Validation of the BRODERS classifier (Benign versus aggRessive nODule Evaluation using Radiomic Stratification), a novel HRCT-based radiomic classifier for indeterminate pulmonary nodules.

INTRODUCTION: Implementation of low-dose chest computed tomography (CT) lung cancer screening and the ever-increasing use of cross-sectional imaging are resulting in the identification of many screen- and incidentally detected indeterminate pulmonary nodules. While the management of nodules with low or high pre-test probability of malignancy is relatively straightforward, those with intermediate pre-test probability commonly require advanced imaging or biopsy. Noninvasive risk stratification tools are highly desirable. METHODS: We previously developed the BRODERS classifier (Benign versus aggRessive nODule Evaluation using Radiomic Stratification), a conventional predictive radiomic model based on eight imaging features capturing nodule location, shape, size, texture and surface characteristics. Herein we report its external validation using a dataset of incidentally identified lung nodules (Vanderbilt University Lung Nodule Registry) in comparison to the Brock model. Area under the curve (AUC), as well as sensitivity, specificity, negative and positive predictive values were calculated. RESULTS: For the entire Vanderbilt validation set (n=170, 54% malignant), the AUC was 0.87 (95% CI 0.81-0.92) for the Brock model and 0.90 (95% CI 0.85-0.94) for the BRODERS model. Using the optimal cut-off determined by Youden's index, the sensitivity was 92.3%, the specificity was 62.0%, the positive (PPV) and negative predictive values (NPV) were 73.7% and 87.5%, respectively. For nodules with intermediate pre-test probability of malignancy, Brock score of 5-65% (n=97), the sensitivity and specificity were 94% and 46%, respectively, the PPV was 78.4% and the NPV was 79.2%. CONCLUSIONS: The BRODERS radiomic predictive model performs well on an independent dataset and may facilitate the management of indeterminate pulmonary nodules.

Effect of Catheter Ablation vs Antiarrhythmic Drug Therapy on Mortality, Stroke, Bleeding, and Cardiac Arrest Among Patients With Atrial Fibrillation: The CABANA Randomized Clinical Trial.

Importance: Catheter ablation is effective in restoring sinus rhythm in atrial fibrillation (AF), but its effects on long-term mortality and stroke risk are uncertain. Objective: To determine whether catheter ablation is more effective than conventional medical therapy for improving outcomes in AF. Design, Setting, and Participants: The Catheter Ablation vs Antiarrhythmic Drug Therapy for Atrial Fibrillation trial is an investigator-initiated, open-label, multicenter, randomized trial involving 126 centers in 10 countries. A total of 2204 symptomatic patients with AF aged 65 years and older or younger than 65 years with 1 or more risk factors for stroke were enrolled from November 2009 to April 2016, with follow-up through December 31, 2017. Interventions: The catheter ablation group (n = 1108) underwent pulmonary vein isolation, with additional ablative procedures at the discretion of site investigators. The drug therapy group (n = 1096) received standard rhythm and/or rate control drugs guided by contemporaneous guidelines. Main Outcomes and Measures: The primary end point was a composite of death, disabling stroke, serious bleeding, or cardiac arrest. Among 13 prespecified secondary end points, 3 are included in this report: all-cause mortality; total mortality or cardiovascular hospitalization; and AF recurrence. Results: Of the 2204 patients randomized (median age, 68 years; 37.2% female; 42.9% had paroxysmal AF and 57.1% had persistent AF), 89.3% completed the trial. Of the patients assigned to catheter ablation, 1006 (90.8%) underwent the procedure. Of the patients assigned to drug therapy, 301 (27.5%) ultimately received catheter ablation. In the intention-to-treat analysis, over a median follow-up of 48.5 months, the primary end point occurred in 8.0% (n = 89) of patients in the ablation group vs 9.2% (n = 101) of patients in the drug therapy group (hazard ratio [HR], 0.86 [95% CI, 0.65-1.15]; P = .30). Among the secondary end points, outcomes in the ablation group vs the drug therapy group, respectively, were 5.2% vs 6.1% for all-cause mortality (HR, 0.85 [95% CI, 0.60-1.21]; P = .38), 51.7% vs 58.1% for death or cardiovascular hospitalization (HR, 0.83 [95% CI, 0.74-0.93]; P = .001), and 49.9% vs 69.5% for AF recurrence (HR, 0.52 [95% CI, 0.45-0.60]; P < .001). Conclusions and Relevance: Among patients with AF, the strategy of catheter ablation, compared with medical therapy, did not significantly reduce the primary composite end point of death, disabling stroke, serious bleeding, or cardiac arrest. However, the estimated treatment effect of catheter ablation was affected by lower-than-expected event rates and treatment crossovers, which should be considered in interpreting the results of the trial. Trial Registration: ClinicalTrials.gov Identifier: NCT00911508.

