Evolution of surface-based deformable image registration for adaptive radiotherapy of non-small cell lung cancer (NSCLC)

Feasibility of Ethos adaptive treatments of lung tumors and associated quality assurance

MOTIVATION

Online adaptive radiotherapy with Ethos is based on the anatomy determined from daily cone beam computed tomography (CBCT) images. Dose optimization and computation are performed on the density map of a synthetic CT (sCT), a deformable registration of the initial planning CT (pCT) onto the current CBCT. Large density changes as present in the lung region are challenging the system.

METHODS

Treatment plans for Ethos were created and delivered for 1, 2, and 3 cm diameter lung lesions in an anthropomorphic phantom, combining different insets in the pCT and during adaptive and non-adaptive treatment sessions. Primary and secondary dose calculations as well as back-projected dose from portal images were evaluated.

RESULTS

Density changes due to changed insets were not considered in the sCTs. This resulted in errors in the dose; for example, -15.9% of the mean dose for a plan when changing from a 3 cm inset in the pCT to 1 cm at the time of treatment. Secondary dose calculation is based on the sCT and could therefore not reveal these dose errors. However, dose calculation on the CBCT, either as a recalculation in the treatment planning system or as pre-treatment quality assurance (QA) before the treatment, indicated the differences. EPID in-vivo QA also reported discrepancies between calculated and delivered dose distributions.

CONCLUSIONS

An incorrect density distribution in the sCT has an impact on the dose calculation accuracy in the adaptive treatment workflow with the Ethos system. Additional quality checks of the sCT can detect such errors.

Evaluation of DIR schemes on tumor/organ with progressive shrinkage: accuracy of tumor/organ internal tissue tracking during the radiation treatment

PURPOSE

Accuracy of intratumoral treatment dose accumulation and response assessment highly depends on the accuracy of a DIR method. However, achievable accuracy of the existing DIR methods for tumor/organ with large and progressive shrinkage during the radiotherapy course have not been explored. This study aimed to use a bio-tissue phantom to quantify the achievable accuracy of different DIR schemes.

MATERIALS /METHODS

A fresh porcine liver was used for phantom material. Sixty gold markers were implanted on the surface and inside of the liver. To simulate the progressive radiation-induced tumor/organ shrinkage, the phantom was heated using a microwave oven incrementally from 30s to 200s in 8 phases. For each phase, the phantom was scanned by CT. Two extra image sets were generated from the original images: 1) the image set with overriding the high-density gold markers (feature image); 2) the image set with overriding the entire phantom to the mean soft tissue intensity (featureless image). Ten DIR schemes were evaluated to mimic clinical treatment situations of tumor/critical organ with respect to their surface and internal condition of image features, availability of intermediate feedback images and DIR methods. The internal marker's positions were utilized to evaluate DIR accuracy quantified by target registration error (TRE).

RESULTS

Volume reduction was about 20% ∼ 40% of the initial volume after 90s ∼ 200s of the heating. Without image features on the surface and inside of the phantom, the hybrid-DIR (image-based DIR followed by biomechanical model-based refinement) with the surface constraint achieved the registration TRE from 2.6 ± 1.2mm to 5.3 ± 2.6mm proportional to the %volume shrinkage. Meanwhile, the hybrid-DIR with the surface-marker constraint achieved the TRE from 2.4 ± 1.2mm to 2.6 ± 1.0mm. If both the surface and internal image features would be viable on the feedback images, the achievable accuracy could be minimal with the TRE from 1.6±0.9mm to 1.9 ± 1.2mm.

CONCLUSIONS

Standard DIR methods cannot guarantee intratumoral tissue registration accuracy for tumor/organ with large progressive shrinkage. Achievable accuracy with using the hybrid DIR method is highly dependent on the surface registration accuracy. If the surface registration mean TRE can be controlled within 2mm, the mean TRE of internal tissue can be controlled within 3mm.

Identification of modes of tumor regression in non-small cell lung cancer patients during radiotherapy

PURPOSE

Observed gross tumor volume (GTV) shrinkage during radiotherapy (RT) raises the question of whether to adapt treatment to changes observed on the acquired images. In the literature, two modes of tumor regression have been described: elastic and non-elastic. These modes of tumor regression will affect the safety of treatment adaptation. This study applies a novel approach, using routine cone-beam computed tomography (CBCT) and deformable image registration to automatically distinguish between elastic and non-elastic tumor regression.

METHODS

In this retrospective study, 150 locally advanced non-small cell lung cancer patients treated with 55 Gray of radiotherapy were included. First, the two modes of tumor regression were simulated. For each mode of tumor regression, one timepoint was simulated. Based on the results of simulated data, the approach used for analysis in real patients was developed. CBCTs were non-rigidly registered to the baseline CBCT using a cubic B-spline algorithm, NiftyReg. Next, the Jacobian determinants were computed from the deformation vector fields. To capture local volume changes, 10 Jacobian values were sampled perpendicular to the surface of the GTV, across the lung-tumor boundary. From the simulated data, we can distinguish elastic from non-elastic tumor regression by comparing the Jacobian values samples between 5 and 12.5 mm inside and 5 and 12.5 mm outside the planning GTV. Finally, morphometric results were compared between tumors of different histologies.

