External Beam Radiotherapy Planning Research Articles

Improvement of accumulated dose distribution in combined cervical cancer radiotherapy with deep learning-based dose prediction.

Difficulties remain in dose optimization and evaluation of cervical cancer radiotherapy that combines external beam radiotherapy (EBRT) and brachytherapy (BT). This study estimates and improves the accumulated dose distribution of EBRT and BT with deep learning-based dose prediction. A total of 30 patients treated with combined cervical cancer radiotherapy were enrolled in this study. The dose distributions of EBRT and BT plans were accumulated using commercial deformable image registration. A ResNet-101-based deep learning model was trained to predict pixel-wise dose distributions. To test the role of the predicted accumulated dose in clinic, each EBRT plan was designed using conventional method and then redesigned referencing the predicted accumulated dose distribution. Bladder and rectum dosimetric parameters and normal tissue complication probability (NTCP) values were calculated and compared between the conventional and redesigned accumulated doses. The redesigned accumulated doses showed a decrease in mean values of V50, V60, and D2cc for the bladder (-3.02%, -1.71%, and -1.19 Gy, respectively) and rectum (-4.82%, -1.97%, and -4.13 Gy, respectively). The mean NTCP values for the bladder and rectum were also decreased by 0.02‰ and 0.98%, respectively. All values had statistically significant differences (p < 0.01), except for the bladder D2cc (p = 0.112). This study realized accumulated dose prediction for combined cervical cancer radiotherapy without knowing the BT dose. The predicted dose served as a reference for EBRT treatment planning, leading to a superior accumulated dose distribution and lower NTCP values.

Assessing the Feasibility of Using Artificial Intelligence–Segmented Dominant Intraprostatic Lesion for Focal Intraprostatic Boost With External Beam Radiation Therapy

The delineation of dominant intraprostatic gross tumor volumes (GTVs) on multiparametric magnetic resonance imaging (mpMRI) can be subject to interobserver variability. We evaluated whether deep learning artificial intelligence (AI)-segmented GTVs can provide a similar degree of intraprostatic boosting with external beam radiation therapy (EBRT) as radiation oncologist (RO)-delineated GTVs. We identified 124 patients who underwent mpMRI followed by EBRT between 2010 and 2013. A reference GTV was delineated by an RO and approved by a board-certified radiologist. We trained an AI algorithm for GTV delineation on 89 patients, and tested the algorithm on 35 patients, each with at least 1 PI-RADS (Prostate Imaging Reporting and Data System) 4 or 5 lesion (46 total lesions). We then asked 5 additional ROs to independently delineate GTVs on the test set. We compared lesion detectability and geometric accuracy of the GTVs from AI and 5 ROs against the reference GTV. Then, we generated EBRT plans (77 Gy prostate) that boosted each observer-specific GTV to 95 Gy. We compared reference GTV dose (D98%) across observers using a mixed-effects model. On a lesion level, AI GTV exhibited a sensitivity of 82.6% and positive predictive value of 86.4%. Respective ranges among the 5 RO GTVs were 84.8% to 95.7% and 95.1% to 100.0%. Among 30 GTVs mutually identified by all observers, no significant differences in Dice coefficient were detected between AI and any of the 5 ROs. Across all patients, only 2 of 5 ROs had a reference GTV D98% that significantly differed from that of AI by 2.56 Gy (P=.02) and 3.20 Gy (P=.003). The presence of false-negative (-5.97 Gy; P < .001) but not false-positive (P=.24) lesions was associated with reference GTV D98%. AI-segmented GTVs demonstrate potential for intraprostatic boosting, although the degree of boosting may be adversely affected by false-negative lesions. Prospective review of AI-segmented GTVs remains essential.

Implementation of a knowledge-based decision support system for treatment plan auditing through automation.

