Dawn Owen

Outcomes in Patients Treated With Mastectomy for Ductal Carcinoma In Situ

PURPOSE To examine, in a large, population-based cohort of women, the risk factors for recurrence after mastectomy for pure ductal carcinoma in situ (DCIS) and to identify which patients may benefit from postmastectomy radiation therapy. METHODS AND MATERIALS Data were analyzed for 637 subjects with pure DCIS, diagnosed between January 1990 and December 1999, treated initially with mastectomy. Locoregional relapse (LRR), breast cancer-specific survival, and overall survival were described using the Kaplan-Meier method. Reported risk factors for LRR (age, margins, size, Van Nuys Prognostic Index, grade, necrosis, and histologic subtype) were analyzed by univariate (log-rank) and multivariate (Cox modeling) methods. RESULTS Median follow-up was 12.0 years. Characteristics of the cohort were median age 55 years, 8.6% aged ≤ 40 years, 30.5% tumors >4 cm, 42.5% grade 3 histology, 37.7% multifocal disease, and 4.9% positive margins. At 10 years, LRR was 1.0%, breast cancer-specific survival was 98.0%, and overall survival was 90.3%. All recurrences (n=12) involved ipsilateral chest wall disease, with the majority being invasive disease (11 of 12). None of the 12 patients with recurrence died of breast cancer; all were successfully salvaged (median follow-up of 4.4 years). Ten-year LRR was higher with age ≤ 40 years (7.5% vs 1.5%; P=.003). CONCLUSION Mastectomy provides excellent locoregional control for DCIS. Routine use of postmastectomy radiation therapy is not justified. Young age (≤40 years) predicts slightly higher LRR, but possibly owing to the small number of cases with multiple risk factors for relapse, a subgroup with a high risk of LRR (ie, approximately 15%) was not identified.

Biomechanical deformable image registration of longitudinal lung CT images using vessel information.

Spatial correlation of lung tissue across longitudinal images, as the patient responds to treatment, is a critical step in adaptive radiotherapy. The goal of this work is to expand a biomechanical model-based deformable registration algorithm (Morfeus) to achieve accurate registration in the presence of significant anatomical changes. Six lung cancer patients previously treated with conventionally fractionated radiotherapy were retrospectively evaluated. Exhale CT scans were obtained at treatment planning and following three weeks of treatment. For each patient, the planning CT was registered to the follow-up CT using Morfeus, a biomechanical model-based deformable registration algorithm. To model the complex response of the lung, an extension to Morfeus has been developed: an initial deformation was estimated with Morfeus consisting of boundary conditions on the chest wall and incorporating a sliding interface with the lungs. It was hypothesized that the addition of boundary conditions based on vessel tree matching would provide a robust reduction of the residual registration error. To achieve this, the vessel trees were segmented on the two images by thresholding a vesselness image based on the Hessian matrixs eigenvalues. For each point on the reference vessel tree centerline, the displacement vector was estimated by applying a variant of the Demons registration algorithm between the planning CT and the deformed follow-up CT. An expert independently identified corresponding landmarks well distributed in the lung to compute target registration errors (TRE). The TRE was: [Formula: see text], [Formula: see text] and [Formula: see text] mm after rigid registration, Morfeus and Morfeus with boundary conditions on the vessel tree, respectively. In conclusion, the addition of boundary conditions on the vessels significantly improved the accuracy in modeling the response of the lung and tumor over the course of radiotherapy. Minimizing and modeling these geometrical uncertainties will enable future plan adaptation strategies.

An analysis of knowledge-based planning for stereotactic body radiation therapy of the spine

PURPOSE Planning for spine stereotactic body radiation therapy (SBRT) is time consuming, and differences in planner experience and technique result in discrepancies in plan quality between facilities. Here, knowledge-based planning is analyzed to determine if it may be effective in improving the quality and efficiency of spine SBRT planning. MATERIALS AND METHODS Thirty-eight spine SBRT cases were collected from the University of Michigan database and inverse planned to deliver 3 10-Gy fractions to the planning target volume (PTV). These plans were used to train a knowledge-based model (model A) using RapidPlan (Varian Medical Systems). The model was evaluated for outliers and validated in 10 independent cases. Each of these cases was manually planned to compare the quality of the model-generated plans with the manual plans. To further test the robustness of the software, 2 additional models (models B and C) were created with intentional outliers resulting from inconsistent contouring. RESULTS Using models A, B, and C, all 10 generated plans met all dose objectives for modeled organs at risk (OARs) (spinal cord, cord planning risk volume, and esophagus) without user intervention. The target coverage and OAR dose sparing was improved or equivalent to manual planning by an expert dosimetrist; however, manually created plans typically required 1 to 1.5 hours to produce and model-generated plans required only 10 to 15 minutes with minimal human intervention to meet all dose objectives. CONCLUSIONS The clinical quality of plans produced by RapidPlan were found to improve on or be similar to the manually created plans in terms of normal tissue objectives and PTV dose coverage and could be produced in a fraction of the time. RapidPlan is a robust technique that can improve planning efficiency in spine SBRT while maintaining or potentially improving plan quality and standardization across planners and centers.

