Radiation therapy margin reduction for patients with localized prostate cancer: A prospective study of the dosimetric impact and quality of life.

OBJECTIVES: To investigate the impact of reducing Clinical Target Volume (CTV) to Planning Target Volume (PTV) margins on delivered radiation therapy (RT) dose and patient reported quality-of-life (QOL) for patients with localized prostate cancer. METHODS: Twenty patients were included in a single institution IRB-approved prospective study. Nine were planned with reduced margins (4 mm at prostate/rectum interface, 5 mm elsewhere), and 11 with standard margins (6/10 mm). Cumulative delivered dose was calculated using deformable dose accumulation. Each daily CBCT dataset was deformed to the planning CT (pCT), dose was computed, and accumulated on the resampled pCT using a parameter-optimized, B-spline algorithm (Elastix, ITK/VTK). EPIC-26 patient reported QOL was prospectively collected pre-treatment, post-treatment, and at 2-, 6-, 12-, 18-, 24-, 36-, 48-, and 60-month follow-ups. Post -RT QOL scores were baseline corrected and standardized to a [0-100] scale using EPIC-26 methodology. Correlations between QOL scores and dosimetric parameters were investigated, and the overall QOL differences between the two groups (QOLMargin-reduced -QOLcontrol ) were calculated. RESULTS: The median QOL follow-up length for the 20 patients was 48 months. Difference between delivered dose and planned dose did not reach statistical significance (p > 0.1) for both targets and organs at risk between the two groups. At 4 years post-RT, standardized mean QOLMargin-reduced -QOLcontrol were improved for Urinary Incontinence, Urinary Irritative/Obstructive, Bowel, and Sexual EPIC domains by 3.5, 14.8, 10.2, and 16.1, respectively (higher values better). The control group showed larger PTV/rectum and PTV/bladder intersection volumes (7.2 ± 5.8, 18.2 ± 8.1 cc) than the margin-reduced group (2.6 ± 1.8, 12.5 ± 8.3 cc), though the dose to these intersection volumes did not reach statistical significance (p > 0.1) between the groups. PTV/rectum intersection volume showed a moderate correlation (r = -0.56, p < 0.05) to Bowel EPIC domain. CONCLUSIONS: Results of this prospective study showed that margin-reduced group exhibited clinically meaningful improvement of QOL without compromising the target dose coverage.

How does CBCT reconstruction algorithm impact on deformably mapped targets and accumulated dose distributions?

PURPOSE: We performed quantitative analysis of differences in deformable image registration (DIR) and deformable dose accumulation (DDA) computed on CBCT datasets reconstructed using the standard (Feldkamp-Davis-Kress: FDK_CBCT) and a novel iterative (iterative_CBCT) CBCT reconstruction algorithms. METHODS: Both FDK_CBCT and iterative_CBCT images were reconstructed for 323 fractions of treatment for 10 prostate cancer patients. Planning CT images were deformably registered to each CBCT image data set. After daily dose distributions were computed, they were mapped to planning CT to obtain deformed doses. Dosimetric and image registration results based CBCT images reconstructed by two algorithms were compared at three levels: (A) voxel doses over entire dose calculation volume, (B) clinical constraint results on targets and sensitive structures, and (C) contours propagated to CBCT images using DIR results based on three algorithms (SmartAdapt, Velocity, and Elastix) were compared with manually delineated contours as ground truth. RESULTS: (A) Average daily dose differences and average normalized DDA differences between FDK_CBCT and iterative_CBCT were ≤1 cGy. Maximum daily point dose differences increased from 0.22 ± 0.06 Gy (before the deformable dose mapping operation) to 1.33 ± 0.38 Gy after the deformable dose mapping. Maximum differences of normalized DDA per fraction were up to 0.80 Gy (0.42 ± 0.19 Gy). (B) Differences in target minimum doses were up to 8.31 Gy (-0.62 ± 4.60 Gy) and differences in critical structure doses were 0.70 ± 1.49 Gy. (C) For mapped prostate contours based on iterative_CBCT (relative to standard FDK_CBCT), dice similarity coefficient increased by 0.10 ± 0.09 (p < 0.0001), mass center distances decreased by 2.5 ± 3.0 mm (p < 0.00005), and Hausdorff distances decreased by 3.3 ± 4.4 mm (p < 0.00015). CONCLUSIONS: The new iterative CBCT reconstruction algorithm leads to different mapped volumes of interest, deformed and cumulative doses than results based on conventional FDK_CBCT.

