SlicerRT: radiation therapy research toolkit for 3D Slicer

Radiomics-based features for pattern recognition of lung cancer histopathology and metastases

BACKGROUND AND OBJECTIVES

lung cancer is the leading cause of cancer-related deaths in the world, and its poor prognosis varies markedly according to tumor staging. Computed tomography (CT) is the imaging modality of choice for lung cancer evaluation, being used for diagnosis and clinical staging. Besides tumor stage, other features, like histopathological subtype, can also add prognostic information. In this work, radiomics-based CT features were used to predict lung cancer histopathology and metastases using machine learning models.

METHODS

local image datasets of confirmed primary malignant pulmonary tumors were retrospectively evaluated for testing and validation. CT images acquired with same protocol were semiautomatically segmented. Tumors were characterized by clinical features and computer attributes of intensity, histogram, texture, shape, and volume. Three machine learning classifiers used up to 100 selected features to perform the analysis.

RESULTS

radiomics-based features yielded areas under the receiver operating characteristic curve of 0.89, 0.97, and 0.92 at testing and 0.75, 0.71, and 0.81 at validation for lymph nodal metastasis, distant metastasis, and histopathology pattern recognition, respectively.

CONCLUSIONS

the radiomics characterization approach presented great potential to be used in a computational model to aid lung cancer histopathological subtype diagnosis as a "virtual biopsy" and metastatic prediction for therapy decision support without the necessity of a whole-body imaging scanning.

New approach of ultra-focal brachytherapy for low- and intermediate-risk prostate cancer with custom-linked I-125 seeds: A feasibility study of optimal dose coverage

PURPOSE

To present the feasibility study of optimal dose coverage in ultra-focal brachytherapy (UFB) with multiparametric MRI for low- and intermediate-risk prostate cancer.

METHODS AND MATERIALS

UFB provisional dose plans for small target volumes (<7 cc) were calculated on a prostate training phantom to optimize the seeds number and strength. Clinical UFB consisted in a contour-based nonrigid registration (MRI/Ultrasound) to implant a fiducial marker at the location of the tumor focus. Dosimetry was performed with iodine-125 seeds and a prescribed dose of 160 Gy. On CT scans acquired at 1 month, dose coverage of 152 Gy to the ultra-focal gross tumor volume was evaluated. Registrations between magnetic resonance and CT scans were assessed on the first 8 patients with three software solutions: VariSeed, 3D Slicer, and Mirada, and quantitative evaluations of the registrations were performed. Impact of these registrations on the initial dose matrix was performed.

RESULTS

Mean differences between simulated dose plans and extrapolated Bard nomogram for UFB volumes were 36.3% (26-56) for the total activity, 18.3% (10-30) for seed strength, and 22.5% (16-38) for number of seeds. Registration method implemented in Mirada performed significantly better than VariSeed and 3D Slicer (p = 0.0117 and p = 0.0357, respectively). For dose plan evaluation between Mirada and VariSeed, D₁₀₀% (Gy) for ultra-focal gross tumor volume had a mean difference of 28.06 Gy, mean values being still above the objective of 152 Gy. D₉₀% for the prostate had a mean difference of 1.17 Gy. For urethra and rectum, dose limits were far below the recommendations.

CONCLUSIONS

This UFB study confirmed the possibility to treat with optimal dose coverage target volumes smaller than 7 cc.

ESTRO ACROP: Technology for precision small animal radiotherapy research: Optimal use and challenges

Many radiotherapy research centers have recently installed novel research platforms enabling the investigation of the radiation response of tumors and normal tissues in small animal models, possibly in combination with other treatment modalities. Many more research institutes are expected to follow in the coming years. These novel platforms are capable of mimicking human radiotherapy more closely than older technology. To facilitate the optimal use of these novel integrated precision irradiators and various small animal imaging devices, and to maximize the impact of the associated research, the ESTRO committee on coordinating guidelines ACROP (Advisory Committee in Radiation Oncology Practice) has commissioned a report to review the state of the art of the technology used in this new field of research, and to issue recommendations. This report discusses the combination of precision irradiation systems, small animal imaging (CT, MRI, PET, SPECT, bioluminescence) systems, image registration, treatment planning, and data processing. It also provides guidelines for reporting on studies.

Patient-specific calibration of cone-beam computed tomography data sets for radiotherapy dose calculations and treatment plan assessment

Purpose

In this work, we propose a new method of calibrating cone beam computed tomography (CBCT) data sets for radiotherapy dose calculation and plan assessment. The motivation for this patient‐specific calibration (PSC) method is to develop an efficient, robust, and accurate CBCT calibration process that is less susceptible to deformable image registration (DIR) errors.

Methods

Instead of mapping the CT numbers voxel‐by‐voxel with traditional DIR calibration methods, the PSC methods generates correlation plots between deformably registered planning CT and CBCT voxel values, for each image slice. A linear calibration curve specific to each slice is then obtained by least‐squares fitting, and applied to the CBCT slice's voxel values. This allows each CBCT slice to be corrected using DIR without altering the patient geometry through regional DIR errors.

A retrospective study was performed on 15 head‐and‐neck cancer patients, each having routine CBCTs and a middle‐of‐treatment re‐planning CT (reCT). The original treatment plan was re‐calculated on the patient's reCT image set (serving as the gold standard) as well as the image sets produced by voxel‐to‐voxel DIR, density‐overriding, and the new PSC calibration methods. Dose accuracy of each calibration method was compared to the reference reCT data set using common dose‐volume metrics and 3D gamma analysis. A phantom study was also performed to assess the accuracy of the DIR and PSC CBCT calibration methods compared with planning CT.

Results

Compared with the gold standard using reCT, the average dose metric differences were ≤ 1.1% for all three methods (PSC: −0.3%; DIR: −0.7%; density‐override: −1.1%). The average gamma pass rates with thresholds 3%, 3 mm were also similar among the three techniques (PSC: 95.0%; DIR: 96.1%; density‐override: 94.4%).

Conclusions

An automated patient‐specific calibration method was developed which yielded strong dosimetric agreement with the results obtained using a re‐planning CT for head‐and‐neck patients.

An automated dose tracking system for adaptive radiation therapy

BACKGROUND AND OBJECTIVE

The implementation of adaptive radiation therapy (ART) into routine clinical practice is technically challenging and requires significant resources to perform and validate each process step. The objective of this report is to identify the key components of ART, to illustrate how a specific automated procedure improves efficiency, and to facilitate the routine clinical application of ART.

