Neural network dose prediction for cervical brachytherapy: Overcoming data scarcity for applicator-specific models.

BACKGROUND: 3D neural network dose predictions are useful for automating brachytherapy (BT) treatment planning for cervical cancer. Cervical BT can be delivered with numerous applicators, which necessitates developing models that generalize to multiple applicator types. The variability and scarcity of data for any given applicator type poses challenges for deep learning. PURPOSE: The goal of this work was to compare three methods of neural network training-a single model trained on all applicator data, fine-tuning the combined model to each applicator, and individual (IDV) applicator models-to determine the optimal method for dose prediction. METHODS: Models were produced for four applicator types-tandem-and-ovoid (T&O), T&O with 1-7 needles (T&ON), tandem-and-ring (T&R) and T&R with 1-4 needles (T&RN). First, the combined model was trained on 859 treatment plans from 266 cervical cancer patients treated from 2010 onwards. The train/validation/test split was 70%/16%/14%, with approximately 49%/10%/19%/22% T&O/T&ON/T&R/T&RN in each dataset. Inputs included four channels for anatomical masks (high-risk clinical target volume [HRCTV], bladder, rectum, and sigmoid), a mask indicating dwell position locations, and applicator channels for each applicator component. Applicator channels were created by mapping the 3D dose for a single dwell position to each dwell position and summing over each applicator component with uniform dwell time weighting. A 3D Cascade U-Net, which consists of two U-Nets in sequence, and mean squared error loss function were used. The combined model was then fine-tuned to produce four applicator-specific models by freezing the first U-Net and encoding layers of the second and resuming training on applicator-specific data. Finally, four IDV models were trained using only data from each applicator type. Performance of these three model types was compared using the following metrics for the test set: mean error (ME, representing model bias) and mean absolute error (MAE) over all dose voxels and ME of clinical metrics (HRCTV D90% and D2cc of bladder, rectum, and sigmoid), averaged over all patients. A positive ME indicates the clinical dose was higher than predicted. 3D global gamma analysis with the prescription dose as reference value was performed. Dice similarity coefficients (DSC) were computed for each isodose volume. RESULTS: Fine-tuned and combined models showed better performance than IDV applicator training. Fine-tuning resulted in modest improvements in about half the metrics, compared to the combined model, while the remainder were mostly unchanged. Fine-tuned MAE = 3.98%/2.69%/5.36%/3.80% for T&O/T&R/T&ON/T&RN, and ME over all voxels = -0.08%/-0.89%/-0.59%/1.42%. ME D2cc were bladder = -0.77%/1.00%/-0.66%/-1.53%, rectum = 1.11%/-0.22%/-0.29%/-3.37%, sigmoid = -0.47%/-0.06%/-2.37%/-1.40%, and ME D90 = 2.6%/-4.4%/4.8%/0.0%. Gamma pass rates (3%/3 mm) were 86%/91%/83%/89%. Mean DSCs were 0.92%/0.92%/0.88%/0.91% for isodoses ≤ 150% of prescription. CONCLUSIONS: 3D BT dose was accurately predicted for all applicator types, as indicated by the low MAE and MEs, high gamma scores and high DSCs. Training on all treatment data overcomes challenges with data scarcity in each applicator type, resulting in superior performance than can be achieved by training on IDV applicators alone. This could presumably be explained by the fact that the larger, more diverse dataset allows the neural network to learn underlying trends and characteristics in dose that are common to all treatment applicators. Accurate, applicator-specific dose predictions could enable automated, knowledge-based planning for any cervical brachytherapy treatment.

Quantitative MRI biomarker for classification of clinically significant prostate cancer: calibration for reproducibility across echo times.