Independent auditing is a necessary component of a comprehensive quality assurance (QA) program and can also be utilized for continuous quality improvement (QI) in various radiotherapy processes. Two senior physicists at our institution have been performing a time intensive manual audit of cross-campus treatment plans annually, with the aim of further standardizing our planning procedures, updating policies and guidelines, and providing training opportunities of all staff members. A knowledge-based automated anomaly-detection algorithm to provide decision support and strengthen our manual retrospective plan auditing process was developed. This standardized and improved the efficiency of the assessment of our external beam radiotherapy (EBRT) treatment planning across all eight campuses of our institution. A total of 843 external beam radiotherapy plans for 721 lung patients from January 2020 to March 2021 were automatically acquired from our clinical treatment planning and management systems. From each plan, 44 parameters were automatically extracted and pre-processed. A knowledge-based anomaly detection algorithm, namely, "isolation forest" (iForest), was then applied to the plan dataset. An anomaly score was determined for each plan using recursive partitioning mechanism. Top 20 plans ranked with the highest anomaly scores for each treatment technique (2D/3D/IMRT/VMAT/SBRT) including auto-populated parameters were used to guide the manual auditing process and validated by two plan auditors. The two auditors verified that 75.6% plans with the highest iForest anomaly scores have similar concerning qualities that may lead to actionable recommendations for our planning procedures and staff training materials. The time to audit a chart was approximately 20.8 min on average when done manually and 14.0 min when done with the iForest guidance. Approximately 6.8 min were saved per chart with the iForest method. For our typical internal audit review of 250 charts annually, the total time savings are approximately 30hr per year. iForest effectively detects anomalous plans and strengthens our cross-campus manual plan auditing procedure by adding decision support and further improve standardization. Due to the use of automation, this method was efficient and will be used to establish a standard plan auditing procedure, which could occur more frequently.

Improving normal tissue sparing using scripting in endometrial cancer radiation therapy planning.

The aim of this study was to improve the protection of organs at risk (OARs), decrease the total planning time and maintain sufficient target doses using scripting endometrial cancer external beam radiation therapy (EBRT) planning. Computed tomography (CT) data of 14 endometrial cancer patients were included in this study. Manual and automatic planning with scripting were performed for each CT. Scripts were created in the RayStation™ (RaySearch Laboratories AB, Stockholm, Sweden) planning system using a Python code. In scripting, seven additional contours were automatically created to reduce the OAR doses. The scripted and manual plans were compared to each other in terms of planning time, dose-volume histogram (DVH) parameters, and total monitor unit (MU) values. While the mean total planning time for manual planning was 368 ± 8s, it was only 55 ± 2s for the automatic planning with scripting (p < 0.001). The mean doses of OARs decreased with automatic planning (p < 0.001). In addition, the maximum doses (D2% and D1%) for bilateral femoral heads and the rectum were significantly reduced. It was observed that the total MU value increased from 1146 ± 126 (manual planning) to 1369 ± 95 (scripted planning). It is concluded that scripted planning has significant time and dosimetric advantages over manual planning for endometrial cancer EBRT planning.

Determining Combined Modality Dosimetric Constraints by Integration of IMRT and LDR Prostate Brachytherapy Dosimetry and Correlation with Toxicity

Intermediate- and high-risk prostate cancer patients undergoing combination external beam radiation therapy (EBRT) and low dose rate (LDR) brachytherapy have demonstrated increased genitourinary (GU) toxicity. We have previously demonstrated a method to combine EBRT and LDR dosimetry. In this work, we use this technique for a sample of patients with intermediate- and high-risk prostate cancer, correlate with clinical toxicity, and suggest preliminary summed organ-at-risk constraints for future investigation. Intensity modulated EBRT and 103Pd-based LDR treatment plans were combined for 138 patients using biological effective dose (BED) and deformable image registration. GU and gastrointestinal (GI) toxicity were compared with combined dosimetry for the urethra, bladder, and rectum. Differences between doses in each toxicity grade were assessed by analysis of variance (α=0.05). Combined dosimetric constraints are proposed using the mean organ-at-risk dose, subtracting 1 standard deviation for a conservative recommendation. The majority of our 138-patient cohort experienced grade 0 to 2 GU or GI toxicity. Six grade 3 toxicities were noted. Mean prostate BED D90 (± 1 standard deviation) was 165.5±11.1 Gy. Mean urethra BED D10 was 230.3±33.9 Gy. Mean bladder BED was 35.2±11.0 Gy. Mean rectum BED D2cc was 85.6±24.3 Gy. Significant dosimetric differences between toxicity grades were found for mean bladder BED, bladder D15, and rectum D50, but differences between individual means were not statistically significant. Given the low incidence of grade 3 GU and GI toxicity, we propose urethra D10 <200 Gy, rectum D2cc <60 Gy, and bladder D15 <45 Gy as preliminary dose constraints for combined modality therapy. We successfully applied our dose integration technique to a sample of patients with intermediate- and high-risk prostate cancer. Incidence of grade 3 toxicity was low, suggesting that combined doses observed in this study were safe. We suggest preliminary dose constraints as a conservative starting point to investigate and escalate prospectively in a future study.

