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Purpose: CT simulation is required for centers performing 3D conformal radiotherapy and intensity modulated radiation therapy. Therefore, CT simulator downtime is likely to lead to delays in patient care. We sought to characterize CT simulator downtime within the African context., Materials and Methods: A pilot clinician survey was developed to evaluate CT simulator downtime frequency, causes, and workflow impact over the last year. It was distributed to African Organization for Research and Training in Cancer (AORTIC) Conference attendees in November 2023 and through radiotherapy networks on the African continent. Descriptive statistics were used to summarize data., Results: Responses were obtained for 22 CT scanners in 16 centers across 9 African countries. Nigeria (n=6) and South Africa (n=3) had the most centers represented. Most centers (n=10, 63%) had a single CT scanner capable of simulation, five (31%) had two, and one (6%) had three scanners. For the 19 CT simulators with downtime information available, 11 (58%) were down for at least 15 days in the last year. Median downtime per episode was 3.5 days [IQR 1 - 9.75]. Three CT simulators were down all year, two of which were the only CT simulator at their respective centers. CT simulators were down due to intrinsic causes for median 8 days [IQR 3 - 37.5] and extrinsic causes for median 1 day [IQR 0 - 7.5]. Most machines (n=17, 77%) were under an active maintenance contract. Most centers (n=11, 69%) lacked access to an alternate CT scanner for simulation during downtime, while three (19%) maintained normal workflow., Conclusions: CT simulator downtime is highly variable across the African continent and can cause significant disruptions in radiotherapy treatment at some centers. Intrinsic causes led to most downtime. These results suggest reducing CT simulator downtime frequency and duration or implementing simulation-free workflows may decrease patient delays., Competing Interests: Declaration of competing interest Lauren P Wallner: Honoraria from Kaiser Permanente, Consulting or Advisory Role at Gilead Sciences, Travel, Accommodations, Expenses provided by Gilead Sciences Laurence E Court: Stock and Other Ownership Interests at LEO Cancer Care Research and research funding from Varian Medical Systems/Siemens Healthineers No other authors have competing interests to declare., (Copyright © 2025. Published by Elsevier Inc.) more...

Purpose: Our purpose was to analyze the effect on gastrointestinal (GI) toxicity models when their dose-volume metrics predictors are derived from segmentations of the peritoneal cavity after different contouring approaches., Methods and Materials: A random forest machine learning approach was used to predict acute grade ≥3 GI toxicity from dose-volume metrics and clinicopathologic factors for 246 patients (toxicity incidence = 9.5%) treated with definitive chemoradiation for squamous cell carcinoma of the anus. Three types of random forest models were constructed based on different bowel bag segmentation approaches: (1) physician-delineated after Radiation Therapy Oncology Group (RTOG) guidelines, (2) autosegmented by a deep learning model (nnU-Net) following RTOG guidelines, and (3) autosegmented but spanning the entire bowel space. Each model type was evaluated using repeated cross-validation (100 iterations; 50%/50% training/test split). The performance of the models was assessed using area under the precision-recall curve (AUPRC) and the receiver operating characteristic curve (AUROCC), as well as optimal F1 score., Results: When following RTOG guidelines, the models based on the nnU-Net auto segmentations (mean values: AUROCC, 0.71 ± 0.07; AUPRC, 0.42 ± 0.09; F1 score, 0.46 ± 0.08) significantly outperformed (P < .001) those based on the physician-delineated contours (mean values: AUROCC, 0.67 ± 0.07; AUPRC, 0.34 ± 0.08; F1 score, 0.36 ± 0.07). When spanning the entire bowel space, the performance of the autosegmentation models improved considerably (mean values: AUROCC, 0.87 ± 0.05; AUPRC, 0.70 ± 0.09; F1 score, 0.68 ± 0.09)., Conclusions: Random forest models were superior at predicting acute grade ≥3 GI toxicity when based on RTOG-defined bowel bag autosegmentations rather than physician-delineated contours. Models based on autosegmentations spanning the entire bowel space show further considerable improvement in model performance. The results of this study should be further validated using an external data set., (Copyright © 2023 Elsevier Inc. All rights reserved.) more...

Purpose: The aim of this study was to investigate the dosimetric and clinical effects of 4-dimensional computed tomography (4DCT)-based longitudinal dose accumulation in patients with locally advanced non-small cell lung cancer treated with standard-fractionated intensity-modulated radiation therapy (IMRT)., Methods and Materials: Sixty-seven patients were retrospectively selected from a randomized clinical trial. Their original IMRT plan, planning and verification 4DCTs, and ∼4-month posttreatment follow-up CTs were imported into a commercial treatment planning system. Two deformable image registration algorithms were implemented for dose accumulation, and their accuracies were assessed. The planned and accumulated doses computed using average-intensity images or phase images were compared. At the organ level, mean lung dose and normal-tissue complication probability (NTCP) for grade ≥2 radiation pneumonitis were compared. At the region level, mean dose in lung subsections and the volumetric overlap between isodose intervals were compared. At the voxel level, the accuracy in estimating the delivered dose was compared by evaluating the fit of a dose versus radiographic image density change (IDC) model. The dose-IDC model fit was also compared for subcohorts based on the magnitude of NTCP difference (|ΔNTCP|) between planned and accumulated doses., Results: Deformable image registration accuracy was quantified, and the uncertainty was considered for the voxel-level analysis. Compared with planned doses, accumulated doses on average resulted in <1-Gy lung dose increase and <2% NTCP increase (up to 8.2 Gy and 18.8% for a patient, respectively). Volumetric overlap of isodose intervals between the planned and accumulated dose distributions ranged from 0.01 to 0.93. Voxel-level dose-IDC models demonstrated a fit improvement from planned dose to accumulated dose (pseudo-R 2 increased 0.0023) and a further improvement for patients with ≥2% |ΔNTCP| versus for patients with <2% |ΔNTCP|., Conclusions: With a relatively large cohort, robust image registrations, multilevel metric comparisons, and radiographic image-based evidence, we demonstrated that dose accumulation more accurately represents the delivered dose and can be especially beneficial for patients with greater longitudinal response., (Copyright © 2023 Elsevier Inc. All rights reserved.) more...

