This study aimed to optimize 4DCT image reconstruction techniques for the treatment planning of lung stereotactic body radiotherapy (SBRT) based on respiratory parameters using respiratory motion phantom. We quantified respiratory parameters using 30 respiratory motion datasets. The 4DCT images were acquired, and the phase- and amplitude-based reconstruction images (RI) were created. The target dose was calculated based on these reconstructed images. Statistical analysis was performed using Pearson's correlation coefficient (r) to determine the relationship between respiratory parameters and target dose in each reconstructed technique and respiratory region. In the inhalation region of phase-based RI, r of the target dose and baseline drift was -0.52. In particular, the target dose was significantly reduced for respiratory parameters with a baseline drift of 0.8mm/s and above. No other respiratory parameters or respiratory regions were significantly correlated with target dose in phase-based RI. In amplitude-based RI, there were no significant differences in the correlation between all respiratory parameters and target dose in the exhalation or inhalation regions. These results showed that the target dose of the amplitude-based RI did not depend on changes in respiratory parameters or respiratory regions, compared to the phase-based RI. However, it is possible to guarantee the target dose by considering respiratory parameters during the inhalation region of the phase-based RI.

MODELLING GBM RECURRENCE: THE INflUENCE OF PERI-LESIONAL OEDEMA AND THE DISCONNECTOME

Abstract AIMS Residual tumour burden after surgery in GBM patients is a prognostic imaging biomarker, often involving the area of T2 signal elevation surrounding the tumour core, histopathologically representing infiltrative oedema with tumour cells. We present the first stage of a model to improve the prediction GBM recurrence by specifically investigating the peri-lesional oedema compartment. METHOD UK-wide sample of histologically proven IDHwt GBMs with MRIs at the time of diagnosis underwent state-of- the-art in-house tumour segmentation pipeline and radiomic feature extraction of whole-tumour, enhancing, non-enhancing and oedema components, and masked disconnectome map components. Of these, early GBM recurrence, within 6 months after completion of radiotherapy, was curated and distribution mapped across the brain. RESULTS 1464 patients were identified: male = 901, median age 63 years, average overall survival 597 days. The radiomic features: Compactness 1 and 2, Surface Area, Spherical Disproportion, Sphericity, and Maximum 2D Diameter column of the disconnectome-related perilesional oedema compartment were most predictive of survival outcome (p value <0.01). Of these, 47 patients with average overall survival 357 days and average time from end of radiotherapy to progression of 131 days were identified. CONCLUSION Our early results reveal the relationship between perilesional oedema MRI features and survival, with disconnectome-related perilesional oedema features most predictive. This suggests that extended brain network aberrations caused by gliomas may also influence tumour recurrence. Further work will focus on the development of more robust predictive models of tumour recurrence that have potential for significant impact on surgical and radiotherapy planning.

AUDIT TO EVALUATE CURRENT RADIOTHERAPY (RT) PLANNING PATHWAY: COULD CURRENT PRACTICE BE IMPROVED BY THE TIMING OF MAGNETIC RESONANCE IMAGING (MRI)?

Abstract AIMS To evaluate the current guidance for glioblastoma (GBM) and primary brain radiotherapy (RT) planning. Current practice in this centre utilises pre and post-surgical MRI for RT target delineation. This study aims to explore the practicality and impact of scheduling an RT planning-specific MRI no more than 2 weeks before RT treatment start date (TSD). Time from surgery to RT TSD will also be explored. METHOD Fifty GBM patients, treated between August 2022 and October 2023, were audited retrospectively. Included patients were treated with radical intent and must have had surgery or biopsy. Age, gender or performance status (PS) were excluded from audit criteria. Age of MRI used for RT planning and surgery to TSD was noted. RESULTS Early results showed that the average age of MRI used for RT planning was 7 weeks old and Surgery to TSD was 7 weeks. A new pathway was introduced after 37 patients as these results were considered unacceptable. The new pathway included 1 reserved MRI appointment and one reserved RT Mask/CT appointment per week. 13 patients’ pathways were audited after introduction of the new pathway. The results showed that the average age of MRI used for RT planning was 2 weeks old and surgery to TSD was 6 weeks. CONCLUSION Limitations of the audit included disparity between number of patients before and after introduction of the new pathway. This was because of the time limitation for completion of the study. Improvement was seen in timing of MRI to TSD. However, the small improvement in timing of surgery to TSD was impacted by human factors rather than organisational influence, for example, surgical deconditioning, delays for wound healing and patient choice. This study has shown that the ideal timing of MRI can be achieved.