Incorporating big data into treatment plan evaluation: Development of statistical DVH metrics and visualization dashboards

Purpose To develop statistical dose-volume histogram (DVH)–based metrics and a visualization method to quantify the comparison of treatment plans with historical experience and among different institutions. Methods and materials The descriptive statistical summary (ie, median, first and third quartiles, and 95% confidence intervals) of volume-normalized DVH curve sets of past experiences was visualized through the creation of statistical DVH plots. Detailed distribution parameters were calculated and stored in JavaScript Object Notation files to facilitate management, including transfer and potential multi-institutional comparisons. In the treatment plan evaluation, structure DVH curves were scored against computed statistical DVHs and weighted experience scores (WESs). Individual, clinically used, DVH-based metrics were integrated into a generalized evaluation metric (GEM) as a priority-weighted sum of normalized incomplete gamma functions. Historical treatment plans for 351 patients with head and neck cancer, 104 with prostate cancer who were treated with conventional fractionation, and 94 with liver cancer who were treated with stereotactic body radiation therapy were analyzed to demonstrate the usage of statistical DVH, WES, and GEM in a plan evaluation. A shareable dashboard plugin was created to display statistical DVHs and integrate GEM and WES scores into a clinical plan evaluation within the treatment planning system. Benchmarking with normal tissue complication probability scores was carried out to compare the behavior of GEM and WES scores. Results DVH curves from historical treatment plans were characterized and presented, with difficult-to-spare structures (ie, frequently compromised organs at risk) identified. Quantitative evaluations by GEM and/or WES compared favorably with the normal tissue complication probability Lyman-Kutcher-Burman model, transforming a set of discrete threshold-priority limits into a continuous model reflecting physician objectives and historical experience. Conclusions Statistical DVH offers an easy-to-read, detailed, and comprehensive way to visualize the quantitative comparison with historical experiences and among institutions. WES and GEM metrics offer a flexible means of incorporating discrete threshold-prioritizations and historic context into a set of standardized scoring metrics. Together, they provide a practical approach for incorporating big data into clinical practice for treatment plan evaluations.

Quantification of liver function by linearization of a two-compartment model of gadoxetic acid uptake using dynamic contrast-enhanced magnetic resonance imaging

Dynamic gadoxetic acid‐enhanced magnetic resonance imaging (MRI) allows the investigation of liver function through the observation of the perfusion and uptake of contrast agent in the parenchyma. Voxel‐by‐voxel quantification of the contrast uptake rate (k1) from dynamic gadoxetic acid‐enhanced MRI through the standard dual‐input, two‐compartment model could be susceptible to overfitting of variance in the data. The aim of this study was to develop a linearized, but more robust, model. To evaluate the estimated k1 values using this linearized analysis, high‐temporal‐resolution gadoxetic acid‐enhanced MRI scans were obtained in 13 examinations, and k1 maps were created using both models. Comparison of liver k1 values estimated from the two methods produced a median correlation coefficient of 0.91 across the 12 scans that could be used. Temporally sparse clinical MRI data with gadoxetic acid uptake were also employed to create k1 maps of 27 examinations using the linearized model. Of 20 scans, the created k1 maps were compared with overall liver function as measured by indocyanine green (ICG) retention, and yielded a correlation coefficient of 0.72. In the 27 k1 maps created via the linearized model, the mean liver k1 value was 3.93 ± 1.79 mL/100 mL/min, consistent with previous studies. The results indicate that the linearized model provides a simple and robust method for the assessment of the rate of contrast uptake that can be applied to both high‐temporal‐resolution dynamic contrast‐enhanced MRI and typical clinical multiphase MRI data, and that correlates well with the results of both two‐compartment analysis and independent whole liver function measurements.

Performance/outcomes data and physician process challenges for practical big data efforts in radiation oncology

It is an exciting time for big data efforts in radiation oncology. The use of big data to help aid both outcomes and decision-making research is becoming a reality. However, there are true challenges that exist in the space of gathering and utilizing performance and outcomes data. Here, we summarize the current state of big data in radiation oncology with respect to outcomes and discuss some of the efforts and challenges in radiation oncology big data.

