Volumetric Uncertainty in Radiotherapy

The influence of patient positioning and immobilization equipment on MR image quality and image registration in radiation therapy

INTRODUCTION

MRI is preferred for brain tumor assessment, while CT is used for radiotherapy simulation. This study evaluated immobilization equipment's impact on CT-MRI registration accuracy and MR image quality in RT setup.

METHODS

We included CT and MR images from 11 patients with high-grade glioma, all of whom were immobilized with a thermoplastic mask and headrest. T1- and T2-weighted MR images were acquired using an MR head coil in a diagnostic setup (DS) and a body matrix coil in RT setup. To assess MR image quality, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were considered in some dedicated regions of interest. We also evaluated the impact of immobilization equipment on CT-MRI rigid registration using line profile and external contour methods.

RESULTS

The CNR and SNR reduction was in the RT setup of imaging. This was more evident in T1-weighted images than in T2-weighted ones. The SNR decreased by 14.91% and 12.09%, while CNR decreased by 25.12% and 20.15% in T1- and T2-weighted images, respectively. The immobilization equipment in the RT setup decreased the mean error in rigid registration by 1.02 mm. The external contour method yielded Dice similarity coefficients (DSC) of 0.84 and 0.92 for CT-DS MRI and CT-RT MRI registration, respectively.

CONCLUSION

The image quality reduction in the RT setup was due to the imaged region's anatomy and its position relative to the applied coil. Furthermore, optimizing the pulse sequence is crucial for MR imaging in RT applications. Although the use of immobilization equipment may decrease the image quality in the RT setup, it does not affect organ delineation, and the image quality is still satisfactory for this purpose. Also, the use of immobilization equipment in the RT setup has increased registration accuracy.

Contour similarity and its implication on inverse prostate SBRT treatment planning

PURPOSE

Success of auto-segmentation is measured by the similarity between auto and manual contours that is often quantified by Dice coefficient (DC). The dosimetric impact of contour variability on inverse planning has been rarely reported. The main aim of this study is to investigate whether automatically generated organs-at-risk (OARs) could be used in inverse prostate stereotactic body radiation therapy (SBRT) planning and whether the dosimetric parameters are still clinically acceptable after radiation oncologists modify the OARs.

METHODS AND MATERIALS

Planning computed tomography images from 10 patients treated with SBRT for prostate cancer were selected and automatically segmented by commercially available atlas-based software. The automatically generated OAR contours were compared with the manually drawn contours. Two volumetric modulated arc therapy (VMAT) plans, autoRec-VMAT (where only automatically generated rectums were used in optimization) and autoAll-VMAT (where automatically generated OARs were used in inverse optimization) were generated. Dosimetric parameters based on the manually drawn PTV and OARs were compared with the clinically approved plans.

RESULTS

The DCs for the rectum contours varied from 0.55 to 0.74 with a mean value of 0.665. Differences of D₉₅ of the PTV between autoRec-VMAT and manu-VMAT plans varied from 0.03% to -2.85% with a mean value of -0.64%. Differences of D_0.03cc of manual rectum between the two plans varied from -0.86% to 9.94% with a mean value of 2.71%. D₉₅ of PTV between autoAll-VMAT and manu-VMAT plans varied from 0.28% to -2.9% with a mean value -0.83%. Differences of D_0.03cc of manual rectum between the two plans varied from -0.76% to 6.72% with a mean value of 2.62%.

CONCLUSION

Our study implies that it is possible to use unedited automatically generated OARs to perform initial inverse prostate SBRT planning. After radiation oncologists modify/approve the OARs, the plan qualities based on the manually drawn OARs are still clinically acceptable, and a re-optimization may not be needed.

Evaluation of the clinical impact of the differences between planned and delivered dose in prostate cancer radiotherapy based on CT-on-rails IGRT and patient-reported outcome scores

PURPOSE

To estimate the clinical impact of differences between delivered and planned dose using dose metrics and normal tissue complication probability (NTCP) modeling.

METHODS

Forty-six consecutive patients with prostate adenocarcinoma between 2010 and 2015 treated with intensity-modulated radiation therapy (IMRT) and who had undergone computed tomography on rails imaging were included. Delivered doses to bladder and rectum were estimated using a contour-based deformable image registration method. The bladder and rectum NTCP were calculated using dose-response parameters applied to planned and delivered dose distributions. Seven urinary and gastrointestinal symptoms were prospectively collected using the validated prostate cancer symptom indices patient reported outcome (PRO) at pre-treatment, weekly treatment, and post-treatment follow-up visits. Correlations between planned and delivered doses against PRO were evaluated in this study.

