Toward adaptive radiotherapy for head and neck patients: Feasibility study on using CT-to-CBCT deformable registration for "dose of the day" calculations

Skin dose calculation during radiotherapy of head and neck cancer using deformable image registration of planning and mega-voltage computed tomography scans

Background and Purpose

Head-Neck (HN) patients may experience severe acute skin complications that can cause treatment interruption and increase the risk of late fibrosis. This study assessed a method for accurately monitoring skin dose changes during helical tomotherapy for HN cancer based on deformable image registration of planning computed tomography (CT) and mega-voltage CT (MVCT).

Materials and Methods

Planning CTs of nine patients were deformably registered to mid-treatment MVCT (MV15) images resulting in CTdef images. The original plans were recalculated on both CTdef and mid-treatment kilo-voltage CT (CT15) taken as ground truth. Superficial layers (SL) of the body with thicknesses of 2, 3 and 5 mm (SL2, SL3, SL5) were considered as derma surrogates. SL V95%, V97%, V98%, V100%, V102%, V105% and V107% of the prescribed PTV dose were extracted for CT15/CTdef and compared (considering patients with skin dose > 95%). For comparison, doses were calculated directly on the calibrated MVCT and analyzed in the same way.

Results

Differences between SL2/SL3/SL5 V95%-V107% in CT15/CTdef were very small: for eight of nine patients the difference between the considered SL2 Vd% computed on CTdef and CT15 was less than 1.4 cm³ for all d%. A larger value was found when using MVCT for skin dose calculation (4.8 cm³ for SL2), although CTdef body contour matched CT15 body with accuracy similar to that of MV15.

Conclusions

Deforming the planning CT-to-MVCT was shown to be accurate considering external body contours and skin DVHs. The method was able to accurately identify superficial overdosing.

Online daily assessment of dose change in head and neck radiotherapy without dose-recalculation

BACKGROUND

Head and neck cancers are commonly treated with radiation therapy, but due to possible volume changes, plan adaptation may be required during the course of treatment. Currently, plan adaptations consume significant clinical resources. Existing methods to evaluate the need for plan adaptation requires deformable image registration (DIR) to a new CT simulation or daily cone beam CT (CBCT) images and the recalculation of the dose distribution. In this study, we explore a tool to assist the decision for plan adaptation using a CBCT without re-computation of dose, allowing for rapid online assessment.

METHODS

This study involved 18 head and neck cancer patients treated with CBCT image guidance who had their treatment plan modified based on a new CT simulation (ReCT). Dose changes were estimated using different methods and compared to the current gold standard of using DIR between the planning CT scan (PCT) and ReCT with recomputed dose. The first and second methods used DIR between the PCT and daily CBCT with the planned dose or recalculated dose from the ReCT respectively, with the dose transferred to the CBCT using rigid registration. The necessity of plan adaptation was assessed by the change in dose to 95% of the planning target volume (D95) and mean dose to the parotids.

RESULTS

The treatment plans were adapted clinically for all 18 patients but only 7 actually needed an adaptation yielding 11 unnecessary adaptations. Applying a method using the daily CBCT with the planned dose distribution would have yielded only four unnecessary adaptations and no missed adaptations: a significant improvement from that done clinically.

CONCLUSION

Using the DIR between the planning CT and daily CBCT can flag cases for plan adaptation before every fraction while not requiring a new re-planning CT scan and dose recalculation.

Toward adaptive radiotherapy for lung patients: feasibility study on deforming planning CT to CBCT to assess the impact of anatomical changes on dosimetry

Changes in lung architecture during a course of radiotherapy can alter the planned dose distribution to the extent that it becomes clinically unacceptable. This study aims to validate a quantitative method of determining whether a replan is required during the course of conformal radiotherapy. The proposed method uses deformable image registration (DIR) to flexibly map planning CT (pCT) data to the anatomy of online CBCT images. The resulting deformed CT (dCT) images are used as a basis for assessing the effect of anatomical change on dose distributions. The study used retrospective data from a sample of seven replanned lung patients. The settings of an in-house, open-source DIR algorithm were first optimised for CT-to-CBCT registrations of the anatomy of the thorax. Using these optimised parameters, each patient's pCT was deformed to the CBCT acquired immediately before the replan. Registration accuracy was rigorously validated both geometrically and dosimetrically to confirm that the dCTs could reliably be used to inform replan decisions. A retrospective evaluation of the changes in dose delivered over time was then carried out for a single patient to demonstrate the clinical application of the proposed method. The geometric analysis showed good agreement between deformed structures and those same structures manually outlined on the CBCT images. Results were consistently better than those achieved with rigid-only registration. In the dosimetric analysis, dose distributions derived from the dCTs were found to match closely to the 'gold standard' replan CT (rCT) distributions across dose volume histogram and absolute dose difference measures. The retrospective analysis of serial CBCTs of a single patient produced reliable quantitative assessment of the dose delivery. Had the proposed method been available at the time of treatment, it would have enabled a more objective replan decision. DIR is a valuable clinical tool for dose recalculation in adaptive radiotherapy protocols for lung cancer patients.

Prospective in silico study of the feasibility and dosimetric advantages of MRI-guided dose adaptation for human papillomavirus positive oropharyngeal cancer patients compared with standard IMRT

PURPOSE

We aim to determine the feasibility and dosimetric benefits of a novel MRI-guided IMRT dose-adaption strategy for human papillomavirus positive (HPV+) oropharyngeal squamous cell carcinoma (OPC).

MATERIALS/METHODS

Patients with locally advanced HPV+ OPC underwent pre-treatment and in-treatment MRIs every two weeks using RT immobilization setup. For each patient, two IMRT plans were created (i.e. standard and adaptive). The prescription dose for the standard plans was 2.12 Gy/fx for 33 fractions to the initial PTV. For adaptive plans, a new PTVadaptive was generated based on serial MRIs in case of detectable tumor shrinkage. Prescription dose to PTVadaptive was 2.12 Gy/fx to allow for maximum dose to the residual disease. Any previously involved volumes received minimally a floor dose of 50.16 Gy. Uninvolved elective nodal volumes were prescribed 50.16 Gy in 1.52 Gy/fx. Dosimetric parameters of organs at risk (OARs) were recorded for standard vs. adaptive plans. Normal tissue complication probability (NTCP) for toxicity endpoints was calculated using literature-derived multivariate logistic regression models.

RESULTS

Five patients were included in this pilot study, 3 men and 2 women. Median age was 58 years (range 45-69). Three tumors originated at the tonsillar fossa and two at the base of tongue. The average dose to 95% of initial PTV volume was 70.7 Gy (SD,0.3) for standard plans vs. 58.5 Gy (SD,2.0) for adaptive plans. The majority of OARs showed decrease in dosimetric parameters using adaptive plans vs. standard plans, particularly swallowing related structures. The average reduction in the probability of developing dysphagia ≥ grade2, feeding tube persistence at 6-month post-treatment and hypothyroidism at 1-year post-treatment was 11%, 4%, and 5%, respectively. The probability of xerostomia at 6-month was only reduced by 1% for adaptive plans vs. standard IMRT.