METHODS

Data was used from patient images, exported from a clinical database and converted to an intermediate format for point-wise dose tracking and accumulation. The process was automated using in-house developed software containing three modularized components: an ART engine, user interactive tools, and integration tools. The ART engine conducts computing tasks using the following modules: data importing, image pre-processing, dose mapping, dose accumulation, and reporting. In addition, custom graphical user interfaces (GUIs) were developed to allow user interaction with select processes such as deformable image registration (DIR). A commercial scripting application programming interface was used to incorporate automated dose calculation for application in routine treatment planning. Each module was considered an independent program, written in C++or C#, running in a distributed Windows environment, scheduled and monitored by integration tools.

RESULTS

The automated tracking system was retrospectively evaluated for 20 patients with prostate cancer and 96 patients with head and neck cancer, under institutional review board (IRB) approval. In addition, the system was evaluated prospectively using 4 patients with head and neck cancer. Altogether 780 prostate dose fractions and 2586 head and neck cancer dose fractions went processed, including DIR and dose mapping. On average, daily cumulative dose was computed in 3 h and the manual work was limited to 13 min per case with approximately 10% of cases requiring an additional 10 min for image registration refinement.

CONCLUSIONS

An efficient and convenient dose tracking system for ART in the clinical setting is presented. The software and automated processes were rigorously evaluated and validated using patient image datasets. Automation of the various procedures has improved efficiency significantly, allowing for the routine clinical application of ART for improving radiation therapy effectiveness.

Validation of MRI to TRUS registration for high-dose-rate prostate brachytherapy

PURPOSE

The objective of this study was to develop and validate an open-source module for MRI to transrectal ultrasound (TRUS) registration to support tumor-targeted prostate brachytherapy.

METHODS AND MATERIALS

In this study, 15 patients with prostate cancer lesions visible on multiparametric MRI were selected for the validation. T2-weighted images with 1-mm isotropic voxel size and diffusion weighted images were acquired on a 1.5T Siemens imager. Three-dimensional (3D) TRUS images with 0.5-mm slice thickness were acquired. The investigated registration module was incorporated in the open-source 3D Slicer platform, which can compute rigid and deformable transformations. An extension of 3D Slicer, SlicerRT, allows import of and export to DICOM-RT formats. For validation, similarity indices, prostate volumes, and centroid positions were determined in addition to registration errors for common 3D points identified by an experienced radiation oncologist.

RESULTS

The average time to compute the registration was 35 ± 3 s. For the rigid and deformable registration, respectively, Dice similarity coefficients were 0.87 ± 0.05 and 0.93 ± 0.01 while the 95% Hausdorff distances were 4.2 ± 1.0 and 2.2 ± 0.3 mm. MRI volumes obtained after the rigid and deformable registration were not statistically different (p > 0.05) from reference TRUS volumes. For the rigid and deformable registration, respectively, 3D distance errors between reference and registered centroid positions were 2.1 ± 1.0 and 0.4 ± 0.1 mm while registration errors between common points were 3.5 ± 3.2 and 2.3 ± 1.1 mm. Deformable registration was found significantly better (p < 0.05) than rigid registration for all parameters.

CONCLUSIONS

An open-source MRI to TRUS registration platform was validated for integration in the brachytherapy workflow.

Reliable landmarks for precise topographical analyses of pathological structural changes of the ovine tibial plateau in 2-D and 3-D subspaces

Selecting identical topographical locations to analyse pathological structural changes of the osteochondral unit in translational models remains difficult. The specific aim of the study was to provide objectively defined reference points on the ovine tibial plateau based on 2-D sections of micro-CT images useful for reproducible sample harvesting and as standardized landmarks for landmark-based 3-D image registration. We propose 5 reference points, 11 reference lines and 12 subregions that are detectable macroscopically and on 2-D micro-CT sections. Their value was confirmed applying landmark-based rigid and affine 3-D registration methods. Intra- and interobserver comparison showed high reliabilities, and constant positions (standard errors < 1%). Spatial patterns of the thicknesses of the articular cartilage and subchondral bone plate were revealed by measurements in 96 individual points of the tibial plateau. As a case study, pathological phenomena 6 months following OA induction in vivo such as osteophytes and areas of OA development were mapped to the individual subregions. These new reference points and subregions are directly identifiable on tibial plateau specimens or macroscopic images, enabling a precise topographical location of pathological structural changes of the osteochondral unit in both 2-D and 3-D subspaces in a region-appropriate fashion relevant for translational investigations.

Artificial neural network based gynaecological image-guided adaptive brachytherapy treatment planning correction of intra-fractional organs at risk dose variation

PURPOSE

Intra-fractional organs at risk (OARs) deformations can lead to dose variation during image-guided adaptive brachytherapy (IGABT). The aim of this study was to modify the final accepted brachytherapy treatment plan to dosimetrically compensate for these intra-fractional organs-applicators position variations and, at the same time, fulfilling the dosimetric criteria.

MATERIAL AND METHODS

Thirty patients with locally advanced cervical cancer, after external beam radiotherapy (EBRT) of 45-50 Gy over five to six weeks with concomitant weekly chemotherapy, and qualified for intracavitary high-dose-rate (HDR) brachytherapy with tandem-ovoid applicators were selected for this study. Second computed tomography scan was done for each patient after finishing brachytherapy treatment with applicators in situ. Artificial neural networks (ANNs) based models were used to predict intra-fractional OARs dose-volume histogram parameters variations and propose a new final plan.

RESULTS

A model was developed to estimate the intra-fractional organs dose variations during gynaecological intracavitary brachytherapy. Also, ANNs were used to modify the final brachytherapy treatment plan to compensate dosimetrically for changes in 'organs-applicators', while maintaining target dose at the original level.

CONCLUSIONS

There are semi-automatic and fast responding models that can be used in the routine clinical workflow to reduce individually IGABT uncertainties. These models can be more validated by more patients' plans to be able to serve as a clinical tool.