RESULTS

Planned mean doses to bladder and rectum were 44.9 ± 13.6 Gy and 42.8 ± 7.3 Gy, while delivered doses were 46.1 ± 13.4 Gy and 41.3 ± 8.7 Gy, respectively. D_10cc for rectum was 64.1 ± 7.6 Gy for planned and 60.1 ± 9.3 Gy for delivered doses. NTCP values of treatment plan were 22.3% ± 8.4% and 12.6% ± 5.9%, while those for delivered doses were 23.2% ± 8.4% and 9.9% ± 8.3% for bladder and rectum, respectively. Seven of 25 patients with follow-up data showed urinary complications (28%) and three had rectal complications (12%). Correlations of NTCP values of planned and delivered doses with PRO follow-up data were random for bladder and moderate for rectum (0.68 and 0.67, respectively).

CONCLUSION

Sensitivity of bladder to clinical variations of dose accumulation indicates that an automated solution based on a DIR that considers inter-fractional organ deformation could recommend intervention. This is intended to achieve additional rectum sparing in cases that indicate higher than expected dose accumulation early during patient treatment in order to prevent acute severity of bowel symptoms.

FIELDRT: an open-source platform for the assessment of target volume delineation in radiation therapy

Objectives:

Target volume delineation (TVD) has been identified as a weakness in the accuracy of radiotherapy, both within and outside of clinical trials due to the intra/interobserver variations affecting the TVD quality. Sources of variations such as poor compliance or protocol violation may have adverse effect on treatment outcomes. In this paper, we present and describe the FIELD^RT software developed for the ARENA project to improve the quality of TVD through qualitative and quantitative feedbacks and individual and personalized summary of trainee”s performance.

Methods:

For each site-specific clinical case included in the FIELD^RT software, reference volumes, minimum and maximum “acceptable” volumes and organ at risk were derived by outlines of consultants and senior trainees. The software components currently developed include: (a) user-friendly importing interface (b) analysis toolbox to compute quantitative and qualitative (c) visualiser and (d) structured report generator for personalised feedback. The FIELD^RT software was validated by comparing the performance of 63 trainees and by measuring performance over time. In addition, a trainee evaluation day was held in 2019 to collect feedback on FIELD^RT.

Results:

Results show the trainees’ improvement when reoutlining a case after reviewing the feedback generated from the FIELD^RT software. Comments and feedback received after evaluation day were positive and confirmed that FIELD^RT can be a useful application for training purposes.

Conclusion:

We presented a new open-source software to support education in TVD and ongoing continuous professional development for clinical oncology trainees and consultants. ARENA in combination with FIELD^RT implements site-specific modules with reference target and organs at risk volumes and automatically evaluates individual performance using several quantitative and qualitative feedbacks. Pilot results suggests this software could be used as an education tool to reduce variation in TVD so to guarantee high quality in radiotherapy.

Advances in knowledge:

FIELD^RT is a new easy and free to use software aiming at supporting education in TVD and ongoing continuous professional development. The software provides quantitative/qualitative feedback and an exportable report with an individual and personalised summary of trainee’s performance.

Evaluation of a commercial DIR platform for contour propagation in prostate cancer patients treated with IMRT/VMAT

Purpose

To assess the performance and limitations of contour propagation with three commercial deformable image registration (DIR) algorithms using fractional scans of CT‐on‐rails (CTOR) and Cone Beam CT (CBCT) in image guided prostate therapy patients treated with IMRT/VMAT.

Methods

Twenty prostate cancer patients treated with IMRT/VMAT were selected for analysis. A total of 453 fractions across those patients were analyzed. Image data were imported into MIM (MIM Software, Inc., Cleveland, OH) and three DIR algorithms (DIR Profile, normalized intensity‐based (NIB) and shadowed NIB DIR algorithms) were applied to deformably register each fraction with the planning CT. Manually drawn contours of bladder and rectum were utilized for comparison against the DIR propagated contours in each fraction. Four metrics were utilized in the evaluation of contour similarity, the Hausdorff Distance (HD), Mean Distance to Agreement (MDA), Dice Similarity Coefficient (DSC), and Jaccard indices. A subfactor analysis was performed per modality (CTOR vs. CBCT) and time (fraction). Point estimates and 95% confidence intervals were assessed via a Linear Mixed Effect model for the contour similarity metrics.