Purpose: Evidence of a volume-outcome association in cancer surgery has shaped the centralization of cancer services; however, it is unknown whether a similar association exists for radiation therapy. The objective of this study was to determine the association between radiation therapy treatment volume and patient outcomes., Methods and Materials: This systematic review and meta-analysis included studies that compared outcomes of patients who underwent definitive radiation therapy at high-volume radiation therapy facilities (HVRFs) versus low-volume facilities (LVRFs). The systematic review used Ovid MEDLINE and Embase. For the meta-analysis, a random effects model was used. Absolute effects and hazard ratios (HRs) were used to compare patient outcomes., Results: The search identified 20 studies assessing the association between radiation therapy volume and patient outcomes. Seven of the studies looked at head and neck cancers (HNCs). The remaining studies covered cervical (4), prostate (4), bladder (3), lung (2), anal (2), esophageal (1), brain (2), liver (1), and pancreatic cancer (1). The meta-analysis demonstrated that HVRFs were associated with a lower chance of death compared with LVRFs (pooled HR, 0.90; 95% CI, 0.87- 0.94). HNCs had the strongest evidence of a volume-outcome association for both nasopharyngeal cancer (pooled HR, 0.74; 95% CI, 0.62-0.89) and nonnasopharyngeal HNC subsites (pooled HR, 0.80; 95% CI, 0.75-0.84), followed by prostate cancer (pooled HR, 0.92; 95% CI, 0.86-0.98). The remaining cancer types showed weak evidence of an association. The results also demonstrate that some centers defined as HVRFs are undertaking very few procedures per annum (<5 radiation therapy cases per year)., Conclusions: An association between radiation therapy treatment volume and patient outcomes exists for most cancer types. Centralization of radiation therapy services should be considered for cancer types with the strongest volume-outcome association, but the effect on equitable access to services needs to be explicitly considered., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.) more...

Purpose: Complicating factors such as time pressures, anatomic variants in the spine, and similarities in adjacent vertebrae are associated with incorrect level treatments of the spine. The purpose of this work was to mitigate such challenges by fully automating the treatment planning process for diagnostic and simulation computed tomography (CT) scans., Methods and Materials: Vertebral bodies are labeled on CT scans of any length using 2 intendent deep-learning models-mirroring 2 different experts labeling the spine. Then, a U-Net++ architecture was trained, validated, and tested to contour each vertebra (n = 220 CT scans). Features from the CT and auto-contours were input into a random forest classifier to predict whether vertebrae were correctly labeled. This classifier was trained using auto-contours from cone beam computed tomography, positron emission tomography/CT, simulation CT, and diagnostic CT images (n = 56 CT scans, 751 contours). Auto-plans were generated via scripting. Each model was combined into a framework to make a fully automated clinical tool. A retrospective planning study was conducted in which 3 radiation oncologists scored auto-plan quality on an unseen patient cohort (n = 60) on a 5-point scale. CT scans varied in scan length, presence of surgical implants, imaging protocol, and metastatic burden., Results: The results showed that the uniquely designed convolutional neural networks accurately labeled and segmented vertebral bodies C1-L5 regardless of imaging protocol or metastatic burden. Mean dice-similarity coefficient was 85.0% (cervical), 90.3% (thoracic), and 93.7% (lumbar). The random forest classifier predicted mislabeling across various CT scan types with an area under the curve of 0.82. All contouring and labeling errors within treatment regions (11 of 11), including errors from patient plans with atypical anatomy (eg, T13, L6) were detected. Radiation oncologists scored 98% of simulation CT-based plans and 92% of diagnostic CT-based plans as clinically acceptable or needing minor edits for patients with typical anatomy. On average, end-to-end treatment planning time of the clinical tool was less than 8 minutes., Conclusions: This novel method to automatically verify, contour, and plan palliative spine treatments is efficient and effective across various CT scan types. Furthermore, it is the first to create a clinical tool that can automatically verify vertebral level in CT images., (Published by Elsevier Inc.) more...

Purpose: This study investigated deep learning models for automatic segmentation to support the development of daily online dose optimization strategies, eliminating the need for internal target volume expansions and thereby reducing toxicity events of intensity modulated radiation therapy for cervical cancer., Methods and Materials: The cervix-uterus, vagina, parametrium, bladder, rectum, sigmoid, femoral heads, kidneys, spinal cord, and bowel bag were delineated on 408 computed tomography (CT) scans from patients treated at MD Anderson Cancer Center (n = 214), Polyclinique Bordeaux Nord Aquitaine (n = 30), and enrolled in a Medical Image Computing & Computer Assisted Intervention challenge (n = 3). The data were divided into 255 training, 61 validation, 62 internal test, and 30 external test CT scans. Two models were investigated: the 2-dimensional (2D) DeepLabV3+ (Google) and 3-dimensional (3D) Unet in RayStation (RaySearch Laboratories). Three intensity modulated radiation therapy plans were generated on each CT of the internal and external test sets using either the manual, 2D model, or 3D model segmentations. The dose constraints followed the External beam radiochemotherapy and MRI based adaptive BRAchytherapy in locally advanced CErvical cancer (EMBRACE) II protocol, with reduced margins of 5 and 3 mm for the target and nodal planning target volume. Geometric discrepancies between the manual and predicted contours were assessed using the Dice similarity coefficient (DSC), distance-to-agreement, and Hausdorff distance. Dosimetric discrepancies between the manual and model doses were assessed using clinical indices on the manual contours and the gamma index. Interobserver variability was assessed for the cervix-uterus, parametrium, and vagina for the definition of the primary clinical target volume (CTV T ) on the external test set., Results: Average DSCs across all organs were 0.67 to 0.96, 0.71 to 0.97, and 0.42 to 0.92 for the 2D model and 0.66 to 0.96, 0.70 to 0.97, and 0.37 to 0.93 for the 3D model on the validation, internal, and external test sets. Average DSCs of the CTV T were 0.88 and 0.81 for the 2D model and 0.87 and 0.82 for the 3D model on the internal and external test sets. Interobserver variability of the CTV T corresponded to a mean (range) DSC of 0.85 (0.77-0.90) on the external test set. On the internal test set, the doses from the 2D and 3D model contours provided a CTV T V42.75 Gy >98% for 98% and 91% of the CT scans, respectively. On the external test set, these percentages were increased to 100% and 93% for the 2D and 3D models, respectively., Conclusions: The investigated models provided auto-segmentation of the cervix anatomy with similar performances on 2 institutional data sets and reasonable dosimetric accuracies using small planning target volume margins, paving the way to automatic online dose optimization for advanced adaptive radiation therapy strategies., (Copyright © 2020 Elsevier Inc. All rights reserved.) more...

