The distance discordance metric-a novel approach to quantifying spatial uncertainties in intra- and inter-patient deformable image registration

Baseline shift corrections towards the heart: External validation of the impact on survival in early-stage NSCLC patients

PURPOSE

To externally validate Johnson-Hart et al. findings: the association of tumor baseline shifts towards the heart with overall survival (OS) in SBRT for NSCLC. Further analysis included investigating the presence of interfractional heart baseline shifts and the association of OS with heart dose change during treatment.

METHODS

Data from 416 SBRT early-stage NSCLC patients was collected. Pearson's correlations (PCCs) between clinical variables and treatment-averaged tumor shifts towards/away from the heart were explored. Validation of published multivariable Cox model was performed. PCCs between heart and tumor baseline shifts were analyzed. Dose accumulation was performed following daily CBCT-to-pCT deformable registration. Maximum heart dose (D0) was computed for planned and accumulated doses. Differences in OS according to shifts towards/away from the heart or D0 increase/decrease were analyzed. Significant D0 differences between patients with D0 increase/decrease and different tumor locations were explored.

RESULTS

Tumor shifts towards/away from the heart showed no significant association with OS (p = 0.91). Distance between PTV and heart correlated significantly (PCC = 0.18) with shifts to the heart. Cox model did not validate in our cohort. Heart presented baseline shifts positively correlated with tumor baseline shifts in all three directions (PCC ≥ 0.38; p < 0.001). Counterintuitively, patients experiencing increased D0 during treatment showed significantly better OS (p = 0.0077). Upper-lobe tumor patients with increased D0 had lower D0 than those with decreased D0 (right-upper-lobe p ≤ 0.018).

CONCLUSIONS

In our SBRT cohort, the shifts towards the heart were not associated with worse OS. Moderate correlations were found between tumor and heart baseline shifts in each direction. Moreover, the distance between the PTV and the heart showed a significant correlation with shifts to the heart.

Review and recommendations on deformable image registration uncertainties for radiotherapy applications

Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.

Feasibility of delivered dose reconstruction for MR-guided SBRT of pancreatic tumors with fast, real-time 3D cine MRI

BACKGROUND AND PURPOSE

In MR-guided SBRT of pancreatic cancer, intrafraction motion is typically monitored with (interleaved) 2D cine MRI. However, tumor surroundings are often not fully captured in these images, and motion might be distorted by through-plane movement. In this study, the feasibility of highly accelerated 3D cine MRI to reconstruct the delivered dose during MR-guided SBRT was assessed.

MATERIALS AND METHODS

A 3D cine MRI sequence was developed for fast, time-resolved 4D imaging, featuring a low spatial resolution that allows for rapid volumetric imaging at 430 ms. The 3D cines were acquired during the entire beam-on time of 23 fractions of online adaptive MR-guided SBRT for pancreatic tumors on a 1.5 T MR-Linac. A 3D deformation vector field (DVF) was extracted for every cine dynamic using deformable image registration. Next, these DVFs were used to warp the partial dose delivered in the time interval between consecutive cine acquisitions. The warped dose plans were summed to obtain a total delivered dose. The delivered dose was also calculated under various motion correction strategies. Key DVH parameters of the GTV, duodenum, small bowel and stomach were extracted from the delivered dose and compared to the planned dose. The uncertainty of the calculated DVFs was determined with the inverse consistency error (ICE) in the high-dose regions.

RESULTS

The mean (SD) relative (ratio delivered/planned) D_99% of the GTV was 0.94 (0.06), and the mean (SD) relative D_0.5cc of the duodenum, small bowel, and stomach were respectively 0.98 (0.04), 1.00 (0.07), and 0.98 (0.06). In the fractions with the lowest delivered tumor coverage, it was found that significant lateral drifts had occurred. The DVFs used for dose warping had a low uncertainty with a mean (SD) ICE of 0.65 (0.07) mm.