Catheter Ablation versus Antiarrhythmic Drug Therapy for Atrial Fibrillation (CABANA) Trial: Study Rationale and Design.

The Catheter Ablation Versus Anti-arrhythmic Drug Therapy for Atrial Fibrillation (CABANA,NCT00911508)(1) trial is testing the hypothesis that the treatment strategy of percutaneous left atrial catheter ablation for the purpose of eliminating atrial fibrillation (AF) is superior to current state-of-the-art pharmacologic therapy. This international 140-center clinical trial was designed to randomize 2200 patients to a strategy of catheter ablation versus state-of-the-art rate or rhythm control drug therapy. Inclusion criteria include: 1) age> 65, or ≤65 with≥ 1 risk factor for stroke, 2) documented AF warranting treatment, and 3) eligibility for both catheter ablation and≥ 2 anti-arrhythmic or≥ 2 rate control drugs. Patients were followed every 3 to 6 months (median 4 years) and underwent repeat trans-telephonic monitoring, Holter monitoring, and CT/MR in a subgroup of patient studies to assess the impact of treatment on AF recurrence and atrial structure. With 1100 patients in each treatment arm, CABANA is projected to have 90% power for detecting a 30% relative reduction in the primary composite endpoint of total mortality, disabling stroke, serious bleeding, or cardiac arrest. Secondary endpoints include total mortality; mortality or cardiovascular hospitalization; a combination of mortality, stroke, hospitalization for heart failure or acute coronary artery events; cardiovascular death alone; and heart failure death, as well as AF recurrence, quality of life, and cost effectiveness. At a time when AF incidence is rising rapidly, CABANA will provide critical evidence with which to guide therapy and shape health care policy related to AF for years to come.

Noninvasive Computed Tomography-based Risk Stratification of Lung Adenocarcinomas in the National Lung Screening Trial.

RATIONALE: Screening for lung cancer using low-dose computed tomography (CT) reduces lung cancer mortality. However, in addition to a high rate of benign nodules, lung cancer screening detects a large number of indolent cancers that generally belong to the adenocarcinoma spectrum. Individualized management of screen-detected adenocarcinomas would be facilitated by noninvasive risk stratification. OBJECTIVES: To validate that Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel image analysis software, successfully risk stratifies screen-detected lung adenocarcinomas based on clinical disease outcomes. METHODS: We identified retrospective 294 eligible patients diagnosed with lung adenocarcinoma spectrum lesions in the low-dose CT arm of the National Lung Screening Trial. The last low-dose CT scan before the diagnosis of lung adenocarcinoma was analyzed using CANARY blinded to clinical data. Based on their parametric CANARY signatures, all the lung adenocarcinoma nodules were risk stratified into three groups. CANARY risk groups were compared using survival analysis for progression-free survival. MEASUREMENTS AND MAIN RESULTS: A total of 294 patients were included in the analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into the Good, Intermediate, and Poor CANARY risk groups yielded distinct progression-free survival curves (P < 0.0001). This observation was confirmed in the unadjusted and adjusted (age, sex, race, and smoking status) progression-free survival analysis of all stage I cases. CONCLUSIONS: CANARY allows the noninvasive risk stratification of lung adenocarcinomas into three groups with distinct post-treatment progression-free survival. Our results suggest that CANARY could ultimately facilitate individualized management of incidentally or screen-detected lung adenocarcinomas.

Comparison of manual and semiautomated techniques for analyzing gastric volumes with MRI in humans.