Purpose: To develop a deep learning model that generates consistent, high-quality lymph node clinical target volumes (CTV) contours for head and neck cancer (HNC) patients, as an integral part of a fully automated radiation treatment planning workflow., Methods and Materials: Computed tomography (CT) scans from 71 HNC patients were retrospectively collected and split into training (n = 51), cross-validation (n = 10), and test (n = 10) data sets. All had target volume delineations covering lymph node levels Ia through V (Ia-V), Ib through V (Ib-V), II through IV (II-IV), and retropharyngeal (RP) nodes, which were previously approved by a radiation oncologist specializing in HNC. Volumes of interest (VOIs) about nodal levels were automatically identified using computer vision techniques. The VOI (cropped CT image) and approved contours were used to train a U-Net autosegmentation model. Each lymph node level was trained independently, with model parameters optimized by assessing performance on the cross-validation data set. Once optimal model parameters were identified, overlap and distance metrics were calculated between ground truth and autosegmentations on the test set. Lastly, this final model was used on 32 additional patient scans (not included in original 71 cases) and autosegmentations visually rated by 3 radiation oncologists as being "clinically acceptable without requiring edits," "requiring minor edits," or "requiring major edits.", Results: When comparing ground truths to autosegmentations on the test data set, median Dice Similarity Coefficients were 0.90, 0.90, 0.89, and 0.81, and median mean surface distance values were 1.0 mm, 1.0 mm, 1.1 mm, and 1.3 mm for node levels Ia-V, Ib-V, II-IV, and RP nodes, respectively. Qualitative scoring varied among physicians. Overall, 99% of autosegmented target volumes were either scored as being clinically acceptable or requiring minor edits (ie, stylistic recommendations, <2 minutes)., Conclusions: We developed a fully automated artificial intelligence approach to autodelineate nodal CTVs for patients with intact HNC. Most autosegmentations were found to be clinically acceptable after qualitative review when considering recommended stylistic edits. This promising work automatically delineates nodal CTVs in a robust and consistent manner; this approach can be implemented in ongoing efforts for fully automated radiation treatment planning., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.) more...

Purpose: To develop and validate a radiomics signature that can predict the clinical outcomes for patients with stage I non-small cell lung cancer (NSCLC)., Methods and Materials: We retrospectively analyzed contrast-enhanced computed tomography images of patients from a training cohort (n = 147) treated with surgery and an independent validation cohort (n = 295) treated with stereotactic ablative radiation therapy. Twelve radiomics features with established strategies for filtering and preprocessing were extracted. The random survival forests (RSF) method was used to build models from subsets of the 12 candidate features based on their survival relevance and generate a mortality risk index for each observation in the training set. An optimal model was selected, and its ability to predict clinical outcomes was evaluated in the validation set using predicted mortality risk indexes., Results: The optimal RSF model, consisting of 2 predictive features, kurtosis and the gray level co-occurrence matrix feature homogeneity2, allowed for significant risk stratification (log-rank P < .0001) and remained an independent predictor of overall survival after adjusting for age, tumor volume and histologic type, and Karnofsky performance status (hazard ratio [HR] 1.27; P < 2e-16) in the training set. The resultant mortality risk indexes were significantly associated with overall survival in the validation set (log-rank P = .0173; HR 1.02, P = .0438). They were also significant for distant metastasis (log-rank P < .05; HR 1.04, P = .0407) and were borderline significant for regional recurrence on univariate analysis (log-rank P < .05; HR 1.04, P = .0617)., Conclusions: Our radiomics model accurately predicted several clinical outcomes and allowed pretreatment risk stratification in stage I NSCLC, allowing the choice of treatment to be tailored to each patient's individual risk profile., (Copyright © 2017 Elsevier Inc. All rights reserved.) more...

Purpose: Automating and standardizing the contouring of clinical target volumes (CTVs) can reduce interphysician variability, which is one of the largest sources of uncertainty in head and neck radiation therapy. In addition to using uniform margin expansions to auto-delineate high-risk CTVs, very little work has been performed to provide patient- and disease-specific high-risk CTVs. The aim of the present study was to develop a deep neural network for the auto-delineation of high-risk CTVs., Methods and Materials: Fifty-two oropharyngeal cancer patients were selected for the present study. All patients were treated at The University of Texas MD Anderson Cancer Center from January 2006 to August 2010 and had previously contoured gross tumor volumes and CTVs. We developed a deep learning algorithm using deep auto-encoders to identify physician contouring patterns at our institution. These models use distance map information from surrounding anatomic structures and the gross tumor volume as input parameters and conduct voxel-based classification to identify voxels that are part of the high-risk CTV. In addition, we developed a novel probability threshold selection function, based on the Dice similarity coefficient (DSC), to improve the generalization of the predicted volumes. The DSC-based function is implemented during an inner cross-validation loop, and probability thresholds are selected a priori during model parameter optimization. We performed a volumetric comparison between the predicted and manually contoured volumes to assess our model., Results: The predicted volumes had a median DSC value of 0.81 (range 0.62-0.90), median mean surface distance of 2.8 mm (range 1.6-5.5), and median 95th Hausdorff distance of 7.5 mm (range 4.7-17.9) when comparing our predicted high-risk CTVs with the physician manual contours., Conclusions: These predicted high-risk CTVs provided close agreement to the ground-truth compared with current interobserver variability. The predicted contours could be implemented clinically, with only minor or no changes., (Copyright © 2018 Elsevier Inc. All rights reserved.) more...