Background: Restriction Spectrum Imaging restriction score (RSIrs) is a quantitative biomarker for detecting clinically significant prostate cancer (csPCa). However, the quantitative value of the RSIrs is affected by imaging parameters such as echo time (TE). Purpose: The purpose of the present study is to develop a calibration method to account for differences in echo times and facilitate use of RSIrs as a quantitative biomarker for the detection of csPCa. Methods: This study included 197 consecutive patients who underwent MRI and biopsy examination; 97 were diagnosed with csPCa (grade group ≥ 2). RSI data were acquired three times during the same session: twice at minimum TE∼75ms and once at TE=90ms (TEmin 1 , TEmin 2 , and TE90, respectively). A proposed calibration method, trained on patients without csPCa, estimated a linear scaling factor (f) for each of the four diffusion compartments (C) of the RSI signal model. A linear regression model was determined to match C-maps of TE90 to the reference C-maps of TEmin 1 within the interval ranging from 95 th to 99 th percentile of signal intensity within the prostate. RSIrs comparisons were made at 98 th percentile within each patient's prostate. We compared RSIrs from calibrated TE90 (RSIrs TE90corr ) and uncorrected TE90 (RSIrs TE90 ) to RSIrs from reference TEmin 1 (RSIrs TEmin1 ) and repeated TEmin 2 (RSIrs TEmin2 ). Calibration performance was evaluated with sensitivity, specificity, area under the ROC curve, positive predicted value, negative predicted value, and F1-score. Results: Scaling factors for C 1 , C 2 , C 3 , and C 4 were estimated as 1.70, 1.38, 1.03, and 1.19, respectively. In non-csPCa cases, the 98 th percentile of RSIrs TEmin2 and RSIrs TEmin1 differed by 0.27±0.86SI (mean±standard deviation), whereas RSIrs TE90 differed from RSIrs TEmin1 by 1.81±1.20SI. After calibration, this bias was reduced to -0.41±1.20SI, representing a 78% reduction in absolute error. For patients with csPCa, the difference was 0.54±1.98SI between RSIrs TEmin2 and RSIrs TEmin1 and 2.28±2.06SI between RSIrs TE90 and RSIrs TEmin1 . After calibration, the mean difference decreased to -0.86SI, a 38% reduction in absolute error. At the Youden index for patient-level classification of csPCa (8.94SI), RSIrs TEmin1 has a sensitivity of 66% and a specificity of 72%. Prior to calibration, RSIrs TE90 at the same threshold tended to over-diagnose benign cases (sensitivity 44%, specificity 88%). Post-calibration, RSIrs TE90corr performs more similarly to the reference (sensitivity 71%, specificity 62%). Conclusion: The proposed linear calibration method produces similar quantitative biomarker values for acquisitions with different TE, reducing TE-induced error by 78% and 38% for non-csPCa and csPCa, respectively.

Estimating follow-up CTs from geometric deformations of catheter implants in interstitial breast brachytherapy: A feasibility study using electromagnetic tracking.

BACKGROUND: Electromagnetic tracking (EMT) systems have been shown to provide valuable information on the geometry of catheter implants in breast cancer patients undergoing interstitial brachytherapy (iBT). In the context of an extended patient-specific, pre-treatment verification, EMT can play a key role in determining the potential need and, if applicable, the appropriate time for treatment adaptation. To detect dosimetric shortcomings the relative position between catheters, and target volume and critical structures must be known. Since EMT cannot provide the anatomical context and standard imaging techniques such as cone-beam CT are not yet available in most brachytherapy suites, it is not possible to detect anatomic changes on a daily or fraction basis, so the need for adaptive planning cannot be identified. PURPOSE: The aim of this feasibility study is to develop and evaluate a technique capable of estimating follow-up CTs at any time based on the initial treatment planning CT (PCT) and surrogate information about changes of the implant geometry from an EMT system. METHODS: A deformation vector field is calculated from two different implant reconstructions acquired in treatment position through EMT, the first immediately after the PCT and the second at another time point during the course of treatment. The calculation is based on discrete displacement vectors of pairs of control and target points. These are extrapolated by means of different radial basis functions in order to cover the entire CT volume. The adequate parameters for the calculation of the deformation field were identified. By warping the PCT according to the deformation field, one obtains an estimated CT (ECT) that reflects the geometric changes. For the proof of concept, ECTs were computed for the time point of the clinical follow-up CT (FCT) that is embedded in the treatment workflow after the fourth fraction. RESULTS: ECT and clinical FCTs of 20 patients were compared to each other quantitatively in terms of absolute Hounsfield unit differences in the planning target volume (PTV) and in a convex hull (CH) enclosing the catheters. The median differences were 31.2  and 29.5 HU for the CH and the PTV, respectively. CONCLUSION: The proposed ECT approach was able to approximate the "anatomy of the day" and therefore, in principle, allows a dosimetric appraisal of the treatment plan quality before each fraction. In this way, it can contribute to a more detailed patient-specific quality assurance in iBT of the breast and help to identify the timing for a potential treatment adaptation.

ReIGNITE Radiation Therapy Boost: A Prospective, International Study of Radiation Oncologists' Accuracy in Contouring Prostate Tumors for Focal Radiation Therapy Boost on Conventional Magnetic Resonance Imaging Alone or With Assistance of Restriction Spectrum Imaging.