Investigating the generalisation of an atlas-based synthetic-CT algorithm to another centre and MR scanner for prostate MR-only radiotherapy

There is increasing interest in MR-only radiotherapy planning since it provides superb soft-tissue contrast without the registration uncertainties inherent in a CT-MR registration. However, MR images cannot readily provide the electron density information necessary for radiotherapy dose calculation. An algorithm which generates synthetic CTs for dose calculations from MR images of the prostate using an atlas of 3 T MR images has been previously reported by two of the authors. This paper aimed to evaluate this algorithm using MR data acquired at a different field strength and a different centre to the algorithm atlas. Twenty-one prostate patients received planning 1.5 T MR and CT scans with routine immobilisation devices on a flat-top couch set-up using external lasers. The MR receive coils were supported by a coil bridge. Synthetic CTs were generated from the planning MR images with ([Formula: see text]) and without (sCT) a one voxel body contour expansion included in the algorithm. This was to test whether this expansion was required for 1.5 T images. Both synthetic CTs were rigidly registered to the planning CT (pCT). A 6 MV volumetric modulated arc therapy plan was created on the pCT and recalculated on the sCT and [Formula: see text]. The synthetic CTs' dose distributions were compared to the dose distribution calculated on the pCT. The percentage dose difference at isocentre without the body contour expansion (sCT-pCT) was [Formula: see text] and with ([Formula: see text]-pCT) was [Formula: see text] (mean  ±  one standard deviation). The [Formula: see text] result was within one standard deviation of zero and agreed with the result reported previously using 3 T MR data. The sCT dose difference only agreed within two standard deviations. The mean  ±  one standard deviation gamma pass rate was [Formula: see text] for the sCT and [Formula: see text] for the [Formula: see text] (with [Formula: see text] global dose difference and [Formula: see text] distance to agreement gamma criteria). The one voxel body contour expansion improves the synthetic CT accuracy for MR images acquired at 1.5 T but requires the MR voxel size to be similar to the atlas MR voxel size. This study suggests that the atlas-based algorithm can be generalised to MR data acquired using a different field strength at a different centre.

Visualization of 4D multimodal imaging data and its applications in radiotherapy planning

PURPOSE

To explore the benefit of using 4D multimodal visualization and interaction techniques for defined radiotherapy planning tasks over a treatment planning system used in clinical routine (C-TPS) without dedicated 4D visualization.

METHODS

We developed a 4D visualization system (4D-VS) with dedicated rendering and fusion of 4D multimodal imaging data based on a list of requirements developed in collaboration with radiation oncologists. We conducted a user evaluation in which the benefits of our approach were evaluated in comparison to C-TPS for three specific tasks: assessment of internal target volume (ITV) delineation, classification of tumor location in peripheral or central, and assessment of dose distribution. For all three tasks, we presented test cases for which we measured correctness, certainty, consistency followed by an additional survey regarding specific visualization features.

RESULTS

Lower quality of the test ITVs (ground truth quality was available) was more likely to be detected using 4D-VS. ITV ratings were more consistent in 4D-VS and the classification of tumor location had a higher accuracy. Overall evaluation of the survey indicates 4D-VS provides better spatial comprehensibility and simplifies the tasks which were performed during testing.

CONCLUSIONS

The use of 4D-VS has improved the assessment of ITV delineations and classification of tumor location. The visualization features of 4D-VS have been identified as helpful for the assessment of dose distribution during user testing.

A precision 3D conformal treatment technique in rats: Application to whole-brain radiotherapy with hippocampal avoidance

PURPOSE

To develop and validate three-dimensional (3D) conformal hippocampal sparing whole-brain radiation therapy (HA-WBRT) for Wistar rats utilizing precision 3D-printed immobilization and micro-blocks. This technique paves the way for future preclinical studies investigating brain treatments that reduce neurotoxicity.

METHODS AND MATERIALS

A novel preclinical treatment planning and delivery process was developed to enable precision 3D conformal treatment and hippocampal avoidance capability for the Xrad 225cx small animal irradiator. A range of conformal avoidance plans were evaluated consisting of equiangularly spaced coplanar axial beams, with plans containing 2, 4, 7, and 8 fields. The hippocampal sparing and coverage of these plans were investigated through Monte Carlo dose calculation (SmART-Plan Xrad 225cx planning system). Treatment delivery was implemented through a novel process where hippocampal block shapes were computer generated from an MRI rat atlas which was registered to on-board cone beam CT of the rat in treatment position. The blocks were 3D printed with a tungsten-doped filament at lateral resolution of 80 μm. Precision immobilization was achieved utilizing a 3D-printed support system which enabled angled positioning of the rat head in supine position and bite block to improve coverage of the central diencephalon. Treatment delivery was verified on rodent-morphic Presage^® 3D dosimeters optically scanned at 0.2-mm isotropic resolution. Biological verification of hippocampal avoidance was performed with immunohistologic staining.

RESULTS

All simulated plans spared the hippocampus while delivering high dose to the brain (22.5-26.2 Gy mean dose to brain at mean hippocampal dose of 7 Gy). No significant improvement in hippocampal sparing was observed by adding beams beyond four fields. Dosimetric sparing of hippocampal region of the four-field plan was verified with the Presage^® dosimeter (mean dose = 9.6 Gy, D100% = 7.1 Gy). Simulation and dosimeter match at distance-to-agreement of 2 mm and dose difference of ±3% at 91.7% gamma passing rate (passing criteria of γ < 1). Agreement is less at 1 mm and ±5% at 69.0% gamma passing rate. The four-field plan was further validated with immunohistochemistry and showed a significant reduction in DNA double-strand breaks within the spared region compared with whole-brain irradiated groups (P = 0.021). However, coverage of the whole brain was low at 48.5-57.8% of the volume receiving 30Gy at 7Gy mean hippocampal dose in simulation and 46.7-52.5% in dosimetric measurements. This can be attributed to the shape of the rat hippocampus and the inability of treatment platform to employ non-coplanar beams.

CONCLUSION

A novel approach for conformal microradiation therapy using 3D-printing technology was developed, implemented, and validated. A workflow was developed to generate accurate 3D-printed blocks from registered high-resolution rat MRI atlas structures. Although hippocampus was spared with this technique, whole-brain target coverage was suboptimal, indicating that non-coplanar beams and IMRT capability may be required to meet stringent dose criteria associated with current human RTOG trials.

Voxel-by-voxel correlation between radiologically radiation induced lung injury and dose after image-guided, intensity modulated radiotherapy for lung tumors

PURPOSE

To correlate radiation dose to the risk of severe radiologically-evident radiation-induced lung injury (RRLI) using voxel-by-voxel analysis of the follow-up computed tomography (CT) of patients treated for lung cancer with hypofractionated helical Tomotherapy.