ANALYSING THE RATE OF RECURRENCE AND LEPTOMENINGEAL DISEASE IN POSTERIOR FOSSA BRAIN METASTASES FOLLOWING POSTOPERATIVE RADIOTHERAPY- SINGLE CENTRE EXPERIENCE

Abstract AIMS The management of posterior fossa brain metastases is complex and necessitates a multidisciplinary approach involving neurosurgeons and oncologists. Post-operative radiotherapy (PORT) to surgical cavity has demonstrated positive oncologic outcomes as well as preserving cognitive function when compared to conventional whole brain radiation therapy. However, larger post-operative volumes in posterior fossa and greater target volume uncertainty due to presence of pseudomeningocele may result in an increased risk of local recurrence (LR) and leptomeningeal disease (LMD). The aim of this retrospective single centre study was to determine the rates of LR and LMD in patients with posterior fossa metastases who underwent PORT to surgical cavity. METHOD Retrospective analysis of data of patient who underwent PORT in between 2017-2022, for posterior fossa brain metastases at our centre. Clinical, imaging and radiotherapy data was collected from electronic medical records. Statistical analysis was performed using SPSS Statistics version 28.0.1. RESULTS We identified 42 patients meeting the study criteria. The median age of the patients was 60.5 years. 71.4% of patients were females, while 28.6% were males. 52.4% of patients had pseudomeningocoele on their radiotherapy planning scans. The median time gap between the date of surgery and initiation of radiotherapy was 34.5 days. 20 out of 42 (47.6%) patients had local recurrence of a posterior fossa brain metastasis and 7 out of 42 (16.7%) patients developed LMD. Out of 7 patients with LMD, 4 patients had pseudomeningocoele present at the time of PORT. The timing of radiotherapy after surgery (≤4 weeks or >4 weeks) showed no statistically significant impact on LR (p-value: 0.413, log-rank test). CONCLUSION The risk of LR remains high despite PORT. This study highlights the challenges in management of posterior fossa metastases. High LR and LMD rates underscore the need for improved treatment strategies.

Uninvolved liver dose prediction in stereotactic body radiation therapy for liver cancer based on the neural network method.

The quality of a radiotherapy plan often depends on the knowledge and expertise of the plan designers. To predict the uninvolved liver dose in stereotactic body radiotherapy (SBRT) for liver cancer using a neural network-based method. A total of 114 SBRT plans for liver cancer were used to test the neural network method. Sub-organs of the uninvolved liver were automatically generated. Correlations between the volume of each sub-organ, uninvolved liver dose, and neural network prediction model were established using MATLAB. Of the cases, 70% were selected as the training set, 15% as the validation set, and 15% as the test set. The regression R-value and mean square error (MSE) were used to evaluate the model. The volume of the uninvolved liver was related to the volume of the corresponding sub-organs. For all sets of R-values of the prediction model, except for Dn0 which was 0.7513, all R-values of Dn10-Dn100 and Dnmean were > 0.8. The MSE of the prediction model was also low. We developed a neural network-based method to predict the uninvolved liver dose in SBRT for liver cancer. It is simple and easy to use and warrants further promotion and application.