RESULTS

Most patients (92.3%) in our cohort showed stable disease in the first week of treatment and non-elastic shrinkage in the later weeks of treatment. At week 2, 125 patients (88%) showed stable disease, three patients (2.1%) disease progression, and 11 patients (8%) regression. By treatment completion, 91 patients (64%) had stable disease, one patient (0.7%) progression and 46 patients (32%) regression. A slight difference in the mode of tumor change was observed between tumors of different histologies.

CONCLUSION

Our novel approach shows that it may be possible to automatically quantify and identify global changes in lung cancer patients during RT, using routine CBCT images. Our results show that different regions of the tumor change in different ways. Therefore, careful consideration should be taken when adapting RT.

Enhanced super-resolution reconstruction of T1w time-resolved 4DMRI in low-contrast tissue using 2-step hybrid deformable image registration

Purpose

Deformable image registration (DIR) in low‐contrast tissues is often suboptimal because of low visibility of landmarks, low driving‐force to deform, and low penalty for misalignment. We aim to overcome the shortcomings for improved reconstruction of time‐resolved four‐dimensional magnetic resonance imaging (TR‐4DMRI).

Methods and Materials

Super‐resolution TR‐4DMRI reconstruction utilizes DIR to combine high‐resolution (highR:2x2x2mm³) breath‐hold (BH) and low‐resolution (lowR:5x5x5mm³) free‐breathing (FB) 3D cine (2Hz) images to achieve clinically acceptable spatiotemporal resolution. A 2‐step hybrid DIR approach was developed to segment low‐dynamic‐range (LDR) regions: low‐intensity lungs and high‐intensity “bodyshell” (=body‐lungs) for DIR refinement after conventional DIR. The intensity in LDR regions was renormalized to the full dynamic range (FDR) to enhance local tissue contrast. A T1‐mapped 4D XCAT digital phantom was created, and seven volunteers and five lung cancer patients were scanned with two BH and one 3D cine series per subject to compare the 1‐step conventional and 2‐step hybrid DIR using: (a) the ground truth in the phantom, (b) highR‐BH references, which were used to simulate 3D cine images by down‐sampling and Rayleigh‐noise‐adding, and (c) cross‐verification between two TR‐4DMRI images reconstructed from two BHs. To assess DIR improvement, 8‐17 blood vessel bifurcations were used in volunteers, and lung tumor position, size, and shape were used in phantom and patients, together with the voxel intensity correlation (VIC), structural similarity (SSIM), and cross‐consistency check (CCC).

Results

The 2‐step hybrid DIR improves contrast and DIR accuracy. In volunteers, it improves low‐contrast alignment from 6.5 ± 1.8 mm to 3.3 ± 1.0 mm. In phantom, it improves tumor center of mass alignment (COM = 1.3 ± 0.2 mm) and minimizes DIR directional difference. In patients, it produces almost‐identical tumor COM, size, and shape (dice> 0.85) as the reference. The VIC and SSIM are significantly increased and the number of CCC outliers are reduced by half.

Conclusion

The 2‐step hybrid DIR improves low‐contrast‐tissue alignment and increases lung tumor fidelity. It is recommended to adopt the 2‐step hybrid DIR for TR‐4DMRI reconstruction.

Dosimetric comparison of dose accumulation between rigid registration and deformation registration in intensity-modulated radiation therapy for large volume non-small cell lung cancer

Background

To evaluate the cumulative dose to the target volumes and organs at risk (OARs) after replanning during intensity-modulated radiation therapy (IMRT) for large volume non-small cell lung cancer (NSCLC) based on rigid registration and deformation registration technologies.

Methods

Thirty patients with large volume NSCLC who were treated with IMRT were selected, and two four-dimensional computed tomography (4DCT) scans were acquired before radiotherapy and after 20 fractions of radiotherapy. The initial treatment plan (Plan₁) based on the average density projection CT (CT_1-avg) of the first 4DCT images and the second treatment plan (Plan₂) based on CT_2-avg of the second 4DCT images were calculated. Then, the dose distributions of Plan₂ and Plan₁ were accumulated based on rigid and deformation registration technologies to obtain Plan_rig and Plan_def, respectively. Finally, the volume changes of the gross tumor volume (GTV) and OARs between the two CT scans, and the dose-volume parameters among Plan₁, Plan₂, Plan_rig and Plan_def were compared.