PURPOSE: In a phase III randomized trial, adding a radiation boost to tumor(s) visible on MRI improved prostate cancer (PCa) disease-free and metastasis-free survival without additional toxicity. Radiation oncologists' ability to identify prostate tumors is critical to widely adopting intraprostatic tumor radiotherapy boost for patients. A diffusion MRI biomarker, called the Restriction Spectrum Imaging restriction score (RSIrs), has been shown to improve radiologists' identification of clinically significant PCa. We hypothesized that (1) radiation oncologists would find accurately delineating PCa tumors on conventional MRI challenging and (2) using RSIrs maps would improve radiation oncologists' accuracy for PCa tumor delineation. METHODS AND MATERIALS: In this multi-institutional, international, prospective study, 44 radiation oncologists (participants) and 2 expert radiologists (experts) contoured prostate tumors on 39 total patient cases using conventional MRI with or without RSIrs maps. Participant volumes were compared to the consensus expert volumes. Contouring accuracy metrics included percent overlap with expert volume, Dice coefficient, conformal number, and maximum distance beyond expert volume. RESULTS: 1604 participant volumes were produced. 40 of 44 participants (91%) completely missed ≥1 expert-defined target lesion without RSIrs, compared to 13 of 44 (30%) with RSIrs maps. On conventional MRI alone, 134 of 762 contour attempts (18%) completely missed the target, compared to 18 of 842 (2%) with RSIrs maps. Use of RSIrs maps improved all contour accuracy metrics by approximately 50% or more. Mixed effects modeling confirmed that RSIrs maps were the main variable driving improvement in all metrics. System Usability Scores indicated RSIrs maps significantly improved the contouring experience (72 vs. 58, p < 0.001). CONCLUSIONS: Radiation oncologists struggle with accurately delineating visible PCa tumors on conventional MRI. RSIrs maps improve radiation oncologists' ability to target MRI-visible tumors for prostate tumor boost.

Automated treatment planning framework for brachytherapy of cervical cancer using 3D dose predictions.

Objective. To lay the foundation for automated knowledge-based brachytherapy treatment planning using 3D dose estimations, we describe an optimization framework to convert brachytherapy dose distributions directly into dwell times (DTs).Approach. A dose rate kerneld(r,θ,φ)was produced by exporting 3D dose for one dwell position from the treatment planning system and normalizing by DT. By translating and rotating this kernel to each dwell position, scaling by DT and summing over all dwell positions, dose was computed (Dcalc). We used a Python-coded COBYLA optimizer to iteratively determine the DTs that minimize the mean squared error betweenDcalcand reference doseDref, computed using voxels withDref80%-120% of prescription. As validation of the optimization, we showed that the optimizer replicates clinical plans whenDref= clinical dose in 40 patients treated with tandem-and-ovoid (T&O) or tandem-and-ring (T&R) and 0-3 needles. Then we demonstrated automated planning in 10 T&O usingDref= dose predicted from a convolutional neural network developed in past work. Validation and automated plans were compared to clinical plans using mean absolute differences (MAD=1N∑n=1Nabsxn-xn') over all voxels (xn= Dose,N= #voxels) and DTs (xn= DT,N= #dwell positions), mean differences (MD) in organD2ccand high-risk CTV D90 over all patients (where positive indicates higher clinical dose), and mean Dice similarity coefficients (DSC) for 100% isodose contours.Main results. Validation plans agreed well with clinical plans (MADdose= 1.1%, MADDT= 4 s or 0.8% of total plan time,D2ccMD = -0.2% to 0.2% and D90 MD = -0.6%, DSC = 0.99). For automated plans, MADdose= 6.5% and MADDT= 10.3 s (2.1%). The slightly higher clinical metrics in automated plans (D2ccMD = -3.8% to 1.3% and D90 MD = -5.1%) were due to higher neural network dose predictions. The overall shape of the automated dose distributions were similar to clinical doses (DSC = 0.91).Significance. Automated planning with 3D dose predictions could provide significant time savings and standardize treatment planning across practitioners, regardless of experience.

Comparison of synthesized and acquired high b -value diffusion-weighted MRI for detection of prostate cancer.

Background: High b -value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). To decrease scan time and improve signal-to-noise ratio, high b -value (>1000 s/mm 2 ) images are often synthesized instead of acquired. Purpose: Qualitatively and quantitatively compare synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa. Study Type: Retrospective. Subjects: 151 consecutive patients who underwent prostate MRI and biopsy. Sequence: Axial DWI with b =0, 500, 1000, and 2000 s/mm 2 using a 3T clinical scanner using a 32-channel phased-array body coil. Assessment: We synthesized DWI for b =2000 s/mm 2 via extrapolation based on monoexponential decay, using b =0 and b =500 s/mm 2 (sDWI 500 ) and b =0, b =500, and b =1000 s/mm 2 (sDWI 1000 ). Differences between sDWI and aDWI were evaluated within regions of interest (ROIs). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was also compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI. Statistical Tests: Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC). Statistical significance was assessed using bootstrap difference (two-sided α=0.05). Results: Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46±35% for sDWI 1000 and -67±24% for sDWI 500 . AUC for aDWI, sDWI 500, sDWI 1000 , and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively. When considering the whole field of view, classification accuracy and qualitative image quality decreased notably for sDWI compared to aDWI and RSIrs. Data Conclusion: sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.