Results

No statistically significant differences were observed between the DIR Profile and NIB algorithms. However, statistically significant differences were observed between the shadowed NIB and NIB algorithms for some of the DIR evaluation metrics. The Hausdorff Distance calculation showed the NIB propagated contours vs. shadowed NIB propagated contours against the manual contours were 14.82 mm vs. 8.34 mm for bladder and 15.87 mm vs. 11 mm for rectum, respectively. Similarly, the Mean Distance to Agreement calculation comparing the NIB propagated contours vs. shadowed NIB propagated contours against the manual contours were 2.43 mm vs. 0.98 mm for bladder and 2.57 mm vs. 1.00 mm for rectum, respectively. The Dice Similarity Coefficients comparing the NIB propagated contours and shadowed NIB propagated contours against the manual contours were 0.844 against 0.936 for bladder and 0.772 against 0.907 for rectum, respectively. The Jaccard indices comparing the NIB propagated contours and shadowed NIB propagated contours against the manual contours were 0.749 against 0.884 for bladder and 0.637 against 0.831 for rectum, respectively. The shadowed NIB DIR, which showed the closest agreement with the manual contours performed significantly better than the DIR Profile in all the comparisons. The OAR with the greatest agreement varied substantially across patients and image guided radiation therapy (IGRT) modality. Intra‐patient variability of contour metric evaluation was insignificant across all the DIR algorithms. Statistical significance at α = 0.05 was observed for manual vs. deformably propagated contours for bladder for all the metrics except Hausdorff Distance (P = 0.01 for MDA, P = 0.02 for DSC, P = 0.01 for Jaccard), whereas the corresponding values for rectum were: P = 0.03 for HD, P = 0.01 for MDA, P < 0.01 for DSC, P < 0.01 for Jaccard. The performance of the different metrics varied slightly across the fractions of each patient, which indicates that weekly contour propagation models provide a reasonable approximation of the daily contour propagation models.

Conclusion

The high variance of Hausdorff Distance across all automated methods for bladder indicates widely variable agreement across fractions for all patients. Lower variance across all modalities, methods, and metrics were observed for rectum. The shadowed NIB propagated contours were substantially more similar to the manual contours than the DIR Profile or NIB contours for both the CTOR and CBCT imaging modalities. The relationship of each algorithm to similarity with manual contours is consistent across all observed metrics and organs. Screening of image guidance for substantial differences in bladder and rectal filling compared with the planning CT reference could aid in identifying fractions for which automated DIR would prove insufficient.

Assessment of image quality of a radiotherapy-specific hardware solution for PET/MRI in head and neck cancer patients

BACKGROUND AND PURPOSE

Functional PET/MRI has great potential to improve radiotherapy planning (RTP). However, data integration requires imaging with radiotherapy-specific patient positioning. Here, we investigated the feasibility and image quality of radiotherapy-customized PET/MRI in head-and-neck cancer (HNC) patients using a dedicated hardware setup.

MATERIAL AND METHODS

Ten HNC patients were examined with simultaneous PET/MRI before treatment, with radiotherapy and diagnostic scan setup, respectively. We tested feasibility of radiotherapy-specific patient positioning and compared the image quality between both setups by pairwise image analysis of 18F-FDG-PET, T1/T2-weighted and diffusion-weighted MRI. For image quality assessment, similarity measures including average symmetric surface distance (ASSD) of PET and MR-based tumor contours, MR signal-to-noise ratio (SNR) and mean apparent diffusion coefficient (ADC) value were used.

RESULTS

PET/MRI in radiotherapy position was feasible - all patients were successfully examined. ASSD (median/range) of PET and MR contours was 0.6 (0.4-1.2) and 0.9 (0.5-1.3) mm, respectively. For T2-weighted MRI, a reduced SNR of -26.2% (-39.0--11.7) was observed with radiotherapy setup. No significant difference in mean ADC was found.

CONCLUSIONS

Simultaneous PET/MRI in HNC patients using radiotherapy positioning aids is clinically feasible. Though SNR was reduced, the image quality obtained with a radiotherapy setup meets RTP requirements and the data can thus be used for personalized RTP.

Optimizing the target detectability of cone beam CT performed in image-guided radiation therapy for patients of different body sizes

Purpose

The target detectability of cone beam computed tomography (CBCT) performed in image‐guided radiation therapy (IGRT) was investigated to achieve sufficient image quality for patient positioning over a course of treatment session while maintaining radiation exposure from CBCT imaging as low as reasonably achievable (ALARA).

Methods

Body CBCT scans operated in half‐fan mode were acquired with three different protocols: CBCT_lowD, CBCT_midD, and CBCT_highD, which resulted in weighted CT dose index (CTDI_w) of 0.36, 1.43, and 2.78 cGy, respectively. An electron density phantom that is 18 cm in diameter was covered by four layers of 2.5‐cm‐thick bolus to simulate patients of different body sizes. Multivariate analysis was used to examine the impact of body size, radiation exposure, and tissue type on the target detectability of CBCT imaging, quantified as contrast‐to‐noise ratio (CNR).

Results

CBCT_midD allows sufficient target detection of adipose, breast, muscle, liver in a background of water for normal‐weight adults with cross‐sectional diameter less than 28 cm, while CBCT_highD is suitable for adult patients with larger body sizes or body mass index over 25 kg/m². Once the cross‐sectional diameter of adult patients is larger than 35 cm, the CTDI_w of CBCT scans should be higher than 2.78 cGy to achieve required CNR. As for pediatric and adolescent patients with cross‐sectional diameter less than 25 cm, CBCT_lowD is able to produce images with sufficient target detection.