METHODS AND MATERIALS

The follow-up CT scans from 32 lung cancer patients treated with various regimens (5, 8, and 25 fractions) were registered to pre-treatment CT using deformable image registration (DIR). The change in density was calculated for each voxel within the combined lungs minus the planning target volume (PTV). Parameters of a Probit formula were derived by fitting the occurrences of changes of density in voxels greater than 0.361gcm^-3 to the radiation dose. The model's predictive capability was assessed using the area under receiver operating characteristic curve (AUC), the Kolmogorov-Smirnov test for goodness-of-fit, and the permutation test (P_test).

RESULTS

The best-fit parameters for prediction of RRLI 6months post RT were D₅₀ of 73.0 (95% CI 59.2.4-85.3.7)Gy, and m of 0.41 (0.39-0.46) for hypofractionated (5 and 8 fractions) and D₅₀ of 96.8 (76.9-123.9)Gy, and m of 0.36 (0.34-0.39) for 25 fractions RT. According to the goodness-of-fit test the null hypothesis of modeled and observed occurrence of RRLI coming from the same distribution could not be rejected. The AUC was 0.581 (0.575-0.583) for fractionated and 0.579 (0.577-0.581) for hypofractionated patients. The predictive models had AUC>upper 95% band of the P_test.

CONCLUSIONS

The correlation of voxel-by-voxel density increase with dose can be used as a support tool for differential diagnosis of tumor from benign changes in the follow-up of lung IMRT patients.

Optimization of a novel large field of view distortion phantom for MR-only treatment planning

PURPOSE

MR-only treatment planning requires images of high geometric fidelity, particularly for large fields of view (FOV). However, the availability of large FOV distortion phantoms with analysis software is currently limited. This work sought to optimize a modular distortion phantom to accommodate multiple bore configurations and implement distortion characterization in a widely implementable solution.

METHOD AND MATERIALS

To determine candidate materials, 1.0 T MR and CT images were acquired of twelve urethane foam samples of various densities and strengths. Samples were precision-machined to accommodate 6 mm diameter paintballs used as landmarks. Final material candidates were selected by balancing strength, machinability, weight, and cost. Bore sizes and minimum aperture width resulting from couch position were tabulated from the literature (14 systems, 5 vendors). Bore geometry and couch position were simulated using MATLAB to generate machine-specific models to optimize the phantom build. Previously developed software for distortion characterization was modified for several magnet geometries (1.0 T, 1.5 T, 3.0 T), compared against previously published 1.0 T results, and integrated into the 3D Slicer application platform.

RESULTS

All foam samples provided sufficient MR image contrast with paintball landmarks. Urethane foam (compressive strength ∼1000 psi, density ~20 lb/ft³ ) was selected for its accurate machinability and weight characteristics. For smaller bores, a phantom version with the following parameters was used: 15 foam plates, 55 × 55 × 37.5 cm³ (L×W×H), 5,082 landmarks, and weight ~30 kg. To accommodate > 70 cm wide bores, an extended build used 20 plates spanning 55 × 55 × 50 cm³ with 7,497 landmarks and weight ~44 kg. Distortion characterization software was implemented as an external module into 3D Slicer's plugin framework and results agreed with the literature.

CONCLUSION

The design and implementation of a modular, extendable distortion phantom was optimized for several bore configurations. The phantom and analysis software will be available for multi-institutional collaborations and cross-validation trials to support MR-only planning.

Quality assurance of radiotherapy in the ongoing EORTC 1219-DAHANCA-29 trial for HPV/p16 negative squamous cell carcinoma of the head and neck: Results of the benchmark case procedure

BACKGROUND AND PURPOSE

The phase III EORTC 1219-DAHANCA 29 intergroup trial evaluates the influence of nimorazole in patients with locally advanced head and neck cancer when treated with accelerated radiotherapy (RT) in combination with chemotherapy. This article describes the results of the RT Benchmark Case (BC) performed before patient inclusion.

MATERIALS AND METHODS

The participating centers were asked to perform a 2-step BC, consisting of (1) a delineation and (2) a planning exercise according to the protocol guidelines. Submissions were prospectively centrally reviewed and feedback was given to the submitting centers. Sørensen-Dice similarity index (DSI) and the 95th percentile Hausdorff distance (HD) were retrospectively used to evaluate the agreement between the centers and the expert contours.

RESULTS

Fifty-four submissions (34 delineation and 20 planning exercises) from 19 centers were reviewed. Nine (47%) centers needed to perform the delineation step twice and three (16%) centers 3 times before receiving an approval. An increase in DSI-value and a decrease in HD, in particular for the prophylactic Clinical Target Volume (pCTV), could be found for the resubmitted cases. No unacceptable variations could be found for the planning exercise.

CONCLUSIONS

These BC-results highlight the need for effective and prospective RTQA in clinical trials. Even with clearly defined protocol guidelines, delineation and not planning remain the main reason for unacceptable protocol variations. The introduction of more objective quantitative analysis methods, such as the HD and DSI, in future trials might strengthen the evaluation by experts.

Interobserver delineation uncertainty in involved-node radiation therapy (INRT) for early-stage Hodgkin lymphoma: on behalf of the Radiotherapy Committee of the EORTC lymphoma group

BACKGROUND AND PURPOSE

In early-stage classical Hodgkin lymphoma (HL) the target volume nowadays consists of the volume of the originally involved nodes. Delineation of this volume on a post-chemotherapy CT-scan is challenging. We report on the interobserver variability in target volume definition and its impact on resulting treatment plans.

MATERIALS AND METHODS

Two representative cases were selected (1: male, stage IB, localization: left axilla; 2: female, stage IIB, localizations: mediastinum and bilateral neck). Eight experienced observers individually defined the clinical target volume (CTV) using involved-node radiotherapy (INRT) as defined by the EORTC-GELA guidelines for the H10 trial. A consensus contour was generated and the standard deviation computed. We investigated the overlap between observer and consensus contour [Sørensen-Dice coefficient (DSC)] and the magnitude of gross deviations between the surfaces of the observer and consensus contour (Hausdorff distance). 3D-conformal (3D-CRT) and intensity-modulated radiotherapy (IMRT) plans were calculated for each contour in order to investigate the impact of interobserver variability on each treatment modality. Similar target coverage was enforced for all plans.