CONCLUSION

These in silico results showed that the proposed MRI-guided adaptive approach is technically feasible and advantageous in reducing dose to OARs, especially swallowing musculature.

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.

Accuracy of radiotherapy dose calculations based on cone-beam CT: comparison of deformable registration and image correction based methods

Radiotherapy dose calculations based on cone-beam CT (CBCT) images can be inaccurate due to unreliable Hounsfield units (HU) in the CBCT. Deformable image registration of planning CT images to CBCT, and direct correction of CBCT image values are two methods proposed to allow heterogeneity corrected dose calculations based on CBCT. In this paper we compare the accuracy and robustness of these two approaches. CBCT images for 44 patients were used including pelvis, lung and head & neck sites. CBCT HU were corrected using a 'shading correction' algorithm and via deformable registration of planning CT to CBCT using either Elastix or Niftyreg. Radiotherapy dose distributions were re-calculated with heterogeneity correction based on the corrected CBCT and several relevant dose metrics for target and OAR volumes were calculated. Accuracy of CBCT based dose metrics was determined using an 'override ratio' method where the ratio of the dose metric to that calculated on a bulk-density assigned version of the same image is assumed to be constant for each patient, allowing comparison to the patient's planning CT as a gold standard. Similar performance is achieved by shading corrected CBCT and both deformable registration algorithms, with mean and standard deviation of dose metric error less than 1% for all sites studied. For lung images, use of deformed CT leads to slightly larger standard deviation of dose metric error than shading corrected CBCT with more dose metric errors greater than 2% observed (7% versus 1%).

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

Purpose

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

Methods

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

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

Results

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

Conclusions

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

An automated, quantitative, and case-specific evaluation of deformable image registration in computed tomography images

A prerequisite for adaptive dose-tracking in radiotherapy is the assessment of the deformable image registration (DIR) quality. In this work, various metrics that quantify DIR uncertainties are investigated using realistic deformation fields of 26 head and neck and 12 lung cancer patients. Metrics related to the physiologically feasibility (the Jacobian determinant, harmonic energy (HE), and octahedral shear strain (OSS)) and numerically robustness of the deformation (the inverse consistency error (ICE), transitivity error (TE), and distance discordance metric (DDM)) were investigated. The deformable registrations were performed using a B-spline transformation model. The DIR error metrics were log-transformed and correlated (Pearson) against the log-transformed ground-truth error on a voxel level. Correlations of r  ⩾  0.5 were found for the DDM and HE. Given a DIR tolerance threshold of 2.0 mm and a negative predictive value of 0.90, the DDM and HE thresholds were 0.49 mm and 0.014, respectively. In conclusion, the log-transformed DDM and HE can be used to identify voxels at risk for large DIR errors with a large negative predictive value. The HE and/or DDM can therefore be used to perform automated quality assurance of each CT-based DIR for head and neck and lung cancer patients.

Technical Note: The impact of deformable image registration methods on dose warping

PURPOSE

The purpose of this study was to investigate the clinical-relevant discrepancy between doses warped by pure image based deformable image registration (IM-DIR) and by biomechanical model based DIR (BM-DIR) on intensity-homogeneous organs.

METHODS AND MATERIALS

Ten patients (5Head&Neck, 5Prostate) were included. A research DIR tool (ADMRIE_v1.12) was utilized for IM-DIR. After IM-DIR, BM-DIR was carried out for organs (parotids, bladder, and rectum) which often encompass sharp dose gradient. Briefly, high-quality tetrahedron meshes were generated and deformable vector fields (DVF) from IM-DIR were interpolated to the surface nodes of the volume meshes as boundary condition. Then, a FEM solver (ABAQUS_v6.14) was used to simulate the displacement of internal nodes, which were then interpolated to image-voxel grids to get the more physically plausible DVF. Both geometrical and subsequent dose warping discrepancies were quantified between the two DIR methods. Target registration discrepancy(TRD) was evaluated to show the geometry difference. The re-calculated doses on second CT were warped to the pre-treatment CT via two DIR. Clinical-relevant dose parameters and γ passing rate were compared between two types of warped dose. The correlation was evaluated between parotid shrinkage and TRD/dose discrepancy.

RESULT

The parotid shrunk to 75.7% ± 9% of its pre-treatment volume and the percentage of volume with TRD>1.5 mm) was 6.5% ± 4.7%. The normalized mean-dose difference (NMDD) of IM-DIR and BM-DIR was -0.8% ± 1.5%, with range (-4.7% to 1.5%). 2 mm/2% passing rate was 99.0% ± 1.4%. A moderate correlation was found between parotid shrinkage and TRD and NMDD. The bladder had a NMDD of -9.9% ± 9.7%, with BM-DIR warped dose systematically higher. Only minor deviation was observed for rectum NMDD (0.5% ± 1.1%).

CONCLUSION

Impact of DIR method on treatment dose warping is patient and organ-specific. Generally, intensity-homogeneous organs, which undergo larger deformation/shrinkage during treatment and encompass sharp dose gradient, will have greater dose warping uncertainty. For these organs, BM-DIR could be beneficial to the evaluation of DIR/dose-warping uncertainty.

Intensity-Modulated Proton Therapy Adaptive Planning for Patients with Oropharyngeal Cancer

Purpose

The authors aimed to illustrate the potential dose differences to clinical target volumes (CTVs) and organs-at-risk (OARs) volumes after proton adaptive treatment planning was used.

Patients and Methods

The records of 10 patients with oropharyngeal cancer were retrospectively reviewed. Each patient's treatment plan was generated by using the Eclipse treatment planning system. Verification computed tomography (CT) scan was performed during the fourth week of treatment. Deformable image registrations were performed between the 2 CT image sets, and the CTVs and major OARs were transferred to the verification CT images to generate the adaptive plan. We compared the accumulated doses to CTVs and OARs between the original and adaptive plans, as well as between the adaptive and verification plans to simulate doses that would have been delivered if the adaptive plans were not used.

Results

Body contours were different on planning and week-4 verification CTs. Mean volumes of all CTVs were reduced by 4% to 8% (P ≤ .04), and the volumes of left and right parotid glands also decreased (by 11% to 12%, P ≤ .004). Brainstem and oral cavity volumes did not significantly differ (all P ≥ .14). All mean doses to the CTV were decreased for up to 7% (P ≤ .04), whereas mean doses to the right parotid and oral cavity increased from a range of 5% to 8% (P ≤ .03), respectively.

Conclusion

Verification and adaptive planning should be recommended during the course of proton therapy for patients with head and neck cancer to ensure adequate dose deliveries to the planned CTVs, while safe doses to OARs can be respected.