Conclusion

The target detectability of soft tissues in default CBCT scans may not be sufficient for overweight or obese adults. Contrary, pediatric and adolescent patients would receive unnecessarily high radiation exposure from default CBCT scans. Therefore, the selection of acquisition parameters for CBCT scans optimized according to patient body size was proposed to ensure sufficient image quality for daily patient positioning in radiation therapy while achieving the ALARA principle.

Variabilities of Magnetic Resonance Imaging-, Computed Tomography-, and Positron Emission Tomography-Computed Tomography-Based Tumor and Lymph Node Delineations for Lung Cancer Radiation Therapy Planning

PURPOSE

To investigate interobserver delineation variability for gross tumor volumes of primary lung tumors and associated pathologic lymph nodes using magnetic resonance imaging (MRI), and to compare the results with computed tomography (CT) alone- and positron emission tomography (PET)-CT-based delineations.

METHODS AND MATERIALS

Seven physicians delineated the tumor volumes of 10 patients for the following scenarios: (1) CT only, (2) PET-CT fusion images registered to CT ("clinical standard"), and (3) postcontrast T1-weighted MRI registered with diffusion-weighted MRI. To compute interobserver variability, the median surface was generated from all observers' contours and used as the reference surface. A physician labeled the interface types (tumor to lung, atelectasis (collapsed lung), hilum, mediastinum, or chest wall) on the median surface. Contoured volumes and bidirectional local distances between individual observers' contours and the reference contour were analyzed.

RESULTS

Computed tomography- and MRI-based tumor volumes normalized relative to PET-CT-based volumes were 1.62 ± 0.76 (mean ± standard deviation) and 1.38 ± 0.44, respectively. Volume differences between the imaging modalities were not significant. Between observers, the mean normalized volumes per patient averaged over all patients varied significantly by a factor of 1.6 (MRI) and 2.0 (CT and PET-CT) (P=4.10 × 10^-5 to 3.82 × 10^-9). The tumor-atelectasis interface had a significantly higher variability than other interfaces for all modalities combined (P=.0006). The interfaces with the smallest uncertainties were tumor-lung (on CT) and tumor-mediastinum (on PET-CT and MRI).

CONCLUSIONS

Although MRI-based contouring showed overall larger variability than PET-CT, contouring variability depended on the interface type and was not significantly different between modalities, despite the limited observer experience with MRI. Multimodality imaging and combining different imaging characteristics might be the best approach to define the tumor volume most accurately.

Validation of a Magnetic Resonance Imaging-based Auto-contouring Software Tool for Gross Tumour Delineation in Head and Neck Cancer Radiotherapy Planning

AIMS

To carry out statistical validation of a newly developed magnetic resonance imaging (MRI) auto-contouring software tool for gross tumour volume (GTV) delineation in head and neck tumours to assist in radiotherapy planning.

MATERIALS AND METHODS

Axial MRI baseline scans were obtained for 10 oropharyngeal and laryngeal cancer patients. GTV was present on 102 axial slices and auto-contoured using the modified fuzzy c-means clustering integrated with the level set method (FCLSM). Peer-reviewed (C-gold) manual contours were used as the reference standard to validate auto-contoured GTVs (C-auto) and mean manual contours (C-manual) from two expert clinicians (C1 and C2). Multiple geometric metrics, including the Dice similarity coefficient (DSC), were used for quantitative validation. A DSC≥0.7 was deemed acceptable. Inter- and intra-variabilities among the manual contours were also validated. The two-dimensional contours were then reconstructed in three dimensions for GTV volume calculation, comparison and three-dimensional visualisation.

RESULTS

The mean DSC between C-gold and C-auto was 0.79. The mean DSC between C-gold and C-manual was 0.79 and that between C1 and C2 was 0.80. The average time for GTV auto-contouring per patient was 8 min (range 6-13 min; mean 45 s per axial slice) compared with 15 min (range 6-23 min; mean 88 s per axial slice) for C1. The average volume concordance between C-gold and C-auto volumes was 86.51% compared with 74.16% between C-gold and C-manual. The average volume concordance between C1 and C2 volumes was 86.82%.

CONCLUSIONS

This newly designed MRI-based auto-contouring software tool shows initial acceptable results in GTV delineation of oropharyngeal and laryngeal tumours using FCLSM. This auto-contouring software tool may help reduce inter- and intra-variability and can assist clinical oncologists with time-consuming, complex radiotherapy planning.

Functional Imaging in Radiotherapy in the Netherlands: Availability and Impact on Clinical Practice

AIMS

Functional imaging with positron emission tomography/computed tomography (PET/CT) and multiparametric magnetic resonance (mpMR) is increasingly applied for radiotherapy purposes. However, evidence and experience are still limited, and this may lead to clinically relevant differences in accessibility, interpretation and decision making. We investigated the current patterns of care in functional imaging for radiotherapy in the Netherlands in a care evaluation study.