RESULTS

The median CTV was 120 cm³ (IQR: 95-173 cm³) for Case 1, and 255 cm³ (IQR: 183-293 cm³) for Case 2. DSC values were generally high (>0.7), and Hausdorff distances were about 30 mm. The SDs between all observer contours, providing an estimate of the systematic error associated with delineation uncertainty, ranged from 1.9 to 3.8 mm (median: 3.2 mm). Variations in mean dose resulting from different observer contours were small and were not higher in IMRT plans than in 3D-CRT plans.

CONCLUSIONS

We observed considerable differences in target volume delineation, but the systematic delineation uncertainty of around 3 mm is comparable to that reported in other tumour sites. This report is a first step towards calculating an evidence-based planning target volume margin for INRT in HL.

A cardiac contouring atlas for radiotherapy

BACKGROUND AND PURPOSE

The heart is a complex anatomical organ and contouring the cardiac substructures is challenging. This study presents a reproducible method for contouring left ventricular and coronary arterial segments on radiotherapy CT-planning scans.

MATERIAL AND METHODS

Segments were defined from cardiology models and agreed by two cardiologists. Reference atlas contours were delineated and written guidelines prepared. Six radiation oncologists tested the atlas. Spatial variation was assessed using the DICE similarity coefficient (DSC) and the directed Hausdorff average distance (d→H,avg). The effect of spatial variation on doses was assessed using six different breast cancer regimens.

RESULTS

The atlas enabled contouring of 15 cardiac segments. Inter-observer contour overlap (mean DSC) was 0.60-0.73 for five left ventricular segments and 0.10-0.53 for ten coronary arterial segments. Inter-observer contour separation (mean d→H,avg) was 1.5-2.2mm for left ventricular segments and 1.3-5.1mm for coronary artery segments. This spatial variation resulted in <1Gy dose variation for most regimens and segments, but 1.2-21.8Gy variation for segments close to a field edge.

CONCLUSIONS

This cardiac atlas enables reproducible contouring of segments of the left ventricle and main coronary arteries to facilitate future studies relating cardiac radiation doses to clinical outcomes.

The utilization of magnetic resonance imaging in the operating room

Online image guidance in the operating room using ultrasound imaging led to the resurgence of prostate brachytherapy in the 1980s. Here we describe the evolution of integrating MRI technology in the brachytherapy suite or operating room. Given the complexity, cost, and inherent safety issues associated with MRI system integration, first steps focused on the computational integration of images rather than systems. This approach has broad appeal given minimal infrastructure costs and efficiencies comparable with standard care workflows. However, many concerns remain regarding accuracy of registration through the course of a brachytherapy procedure. In selected academic institutions, MRI systems have been integrated in or near the brachytherapy suite in varied configurations to improve the precision and quality of treatments. Navigation toolsets specifically adapted to prostate brachytherapy are in development and are reviewed.

Predictive modelling analysis for development of a radiotherapy decision support system in prostate cancer: a preliminary study

Purpose

The aim of this study is to develop predictive models to predict organ at risk (OAR) complication level, classification of OAR dose-volume and combination of this function with our in-house developed treatment decision support system.

Materials and methods

We analysed the support vector machine and decision tree algorithm for predicting OAR complication level and toxicity in order to integrate this function into our in-house radiation treatment planning decision support system. A total of 12 TomoTherapyTM treatment plans for prostate cancer were established, and a hundred modelled plans were generated to analyse the toxicity prediction for bladder and rectum.

Results

The toxicity prediction algorithm analysis showed 91·0% accuracy in the training process. A scatter plot for bladder and rectum was obtained by 100 modelled plans and classification result derived. OAR complication level was analysed and risk factor for 25% bladder and 50% rectum was detected by decision tree. Therefore, it was shown that complication prediction of patients using big data-based clinical information is possible.

Conclusion

We verified the accuracy of the tested algorithm using prostate cancer cases. Side effects can be minimised by applying this predictive modelling algorithm with the planning decision support system for patient-specific radiotherapy planning.

Hybrid positron emission tomography segmentation of heterogeneous lung tumors using 3D Slicer: improved GrowCut algorithm with threshold initialization

This paper presents an improved GrowCut (IGC), a positron emission tomography-based segmentation algorithm, and tests its clinical applicability. Contrary to the traditional method that requires the user to provide the initial seeds, the IGC algorithm starts with a threshold-based estimate of the tumor and a three-dimensional morphologically grown shell around the tumor as the foreground and background seeds, respectively. The repeatability of IGC from the same observer at multiple time points was compared with the traditional GrowCut algorithm. The algorithm was tested in 11 nonsmall cell lung cancer lesions and validated against the clinician-defined manual contour and compared against the clinically used 25% of the maximum standardized uptake value [SUV-(max)], 40% [Formula: see text], and adaptive threshold methods. The time to edit IGC-defined functional volume to arrive at the gross tumor volume (GTV) was compared with that of manual contouring. The repeatability of the IGC algorithm was very high compared with the traditional GrowCut ([Formula: see text]) and demonstrated higher agreement with the manual contour with respect to threshold-based methods. Compared with manual contouring, editing the IGC achieved the GTV in significantly less time ([Formula: see text]). The IGC algorithm offers a highly repeatable functional volume and serves as an effective initial guess that can well minimize the time spent on labor-intensive manual contouring.

Characterization of deformation and physical force in uniform low contrast anatomy and its impact on accuracy of deformable image registration

PURPOSE

Little is known about the effect of force on organ deformation and consequently its impact on precision dose delivery. The purpose of this study was to evaluate the fundamental relationship between anatomic deformation and its causative physical force to ascertain if a threshold limit exists for deformable image registration (DIR) accuracy in uniform low contrast anatomy, beyond which its applicability may be clinically inappropriate.

METHODS

To simulate a simplified model, a tissue equivalent deformable bladder phantom with 21 implanted fiducial markers was developed using a viscoelastic polymer. The bladder phantom was deformed by applying a force in increments from 10 to 70 N. DIR accuracy was studied using intensity based mim and Velocity B-spline algorithms by comparing the 3D vector of the 21 marker locations at the original target image with the synthetically derived marker positions from each target image obtained from DIR.

RESULTS

The relationship between applied force in 1D deformation along the axis of applied force and 3D deformation of the phantom showed a linear response. The maximum and average displacements of markers exhibited a nonlinear response to the applied force. In the absence of implanted markers, DIR performance was suboptimal with a threshold limit of only 20 N (5 mm deformation) beyond which the average marker error was ≥3 mm. DIR performance improved significantly with the addition of only one marker for the intensity based mim algorithm. In contrast, the Velocity B-spline algorithm showed reduced sensitivity to the number of markers introduced in both the source and target images.