Accumulated Dose Prediction for Assisting Radiation Treatment in Cervical Cancer

<h3>Purpose/Objective(s)</h3> For cervical cancer treated with combined external beam radiotherapy (EBRT) and brachytherapy (BT), ideally, the treatment optimization and evaluation should take the accumulated dose distribution into account. However, in current clinical practice different treatment parts are linked to different planning images and optimized independently, resulting in multiple dose distributions. In this study, we used a combination of deformable image registration (DIR) and deep learning techniques to predict the accumulated dose for assisting treatment planning and dose estimation. <h3>Materials/Methods</h3> The dose distributions of both EBRT and BT plans from 32 cervical cancer patients were used for this study. Firstly, the BT images were registered to the EBRT images using DIR to obtain the accumulated dose distributions. Then, a deep learning model based on a 101-layers ResNet was trained to predict pixel-wise dose distributions. The input data was combined anatomic maps including the CT images, structure maps and distance maps. The output data was the corresponding accumulated dose maps. We used 5-fold cross-validation to test the performance of the prediction model. The evaluation parameters included the voxel-based mean absolute error (MAE) and dice similarity coefficient (DSC) of isodose volumes for the prescription dose (PD) of EBRT (45/50 Gy) and the summed PD of EBRT and BT (76.25/82 Gy_EQD2). Finally, we randomly selected 10 patients to validate the effect of the dose prediction on treatment planning. For each patient, two EBRT plans were separately designed by a single physicist in the cases of unknowing and knowing the predicted accumulated dose distribution. The resulting two EBRT doses were separately accumulated with BT dose for comparison. <h3>Results</h3> In the comparison between the predicted and original dose distributions, the mean MAE of the whole body, normal tissue, bladder and rectum were 3.73±1.58, 3.27±1.06, 6.55±3.10 and 8.05±4.95 Gy, respectively. The mean DSC of the isodose volumes for 45/50 Gy and 76.25/82 Gy_EQD2 were 0.89±0.02 and 0.69±0.09, respectively. Compared to the planning without knowing the predicted dose, the planning with knowing the predicted dose resulted in a lower D2cc (-1.2±0.80 Gy, p=0.04), V40 (-3.23±2.19%, p=0.002), V50 (-2.19±%1.34, p=0.001) and V60 (-0.79±0.82%, p=0.02) of the rectum. For the bladder, the V40 of were decreased by 1.48±0.58% (p<0.001) but other dosimetric parameters had no significant difference. <h3>Conclusion</h3> The accumulated dose prediction could help to estimate and further decrease the doses to organs at risk. The predicted dose is recommended to be used as a reference during treatment planning in order to pursue a superior accumulated dose distribution for the combined cervical cancer treatment.

Evaluation of auto-segmentation for EBRT planning structures using deep learning-based workflow on cervical cancer

Deep learning (DL) based approach aims to construct a full workflow solution for cervical cancer with external beam radiation therapy (EBRT) and brachytherapy (BT). The purpose of this study was to evaluate the accuracy of EBRT planning structures derived from DL based auto-segmentation compared with standard manual delineation. Auto-segmentation model based on convolutional neural networks (CNN) was developed to delineate clinical target volumes (CTVs) and organs at risk (OARs) in cervical cancer radiotherapy. A total of 300 retrospective patients from multiple cancer centers were used to train and validate the model, and 75 independent cases were selected as testing data. The accuracy of auto-segmented contours were evaluated using geometric and dosimetric metrics including dice similarity coefficient (DSC), 95% hausdorff distance (95%HD), jaccard coefficient (JC) and dose-volume index (DVI). The correlation between geometric metrics and dosimetric difference was performed by Spearman’s correlation analysis. The right and left kidney, bladder, right and left femoral head showed superior geometric accuracy (DSC: 0.88–0.93; 95%HD: 1.03 mm–2.96 mm; JC: 0.78–0.88), and the Bland–Altman test obtained dose agreement for these contours (P > 0.05) between manual and DL based methods. Wilcoxon’s signed-rank test indicated significant dosimetric differences in CTV, spinal cord and pelvic bone (P < 0.001). A strong correlation between the mean dose of pelvic bone and its 95%HD (R = 0.843, P < 0.001) was found in Spearman’s correlation analysis, and the remaining structures showed weak link between dosimetric difference and all of geometric metrics. Our auto-segmentation achieved a satisfied agreement for most EBRT planning structures, although the clinical acceptance of CTV was a concern. DL based auto-segmentation was an essential component in cervical cancer workflow which would generate the accurate contouring.

A feasibility study of a modified treatment strategy combined external beam radiation therapy and brachytherapy for cervical cancer.