Knowledge-based three-dimensional dose prediction for tandem-and-ovoid brachytherapy.

PURPOSE: The purpose of this work was to develop a knowledge-based dose prediction system using a convolution neural network (CNN) for cervical brachytherapy treatments with a tandem-and-ovoid applicator. METHODS: A 3D U-NET CNN was utilized to make voxel-wise dose predictions based on organ-at-risk (OAR), high-risk clinical target volume (HRCTV), and possible source location geometry. The model comprised 395 previously treated cases: training (273), validation (61), test (61). To assess voxel prediction accuracy, we evaluated dose differences in all cohorts across the dose range of 20-130% of prescription, mean (SD) and standard deviation (σ), as well as isodose dice similarity coefficients for clinical and/or predicted dose distributions. We examined discrete Dose-Volume Histogram (DVH) metrics utilized for brachytherapy plan quality assessment (HRCTV D90%; bladder, rectum, and sigmoid D2cc) with ΔDx=Dx,actual-Dx,predicted mean, standard deviation, and Pearson correlation coefficient further quantifying model performance. RESULTS: Ranges of voxel-wise dose difference accuracy (δD¯±σ) for 20-130% dose interval in training (test) sets ranged from [-0.5% ± 2.0% to +2.0% ± 14.0%] ([-0.1% ± 4.0% to +4.0% ± 26.0%]) in all voxels, [-1.7% ± 5.1% to -3.5% ± 12.8%] ([-2.9% ± 4.8% to -2.6% ± 18.9%]) in HRCTV, [-0.02% ± 2.40% to +3.2% ± 12.0%] ([-2.5% ± 3.6% to +0.8% ± 12.7%]) in bladder, [-0.7% ± 2.4% to +15.5% ± 11.0%] ([-0.9% ± 3.2% to +27.8% ± 11.6%]) in rectum, and [-0.7% ± 2.3% to +10.7% ± 15.0%] ([-0.4% ± 3.0% to +18.4% ± 11.4%]) in sigmoid. Isodose dice similarity coefficients ranged from [0.96,0.91] for training and [0.94,0.87] for test cohorts. Relative DVH metric prediction in the training (test) set were HRCTV ΔD¯90±σΔD = -0.19 ± 0.55Gy (-0.09 ± 0.67 Gy), bladder ΔD¯2cc±σΔD = -0.06 ± 0.54Gy (-0.17 ± 0.67 Gy), rectum ΔD¯2cc±σΔD= -0.03 ± 0.36Gy (-0.04 ± 0.46 Gy), and sigmoid ΔD¯2cc±σΔD = -0.01 ± 0.34Gy (0.00 ± 0.44 Gy). CONCLUSIONS: A 3D knowledge-based dose predictions provide voxel-level and DVH metric estimates that could be used for treatment plan quality control and data-driven plan guidance.

Evaluation of dose differences between intracavitary applicators for cervical brachytherapy using knowledge-based models.

PURPOSE: Currently, there is a lack of patient-specific tools to guide brachytherapy planning and applicator choice for cervical cancer. The purpose of this study is to evaluate the accuracy of organ-at-risk (OAR) dose predictions using knowledge-based intracavitary models, and the use of these models and clinical data to determine the dosimetric differences of tandem-and-ring (T&R) and tandem-and-ovoids (T&O) applicators. MATERIALS AND METHODS: Knowledge-based models, which predict organ D2cc, were trained on 77/75 cases and validated on 32/38 for T&R/T&O applicators. Model performance was quantified using ΔD2cc=D2cc,actual-D2cc,predicted, with standard deviation (σ(ΔD2cc)) representing precision. Model-predicted applicator dose differences were determined by applying T&O models to T&R cases, and vice versa, and compared to clinically-achieved D2cc differences. Applicator differences were assessed using a Student's t-test (p < 0.05 significant). RESULTS: Validation T&O/T&R model precision was 0.65/0.55 Gy, 0.55/0.38 Gy, and 0.43/0.60 Gy for bladder, rectum and sigmoid, respectively, and similar to training. When applying T&O/T&R models to T&R/T&O cases, bladder, rectum and sigmoid D2cc values in EQD2 were on average 5.69/2.62 Gy, 7.31/6.15 Gy and 3.65/0.69 Gy lower for T&R, with similar HRCTV volume and coverage. Clinical data also showed lower T&R OAR doses, with mean EQD2 D2cc deviations of 0.61 Gy, 7.96 Gy (p < 0.01) and 5.86 Gy (p < 0.01) for bladder, rectum and sigmoid. CONCLUSIONS: Accurate knowledge-based dose prediction models were developed for two common intracavitary applicators. These models could be beneficial for standardizing and improving the quality of brachytherapy plans. Both models and clinical data suggest that significant OAR sparing can be achieved with T&R over T&O applicators, particularly for the rectum.