CONCLUSIONS

The limits of applicability of DIR are strongly dependent on the magnitude of deformation. There is a threshold limit beyond which the accuracy of DIR fails in uniform low contrast anatomy. The sensitivity of the DIR performance to the number of fiducial markers present indicates that if DIR performance is solely assessed with the contrast rich features present in clinical anatomy, the results may not be reflective of the true DIR performance in uniform low contrast anatomy.

Visualization of Deformable Image Registration Quality Using Local Image Dissimilarity

Deformable image registration (DIR) has the potential to improve modern radiotherapy in many aspects, including volume definition, treatment planning and image-guided adaptive radiotherapy. Studies have shown its possible clinical benefits. However, measuring DIR accuracy is difficult without known ground truth, but necessary before integration in the radiotherapy workflow. Visual assessment is an important step towards clinical acceptance. We propose a visualization framework which supports the exploration and the assessment of DIR accuracy. It offers different interaction and visualization features for exploration of candidate regions to simplify the process of visual assessment. The visualization is based on voxel-wise comparison of local image patches for which dissimilarity measures are computed and visualized to indicate locally the registration results. We performed an evaluation with three radiation oncologists to demonstrate the viability of our approach. In the evaluation, lung regions were rated by the participants with regards to their visual accuracy and compared to the registration error measured with expert defined landmarks. Regions rated as "accepted" had an average registration error of 1.8 mm, with the highest single landmark error being 3.3 mm. Additionally, survey results show that the proposed visualizations support a fast and intuitive investigation of DIR accuracy, and are suitable for finding even small errors.

Technical Note: scuda: A software platform for cumulative dose assessment

PURPOSE

Accurate tracking of anatomical changes and computation of actually delivered dose to the patient are critical for successful adaptive radiation therapy (ART). Additionally, efficient data management and fast processing are practically important for the adoption in clinic as ART involves a large amount of image and treatment data. The purpose of this study was to develop an accurate and efficient Software platform for CUmulative Dose Assessment (scuda) that can be seamlessly integrated into the clinical workflow.

METHODS

scuda consists of deformable image registration (DIR), segmentation, dose computation modules, and a graphical user interface. It is connected to our image PACS and radiotherapy informatics databases from which it automatically queries/retrieves patient images, radiotherapy plan, beam data, and daily treatment information, thus providing an efficient and unified workflow. For accurate registration of the planning CT and daily CBCTs, the authors iteratively correct CBCT intensities by matching local intensity histograms during the DIR process. Contours of the target tumor and critical structures are then propagated from the planning CT to daily CBCTs using the computed deformations. The actual delivered daily dose is computed using the registered CT and patient setup information by a superposition/convolution algorithm, and accumulated using the computed deformation fields. Both DIR and dose computation modules are accelerated by a graphics processing unit.

RESULTS

The cumulative dose computation process has been validated on 30 head and neck (HN) cancer cases, showing 3.5 ± 5.0 Gy (mean±STD) absolute mean dose differences between the planned and the actually delivered doses in the parotid glands. On average, DIR, dose computation, and segmentation take 20 s/fraction and 17 min for a 35-fraction treatment including additional computation for dose accumulation.

CONCLUSIONS

The authors developed a unified software platform that provides accurate and efficient monitoring of anatomical changes and computation of actually delivered dose to the patient, thus realizing an efficient cumulative dose computation workflow. Evaluation on HN cases demonstrated the utility of our platform for monitoring the treatment quality and detecting significant dosimetric variations that are keys to successful ART.

A Novel Respiratory Motion Perturbation Model Adaptable to Patient Breathing Irregularities

PURPOSE

To develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities.

METHODS AND MATERIALS

A novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained 2 terms: the initial tumor motion trajectory, measured from 4-dimensional computed tomography (4DCT) images, and motion perturbation, calculated from breathing variations in tidal volume (TV) and breathing pattern (BP). The motion perturbation was derived from the patient-specific anatomy, tumor-specific location, and time-dependent breathing variations. Ten patients were studied, and 2 amplitude-binned 4DCT images for each patient were acquired within 2 weeks. The motion trajectories of 40 corresponding bifurcation points in both 4DCT images of each patient were obtained using deformable image registration. An in-house 4D data processing toolbox was developed to calculate the TV and BP as functions of the breathing phase. The motion was predicted from the simulation 4DCT scan to the treatment 4DCT scan, and vice versa, resulting in 800 predictions. For comparison, noncorrected motion differences and the predictions from a published 5-dimensional model were used.

RESULTS

The average motion range in the superoinferior direction was 9.4 ± 4.4 mm, the average ΔTV ranged from 10 to 248 mm³ (-26% to 61%), and the ΔBP ranged from 0 to 0.2 (-71% to 333%) between the 2 4DCT scans. The mean noncorrected motion difference was 2.0 ± 2.8 mm between 2 4DCT motion trajectories. After applying the RMP model, the mean motion difference was reduced significantly to 1.2 ± 1.8 mm (P=.0018), a 40% improvement, similar to the 1.2 ± 1.8 mm (P=.72) predicted with the 5-dimensional model.

CONCLUSIONS

A novel physical RMP model was developed with an average accuracy of 1.2 ± 1.8 mm for interfraction motion prediction, similar to that of a published lung motion model. This physical RMP was analytically derived and is able to adapt to breathing irregularities. Further improvement of this RMP model is under investigation.

Three-dimensional customized bolus for intensity-modulated radiotherapy in a patient with Kimura's disease involving the auricle

In radiotherapy, a commercial bolus often does not provide a suitable fit over irregular surfaces. To address this issue, we fabricated a customized bolus using 3D printing technology. The aim of our study was to evaluate the application of this 3D-printed bolus in a clinical setting. The patient was a 45-year-old man with recurrent Kimura's disease involving the auricle, receiving radiotherapy in our oncology department. A customized bolus, 5mm in thickness, was fabricated based on reconstruction of computed tomography (CT) images. The bolus was printed on a Dimension 1200 series SST 3D printer. Repeat CT-based simulation indicated an acceptable fit of the 3D-printed bolus to the target region, with a maximum air gap of less than 5mm at the tragus. Most of the surface area of the target region was covered by the 95% isodose line. The plan with the 3D-printed bolus improved target coverage compared to that without a bolus. And the plan with the 3D-printed bolus yielded comparable results to those with the paraffin wax bolus. In conclusion, a customized bolus using a 3D printer was successfully applied to an irregular surface.