PurposeTo evaluate the feasibility of a modified treatment strategy combined external beam radiation therapy (EBRT) and brachytherapy (BT) for cervical cancer through a dosimetry analysis.Material and methodsThis study retrospectively selected 12 cervical cancer patients treated with the conventional treatment strategy, which consisted of 45─50 Gy/25 fractions of EBRT using volumetric‐modulated arc therapy (VMAT) and image‐guided BT with a fraction dose of 5─7 Gy. The modified treatment strategy decreased the central EBRT dose while increasing the number of BT fractions. New target volumes were additionally contoured, and new VMAT EBRT plans were generated for the modified treatment strategy. The dosimetric parameters for evaluation included the doses to the most irradiated 2 cc (D2cc) of the organs at risk (OARs) and doses to at least 90% (D90) of the gross tumor volume (GTV) and high‐risk clinical target volume (HR‐CTV). The total doses to OARs and targets obtained by adding the equivalent doses in 2 Gy fraction (EQD2) from the EBRT and BT plans were used for quantitative comparison between the modified and conventional treatment strategies.ResultsComparison to the conventional treatment strategy, the modified treatment strategy resulted in a higher bladder D2cc, a slightly lower rectal D2cc and a similar HR‐CTV D90, all with no significant differences (p > 0.05). The GTV D90 of the modified treatment strategy was significantly higher than that of the conventional treatment strategy (p < 0.01).ConclusionThe modified treatment strategy can significantly increase the BT dose while remaining the total doses to the bladder and rectum basically unchanged, demonstrating its feasibility and promising prospect in clinical use.

Early onset of severe lymphopenia during definitive radiotherapy correlates with mean body dose and predicts poor survival in cervical cancer.

BACKGROUND: Lymphopenia during definitive radiotherapy (RT) has been shown to reduce survival in patients with cervical cancer. However, there are few studies on the significance of onset time of lymphopenia during RT in patients with cervical cancer.OBJECTIVE: This study aimed to exam the prognostic significance of early onset of severe lymphopenia (EOSL) during definitive RT in patients with cervical cancer.METHODS: Newly diagnosed cervical cancer patients treated with definitive RT from January 2015 to December 2019 were eligible for this retrospective study. EOSL was defined as first onset of grade 3–4 lymphopenia 3 weeks from the start of RT. Mean body dose (MBD) was the mean radiation dose absorbed by the body during the whole course of external beam RT (EBRT) and was directly obtained from the dose volume histogram (DVH) of the EBRT planning. Logistic regression analysis and restricted cubic spline (RCS) models were applied to assess relationships between clinicopathological factors and EOSL. Survival analysis was performed using Kaplan-Meier curves and log-rank test. A COX regression model was developed to predict overall survival (OS).RESULTS: A total of 104 patients were included and 59.6% had EOSL. MBD ( 0.04), concurrent cisplatin ( 0.011), and pre-RT absolute lymphocyte count (ALC) ( 0.001) were associated with EOSL. A linear relationship ( for non-linearity 0.803) between MBD and risk of EOSL was found. Patients with EOSL had decreased OS (2-yr 75.1% vs 91.1%, 0.021) and progression-free survival (PFS) (2-yr 71.2% vs 83.7%, 0.071). An OS prediction COX model was developed with C-index of 0.835 and AUC of 0.872.CONCLUSIONS: EOSL during definitive RT correlates with MBD and predicts poor survival in patients with cervical cancer.

Multi-parametric magnetic resonance imaging for radiation treatment planning.

In recent years, multi-parametric magnetic resonance imaging (MpMRI) has played a major role in radiation therapy treatment planning. The superior soft tissue contrast, functional or physiological imaging capabilities, and the flexibility of site-specific image sequence development has placed MpMRI at the forefront. In this article, the present status of MpMRI for external beam radiation therapy planning is reviewed. Common MpMRI sequences, preprocessing, and quality assurance strategies are briefly discussed, and various image registration techniques and strategies are addressed. Image segmentation methods including automatic segmentation and deep learning techniques for organs at risk and target delineation are reviewed. Due to the advancement in MRI-guided online adaptive radiotherapy, treatment planning considerations addressing MRI only planning are also discussed.