Purpose: To determine whether there exists any significant difference in normal tissue toxicity between intensity modulated radiation therapy (IMRT) or proton therapy for the treatment of non-small cell lung cancer., Methods and Materials: A total of 134 study patients (n=49 treated with proton therapy, n=85 with IMRT) treated in a randomized trial had a previously validated esophageal toxicity imaging biomarker, esophageal expansion, quantified during radiation therapy, as well as esophagitis grade (Common Terminology Criteria for Adverse Events version 3.0), on a weekly basis during treatment. Differences between the 2 modalities were statically analyzed using the imaging biomarker metric value (Kruskal-Wallis analysis of variance), as well as the incidence and severity of esophagitis grade (χ 2 and Fisher exact tests, respectively). The dose-response of the imaging biomarker was also compared between modalities using esophageal equivalent uniform dose, as well as delivered dose to an isotropic esophageal subvolume., Results: No statistically significant difference in the distribution of esophagitis grade, the incidence of grade ≥3 esophagitis (15 and 11 patients treated with IMRT and proton therapy, respectively), or the esophageal expansion imaging biomarker between cohorts (P>.05) was found. The distribution of imaging biomarker metric values had similar distributions between treatment arms, despite a slightly higher dose volume in the proton arm (P>.05). Imaging biomarker dose-response was similar between modalities for dose quantified as esophageal equivalent uniform dose and delivered esophageal subvolume dose. Regardless of treatment modality, there was high variability in imaging biomarker response, as well as esophagitis grade, for similar esophageal doses between patients., Conclusions: There was no significant difference in esophageal toxicity from either proton- or photon-based radiation therapy as quantified by esophagitis grade or the esophageal expansion imaging biomarker., (Copyright © 2017 Elsevier Inc. All rights reserved.) more...

Purpose: We sought to investigate the ability of mid-treatment (18)F-fluorodeoxyglucose positron emission tomography (PET) studies to objectively and spatially quantify esophageal injury in vivo from radiation therapy for non-small cell lung cancer., Methods and Materials: This retrospective study was approved by the local institutional review board, with written informed consent obtained before enrollment. We normalized (18)F-fluorodeoxyglucose PET uptake to each patient's low-irradiated region (<5 Gy) of the esophagus, as a radiation response measure. Spatially localized metrics of normalized uptake (normalized standard uptake value [nSUV]) were derived for 79 patients undergoing concurrent chemoradiation therapy for non-small cell lung cancer. We used nSUV metrics to classify esophagitis grade at the time of the PET study, as well as maximum severity by treatment completion, according to National Cancer Institute Common Terminology Criteria for Adverse Events, using multivariate least absolute shrinkage and selection operator (LASSO) logistic regression and repeated 3-fold cross validation (training, validation, and test folds). This 3-fold cross-validation LASSO model procedure was used to predict toxicity progression from 43 asymptomatic patients during the PET study. Dose-volume metrics were also tested in both the multivariate classification and the symptom progression prediction analyses. Classification performance was quantified with the area under the curve (AUC) from receiver operating characteristic analysis on the test set from the 3-fold analyses., Results: Statistical analysis showed increasing nSUV is related to esophagitis severity. Axial-averaged maximum nSUV for 1 esophageal slice and esophageal length with at least 40% of axial-averaged nSUV both had AUCs of 0.85 for classifying grade 2 or higher esophagitis at the time of the PET study and AUCs of 0.91 and 0.92, respectively, for maximum grade 2 or higher by treatment completion. Symptom progression was predicted with an AUC of 0.75. Dose metrics performed poorly at classifying esophagitis (AUC of 0.52, grade 2 or higher mid treatment) or predicting symptom progression (AUC of 0.67)., Conclusions: Normalized uptake can objectively, locally, and noninvasively quantify esophagitis during radiation therapy and predict eventual symptoms from asymptomatic patients. Normalized uptake may provide patient-specific dose-response information not discernible from dose., Competing Interests: No authors have any conflicts of interest associated with this work., (Copyright © 2016 Elsevier Inc. All rights reserved.) more...

Purpose: To study radiation-induced esophageal expansion as an objective measure of radiation esophagitis in patients with non-small cell lung cancer (NSCLC) treated with intensity modulated radiation therapy., Methods and Materials: Eighty-five patients had weekly intra-treatment CT imaging and esophagitis scoring according to Common Terminlogy Criteria for Adverse Events 4.0, (24 Grade 0, 45 Grade 2, and 16 Grade 3). Nineteen esophageal expansion metrics based on mean, maximum, spatial length, and volume of expansion were calculated as voxel-based relative volume change, using the Jacobian determinant from deformable image registration between the planning and weekly CTs. An anatomic variability correction method was validated and applied to these metrics to reduce uncertainty. An analysis of expansion metrics and radiation esophagitis grade was conducted using normal tissue complication probability from univariate logistic regression and Spearman rank for grade 2 and grade 3 esophagitis endpoints, as well as the timing of expansion and esophagitis grade. Metrics' performance in classifying esophagitis was tested with receiver operating characteristic analysis., Results: Expansion increased with esophagitis grade. Thirteen of 19 expansion metrics had receiver operating characteristic area under the curve values >0.80 for both grade 2 and grade 3 esophagitis endpoints, with the highest performance from maximum axial expansion (MaxExp1) and esophageal length with axial expansion ≥30% (LenExp30%) with area under the curve values of 0.93 and 0.91 for grade 2, 0.90 and 0.90 for grade 3 esophagitis, respectively., Conclusions: Esophageal expansion may be a suitable objective measure of esophagitis, particularly maximum axial esophageal expansion and esophageal length with axial expansion ≥30%, with 2.1 Jacobian value and 98.6 mm as the metric value for 50% probability of grade 3 esophagitis. The uncertainty in esophageal Jacobian calculations can be reduced with anatomic correction methods., (Copyright © 2016 Elsevier Inc. All rights reserved.) more...

Purpose: To determine whether previously identified quantitative image features (QIFs) based on (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) (co-occurrence matrix energy and solidity) are able to isolate subgroups of patients who would receive a benefit or detriment from dose escalation in terms of overall survival (OS) or progression-free survival (PFS)., Methods and Materials: Subgroups of a previously analyzed 225 patient cohort were generated with the use of 5-percentile increment cutoff values of disease solidity and primary tumor co-occurrence matrix energy. The subgroups were analyzed with a log-rank test to determine whether there was a difference in OS and PFS between patients treated with 60 to 70 Gy and those receiving 74 Gy., Results: In the entire patient cohort, there was no statistical difference in terms of OS or PFS between patients receiving 74 Gy and those receiving 60 to 70 Gy. It was qualitatively observed that as disease solidity and primary co-occurrence matrix energy increased, patients receiving 74 Gy had an improved OS and PFS compared with those receiving 60 to 70 Gy. The opposite trend (detriment of receiving 74 Gy) was also observed regarding low values of disease solidity and primary co-occurrence matrix energy., Conclusions: FDG-PET-based QIFs were found to be capable of isolating subgroups of patients who received a benefit or detriment from dose escalation., (Copyright © 2016 Elsevier Inc. All rights reserved.) more...