Gastric emptying, accommodation, and motility can be quantified with magnetic resonance imaging (MRI). The first step in image analysis entails segmenting the stomach from surrounding structures, usually by a time-consuming manual process. We have developed a semiautomated process to segment and measure gastric volumes with MRI. Gastric images were acquired with a three-dimensional gradient echo MRI sequence at 5, 10, 20, and 30 min after ingestion of a liquid nutrient (Ensure, 296 ml) labeled with gadolinium in 20 healthy volunteers and 29 patients with dyspeptic symptoms. The agreement between gastric volumes measured by manual segmentation and our new semiautomated algorithm was assessed with Lin's concordance correlation coefficient (CCC) and the Bland Altman test. At 5 min after a meal, food volumes measured by manual (352 ± 4 ml) and semiautomated (346 ± 4 ml) techniques were correlated {CCC[95% confidence interval (CI)] 0.70 (0.52, 0.81)}; air volumes measured by manual (88 ± 6 ml) and semiautomated (84 ± 6 ml) techniques were also correlated [CCC (95% CI) 0.89 (0.82, 0.94)]. Findings were similar at subsequent time points. The Bland Altman test was not significant. The time required for semiautomated segmentation ranged from an average of 204 s for the 5-min images to 233 s for the 20-min images. These times were appreciably smaller than the typical times of many tens of minutes, even hours, required for manual segmentation. To conclude, a semiautomated process can measure gastric food and air volume using MRI with comparable accuracy and far better efficiency than a manual process.

Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis.

Accurate assessment of prognosis in idiopathic pulmonary fibrosis remains elusive due to significant individual radiological and physiological variability. We hypothesised that short-term radiological changes may be predictive of survival. We explored the use of CALIPER (Computer-Aided Lung Informatics for Pathology Evaluation and Rating), a novel software tool developed by the Biomedical Imaging Resource Laboratory at the Mayo Clinic Rochester (Rochester, MN, USA) for the analysis and quantification of parenchymal lung abnormalities on high-resolution computed tomography. We assessed baseline and follow-up (time-points 1 and 2, respectively) high-resolution computed tomography scans in 55 selected idiopathic pulmonary fibrosis patients and correlated CALIPER-quantified measurements with expert radiologists' assessments and clinical outcomes. Findings of interval change (mean 289 days) in volume of reticular densities (hazard ratio 1.91, p=0.006), total volume of interstitial abnormalities (hazard ratio 1.70, p=0.003) and per cent total interstitial abnormalities (hazard ratio 1.52, p=0.017) as quantified by CALIPER were predictive of survival after a median follow-up of 2.4 years. Radiologist interpretation of short-term global interstitial lung disease progression, but not specific radiological features, was also predictive of mortality. These data demonstrate the feasibility of quantifying interval short-term changes on high-resolution computed tomography and their possible use as independent predictors of survival in idiopathic pulmonary fibrosis.

Active relearning for robust supervised training of emphysema patterns.

Radiologists are adept at recognizing the character and extent of lung parenchymal abnormalities in computed tomography (CT) scans. However, the inconsistent differential diagnosis due to subjective aggregation necessitates the exploration of automated classification based on supervised or unsupervised learning. The robustness of supervised learning depends on the training samples. Towards optimizing emphysema classification, we introduce a physician-in-the-loop feedback approach to minimize ambiguity in the selected training samples. An experienced thoracic radiologist selected 412 regions of interest (ROIs) across 15 datasets to represent 124, 129, 139 and 20 training samples of mild, moderate, severe emphysema and normal appearance, respectively. Using multi-view (multiple metrics to capture complementary features) inductive learning, an ensemble of seven un-optimized support vector models (SVM) each based on a specific metric was constructed in less than 6 s. The training samples were classified using seven SVM models and consensus labels were created using majority voting. In the active relearning phase, the ensemble-expert label conflicts were resolved by the expert. The efficacy and generality of active relearning feedback was assessed in the optimized parameter space of six general purpose classifiers across the seven dissimilarity metrics. The proposed just-in-time active relearning feedback with un-optimized SVMs yielded 15 % increase in classification accuracy and 25 % reduction in the number of support vectors. The average improvement in accuracy of six classifiers in their optimized parameter space was 21 %. The proposed cooperative feedback method enhances the quality of training samples used to construct automated classification of emphysematous CT scans. Such an approach could lead to substantial improvement in quantification of emphysema.

Toward modeling of radio-frequency ablation lesions for image-guided left atrial fibrillation therapy: model formulation and preliminary evaluation.

In the context of image-guided left atrial fibrillation therapy, relatively very little work has been done to consider the changes that occur in the tissue during ablation in order to monitor therapy delivery. Here we describe a technique to predict the lesion progression and monitor the radio-frequency energy delivery via a thermal ablation model that uses heat transfer principles to estimate the tissue temperature distribution and resulting lesion. A preliminary evaluation of the model was conducted in ex vivo skeletal beef muscle tissue while emulating a clinically relevant tissue ablation protocol. The predicted temperature distribution within the tissue was assessed against that measured directly using fiberoptic temperature probes and showed agreement within 5°C between the model-predicted and experimentally measured tissue temperatures at prescribed locations. We believe this technique is capable of providing reasonably accurate representations of the tissue response to radio-frequency energy delivery.