Clinicopathologic analysis of microscopic tumor extension in glioma for external beam radiotherapy planning

BackgroundThere is no consensus regarding the clinical target volume (CTV) margins in radiotherapy for glioma. In this study, we aimed to perform a complete macropathologic analysis examining microscopic tumor extension (ME) to more accurately define the CTV in glioma.MethodsThirty-eight supra-total resection specimens of glioma patients were examined on histologic sections. The ME distance, defined as the maximum linear distance from the tumor border to the invasive tumor cells, was measured at each section. We defined the CTV based on the relationships between ME distance and clinicopathologic features.ResultsBetween February 2016 and July 2020, a total of 814 slides were examined, corresponding to 162 slides for low-grade glioma (LGG) and 652 slides for high-grade glioma (HGG). The ME value was 0.69 ± 0.43 cm for LGG and 1.29 ± 0.54 cm for HGG (P < 0.001). After multivariate analysis, tumor grade, O6-methylguanine-DNA-methyltransferase promoter methylated status (MGMTm), isocitrate dehydrogenase wild-type status (IDHwt), and 1p/19q non-co-deleted status (non-codel) were positively correlated with ME distance (all P < 0.05). We defined the CTV of glioma based on tumor grade. To take into account approximately 95% of the ME, a margin of 1.00 cm, 1.50 cm, and 2.00 cm were chosen for grade II, grade III, and grade IV glioma, respectively. Paired analysis of molecularly defined patients confirmed that tumors that had all three molecular alterations (i.e., MGMTm/IDHwt/non-codel) were the most aggressive subgroups (all P < 0.05). For these patients, the margin could be up to 1.50 cm, 2.00 cm, and 2.50 cm for grade II, grade III, and grade IV glioma, respectively, to cover the subclinical lesions in 95% of cases.ConclusionsThe ME was different between the grades of gliomas. It may be reasonable to recommend 1.00 cm, 1.50 cm, and 2.00 cm CTV margins for grade II, grade III, and grade IV glioma, respectively. Considering the highly aggressive nature of MGMTm/IDHwt/non-codel tumors, for these patients, the margin could be further expanded by 0.5 cm. These recommendations would encompass microscopic disease extension in 95% of cases.Trial registrationThe trial was registered with Chinese Clinical Trial Registry (ChiCTR2100049376).

Impact of different treatment plans on EQD2 for intracavitary brachytherapy of cervical cancer

BackgroundCancer is one of the leading causes of death worldwide. According to GLOBOCAN estimates, there were 341,831 deaths from cervical cancer in 185 countries in 2020. The aim of this study was to compare equieffective dose (EQD2) at 2 Gy per fraction by using dose volume histograms (DVHs) derived from external beam radiotherapy (EBRT) and high-dose rate brachytherapy (HDR-BRT) treatment plans used in cervical cancer radiotherapy.MethodsFifteen patients with stage IIB-IIIB cervical cancer were included in this retrospective study. Treatment with three-dimensional conformal radiotherapy (3D-CRT) or intensity-modulated radiotherapy (IMRT) was planned for all patients in 28 fractions, with a total of 50.4 Gy to be delivered to the whole pelvic region. After EBRT, manual optimization (MO) or inverse optimization (IO) HDR-BRT plans were created in 4 fractions with a total of 28 Gy. The plans obtained were grouped as IMRT + IO, IMRT + MO, 3DCRT + IO, and 3DCRT + MO by calculating EQD2s among these plans. D90, D95, and D98 values were compared in all plans for CTVHR total EQD2. In addition, EQD2 values ​for critical organs at risk (OARs) such as rectum, bladder, small intestine, and sigmoid were compared in all plans for volumes of 2 cm3, 1 cm3, and 0.1 cm3, respectively.ResultsThere was no significant difference between the treatment groups in terms of CTVHR D90 and CTVIR D90 values; However, CTVHR D95 (p = 0.000) and CTVHR D98 (p = 0.000) values ​were found to be better in IMRT + IO technique. The IMRT + IO technique provided better protection for 2 cm3, 1 cm3, and 0.1 cm3 volumes of OARs compared to other techniques.ConclusionsConsidering all parameters such as CTVHR, CTVIR, rectum, bladder, small intestine, and sigmoid, combination of IMRT + IO treatment option was found to be significantly superior in total EQD2 calculations compared to other plans.

A Case Series of Dosimetric Comparison-VMAT (RapidArc), IMRT, 3DCRT for Extended Field Radiotherapy in Cervical Cancer

