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Kondziolka D.,NYU Langone Medical Center | Parry P.V.,University of Pittsburgh | Lunsford L.D.,University of Pittsburgh | Kano H.,University of Pittsburgh | And 16 more authors.
Journal of Neurosurgery | Year: 2014

Object. Estimating survival time in cancer patients is crucial for clinicians, patients, families, and payers. To provide appropriate and cost-effective care, various data sources are used to provide rational, reliable, and reproducible estimates. The accuracy of such estimates is unknown. Methods. The authors prospectively estimated survival in 150 consecutive cancer patients (median age 62 years) with brain metastases undergoing radiosurgery. They recorded cancer type, number of brain metastases, neurological presentation, extracranial disease status, Karnofsky Performance Scale score, Recursive Partitioning Analysis class, prior whole-brain radiotherapy, and synchronous or metachronous presentation. Finally, the authors asked 18 medical, radiation, or surgical oncologists to predict survival from the time of treatment. Results. The actual median patient survival was 10.3 months (95% CI 6.4-14). The median physician-predicted survival was 9.7 months (neurosurgeons = 11.8 months, radiation oncologists = 11.0 months, and medical oncologist = 7.2 months). For patients who died before 10 months, both neurosurgeons and radiation oncologists generally predicted survivals that were more optimistic and medical oncologists that were less so, although no group could accurately predict survivors alive at 14 months. All physicians had individual patient survival predictions that were incorrect by as much as 12-18 months, and 14 of 18 physicians had individual predictions that were in error by more than 18 months. Of the 2700 predictions, 1226 (45%) were off by more than 6 months and 488 (18%) were off by more than 12 months. Conclusions. Although crucial, predicting the survival of cancer patients is difficult. In this study all physicians were unable to accurately predict longer-term survivors. Despite valuable clinical data and predictive scoring techniques, brain and systemic management often led to patient survivals well beyond estimated survivals. ©AANS, 2014. Source


Varadhan R.,Minneapolis Radiation Oncology | Karangelis G.,Oncology Systems Ltd | Krishnan K.,Kitware | Hui S.,University of Minnesota
Journal of Applied Clinical Medical Physics | Year: 2013

Quantitative validation of deformable image registration (DIR) algorithms is extremely difficult because of the complexity involved in constructing a deformable phantom that can duplicate various clinical scenarios. The purpose of this study is to describe a framework to test the accuracy of DIR based on computational modeling and evaluating using inverse consistency and other methods. Three clinically relevant organ deformations were created in prostate (distended rectum and rectal gas), head and neck (large neck flexion), and lung (inhale and exhale lung volumes with variable contrast enhancement) study sets. DIR was performed using both B-spline and diffeomorphic demons algorithms in the forward and inverse direction. A compositive accumulation of forward and inverse deformation vector fields was done to quantify the inverse consistency error (ICE). The anatomical correspondence of tumor and organs at risk was quantified by comparing the original RT structures with those obtained after DIR. Further, the physical characteristics of the deformation field, namely the Jacobian and harmonic energy, were computed to quantify the preservation of image topology and regularity of spatial transformation obtained in DIR. The ICE was comparable in prostate case but the B-spline algorithm had significantly better anatomical correspondence for rectum and prostate than diffeomorphic demons algorithm. The ICE was 6.5 mm for demons algorithm for head and neck case when compared to 0.7 mm for B-spline. Since the induced neck flexion was large, the average Dice similarity coefficient between both algorithms was only 0.87, 0.52, 0.81, and 0.67 for tumor, cord, parotids, and mandible, respectively. The B-spline algorithm accurately estimated deformations between images with variable contrast in our lung study, while diffeomorphic demons algorithm led to gross errors on structures affected by contrast variation. The proposed framework offers the application of known deformations on any image datasets, to evaluate the overall accuracy and limitations of a DIR algorithm used in radiation oncology. The evaluation based on anatomical correspondence, physical characteristics of deformation field, and image characteristics can facilitate DIR verification with the ultimate goal of implementing adaptive radiotherapy. The suitability of application of a particular evaluation metric in validating DIR is dependent on the clinical deformation observed. Source


Sperduto P.W.,Minneapolis Radiation Oncology | Shanley R.,University of Minnesota | Luo X.,University of Minnesota | Andrews D.,Thomas Jefferson University | And 6 more authors.
International Journal of Radiation Oncology Biology Physics | Year: 2014