CONCLUSION

We employed a fast, real-time 3D cine MRI sequence for dose reconstruction in the upper abdomen, and demonstrated that accurate DVFs, acquired directly from these images, can be used for dose warping. The reconstructed delivered dose showed only a modest degradation of tumor coverage, mostly attainable to baseline drifts. This emphasizes the need for motion monitoring and development of intrafraction treatment adaptation solutions, such as baseline drift corrections.

Dose accumulation for MR-guided adaptive radiotherapy: From practical considerations to state-of-the-art clinical implementation

MRI-linear accelerator (MR-linac) devices have been introduced into clinical practice in recent years and have enabled MR-guided adaptive radiation therapy (MRgART). However, by accounting for anatomical changes throughout radiation therapy (RT) and delivering different treatment plans at each fraction, adaptive radiation therapy (ART) highlights several challenges in terms of calculating the total delivered dose. Dose accumulation strategies-which typically involve deformable image registration between planning images, deformable dose mapping, and voxel-wise dose summation-can be employed for ART to estimate the delivered dose. In MRgART, plan adaptation on MRI instead of CT necessitates additional considerations in the dose accumulation process because MRI pixel values do not contain the quantitative information used for dose calculation. In this review, we discuss considerations for dose accumulation specific to MRgART and in relation to current MR-linac clinical workflows. We present a general dose accumulation framework for MRgART and discuss relevant quality assurance criteria. Finally, we highlight the clinical importance of dose accumulation in the ART era as well as the possible ways in which dose accumulation can transform clinical practice and improve our ability to deliver personalized RT.

An Open-Source Package for Thermal and Multispectral Image Analysis for Plants in Glasshouse

Advanced plant phenotyping techniques to measure biophysical traits of crops are helping to deliver improved crop varieties faster. Phenotyping of plants using different sensors for image acquisition and its analysis with novel computational algorithms are increasingly being adapted to measure plant traits. Thermal and multispectral imagery provides novel opportunities to reliably phenotype crop genotypes tested for biotic and abiotic stresses under glasshouse conditions. However, optimization for image acquisition, pre-processing, and analysis is required to correct for optical distortion, image co-registration, radiometric rescaling, and illumination correction. This study provides a computational pipeline that optimizes these issues and synchronizes image acquisition from thermal and multispectral sensors. The image processing pipeline provides a processed stacked image comprising RGB, green, red, NIR, red edge, and thermal, containing only the pixels present in the object of interest, e.g., plant canopy. These multimodal outputs in thermal and multispectral imageries of the plants can be compared and analysed mutually to provide complementary insights and develop vegetative indices effectively. This study offers digital platform and analytics to monitor early symptoms of biotic and abiotic stresses and to screen a large number of genotypes for improved growth and productivity. The pipeline is packaged as open source and is hosted online so that it can be utilized by researchers working with similar sensors for crop phenotyping.

Detailed dosimetric evaluation of inter-fraction and respiratory motion in lung stereotactic body radiation therapy based on daily 4D cone beam CT images