Purpose: To compare plans of 3DCRT, IMRT and VMAT (RapidArc) and evaluate them in different dosimetric aspects along with dose to organs at risk with each technique to determine the best treatment technique for Extended field RT in cervical cancer patients Material &amp; Methods: We evaluated External Beam radiotherapy plans of 10 patients of FIGO 2018 stage rIIIC2 who received Extended Field Radiotherapy (EFRT) to primary site along with regional nodes-bilateral external, internal iliac lymph nodes, presacral and para-aortic lymph nodes. The dose prescribed for all patients was 50.4Gy/28 fractions at 180cGy/fraction. Few patients had received gross nodal boost following this, but for better comparison only the initial phase of 50.4Gy/28 fractions was considered. All patients were planned with 3DCRT, IMRT and RapidArc. We evaluated and compared these plans dosimetrically in terms of Homogeneity Index, Conformity Index, Target Volume Coverage, Gradient Index, Unified Dosimetry Index, Integral dose, Monitor units and Doses to Organs at risk such as Anorectum, Bladder, Bowel Bag, Bilateral Femoral Heads, Bilateral Kidneys and Bone Marrow. Results: Intensity modulated techniques RapidArc and IMRT significantly spared critical organs compared to 3DCRT. Between RapidArc and IMRT, the critical organ sparing was comparable, but RapidArc had better target coverage, lesser MU and lesser treatment time. All techniques had acceptable HI, CI, GI, UDI and whole body Integral dose. Conclusion: Intensity modulated techniques should be the standard for EFRT in cervical cancer. Both RapidArc and IMRT are acceptable techniques of treatment delivery although the former may be preferred if and when available.

Hydrogel spacer shrinkage during external-beam radiation therapy following low-dose-rate brachytherapy for high-risk prostate cancer: a case series\xa0

BackgroundFew studies have assessed hydrogel spacer shrinkage during external-beam radiation therapy following brachytherapy for localized high-risk prostate cancer. This case presentation evaluated the changes in hydrogel spacer appearance by magnetic resonance imaging during external-beam radiation therapy after brachytherapy for prostate cancer and analyzed the effect of this shrinkage on the dose distribution in four cases.Case presentationIn all cases, we implanted 125I sources using a modified peripheral loading pattern for seed placement. The prescribed dose for each implant was 110 Gy. After delivering the sources, a hydrogel spacer was injected. All cases underwent external-beam radiation therapy approximately 1–2 months after brachytherapy. The prescribed dose of external-beam radiation therapy was 45 Gy in 1.8-Gy fractions. Magnetic resonance imaging was performed for evaluation on the day following seed implantation (baseline), at external-beam radiation therapy planning, and during external-beam radiation therapy. The median hydrogel spacer volume was 16.2 (range 10.9–17.7) cc at baseline, 14.4 (range, 9.4–16.1) cc at external-beam radiation therapy planning, and 7.1 (range, 2.0–11.4) cc during external-beam radiation therapy. The hydrogel spacer volume during external-beam radiation therapy was significantly lower than that at external-beam radiation therapy planning. The rectum V60–80 (rectal volume receiving at least 60–80% of the prescribed dose of external-beam radiation therapy) during external-beam radiation therapy was significantly higher than that at external-beam radiation therapy planning.ConclusionsThe potential reduction in hydrogel spacer size during external-beam radiation therapy following brachytherapy can lead to unexpected irradiation to the rectum. This case presentation would be helpful for similar cases.

Automatic couch position calculation using eclipse scripting for external beam radiotherapy.

PurposeThe treatment couch position of a patient in external beam radiation therapy (EBRT) is usually acquired during initial treatment setup. This procedure has shown potential failure modes leading to near misses and adverse events in radiation treatment. This study aims to develop a method to automatically determine the couch position before setting up a patient for initial treatment.MethodsThe Qfix couch‐tops (kVue and DoseMax) have embedded reference marks (BBs) indicating its index levels and couch centerline. With the ESAPI, a C# script was programmed to automatically find the couch‐top and embedded BBs in the planning CT and derive the treatment couch position according to treatment isocenter of a plan. Couch positions of EBRT plans with the kVue couch‐top and SBRT plans using the DoseMax were calculated using the script. The calculation was evaluated by comparing calculated positions with couch coordinates captured during the initial treatment setup after image guidance. The calculations were further compared with daily treatment couch positions post image‐guided adjustment for each treatment fraction.ResultsFor plans using the kVue couch‐top for various treatment sites, the median (5–95 percentiles) differences between calculated and captured couch positions were 0.1 (−0.2 – 0.9), 0.5 (−1.1–2.0), 0.10 (−1.3–1.3) cm in the vertical, longitudinal, and lateral direction respectively. For the DoseMax couch‐top, the median differences were 0.1 (−0.2–0.7), 0.2 (−0.3–1.1), and 0.2 (−0.7–0.9) cm in respective direction. The calculated positions were within 1 and 2 cm from the mean fraction positions for 95% patients on DoseMax and kVue couch‐top respectively.ConclusionsA method that automatically and accurately calculates treatment couch position from simulation CT was implemented in Varian Eclipse for Qfix couch‐tops. This technique increases the efficiency of patient setup and enhances patient safety by reducing the risks of positioning errors.