Knowledge-based dose prediction models to inform gynecologic brachytherapy needle supplementation for locally advanced cervical cancer.

PURPOSE: The use of interstitial needles, combined with intracavitary applicators, enables customized dose distributions and is beneficial for complex cases, but increases procedure time. Overall, applicator selection is not standardized and depends on physician expertise and preference. The purpose of this study is to determine whether dose prediction models can guide needle supplementation decision-making for cervical cancer. MATERIALS AND METHODS: Intracavitary knowledge-based models for organ-at-risk (OAR) dose estimation were trained and validated for tandem-and-ring/ovoids (T&R/T&O) implants. Models were applied to hybrid cases with 1-3 implanted needles to predict OAR dose without needles. As a reference, 70/67 hybrid T&R/T&O cases were replanned without needles, following a standardized procedure guided by dose predictions. If a replanned dose exceeded the dose objective, the case was categorized as requiring needles. Receiver operating characteristic (ROC) curves of needle classification accuracy were generated. Optimal classification thresholds were determined from the Youden Index. RESULTS: Needle supplementation reduced dose to OARs. However, 67%/39% of replans for T&R/T&O met all dose constraints without needles. The ROC for T&R/T&O models had an area-under-curve of 0.89/0.86, proving high classification accuracy. The optimal threshold of 99%/101% of the dose limit for T&R/T&O resulted in classification sensitivity and specificity of 78%/86% and 85%/78%. CONCLUSIONS: Needle supplementation reduced OAR dose for most cases but was not always required to meet standard dose objectives, particularly for T&R cases. Our knowledge-based dose prediction model accurately identified cases that could have met constraints without needle supplementation, suggesting that such models may be beneficial for applicator selection.

ORBIT-RT: A Real-Time, Open Platform for Knowledge-Based Quality Control of Radiotherapy Treatment Planning.

PURPOSE: Access to knowledge-based treatment plan quality control has been hindered by the complexity of developing models and integration with different treatment planning systems (TPS). Online Real-time Benchmarking Information Technology for RadioTherapy (ORBIT-RT) provides a free, web-based platform for knowledge-based dose estimation that can be used by clinicians worldwide to benchmark the quality of their radiotherapy plans. MATERIALS AND METHODS: The ORBIT-RT platform was developed to satisfy four primary design criteria: web-based access, TPS independence, Health Insurance Portability and Accountability Act compliance, and autonomous operation. ORBIT-RT uses a cloud-based server to automatically anonymize a user's Digital Imaging and Communications in Medicine for RadioTherapy (DICOM-RT) file before upload and processing of the case. From there, ORBIT-RT uses established knowledge-based dose-volume histogram (DVH) estimation methods to autonomously create DVH estimations for the uploaded DICOM-RT. ORBIT-RT performance was evaluated with an independent validation set of 45 volumetric modulated arc therapy prostate plans with two key metrics: (i) accuracy of the DVH estimations, as quantified by their error, DVHclinical - DVHprediction and (ii) time to process and display the DVH estimations on the ORBIT-RT platform. RESULTS: ORBIT-RT organ DVH predictions show < 1% bias and 3% error uncertainty at doses > 80% of prescription for the prostate validation set. The ORBIT-RT extensions require 3.0 seconds per organ to analyze. The DICOM upload, data transfer, and DVH output display extend the entire system workflow to 2.5-3 minutes. CONCLUSION: ORBIT-RT demonstrated fast and fully autonomous knowledge-based feedback on a web-based platform that takes only anonymized DICOM-RT as input. The ORBIT-RT system can be used for real-time quality control feedback that provides users with objective comparisons for final plan DVHs.

A knowledge-based organ dose prediction tool for brachytherapy treatment planning of patients with cervical cancer.