Validating Dose Uncertainty Estimates Produced by AUTODIRECT: An Automated Program to Evaluate Deformable Image Registration Accuracy

Deformable image registration is a powerful tool for mapping information, such as radiation therapy dose calculations, from one computed tomography image to another. However, deformable image registration is susceptible to mapping errors. Recently, an automated deformable image registration evaluation of confidence tool was proposed to predict voxel-specific deformable image registration dose mapping errors on a patient-by-patient basis. The purpose of this work is to conduct an extensive analysis of automated deformable image registration evaluation of confidence tool to show its effectiveness in estimating dose mapping errors. The proposed format of automated deformable image registration evaluation of confidence tool utilizes 4 simulated patient deformations (3 B-spline-based deformations and 1 rigid transformation) to predict the uncertainty in a deformable image registration algorithm's performance. This workflow is validated for 2 DIR algorithms (B-spline multipass from Velocity and Plastimatch) with 1 physical and 11 virtual phantoms, which have known ground-truth deformations, and with 3 pairs of real patient lung images, which have several hundred identified landmarks. The true dose mapping error distributions closely followed the Student t distributions predicted by automated deformable image registration evaluation of confidence tool for the validation tests: on average, the automated deformable image registration evaluation of confidence tool-produced confidence levels of 50%, 68%, and 95% contained 48.8%, 66.3%, and 93.8% and 50.1%, 67.6%, and 93.8% of the actual errors from Velocity and Plastimatch, respectively. Despite the sparsity of landmark points, the observed error distribution from the 3 lung patient data sets also followed the expected error distribution. The dose error distributions from automated deformable image registration evaluation of confidence tool also demonstrate good resemblance to the true dose error distributions. Automated deformable image registration evaluation of confidence tool was also found to produce accurate confidence intervals for the dose-volume histograms of the deformed dose.

Prognostic factors associated with the accuracy of deformable image registration in lung cancer patients treated with stereotactic body radiotherapy

We evaluated the accuracy of an in-house program in lung stereotactic body radiation therapy (SBRT) cancer patients, and explored the prognostic factors associated with the accuracy of deformable image registrations (DIRs). The accuracy of the 3 programs which implement the free-form deformation and the B-spline algorithm was compared regarding the structures on 4-dimensional computed tomography (4DCT) image datasets between the peak-inhale and peak-exhale phases. The dice similarity coefficient (DSC) and normalized DSC (NDSC) were measured for the gross tumor volumes from 19 lung SBRT patients. We evaluated the accuracy of DIR using gross tumor volume, magnitude of displacement from 0% phase to 50% phase, whole lung volume in the 50% phase image, and status of tumor pleural attachment. The median NDSC values using the NiftyReg, MIM Maestro and Velocity AI programs were 1.027, 1.005, and 0.946, respectively, indicating that NiftyReg and MIM Maestro programs had similar accuracy with an uncertainty of < 1 mm. Larger uncertainty of 1 to 2 mm was observed using the Velocity AI program. The NiftyReg and the MIM programs provided higher NDSC values than the median values when the gross tumor volume was attached to the pleura (p <0.05). However, it showed a different trend in using the Velocity AI program. All software programs provided unexpected results, and there is a possibility that such results would reduce the accuracy of 4D treatment planning and adaptive radiotherapy. The unexpected results may be because the tumors are surrounded by other tissues, and there are differences regarding the region of interest for rigid and nonrigid registration. Furthermore, our results indicated that the pleural attachment status might be an important predictor of DIR accuracy for thoracic images, indicating that there is a potentially large dose distribution discrepancy concerning 4D treatment planning and adaptive radiotherapy.

Study of Variation in Dose Calculation Accuracy Between kV Cone-Beam Computed Tomography and kV fan-Beam Computed Tomography

Cone-beam computed tomography (CBCT) images are presently used for geometric verification for daily patient positioning. In this work, we have compared the images of CBCT with the images of conventional fan beam CT (FBCT) in terms of image quality and Hounsfield units (HUs). We also compared the dose calculated using CBCT with that of FBCT. Homogenous RW3 plates and Catphan phantom were scanned by FBCT and CBCT. In RW3 and Catphan phantom, percentage depth dose (PDD), profiles, isodose distributions (for intensity modulated radiotherapy plans), and calculated dose volume histograms were compared. The HU difference was within ± 20 HU (central region) and ± 30 HU (peripheral region) for homogeneous RW3 plates. In the Catphan phantom, the difference in HU was ± 20 HU in the central area and peripheral areas. The HU differences were within ± 30 HU for all HU ranges starting from -1000 to 990 in phantom and patient images. In treatment plans done with simple symmetric and asymmetric fields, dose difference (DD) between CBCT plan and FBCT plan was within 1.2% for both phantoms. In intensity modulated radiotherapy (IMRT) treatment plans, for different target volumes, the difference was <2%. This feasibility study investigated HU variation and dose calculation accuracy between FBCT and CBCT based planning and has validated inverse planning algorithms with CBCT. In our study, we observed a larger deviation of HU values in the peripheral region compared to the central region. This is due to the ring artifact and scatter contribution which may prevent the use of CBCT as the primary imaging modality for radiotherapy treatment planning. The reconstruction algorithm needs to be modified further for improving the image quality and accuracy in HU values. However, our study with TG-119 and intensity modulated radiotherapy test targets shows that CBCT can be used for adaptive replanning as the recalculation of dose with the anisotropic analytical algorithm is in full accord with conventional planning CT except in the build-up regions. Patient images with CBCT have to be carefully analyzed for any artifacts before using them for such dose calculations.

Evaluation of deformable image registration for contour propagation between CT and cone-beam CT images in adaptive head and neck radiotherapy

Deformable image registration (DIR) is a critical technic in adaptive radiotherapy (ART) to propagate contours between planning computerized tomography (CT) images and treatment CT/Cone-beam CT (CBCT) image to account for organ deformation for treatment re-planning. To validate the ability and accuracy of DIR algorithms in organ at risk (OAR) contours mapping, seven intensity-based DIR strategies are tested on the planning CT and weekly CBCT images from six Head & Neck cancer patients who underwent a 6 ∼ 7 weeks intensity-modulated radiation therapy (IMRT). Three similarity metrics, i.e. the Dice similarity coefficient (DSC), the percentage error (PE) and the Hausdorff distance (HD), are employed to measure the agreement between the propagated contours and the physician delineated ground truths. It is found that the performance of all the evaluated DIR algorithms declines as the treatment proceeds. No statistically significant performance difference is observed between different DIR algorithms (p> 0.05), except for the double force demons (DFD) which yields the worst result in terms of DSC and PE. For the metric HD, all the DIR algorithms behaved unsatisfactorily with no statistically significant performance difference (p= 0.273). These findings suggested that special care should be taken when utilizing the intensity-based DIR algorithms involved in this study to deform OAR contours between CT and CBCT, especially for those organs with low contrast.

Dosimetric advantages of a clinical daily adaptive plan selection strategy compared with a non-adaptive strategy in cervical cancer radiation therapy

BACKGROUND

Radiation therapy (RT) using a daily plan selection adaptive strategy can be applied to account for interfraction organ motion while limiting organ at risk dose. The aim of this study was to quantify the dosimetric consequences of daily plan selection compared with non-adaptive RT in cervical cancer.