Objective. Periodic respiratory motion and inter-fraction variations are sources of geometric uncertainty in stereotactic body radiation therapy (SBRT) of pulmonary lesions. This study extensively evaluates and validates the separate and combined dosimetric effect of both factors using 4D-CT and daily 4D-cone beam CT (CBCT) dose accumulation scenarios.Approach. A first cohort of twenty early stage or metastatic disease lung cancer patients were retrospectively selected to evaluate each scenario. The planned-dose (3D_Ref) was optimized on a 3D mid-position CT. To estimate the dosimetric impact of respiratory motion (4D_Ref), inter-fractional variations (3D_Acc) and the combined effect of both factors (4D_Acc), three dose accumulation scenarios based on 4D-CT, daily mid-cone beam CT (CBCT) position and 4D-CBCT were implemented via CT-CT/CT-CBCT deformable image registration (DIR) techniques. Each scenario was compared to 3D_Ref.A separate cohort of ten lung SBRT patients was selected to validate DIR techniques. The distance discordance metric (DDM) was implemented per voxel and per patient for tumor and organs at risk (OARs), and the dosimetric impact for CT-CBCT DIR geometric errors was calculated.Main results.Median and interquartile range (IQR) of the dose difference per voxel were 0.05/2.69 Gy and -0.12/2.68 Gy for3DAcc-3DRefand4DAcc-3DRef.For4DRef-3DRefthe IQR was considerably smaller -0.15/0.78 Gy. These findings were confirmed by dose volume histogram parameters calculated in tumor and OARs. For CT-CT/CT-CBCT DIR validation, DDM (95th percentile) was highest for heart (6.26 mm)/spinal cord (8.00 mm), and below 3 mm for tumor and the rest of OARs. The dosimetric impact of CT-CBCT DIR errors was below 2 Gy for tumor and OARs.Significance. The dosimetric impact of inter-fraction variations were shown to dominate those of periodic respiration in SBRT for pulmonary lesions. Therefore, treatment evaluation and dose-effect studies would benefit more from dose accumulation focusing on day-to-day changes then those that focus on respiratory motion.

Estimating medical image registration error and confidence: A taxonomy and scoping review

Given that image registration is a fundamental and ubiquitous task in both clinical and research domains of the medical field, errors in registration can have serious consequences. Since such errors can mislead clinicians during image-guided therapies or bias the results of a downstream analysis, methods to estimate registration error are becoming more popular. To give structure to this new heterogenous field we developed a taxonomy and performed a scoping review of methods that quantitatively and automatically provide a dense estimation of registration error. The taxonomy breaks down error estimation methods into Approach (Image- or Transformation-based), Framework (Machine Learning or Direct) and Measurement (error or confidence) components. Following the PRISMA guidelines for scoping reviews, the 570 records found were reduced to twenty studies that met inclusion criteria, which were then reviewed according to the proposed taxonomy. Trends in the field, advantages and disadvantages of the methods, and potential sources of bias are also discussed. We provide suggestions for best practices and identify areas of future research.

MIRSIG position paper: the use of image registration and fusion algorithms in radiotherapy

The report of the American Association of Physicists in Medicine (AAPM) Task Group No. 132 published in 2017 reviewed rigid image registration and deformable image registration (DIR) approaches and solutions to provide recommendations for quality assurance and quality control of clinical image registration and fusion techniques in radiotherapy. However, that report did not include the use of DIR for advanced applications such as dose warping or warping of other matrices of interest. Considering that DIR warping tools are now readily available, discussions were hosted by the Medical Image Registration Special Interest Group (MIRSIG) of the Australasian College of Physical Scientists & Engineers in Medicine in 2018 to form a consensus on best practice guidelines. This position statement authored by MIRSIG endorses the recommendations of the report of AAPM task group 132 and expands on the best practice advice from the 'Deforming to Best Practice' MIRSIG publication to provide guidelines on the use of DIR for advanced applications.

Towards mid-position based Stereotactic Body Radiation Therapy on the MR-linac for central lung tumours

Background and purpose: Central lung tumours can be treated by magnetic resonance (MR)-guided radiotherapy. Complications might be reduced by decreasing the Planning Target Volume (PTV) using mid-position (midP)-based planning instead of Internal Target Volume (ITV)-based planning. In this study, we aimed to verify a method to automatically derive patient-specific PTV margins for midP-based planning, and show dosimetric robustness of midP-based planning for a 1.5T MR-linac.

Materials and methods: Central(n = 12) and peripheral(n = 4) central lung tumour cases who received 8x7.5 Gy were included. A midP-image was reconstructed from ten phases of the 4D-Computed Tomography using deformable image registration. The Gross Tumor Volume (GTV) was delineated on the midP-image and the PTV margin was automatically calculated based on van Herk’s margin recipe, treating the standard deviation of all Deformation Vector Fields, within the GTV, as random error component. Dosimetric robustness of midP-based planning for MR-linac using automatically derived margins was verified by 4D dose-accumulation. MidP-based plans were compared to ITV-based plans. Automatically derived margins were verified with manually derived margins.