Evaluation and Clinical Application of a Commercially Available Iterative Reconstruction Algorithm for CBCT-Based IGRT.

PURPOSE: We have quantitatively evaluated the image quality of a new commercially available iterative cone-beam computed tomography reconstruction algorithm over standard cone-beam computed tomography image reconstruction results. METHODS: This iterative cone-beam computed tomography reconstruction pipeline uses a finite element solver (AcurosCTS)-based scatter correction and a statistical (iterative) reconstruction in addition to a standard kernel-based correction followed by filtered back-projection-based Feldkamp-Davis-Kress cone-beam computed tomography reconstruction. Standard full-fan half-rotation Head, half-fan full-rotation Head, and standard Pelvis cone-beam computed tomography protocols have been investigated to scan a quality assurance phantom via the following image quality metrics: uniformity, HU constancy, spatial resolution, low contrast detection, noise level, and contrast-to-noise ratio. An anthropomorphic head phantom was scanned for verification of noise reduction. Clinical patient image data sets for 5 head/neck patients and 5 prostate patients were qualitatively evaluated. RESULTS: Quality assurance phantom study results showed that relative to filtered back-projection-based cone-beam computed tomography, noise was reduced from 28.8 ± 0.3 HU to a range between 18.3 ± 0.2 and 5.9 ± 0.2 HU for Full-Fan Head scans, from 14.4 ± 0.2 HU to a range between 12.8 ± 0.3 and 5.2 ± 0.3 HU for Half-Fan Head scans, and from 6.2 ± 0.1 HU to a range between 3.8 ± 0.1 and 2.0 ± 0.2 HU for Pelvis scans, with the iterative cone-beam computed tomography algorithm. Spatial resolution was marginally improved while results for uniformity and HU constancy were similar. For the head phantom study, noise was reduced from 43.6 HU to a range between 24.8 and 13.0 HU for a Full-Fan Head and from 35.1 HU to a range between 22.9 and 14.0 HU for a Half-Fan Head scan. The patient data study showed that artifacts due to photon starvation and streak artifacts were all reduced, and image noise in specified target regions were reduced to 62% ± 15% for 10 patients. CONCLUSION: Noise and contrast-to-noise ratio image quality characteristics were significantly improved using the iterative cone-beam computed tomography reconstruction algorithm relative to the filtered back-projection-based cone-beam computed tomography method. These improvements will enhance the accuracy of cone-beam computed tomography-based image-guided applications.

Evaluation of a magnetic resonance guided linear accelerator for stereotactic radiosurgery treatment.

INTRODUCTION: The purpose of this study was to investigate the systematic localization accuracy, treatment planning capability, and delivery accuracy of an integrated magnetic resonance imaging guided Linear Accelerator (MR-Linac) platform for stereotactic radiosurgery. MATERIALS AND METHODS: The phantom for the end-to-end test comprises three different compartments: a rectangular MR/CT target phantom, a Winston-Lutz cube, and a rectangular MR/CT isocenter phantom. Hidden target tests were performed at gantry angles of 0, 90, 180, and 270 degrees to quantify the systematic accuracy. Five patient plans with a total of eleven lesions were used to evaluate the dosimetric accuracy. Single-isocenter IMRT treatment plans using 10-15 coplanar beams were generated to treat the multiple metastases. RESULTS: The end-to-end localization accuracy of the system was 1.0 ±â€¯0.1 mm. The conformity index, homogeneity index and gradient index of the plans were 1.26 ±â€¯0.22, 1.22 ±â€¯0.10, and 5.38 ±â€¯1.44, respectively. The average absolute point dose difference between measured and calculated dose was 1.64 ±â€¯1.90%, and the mean percentage of points passing the 3%/1 mm gamma criteria was 96.87%. CONCLUSIONS: Our experience demonstrates that excellent plan quality and delivery accuracy was achievable on the MR-Linac for treating multiple brain metastases with a single isocenter.