A Dosimetric Comparison of Pelvic Lymph Node Volume Delineation Using Magnetic Resonance Imaging Versus Computed Tomography in Gynecological Cancers

Definitive external beam radiotherapy (EBRT) targets the primary tumor and at-risk pelvic lymph node groups. Magnetic resonance imaging (MRI), with its superior soft tissue definition compared with computed tomography (CT), is routinely used in cervical cancer EBRT planning to accurately define the primary tumor. MRI can also provide more accurate visualization of lymph nodes, vessels and tissue planes, such that MRI-based nodal clinical target volume (CTVn) delineation may result in smaller volumes and reduced dose to organs at risk (OAR). The aim of this study was to dosimetrically compare EBRT plans in patients with CTVn delineation using MRI fused with CT (CT-MRI) and CT alone. This study was important to examine the advantage of MRI in radiotherapy; prior to the addition of a new MRI simulator and MRI Linac in our center. Nine patients with cervical cancer and two patients with recurrent endometrial cancer were treated using definitive EBRT at our institution with diagnostic MRI scans and were included in this study. The planning CT (pCT) scan for each patient was obtained and fused with T2-weighted MRI scan using bony landmarks and deformable registration. Two separate CTVn volumes were contoured by a radiation oncologist, one based on pCT and a second based on MRI. All other structures including primary CTV (CTVp) and OAR (rectum, sigmoid, bowel, bladder, and femurs) were contoured on the pCT only. Planning target volume (PTV) contours were created by combining CTVn and CTVp with a 1 cm margin. Volumetric modulated arc therapy (VMAT) plans were generated for both pCT-based PTVs and CT-MRI-based PTVs using institutional protocol. Plans were evaluated for PTV volume, coverage (D98) and dose to OAR. Differences between pCT and CT-MRI were analyzed using paired t-tests and results are presented as means and SD (standard deviation). Twenty-two VMAT plans were generated. The mean (SD) PTV volume was 1485.9 cm³ (171.7) for pCT and 1424.5 cm³ (168.0) for the CT-MRI plan (p<0.001). The mean (SD) PTV D98 for pCT and CT-MRI was the same at 43.1 Gy (0.3) (p = 0.677). There was no significant dosimetric difference noted to any of the OAR (Table). This novel method for reducing the CTVn volume by using MRI to avoid anatomical boundaries such as fascial planes and bowel produced an overall reduction in the target volume. However, this did not result in a dosimetric advantage to the surrounding OAR. The most clinically relevant benefit of MRI in gynecological EBRT planning remains in the accurate definition of the primary tumor.Tabled 1Abstract 3080; Table;Organ at RiskpCT, Mean (SD)CT-MRI, Mean (SD)p-valueRectum (V40)56.9% (5.2)49.8% (11.8)0.111Sigmoid (V40)82.2% (20.6)78.7% (28.7)0.588Sigmoid (V45)27.5% (13.9)26.5% (17.8)0.787Bowel (V40)197.8cm³ (97.8)210.8cm³ (103.5)0.605Bowel (V45)73.3cm³ (43.1)67.3cm³ (45.9)0.664Bladder (V45)22.5% (4.1)24.5% (5.9)0.172Right Femur (V30)10.9% (2.3)10.3% (2.9)0.458Left Femur (V30)12.0% (3.1)11.6% (2.2)0.570 Open table in a new tab

Current Status of Anatomical Magnetic Resonance Imaging in Brachytherapy and External Beam Radiotherapy Planning and Delivery

Radiotherapy planning and delivery have dramatically improved in recent times. Imaging is key to a successful three-dimensional and increasingly four-dimensional based pathway with computed tomography embedded as the backbone modality. Computed tomography has significant limitations for many tumour sites where soft-tissue discrimination is suboptimal, and where magnetic resonance imaging (MRI) has largely superseded in the diagnostic arena. MRI is increasingly used together with computed tomography in the radiotherapy planning pathway and is now established as a prerequisite for several tumours. With the advent of combined MRI and linear accelerator (MR-linac) systems, a transition to MRI-based radiotherapy planning is becoming reality, with increasing experience and research involving these new platforms. In this overview, we aim to highlight how magnetic resonance-guided imaging has improved radiotherapy, using gynaecological malignancies to illustrate, in both external beam radiotherapy and image-guided brachytherapy, and will assess the early evidence for magnetic resonance-guided radiotherapy using combined MR-linac systems.

Prediction of inter-fractional radiotherapy dose plans with domain translation in spatiotemporal embeddings.