Results

Compared with those on the first CT, the mean GTV and heart volume on the second CT decreased by 44.2% and 5.5%, respectively, while the mean volumes of the ipsilateral lung, contralateral lung and total lung increased by 5.2%, 6.2% and 5.8%, respectively. The differences in the above volume parameters between the two CT scans were statistically significant (P<0.05). Compared with those in Plan₁, the D₉₅, D₉₈ and V_100% values of the IGTV (GTV fusion of 10 CT phases) and planning target volume (PTV) in Plan₂ did not change significantly (P>0.05), and those of Plan_rig and Plan_def decreased slightly (P<0.05). The dose-volume parameters of the spinal cord, heart, ipsilateral lung and total lung in Plan₂, Plan_rig and Plan_def were significantly lower than those in Plan₁ (P<0.05). Among these parameters, V₃₀ and the mean dose to the heart in Plan₂, Plan_rig and Plan_def decreased by 27.3%, 16.5%, and 15.3% and 15.2%, 6.6%, and 5.6% compared to those in Plan₁, respectively; V₂₀ and the mean dose to the total lung in Plan₂, Plan_rig and Plan_def decreased by 15.6%, 4.5%, and 3.7% and 15.7%, 6.2%, and 5.1% compared to those in Plan₁, respectively. Some dose-volume parameters (including D₉₅ and D₉₈ to the target volume, V₄₀ of the heart, V₂₀ and the mean dose to the ipsilateral lung and the total lung) of Plan_def were slightly higher than those in Plan_rig (P<0.05). The Dice similarity coefficients (DSCs) of the OARs after deformation registration were significantly higher than those after rigid registration (P<0.05).

Conclusions

The dose-volume parameters of OARs in Plan₂ were noticeably different from those in Plan₁, so all of these parameters have large deviations in evaluating the actual dose to the OARs. And, the dose-volume parameters obtained by deformation registration can better predict the actual dose than those obtained by rigid registration.

CALIPER: A deformable image registration algorithm for large geometric changes during radiotherapy for locally advanced non-small cell lung cancer

PURPOSE

Locally advanced non-small cell lung cancer (NSCLC) patients may experience dramatic changes in anatomy during radiotherapy and could benefit from adaptive radiotherapy (ART). Deformable image registration (DIR) is necessary to accurately accumulate dose during plan adaptation, but current algorithms perform poorly in the presence of large geometric changes, namely atelectasis resolution. The goal of this work was to develop a DIR framework, named Consistent Anatomy in Lung Parametric imagE Registration (CALIPER), to handle large geometric changes in the thorax.

METHODS

Registrations were performed on pairs of baseline and mid-treatment CT datasets of NSCLC patients presenting with atelectasis at the start of treatment. Pairs were classified based on atelectasis volume change as either full, partial, or no resolution. The evaluated registration algorithms consisted of several combinations of a hybrid intensity- and feature-based similarity cost function to investigate the ability to simultaneously match healthy lung parenchyma and adjacent atelectasis. These components of the cost function included a mass-preserving intensity cost in the lung parenchyma, use of filters to enhance vascular structures in the lung parenchyma, manually delineated lung lobes as labels, and several intensity cost functions to model atelectasis change. Registration error was quantified with landmark-based target registration error and post-registration alignment of atelectatic lobes.

RESULTS

The registrations using both lobe labels and vasculature enhancement in addition to intensity of the CT images were found to have the highest accuracy. Of these registrations, the mean (SD) of mean landmark error across patients was 2.50 (1.16) mm, 2.80 (0.70) mm, and 2.04 (0.13) mm for no change, partial resolution, and full atelectasis resolution, respectively. The mean (SD) atelectatic lobe Dice similarity coefficient was 0.91 (0.08), 0.90 (0.08), and 0.89 (0.04), respectively, for the same groups. Registration accuracy was comparable to healthy lung registrations of current state-of-the-art algorithms reported in literature.

CONCLUSIONS

The CALIPER algorithm developed in this work achieves accurate image registration for challenging cases involving large geometric and topological changes in NSCLC patients, a requirement for enabling ART in this patient group.

Adaptive radiotherapy for NSCLC patients: utilizing the principle of energy conservation to evaluate dose mapping operations