PURPOSE: The purpose of this study is to explore knowledge-based organ-at-risk dose estimation for intracavitary brachytherapy planning for cervical cancer. Using established external-beam knowledge-based dose-volume histogram (DVH) estimation methods, we sought to predict bladder, rectum, and sigmoid D2cc for tandem and ovoid treatments. METHODS AND MATERIALS: A total of 136 patients with loco-regionally advanced cervical cancer treated with 456 (356:100 training:validation ratio) CT-based tandem and ovoid brachytherapy fractions were analyzed. Single fraction prescription doses were 5.5-8 Gy with dose criteria for the high-risk clinical target volume, bladder, rectum, and sigmoid. DVH estimations were obtained by subdividing training set organs-at-risk into high-risk clinical target volume boundary distance subvolumes and computing cohort-averaged differential DVHs. Full DVH estimation was then performed on the training and validation sets. Model performance was quantified by ΔD2cc = D2cc(actual)-D2cc(predicted) (mean and standard deviation). ΔD2cc between training and validation sets were compared with a Student's t test (p < 0.01 significant). Categorical variables (physician, fraction-number, total fractions, and case complexity) that might explain model variance were examined using an analysis of variance test (Bonferroni-corrected p < 0.01 threshold). RESULTS: Training set deviations were bladder ΔD2cc = -0.04 ± 0.61 Gy, rectum ΔD2cc = 0.02 ± 0.57 Gy, and sigmoid ΔD2cc = -0.05 ± 0.52 Gy. Model predictions on validation set did not statistically differ: bladder ΔD2cc = -0.02 ± 0.46 Gy (p = 0.80), rectum ΔD2cc = -0.007 ± 0.47 Gy (p = 0.53), and sigmoid ΔD2cc = -0.07 ± 0.47 Gy (p = 0.70). The only significant categorical variable was the attending physician for bladder and rectum ΔD2cc. CONCLUSION: A simple boundary distance-driven knowledge-based DVH estimation exhibited promising results in predicting critical brachytherapy dose metrics. Future work will examine the utility of these predictions for quality control and automated brachytherapy planning.

Adaptive radiotherapy and the dosimetric impact of inter- and intrafractional motion on the planning target volume for prostate cancer patients.

PURPOSE: To investigate the dosimetric influence of daily interfractional (inter) setup errors and intrafractional (intra) target motion on the planning target volume (PTV) and the possibility of an offline adaptive radiotherapy (ART) method to correct larger patient positioning uncertainties in image-guided radiotherapy for prostate cancer (PCa). MATERIALS AND METHODS: A CTV (clinical target volume)-to-PTV margin ranging from 15 mm in LR (left-right) and SI (superior-inferior) and 5-10 mm in AP (anterior-posterior) direction was applied to all patients. The dosimetric influence of this margin was retrospectively calculated by analysing systematic and random components of inter and intra errors of 31 consecutive intermediate- and high-risk localized PCa patients using daily cone beam computed tomography and kV/kV (kilo-Voltage) imaging. For each patient inter variation was assessed by observing the first 4 treatment days, which led to an offline ART-based treatment plan in case of larger variations. RESULTS: Systematic inter uncertainties were larger (1.12 in LR, 2.28 in SI and 1.48 mm in AP) than intra systematic errors (0.44 in LR, 0.69 in SI and 0.80 mm in AP). Same findings for the random error in SI direction with 3.19 (inter) and 2.30 mm (intra), whereas in LR and AP results were alike with 1.89 (inter) and 1.91 mm (intra) and 2.10 (inter) and 2.27 mm (intra), respectively. The calculated margin revealed dimensions of 4-5 mm in LR, 8-9 mm in SI and 6-7 mm in AP direction. Treatment plans which had to be adapted showed smaller variations with 1.12 (LR) and 1.72 mm (SI) for Σ and 4.17 (LR) and 3.75 mm (SI) for σ compared to initial plans with 1.77 and 2.62 mm for Σ and 4.46 and 5.39 mm for σ in LR and SI, respectively. CONCLUSION: The currently clinically used margin of 15 mm in LR and SI and 5-10 mm in AP direction includes inter and intra uncertainties. The results show that offline ART is feasible which becomes a necessity with further reductions in PTV margins.

Is adaptive treatment planning in multi-catheter interstitial breast brachytherapy necessary?

PURPOSE: For 55 patients treated with interstitial multi-catheter breast brachytherapy the need for adaptive treatment planning was assessed. METHODS AND MATERIALS: For all patients a treatment planning computed tomography (CT) and a follow-up CT were acquired and used for the retrospective evaluation. Keeping dwell time and dwell positions constant, the treatment plan assessed directly after catheter implantation was compared to the situation 48 h after implantation. Both manual catheter reconstructions, based on the planning and follow-up CT, were rigid registered to each other and the resulting deviations analyzed, like the difference between corresponding dwell positions (ΔDP) or the discrete Fréchet distance. Further, the dosimetric changes, e.g., coverage index (ΔCI), conformal index (ΔCOIN) and dose non-uniformity ratio (ΔDNR) were considered for a deformed planning target volume (PTV) and the rigid warped PTV structure. The PTV was deformed according to the vector field estimated between the two acquired CTs. RESULTS: Over all patients with rigid aligned CTs a mean ΔDP, ΔCI, ΔCOIN and ΔDNR were determined to 2.41 ±â€¯1.73 mm, 3.10 ±â€¯3.17%, 0.009 ±â€¯0.007 and 0.036 ±â€¯0.040, respectively. Considering the deformed PTV ΔCI was estimated to 5.05 ±â€¯4.14%. CONCLUSION: In conclusion, in 4% of the cases re-planning would have been beneficial to ensure the planned dose delivery. Large PTV changes or large DP deviations were found to be the main reasons for dosimetric variations.