An automated dose tracking system for adaptive radiation therapy.

BACKGROUND AND OBJECTIVE: The implementation of adaptive radiation therapy (ART) into routine clinical practice is technically challenging and requires significant resources to perform and validate each process step. The objective of this report is to identify the key components of ART, to illustrate how a specific automated procedure improves efficiency, and to facilitate the routine clinical application of ART. METHODS: Data was used from patient images, exported from a clinical database and converted to an intermediate format for point-wise dose tracking and accumulation. The process was automated using in-house developed software containing three modularized components: an ART engine, user interactive tools, and integration tools. The ART engine conducts computing tasks using the following modules: data importing, image pre-processing, dose mapping, dose accumulation, and reporting. In addition, custom graphical user interfaces (GUIs) were developed to allow user interaction with select processes such as deformable image registration (DIR). A commercial scripting application programming interface was used to incorporate automated dose calculation for application in routine treatment planning. Each module was considered an independent program, written in C++or C#, running in a distributed Windows environment, scheduled and monitored by integration tools. RESULTS: The automated tracking system was retrospectively evaluated for 20 patients with prostate cancer and 96 patients with head and neck cancer, under institutional review board (IRB) approval. In addition, the system was evaluated prospectively using 4 patients with head and neck cancer. Altogether 780 prostate dose fractions and 2586 head and neck cancer dose fractions went processed, including DIR and dose mapping. On average, daily cumulative dose was computed in 3 h and the manual work was limited to 13 min per case with approximately 10% of cases requiring an additional 10 min for image registration refinement. CONCLUSIONS: An efficient and convenient dose tracking system for ART in the clinical setting is presented. The software and automated processes were rigorously evaluated and validated using patient image datasets. Automation of the various procedures has improved efficiency significantly, allowing for the routine clinical application of ART for improving radiation therapy effectiveness.

Changes in pharyngeal constrictor volumes during head and neck radiation therapy: Implications for dose delivery.

OBJECTIVE: The objective of this study was to evaluate the anatomical changes and associated dosimetric consequences to pharyngeal constrictor muscles (PCMs) that occur during head and neck (H and N) radiotherapy (RT). MATERIALS AND METHODS: A cohort of 13 oropharyngeal cancer patients with daily cone beam computed tomography (CBCT) was retrospectively studied. On every 5th CBCT image, PCM was manually delineated by a radiation oncologist. The anterior-posterior PCM thickness was measured at the midline level of C3 vertebral body. Delivered dose to PCM was estimated by calculating dose on daily images and performing dose accumulation on corresponding planning CT images using a parameter-optimized B-spline-based deformable image registration algorithm. The mean and maximum delivered dose (Dmean, Dmax) to PCM were determined and compared with the corresponding planned quantities. RESULTS: The average (±standard deviation) volume increase (ΔV) and thickness increase (Δt) over the course of 35 total fractions were 54 ± 33% (11.9 ± 7.6 cc) and 63 ± 39% (2.9 ± 1.9 mm), respectively. The resultant cumulative mean dose increase from planned dose to PCM (ΔDmean) was 1.4 ± 1.3% (0.9 ± 0.8 Gy), while the maximum dose increase (ΔDmax) was 0.0 ± 1.6% (0.0 ± 1.1 Gy). Patients who underwent adaptive replanning (n = 6) showed a smaller mean dose increase than those without (n = 7); 0.5 ± 0.2% (0.3 ± 0.1 Gy) versus 2.2 ± 1.4% (1.4 ± 0.9 Gy). There were statistically significant (P = 0.001) strong correlations between ΔDmean and Δt (Pearson coefficient r = 0.78), as well as between ΔDmean and ΔV (r = 0.52). CONCLUSION: The patients underwent considerable anatomical changes to PCM during H and N RT. However, the resultant increase in dose to PCM was minor to moderate. PCM thickness measured at C3 level is a good predictor for the mean dose increase to PCM.

