Assessment of Interfraction Patient Setup for Head-and-Neck Cancer Intensity Modulated Radiation Therapy Using Multiple Computed Tomography-Based Image Guidance

Planning target volume margin in head and neck cancer patients undergoing radiation therapy: Estimations derived from own data and literature

Planning target volume (PTV) to deliver the desired dose to the clinical target volume (CTV) accounts for systematic (∑) and random (σ) errors during the planning and execution of intensity modulated radiation therapy (IMRT). As these errors vary at different departments, this study was conducted to determine the 3-dimensional PTV (PTV3D) margins for head and neck cancer (HNC) at our center. The same was also estimated from reported studies for a comparative assessment. A total of 77 patients with HNCs undergoing IMRT were included. Of these, 39 patients received radical RT and 38 received postoperative IMRT. An extended no action level protocol was implemented using on-board imaging. Shifts in the mediolateral (ML), anteroposterior (AP), and superoinferior (SI) directions of each patient were recorded for every fraction. PTV margins in each direction (ML, AP, SI) and PTV3D were calculated using van Herk's equation. Weighted PTV3D was also computed from the ∑ and σ errors in each direction published in the literature for HNC. Our patients were staged T2-4 (66/77) and N0 (39/77). In all, 2280 on-board images were acquired, and daily shifts in each direction were recorded. The PTV margins in the ML, AP, and SI directions were computed as 3.2 mm, 2.9 mm, and 2.6 mm, respectively. The PTV3D margin was estimated to be 6.5 mm. This compared well with the weighted median PTV3D of 7.2 mm (range: 3.2 to 9.9) computed from the 16 studies reported in the literature. To ensure ≥95% CTV dose coverage in 90% of HNC patients, PTV3D margin for our department was estimated as 6.5 mm. This agrees with the weighted median PTV3D margin of 7.2 mm computed from the 16 published studies in HNCs. Site-specific PTV3D margin estimations should be an integral component of the quality assurance protocol of each department to ensure adequate coverage of dose to CTV during IMRT.

Human-level comparable control volume mapping with a deep unsupervised-learning model for image-guided radiation therapy

PURPOSE

To develop a deep unsupervised learning method with control volume (CV) mapping from patient positioning daily CT (dCT) to planning computed tomography (pCT) for precise patient positioning.

METHODS

We propose an unsupervised learning framework, which maps CVs from dCT to pCT to automatically generate the couch shifts, including translation and rotation dimensions. The network inputs are dCT, pCT and CV positions in the pCT. The output is the transformation parameter of the dCT used to setup the head and neck cancer (HNC) patients. The network is trained to maximize image similarity between the CV in the pCT and the CV in the dCT. A total of 554 CT scans from 158 HNC patients were used for the evaluation of the proposed model. At different points in time, each patient had many CT scans. Couch shifts are calculated for the testing by averaging the translation and rotation from the CVs. The ground-truth of the shifts come from bone landmarks determined by an experienced radiation oncologist.

RESULTS

The system positioning errors of translation and rotation are less than 0.47 mm and 0.17°, respectively. The random positioning errors of translation and rotation are less than 1.13 mm and 0.29°, respectively. The proposed method enhanced the proportion of cases registered within a preset tolerance (2.0 mm/1.0°) from 66.67% to 90.91% as compared to standard registrations.

CONCLUSIONS

We proposed a deep unsupervised learning architecture for patient positioning with inclusion of CVs mapping, which weights the CVs regions differently to mitigate any potential adverse influence of image artifacts on the registration. Our experimental results show that the proposed method achieved efficient and effective HNC patient positioning.

Head and neck radiotherapy on the MR linac: a multicenter planning challenge amongst MRIdian platform users

Purpose

Purpose of this study is to evaluate plan quality on the MRIdian (Viewray Inc., Oakwood Village, OH, USA) system for head and neck cancer (HNC) through comparison of planning approaches of several centers.