Tumor regression during the course of fractionated radiotherapy confounds the ability to accurately estimate the total dose delivered to tumor targets. Here we present a new criterion to improve the accuracy of image intensity-based dose mapping operations for adaptive radiotherapy for patients with non-small cell lung cancer (NSCLC). Six NSCLC patients were retrospectively investigated in this study. An image intensity-based B-spline registration algorithm was used for deformable image registration (DIR) of weekly CBCT images to a reference image. The resultant displacement vector fields were employed to map the doses calculated on weekly images to the reference image. The concept of energy conservation was introduced as a criterion to evaluate the accuracy of the dose mapping operations. A finite element method (FEM)-based mechanical model was implemented to improve the performance of the B-Spline-based registration algorithm in regions involving tumor regression. For the six patients, deformed tumor volumes changed by 21.2  ±  15.0% and 4.1  ±  3.7% on average for the B-Spline and the FEM-based registrations performed from fraction 1 to fraction 21, respectively. The energy deposited in the gross tumor volume (GTV) was 0.66 Joules (J) per fraction on average. The energy derived from the fractional dose reconstructed by the B-spline and FEM-based DIR algorithms in the deformed GTV's was 0.51 J and 0.64 J, respectively. Based on landmark comparisons for the 6 patients, mean error for the FEM-based DIR algorithm was 2.5  ±  1.9 mm. The cross-correlation coefficient between the landmark-measured displacement error and the loss of radiation energy was  -0.16 for the FEM-based algorithm. To avoid uncertainties in measuring distorted landmarks, the B-Spline-based registrations were compared to the FEM registrations, and their displacement differences equal 4.2  ±  4.7 mm on average. The displacement differences were correlated to their relative loss of radiation energy with a cross-correlation coefficient equal to 0.68. Based on the principle of energy conservation, the FEM-based mechanical model has a better performance than the B-Spline-based DIR algorithm. It is recommended that the principle of energy conservation be incorporated into a comprehensive QA protocol for adaptive radiotherapy.

Evaluation of adaptive treatment planning for patients with non-small cell lung cancer

The purpose of this study was to develop metrics to evaluate uncertainties in deformable dose accumulation for patients with non-small cell lung cancer (NSCLC). Initial treatment plans (primary) and cone-beam CT (CBCT) images were retrospectively processed for seven NSCLC patients, who showed significant tumor regression during the course of treatment. Each plan was developed with IMRT for 2 Gy  ×  33 fractions. A B-spline-based DIR algorithm was used to register weekly CBCT images to a reference image acquired at fraction 21 and the resultant displacement vector fields (DVFs) were then modified using a finite element method (FEM). The doses were calculated on each of these CBCT images and mapped to the reference image using a tri-linear dose interpolation method, based on the B-spline and FEM-generated DVFs. Contours propagated from the planning image were adjusted to the residual tumor and OARs on the reference image to develop a secondary plan. For iso-prescription adaptive plans (relative to initial plans), mean lung dose (MLD) was reduced, on average from 17.3 Gy (initial plan) to 15.2, 14.5 and 14.8 Gy for the plans adapted using the rigid, B-Spline and FEM-based registrations. Similarly, for iso-toxic adaptive plans (considering MLD relative to initial plans) using the rigid, B-Spline and FEM-based registrations, the average doses were 69.9  ±  6.8, 65.7  ±  5.1 and 67.2  ±  5.6 Gy in the initial volume (PTV₁), and 81.5  ±  25.8, 77.7  ±  21.6, and 78.9  ±  22.5 Gy in the residual volume (PTV₂₁), respectively. Tumor volume reduction was correlated with dose escalation (for isotoxic plans, correlation coefficient  =  0.92), and with MLD reduction (for iso-fractional plans, correlation coefficient  =  0.85). For the case of the iso-toxic dose escalation, plans adapted with the B-Spline and FEM DVFs differed from the primary plan adapted with rigid registration by 2.8  ±  1.0 Gy and 1.8  ±  0.9 Gy in PTV₁, and the mean difference between doses accumulated using the B-spline and FEM DVF's was 1.1  ±  0.6 Gy. As a dose mapping-induced energy change, energy defect in the tumor volume was 20.8  ±  13.4% and 4.5  ±  2.4% for the B-spline and FEM-based dose accumulations, respectively. The energy defect of the B-Spline-based dose accumulation is significant in the tumor volume and highly correlated to the difference between the B-Spline and FEM-accumulated doses with their correlation coefficient equal to 0.79. Adaptive planning helps escalate target dose and spare normal tissue for patients with NSCLC, but deformable dose accumulation may have a significant loss of energy in regressed tumor volumes when using image intensity-based DIR algorithms. The metric of energy defect is a useful tool for evaluation of adaptive planning accuracy for lung cancer patients.

Reduction in Tumor Volume by Cone Beam Computed Tomography Predicts Overall Survival in Non-Small Cell Lung Cancer Treated With Chemoradiation Therapy

PURPOSE

We sought to evaluate whether tumor response using cone beam computed tomography (CBCT) performed as part of the routine care during chemoradiation therapy (CRT) could forecast the outcome of unresectable, locally advanced, non-small cell lung cancer (NSCLC).

METHODS AND MATERIALS

We manually delineated primary tumor volumes (TV) of patients with NSCLC who were treated with radical CRT on days 1, 8, 15, 22, 29, 36, and 43 on CBCTs obtained as part of the standard radiation treatment course. Percentage reductions in TV were calculated and then correlated to survival and pattern of recurrence using Cox proportional hazard models. Clinical information including histologic subtype was also considered in the study of such associations.