Use of regularized principal component analysis to model anatomical changes during head and neck radiation therapy for treatment adaptation and response assessment.

PURPOSE: To develop standard (SPCA) and regularized (RPCA) principal component analysis models of anatomical changes from daily cone beam CTs (CBCTs) of head and neck (H&N) patients and assess their potential use in adaptive radiation therapy, and for extracting quantitative information for treatment response assessment. METHODS: Planning CT images of ten H&N patients were artificially deformed to create "digital phantom" images, which modeled systematic anatomical changes during radiation therapy. Artificial deformations closely mirrored patients' actual deformations and were interpolated to generate 35 synthetic CBCTs, representing evolving anatomy over 35 fractions. Deformation vector fields (DVFs) were acquired between pCT and synthetic CBCTs (i.e., digital phantoms) and between pCT and clinical CBCTs. Patient-specific SPCA and RPCA models were built from these synthetic and clinical DVF sets. EigenDVFs (EDVFs) having the largest eigenvalues were hypothesized to capture the major anatomical deformations during treatment. RESULTS: Principal component analysis (PCA) models achieve variable results, depending on the size and location of anatomical change. Random changes prevent or degrade PCA's ability to detect underlying systematic change. RPCA is able to detect smaller systematic changes against the background of random fraction-to-fraction changes and is therefore more successful than SPCA at capturing systematic changes early in treatment. SPCA models were less successful at modeling systematic changes in clinical patient images, which contain a wider range of random motion than synthetic CBCTs, while the regularized approach was able to extract major modes of motion. CONCLUSIONS: Leading EDVFs from the both PCA approaches have the potential to capture systematic anatomical change during H&N radiotherapy when systematic changes are large enough with respect to random fraction-to-fraction changes. In all cases the RPCA approach appears to be more reliable at capturing systematic changes, enabling dosimetric consequences to be projected once trends are established early in a treatment course, or based on population models.

Target and organ dose estimation from intensity modulated head and neck radiation therapy using 3 deformable image registration algorithms.

PURPOSE: To estimate the delivered dose to targets and organs at risk for head and neck radiation therapy by accumulating the dose using 3 deformable image registration (DIR) algorithms. METHODS AND MATERIALS: Five head and neck patients, who had daily cone beam computed tomography (CT) images taken during the course of treatment, were retrospectively studied. To overcome the small field of view limitations and Hounsfield unit uncertainties of cone beam CT, a planning CT was deformably registered and resampled onto each cone beam CT image with a 4.2-cm uniform field of view expansion. The "dose of the day" was calculated on these resampled CT images, warped, and accumulated to the planning CT using 3 different DIR algorithms. Dosimetric indices for targets and organs at risk were determined from dose-volume histograms and compared with corresponding planned quantities. RESULTS: There were no significant differences among the cumulative dose-volume histograms estimated by the 3 DIR algorithms. The cumulative mean dose deviation was less than 2% from the corresponding plan dose in general for the planning and gross tumor volumes. However, the parotid gland mean dose showed a large variation, with a maximum 33% deviation. This was due in part to considerable patient weight loss during the first 3 weeks of treatment. The corresponding target and organ mean dose deviations ± standard deviation, estimated as an average of the 3 DIR algorithms, were 1.0 ± 1.6% for planning target volumes, 1.6 ± 2.3% for gross tumor volumes, 7.3 ± 9.6% for left parotid, 10.3 ± 11.9% for right parotid, and 3.3 ± 4.7% for mucosa. The target coverage deviation (dose to 95% of the volume) was -2.8 ± 1.8% for planning target volumes and 0.2 ± 2.8% for gross tumor volumes. The deviation of the maximum dose to the spinal cord was 2.1 ± 2.4%. CONCLUSIONS: Results of this study indicate that the estimated target dose generally remains within 2% of the intended dose for plans with a 5-mm planning margin. More frequent plan adaptation might be beneficial to avoid unintended excessive dose to parotid glands.