Results: The mean D95% target coverage in GTV + 2 mm was 59.9 Gy and 62.0 Gy for midP- and ITV-based central lung plans, respectively. The mean lung dose was significantly lower for midP-based treatment plans (difference:-0.3 Gy; p<0.042). Automatically derived margins agreed within one millimeter with manually derived margins.

Conclusions: This retrospective study indicates that mid-position-based treatment plans for central lung Stereotactic Body Radiation Therapy yield lower OAR doses compared to ITV-based treatment plans on the MR-linac. Patient-specific GTV-to-PTV margins can be derived automatically and result in clinically acceptable target coverage.

Delivered dose-effect analysis of radiation induced rib fractures after thoracic SBRT

BACKGROUND AND PURPOSE

Anatomical changes during the stereotactic body radiation therapy (SBRT) of early stage non-small cell lung cancer (NSCLC) may cause the delivered dose to deviate from the planned dose. We investigate if normal tissue complication probability (NTCP) models based on the delivered dose predict radiation-induced rib fractures better than models based on the planned dose.

MATERIAL AND METHODS

437 NSCLC patients treated to a median dose of 3x18 Gy were included. Delivered dose was estimated by accumulating EQD2-corrected fraction doses after being deformed with daily CBCT-to-planning CT deformable image registration. Dosimetric parameters D_x (dose to a relative volume x) were extracted for each rib included in the CBCTs field-of-view. An NTCP model was constructed for both planned and delivered dose, optimizing the parameters TD₅₀ (dose with 50% toxicity risk), m (steepness of the curve) and x, using maximum likelihood estimation. Best NTCP model was determined using Akaike weights (Aw). Differences between the models were tested for significance using the Vuong's test.

RESULTS

Median time to fracture of 110 fractured ribs was 22.5 months. The maximum rib dose, D₀, best predicted fractures for both planned and delivered dose. The average delivered D₀ was significantly lower than planned (p < 0.001). NTCP model based on the delivered D₀ was the best, with Aw = 0.95. The models were not significantly different.

CONCLUSION

Delivered maximum dose to the ribs was significantly lower than planned. The NTCP model based on delivered dose improved predictions of radiation-induced rib fractures but did not reach statistical significance.

An approach for estimating dosimetric uncertainties in deformable dose accumulation in pencil beam scanning proton therapy for lung cancer

Deformable image registration (DIR) is an important component for dose accumulation and associated clinical outcome evaluation in radiotherapy. However, the resulting deformation vector field (DVF) is subject to unavoidable discrepancies when different algorithms are applied, leading to dosimetric uncertainties of the accumulated dose. We propose here an approach for proton therapy to estimate dosimetric uncertainties as a consequence of modeled or estimated DVF uncertainties. A patient-specific DVF uncertainty model was built on the first treatment fraction, by correlating the magnitude differences of five DIR results at each voxel to the magnitude of any single reference DIR. In the following fractions, only the reference DIR needs to be applied, and DVF geometric uncertainties were estimated by this model. The associated dosimetric uncertainties were then derived by considering the estimated geometric DVF uncertainty, the dose gradient of fractional recalculated dose distribution and the direction factor from the applied reference DIR of this fraction. This estimated dose uncertainty was respectively compared to the reference dose uncertainty when different DIRs were applied individually for each dose warping. This approach was validated on seven NSCLC patients, each with nine repeated CTs. The proposed model-based method is able to achieve dose uncertainty distribution on a conservative voxel-to-voxel comparison within ±5% of the prescribed dose to the 'reference' dosimetric uncertainty, for 77% of the voxels in the body and 66%-98% of voxels in investigated structures. We propose a method to estimate DIR induced uncertainties in dose accumulation for proton therapy of lung tumor treatments.