Purpose: To determine whether pretreatment CT texture features can improve patient risk stratification beyond conventional prognostic factors (CPFs) in stage III non-small cell lung cancer (NSCLC)., Methods and Materials: We retrospectively reviewed 91 cases with stage III NSCLC treated with definitive chemoradiation therapy. All patients underwent pretreatment diagnostic contrast enhanced computed tomography (CE-CT) followed by 4-dimensional CT (4D-CT) for treatment simulation. We used the average-CT and expiratory (T50-CT) images from the 4D-CT along with the CE-CT for texture extraction. Histogram, gradient, co-occurrence, gray tone difference, and filtration-based techniques were used for texture feature extraction. Penalized Cox regression implementing cross-validation was used for covariate selection and modeling. Models incorporating texture features from the 33 image types and CPFs were compared to those with models incorporating CPFs alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Patients were stratified based on whether their predicted outcome was above or below the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients and quantified using concordance correlation coefficients (CCC). We compared models incorporating the reproducibility seen on test-retest scans to our original models and determined the classification reproducibility., Results: Models incorporating both texture features and CPFs demonstrated a significant improvement in risk stratification compared to models using CPFs alone for OS (P=.046), LRC (P=.01), and FFDM (P=.005). The average CCCs were 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility within our models yielded 80.4% (±3.7% SD), 78.3% (±4.0% SD), and 78.8% (±3.9% SD) classification reproducibility in terms of OS, LRC, and FFDM, respectively., Conclusions: Pretreatment tumor texture may provide prognostic information beyond that obtained from CPFs. Models incorporating feature reproducibility achieved classification rates of ∼80%. External validation would be required to establish texture as a prognostic factor., (Copyright © 2014 Elsevier Inc. All rights reserved.) more...

Purpose: To develop a new approach for interobserver variability analysis., Methods and Materials: Eight radiation oncologists specializing in breast cancer radiation therapy delineated a patient's left breast "from scratch" and from a template that was generated using deformable image registration. Three of the radiation oncologists had previously received training in Radiation Therapy Oncology Group consensus contouring for breast cancer atlas. The simultaneous truth and performance level estimation algorithm was applied to the 8 contours delineated "from scratch" to produce a group consensus contour. Individual Jaccard scores were fitted to a beta distribution model. We also applied this analysis to 2 or more patients, which were contoured by 9 breast radiation oncologists from 8 institutions., Results: The beta distribution model had a mean of 86.2%, standard deviation (SD) of ±5.9%, a skewness of -0.7, and excess kurtosis of 0.55, exemplifying broad interobserver variability. The 3 RTOG-trained physicians had higher agreement scores than average, indicating that their contours were close to the group consensus contour. One physician had high sensitivity but lower specificity than the others, which implies that this physician tended to contour a structure larger than those of the others. Two other physicians had low sensitivity but specificity similar to the others, which implies that they tended to contour a structure smaller than the others. With this information, they could adjust their contouring practice to be more consistent with others if desired. When contouring from the template, the beta distribution model had a mean of 92.3%, SD ± 3.4%, skewness of -0.79, and excess kurtosis of 0.83, which indicated a much better consistency among individual contours. Similar results were obtained for the analysis of 2 additional patients., Conclusions: The proposed statistical approach was able to measure interobserver variability quantitatively and to identify individuals who tended to contour differently from the others. The information could be useful as feedback to improve contouring consistency., (Copyright © 2014 Elsevier Inc. All rights reserved.) more...

Purpose: The purpose of this work was to determine the expansions in 6 anatomic directions that produced optimal margins considering nonrigid setup errors and tissue deformation for patients receiving image-guided radiation therapy (IGRT) of the oropharynx., Methods and Materials: For 20 patients who had received IGRT to the head and neck, we deformably registered each patient's daily images acquired with a computed tomography (CT)-on-rails system to his or her planning CT. By use of the resulting vector fields, the positions of volume elements within the clinical target volume (CTV) (target voxels) or within a 1-cm shell surrounding the CTV (normal tissue voxels) on the planning CT were identified on each daily CT. We generated a total of 15,625 margins by dilating the CTV by 1, 2, 3, 4, or 5 mm in the posterior, anterior, lateral, medial, inferior, and superior directions. The optimal margins were those that minimized the relative volume of normal tissue voxels positioned within the margin while satisfying 1 of 4 geometric target coverage criteria and 1 of 3 population criteria., Results: Each pair of geometric target coverage and population criteria resulted in a unique, anisotropic, optimal margin. The optimal margin expansions ranged in magnitude from 1 to 5 mm depending on the anatomic direction of the expansion and on the geometric target coverage and population criteria. Typically, the expansions were largest in the medial direction, were smallest in the lateral direction, and increased with the demand of the criteria. The anisotropic margin resulting from the optimal set of expansions always included less normal tissue than did any isotropic margin that satisfied the same pair of criteria., Conclusions: We demonstrated the potential of anisotropic margins to reduce normal tissue exposure without compromising target coverage in IGRT to the head and neck., (Copyright © 2013 Elsevier Inc. All rights reserved.) more...

Purpose: To quantify and compare the effects of respiratory motion on paired passively scattered proton therapy (PSPT) and intensity modulated photon therapy (IMRT) plans; and to establish the relationship between the magnitude of tumor motion and the respiratory-induced dose difference for both modalities., Methods and Materials: In a randomized clinical trial comparing PSPT and IMRT, radiation therapy plans have been designed according to common planning protocols. Four-dimensional (4D) dose was computed for PSPT and IMRT plans for a patient cohort with respiratory motion ranging from 3 to 17 mm. Image registration and dose accumulation were performed using grayscale-based deformable image registration algorithms. The dose-volume histogram (DVH) differences (4D-3D [3D = 3-dimensional]) were compared for PSPT and IMRT. Changes in 4D-3D dose were correlated to the magnitude of tumor respiratory motion., Results: The average 4D-3D dose to 95% of the internal target volume was close to zero, with 19 of 20 patients within 1% of prescribed dose for both modalities. The mean 4D-3D between the 2 modalities was not statistically significant (P<.05) for all dose-volume histogram indices (mean ± SD) except the lung V5 (PSPT: +1.1% ± 0.9%; IMRT: +0.4% ± 1.2%) and maximum cord dose (PSPT: +1.5 ± 2.9 Gy; IMRT: 0.0 ± 0.2 Gy). Changes in 4D-3D dose were correlated to tumor motion for only 2 indices: dose to 95% planning target volume, and heterogeneity index., Conclusions: With our current margin formalisms, target coverage was maintained in the presence of respiratory motion up to 17 mm for both PSPT and IMRT. Only 2 of 11 4D-3D indices (lung V5 and spinal cord maximum) were statistically distinguishable between PSPT and IMRT, contrary to the notion that proton therapy will be more susceptible to respiratory motion. Because of the lack of strong correlations with 4D-3D dose differences in PSPT and IMRT, the extent of tumor motion was not an adequate predictor of potential dosimetric error caused by breathing motion., (Copyright © 2013 Elsevier Inc. All rights reserved.) more...