Deformable image registration based automatic CT-to-CT contour propagation for head and neck adaptive radiotherapy in the routine clinical setting.

PURPOSE: To evaluate the clinical potential of deformable image registration (DIR)-based automatic propagation of physician-drawn contours from a planning CT to midtreatment CT images for head and neck (H&N) adaptive radiotherapy. METHODS: Ten H&N patients, each with a planning CT (CT1) and a subsequent CT (CT2) taken approximately 3-4 week into treatment, were considered retrospectively. Clinically relevant organs and targets were manually delineated by a radiation oncologist on both sets of images. Four commercial DIR algorithms, two B-spline-based and two Demons-based, were used to deform CT1 and the relevant contour sets onto corresponding CT2 images. Agreement of the propagated contours with manually drawn contours on CT2 was visually rated by four radiation oncologists in a scale from 1 to 5, the volume overlap was quantified using Dice coefficients, and a distance analysis was done using center of mass (CoM) displacements and Hausdorff distances (HDs). Performance of these four commercial algorithms was validated using a parameter-optimized Elastix DIR algorithm. RESULTS: All algorithms attained Dice coefficients of >0.85 for organs with clear boundaries and those with volumes >9 cm(3). Organs with volumes <3 cm(3) and/or those with poorly defined boundaries showed Dice coefficients of ∼ 0.5-0.6. For the propagation of small organs (<3 cm(3)), the B-spline-based algorithms showed higher mean Dice values (Dice = 0.60) than the Demons-based algorithms (Dice = 0.54). For the gross and planning target volumes, the respective mean Dice coefficients were 0.8 and 0.9. There was no statistically significant difference in the Dice coefficients, CoM, or HD among investigated DIR algorithms. The mean radiation oncologist visual scores of the four algorithms ranged from 3.2 to 3.8, which indicated that the quality of transferred contours was "clinically acceptable with minor modification or major modification in a small number of contours." CONCLUSIONS: Use of DIR-based contour propagation in the routine clinical setting is expected to increase the efficiency of H&N replanning, reducing the amount of time needed for manual target and organ delineations.

An assessment of PTV margin based on actual accumulated dose for prostate cancer radiotherapy.

The purpose of this work is to present the results of a margin reduction study involving dosimetric and radiobiologic assessment of cumulative dose distributions, computed using an image guided adaptive radiotherapy based framework. Eight prostate cancer patients, treated with 7-9, 6 MV, intensity modulated radiation therapy (IMRT) fields, were included in this study. The workflow consists of cone beam CT (CBCT) based localization, deformable image registration of the CBCT to simulation CT image datasets (SIM-CT), dose reconstruction and dose accumulation on the SIM-CT, and plan evaluation using radiobiological models. For each patient, three IMRT plans were generated with different margins applied to the CTV. The PTV margin for the original plan was 10 mm and 6 mm at the prostate/anterior rectal wall interface (10/6 mm) and was reduced to: (a) 5/3 mm, and (b) 3 mm uniformly. The average percent reductions in predicted tumor control probability (TCP) in the accumulated (actual) plans in comparison to the original plans over eight patients were 0.4%, 0.7% and 11.0% with 10/6 mm, 5/3 mm and 3 mm uniform margin respectively. The mean increase in predicted normal tissue complication probability (NTCP) for grades 2/3 rectal bleeding for the actual plans in comparison to the static plans with margins of 10/6, 5/3 and 3 mm uniformly was 3.5%, 2.8% and 2.4% respectively. For the actual dose distributions, predicted NTCP for late rectal bleeding was reduced by 3.6% on average when the margin was reduced from 10/6 mm to 5/3 mm, and further reduced by 1.0% on average when the margin was reduced to 3 mm. The average reduction in complication free tumor control probability (P+) in the actual plans in comparison to the original plans with margins of 10/6, 5/3 and 3 mm was 3.7%, 2.4% and 13.6% correspondingly. The significant reduction of TCP and P+ in the actual plan with 3 mm margin came from one outlier, where individualizing patient treatment plans through margin adaptation based on biological models, might yield higher quality treatments.