RESULTS

We evaluated 38 patients with a median follow-up time of 23.4 months. The median TV reduction was 39.3% (range, 7.3%-69.3%) from day 1 (D1) to day 43 (D43) CBCTs. Overall survival was associated with TV reduction from D1 to D43 (hazard ratio [HR] 0.557, 95% CI 0.39-0.79, P=.0009). For every 10% decrease in TV from D1 to D43, the risk of death decreased by 44.3%. For patients whose TV decreased ≥39.3 or <39.3%, log-rank test demonstrated a separation in survival (P=.02), with median survivals of 31 months versus 10 months, respectively. Neither local recurrence (HR 0.791, 95% CI 0.51-1.23, P=.29), nor distant recurrence (HR 0.78, 95% CI 0.57-1.08, P=.137) correlated with TV decrease from D1 to D43. Histologic subtype showed no impact on our findings.

CONCLUSIONS

TV reduction as determined by CBCT during CRT as part of routine care predicts post-CRT survival. Such knowledge may justify intensification of RT or application of additional therapies. Assessment of genomic characteristics of these tumors may permit a better understanding of behavior or prediction of therapeutic outcomes.

A block matching-based registration algorithm for localization of locally advanced lung tumors

PURPOSE

To implement and evaluate a block matching-based registration (BMR) algorithm for locally advanced lung tumor localization during image-guided radiotherapy.

METHODS

Small (1 cm(3)), nonoverlapping image subvolumes ("blocks") were automatically identified on the planning image to cover the tumor surface using a measure of the local intensity gradient. Blocks were independently and automatically registered to the on-treatment image using a rigid transform. To improve speed and robustness, registrations were performed iteratively from coarse to fine image resolution. At each resolution, all block displacements having a near-maximum similarity score were stored. From this list, a single displacement vector for each block was iteratively selected which maximized the consistency of displacement vectors across immediately neighboring blocks. These selected displacements were regularized using a median filter before proceeding to registrations at finer image resolutions. After evaluating all image resolutions, the global rigid transform of the on-treatment image was computed using a Procrustes analysis, providing the couch shift for patient setup correction. This algorithm was evaluated for 18 locally advanced lung cancer patients, each with 4-7 weekly on-treatment computed tomography scans having physician-delineated gross tumor volumes. Volume overlap (VO) and border displacement errors (BDE) were calculated relative to the nominal physician-identified targets to establish residual error after registration.

RESULTS

Implementation of multiresolution registration improved block matching accuracy by 39% compared to registration using only the full resolution images. By also considering multiple potential displacements per block, initial errors were reduced by 65%. Using the final implementation of the BMR algorithm, VO was significantly improved from 77% ± 21% (range: 0%-100%) in the initial bony alignment to 91% ± 8% (range: 56%-100%;p < 0.001). Left-right, anterior-posterior, and superior-inferior systematic BDE were 3.2, 2.4, and 4.4 mm, respectively, with random BDE of 2.4, 2.1, and 2.7 mm. Margins required to include both localization and delineation uncertainties ranged from 5.0 to 11.7 mm, an average of 40% less than required for bony alignment.

CONCLUSIONS

BMR is a promising approach for automatic lung tumor localization. Further evaluation is warranted to assess the accuracy and robustness of BMR against other potential localization strategies.

Accuracy of deformable image registration for contour propagation in adaptive lung radiotherapy

Background

Deformable image registration (DIR) is an attractive method for automatic propagation of regions of interest (ROIs) in adaptive lung radiotherapy. This study investigates DIR for automatic contour propagation in adaptive Non Small Cell Lung Carcinoma patients.

Methods

Pre and mid-treatment fan beam 4D-kVCT scans were taken for 17 NSCLC patients. Gross tumour volumes (GTV), nodal-GTVs, lungs, esophagus and spinal cord were delineated on all kVCT scans. ROIs were propagated from pre- to mid-treatment images using three DIR algorithms. DIR-propagated ROIs were compared with physician-drawn ROIs on the mid-treatment scan using the Dice score and the mean slicewise Hausdorff distance to agreement (MSHD). A physician scored the DIR-propagated ROIs based on clinical utility.

Results

Good agreement between the DIR-propagated and physician drawn ROIs was observed for the lungs and spinal cord. Agreement was not as good for the nodal-GTVs and esophagus, due to poor soft-tissue contrast surrounding these structures. 96% of OARs and 85% of target volumes were scored as requiring no or minor adjustments.

Conclusions

DIR has been shown to be a clinically useful method for automatic contour propagation in adaptive radiotherapy however thorough assessment of propagated ROIs by the treating physician is recommended.