MATERIAL AND METHODS

Ten consecutive patients who received pelvic irradiation, planning CTs (full and empty bladder), weekly post-fraction CTs and pre-fraction CBCTs were included. Non-adaptive plans were generated based on the PTV defined using the full bladder planning CT. For the adaptive strategy, multiple PTVs were created based on both planning CTs by ITVs of the primary CTVs (i.e., GTV, cervix, corpus-uterus and upper part of the vagina) and corresponding library plans were generated. Daily CBCTs were rigidly aligned to the full bladder planning CT for plan selection. For daily plan recalculation, selected CTs based on initial similarity were deformably registered to CBCTs. Differences in daily target coverage (D_98% > 95%) and in V_0.5Gy, V_1.5Gy, V_2Gy, D_50% and D_2% for rectum, bladder and bowel were assessed.

RESULTS

Non-adaptive RT showed inadequate primary CTV coverage in 17% of the daily fractions. Plan selection compensated for anatomical changes and improved primary CTV coverage significantly (p < 0.01) to 98%. Compared with non-adaptive RT, plan selection decreased the fraction dose to rectum and bowel indicated by significant (p < 0.01) improvements for daily V_0.5Gy, V_1.5Gy, V_2Gy, D_50% and D_2%. However, daily plan selection significantly increased the bladder V_1.5Gy, V_2Gy, D_50% and D_2%.

CONCLUSIONS

In cervical cancer RT, a non-adaptive strategy led to inadequate target coverage for individual patients. Daily plan selection corrected for day-to-day anatomical variations and resulted in adequate target coverage in all fractions. The dose to bowel and rectum was decreased significantly when applying adaptive RT.

Comprehensive evaluation of ten deformable image registration algorithms for contour propagation between CT and cone-beam CT images in adaptive head & neck radiotherapy

Deformable image registration (DIR) is a critical technic in adaptive radiotherapy (ART) for propagating contours between planning computerized tomography (CT) images and treatment CT/cone-beam CT (CBCT) images to account for organ deformation for treatment re-planning. To validate the ability and accuracy of DIR algorithms in organ at risk (OAR) contour mapping, ten intensity-based DIR strategies, which were classified into four categories—optical flow-based, demons-based, level-set-based and spline-based—were tested on planning CT and fractional CBCT images acquired from twenty-one head & neck (H&N) cancer patients who underwent 6~7-week intensity-modulated radiation therapy (IMRT). Three similarity metrics, i.e., the Dice similarity coefficient (DSC), the percentage error (PE) and the Hausdorff distance (HD), were employed to measure the agreement between the propagated contours and the physician-delineated ground truths of four OARs, including the vertebra (VTB), the vertebral foramen (VF), the parotid gland (PG) and the submandibular gland (SMG). It was found that the evaluated DIRs in this work did not necessarily outperform rigid registration. DIR performed better for bony structures than soft-tissue organs, and the DIR performance tended to vary for different ROIs with different degrees of deformation as the treatment proceeded. Generally, the optical flow-based DIR performed best, while the demons-based DIR usually ranked last except for a modified demons-based DISC used for CT-CBCT DIR. These experimental results suggest that the choice of a specific DIR algorithm depends on the image modality, anatomic site, magnitude of deformation and application. Therefore, careful examinations and modifications are required before accepting the auto-propagated contours, especially for automatic re-planning ART systems.

Dual-energy imaging method to improve the image quality and the accuracy of dose calculation for cone-beam computed tomography

PURPOSE

To improve the image quality and accuracy of dose calculation for cone-beam computed tomography (CT) images through implementation of a dual-energy cone-beam computed tomography method (DE-CBCT), and evaluate the improvement quantitatively.

METHODS

Two sets of CBCT projections were acquired using the X-ray volumetric imaging (XVI) system on a Synergy (Elekta, Stockholm, Sweden) system with 120kV (high) and 70kV (low) X-rays, respectively. Then, the electron density relative to water (relative electron density (RED)) of each voxel was calculated using a projection-based dual-energy decomposition method. As a comparison, single-energy cone-beam computed tomography (SE-CBCT) was used to calculate RED with the Hounsfield unit-RED calibration curve generated by a CIRS phantom scan with identical imaging parameters. The imaging dose was measured with a dosimetry phantom. The image quality was evaluated quantitatively using a Catphan 503 phantom with the evaluation indices of the reproducibility of the RED values, high-contrast resolution (MTF_50%), uniformity, and signal-to-noise ratio (SNR). Dose calculation of two simulated volumetric-modulated arc therapy plans using an Eclipse treatment-planning system (Varian Medical Systems, Palo Alto, CA, USA) was performed on an Alderson Rando Head and Neck (H&N) phantom and a Pelvis phantom. Fan-beam planning CT images for the H&N and Pelvis phantom were set as the reference. A global three-dimensional gamma analysis was used to compare dose distributions with the reference. The average gamma values for targets and OAR were analyzed with paired t-tests between DE-CBCT and SE-CBCT.

RESULTS

In two scans (H&N scan and body scan), the imaging dose of DE-CBCT increased by 1.0% and decreased by 1.3%. It had a better reproducibility of the RED values (mean bias: 0.03 and 0.07) compared with SE-CBCT (mean bias: 0.13 and 0.16). It also improved the image uniformity (57.5% and 30.1%) and SNR (9.7% and 2.3%), but did not affect the MTF_50%. Gamma analyses of the 3D dose distribution with criteria of 1%/1mm showed a pass rate of 99.0-100% and 85.3-97.6% for DE-CBCT and 73.5-99.1% and 80.4-92.7% for SE-CBCT. The average gamma values were reduced significantly by DE-CBCT (p< 0.05). Gamma index maps showed that matching of the dose distribution between CBCT-based and reference was improved by DE-CBCT.

CONCLUSIONS

DE-CBCT can achieve both better image quality and higher accuracy of dose calculation, and could be applied to adaptive radiotherapy.

Comparing the dosimetric impact of interfractional anatomical changes in photon, proton and carbon ion radiotherapy for pancreatic cancer patients

Radiotherapy using charged particles is characterized by a low dose to the surrounding healthy organs, while delivering a high dose to the tumor. However, interfractional anatomical changes can greatly affect the robustness of particle therapy. Therefore, we compared the dosimetric impact of interfractional anatomical changes (i.e. body contour differences and gastrointestinal gas volume changes) in photon, proton and carbon ion therapy for pancreatic cancer patients. In this retrospective planning study, photon, proton and carbon ion treatment plans were created for 9 patients. Fraction dose calculations were performed using daily cone-beam CT (CBCT) images. To this end, the planning CT was deformably registered to each CBCT; gastrointestinal gas volumes were delineated on the CBCTs and copied to the deformed CT. Fraction doses were accumulated rigidly. To compare planned and accumulated dose, dose-volume histogram (DVH) parameters of the planned and accumulated dose of the different radiotherapy modalities were determined for the internal gross tumor volume, internal clinical target volume (iCTV) and organs-at-risk (OARs; duodenum, stomach, kidneys, liver and spinal cord). Photon plans were highly robust against interfractional anatomical changes. The difference between the planned and accumulated DVH parameters for the photon plans was less than 0.5% for the target and OARs. In both proton and carbon ion therapy, however, coverage of the iCTV was considerably reduced for the accumulated dose compared with the planned dose. The near-minimum dose ([Formula: see text]) of the iCTV reduced with 8% for proton therapy and with 10% for carbon ion therapy. The DVH parameters of the OARs differed less than 3% for both particle modalities. Fractionated radiotherapy using photons is highly robust against interfractional anatomical changes. In proton and carbon ion therapy, such changes can severely reduce the dose coverage of the target.