Simultaneous multi-slice accelerated 4D-MRI for radiotherapy guidance

4D-MRI is becoming increasingly important for daily guidance of thoracic and abdominal radiotherapy. This study exploits the simultaneous multi-slice (SMS) technique to accelerate the acquisition of a balanced turbo field echo (bTFE) and a turbo spin echo (TSE) coronal 4D-MRI sequence performed on 1.5 T MRI scanners. SMS single-shot bTFE and TSE sequences were developed to acquire a stack of 52 coronal 2D images over 30 dynamics. Simultaneously excited slices were separated by half the field of view. Slices intersecting with the liver-lung interface were used as navigator slices. For each navigator slice location, an end-exhale dynamic was automatically identified, and used to derive the self-sorting signal by rigidly registering the remaining dynamics. Navigator slices were sorted into 10 amplitude bins, and the temporal relationship of simultaneously excited slices was used to generate sorted 4D-MRIs for 12 healthy volunteers. The self-sorting signal was validated using anin vivopeak-to-peak motion analysis. The smoothness of the liver-lung interface was quantified by comparing to sagittal cine images acquired directly after the SMS-4D-MRI sequence. To ensure compatibility with the MR-linac radiotherapy workflow, the 4D-MRIs were transformed into 3D mid-position (MidP) images using deformable image registration. Consistency of the deformable vector fields was quantified in terms of the distance discordance metric (DDM) in the body. The SMS-4D-TSE sequence was additionally acquired for 3 lung cancer patients to investigate tumor visibility. SMS-4D-MRI acquisition and processing took approximately 7 min. 4D-MRI reconstruction was possible for 26 out of 27 acquired datasets. Missing data in the sorted 4D-MRIs varied from 4%-26% for the volunteers and varied from 8%-24% for the patients. Peak-to-peak (SD) amplitudes analysis agreed within 1.8 (1.1) mm and 0.9 (0.4) mm between the sorted 4D-MRIs and the self-sorting signals of the volunteers and patients, respectively. Liver-lung interface smoothness was found to be in the range of 0.6-3.1 mm for volunteers. The percentage of DDM values smaller than 2 mm was in the range of 85%-89% and 86%-92% for the volunteers and patients, respectively. Lung tumors were clearly visibility in the SMS-4D-TSE images and MidP images. Two fast SMS-accelerated 4D-MRI sequences were developed resulting in T₂/T₁or T₂weighted contrast. The SMS-4D-MRIs and derived 3D MidP-MRIs yielded anatomically plausible images and good tumor visibility. SMS-4D-MRI is therefore a strong candidate to be used for treatment simulation and daily guidance of thoracic and abdominal MR-guided radiotherapy.

A 3D cine-MRI acquisition technique and image analysis framework to quantify bowel motion demonstrated in gynecological cancer patients

PURPOSE

Magnetic resonance imaging (MRI) is increasingly used in radiation oncology for target delineation and radiotherapy treatment planning, for example, in patients with gynecological cancers. As a consequence of pelvic radiotherapy, a part of the bowel is irradiated, yielding risk of bowel toxicity. Existing dose-effect models predicting bowel toxicity are inconclusive and bowel motion might be an important confounding factor. The exact motion of the bowel and dosimetric effects of its motion are yet uncharted territories in radiotherapy. In diagnostic radiology methods on the acquisition of dynamic MRI sequences were developed for bowel motility visualization and quantification. Our study aim was to develop an imaging technique based on three-dimensional (3D) cine-MRI to visualize and quantify bowel motion and demonstrate it in a cohort of gynecological cancer patients.