MATERIALS AND METHODS

The availability of functional imaging in radiotherapy centres in the Netherlands was evaluated; features available in >80% of academic and >80% of non-academic centres were considered standard of care. The impact of functional imaging on clinical decision making was evaluated using case questionnaires on lung, head/neck, breast and prostate cancer, with multiple-choice questions on primary tumour delineation, nodal involvement, distant metastasis and incidental findings. Radiation oncologists were allowed to discuss cases in a multidisciplinary approach. Ordinal answers were evaluated by median and interquartile range (IQR) to identify the extent and variability of clinical impact; additional patterns were evaluated descriptively.

RESULTS

Information was collected from 18 radiotherapy centres in the Netherlands (all except two). PET/CT was available for radiotherapy purposes to 94% of centres; 67% in the treatment position and 61% with integrated planning CT. mpMR was available to all centres; 61% in the treatment position. Technologists collaborated between departments to acquire PET/CT or mpMR for radiotherapy in 89%. All sites could carry out image registration for target definition. Functional imaging generally showed a high clinical impact (average median 4.3, scale 1-6) and good observer agreement (average IQR 1.1, scale 0-6). However, several issues resulted in ignoring functional imaging (e.g. positional discrepancies, central necrosis) or poor observer agreement (atelectasis, diagnostic discrepancies, conformation strategies).

CONCLUSIONS

Access to functional imaging with PET/CT and mpMR for radiotherapy purposes, with collaborating technologists and multimodal delineation, can be considered standard of care in the Netherlands. For several specific clinical situations, the interpretation of images may benefit from further standardisation.

PET image segmentation using a Gaussian mixture model and Markov random fields

Background

Classification algorithms for positron emission tomography (PET) images support computational treatment planning in radiotherapy. Common clinical practice is based on manual delineation and fixed or iterative threshold methods, the latter of which requires regression curves dependent on many parameters.

Methods

An improved statistical approach using a Gaussian mixture model (GMM) is proposed to obtain initial estimates of a target volume, followed by a correction step based on a Markov random field (MRF) and a Gibbs distribution to account for dependencies among neighboring voxels. In order to evaluate the proposed algorithm, phantom measurements of spherical and non-spherical objects with the smallest diameter being 8 mm were performed at signal-to-background ratios (SBRs) between 2.06 and 9.39. Additionally ⁶⁸Ga-PET data from patients with lesions in the liver and lymph nodes were evaluated.

Results

The proposed algorithm produces stable results for different reconstruction algorithms and different lesion shapes. Furthermore, it outperforms all threshold methods regarding detection rate, determines the spheres’ volumes more accurately than fixed threshold methods, and produces similar values as iterative thresholding. In a comparison with other statistical approaches, the algorithm performs equally well for larger volumes and even shows improvements for small volumes and SBRs. The comparison with experts’ manual delineations on the clinical data shows the same qualitative behavior as for the phantom measurements.

Conclusions

In conclusion, a generic probabilistic approach that does not require data measured beforehand is presented whose performance, robustness, and swiftness make it a feasible choice for PET segmentation.

Automatic segmentation of male pelvic anatomy on computed tomography images: a comparison with multiple observers in the context of a multicentre clinical trial

Background

This study investigates the variation in segmentation of several pelvic anatomical structures on computed tomography (CT) between multiple observers and a commercial automatic segmentation method, in the context of quality assurance and evaluation during a multicentre clinical trial.

Methods

CT scans of two prostate cancer patients (‘benchmarking cases’), one high risk (HR) and one intermediate risk (IR), were sent to multiple radiotherapy centres for segmentation of prostate, rectum and bladder structures according to the TROG 03.04 “RADAR” trial protocol definitions. The same structures were automatically segmented using iPlan software for the same two patients, allowing structures defined by automatic segmentation to be quantitatively compared with those defined by multiple observers. A sample of twenty trial patient datasets were also used to automatically generate anatomical structures for quantitative comparison with structures defined by individual observers for the same datasets.

Results

There was considerable agreement amongst all observers and automatic segmentation of the benchmarking cases for bladder (mean spatial variations < 0.4 cm across the majority of image slices). Although there was some variation in interpretation of the superior-inferior (cranio-caudal) extent of rectum, human-observer contours were typically within a mean 0.6 cm of automatically-defined contours. Prostate structures were more consistent for the HR case than the IR case with all human observers segmenting a prostate with considerably more volume (mean +113.3%) than that automatically segmented. Similar results were seen across the twenty sample datasets, with disagreement between iPlan and observers dominant at the prostatic apex and superior part of the rectum, which is consistent with observations made during quality assurance reviews during the trial.

Conclusions

This study has demonstrated quantitative analysis for comparison of multi-observer segmentation studies. For automatic segmentation algorithms based on image-registration as in iPlan, it is apparent that agreement between observer and automatic segmentation will be a function of patient-specific image characteristics, particularly for anatomy with poor contrast definition. For this reason, it is suggested that automatic registration based on transformation of a single reference dataset adds a significant systematic bias to the resulting volumes and their use in the context of a multicentre trial should be carefully considered.