Feasibility of offline head & neck adaptive radiotherapy using deformed planning CT electron density mapping on weekly cone beam computed tomography

OBJECTIVE

The purpose of the study was to use deformable mapping of planning CT (pCT) electron density values on weekly cone-beam CT (CBCT) to quantify the anatomical changes and determine the dose-volume relationship in offline adaptive volumetric-modulated arc therapy.

METHODS

10 patients treated with RapidArc plans who had weekly CBCTs were selected retrospectively. The pCT was deformed to weekly CBCTs and the deformed contours were checked for any discrepancies. Clinical target volume 66 Gy and 60 Gy (CTV₆₆ and CTV₆₀), parotids and spinal cord were the structures selected for analysis. Volume reduction and dice similarity index (DSI) were determined. Hybrid RapidArc plans were created and the cumulative dose-volume histograms for selected structures were analyzed.

RESULTS

Results showed a mean volume reduction of 18.82 ± 6.08% and 18.22 ± 6.1% for Clinical target volume 66 Gy and 60 Gy (CTV₆₆ and CTV₆₀), respectively, and their corresponding DSI values were 0.94 ± 0.03 and 0.95 ± 0.01. Mean volume reductions of left and right parotids were 32.79 ± 10.28% and 29.46 ± 8.78%, respectively, and their corresponding mean DSI values were 0.90 ± 0.05 and 0.89 ± 0.05. The cumulative mean dose difference for Planning target volume 66 Gy (PTV₆₆) was -1.35 ± 1.71% and for Planning target volume 60 Gy (PTV₆₀), it was -0.69 ± 1.37%. Spinal cord doses varied for all patients over the course.

CONCLUSION

The results from the study showed that it is clinically feasible to estimate the dose-volume relationship using deformed pCT. Monitoring of patient anatomic changes and incorporating patient-specific replanning strategy are necessary to avoid critical structure complications. Advances in knowledge: Deformable mapping of pCT electron density values on weekly CBCTs has been performed to establish the volumetric and dosimetric changes. The anatomical changes differ among the patients and hence, the choice for adaptive radiotherapy should be strictly patient specific rather than time specific.

Roles of Deformable Image Registration in adaptive RT: From contour propagation to dose monitoring

Adaptive radiation therapy (ART) is based on the optimization of the treatment plan during the treatment delivery to compensate for anatomical deformations. Deformable Image Registration (DIR) then constitutes a key step in order to analyze the huge amount of daily or weekly images to provide clinically usefull information. Two main applications of DIR have been developped in ART: delineation propagation and dose accumulation. If delineation propagation is well validated and transfered in the clinic, some challenges remain to address for dose accumulation. In this paper, we review the recent developments of DIR in ART, particularly in prostate and head-and-neck (H&N), with a focus on their evaluation.

Weekly response assessment of involved lymph nodes to radiotherapy using diffusion-weighted MRI in oropharynx squamous cell carcinoma

Purpose:

Patients with cancers of oropharynx have a favorable prognosis and are an ideal candidate for adaptive therapy. A replan to improve coverage or escalate/de-escalate dose based on morphological information alone may not be adequate as the grossly involved lymph nodes (LNs) of a subset of these patients tend to become cystic and often do not regress. Functional adaptation may be a better approach when considering replanning for these patients. The purpose of this study was to evaluate the weekly trends in treatment related morphological and physiological changes for these LNs using diffusion-weighted MRI (DW-MRI) and evaluate its implications for adaptive replanning.

Methods:

Ten patients with histologically proven oropharynx HNSCC undergoing concurrent chemoradiation were analyzed in this study. MR imaging protocol included axial T1w, T2w, and DW-MRI using a 3 T Philips MR scanner. The patients were scanned weekly in radiation treatment planning position using a 16 element phased-array anterior coil and a 44 element posterior coil. A total of 65 DWI and T2w scans were analyzed. DWI was performed using an optimized single-shot echo planar imaging sequence (TR/TE = 5000/65 ms, slice thickness = 5 mm; slices = 28; b values = 0 and 800 s/mm²). Quantification of the DW-MRI images was performed by calculating the apparent diffusion coefficient (ADC). T2w and DWI scans were imported into the Eclipse treatment planning system and gross tumor volumes (GTVs) corresponding to grossly involved LNs were contoured on each axial slice by physician experts. An attempt was made to remove any cystic or necrotic components so that the ADC analysis was of viable tumor only. A pixel-by-pixel fit of signal intensities within the GTVs was performed assuming monoexponential behavior. From each GTV histogram mean, median, standard deviation, skewness, and kurtosis were calculated. Absolute and percent change in weekly ADC histogram parameters and percent change in T2w GTV were also calculated.

Results:

For all nodes, an immediate change in ADC was observed during first 2–3 weeks after which ADC values either continued to increase or plateaued. A few nodal volumes had a slightly decreased ADC value during later weeks. Percent increase in median ADC from weeks 1 to 6 with respect to baseline was 14%, 25%, 41%, 42%, 45%, and 58%. The corresponding change in median T2 volumes was 8%, 10%, 16%, 22%, 40%, and 42%, respectively. The ADC distribution of the viable tumors was initially highly kurtotic; however, the kurtosis decreased as treatment progressed. The ADC distribution also showed a higher degree of skewness in the first 2 weeks, progressively becoming less skewed as treatment progressed so as to slowly approach a more symmetric distribution.

Conclusions:

Physiological changes in LNs represented by changes in ADC evaluated using DW-MRI are evident sooner than the morphological changes calculated from T2w MRI. The decisions for adaptive replanning may need to be individualized and should be based primarily on tumor functional information. The authors’ data also suggest that for many patients, week 3 maybe the optimal time to intervene and replan. Larger studies are needed to confirm their findings.

Quantitative body mass characterization before and after head and neck cancer radiotherapy: A challenge of height-weight formulae using computed tomography measurement

OBJECTIVES

We undertook a challenge to determine if one or more height-weight formula(e) can be clinically used as a surrogate for direct CT-based imaging assessment of body composition before and after radiotherapy for head and neck cancer (HNC) patients, who are at risk for cancer- and therapy-associated cachexia/sarcopenia.