Intensity-modulated radiotherapy versus proton radiotherapy versus carbon ion radiotherapy for spinal bone metastases: a treatment planning study

Outcomes for selected patients with spinal metastases may be improved by dose escalation using stereotactic body radiotherapy (SBRT). As target geometry is complex, we compared SBRT plans using step‐and‐shoot intensity‐modulated radiotherapy (IMRT), carbon ion RT, and proton RT. We prepared plans treating cervical, thoracic, and lumbar metastases for three different techniques — IMRT, carbon ion, and proton plans — to deliver a median single 24 Gy fraction such that at least 90% of the planning target volume (PTV) received more than 18 Gy and were compared for PTV coverage, normal organ sparing, and estimated delivery time. PTV coverage did not show significant differences for the techniques, spinal cord dose sparing was lowered with the particle techniques. For the cervical lesion spinal cord maximum dose, dose of 1% (D1), and percent volume receiving 10 Gy (V10Gy) were 11.9 Gy, 9.1 Gy, and 0.5% in IMRT. This could be lowered to 4.3 Gy, 2.5 Gy, and 0% in carbon ion planning and to 8.1 Gy, 6.1 Gy, and 0% in proton planning. Regarding the thoracic lesion no difference was found for the spinal cord. For the lumbar lesion maximum dose, D1 and percent volume receiving 5 Gy (V5Gy) were 13.4 Gy, 8.9 Gy, and 8.9% for IMRT; 1.8 Gy, 0.7 Gy, and 0% for carbon ions; and 0 Gy,<0.01 Gy, and 0% for protons. Estimated mean treatment times were shorter in particle techniques (6–7 min vs. 12–14 min with IMRT). This planning study indicates that carbon ion and proton RT can deliver high‐quality PTV coverage for complex treatment volumes that surround the spinal cord.

PACS number: 87.55.dk

An open-source genetic algorithm for determining optimal seed distributions for low-dose-rate prostate brachytherapy

PURPOSE

An open source optimizer that generates seed distributions for low-dose-rate prostate brachytherapy was designed, tested, and validated.

METHODS

The optimizer was a simple genetic algorithm (SGA) that, given a set of prostate and urethra contours, determines the optimal seed distribution in terms of coverage of the prostate with the prescribed dose while avoiding hotspots within the urethra. The algorithm was validated in a retrospective study on 45 previously contoured low-dose-rate prostate brachytherapy patients. Dosimetric indices were evaluated to ensure solutions adhered to clinical standards. The SGA performance was further benchmarked by comparing solutions obtained from a commercial optimizer (inverse planning simulated annealing [IPSA]) with the same cohort of 45 patients.

RESULTS

Clinically acceptable target coverage by the prescribed dose (V100) was obtained for both SGA and IPSA, with a mean ± standard deviation of 98 ± 2% and 99.5 ± 0.5%, respectively. For the prostate D90, SGA and IPSA yielded 177 ± 8 Gy and 186 ± 7 Gy, respectively, which were both clinically acceptable. Both algorithms yielded reasonable dose to the rectum, with V100 < 0.3 cc. A reduction in dose to the urethra was seen using SGA. SGA solutions showed a slight prostate volume dependence, with smaller prostates (<25 cc) yielding less desirable, although still clinically viable, dosimetric outcomes. SGA plans used, on average, fewer needles than IPSA (21 vs. 24, respectively), which may lead to a reduction in urinary toxicity and edema that alters post-implant dosimetry.

CONCLUSIONS

An open source SGA was validated that provides a research tool for the brachytherapy community.

Contouring variability of human- and deformable-generated contours in radiotherapy for prostate cancer

This study was designed to evaluate contouring variability of human-and deformable-generated contours on planning CT (PCT) and CBCT for ten patients with low-or intermediate-risk prostate cancer. For each patient in this study, five radiation oncologists contoured the prostate, bladder, and rectum, on one PCT dataset and five CBCT datasets. Consensus contours were generated using the STAPLE method in the CERR software package. Observer contours were compared to consensus contour, and contour metrics (Dice coefficient, Hausdorff distance, Contour Distance, Center-of-Mass [COM] Deviation) were calculated. In addition, the first day CBCT was registered to subsequent CBCT fractions (CBCTn: CBCT2-CBCT5) via B-spline Deformable Image Registration (DIR). Contours were transferred from CBCT1 to CBCTn via the deformation field, and contour metrics were calculated through comparison with consensus contours generated from human contour set. The average contour metrics for prostate contours on PCT and CBCT were as follows: Dice coefficient-0.892 (PCT), 0.872 (CBCT-Human), 0.824 (CBCT-Deformed); Hausdorff distance-4.75 mm (PCT), 5.22 mm (CBCT-Human), 5.94 mm (CBCT-Deformed); Contour Distance (overall contour)-1.41 mm (PCT), 1.66 mm (CBCT-Human), 2.30 mm (CBCT-Deformed); COM Deviation-2.01 mm (PCT), 2.78 mm (CBCT-Human), 3.45 mm (CBCT-Deformed). For human contours on PCT and CBCT, the difference in average Dice coefficient between PCT and CBCT (approx. 2%) and Hausdorff distance (approx. 0.5 mm) was small compared to the variation between observers for each patient (standard deviation in Dice coefficient of 5% and Hausdorff distance of 2.0 mm). However, additional contouring variation was found for the deformable-generated contours (approximately 5.0% decrease in Dice coefficient and 0.7 mm increase in Hausdorff distance relative to human-generated contours on CBCT). Though deformable contours provide a reasonable starting point for contouring on CBCT, we conclude that contours generated with B-Spline DIR require physician review and editing if they are to be used in the clinic.

Radiotherapy of Hodgkin and Non-Hodgkin Lymphoma

Purpose:

To improve the contouring of clinical target volume for the radiotherapy of neck Hodgkin/non-Hodgkin lymphoma by localizing the prechemotherapy gross target volume onto the simulation computed tomography using [18F]-fluorodeoxyglucose positron emission tomography/computed tomography.