Estimation of inter-fractional variations in interstitial multi-catheter breast brachytherapy using a hybrid treatment delivery system.

PURPOSE: Irradiation of the tumor bed using interstitial multi-catheter brachytherapy is one of the treatment options for breast cancer patients. In order to ensure the planned dose delivery an advanced quality intervention method using an electromagnetic tracking (EMT) system is presented. The system is used to assess inter-fractional variations within the framework of a patient study. METHODS AND MATERIALS: Until now 41 patients were included in the study for the evaluation and overall 355 EMT measurements were performed. The catheter traces are measured automatically and sequentially using an afterloader prototype (Flexitron, Elekta, Veenendaal, The Netherlands) equipped with an EMT sensor. The implant geometry is tracked directly after implantation, after CT imaging and after each irradiation fraction. The acquired data is rigidly registered to the catheter traces defined in the treatment plan and the dwell positions (DP) are reconstructed. DPs defined in treatment planning serve as reference. Breathing motion was corrected and recorded using three reference 6DoF sensors placed on the patients' skin. The Euclidean distance between the planned and reconstructed DPs provides information about possible inter-fractional deviations. Further, the influence of various factors on the occurrence of large deviations was investigated, like the patients' age, the length of the catheter, the breast volume, etc. RESULTS: Over all patient measurements a median Euclidean distance of 2.19 mm was determined between the reconstructed DPs and the reference DPs. The median deviation combining all datasets was minimal (1.67 mm) at the measurement directly after CT imaging. The deviations between the different fractions have a median distance of 2.31 mm which could be improved to 2.05 mm by adapting the treatment plan according to the follow-up CT. No correlation between the distance to the skin, ribs, mammilla or the breast volume and the occurrences of large deviations was found. The largest deviations were determined in the upper inner quadrant of the breast. CONCLUSION: The afterloader prototype could be well integrated into the clinical routine and is beneficial for ensuring the quality of the brachytherapy. Overall, a small median DP deviation, lower than the used step size of 2.5 mm, was detected.

Error detection using an electromagnetic tracking system in multi-catheter breast interstitial brachytherapy.

The hybrid treatment delivery system (HTDS) has been proposed as a possible option for a quality assurance in the multi-catheter interstitial brachytherapy for breast cancer patients. The system, which consists out of a prototype afterloader with an integrated electromagnetic tracking (EMT) sensor and an EMT system, allows the automatic measurement of implanted catheters. To test the feasibility of the system for error detection, possible treatment planning errors and treatment delivery errors were simulated. Planning errors such as an incorrect offset value, an incorrect indexer length, tip/connector end swaps, and partial swaps, and; treatment delivery errors such as catheter shifts and catheter connection swaps were manually simulated using phantoms. An in-house Matlab routine was used to assess geometrical deviations between the dwell positions defined based on CT and EMT measurement. Additionally, the influence of implant motion on the detection ability of the system was assessed. An algorithm for the detection and specification of errors based on the error simulation results was developed. At the University Hospital Erlangen, a patient study is ongoing, where errors in patient data were analyzed using the proposed algorithm. All simulated planning errors were detected. Catheter connection swaps can be detected 100% of the time. A shift detection rate of >97% was observed for shifts larger than 1.1 mm, both in the static and the motion measurements. Catheter reconstruction uncertainties and catheter shifts <2 mm were found to be the most common treatment planning and delivery errors in patient data. HTDS proved to be a reliable method for error detection.

Impact of inter- and intra-observer variabilities of catheter reconstruction on multi-catheter interstitial brachytherapy of breast cancer patients.