MATERIALS AND METHODS

This retrospective single-institution study included 215 HNC patients, treated with curative radiotherapy between 2003 and 2013. Height/weight measures were tabulated. Skeletal muscle mass was contoured on pre- and post-treatment CT at the L3 vertebral level. Three common lean body mass (LBM) formulae (Hume, Boer, and James) were calculated, and compared to CT assessment at each time point.

RESULTS

156 patients (73%) had tumors arising in the oropharynx and 130 (61%) received concurrent chemotherapy. Mean pretreatment body mass index (BMI) was 28.5±4.9kg/m(2) in men and 27.8±8kg/m(2) in women. Mean post-treatment BMI were 26.2±4.4kg/m(2) in men, 26±7.5kg/m(2) in women. Mean CT-derived LBM decreased from 55.2±11.8kg pre-therapy to 49.27±9.84kg post-radiation. Methods comparison revealed 95% limit of agreement of ±12.5-13.2kg between CT and height-weight formulae. Post-treatment LBM with the three formulae was significantly different from CT (p<0.0001). In all instances, no height-weight formula was practically equivalent to CT within±5kg.

CONCLUSION

Formulae cannot accurately substitute for direct quantitative imaging LBM measurements. We therefore recommend CT-based LBM assessment as a routine practice of head and neck cancer patient body composition.

Analytical modeling and feasibility study of a multi-GPU cloud-based server (MGCS) framework for non-voxel-based dose calculations

PURPOSE

In this paper, a multi-GPU cloud-based server (MGCS) framework is presented for dose calculations, exploring the feasibility of remote computing power for parallelization and acceleration of computationally and time intensive radiotherapy tasks in moving toward online adaptive therapies.

METHODS

An analytical model was developed to estimate theoretical MGCS performance acceleration and intelligently determine workload distribution. Numerical studies were performed with a computing setup of 14 GPUs distributed over 4 servers interconnected by a 1 Gigabits per second (Gbps) network. Inter-process communication methods were optimized to facilitate resource distribution and minimize data transfers over the server interconnect.

RESULTS

The analytically predicted computation time predicted matched experimentally observations within 1-5 %. MGCS performance approached a theoretical limit of acceleration proportional to the number of GPUs utilized when computational tasks far outweighed memory operations. The MGCS implementation reproduced ground-truth dose computations with negligible differences, by distributing the work among several processes and implemented optimization strategies.

CONCLUSIONS

The results showed that a cloud-based computation engine was a feasible solution for enabling clinics to make use of fast dose calculations for advanced treatment planning and adaptive radiotherapy. The cloud-based system was able to exceed the performance of a local machine even for optimized calculations, and provided significant acceleration for computationally intensive tasks. Such a framework can provide access to advanced technology and computational methods to many clinics, providing an avenue for standardization across institutions without the requirements of purchasing, maintaining, and continually updating hardware.

Assessment of dose variation for accelerated partial-breast irradiation using rigid and deformable image registrations

PURPOSE

The aim of this study was to estimate the delivered dose to the target and organs at risk (OAR) for external beam accelerated partial-breast irradiation (APBI) accounting for day-to-day setup uncertainties, using rigid and deformable image registration.

METHODS AND MATERIALS

One planning computed tomography (CT) scan and 5 cone beam CT scans for each of 25 patients previously treated with tangential breast radiation therapy were used. All cone beam CT scans were registered to the planning CT scan using 3 techniques: (1) rigid registration based on bony anatomy only, (2) rigid registration based on soft-tissue only, and (3) deformable image registration. For each patient, 4 dose distributions were calculated for APBI. The first dose distribution was the original plan. The other 3 were "dose-of-the-day" for each of the registration approaches. The effects of image registrations on estimating delivered dose to targets and OAR were determined.

RESULTS

The average reductions in V₉₅ (percentage of the PTV that received 95% of the prescribed dose) were 6%, 7%, and 5% for bone, soft-tissue, and deformable registrations, respectively. The average increase in mean dose to the heart were 9%, 9%, and 18% for bone, soft-tissue, and deformable registrations, respectively, whereas the average increase in maximum dose to the contralateral breast were 19%, 20%, and 28%, respectively.

CONCLUSIONS

The results of this study have shown that there are differences between the planned and estimated delivered dose for APBI because of day-to-day setup uncertainties that may need to be accounted for. Estimated dosimetric impact of setup variation and breast deformation assessed using deformable registration was greater for OARs and smaller for target volumes compared to rigid registration.

Automatic deformable surface registration for medical applications by radial basis function-based robust point-matching

Deformable surface mesh registration is a useful technique for various medical applications, such as intra-operative treatment guidance and intra- or inter-patient study. In this paper, we propose an automatic deformable mesh registration technique. The proposed method iteratively deforms a source mesh to a target mesh without manual feature extraction. Each iteration of the registration consists of two steps, automatic correspondence finding using robust point-matching (RPM) and local deformation using a radial basis function (RBF). The proposed RBF-based RPM algorithm solves the interlocking problems of correspondence and deformation using a deterministic annealing framework with fuzzy correspondence and RBF interpolation. Simulation tests showed promising results, with the average deviations decreasing by factors of 21.2 and 11.9, respectively. In the human model test, the average deviation decreased from 1.72±1.88mm to 0.57±0.66mm. We demonstrate the effectiveness of the proposed method by presenting some medical applications.

Investigating CT to CBCT image registration for head and neck proton therapy as a tool for daily dose recalculation

PURPOSE

Intensity modulated proton therapy (IMPT) of head and neck (H&N) cancer patients may be improved by plan adaptation. The decision to adapt the treatment plan based on a dose recalculation on the current anatomy requires a diagnostic quality computed tomography (CT) scan of the patient. As gantry-mounted cone beam CT (CBCT) scanners are currently being offered by vendors, they may offer daily or weekly updates of patient anatomy. CBCT image quality may not be sufficient for accurate proton dose calculation and it is likely necessary to perform CBCT CT number correction. In this work, the authors investigated deformable image registration (DIR) of the planning CT (pCT) to the CBCT to generate a virtual CT (vCT) to be used for proton dose recalculation.

METHODS

Datasets of six H&N cancer patients undergoing photon intensity modulated radiation therapy were used in this study to validate the vCT approach. Each dataset contained a CBCT acquired within 3 days of a replanning CT (rpCT), in addition to a pCT. The pCT and rpCT were delineated by a physician. A Morphons algorithm was employed in this work to perform DIR of the pCT to CBCT following a rigid registration of the two images. The contours from the pCT were deformed using the vector field resulting from DIR to yield a contoured vCT. The DIR accuracy was evaluated with a scale invariant feature transform (SIFT) algorithm comparing automatically identified matching features between vCT and CBCT. The rpCT was used as reference for evaluation of the vCT. The vCT and rpCT CT numbers were converted to stopping power ratio and the water equivalent thickness (WET) was calculated. IMPT dose distributions from treatment plans optimized on the pCT were recalculated with a Monte Carlo algorithm on the rpCT and vCT for comparison in terms of gamma index, dose volume histogram (DVH) statistics as well as proton range. The DIR generated contours on the vCT were compared to physician-drawn contours on the rpCT.