Methods

A total of 14 planners using the MRIdian planning system participated in this treatment challenge, centrally organized by ViewRay, for one contoured case of oropharyngeal carcinoma with standard constraints for organs at risk (OAR). Homogeneity, conformity, sparing of OARs, and other parameters were evaluated according to The International Commission on Radiation Units and Measurements (ICRU) recommendations anonymously, and then compared between centers. Differences amongst centers were assessed by means of Wilcoxon test. Each plan had to fulfil hard constraints based on dose–volume histogram (DVH) parameters and delivery time. A plan quality metric (PQM) was evaluated. The PQM was defined as the sum of 16 submetrics characterizing different DVH goals.

Results

For most dose parameters the median score of all centers was higher than the threshold that results in an ideal score. Six participants achieved the maximum number of points for the OAR dose parameters, and none had an unacceptable performance on any of the metrics. Each planner was able to achieve all the requirements except for one which exceeded delivery time. The number of segments correlated to improved PQM and inversely correlated to brainstem D_0.1cc and to Planning Target Volume1 (PTV) D_0.1cc. Total planning experience inversely correlated to spinal canal dose.

Conclusion

Magnetic Resonance Image (MRI) linac-based planning for HNC is already feasible with good quality. Generally, an increased number of segments and increasing planning experience are able to provide better results regarding planning quality without significantly prolonging overall treatment time.

Supplementary Information

The online version of this article (10.1007/s00066-021-01771-8) contains supplementary material, which is available to authorized users.

Clinical Development and Evaluation of Megavoltage Topogram for Fast Patient Alignment on Helical Tomotherapy

Purpose

To develop and evaluate a fast patient localization tool using megavoltage (MV)-topogram on helical tomotherapy.

Methods and Materials

Eighty-one MV-topogram pairs for 18 pelvis patients undergoing radiation were acquired weekly under an institutional review board–approved clinical trial. The MV-topogram imaging protocol requires 2 orthogonal acquisitions at static gantry angles of 0 degrees and 90 degrees for a programed scan length. A MATLAB based in-house software was developed to reconstruct the MV-topograms offline. Reference images (digitally reconstructed topograms, digitally reconstructed topograms) were generated using the planning computed tomography and tomotherapy geometry. The MV-topogram based alignment was determined by registering the MV-topograms to the digitally reconstructed topogram using bony landmark on commercial MIM software. The daily shifts in 3 translational directions determined from MV-topograms were compared with the megavoltage computed tomography (MVCT) based patient shifts. Linear-regression and two one-sided tests equivalence tests were performed to investigate the relation and equivalence between the 2 techniques. Seventy-eight MV-topogram pairs for 19 head and neck patients were included to validate the finding.

Results

The magnitudes of alignment differences of (MVCT − MV-topogram) (and standard deviations) were −0.3 ± 2.1, −0.8 ± 2.4, and 1.6 ± 1.7 mm for pelvis and 0.6 ± 1.2, 0.8 ± 4.2, 1.6 ± 2.6 mm for head and neck; the linear-regression coefficients between 2 imaging techniques were 1.18, 1.10, 0.94, and 0.86, 0.63, 0.38 in the lateral, longitudinal, vertical directions for pelvis and head and neck, respectively. The acquisition time for a pair of MV-topograms was up to 12.7 times less than MVCT scans (coarse scan mode) while covering longer longitudinal length.

Conclusions

MV-topograms showed equivalent clinical performance to the standard MVCT with significantly less acquisition time for pelvis and H&N patients. The MV-topogram can be used as an alternative or complimentary tool for bony landmark-based patient alignment on tomotherapy.

A pilot study of highly accelerated 3D MRI in the head and neck position verification for MR-guided radiotherapy

Background

To evaluate the performance of a highly accelerated 3D MRI on inter-fractional positional measurement for MR-guided radiotherapy (MRgRT) in the head and neck (HN).

Methods

Fourteen healthy volunteers received 159 scans on a 1.5 T MR-sim to simulate MRgRT fractions. MRI acquisition included a high-resolution (HQI-MRI, voxel-size =1.05×1.05×1.05 mm³, duration =5 min) and a highly-accelerated low-resolution (true-LQI-MRI, acceleration-factor =9, voxel-size =1.4×1.4×1.4 mm³, duration =86 s) T1w spin-echo sequence (TR/TE =420/7.2 ms). The first session HQI-MRI was used as the reference to mimic planning MRI. Other HQI-MRI was also retrospectively down-sampled in K-space and GRAPPA reconstructed to generate pseudo-LQI-MRI. Inter-sessional positional shift calculated from HQI-MRI, true-LQI-MRI and pseudo-LQI-MRI rigidly registering to the reference were analyzed and compared in the overall HN and the sub-regions of brain, nasopharynx, oropharynx and hypopharynx.