External beam radiation therapy fractions have become extremely complex and tedious procedures to plan, due to stringent requirements of delivering the highest radiation dose to the tumor while maximally avoiding organs at risk. However, due to anatomic and/or biological changes between fractions, dose re-optimization may be needed. Re-optimization is a time-consuming task which is typically triggered based on subjective visual assessment by an experienced physician. To address limitations in this process, we introduce a predictive framework which learns the evolution of tumor anatomy as well as inter-fractional dose delivery variations for head and neck cancers. First, joint low-dimensional discriminant embeddings maximizing the separation between responsive and non-responsive groups to external beam radiotherapy plans are constructed from deep neural networks in order to capture patient-specific dose modulations with respect to anatomical variations. Then, latent representations are fed to a domain-level adversarial network to translate observed anatomical changes into dosimetric variations, which aims to enforce local semantic consistency in the overall translation. Dose distribution trajectories are represented in a group-average piecewise-geodesic setting to handle anatomical variations during therapy, using a quadratic optimization to perform curve regression. At test time, an annotated baseline CT is projected onto the latent space and translated to dose domain, from which a spatiotemporal regression model is constructed using parallel transport trajectories defined from closest samples. This allows to predict dosimetry changes during the course of treatment. The model was trained on 337 cases and tested on 50 separate patients using sequential CT and associated dosimetry data, with the probabilistic framework yielding a Dice score of 92% and an overall dose difference of 1.2Gy in organs at risk and tumor volume over the course of multi-day treatment course, with a 5% reduction in delivered fraction segments.

Assessment of MRI-Based Attenuation Correction for MRI-Only Radiotherapy Treatment Planning of the Brain.

Magnetic resonance imaging-only radiotherapy treatment planning (MRI-only RTP) and positron emission tomography (PET)–MRI imaging require generation of synthetic computed tomography (sCT) images from MRI images. In this study, initial dosimetric evaluation was performed for a previously developed MRI-based attenuation correction (MRAC) method for use in MRI-only RTP of the brain. MRAC-based sCT images were retrospectively generated from Dixon MR images of 20 patients who had previously received external beam radiation therapy (EBRT). Bone segmentation performance and Dice similarity coefficient of the sCT conversion method were evaluated for bone volumes on CT images. Dose calculation accuracy was assessed by recalculating the CT-based EBRT plans using the sCT images as the base attenuation data. Dose comparison was done for the sCT- and CT-based EBRT plans in planning target volume (PTV) and organs at risk (OAR). Parametric dose comparison showed mean relative differences of <0.4% for PTV and <1.0% for OARs. Mean gamma index pass rates of 95.7% with the 2%/2 mm agreement criterion and 96.5% with the 1%/1 mm agreement criterion were determined for glioma and metastasis patients, respectively. Based on the results, MRI-only RTP using sCT images generated from MRAC images can be a feasible alternative for radiotherapy of the brain.

Effect of Computed Tomography Slice Thickness on Calculated Coronary Artery Calcium Score in the Assessment of Possible Radiation Induced Cardiac Toxicity

Studies have suggested that the occurrence of radiation induced cardiac toxicity in breast cancer patients is significantly higher in women with pre-existing cardiac risk factors. Therefore, it is important to quantify the relationship between radiation induced cardiac toxicity and a measurable level of pre-existing cardiac risk such as the patient’s coronary artery calcium Agatston score. To assess the extent of coronary artery calcium present in the walls of patients’ coronary arteries before they received treatment, Agatston scores may be calculated using thoracic CT scans acquired for external beam radiotherapy planning. However, these planning CT scans can vary in slice thickness and resolution, thus complicating the calculation of calcium scores using scans with slice thicknesses other than the 3mm routinely employed for traditional Agatston scoring. The objective of this project is to quantify the effect of varying CT scan slice thickness in the calculation of coronary artery calcium scores so that a method of standardization might be developed. This is accomplished through the design, fabrication, and scanning of an anthropomorphic phantom featuring calcium inserts of varying sizes. Analysis of how the scores change with increasing slice thickness is used to construct a simple linear scaling method of standardization which corrects for varying slice thickness and the resulting partial volume distortions. A linear scaling method was successfully validated for the calculation of coronary artery calcium Agatston scores across a range of slice thicknesses increasing from 0.625 mm to 5 mm. Scaling is applied by multiplying the score by the slice thickness and dividing by 3 mm. This method is potentially applicable in any clinical or research endeavour which calls for retroactive cardiac calcium quantification. With a simple linear scaling method, external beam radiation therapy planning CT scans with slice thicknesses ranging from 0.625 mm to 5 mm can be used to calculate coronary artery calcium Agatston scores and thereby measure a patient’s level of cardiac risk before treatment.