Purpose: To evaluate a method for quantifying the effect of setup errors and range uncertainties on dose distribution and dose-volume histogram using statistical parameters; and to assess existing planning practice in selected treatment sites under setup and range uncertainties., Methods and Materials: Twenty passively scattered proton lung cancer plans, 10 prostate, and 1 brain cancer scanning-beam proton plan(s) were analyzed. To account for the dose under uncertainties, we performed a comprehensive simulation in which the dose was recalculated 600 times per given plan under the influence of random and systematic setup errors and proton range errors. On the basis of simulation results, we determined the probability of dose variations and calculated the expected values and standard deviations of dose-volume histograms. The uncertainties in dose were spatially visualized on the planning CT as a probability map of failure to target coverage or overdose of critical structures., Results: The expected value of target coverage under the uncertainties was consistently lower than that of the nominal value determined from the clinical target volume coverage without setup error or range uncertainty, with a mean difference of -1.1% (-0.9% for breath-hold), -0.3%, and -2.2% for lung, prostate, and a brain cases, respectively. The organs with most sensitive dose under uncertainties were esophagus and spinal cord for lung, rectum for prostate, and brain stem for brain cancer., Conclusions: A clinically feasible robustness plan analysis tool based on direct dose calculation and statistical simulation has been developed. Both the expectation value and standard deviation are useful to evaluate the impact of uncertainties. The existing proton beam planning method used in this institution seems to be adequate in terms of target coverage. However, structures that are small in volume or located near the target area showed greater sensitivity to uncertainties., (Copyright © 2013 Elsevier Inc. All rights reserved.) more...

Purpose: To evaluate early swallowing after intensity-modulated radiotherapy for head and neck squamous cell carcinoma and determine factors correlating with aspiration and/or stricture., Methods and Materials: Consecutive patients treated with intensity-modulated radiotherapy with or without chemotherapy between September 2004 and August 2006 at the Dana Farber Cancer Institute/Brigham and Women's Hospital were evaluated with institutional review board approval. Patients underwent swallowing evaluation after completion of therapy; including video swallow studies. The clinical- and treatment-related variables were examined for correlation with aspiration or strictures, as well as doses to the larynx, pharyngeal constrictor muscles, and cervical esophagus. The correlation was assessed with logistic regression analysis., Results: A total of 96 patients were evaluated. Their median age was 55 years, and 79 (82%) were men. The primary site of cancer was the oropharynx in 43, hypopharynx/larynx in 17, oral cavity in 13, nasopharynx in 11, maxillary sinus in 2, and unknown primary in 10. Of the 96 patients, 85% underwent definitive RT and 15% postoperative RT. Also, 28 patients underwent induction chemotherapy followed by concurrent chemotherapy, 59 received concurrent chemotherapy, and 9 patients underwent RT alone. The median follow-up was 10 months. Of the 96 patients, 31 (32%) had clinically significant aspiration and 36 (37%) developed a stricture. The radiation dose-volume metrics, including the volume of the larynx receiving >or=50 Gy (p = 0.04 and p = 0.03, respectively) and volume of the inferior constrictor receiving >or=50 Gy (p = 0.05 and p = 0.02, respectively) were significantly associated with both aspiration and stricture. The mean larynx dose correlated with aspiration (p = 0.003). Smoking history was the only clinical factor to correlate with stricture (p = 0.05) but not aspiration., Conclusion: Aspiration and stricture are common side effects after intensity-modulated radiotherapy for head-and-neck squamous cell carcinoma. The dose given to the larynx and inferior constrictors correlated with these side effects. more...

Purpose: To improve the target coverage and normal tissue sparing of intensity-modulated radiotherapy (IMRT) for mesothelioma after extrapleural pneumonectomy., Methods and Materials: Thirteen plans from patients previously treated with IMRT for mesothelioma were replanned using a restricted field technique. This technique was novel in two ways. It limited the entrance beams to 200 degrees around the target and three to four beams per case had their field apertures restricted down to the level of the heart or liver to further limit the contralateral lung dose. New constraints were added that included a mean lung dose of <9.5 Gy and volume receiving >or=5 Gy of <55%., Results: In all cases, the planning target volume coverage was excellent, with an average of 97% coverage of the planning target volume by the target dose. No change was seen in the target coverage with the new technique. The heart, kidneys, and esophagus were all kept under tolerance in all cases. The average mean lung dose, volume receiving >or=20 Gy, and volume receiving >or=5 Gy with the new technique was 6.6 Gy, 3.0%, and 50.8%, respectively, compared with 13.8 Gy, 15%, and 90% with the previous technique (p < 0.0001 for all three comparisons). The maximal value for any case in the cohort was 8.0 Gy, 7.3%, and 57.5% for the mean lung dose, volume receiving >or=20 Gy, and volume receiving >or=5 Gy, respectively., Conclusion: Restricted field IMRT provides an improved method to deliver IMRT to a complex target after extrapleural pneumonectomy. An upcoming Phase I trial will provide validation of these results. more...