Detail-on-demand visualization for lean understanding of lung abnormalities.

In some respects, the lung is an anatomical bog - having limited referential landmarks. Nonetheless, precise understanding of the abnormalities that inflict this organ is crucial to effective clinical diagnosis and treatment. However, wading interactively through a three-dimensional scan of the lung poses a visual quagmire to the radiologist, resulting in significant interpretive differences due to inter and intra observer variation. Despite the continuing progress in quantitative imaging, lack of unambiguous visualization with accurately, relevant cues severely hinders the clinical adoption of many computational tools. We address this unmet need through a lean visualization paradigm wherein information is presented hierarchically to provide an interactive macro-to-micro view of lung pathologies. At the macro level, the structural and functional information is summarized into a synoptic glyph that is readily interpreted and correlated to a priori known disease states. The glyphs are "patho-spatio-temporally" tagged to facilitate navigation through the level-of-detail scales, down to the micro level values in the image voxels, providing quantitative interpretation of tissue type and the confidence level in the quantitation. A novel volume compositing scheme is proposed to specify and guide to the optimal site for surgical lung biopsy. This intuitive, interactive interface for rapid and unambiguous navigation towards the clinical endpoint harnesses the power of bio-informatics technology to provide an efficient, clinically relevant and comprehensive summary of pulmonary disease, including precise location, spatial extent and intrinsic character.

Fast adaptation of pre-operative patient specific models to real-time intra-operative volumetric data streams.

Image-guided catheter ablation therapy is becoming an increasingly popular treatment option for atrial fibrillation. Successful treatment relies on accurate guidance of the treatment catheter. Integration of high-resolution, pre-operative data with electrophysiology data and positional data from tracked catheters improves targeting, but lacks the means to monitor changes in the atrial wall. Intra-operative ultrasound provides a method for imaging the atrial wall, but the real-time, dynamic nature of the data makes it difficult to seamlessly integrate with the static pre-operative patient-specific model. In this work, we propose a technique which uses a self-organizing map (SOM) for dynamically adapting a pre-operative model to surface patch data. The surface patch would be derived from a segmentation of the anatomy in a real-time, intra-operative ultrasound data stream. The method is demonstrated on two regular geometric shapes as well as data simulated from a real, patient computed tomography dataset.

Treatment-Related Changes in Left Atrial Structure in Atrial Fibrillation: Findings From the CABANA Imaging Substudy.

[Figure: see text].

Virtual pelvic anatomy simulator: a pilot study of usability and perceived effectiveness.

BACKGROUND: Simulators for surgical education are in high demand due to new curriculum requirements for surgical residency accreditation. Our aim was to assess the usability and perceived effectiveness of a three-dimensional (3-D) pelvic anatomy teaching module derived from human magnetic resonance and computerized tomography images. METHODS: A convenience sample of medical students and surgery residents was surveyed. Results are frequency (proportion) of respondents who agreed or strongly agreed with each statement. RESULTS: Ten participants (5 medical students, 5 surgical residents) completed the survey. At baseline, a minority (30%) self-reported a very good knowledge of pelvic anatomy; none reported excellent knowledge of pelvic anatomy. All participants agreed that the module teaches clinically relevant anatomy; 90% preferred this type of education to traditional methods. Fifty percent of participants felt the module needed a higher level of anatomic detail. Participants specifically requested inclusion of Denonvillier's and Waldeyer's fascia, and the component muscles of the pelvic floor. CONCLUSIONS: These pilot results suggest that our 3-D pelvic anatomy teaching module is easy to use and would enhance student learning of anatomy over traditional methods in an effective manner. Further study is warranted to assess the incremental impact of this and standard educational interventions for teaching surgical anatomy.

Virtual pelvic anatomy and surgery simulator: an innovative tool for teaching pelvic surgical anatomy.

Pelvic three-dimensional (3-D) anatomy is complex and can be difficult to visualize. We have developed an alpha-version virtual anatomic model that will facilitate a) student learning of anatomy b) resident preparedness for operation, c) surgical planning for complex, multidisciplinary procedures. This educational module is composed of the virtual anorectum, an anatomically accurate, interactive model of the anorectum and pelvic viscera based on co-registered human computed tomographic (CT) and magnetic resonance (MR) images. It also consists of a physical model fabricated from the same data-set using stereolithography. Usability and functionality was assessed in a sample of surgical trainees. Feedback demonstrated that the module is an efficient adjunct to medical education and surgical planning. Ultimately, we envision a deformable virtual model that allows residents and surgeons to rehearse complex surgical procedures by performing virtual surgery, thereby improving preparedness for real operations. Such a model will be integrated into a colorectal surgery educational curriculum, and in the future may represent a unique method of competency testing.