Experimental Assessment of Magnetic Resonance Imaging Distortion for Radiation Therapy Planning

MRI is widely used in radiation therapy planning, particularly in stereotactic radiosurgery for brain metastases. The article addresses the geometric distortion of MRI images, which can lead to errors in radiation therapy planning. A series of experiments with a simple phantom were conducted on two MRI scanners with 0.5 T and 1.5 T magnetic fields. Deviations in the positions of the phantom objects from their actual locations were observed. The detected deviations can reach up to 5 mm. A theoretical dependence of the magnetic field gradient on the distance to the center of homogeneity was calculated, which agrees well with the approximation of experimental data. An assessment was made of the dependence of the image area distortion of objects located at the center of the field homogeneity on their actual sizes. It was found that the area deviation can reach up to 20%.

Current situation and trends of radiation therapy in Japan based on the National Database Open Data.

This study aimed to visualize the current situation and trends in radiation therapy in Japan using open data from the Japanese National Database of Health Insurance Claims and Specific Health Checkups (NDB). We downloaded the NDB open data from the website of Japan's Ministry of Health, Labor and Welfare and used Python libraries to analyze the receipt data related to radiation therapy from fiscal year 2014 to 2022. The number of radiation therapy plans peaked in 2019, temporarily declined and subsequently showed a gradual increase. Conversely, the total points associated with radiation therapy have consistently increased without any decline. The use of high-precision radiation therapies such as intensity-modulated radiation therapy (IMRT) has increased over time. Significant regional differences exist, with the Chubu and Kyushu regions showing higher total points and receipts per certified radiation oncologist. A correlation was observed between the number of IMRT plans per population and the number of certified radiation oncologists. Males exhibited a sharp peak in their early 70s, while females demonstrated a mild peak from their 40s to 80s. In recent years, the points for males in their early 70s have rapidly increased. We used the NDB open data to illustrate the current situation and trends in radiation therapy in Japan, highlighting reduced costs and workloads. This study underscored the regional differences in radiation therapy and emphasized the need to discuss strategies for meeting future demand.

Effects of Inc parameter on quality of VMAT radiotherapy plans for right breast cancer based on dosimetric study.

This study aimed to investigate the influence of gantry angle increment (Inc) parameters on the Monaco treatment planning system for volumetric modulated arc therapy (VMAT) in right breast cancer, and to determine the optimal Inc parameters. Twenty-three patients with right breast cancer at the Sir Run Run Shaw Hospital from August 2022 to August 2023 were retrospectively selected. Four VMAT plans were generated for each patient incorporating Inc of 10°, 20° (control group), 30°, and 40°, while the other optimization parameters and constraint functions remained constant. The D98 and conformity index were lower in the Inc30 and Inc40 groups than in the Inc20 group. As Inc increased from 10° to 30°, the irradiated dose to the ipsilateral lung, including the V20, V5, and Dmax, mean dose, gradually increased. There were no statistically significant differences in the irradiated dose to the contralateral breast, contralateral lung, heart, esophagus, and brachial plexus. The number of monitor units and control points decreased with increasing Inc. Smaller Inc values can achieve higher target coverage and lower irradiated dose to the ipsilateral lung, but will reduce delivery efficiency. Considering the plan quality and delivery efficiency, an Inc of 10° or 20° is recommended for right breast cancer VMAT plans.

Development of an EGSnrc multi-leaf collimator component module and treatment head model for a low-field MRI linear accelerator.