RESULTS

The DIR accuracy was better than 1.4 mm according to the SIFT evaluation. The mean WET differences between vCT (pCT) and rpCT were below 1 mm (2.6 mm). The amount of voxels passing 3%/3 mm gamma criteria were above 95% for the vCT vs rpCT. When using the rpCT contour set to derive DVH statistics from dose distributions calculated on the rpCT and vCT the differences, expressed in terms of 30 fractions of 2 Gy, were within [-4, 2 Gy] for parotid glands (D(mean)), spinal cord (D(2%)), brainstem (D(2%)), and CTV (D(95%)). When using DIR generated contours for the vCT, those differences ranged within [-8, 11 Gy].

CONCLUSIONS

In this work, the authors generated CBCT based stopping power distributions using DIR of the pCT to a CBCT scan. DIR accuracy was below 1.4 mm as evaluated by the SIFT algorithm. Dose distributions calculated on the vCT agreed well to those calculated on the rpCT when using gamma index evaluation as well as DVH statistics based on the same contours. The use of DIR generated contours introduced variability in DVH statistics.

Feasibility of automated proton therapy plan adaptation for head and neck tumors using cone beam CT images

Background

Intensity modulated proton therapy (IMPT) of head and neck (H&N) tumors may benefit from plan adaptation to correct for the dose perturbations caused by weight loss and tumor volume changes observed in these patients. As cone beam CT (CBCT) is increasingly considered in proton therapy, it may be possible to use available CBCT images following intensity correction for plan adaptation. This is the first study exploring IMPT plan adaptation on CBCT images corrected and delineated by deformable image registration of the planning CT (pCT) to the CBCT, yielding a virtual CT (vCT).

Methods

A Morphons algorithm was used to deform the pCTs and corresponding delineations of 9 H&N cancer patients to a weekly CBCT acquired within ±3 days of a control replanning CT scan (rpCT). The IMPT treatment plans were adapted using the vCT and the adapted and original plans were recalculated on the rpCT for dose/volume parameter evaluation of the impact of adaptation.

Results

On the rpCT, the adapted plans were equivalent to the original plans in terms of target volumes D₉₅ and V₉₅, but showed a significant reduction of D₂ in these volumes. OAR doses were mostly equivalent or reduced. In particular, the adapted plans did not reduce parotid gland D_mean, but the dose to the optical system. For three patients the spinal cord or brain stem received higher, though well below tolerance, maximum dose. Subsequent tightening of the treatment planning constraints for these OARs on new vCT-adapted plans did not degrade target coverage and yielded pCT equivalent plans on the vCT.

Conclusions

An offline automated procedure to generate an adapted IMPT plan on CBCT images was developed and investigated. When evaluating the adapted plan on a control rpCT we observed reduced D₂ in target volumes as major improvement. OAR sparing was only partially improved by the procedure. Despite potential limitations in the accuracy of the vCT approach, an improved quality of the adapted plans could be achieved.

Electronic supplementary material

The online version of this article (doi:10.1186/s13014-016-0641-7) contains supplementary material, which is available to authorized users.

A simple method of evaluating margin-growing accuracy in image-guided radiation therapy

OBJECTIVE

In order to not add extra uncertainty to radiotherapy planning process, accurate margin algorithm is necessary, therefore we propose a centre-shift method to estimate its accuracy.

METHODS

A series of spherical phantoms are used with different CT slice separations (SSs) and pixel sizes (PSs). They are grown by different margins, and displaced geometric centres provide a window on accuracy. Volume difference between pre- and post-expansion is also calculated to double-check the accuracy.

RESULTS

The measured margin nearly varies as multiples of PS in the transaxial plane; in the superior-inferior direction, it is approximately equal to SS when the ideal margin is smaller than SS. A sphere's volume of <1 cm(3) is underestimated by 3-70% for all PSs, and 2-100% for SS of ≤5 mm but overestimated up to 112% for >5 mm. For volumes of >1 cm(3), relative volume error decreases, and it is nearly zero for >100 cm(3). The dependence of margin accuracy on SS and PS is largely eliminated by volume difference method.

CONCLUSION

We have proposed a simple method to estimate margin-growing accuracy and suggested corrective action to minimize the variation.

ADVANCES IN KNOWLEDGE

One big difference from the previous results is that SS and PS both influence the accuracy of margin growth and volume calculation in Eclipse(™) treatment planning system (Varian Medical System, Palo Alto, CA).

Phase correlation applied to the 3D registration of CT and CBCT image volumes

PURPOSE

In this study, a 3D phase correlation algorithm was investigated to test feasibility for use in determining the anatomical changes that occur throughout a patient's radiotherapy treatment. The algorithm determines the transformations between two image volumes through analysis in the Fourier domain and has not previously been used in radiotherapy for 3D registration of CT and CBCT volumes.

METHODS

Various known transformations were applied to a patient's prostate CT image volume to create 12 different test cases. The mean absolute error and standard deviation were determined by evaluating the difference between the known contours and those calculated from the registration process on a point-by-point basis. Similar evaluations were performed on images with increasing levels of noise added. The improvement in structure overlap offered by the algorithm in registering clinical CBCT to CT images was evaluated using the Dice Similarity Coefficient (DSC).

RESULTS

A mean error of 2.35 (σ = 1.54) mm was calculated for the 12 deformations applied. When increasing levels of noise were introduced to the images, the mean errors were observed to rise up to a maximum increase of 1.77 mm. For CBCT to CT registration, maximum improvements in the DSC of 0.09 and 0.46 were observed for the bladder and rectum, respectively.

CONCLUSIONS

The Fourier-based 3D phase correlation registration algorithm investigated displayed promising results in CT to CT and CT to CBCT registration, offers potential in terms of efficiency and robustness to noise, and is suitable for use in radiotherapy for monitoring patient anatomy throughout treatment.

Quantitative assessment of anatomical change using a virtual proton depth radiograph for adaptive head and neck proton therapy

The aim of this work is to demonstrate the feasibility of using water-equivalent thickness (WET) and virtual proton depth radiographs (PDRs) of intensity corrected cone-beam computed tomography (CBCT) to detect anatomical change and patient setup error to trigger adaptive head and neck proton therapy. The planning CT (pCT) and linear accelerator (linac) equipped CBCTs acquired weekly during treatment of a head and neck patient were used in this study. Deformable image registration (DIR) was used to register each CBCT with the pCT and map Hounsfield units (HUs) from the planning CT (pCT) onto the daily CBCT. The deformed pCT is referred as the corrected CBCT (cCBCT). Two dimensional virtual lateral PDRs were generated using a ray-tracing technique to project the cumulative WET from a virtual source through the cCBCT and the pCT onto a virtual plane. The PDRs were used to identify anatomic regions with large variations in the proton range between the cCBCT and pCT using a threshold of 3 mm relative difference of WET and 3 mm search radius criteria. The relationship between PDR differences and dose distribution is established. Due to weight change and tumor response during treatment, large variations in WETs were observed in the relative PDRs which corresponded spatially with an increase in the number of failing points within the GTV, especially in the pharynx area. Failing points were also evident near the posterior neck due to setup variations. Differences in PDRs correlated spatially to differences in the distal dose distribution in the beam's eye view. Virtual PDRs generated from volumetric data, such as pCTs or CBCTs, are potentially a useful quantitative tool in proton therapy. PDRs and WET analysis may be used to detect anatomical change from baseline during treatment and trigger further analysis in adaptive proton therapy.