Performance validation of deformable image registration in the pelvic region

Patients undergoing radiotherapy will inevitably show anatomical changes during the course of treatment. These can be weight loss, tumour shrinkage, and organ motion or filling changes. For advanced and adaptive radiotherapy (ART) information about anatomical changes must be extracted from repeated images in order to be able to evaluate and manage these changes. Deformable image registration (DIR) is a tool that can be used to efficiently gather information about anatomical changes. The aim of the present study was to evaluate the performance of two DIR methods for automatic organ at risk (OAR) contour propagation. Datasets from ten gynaecological patients having repeated computed tomography (CT) and cone beam computed tomography (CBCT) scans were collected. Contours were delineated on the planning CT and on every repeated scan by an expert clinician. DIR using our in-house developed featurelet-based method and the iPlan(®) BrainLab treatment planning system software was performed with the planning CT as reference and a selection of repeated scans as the target dataset. The planning CT contours were deformed using the resulting deformation fields and compared to the manually defined contours. Dice's similarity coefficients (DSCs) were calculated for each fractional patient scan structure, comparing the volume overlap using DIR with that using rigid registration only. No significant improvement in volume overlap was found after DIR as compared with rigid registration, independent of which image modality or DIR method was used. DIR needs to be further improved in order to facilitate contour propagation in the pelvic region in ART approaches.

Evaluation of 4-dimensional computed tomography to 4-dimensional cone-beam computed tomography deformable image registration for lung cancer adaptive radiation therapy

PURPOSE

To evaluate 2 deformable image registration (DIR) algorithms for the purpose of contour mapping to support image-guided adaptive radiation therapy with 4-dimensional cone-beam CT (4DCBCT).

METHODS AND MATERIALS

One planning 4D fan-beam CT (4DFBCT) and 7 weekly 4DCBCT scans were acquired for 10 locally advanced non-small cell lung cancer patients. The gross tumor volume was delineated by a physician in all 4D images. End-of-inspiration phase planning 4DFBCT was registered to the corresponding phase in weekly 4DCBCT images for day-to-day registrations. For phase-to-phase registration, the end-of-inspiration phase from each 4D image was registered to the end-of-expiration phase. Two DIR algorithms-small deformation inverse consistent linear elastic (SICLE) and Insight Toolkit diffeomorphic demons (DEMONS)-were evaluated. Physician-delineated contours were compared with the warped contours by using the Dice similarity coefficient (DSC), average symmetric distance, and false-positive and false-negative indices. The DIR results are compared with rigid registration of tumor.

RESULTS

For day-to-day registrations, the mean DSC was 0.75 ± 0.09 with SICLE, 0.70 ± 0.12 with DEMONS, 0.66 ± 0.12 with rigid-tumor registration, and 0.60 ± 0.14 with rigid-bone registration. Results were comparable to intraobserver variability calculated from phase-to-phase registrations as well as measured interobserver variation for 1 patient. SICLE and DEMONS, when compared with rigid-bone (4.1 mm) and rigid-tumor (3.6 mm) registration, respectively reduced the average symmetric distance to 2.6 and 3.3 mm. On average, SICLE and DEMONS increased the DSC to 0.80 and 0.79, respectively, compared with rigid-tumor (0.78) registrations for 4DCBCT phase-to-phase registrations.

CONCLUSIONS

Deformable image registration achieved comparable accuracy to reported interobserver delineation variability and higher accuracy than rigid-tumor registration. Deformable image registration performance varied with the algorithm and the patient.

Combining advanced radiotherapy technologies to maximize safety and tumor control probability in stage III non-small cell lung cancer

BACKGROUND

The goal of the current study was to investigate the tumor control probability (TCP) of advanced radiotherapy technologies for stage III non-small cell lung cancer (NSCLC) and to evaluate potential interplay effects between their applications.

MATERIALS AND METHODS

Three-dimensional conformal radiotherapy (3D-CRT) with conventionally fractionated doses of 66 Gy served as reference for 13 patients with stage III NSCLC. Isotoxic dose escalation relative to the corresponding 3D-CRT plans was performed for three technologies and their combinations: intensity-modulated radiotherapy (IMRT), IMRT with a simultaneous integrated boost (IMRT-SIB) of 10% to the gross tumor volume (GTV), and adaptive re-planning twice during the treatment course (ART). All analyses were based on accumulated dose distributions using deformable image registration of CT images, which were acquired weekly during the treatment course.

RESULTS

IMRT reduced the mean lung dose (MLD) by 5.6% ± 3.8% compared to 3D-CRT. ART resulted in lung sparing of 7.9% ± 4.8% and 9.2% ± 3.9% in 3D-CRT and IMRT planning, respectively. IMRT and ART escalated the irradiation dose by 6.6% ± 3.2% and 8.8% ± 6.3%, respectively, which was not statistically different. For the 7 patients with the largest GTVs, IMRT-SIB was superior to IMRT and ART with dose escalation of 11.9% ± 3.7%. The combination of ART, IMRT, and SIB achieved maximum dose escalation in all 13 patients by 17.1% ± 5.4% on average, which increased TCP from 19.9% ± 7.0 to 37.1% ± 10.1%. Adaptive re-planning was required to continuously conform the escalated and hypofractionated SIB doses to the shrinking tumor.