Monte Carlo (MC) modeling of MR-guided radiotherapy (MRgRT) treatment machines enables the characterization of photon/electron interactions in the presence of a magnetic field. The EGSnrc MC code system is a well-established system for radiation dose calculations. The multi-leaf collimator (MLC) component modules presently available within the EGSnrc MC code system do not include a model of the double-focused MLC available on a low-field (0.35T) MRI linear accelerator (MR linac). Here we developed and validated a new component module (CM) for the low-field MRgRT MLC using the EGSnrc/BEAMnrc/DOSXYZnrc code system. We performed detailed modeling of the treatment head and validated the model using measurements and calculations from the vendor-specific treatment planning system (TPS). The detailed geometry of the low-field MR linac MLC and other treatment head structures were modeled using BEAMnrc. Comparisons of DOSXYZnrc simulated dose against measurements and the low-field MR linac TPS for a variety of AAPM TG-53 task group report suggested square and shaped fields, as well as a step-and-shoot intensity-modulated radiotherapy (IMRT) plan, are presented. Our model agrees with both measured and TPS calculated data on average within 2%/2mm (dose/DTA) criterion for square field profiles. Output factors agreed within 1% for field sizes down to 2.49×2.49cm2 and within 2% of TPS data for the smallest field size of 0.83×0.83cm2. Shaped field and IMRT MC calculations agreed with measured and TPS data such that the gamma pass rates (3%/2mm) were 99.5% and (3%/3mm) 96.2%, respectively. We developed and validated an MLC CM (SYNCVRMLC) for the low-field MR linac using the EGSnrc MC code systems. This new CM will facilitate MC computation of fluence and dose distributions using BEAMnrc/DOSXYZnrc for patients treated on the low-field MR linac.

Adjuvant Radiotherapy in Bladder Cancers: A Dosimetric Study Focusing on Ileal Conduit Sparing

PurposeTo compare ileal conduit (IC) and other organ at risk (OAR) dosimetry between treatment techniques in a prospective cohort of patients planned for adjuvant radiotherapy (RT) after radical cystectomy and IC reconstruction. Methods and materialsComputed tomography (CT datasets of twenty patients who underwent adjuvant RT were obtained and used prospectively for delineation of target volumes (primary and nodal) and OARs, including IC, uretero-ileal anastomosis and ileal stoma using a specified protocol for simulation including a delayed CT to identify IC. Three RT plans were generated for each patient for a dose of 54 gray (Gy) in 27 fractions (PTV V95% >95%): 3-dimensional conformal radiotherapy (3DCRT) with (3DCRT_S) and without (3DCRT_N) stoma shielding, and volumetric modulated arc therapy (VMAT), with OAR constraints specified for VMAT plans (IC: Dmax<54Gy, V50Gy < 20 cc). Constraints were given for other pelvic OARs (bowel, rectum, femur heads) as per published literature. Plans were evaluated for target coverage as well as OAR doses; in particular, IC and ileal stoma). ANOVA test was used to compare medians of achieved doses, and a p-value <0.05 was statistically significant. ResultsThe median IC volume was 63.34 (55.29–82.93) cc. The cranial end of IC was at L5 or L4 vertebral level in 95% of patients and caudal level at S2 or S3 in 80% of patients. In contrast, the ileal stoma spanned from L4 or L5 vertebral level cranially (100%) to L5 level caudally (80%). PTV V95% was similar for 3DCRT_N and VMAT plans while it was significantly lower for 3DCRT_S in areas of ileal stoma shielding (99.95% vs 99.01% vs 96.29%, p < 0.01). Median IC V50Gy was comparable in 3DCRT_N (38.81 cc) and 3DCRT_S (35.62 cc) while it was significantly lower in the VMAT plan (17.05 cc, p < 0.01). IC Dmax did not differ significantly between the three plans. On the other hand, when 3DCRT_N, 3DCRT_S, and VMAT plans were compared for ileal stoma doses, Dmean was comparable (11.93 Gy vs 7.41 Gy vs 9.54 Gy, p = 0.06) while Dmax was significantly higher for 3DCRT_N plan and least for VMAT plan (35.32 Gy vs 27.57 Gy vs 24.22 Gy, p < 0.01). VMAT plans fared significantly better than both 3DCRT plans for uretero-ileal anastomosis, bowel, and rectal dosimetry. ConclusionsIleal stoma shielding in 3DCRT compromises PTV coverage but does not spare IC effectively. Sparing IC with VMAT is feasible without compromising PTV coverage. Dosimetric gains with VMAT are expected to benefit patients needing higher pelvic RT doses and nodal RT by reducing the risk of anastomotic and mucosal complications. Clinical benefits should be evaluated in a prospective protocol.