Improving radiotherapy quality assurance in clinical trials: assessment of target volume delineation of the pre-accrual benchmark case

As the complexity of radiotherapy (RT) trials increases, issues surrounding target volume delineation will become more important. Some form of outlining assessment prior to trial entry is increasingly being mandated in UK RT trials. This document produced by the Outlining and Imaging Subgroup (OISG) of the National Cancer Research Institute will address methods to reduce interobserver variation in clinical trials and how to conduct an assessment of outlining through a pre-accrual benchmark case. We review currently available methods of describing the variation and identify areas where further work is needed. The OISG would encourage ongoing discussion with chief investigators in order to provide advice on individual aspects of benchmark case assessment for current and future trials.

Tools to analyse and display variations in anatomical delineation

Variations in anatomical delineation, principally due to a combination of inter-observer contributions and image-specificity, remain one of the most significant impediments to geometrically-accurate radiotherapy. Quantification of spatial variability of the delineated contours comprising a structure can be made with a variety of metrics, and the availability of software tools to apply such metrics to data collected during inter-observer or repeat-imaging studies would allow their validation. A suite of such tools have been developed which use an Extensible Markup Language format for the exchange of delineated 3D structures with radiotherapy planning or review systems. These tools provide basic operations for manipulating and operating on individual structures and related structure sets, and for deriving statistics on spatial variations of contours that can be mapped onto the surface of a reference structure. Use of these tools on a sample dataset is demonstrated together with import and display of results in the SWAN treatment plan review system.

PET based volume segmentation with emphasis on the iterative TrueX algorithm

PURPOSE

To assess the influence of reconstruction algorithms for positron emission tomography (PET) based volume quantification. The specifically detected activity in the threshold defined volume was investigated for different reconstruction algorithms as a function of volume size and signal to background ratio (SBR), especially for volumes smaller than 1ml. Special attention was given to the Siemens specific iterative reconstruction algorithm TrueX.

METHODS

Measurements were performed with a modified in-house produced IEC body phantom on a Siemens Biograph 64 True Point PET/CT scanner (Siemens, Medical Systems) for six different SBRs (2.1, 3.8, 4.9, 6.7, 8.9, 9.4 and without active background (BG)). The phantom consisted of a water-filled cavity with built-in plastic spheres (0.27, 0.52, 1.15, 2.57, 5.58 and 11.49ml). The following reconstruction algorithms available on the Siemens Syngo workstation were evaluated: Iterative OSEM (OSEM) (4 iterations, 21 subsets), iterative TrueX (TrueX) (4 iterations, 21 subsets) and filtered backprojection (FBP). For the threshold based volume segmentation the software Rover (ABX, Dresden) was used.

RESULTS

For spheres larger than 2.5ml a constant threshold (standard deviation (SD) 10%) level was found for a given SBR and reconstruction algorithm and therefore a mean threshold for the largest three spheres was calculated. This threshold could be approximated by a function inversely proportional to the SBR. The threshold decreased with increasing SBR for all sphere sizes. For the OSEM algorithm the threshold for small spheres with 0.27, 0.52 and 1.15ml varied between 17% and 44% (depending on sphere size). The threshold for the TrueX algorithm was substantially lower (up to 17%) than for the OSEM algorithm for all sphere sizes. The maximum activity in a specific volume yielded the true activity for the OSEM algorithm when using a SBR independent correction factor C, which depended on sphere size. For the largest three volumes a constant factor C=1.10±0.03 was found. For smaller volumes, C increased exponentially due to the partial volume effect. For the TrueX algorithm the maximum activity overestimated the true activity.

CONCLUSION

The threshold values for PET based target volume segmentation increased with increasing sphere size for all tested algorithms. True activity values of spheres in the phantom could be extracted using experimentally determined correction factors C. The TrueX algorithm has to be used carefully for quantitative comparison (e.g. follow-up) and multicenter studies.

Improving target delineation on 4-dimensional CT scans in stage I NSCLC using a deformable registration tool

INTRODUCTION

Correct target definition is crucial in stereotactic radiotherapy for lung tumors. We evaluated use of deformable registration (DR) for target contouring on 4-dimensional (4D) CT scans.

MATERIALS AND METHODS

Three clinicians contoured gross tumor volume (GTV) in an end-inspiration phase of 4DCT of 6 patients on two occasions. Two clinicians contoured GTVs in all phases of 4DCT and on maximum intensity projections (MIP). The initial GTV was auto-propagated to 9 other phases using a B-spline algorithm (VelocityAI). Internal target volumes (ITVs) generated were (i) ITV(10manual) encompassing all physician-contoured GTVs, (ii) ITV-MIP(optimized) from MIP after review of individual 4DCT phases, (iii) ITV(10deformed) encompassing auto-propagated GTVs using DR, and (iv) ITV(10deformed-optimized), from an ITV(10deformed) target that was modified to form a 'clinically optimal' ITV. Volume-overlaps were scored using Dice's Similarity Coefficients (DSCs).