The suitability of common metrics for assessing parotid and larynx autosegmentation accuracy

Contouring structures in the head and neck is time‐consuming, and automatic segmentation is an important part of an adaptive radiotherapy workflow. Geometric accuracy of automatic segmentation algorithms has been widely reported, but there is no consensus as to which metrics provide clinically meaningful results. This study investigated whether geometric accuracy (as quantified by several commonly used metrics) was associated with dosimetric differences for the parotid and larynx, comparing automatically generated contours against manually drawn ground truth contours. This enabled the suitability of different commonly used metrics to be assessed for measuring automatic segmentation accuracy of the parotid and larynx. Parotid and larynx structures for 10 head and neck patients were outlined by five clinicians to create ground truth structures. An automatic segmentation algorithm was used to create automatically generated normal structures, which were then used to create volumetric‐modulated arc therapy plans. The mean doses to the automatically generated structures were compared with those of the corresponding ground truth structures, and the relative difference in mean dose was calculated for each structure. It was found that this difference did not correlate with the geometric accuracy provided by several metrics, notably the Dice similarity coefficient, which is a commonly used measure of spatial overlap. Surface‐based metrics provided stronger correlation and are, therefore, more suitable for assessing automatic segmentation of the parotid and larynx.

PACS number(s): 87.57.nm, 87.55.D, 87.55.Qr

Adaptive Radiotherapy for Head Neck Cancer

Changes in patient anatomy may occur either from a tumour volume, position or function of a specific organ at risk, or target volume, weight loss or a reduction in postoperative oedema, and may vary between patients. Adaptive radiotherapy aims to correct morphological variations by realizing one or more plans during the treatment course. Imaging is used to detect these variations, thereby deciding on a potential replanning. At present, adaptive radiotherapy for head neck cancer (HNC) mainly deals with treatment response, such as weight loss or tumor shrinkage. Therefore a properly timed repeat CT scan during treatment is a suitable basis for plan adaptation to account for treatment response.

Analysis of Dosimetric Impacts of Cone Beam Computed Tomography-Based Volumetric Modulated Arc Therapy Planning

OBJECTIVE

To quantify the Hounsfield unit (HU) variations between computed tomography (CT) and cone beam CT (CBCT) and study its impact on volumetric modulated arc therapy (VMAT) plans.

METHODS

HU number variations in CT and CBCT images were evaluated using the Catphan-504 phantom, and changes in seven different materials within the phantom (air, polymethylpentene, low-density polyethylene, polystyrene, acrylic, Delrin, and Teflon) were studied. The HU variations in half-fan and full-fan modes of CBCT were evaluated. The effect of variations in the shape of the body cross sections was assessed by reducing the body of the Catphan by 0.5 cm and 1.0 cm. CBCT-based VMAT plans in 27 patients (10 prostate, 10 brain, and 7 head and neck (HN)) were compared with corresponding CT-based plans. The dosimetric variations were assessed referring to different points on the dose volume histogram (D_5%, D_50%, and D_95% for PTVs and D_1%, D_max, and D_mean for organs at risk). The relative percentage of difference (ΔD (%)) between CT- and CBCT-based VMAT plans were examined on these points. To evaluate the dosimetric accuracy, dose distributions were compared using Omnipro-I'mRT software. The VMAT plans were evaluated based on 3 mm-3%, 2 mm-2%, and 1 mm-1% gamma criteria.

RESULTS

The HU difference in CT and CBCT was highest for air, Delrin, and Teflon, whereas the difference was less than 20 HU for the other materials. The dose volume histograms of both CT- and CBCT-based plans were in excellent agreement in both phantom and patients, except in HN cases where the difference was 7%. The average 3 mm-3% gamma pass points in brain, prostate, and HN patients were 97 ± 0.2%, 96 ± 0.06%, and 93.3 ± 1.1%, respectively. The gamma pass rates reduced to 88.8 ± 0.06%, 91 ± 0.04%, and 79 ± 6% in 2 mm-2%, and further declined to 76.6 ± 0.09%, 75.2 ± 0.5%, and 60 ± 6% using the stringent 1 mm-1% gamma criteria for brain, prostate, and HN cases, respectively.

CONCLUSION

Based on the results of this study, it is our belief that CBCT images can be used as a tool for evaluating the dosimetric variation in patient VMAT plans.

Use of registration-based contour propagation in texture analysis for esophageal cancer pathologic response prediction

Change in PET-based textural features has shown promise in predicting cancer response to treatment. However, contouring tumour volumes on longitudinal scans is time-consuming. This study investigated the usefulness of contour propagation in texture analysis for the purpose of pathologic response prediction in esophageal cancer. Forty-five esophageal cancer patients underwent PET/CT scans before and after chemo-radiotherapy. Patients were classified into responders and non-responders after the surgery. Physician-defined tumour ROIs on pre-treatment PET were propagated onto the post-treatment PET using rigid and ten deformable registration algorithms. PET images were converted into 256 discrete values. Co-occurrence, run-length, and size zone matrix textures were computed within all ROIs. The relative difference of each texture at different treatment time-points was used to predict the pathologic responders. Their predictive value was assessed using the area under the receiver-operating-characteristic curve (AUC). Propagated ROIs from different algorithms were compared using Dice similarity index (DSI). Contours propagated by the fast-demons, fast-free-form and rigid algorithms did not fully capture the high FDG uptake regions of tumours. Fast-demons propagated ROIs had the least agreement with other contours (DSI = 58%). Moderate to substantial overlap were found in the ROIs propagated by all other algorithms (DSI = 69%-79%). Rigidly propagated ROIs with co-occurrence texture failed to significantly differentiate between responders and non-responders (AUC = 0.58, q-value = 0.33), while the differentiation was significant with other textures (AUC = 0.71-0.73, p < 0.009). Among the deformable algorithms, fast-demons (AUC = 0.68-0.70, q-value < 0.03) and fast-free-form (AUC = 0.69-0.74, q-value < 0.04) were the least predictive. ROIs propagated by all other deformable algorithms with any texture significantly predicted pathologic responders (AUC = 0.72-0.78, q-value < 0.01). Propagated ROIs using deformable registration for all textures can lead to accurate prediction of pathologic response, potentially expediting the temporal texture analysis process. However, fast-demons, fast-free-form, and rigid algorithms should be applied with care due to their inferior performance compared to other algorithms.