METHODS

We developed an MRI acquisition suitable for 3D bowel motion quantification, namely a balanced turbo field echo sequence (TE = 1.39 ms, TR = 2.8 ms), acquiring images in 3.7 s (dynamic) with a 1.25 × 1.25 × 2.5 mm³ resolution, yielding a field of view of 200 × 200 × 125 mm³ . These MRI bowel motion sequences were acquired in 22 gynecological patients. During a 10-min scan, 160 dynamics were acquired. Subsequent dynamics were deformably registered using a B-spline transformation model, resulting in 159 3D deformation vector fields (DVFs) per MRI set. From the 159 DVFs, the average vector length was calculated per voxel to generate bowel motion maps. Quality assurance was performed on all 159 DVFs per MRI, using the Jacobian Determinant and the Harmonic Energy as deformable image registration error metrics. In order to quantify bowel motion, we introduced the concept of cumulative motion-volume histogram (MVH) of the bowel bag volume. Finally, interpatient variation of bowel motion was analyzed using the MVH parameters M10%, M50%, and M90%. The M10%/M50%/M90% represents the minimum bowel motion per frame of 10%/50%/90% of the bowel bag volume.

RESULTS

The motion maps resulted in a visualization of areas with small and large movements within the bowel bag. After applying quality assurance, the M10%, M50%, and M90% were 4.4 (range 2.2-7.6) mm, 2.2 (range 0.9-4.1) mm, and 0.5 (range 0.2-1.4) mm per frame, on average over all patients, respectively.

CONCLUSION

We have developed a method to visualize and quantify 3D bowel motion with the use of bowel motion specific MRI sequences in 22 gynecological cancer patients. This 3D cine-MRI-based quantification tool and the concept of MVHs can be used in further studies to determine the effect of radiotherapy on bowel motion and to find the relation with dose effects to the small bowel. In addition, the developed technique can be a very interesting application for bowel motility assessment in diagnostic radiology.

A multivariable study of deformable image registration evaluation metrics in 4DCT of thoracic cancer patients

Deformable image registration (DIR) accuracy is often validated using manually identified landmarks or known deformations generated using digital or physical phantoms. In daily practice, the application of these approaches is limited since they are time-consuming or require additional equipment. An alternative is the use of metrics automatically derived from the registrations, but their interpretation is not straightforward. In this work we aim to determine the suitability of DIR-derived metrics to validate the accuracy of 4 commonly used DIR algorithms. First, we investigated the DIR accuracy using a landmark-based metric (target registration error (TRE)) and a digital phantom-based metric (known deformation recovery error (KDE)). 4DCT scans of 16 thoracic cancer patients along with corresponding pairwise anatomical landmarks (AL) locations were collected from two public databases. Digital phantoms with known deformations were generated by each DIR algorithm to test all other algorithms and compute KDE. TRE and KDE were evaluated at AL. KDE was additionally quantified in coordinates randomly sampled (RS) inside the lungs. Second, we investigated the associations of 5 DIR-derived metrics (distance discordance metric (DDM), inverse consistency error (ICE), transitivity (TE), spatial (SS) and temporal smoothness (TS)) with DIR accuracy through uni- and multivariable linear regression models. TRE values were found higher compared to KDE values and these varied depending on the phantom used. The algorithm with the best accuracy achieved average values of TRE = 1.1 mm and KDE ranging from 0.3 to 0.8 mm. DDM was the best predictor of DIR accuracy, with moderate correlations (R ² < 0.61). Poor correlations were obtained at AL for algorithms with better accuracy, which improved when evaluated at RS. Only slight correlation improvement was obtained with a multivariable analysis (R ² < 0.64). DDM can be a useful metric to identify inaccuracies for different DIR algorithms without employing landmarks or digital phantoms.

An uncertainty metric to evaluate deformation vector fields for dose accumulation in radiotherapy

Background and purpose

In adaptive radiotherapy, deformable image registration (DIR) is used to propagate delineations of tumors and organs into a new therapy plan and to calculate the accumulated total dose. Many DIR accuracy metrics have been proposed. An alternative proposed here could be a local uncertainty (LU) metric for DIR results.

Materials and methods

The LU represented the uncertainty of each DIR position and was focused on deformation evaluation in uniformly-dense regions. Four cases demonstrated LU calculations: two head and neck cancer cases, a lung cancer case, and a prostate cancer case. Each underwent two CT examinations for radiotherapy planning.