PURPOSE: The aim of this study was to evaluate inter- and intra-observer variabilities of catheter reconstruction and its dosimetric impact for multi-catheter interstitial breast cancer patients. METHODS AND MATERIALS: In order to evaluate inter-observer variabilities (IOV) three medical physicists reconstructed the catheter traces of 13 patients. These manual reconstructions were further compared to the automatic reconstruction algorithm integrated into the planning system and one on purpose imprecise manual reconstruction. For intra-observer variabilities (IAV) repeated reconstructions of two physicists were compared for 13 patients. In total 426 catheters were considered. Keeping dwell times, dwell positions, the optimization and the normalization relative points constant the geometrical deviations between the corresponding dwell positions of the reference data set and the investigated reconstructions were evaluated. Also, the effect on the quality indices, such as coverage index (CI), dose non-uniformity ratio (DNR) or conformal index (COIN), and the exposure of the organs at risk were analyzed. RESULTS: Over all patients and all different catheter reconstructions considered for IOV a mean deviation between the corresponding dwell positions of 0.60 ±â€¯0.35 mm was detected. The first observer had a mean deviation of 0.54 ±â€¯0.32 mm, whereas the second observer yielded a mean deviation of 0.58 ±â€¯0.37 mm. The length of the catheter traces varied in the mean by 0.51 ±â€¯0.45 mm. The mean relative deviation of the CI, DNR, COIN, mean heart dose and mean lung dose varied by 0.27 ±â€¯0.31%, 0.0027 ±â€¯0.0025, 0.0036 ±â€¯0.0033, 0.024 ±â€¯0.019%, 0.05 ±â€¯0.11%, respectively. The skin dose (D0.2ccm) changed in the maximum 8.52%. On average IAV reached a deviation between the corresponding dwell positions of 0.49 ±â€¯0.30 mm. IOVs and IAVs proved to be significantly different (Wilcoxon's test p < 0.01). CONCLUSIONS: The study proved that a repeated reconstruction of the catheter traces does not lead to large geometrical deviations or to a significant change in the dose exposure. But the lack of ground truth makes the estimation of the quality of the reconstruction challenging. A precise reconstruction mapping the reality is a necessity for the planned dose delivery. With all considered reconstruction techniques reliable quality indices for the target and the organs at risk could be obtained.

Introduction of a hybrid treatment delivery system used for quality assurance in multi-catheter interstitial brachytherapy.

Multi-catheter interstitial brachytherapy (iBT) is a treatment option for breast cancer patients after breast conserving surgery. Typically, only a few additional quality interventions after the first irradiation have been introduced to ensure the planned treatment delivery. Therefore, the purpose of this study is to show the possibilities of an electromagnetic tracking (EMT) system integrated into the afterloader for quality assurance (QA) in high-dose rate (HDR) iBT of patients with breast cancer. The hybrid afterloader system equipped with an electromagnetic sensor was used for all phantom and patient measurements. Phantom measurements were conducted to estimate the quality of different evaluation schemes. After a coherent point drift registration of the EMT traces to the reconstructed catheters based on computed tomograms the dwell positions (DP) were defined. Different fitting and interpolation methods were analyzed for the reconstruction of DPs. All estimated DPs were compared to the DPs defined in treatment planning. Until now, the implant geometry of 20 patients treated with HDR brachytherapy was acquired and explored. Regarding the reconstruction techniques, both fitting and interpolation were able to detect manually introduced shifts and swaps. Nonetheless, interpolation showed superior results (RMSE = 1.27 mm), whereas fitting seemed to be more stable to distortion and motion. The EMT system proved to be beneficial for QA in brachytherapy and furthermore, clinical feasibility was proven.

Dosimetric accuracy of the cone-beam CT-based treatment planning of the Vero system: a phantom study.

We report an investigation on the accuracy of dose calculation based on the cone-beam computed tomography (CBCT) images of the nonbowtie filter kV imaging system of the Vero linear accelerator. Different sets of materials and tube voltages were employed to generate the Hounsfield unit lookup tables (HLUTs) for both CBCT and fan-beam CT (FBCT) systems. The HLUTs were then implemented for the dose calculation in a treatment planning system (TPS). Dosimetric evaluation was carried out on an in-house-developed cube phantom that consists of water-equivalent slabs and inhomogeneity inserts. Two independent dosimeters positioned in the cube phantom were used in this study for point-dose and two-dimensional (2D) dose distribution measurements. The differences of HLUTs from various materials and tube voltages in both CT systems resulted in differences in dose calculation accuracy. We found that the higher the tube voltage used to obtain CT images, the better the point-dose calculation and the gamma passing rate of the 2D dose distribution agree to the values determined in the TPS. Moreover, the insert materials that are not tissue-equivalent led to higher dose-calculation inaccuracy. There were negligible differences in dosimetric evaluation between the CBCT- and FBCT-based treatment planning if the HLUTs were generated using the tissue-equivalent materials. In this study, the CBCT images of the Vero system from a complex inhomogeneity phantom can be applied for the TPS dose calculation if the system is calibrated using tissue-equivalent materials scanned at high tube voltage (i.e., 120 kV).