Effect of replanning boost radiotherapy plan in locally advanced unresectable middle to lower thoracic esophageal cancer

Thoracic bulky esophageal cancer shrinks during radiotherapy, changing the location and shape of the surrounding heart and lungs. The current study aimed to explore how replanning by volumetric-modulated arc radiotherapy (VMAT) and three-dimensional conformal radiotherapy (3DCRT) influences the target coverage and dose to organs at risk in locally advanced unresectable middle to lower thoracic esophageal cancer. We retrospectively collected CT simulation images of initial and boost radiotherapy plans for locally advanced unresectable thoracic esophageal cancer in 17 consecutive patients. First, we created boost plans of 20 Gy using 3DCRT and VMAT on the initially acquired CT images. Second, we replicated the process on CT images acquired after 20–40 Gy of radiotherapy. We then compared non-replanned boost radiotherapy plans with replanned boost plans. Replanned radiotherapy delivered more conformal doses to the target and reduced heart and lung doses. VMAT reduced more irradiated mean doses to the heart than 3DCRT in the case of replanning (1.7 and 1.1 Gy, p < 0.001). Replanning to accommodate tumor shrinkage during radiotherapy effectively lowers the irradiated doses to the heart and lungs in patients with locally advanced unresectable middle to lower thoracic esophageal cancer, especially those treated with VMAT.

Patterns of intersectional tumor volumes in T2-weighted MRI and [18F]FET PET in adult glioma: a prospective, observational study

Brain tumor volumes as assessed by magnetic resonance imaging (MRI) do not always spatially overlap with biological tumor volumes (BTV) measured by [18F]Fluoroethyltyrosine positron emission tomography ([18F]FET PET). We prospectively investigated volumetric patterns based on the extent of tumor volume overlap between the two modalities. Eighty-six patients with newly diagnosed glioma who had undergone MRI and [18F]FET PET between 2007 and 2009 were included in this prospective study and (re-)classified according to CNS WHO 2021 (Classification of Tumors of the Central Nervous System by the World Health Organization). Four different patterns of volume overlap were defined mathematically according to the extent of overlap between MRI-based T2 tumor volume (non-enhancing tumor volume, nCEV) and BTVs. Progression-free (PFS) and overall survival (OS) were determined. Seventy patients were diagnosed with isocitrate dehydrogenase wildtype (IDHwt) glioblastoma and 16 with IDH-mutant glioma, respectively. The most common pattern was characterized by a larger non-contrast-enhancing tumor volume (nCEV) that enclosed all or most of the BTV and was observed in 46 patients (54%) (pattern 1). This pattern was more frequent in IDH-mutant gliomas than in IDH-wildtype glioblastoma (81% versus 47%, p = 0.02). In multivariate analyses, pattern 1 was associated with prolonged PFS (HR 0.59; 95 CI 0.34-1.0; p = 0.05), but not OS (HR 0.66; 95 CI 0.4–1.08; p = 0.1). For OS, presence of an IDH mutation (p = 0.05) and lower age (p = 0.03) were associated with prolonged OS. The spatial relation between nCEV and BTV varies within and between glioma entities. Most frequently, a larger nCEV encases the BTV. Some patients show spatially dissociated nCEVs and BTVs. Not accounting for this phenomenon in surgery or radiotherapy planning might lead to undertreatment.

Unsupervised machine learning model for detecting anomalous volumetric modulated arc therapy plans for lung cancer patients.