Purpose: To investigate experimentally the impact of different head-and-neck intensity-modulated radiation therapy (IMRT) planning techniques on doses to the skin and shallow targets., Methods and Materials: A semicylindrical phantom was constructed with micro-MOSFET dosimeters (Thomson-Nielson, Ottawa, Ontario, Canada) at 0-, 3-, 6-, 9-, and 12-mm depths. The planning target volume (PTV) was pulled back 0, 3, or 5 mm from the body contour. The IMRT plans were created to maximize PTV coverage, with one of the following strategies: (a) aim for a maximum 110% hotspot, with 115% allowed; (b) aims for a maximum 105% hotspot; (c) aims for a maximum 105% hotspot and 50% of skin to get a maximum 70% of the prescribed dose; and (d) aim for 99% of the PTV volume to receive 90-93% of prescribed dose, with a maximum 105% hotspot, and with the dose to the skin structure minimized. Doses delivered using a linear accelerator were measured. Setup uncertainty was simulated by intentionally shifting the phantom in a range of +/-8 mm, and calculating the delivered dose for a range of systematic and random uncertainties., Results: From lowest to highest skin dose, the planning strategies were in the order of c, d, b, and a, but c showed a tendency to underdose tissues at depth. Delivered doses varied by 10-20%, depending on planning strategy. For typical setup uncertainties, cumulative dose reduction to a point 6 mm deep was <4%., Conclusions: It is useful to use skin as a sensitive structure, but a minimum dose constraint must be used for the PTV if unwanted reductions in dose to nodes near the body surface are to be avoided. Setup uncertainties are unlikely to give excessive reductions in cumulative dose. more...

Purpose: To describe the initial experience at Dana-Farber Cancer Institute/Brigham and Women's Hospital with intensity-modulated radiation therapy (IMRT) as adjuvant therapy after extrapleural pneumonectomy (EPP) and adjuvant chemotherapy., Methods and Materials: The medical records of patients treated with IMRT after EPP and adjuvant chemotherapy were retrospectively reviewed. IMRT was given to a dose of 54 Gy to the clinical target volume in 1.8 Gy daily fractions. Treatment was delivered with a dynamic multileaf collimator using a sliding window technique. Eleven of 13 patients received heated intraoperative cisplatin chemotherapy (225 mg/m(2)). Two patients received neoadjuvant intravenous cisplatin/pemetrexed, and 10 patients received adjuvant cisplatin/pemetrexed chemotherapy after EPP but before radiation therapy. All patients received at least 2 cycles of intravenous chemotherapy. The contralateral lung was limited to a V20 (volume of lung receiving 20 Gy or more) of 20% and a mean lung dose (MLD) of 15 Gy. All patients underwent fluorodeoxyglucose positron emission tomography (FDG-PET) for staging, and any FDG-avid areas in the hemithorax were given a simultaneous boost of radiotherapy to 60 Gy. Statistical comparisons were done using two-sided t test., Results: Thirteen patients were treated with IMRT from December 2004 to September 2005. Six patients developed fatal pneumonitis after treatment. The median time from completion of IMRT to the onset of radiation pneumonitis was 30 days (range 5-57 days). Thirty percent of patients (4 of 13) developed acute Grade 3 nausea and vomiting. One patient developed acute Grade 3 thrombocytopenia. The median V20, MLD, and V5 (volume of lung receiving 5 Gy or more) for the patients who developed pneumonitis was 17.6% (range, 15.3-22.3%), 15.2 Gy (range, 13.3-17 Gy), and 98.6% (range, 81-100%), respectively, as compared with 10.9% (range, 5.5-24.7%) (p = 0.08), 12.9 Gy (range, 8.7-16.9 Gy) (p = 0.07), and 90% (range, 66-98.3%) (p = 0.20), respectively, for the patients who did not develop pneumonitis., Conclusions: Intensity-modulated RT treatment for mesothelioma after EPP and adjuvant chemotherapy resulted in a high rate of fatal pneumonitis when standard dose parameters were used. We therefore recommend caution in the utilization of this technique. Our data suggest that with IMRT, metrics such as V5 and MLD should be considered in addition to V20 to determine tolerance levels in future patients. more...

Purpose: To determine the effects of Fletcher Suit Delclos ovoid shielding on dose to the bladder and rectum during intracavitary radiotherapy for cervical cancer., Methods and Materials: The Monte Carlo method was used to calculate the dose in 12 patients receiving low-dose-rate intracavitary radiotherapy with both shielded and unshielded ovoids. Cumulative dose-difference surface histograms were computed for the bladder and rectum. Doses to the 2-cm(3) and 5-cm(3) volumes of highest dose were computed for the bladder and rectum with and without shielding., Results: Shielding affected dose to the 2-cm(3) and 5-cm(3) volumes of highest dose for the rectum (10.1% and 11.1% differences, respectively). Shielding did not have a major impact on the dose to the 2-cm(3) and 5-cm(3) volumes of highest dose for the bladder. The average dose reduction to 5% of the surface area of the bladder was 53 cGy. Reductions as large as 150 cGy were observed to 5% of the surface area of the bladder. The average dose reduction to 5% of the surface area of the rectum was 195 cGy. Reductions as large as 405 cGy were observed to 5% of the surface area of the rectum., Conclusions: Our data suggest that the ovoid shields can greatly reduce the radiation dose delivered to the rectum. We did not find the same degree of effect on the dose to the bladder. To calculate the dose accurately, however, the ovoid shields must be included in the dose model. more...

Purpose: To propose and evaluate online adaptive radiation therapy (ART) using in-room computed tomography (CT) imaging that detects changes in the target position and shape of the prostate and seminal vesicles (SVs) and then automatically modifies the multileaf collimator (MLC) leaf pairs in a slice-by-slice fashion., Methods and Materials: For intensity-modulated radiation therapy (IMRT) using a coplanar beam arrangement, each MLC leaf pair projects onto a specific anatomic slice. The proposed strategy assumes that shape deformation is a function of only the superior-inferior (SI) position. That is, there is no shape change within a CT slice, but each slice can be displaced in the anteroposterior (AP) or right-left (RL) direction relative to adjacent slices. First, global shifts (in SI, AP, and RL directions) were calculated by three-dimensional (3D) registration of the bulk of the prostate in the treatment planning CT images with the daily CT images taken immediately before treatment. Local shifts in the AP direction were then found using slice-by-slice registration, in which the CT slices were individually registered. The translational shift within a slice could then be projected to a translational shift in the position of the corresponding MLC leaf pair for each treatment segment for each gantry angle. Global shifts in the SI direction were accounted for by moving the open portal superiorly or inferiorly by an integral number of leaf pairs. The proposed slice-by-slice registration technique was tested by using daily CT images from 46 CT image sets (23 each from 2 patients) taken before the standard delivery of IMRT for prostate cancer. A dosimetric evaluation was carried out by using an 8-field IMRT plan., Results: The shifts and shape change of the prostate and SVs could be separated into 3D global shifts in the RL, AP, and SI directions, plus local shifts in the AP direction, which were different for each CT slice. The MLC leaf positions were successfully modified to compensate for these global shifts and local shape variations. The ART method improved geometric coverage of the prostate and SVs compared with the couch-shift method, particularly for the superior part of the prostate and all the SVs, for which the interfraction shape change was the largest. The dosimetric comparison showed that the ART method covered the target better and reduced the rectal dose more than a simple couch-translation method., Conclusions: ART corrected for interfraction changes in the position and shape of the prostate and SVs and gave dose distributions that were considerably closer to the planned dose distributions than could be achieved with simple alignment strategies that neglect shape change. The ART proposed in this investigation requires neither contouring of the daily CT images nor extensive calculations; therefore, it may prove to be an effective and clinically practical solution to the problem of interfraction shape changes. more...