Purpose: Radiation Therapy Oncology Group (RTOG) 9508 showed a survival advantage for patients with 1 but not 2 or 3 brain metastasis (BM) treated with whole-brain radiation therapy (WBRT) and stereotactic radiosurgery (SRS) versus WBRT alone. An improved prognostic index, the graded prognostic assessment (GPA) has been developed. Our hypothesis was that if the data from RTOG 9508 were poststratified by the GPA, the conclusions may vary.Methods and Materials: In this analysis, 252 of the 331 patients were evaluable by GPA. Of those, 211 had lung cancer. Breast cancer patients were excluded because the components of the breast GPA are not in the RTOG database. Multiple Cox regression was used to compare survival between treatment groups, adjusting for GPA. Treatment comparisons within subgroups were performed with the log-rank test. A free online tool (brainmetgpa.com) simplified GPA use.Results: The fundamental conclusions of the primary analysis were confirmed in that there was no survival benefit overall for patients with 1 to 3 metastases; however, there was a benefit for the subset of patients with GPA 3.5 to 4.0 (median survival time [MST] for WBRT + SRS vs WBRT alone was 21.0 versus 10.3 months, P=.05) regardless of the number of metastases. Among patients with GPA 3.5 to 4.0 treated with WBRT and SRS, the MST for patients with 1 versus 2 to 3 metastases was 21 and 14.1 months, respectively.Conclusions: This secondary analysis of predominantly lung cancer patients, consistent with the original analysis, shows no survival advantage for the group overall when treated with WBRT and SRS; however, in patients with high GPA (3.5-4), there is a survival advantage regardless of whether they have 1, 2, or 3 BM. This benefit did not extend to patients with lower GPA. Prospective validation of this survival benefit for patients with multiple BM and high GPA when treated with WBRT and SRS is warranted. © 2014 Elsevier Inc. Source


Varadhan R.,Minneapolis Radiation Oncology
Journal of applied clinical medical physics / American College of Medical Physics | Year: 2013

Quantitative validation of deformable image registration (DIR) algorithms is extremely difficult because of the complexity involved in constructing a deformable phantom that can duplicate various clinical scenarios. The purpose of this study is to describe a framework to test the accuracy of DIR based on computational modeling and evaluating using inverse consistency and other methods. Three clinically relevant organ deformations were created in prostate (distended rectum and rectal gas), head and neck (large neck flexion), and lung (inhale and exhale lung volumes with variable contrast enhancement) study sets. DIR was performed using both B-spline and diffeomorphic demons algorithms in the forward and inverse direction. A compositive accumulation of forward and inverse deformation vector fields was done to quantify the inverse consistency error (ICE). The anatomical correspondence of tumor and organs at risk was quantified by comparing the original RT structures with those obtained after DIR. Further, the physical characteristics of the deformation field, namely the Jacobian and harmonic energy, were computed to quantify the preservation of image topology and regularity of spatial transformation obtained in DIR. The ICE was comparable in prostate case but the B-spline algorithm had significantly better anatomical correspondence for rectum and prostate than diffeomorphic demons algorithm. The ICE was 6.5 mm for demons algorithm for head and neck case when compared to 0.7 mm for B-spline. Since the induced neck flexion was large, the average Dice similarity coefficient between both algorithms was only 0.87, 0.52, 0.81, and 0.67 for tumor, cord, parotids, and mandible, respectively. The B-spline algorithm accurately estimated deformations between images with variable contrast in our lung study, while diffeomorphic demons algorithm led to gross errors on structures affected by contrast variation. The proposed framework offers the application of known deformations on any image datasets, to evaluate the overall accuracy and limitations of a DIR algorithm used in radiation oncology. The evaluation based on anatomical correspondence, physical characteristics of deformation field, and image characteristics can facilitate DIR verification with the ultimate goal of implementing adaptive radiotherapy. The suitability of application of a particular evaluation metric in validating DIR is dependent on the clinical deformation observed. Source


Sperduto P.W.,University of Minnesota | Chao S.T.,Cleveland Clinic | Sneed P.K.,University of California at San Francisco | Luo X.,University of Minnesota | And 14 more authors.
International Journal of Radiation Oncology Biology Physics | Year: 2010

Purpose: Controversy endures regarding the optimal treatment of patients with brain metastases (BMs). Debate persists, despite many randomized trials, perhaps because BM patients are a heterogeneous population. The purpose of the present study was to identify significant diagnosis-specific prognostic factors and indexes (Diagnosis-Specific Graded Prognostic Assessment [DS-GPA]). Methods and Materials: A retrospective database of 5,067 patients treated for BMs between 1985 and 2007 was generated from 11 institutions. After exclusion of the patients with recurrent BMs or incomplete data, 4,259 patients with newly diagnosed BMs remained eligible for analysis. Univariate and multivariate analyses of the prognostic factors and outcomes by primary site and treatment were performed. The significant prognostic factors were determined and used to define the DS-GPA prognostic indexes. The DS-GPA scores were calculated and correlated with the outcomes, stratified by diagnosis and treatment. Results: The significant prognostic factors varied by diagnosis. For non-small-cell lung cancer and small-cell lung cancer, the significant prognostic factors were Karnofsky performance status, age, presence of extracranial metastases, and number of BMs, confirming the original GPA for these diagnoses. For melanoma and renal cell cancer, the significant prognostic factors were Karnofsky performance status and the number of BMs. For breast and gastrointestinal cancer, the only significant prognostic factor was the Karnofsky performance status. Two new DS-GPA indexes were thus designed for breast/gastrointestinal cancer and melanoma/renal cell carcinoma. The median survival by GPA score, diagnosis, and treatment were determined. Conclusion: The prognostic factors for BM patients varied by diagnosis. The original GPA was confirmed for non-small-cell lung cancer and small-cell lung cancer. New DS-GPA indexes were determined for other histologic types and correlated with the outcome, and statistical separation between the groups was confirmed. These data should be considered in the design of future randomized trials and in clinical decision-making. © 2010 Elsevier Inc. All rights reserved. Source

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