Results

LU maps were calculated from each DIR of the clinical cases. Reduced fat regions had LUs of 4.6 ± 0.9 mm, 4.8 ± 1.0 mm, and 4.5 ± 0.7 mm, while the shrunken left parotid gland had a LU of 4.1 ± 0.8 mm and the shrunken lung tumor had a LU of 3.7 ± 0.7 mm. The bowels in the pelvic region had a LU of 10.2 ± 3.7 mm. LU histograms for the cases were similar and 99% of the voxels had a LU < 3 mm.

Conclusions

LU is a new uncertainty metric for DIR that was demonstrated for clinical cases. It had a tolerance of <3 mm.

A multiple-image-based method to evaluate the performance of deformable image registration in the pelvis

Deformable image registration (DIR) is essential for adaptive radiotherapy (RT) for tumor sites subject to motion, changes in tumor volume, as well as changes in patient normal anatomy due to weight loss. Several methods have been published to evaluate DIR-related uncertainties but they are not widely adopted. The aim of this study was, therefore, to evaluate intra-patient DIR for two highly deformable organs-the bladder and the rectum-in prostate cancer RT using a quantitative metric based on multiple image registration, the distance discordance metric (DDM). Voxel-by-voxel DIR uncertainties of the bladder and rectum were evaluated using DDM on weekly CT scans of 38 subjects previously treated with RT for prostate cancer (six scans/subject). The DDM was obtained from group-wise B-spline registration of each patient's collection of repeat CT scans. For each structure, registration uncertainties were derived from DDM-related metrics. In addition, five other quantitative measures, including inverse consistency error (ICE), transitivity error (TE), Dice similarity (DSC) and volume ratios between corresponding structures from pre- and post- registered images were computed and compared with the DDM. The DDM varied across subjects and structures; DDMmean of the bladder ranged from 2 to 13 mm and from 1 to 11 mm for the rectum. There was a high correlation between DDMmean of the bladder and the rectum (Pearson's correlation coefficient, R p  =  0.62). The correlation between DDMmean and the volume ratios post-DIR was stronger (R p  =  0.51; 0.68) than the correlation with the TE (bladder: R p  =  0.46; rectum: R p  =  0.47), or the ICE (bladder: R p  =  0.34; rectum: R p  =  0.37). There was a negative correlation between DSC and DDMmean of both the bladder (R p  =  -0.23) and the rectum (R p  =  -0.63). The DDM uncertainty metric indicated considerable DIR variability across subjects and structures. Our results show a stronger correlation with volume ratios and with the DSC using DDM compared to using ICE and TE. The DDM has the potential to quantitatively identify regions of large DIR uncertainties and consequently identify anatomical/scan outliers. The DDM can, thus, be applied to improve the adaptive RT process for tumor sites subject to motion.

Performance variations among clinically available deformable image registration tools in adaptive radiotherapy - how should we evaluate and interpret the result?

The purpose of this study is to evaluate the performance variations in commercial deformable image registration (DIR) tools for adaptive radiation therapy and further to interpret the differences using clinically available terms. Three clinical examples (prostate, head and neck (HN), and cranial spinal irradiation (CSI) with L‐spine boost) were evaluated in this study. Firstly, computerized deformed CT images were generated using simulation QA software with virtual deformations of bladder filling (prostate), neck flexion/bite‐block repositioning/tumor shrinkage (HN), and vertebral body rotation (CSI). The corresponding transformation matrices served as a “reference” for the following comparisons. Three commercialized DIR algorithms: the free‐form deformation from MIMVista 5.5 and the RegRefine from MIMMaestro 6.0, the multipass B‐spline from VelocityAI v3.0.1, and the adaptive demons from OnQ rts 2.1.15, were applied between the initial images and the deformed CT sets. The generated adaptive contours and dose distributions were compared with the “reference” and among each other. The performance in transferring contours was comparable among all three tools with an average Dice similarity coefficient of 0.81 for all the organs. However, the dose warping accuracy appeared to rely on the evaluation end points and methodologies. Point‐dose differences could show a difference of up to 23.3 Gy inside the PTVs and to overestimate up to 13.2 Gy for OARs, which was substantial for a 72 Gy prescription dose. Dosevolume histogram‐based evaluation might not be sensitive enough to illustrate all the detailed variations, while isodose assessment on a slice‐by‐slice basis could be tedious. We further explored the possibility of using 3D gamma index analysis for warping dose variation assessment, and observed differences in dose warping using different DIR tools. Overall, our results demonstrated that evaluation based only on the performance of contour transformation could not guarantee the accuracy in dose warping, while dose‐transferring validation strongly relied on the evaluation endpoint. As dose‐transferring errors could cause misinterpretations when attempting to accumulate dose for adaptive radiation therapy and more DIR tools are available for clinical use, a standard and clinically meaningful quality assurance criterion should be established for DIR QA in the near future.