CONCLUSION

Combining advanced radiotherapy technologies is considered as a safe and effective strategy to maximize local tumor control probability in stage III NSCLC.

Localization accuracy from automatic and semi-automatic rigid registration of locally-advanced lung cancer targets during image-guided radiation therapy

PURPOSE

To evaluate localization accuracy resulting from rigid registration of locally-advanced lung cancer targets using fully automatic and semi-automatic protocols for image-guided radiation therapy.

METHODS

Seventeen lung cancer patients, fourteen also presenting with involved lymph nodes, received computed tomography (CT) scans once per week throughout treatment under active breathing control. A physician contoured both lung and lymph node targets for all weekly scans. Various automatic and semi-automatic rigid registration techniques were then performed for both individual and simultaneous alignments of the primary gross tumor volume (GTV(P)) and involved lymph nodes (GTV(LN)) to simulate the localization process in image-guided radiation therapy. Techniques included "standard" (direct registration of weekly images to a planning CT), "seeded" (manual prealignment of targets to guide standard registration), "transitive-based" (alignment of pretreatment and planning CTs through one or more intermediate images), and "rereferenced" (designation of a new reference image for registration). Localization error (LE) was assessed as the residual centroid and border distances between targets from planning and weekly CTs after registration.

RESULTS

Initial bony alignment resulted in centroid LE of 7.3 ± 5.4 mm and 5.4 ± 3.4 mm for the GTV(P) and GTV(LN), respectively. Compared to bony alignment, transitive-based and seeded registrations significantly reduced GTV(P) centroid LE to 4.7 ± 3.7 mm (p = 0.011) and 4.3 ± 2.5 mm (p < 1 × 10(-3)), respectively, but the smallest GTV(P) LE of 2.4 ± 2.1 mm was provided by rereferenced registration (p < 1 × 10(-6)). Standard registration significantly reduced GTV(LN) centroid LE to 3.2 ± 2.5 mm (p < 1 × 10(-3)) compared to bony alignment, with little additional gain offered by the other registration techniques. For simultaneous target alignment, centroid LE as low as 3.9 ± 2.7 mm and 3.8 ± 2.3 mm were achieved for the GTV(P) and GTV(LN), respectively, using rereferenced registration.

CONCLUSIONS

Target shape, volume, and configuration changes during radiation therapy limited the accuracy of standard rigid registration for image-guided localization in locally-advanced lung cancer. Significant error reductions were possible using other rigid registration techniques, with LE approaching the lower limit imposed by interfraction target variability throughout treatment.

Tumor volume as a potential imaging-based risk-stratification factor in trimodality therapy for locally advanced non-small cell lung cancer

INTRODUCTION

The role of trimodality therapy for locally advanced non-small cell lung cancer (NSCLC) continues to be defined. We hypothesized that imaging parameters on pre- and postradiation positron emission tomography (PET)-computed tomography (CT) imaging are prognostic for outcome after preoperative chemoradiotherapy (CRT)/resection/consolidation chemotherapy and could help risk-stratify patients in clinical trials.

METHODS

We enrolled 13 patients on a prospective clinical trial of trimodality therapy for resectable locally advanced NSCLC. PET-CT was acquired for radiation planning and after 45 Gy. Gross tumor volume (GTV) and standardized uptake value were measured at pre- and post-CRT time points and correlated with nodal pathologic complete response, loco-regional and/or distant progression, and overall survival. In addition, we evaluated the performance of automatic deformable image registration (ADIR) software for volumetric response assessment.

RESULTS

All patients responded with average total GTV reductions after 45 Gy of 43% (range: 27-64%). Pre- and post-CRT GTVs were highly correlated (R² = 0.9), and their respective median values divided the patients into the same two groups. ADIR measurements agreed closely with manually segmented post-CRT GTVs. Patients with GTV ≥ median (137 ml pre-CRT and 67 ml post-CRT) had 3-year progression-free survival (PFS) of 14% versus 75% for GTV less than median, a significant difference (p = 0.049). Pre- and post-CRT PET-standardized uptake value did not correlate significantly with pathologic complete response, PFS, or overall survival.

CONCLUSIONS

Preoperative CRT with carboplatin/docetaxel/45 Gy resulted in excellent response rates. In this exploratory analysis, pre- and post-CRT GTV predicted PFS in trimodality therapy, consistent with our earlier studies in a broader cohort of NSCLC. ADIR seems robust enough for volumetric response assessment in clinical trials.

Adaptive radiotherapy for locally advanced non-small-cell lung cancer does not underdose the microscopic disease and has the potential to increase tumor control

PURPOSE

To evaluate doses to the microscopic disease (MD) in adaptive radiotherapy (ART) for locally advanced non-small-cell lung cancer (NSCLC) and to model tumor control probability (TCP).