RESULTS

Intra-clinician GTV reproducibility was greater than inter-clinician reproducibility (mean DSC 0.93 vs. 0.88, p<0.0004). In five of 6 patients, ITV-MIP(optimized) differed from the ITV(10deformed-optimized). In all patients, the DSC between ITV(10deformed-optimized) and ITV(10deformed) was higher than that between ITV(10deformed-optimized) and ITV-MIP(optimized) (p<0.02 T-test).

CONCLUSION

ITVs created in stage I tumors using DR were closer to 'clinically optimal' ITVs than was the case with a MIP-modified approach.

Computer input devices: neutral party or source of significant error in manual lesion segmentation?

Lesion segmentation involves outlining the contour of an abnormality on an image to distinguish boundaries between normal and abnormal tissue and is essential to track malignant and benign disease in medical imaging for clinical, research, and treatment purposes. A laser optical mouse and a graphics tablet were used by radiologists to segment 12 simulated reference lesions per subject in two groups (one group comprised three lesion morphologies in two sizes, one for each input device for each device two sets of six, composed of three morphologies in two sizes each). Time for segmentation was recorded. Subjects completed an opinion survey following segmentation. Error in contour segmentation was calculated using root mean square error. Error in area of segmentation was calculated compared to the reference lesion. 11 radiologists segmented a total of 132 simulated lesions. Overall error in contour segmentation was less with the graphics tablet than with the mouse (P < 0.0001). Error in area of segmentation was not significantly different between the tablet and the mouse (P = 0.62). Time for segmentation was less with the tablet than the mouse (P = 0.011). All subjects preferred the graphics tablet for future segmentation (P = 0.011) and felt subjectively that the tablet was faster, easier, and more accurate (P = 0.0005). For purposes in which accuracy in contour of lesion segmentation is of the greater importance, the graphics tablet is superior to the mouse in accuracy with a small speed benefit. For purposes in which accuracy of area of lesion segmentation is of greater importance, the graphics tablet and mouse are equally accurate.

Anatomical imaging for radiotherapy

The goal of radiation therapy is to achieve maximal therapeutic benefit expressed in terms of a high probability of local control of disease with minimal side effects. Physically this often equates to the delivery of a high dose of radiation to the tumour or target region whilst maintaining an acceptably low dose to other tissues, particularly those adjacent to the target. Techniques such as intensity modulated radiotherapy (IMRT), stereotactic radiosurgery and computer planned brachytherapy provide the means to calculate the radiation dose delivery to achieve the desired dose distribution. Imaging is an essential tool in all state of the art planning and delivery techniques: (i) to enable planning of the desired treatment, (ii) to verify the treatment is delivered as planned and (iii) to follow-up treatment outcome to monitor that the treatment has had the desired effect. Clinical imaging techniques can be loosely classified into anatomic methods which measure the basic physical characteristics of tissue such as their density and biological imaging techniques which measure functional characteristics such as metabolism. In this review we consider anatomical imaging techniques. Biological imaging is considered in another article. Anatomical imaging is generally used for goals (i) and (ii) above. Computed tomography (CT) has been the mainstay of anatomical treatment planning for many years, enabling some delineation of soft tissue as well as radiation attenuation estimation for dose prediction. Magnetic resonance imaging is fast becoming widespread alongside CT, enabling superior soft-tissue visualization. Traditionally scanning for treatment planning has relied on the use of a single snapshot scan. Recent years have seen the development of techniques such as 4D CT and adaptive radiotherapy (ART). In 4D CT raw data are encoded with phase information and reconstructed to yield a set of scans detailing motion through the breathing, or cardiac, cycle. In ART a set of scans is taken on different days. Both allow planning to account for variability intrinsic to the patient. Treatment verification has been carried out using a variety of technologies including: MV portal imaging, kV portal/fluoroscopy, MVCT, conebeam kVCT, ultrasound and optical surface imaging. The various methods have their pros and cons. The four x-ray methods involve an extra radiation dose to normal tissue. The portal methods may not generally be used to visualize soft tissue, consequently they are often used in conjunction with implanted fiducial markers. The two CT-based methods allow measurement of inter-fraction variation only. Ultrasound allows soft-tissue measurement with zero dose but requires skilled interpretation, and there is evidence of systematic differences between ultrasound and other data sources, perhaps due to the effects of the probe pressure. Optical imaging also involves zero dose but requires good correlation between the target and the external measurement and thus is often used in conjunction with an x-ray method. The use of anatomical imaging in radiotherapy allows treatment uncertainties to be determined. These include errors between the mean position at treatment and that at planning (the systematic error) and the day-to-day variation in treatment set-up (the random error). Positional variations may also be categorized in terms of inter- and intra-fraction errors. Various empirical treatment margin formulae and intervention approaches exist to determine the optimum strategies for treatment in the presence of these known errors. Other methods exist to try to minimize error margins drastically including the currently available breath-hold techniques and the tracking methods which are largely in development. This paper will review anatomical imaging techniques in radiotherapy and how they are used to boost the therapeutic benefit of the treatment.