Material and Methods:

The gross target volume delineated on prechemotherapy [18F]-fluorodeoxyglucose positron emission tomography/computed tomography images was warped onto simulation computed tomography using deformable image registration. Fifteen patients with neck Hodgkin/non-Hodgkin lymphoma were analyzed. Quality of image registration was measured by computing the Dice similarity coefficient on warped organs at risk. Five radiation oncologists visually scored the localization of automatic gross target volume, ranking it from 1 (wrong) to 5 (excellent). Deformable registration was compared to rigid registration by computing the overlap index between the automatic gross target volume and the planned clinical target volume and quantifying the V95 coverage.

Results:

The Dice similarity coefficient was 0.80 ± 0.07 (median ± quartiles). The physicians’ survey had a median score equal to 4 (good). By comparing the rigid versus deformable registration, the overlap index increased from a factor of about 4 and the V95 (percentage of volume receiving the 95% of the prescribed dose) went from 0.84 ± 0.38 to 0.99 ± 0.10 (median ± quartiles).

Conclusion:

This study demonstrates the impact of using deformable registration between prechemotherapy [18F]-fluorodeoxyglucose positron emission tomography/computed tomography and simulation computed tomography, in order to automatically localize the gross target volume for radiotherapy treatment of patients with Hodgkin/non-Hodgkin lymphoma.

Video-rate optical dosimetry and dynamic visualization of IMRT and VMAT treatment plans in water using Cherenkov radiation

PURPOSE

A novel technique for optical dosimetry of dynamic intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) plans was investigated for the first time by capturing images of the induced Cherenkov radiation in water.

METHODS

A high-sensitivity, intensified CCD camera (ICCD) was configured to acquire a two-dimensional (2D) projection image of the Cherenkov radiation induced by IMRT and VMAT plans, based on the Task Group 119 (TG-119) C-Shape geometry. Plans were generated using the Varian Eclipse treatment planning system (TPS) and delivered using 6 MV x-rays from a Varian TrueBeam Linear Accelerator (Linac) incident on a water tank doped with the fluorophore quinine sulfate. The ICCD acquisition was gated to the Linac target trigger pulse to reduce background light artifacts, read out for a single radiation pulse, and binned to a resolution of 512 × 512 pixels. The resulting videos were analyzed temporally for various regions of interest (ROI) covering the planning target volume (PTV) and organ at risk (OAR), and summed to obtain an overall light intensity distribution, which was compared to the expected dose distribution from the TPS using a gamma-index analysis.

RESULTS

The chosen camera settings resulted in 23.5 frames per second dosimetry videos. Temporal intensity plots of the PTV and OAR ROIs confirmed the preferential delivery of dose to the PTV versus the OAR, and the gamma analysis yielded 95.9% and 96.2% agreement between the experimentally captured Cherenkov light distribution and expected TPS dose distribution based upon a 3%/3 mm dose difference and distance-to-agreement criterion for the IMRT and VMAT plans, respectively.

CONCLUSIONS

The results from this initial study demonstrate the first documented use of Cherenkov radiation for video-rate optical dosimetry of dynamic IMRT and VMAT treatment plans. The proposed modality has several potential advantages over alternative methods including the real-time nature of the acquisition, and upon future refinement may prove to be a robust and novel dosimetry method with both research and clinical applications.

Magnetic resonance imaging and histology correlation in the neocortex in temporal lobe epilepsy

OBJECTIVE

To investigate the histopathological correlates of quantitative relaxometry and diffusion tensor imaging (DTI) and to determine their efficacy in epileptogenic lesion detection for preoperative evaluation of focal epilepsy.

METHODS

We correlated quantitative relaxometry and DTI with histological features of neuronal density and morphology in 55 regions of the temporal lobe neocortex, selected from 13 patients who underwent epilepsy surgery. We made use of a validated nonrigid image registration protocol to obtain accurate correspondences between in vivo magnetic resonance imaging and histology images.

RESULTS

We found T1 to be a predictor of neuronal density in the neocortical gray matter (GM) using linear mixed effects models with random effects for subjects. Fractional anisotropy (FA) was a predictor of neuronal density of large-caliber neurons only (pyramidal cells, layers 3 and 5). Comparing multivariate to univariate mixed effects models with nested variables demonstrated that employing T1 and FA together provided a significantly better fit than T1 or FA alone in predicting density of large-caliber neurons. Correlations with clinical variables revealed significant positive correlations between neuronal density and age (rs  = 0.726, pfwe  = 0.021). This study is the first to relate in vivo T1 and FA values to the proportion of neurons in GM.

INTERPRETATION

Our results suggest that quantitative T1 mapping and DTI may have a role in preoperative evaluation of focal epilepsy and can be extended to identify GM pathology in a variety of neurological disorders.

Design and initial evaluation of a treatment planning software system for MRI-guided laser ablation in the brain

PURPOSE

An open-source software system for planning magnetic resonance (MR)-guided laser-induced thermal therapy (MRgLITT) in brain is presented. The system was designed to provide a streamlined and operator-friendly graphical user interface (GUI) for simulating and visualizing potential outcomes of various treatment scenarios to aid in decisions on treatment approach or feasibility.

METHODS

A portable software module was developed on the 3D Slicer platform, an open-source medical imaging and visualization framework. The module introduces an interactive GUI for investigating different laser positions and power settings as well as the influence of patient-specific tissue properties for quickly creating and evaluating custom treatment options. It also provides a common treatment planning interface for use by both open-source and commercial finite element solvers. In this study, an open-source finite element solver for Pennes' bioheat equation is interfaced to the module to provide rapid 3D estimates of the steady-state temperature distribution and potential tissue damage in the presence of patient-specific tissue boundary conditions identified on segmented MR images.

RESULTS

The total time to initialize and simulate an MRgLITT procedure using the GUI was [Formula: see text]5 min. Each independent simulation took [Formula: see text]30 s, including the time to visualize the results fused with the planning MRI. For demonstration purposes, a simulated steady-state isotherm contour [Formula: see text] was correlated with MR temperature imaging (N = 5). The mean Hausdorff distance between simulated and actual contours was 2.0 mm [Formula: see text], whereas the mean Dice similarity coefficient was 0.93 [Formula: see text].

CONCLUSIONS

We have designed, implemented, and conducted initial feasibility evaluations of a software tool for intuitive and rapid planning of MRgLITT in brain. The retrospective in vivo dataset presented herein illustrates the feasibility and potential of incorporating fast, image-based bioheat predictions into an interactive virtual planning environment for such procedures.