METHODS AND MATERIALS

In a retrospective planning study, three-dimensional conformal treatment plans for 13 patients with locally advanced NSCLC were adapted to shape and volume changes of the gross tumor volume (GTV) once or twice during conventionally fractionated radiotherapy with total doses of 66 Gy; doses in the ART plans were escalated using an iso-mean lung dose (MLD) approach compared to non-adapted treatment. Dose distributions to the volumes of suspect MD were simulated for a scenario with synchronous shrinkage of the MD and GTV and for a scenario of a stationary MD despite GTV shrinkage; simulations were performed using deformable image registration. TCP calculations considering doses to the GTV and MD were performed using three different models.

RESULTS

Coverage of the MD at 50 Gy was not compromised by ART. Coverage at 60 Gy in the scenario of a stationary MD was significantly reduced from 92% ± 10% to 73% ± 19% using ART; however, the coverage was restored by iso-MLD dose escalation. Dose distributions in the MD were sufficient to achieve a TCP >80% on average in all simulation experiments, with the clonogenic cell density the major factor influencing TCP. The combined TCP for the GTV and MD was 19.9% averaged over all patients and TCP models in non-adaptive treatment with 66 Gy. Iso-MLD dose escalation achieved by ART increased the overall TCP by absolute 6% (adapting plan once) and by 8.7% (adapting plan twice) on average. Absolute TCP values were significantly different between the TCP models; however, all TCP models suggested very similar TCP increase by using ART.

CONCLUSIONS

Adaptation of radiotherapy to the shrinking GTV did not compromise dose coverage of volumes of suspect microscopic disease and has the potential to increase TCP by >40% compared with radiotherapy planning without ART.

Validation of an elastic registration technique to estimate anatomical lung modification in non-small-cell lung cancer tomotherapy

BACKGROUND

The study of lung parenchyma anatomical modification is useful to estimate dose discrepancies during the radiation treatment of Non-Small-Cell Lung Cancer (NSCLC) patients. We propose and validate a method, based on free-form deformation and mutual information, to elastically register planning kVCT with daily MVCT images, to estimate lung parenchyma modification during Tomotherapy.

METHODS

We analyzed 15 registrations between the planning kVCT and 3 MVCT images for each of the 5 NSCLC patients. Image registration accuracy was evaluated by visual inspection and, quantitatively, by Correlation Coefficients (CC) and Target Registration Errors (TRE). Finally, a lung volume correspondence analysis was performed to specifically evaluate registration accuracy in lungs.

RESULTS

Results showed that elastic registration was always satisfactory, both qualitatively and quantitatively: TRE after elastic registration (average value of 3.6 mm) remained comparable and often smaller than voxel resolution. Lung volume variations were well estimated by elastic registration (average volume and centroid errors of 1.78% and 0.87 mm, respectively).

CONCLUSIONS

Our results demonstrate that this method is able to estimate lung deformations in thorax MVCT, with an accuracy within 3.6 mm comparable or smaller than the voxel dimension of the kVCT and MVCT images. It could be used to estimate lung parenchyma dose variations in thoracic Tomotherapy.

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.

Potential of adaptive radiotherapy to escalate the radiation dose in combined radiochemotherapy for locally advanced non-small cell lung cancer

PURPOSE

To evaluate the potential of adaptive radiotherapy (ART) for advanced-stage non-small cell lung cancer (NSCLC) in terms of lung sparing and dose escalation.

METHODS AND MATERIALS

In 13 patients with locally advanced NSCLC, weekly CT images were acquired during radio- (n=1) or radiochemotherapy (n=12) for simulation of ART. Three-dimensional (3D) conformal treatment plans were generated: conventionally fractionated doses of 66 Gy were prescribed to the planning target volume without elective lymph node irradiation (Plan_3D). Using a surface-based algorithm of deformable image registration, accumulated doses were calculated in the CT images acquired during the treatment course (Plan_4D). Field sizes were adapted to tumor shrinkage once in week 3 or 5 and twice in weeks 3 and 5.

RESULTS

A continuous tumor regression of 1.2% per day resulted in a residual gross tumor volume (GTV) of 49%±15% after six weeks of treatment. No systematic differences between Plan_3D and Plan_4D were observed regarding doses to the GTV, lung, and spinal cord. Plan adaptation to tumor shrinkage resulted in significantly decreased lung doses without compromising GTV coverage: single-plan adaptation in Week 3 or 5 and twice-plan adaptation in Weeks 3 and 5 reduced the mean lung dose by 5.0%±4.4%, 5.6%±2.9% and 7.9%±4.8%, respectively. This lung sparing with twice ART allowed an iso-mean lung dose escalation of the GTV dose from 66.8 Gy±0.8 Gy to 73.6 Gy±3.8 Gy.

CONCLUSIONS

Adaptation of radiotherapy to continuous tumor shrinkage during the treatment course reduced doses to the lung, allowed significant dose escalation and has the potential of increased local control.