A bone structural basis for fracture risk in diabetes.

CONTEXT: Elevated areal bone mineral density (aBMD) in type 2 diabetes mellitus is inconsistent with increased fracture risk at some skeletal sites. OBJECTIVES: Because aBMD is an imperfect surrogate for bone strength, we assessed bone structure and strength more directly using quantitative computed tomography. DESIGN: Diabetic and nondiabetic subjects were evaluated in a cross-sectional study. SETTING: Subjects were recruited from a random sample of the Rochester, MN, population. PARTICIPANTS: Forty-nine subjects (28 women and 21 men) with type 2 diabetes were compared with age- and sex-matched nondiabetic controls. MAIN OUTCOME MEASUREMENTS: We measured bone geometry, strength, and volumetric BMD (vBMD) at the hip, spine, and wrist, along with hip aBMD, using central and peripheral quantitative computed tomography and estimated bone load to bone strength ratios at each site. RESULTS: Adjusted for differences in body mass index between cases and controls (29.8 vs. 27.6), hip aBMD was greater in diabetic subjects, but this was accounted for by greater trabecular vBMD. Cortical vBMD was similar in the two groups, as was bone cross-sectional area and cortical thickness. Bone strength measures were generally better in diabetic subjects, but bone loads were higher from their greater weight. Consequently, load to strength ratios (i.e. factor-of-risk) were similar. CONCLUSIONS: Patients with type 2 diabetes enjoy little benefit from elevated aBMD in terms of improved bone load to strength ratios. With no deficit in bone density, the rationale for antiresorptive therapy in diabetic patients is uncertain, but potential adverse effects of diabetes on bone quality need more study.

Correction: Novel high-resolution computed tomography-based radiomic classifier for screen-identified pulmonary nodules in the National Lung Screening Trial.

[This corrects the article DOI: 10.1371/journal.pone.0196910.].

Novel high-resolution computed tomography-based radiomic classifier for screen-identified pulmonary nodules in the National Lung Screening Trial.

PURPOSE: Optimization of the clinical management of screen-detected lung nodules is needed to avoid unnecessary diagnostic interventions. Herein we demonstrate the potential value of a novel radiomics-based approach for the classification of screen-detected indeterminate nodules. MATERIAL AND METHODS: Independent quantitative variables assessing various radiologic nodule features such as sphericity, flatness, elongation, spiculation, lobulation and curvature were developed from the NLST dataset using 726 indeterminate nodules (all ≥ 7 mm, benign, n = 318 and malignant, n = 408). Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) method for variable selection and regularization in order to enhance the prediction accuracy and interpretability of the multivariate model. The bootstrapping method was then applied for the internal validation and the optimism-corrected AUC was reported for the final model. RESULTS: Eight of the originally considered 57 quantitative radiologic features were selected by LASSO multivariate modeling. These 8 features include variables capturing Location: vertical location (Offset carina centroid z), Size: volume estimate (Minimum enclosing brick), Shape: flatness, Density: texture analysis (Score Indicative of Lesion/Lung Aggression/Abnormality (SILA) texture), and surface characteristics: surface complexity (Maximum shape index and Average shape index), and estimates of surface curvature (Average positive mean curvature and Minimum mean curvature), all with P<0.01. The optimism-corrected AUC for these 8 features is 0.939. CONCLUSIONS: Our novel radiomic LDCT-based approach for indeterminate screen-detected nodule characterization appears extremely promising however independent external validation is needed.

Structural determinants of vertebral fracture risk.