Priority-driven plan optimization in locally advanced lung patients based on perfusion SPECT imaging

Purpose Limits on mean lung dose (MLD) allow for individualization of radiation doses at safe levels for patients with lung tumors. However, MLD does not account for individual differences in the extent or spatial distribution of pulmonary dysfunction among patients, which leads to toxicity variability at the same MLD. We investigated dose rearrangement to minimize the radiation dose to the functional lung as assessed by perfusion single photon emission computed tomography (SPECT) and maximize the target coverage to maintain conventional normal tissue limits. Methods and materials Retrospective plans were optimized for 15 patients with locally advanced non-small cell lung cancer who were enrolled in a prospective imaging trial. A staged, priority-based optimization system was used. The baseline priorities were to meet physical MLD and other dose constraints for organs at risk, and to maximize the target generalized equivalent uniform dose (gEUD). To determine the benefit of dose rearrangement with perfusion SPECT, plans were reoptimized to minimize the generalized equivalent uniform functional dose (gEUfD) to the lung as the subsequent priority. Results When only physical MLD is minimized, lung gEUfD was 12.6 ± 4.9 Gy (6.3-21.7 Gy). When the dose is rearranged to minimize gEUfD directly in the optimization objective function, 10 of 15 cases showed a decrease in lung gEUfD of >20% (lung gEUfD mean 9.9 ± 4.3 Gy, range 2.1-16.2 Gy) while maintaining equivalent planning target volume coverage. Although all dose-limiting constraints remained unviolated, the dose rearrangement resulted in slight gEUD increases to the cord (5.4 ± 3.9 Gy), esophagus (3.0 ± 3.7 Gy), and heart (2.3 ± 2.6 Gy). Conclusions Priority-driven optimization in conjunction with perfusion SPECT permits image guided spatial dose redistribution within the lung and allows for a reduced dose to the functional lung without compromising target coverage or exceeding conventional limits for organs at risk.

SU-E-T-97: An Analysis of Knowledge Based Planning for Stereotactic Body Radiation Therapy of the Spine

Purpose: Creating high quality SBRT treatment plans for the spine is often tedious and time consuming. In addition, the quality of treatment plans can vary greatly between treatment facilities due to inconsistencies in planning methods. This study investigates the performance of knowledge-based planning (KBP) for spine SBRT. Methods: Treatment plans were created for 28 spine SBRT patients. Each case was planned to meet strict dose objectives and guidelines. After physician and physicist approval, the plans were added to a custom model in a KBP system (RapidPlan, Varian Eclipse v13.5). The model was then trained to be able to predict estimated DVHs and provide starting objective functions for future patients based on both generated and manual objectives. To validate the model, ten additional spine SBRT cases were planned manually as well as using the model objectives. Plans were compared based on planning time and quality (ability to meet the plan objectives, including dose metrics and conformity). Results: The average dose to the spinal cord and the cord PRV differed between the validation and control plans by <0.25% demonstrating iso-toxicity. Six out of 10 validation plans met all dose objectives without the need for modifications, and overall, target dose coverage was increased by about 4.8%. If the validation plans did not meet the dose requirements initially, only 1–2 iterations of modifying the planning parameters were required before an acceptable plan was achieved. While manually created plans usually required 30 minutes to 3 hours to create, KBP can be used to create similar quality plans in 15–20 minutes. Conclusion: KBP for spinal tumors has shown to greatly decrease the amount of time required to achieve high quality treatment plans with minimal human intervention and could feasibly be used to standardize plan quality between institutions. Supported by Varian Medical Systems

Dosimetric impact of interfractional organs at risk variation during high-dose rate interstitial brachytherapy for gynecologic malignancies

We sought to develop a framework for the identification and management of patients at risk for organs at risk (OARs) overdosing due to interfractional anatomic variation during high-dose rate interstitial brachytherapy for gynecologic malignancies. We analyzed 40 high-dose rate interstitial brachytherapy fractions from 10 patients. Planned OAR doses were compared to delivered doses, which were calculated from computed tomography scans obtained prior to each treatment fraction. Doses were converted to equivalent doses in 2 Gy fractions (EQD2) and doses to the most exposed 2 cm3 (D2cc) were reviewed. Patients were risk-stratified by identifying dose thresholds corresponding to a 10% or lower risk of receiving an OAR dose exceeding the corresponding planning constraint. For each OAR, 30% to 62.5% of patients received total doses greater than planned, although the magnitude of these differences was <4 Gy in over 75% of cases. Using EMBRACE II guidelines, one patient who had met the planning constraint for bladder and one for small bowel were found to have received doses exceeding the recommended limits. We next calculated thresholds for estimating the risk of OAR overdosing in individual patients and developed a framework based on these thresholds to direct time- and resource-intensive imaging and replanning efforts toward patients who are most likely to derive benefit. In summary, differential OAR dosing due to interfractional anatomic variation is common but likely rarely clinically meaningful. The proposed framework could decrease toxicity and maximize clinical efficiency.

Effectiveness and cost of radiofrequency ablation and stereotactic body radiotherapy for treatment of early-stage hepatocellular carcinoma: An analysis of SEER-medicare.

For early‐stage hepatocellular carcinoma (HCC) patients, ablative strategies are potentially curative treatment options. Stereotactic body radiotherapy (SBRT) has emerged as a promising ablative therapy, although its comparison with radiofrequency ablation (RFA) remains confined to a single institution retrospective review. We sought to characterize the comparative outcomes and cost between the two treatment strategies.