PACS number(s): 87.57

Challenges of radiotherapy: report on the 4D treatment planning workshop 2013

This report, compiled by experts on the treatment of mobile targets with advanced radiotherapy, summarizes the main conclusions and innovations achieved during the 4D treatment planning workshop 2013. This annual workshop focuses on research aiming to advance 4D radiotherapy treatments, including all critical aspects of time resolved delivery, such as in-room imaging, motion detection, motion managing, beam application, and quality assurance techniques. The report aims to revise achievements in the field and to discuss remaining challenges and potential solutions. As main achievements advances in the development of a standardized 4D phantom and in the area of 4D-treatment plan optimization were identified. Furthermore, it was noticed that MR imaging gains importance and high interest for sequential 4DCT/MR data sets was expressed, which represents a general trend of the field towards data covering a longer time period of motion. A new point of attention was work related to dose reconstructions, which may play a major role in verification of 4D treatment deliveries. The experimental validation of results achieved by 4D treatment planning and the systematic evaluation of different deformable image registration methods especially for inter-modality fusions were identified as major remaining challenges. A challenge that was also suggested as focus for future 4D workshops was the adaptation of image guidance approaches from conventional radiotherapy into particle therapy. Besides summarizing the last workshop, the authors also want to point out new evolving demands and give an outlook on the focus of the next workshop.

Normal tissue sparing in a phase II trial on daily adaptive plan selection in radiotherapy for urinary bladder cancer

Background: Patients with urinary bladder cancer often display large changes in the shape and size of their bladder target during a course of radiotherapy (RT), making adaptive RT (ART) appealing for this tumour site. We are conducting a clinical phase II trial of daily plan selection-based ART for bladder cancer and here report dose-volume data from the first 20 patients treated in the trial.

MATERIAL AND METHODS

All patients received 60 Gy in 30 fractions to the bladder; in 13 of the patients the pelvic lymph nodes were simultaneously treated to 48 Gy. Daily patient set-up was by use of cone beam computed tomography (CBCT) guidance. The first 5 fractions were delivered with large, population-based (non-adaptive) margins. The bladder contours from the CBCTs acquired in the first 4 fractions were used to create a patient-specific library of three plans, corresponding to a small, medium and large size bladder. From fraction 6, daily online plan selection was performed, where the smallest plan covering the bladder was selected prior to each treatment delivery. A total of 600 treatment fractions in the 20 patients were evaluated.

RESULTS

Small, medium and large size plans were used almost equally often, with an average of 10, 9 and 11 fractions, respectively. The median volume ratio of the course-averaged PTV (PTV-ART) relative to the non-adaptive PTV was 0.70 (range: 0.46-0.89). A linear regression analysis showed a 183 cm(3) (CI 143-223 cm(3)) reduction in PTV-ART compared to the non-adaptive PTV (R(2) = 0.94).

CONCLUSION

Daily adaptive plan selection in RT of bladder cancer results in a considerable normal tissue sparing, of a magnitude that we expect will translate into a clinically significant reduction of the treatment-related morbidity.