UNLABELLED: Vertebral fractures are more strongly associated with specific bone density, structure, and strength parameters than with areal BMD, but all of these variables are correlated. INTRODUCTION: It is unclear whether the association of areal BMD (aBMD) with vertebral fracture risk depends on bone density per se, bone macro- or microstructure, overall bone strength, or spine load/bone strength ratios. MATERIALS AND METHODS: From an age-stratified sample of Rochester, MN, women, we identified 40 with a clinically diagnosed vertebral fracture (confirmed semiquantitatively) caused by moderate trauma (cases; mean age, 78.6 +/- 9.0 yr) and compared them with 40 controls with no osteoporotic fracture (mean age, 70.9 +/- 6.8 yr). Lumbar spine volumetric BMD (vBMD) and geometry were assessed by central QCT, whereas microstructure was evaluated by high-resolution pQCT at the ultradistal radius. Vertebral failure load ( approximately strength) was estimated from voxel-based finite element models, and the factor-of-risk (phi) was determined as the ratio of applied spine loads to failure load. RESULTS: Spine loading (axial compressive force on L3) was similar in vertebral fracture cases and controls (e.g., for 90 degrees forward flexion, 2639 versus 2706 N; age-adjusted p = 0.173). However, fracture cases had inferior values for most bone density and structure variables. Bone strength measures were also reduced, and the factor-of-risk (phi) was 35-37% greater (worse) among women with a vertebral fracture. By age-adjusted logistic regression, relative risks for the strongest fracture predictor in each of the five main variable categories were bone density (total lumbar spine vBMD: OR per SD change, 2.2; 95% CI, 1.1-4.3), bone geometry (vertebral apparent cortical thickness: OR, 2.1; 95% CI, 1.1-4.1), bone microstructure (none significant); bone strength ("cortical" [outer 2 mm] compressive strength: OR, 2.5; 95% CI, 1.3-4.8), and factor-of-risk (phi for 90 degrees forward flexion/overall vertebral compressive strength: OR, 3.2; 95% CI, 1.4-7.5). These variables were correlated with spine aBMD (partial r, -0.32 to 0.75), but each was a stronger predictor of fracture in the logistic regression analyses. CONCLUSIONS: The association of aBMD with vertebral fracture risk is explained by its correlation with more specific bone density, structure, and strength parameters. These may allow deeper insights into fracture pathogenesis.

Prostate brachytherapy seed reconstruction using an adaptive grouping technique.

Fluoroscopy-based three-dimensional seed localization as a component of intraoperative dosimetry for prostate brachytherapy is an active area of research. A novel adaptive-grouping-based reconstruction approach is developed. This approach can recover overlapped seeds that are not detected from the fluoroscopic images. Two versions of the adaptive-grouping-based reconstruction approach are implemented and compared to an epipolar geometry-based seed reconstruction technique. Simulations based on nine patient datasets are used to validate the algorithms. A total of 2259 reconstructions is performed in which different types of error such as random noise in seed image locations and ambiguities in projection geometry are incorporated. Among those reconstructions, nine of the cases with overlapping seeds and the different types of error are performed. It is demonstrated that the adaptive-grouping-based reconstruction method is more accurate than the epipolar geometry method and allows faster reconstruction. At a random noise level of 0.6 mm, the mean distance error in reconstructed seed locations is approximately 1.0 mm for one of the relevant cases examined in detail. The best adaptive-grouping-based approach successfully recovered overlapped seeds in the majority of simulated cases (89%), with the remainder of cases generating one false positive seed. Phantom validation is also performed, and overlapped seeds are successfully recovered with all 92 seeds correctly localized and reconstructed. The mean distance error between segmented seed images and projected seeds is 0.5 mm in the phantom study.

Dosimetry accuracy as a function of seed localization uncertainty in permanent prostate brachytherapy: increased seed number correlates with less variability in prostate dosimetry.

The variation of permanent prostate brachytherapy dosimetry as a function of seed localization uncertainty was investigated for I-125 implants with seed activities commonly employed in contemporary practice. Post-implant imaging and radiation dosimetry data from nine patients who underwent permanent prostate brachytherapy served as the source of clinical data for this simulation study. Gaussian noise with standard deviations ranging from 0.5 to 10 mm was applied to the seed coordinates for each patient dataset and 1000 simulations were performed at each noise level. Dose parameters, including D90, were computed for each case and compared with the actual dosimetry data. A total of 81 000 complete sets of post-brachytherapy dose volume statistics were computed. The results demonstrated that less than 5% deviation of prostate D90 can be expected when the seed localization uncertainty is 2 mm, whereas a seed localization uncertainty of 10 mm yielded an average decrease in D90 of 33 Gy. The mean normalized decrement in the prostate V100 was 10% at 5 mm uncertainty. Implants with greater seed number and larger prostate volume correlated with less sensitivity of D90 and V100 to seed localization uncertainty. Estimated target volume dose parameters tended to decrease with increasing seed localization uncertainty. The bladder V100 varied more significantly both in mean and standard deviation as compared to the urethra V100. A larger number of implanted seeds also correlated to less sensitivity of the bladder V100 to seed localization uncertainty. In contrast, the deviation of urethra V100 did not correlate with the number of implanted seeds or prostate volume.