Purpose: Many patients receiving fractionated radiotherapy (RT) for head-and-neck cancer have marked anatomic changes during their course of treatment, including shrinking of the primary tumor or nodal masses, resolving postoperative changes/edema, and changes in overall body habitus/weight loss. We conducted a pilot study to quantify the magnitude of these anatomic changes with systematic CT imaging., Methods and Materials: Fourteen assessable patients were enrolled in this pilot study. Eligible patients had to have a pathologic diagnosis of head-and-neck cancer, be treated with definitive external beam RT, and had have gross primary and/or cervical nodal disease measuring at least 4 cm in maximal diameter. All patients were treated using a new commercial integrated CT-linear accelerator system (EXaCT) that allows CT imaging at the daily RT sessions while the patient remains immobilized in the treatment position. CT scans were acquired three times weekly during the entire course of RT, and both gross tumor volumes (GTVs: primary tumor and involved lymph nodes) and normal tissues (parotid glands, spinal canal, mandible, and external contour) were manually contoured on every axial slice. Volumetric and positional changes relative to a central bony reference (the center of mass of the C2 vertebral body) were determined for each structure., Results: Gross tumor volumes decreased throughout the course of fractionated RT, at a median rate of 0.2 cm(3) per treatment day (range, 0.01-1.95 cm(3)/d). In terms of the percentage of the initial volume, the GTVs decreased at a median rate of 1.8%/treatment day (range, 0.2-3.1%/d). On the last day of treatment, this corresponded to a median total relative loss of 69.5% of the initial GTV (range, 9.9-91.9%). In addition, the center of the mass of shrinking tumors changed position with time, indicating that GTV loss was frequently asymmetric. At treatment completion, the median center of the mass displacement (after corrections for daily setup variation) was 3.3 mm (range, 0-17.3 mm). Parotid glands also decreased in volume (median, 0.19 cm(3)/d range, 0.04-0.84 cm(3)/d), and generally shifted medially (median, 3.1 mm; range, 0-9.9 mm) with time. This medial displacement of the parotid glands correlated highly with the weight loss that occurred during treatment., Conclusion: Measurable anatomic changes occurred throughout fractionated external beam RT for head-and-neck cancers. These changes in the external contour, shape, and location of the target and critical structures appeared to be significant during the second half of treatment (after 3-4 weeks of treatment) and could have potential dosimetric impact when highly conformal treatment techniques are used. These data may, therefore, be useful in the development of an adaptive RT scheme (periodic adjustment of the conformal treatment plan) that takes into account such treatment-related anatomic changes. In theory, such a strategy would maximize the therapeutic ratio of RT. more...

Purpose: The recent introduction of integrated CT/linear accelerator systems may mean that daily CT localization can become a reality in the clinic, possibly allowing further dose escalation to the prostate while limiting unwanted doses to the rectum and bladder. However, the implementation of CT localization is currently impeded by the lack of precise and robust techniques to align the treatment plan with the daily CT images. The purpose of this study was to evaluate a manual alignment technique, in which the gross target volume contours are overlaid on the daily CT images and then shifted to match the structures visible in the images., Methods and Materials: A total of 28 CT image sets were taken before the standard delivery of intensity-modulated radiotherapy for prostate cancer for 2 patients. Seven observers (four radiation oncologists and three medical physicists) manually shifted the gross target volume contours from the treatment plan to best match the daily CT images. One observer repeated the process 1 week later to evaluate intraobserver variations. The experiment was then repeated, but the CT images from the original treatment plan were used as a reference to reduce interobserver uncertainty when aligning the contours. The shifts in prostate position found by different observers, both with and without reference data, were evaluated using a factorial analysis of variance to determine the standard errors of measurement for the intra- and interobserver uncertainty (SEM(intra) and SEM(inter), respectively). The differences in the SEM for the two groups of observers (radiation oncologists and medical physicists), the two alignment techniques (with and without reference information), and the two patients were evaluated using the t test at 90% confidence levels., Results: With no reference information, the SEM(inter) using one patient data set (Patient 1) was 0.8 mm, 2.0 mm, and 2.2 mm in the right-left (RL), anterior-posterior (AP), and superior-inferior (SI) directions, respectively. The use of the treatment plan as a reference reduced the SEM(inter) to 0.7 mm, 1.0 mm, and 1.6 mm in the RL, AP, and SI directions, respectively. In Patient 2, localization of the prostate was more difficult; the best SEM(inter) achieved with this patient was 0.8 mm, 1.9 mm, and 2.0 mm in the RL, AP, and SI directions, respectively. The SEM(intra) values with Patient 1 were also slightly better than with Patient 2. When reference data were used, the SEM(intra) value was 0.5 mm, 0.7 mm, and 0.5 mm for Patient 1 and 0.6 mm, 1.0 mm, and 0.7 mm for Patient 2 in the RL, AP, and SI directions, respectively. Despite the larger than expected interobserver variation reported here, the SEM(inter) was smaller than the typical day-to-day variation in prostate position. The contour alignment technique may still be useful to aid daily prostate localization or in a correction scheme to minimize the effect of target positional error., Conclusion: The interobserver uncertainties associated with aligning the gross target volume contours with daily CT images were sufficiently small that this method may be used for daily CT localization of the prostate. The use of a reference image is important to improve the consistency among different users in this technique. more...