Volumetric modulated arc therapy (VMAT) is a new treatment modality in modern radiotherapy. To ensure the quality of the radiotherapy plan, a physics plan review is routinely conducted by senior clinicians; however, this process is less efficient and less accurate. In this study, a multi-task AutoEncoder (AE) is proposed to automate anomaly detection of VMAT plans for lung cancer patients. The feature maps are first extracted from a VMAT plan. Then, a multi-task AE is trained based on the input of a feature map, and its output is the two targets (beam aperture and prescribed dose). Based on the distribution of reconstruction errors on the training set, a detection threshold value is obtained. For a testing sample, its reconstruction error is calculated using the AE model and compared with the threshold value to determine its classes (anomaly or regular). The proposed multi-task AE model is compared to the other existing AE models, including Vanilla AE, Contractive AE, and Variational AE. The area under the receiver operating characteristic curve (AUC) and the other statistics are used to evaluate the performance of these models. Among the four tested AE models, the proposed multi-task AE model achieves the highest values in AUC (0.964), accuracy (0.821), precision (0.471), and F1 score (0.632), and the lowest value in FPR (0.206). The proposed multi-task AE model using two-dimensional (2D) feature maps can effectively detect anomalies in radiotherapy plans for lung cancer patients. Compared to the other existing AE models, the multi-task AE is more accurate and efficient. The proposed model provides a feasible way to carry out automated anomaly detection of VMAT plans in radiotherapy.

Dosimetric comparison of gamma knife and linear accelerator (VMAT and IMRT) plans of SBRT of Lung tumours

This study evaluates dosimetric differences in Stereotactic Body Radiation Therapy (SBRT) for lung tumors using plans of Gamma Knife, and Volumetric Modulated Arc Therapy (VMAT), Intensity-Modulated Radiation Therapy (IMRT) plans based on Linear Accelerator, aiming to inform the reader of appropriate treatment strategy selection. Ten patients with 23 lung tumor lesions treated with SBRT at Zhongshan Hospital of Dalian University were analyzed. Plans of Gamma Knife, and VMAT, IMRT plans based on Linear Accelerator were created for each lesion, totaling 18 plans per type. Lesions were treated with 30–50 Gy in 5–10 fractions. Dosimetric parameters, including gradient index (GI), heterogeneity index (HI), conformity index (CI), and doses to the plan target volumes (PTVs), the gross tumor volumes (GTVs) and organs at risk (OARs) were compared. Plans of Gamma Knife showed superior HI and GI, higher PTV and GTV doses, and reduced doses to the ipsilateral and contralateral lungs, esophagus, spinal cord, and heart compared to VMAT and IMRT plans (p < 0.05). However, Plans of Gamma Knife required longer delivery times. When comparing VMAT and IMRT plans, VMAT plans had shorter delivery times than IMRT plans, but required more monitor units (MUs). Additionally, IMRT plans delivered a lower mean dose to the ipsilateral lung compared to VMAT plans. Gamma Knife SBRT plans achieves steeper dose falloff and minimizes radiation to normal lung tissue compared to VMAT and IMRT plans, but with longer delivery times. VMAT and IMRT plans displayed similar dose distributions for lung SBRT.

Quantitative spatial visualization of X-ray irradiation via redox reaction by dynamic nuclear polarization magnetic resonance imaging

The dose of X-ray irradiation is commonly measured by point assessment with an ionization chamber dosimeter. However, to achieve spatially accurate delivery of X-ray to avoid the exposure to normal tissues, an accurate imaging method for spatially and quantitatively detecting exposure is required. Herein, we present a novel method to visualize X-ray exposure using low-field dynamic nuclear polarization magnetic resonance imaging (DNP-MRI) with nitroxyl radical tempol as the chemical dosimeter. In this system, gel phantoms containing glutathione (GSH) and the paramagnetic tempol radical were used to monitor the deposited X-ray-irradiation via the redox reaction. The tempol radical level was evaluated by DNP-MRI whose signal intensity was linearly correlated with the radical concentration. The radical level in the presence of GSH decreased in proportion to the dose of X-irradiation deposited. In an imaging experiment simulating clinical radiotherapy, we used a clinical linear accelerator with a radiotherapy planning software to confirm the utility of the exposure imaging. The X-ray exposure and its distribution were clearly visualized on the gel phantom image acquired by DNP-MRI. The results were consistent with those specified in the radiotherapy plan where the intensity of the radiation beam was modulated. This exposure estimation will be useful for determining an accurate irradiation field and reducing off-target exposure in clinical settings.