Quantifying Appropriate PTV Setup Margins: Analysis of Patient Setup Fidelity and Intrafraction Motion Using Post-Treatment Megavoltage Computed Tomography Scans

PURPOSE

To present a technique that can be implemented in-house to evaluate the efficacy of immobilization and image-guided setup of patients with different treatment sites on helical tomotherapy. This technique uses an analysis of alignment shifts between kilovoltage computed tomography and post-treatment megavoltage computed tomography images. The determination of the shifts calculated by the helical tomotherapy software for a given site can then be used to define appropriate planning target volume internal margins.

METHODS AND MATERIALS

Twelve patients underwent post-treatment megavoltage computed tomography scans on a helical tomotherapy machine to assess patient setup fidelity and net intrafraction motion. Shifts were studied for the prostate, head and neck, and glioblastoma multiforme. Analysis of these data was performed using automatic and manual registration of the kilovoltage computed tomography and post-megavoltage computed tomography images.

RESULTS

The shifts were largest for the prostate, followed by the head and neck, with glioblastoma multiforme having the smallest shifts in general. It appears that it might be more appropriate to use asymmetric planning target volume margins. Each margin value reported is equal to two standard deviations of the average shift in the given direction.

CONCLUSION

This method could be applied using individual patient post-image scanning and combined with adaptive planning to reduce or increase the margins as appropriate.

What's new in target volume definition for radiologists in ICRU Report 71? How can the ICRU volume definitions be integrated in clinical practice?

The optimal definition of the size, shape and location of gross tumour volume is one of the most important steps in the planning of radiation therapy, and necessitates a proper understanding of the procedure from both the oncologic radiologist and the radiation oncologist. This overview reports on the different terms and concepts that have been recommended in the ICRU Reports for this purpose; the latest Report 71 focuses on both previously given recommendations, and especially on electron beam therapy. This paper also highlights some of the problems that are encountered in the use of the International Commission on Radiation Units and Measurements (ICRU) recommendations in clinical practice, and at the interface between the radiation oncologist and the diagnostic oncologist.

A method to calculate coverage probability from uncertainties in radiotherapy via a statistical shape model

In this paper we describe a technique that may be used to model the geometric uncertainties that accrue during the radiotherapy process. Using data from in-treatment cone beam CT scans, we simultaneously analyse non-uniform observer delineation variability and organ motion together with patient set-up errors via the creation of a point distribution model (PDM). We introduce a novel method of generating a coverage probability matrix, that may be used to determine treatment margins and calculate uncertainties in dose, from this statistical shape model. The technique does not assume rigid body motion and can extrapolate shape variability in a statistically meaningful manner. In order to construct the PDM, we generate corresponding surface points over a set of delineations. Correspondences are established at a set of points in parameter space on spherically parameterized and canonical aligned outlines. The method is demonstrated using rectal delineations from serially acquired in-treatment cone beam CT image volumes of a prostate patient (44 image volumes total), each delineated by a minimum of two observers (maximum six). Two PDMs are constructed, one with set-up errors included and one without. We test the normality assumptions of the PDMs and find the distributions to be Gaussian in nature. The rectal PDM variability is in general agreement with data in the literature. The two resultant coverage probability matrices show differences as expected.

Assessing the Difference between Planned and Delivered Intensity-modulated Radiotherapy Dose Distributions based on Radiobiological Measures

AIMS

Because of the highly conformal distributions that can be obtained with intensity-modulated radiotherapy (IMRT), any discrepancy between the intended and delivered distributions would probably affect the clinical outcome. Consequently, there is a need for a measure that would quantify those differences in terms of a change in the expected clinical outcome.

MATERIALS AND METHODS

To evaluate such a measure, cancer of the cervix was used, where the bladder and rectum are proximal and partially overlapping with the internal target volume. A solid phantom simulating the pelvic anatomy was fabricated and a treatment plan was developed to deliver the prescribed dose to the phantom. The phantom was then irradiated with films positioned in several transverse planes. The racetrack microtron at 50 MV was used in the treatment planning and delivery processes. The dose distribution delivered was analysed based on the film measurements and compared against the treatment plan. The differences in the measurements were evaluated using both physical and biological criteria. Whereas the physical comparison of dose distributions can assess the geometric accuracy of delivery, it does not reflect the clinical effect of any measured dose discrepancies.

RESULTS

It is shown how small inaccuracies in delivered dose can affect the treatment outcome in terms of complication-free tumour cure.

CONCLUSIONS

With highly conformal IMRT, the accuracy of the patient set-up and treatment delivery are critical for the success of the treatment. A method is proposed to evaluate the precision of the delivered plan based on changes in complication and control rates as they relate to uncertainties in dose delivery.