Results

The calculated SD of systematic errors (Σ) from HQI-MRI/pseudo-LQI-MRI/true-LQI-MRI images for overall HN were 1.11/1.14/1.08, 0.28/0.26/0.29, 0.43/0.44/0.60, and 0.77/0.79/0.74 mm for translation in LR, AP, SI and 3D, respectively; The corresponding RMS of random errors (σ) were 0.97/0.98/0.96, 0.28/0.27/0.26, 0.77/0.77/0.72, and 0.85/0.87/0.85 mm. For all sub-regions, brain showed the smallest Σ and σ in 3D. Other sub-regions showed direction-dependent error patterns, but the positioning results were consistent, independent of the datasets used for registration.

Conclusions

A highly-accelerated 3D-MRI could be used for MR-guided HN radiotherapy without compromising position verification accuracy.

Fast, Low-Dose Megavoltage-Topogram Localization on TomoTherapy: Initial Clinical Experience With Mesothelioma Patients

PURPOSE

This study aimed to evaluate the potential of megavoltage-topogram (MV-topogram)-based alignment as an alternative to megavoltage computed tomography (MVCT) in reducing setup time and imaging dose for patients with malignant pleural mesothelioma who are receiving TomoTherapy.

METHODS AND MATERIALS

Twelve patients were enrolled in an ongoing institutional review board approved clinical trial at our institute. Patients were set up with a clinical protocol using red lasers. Anteroposterior (AP) and lateral (LAT) MV-topograms were acquired using gantry angles of 0°/90° with a 1 mm collimator opening, all multileaf collimator leaves open, a couch speed of 4 cm/s, and a 12.5-second scanning time. Routine MVCT scans were performed immediately afterward. The MV-topograms were reconstructed and enhanced using contrast-limited adaptive histogram equalization. Anteroposterior and LAT kilovoltage digital reconstructed topogram images were reconstructed based on TomoTherapy geometry from computed tomography simulation scans. Registrations between MV-topograms and kilovoltage-digital reconstructed topogram images were performed manually, and patients' daily shifts were recorded. Results were compared against the corresponding daily MVCT shifts. MV-topogram and MVCT doses were measured and recorded using an ion chamber on a cheese phantom with depths between 1 and 14 cm, as well as the times required to acquire the 2 image modalities.

RESULTS

The mean and standard deviation of shift discrepancies between MV-topogram and MVCT were 0.74 ± 2.08, -0.09 ± 4.46, and 0.45 ± 3.57 mm in the LAT, longitudinal, and vertical directions, respectively. The MVCT imaging doses measured were 14.74 to 26.92 times higher than the MV-topogram doses, depending on depth. On average, MV-topograms with a mean scan length of 50 cm achieved a 5-fold image acquisition time savings over MVCT, with a mean scan length of 38 cm.

CONCLUSIONS

MV-topograms has the potential to provide alignment performance equivalent to that of MVCT for patients with mesothelioma, with a significant reduction in imaging dose and acquisition time.

Prospective assessment of inter- or intra-fractional variation according to body weight or volume change in patients with head and neck cancer undergoing radiotherapy

This study aimed to prospectively investigate the association between body weight (ΔBW) or body volume variations (ΔBV) and inter- or intra-fractional variations (Δ(inter) or Δ(intra)) in patients with head and neck cancer (HNC) undergoing radiotherapy (RT). This study enrolled patients with HNC from December 2015 to December 2017. All patients underwent curative intensity-modulated RT (IMRT) either as definitive or adjuvant treatment. Six-dimensional inter- and intra-fractional variations (Δ(inter) and Δ(intra)) were obtained with ExacTrac (BrainLAB, Feldkirchen, Germany) system. BV was measured 7.5 cm cranio-caudally from the centre using cone beam computed tomography. The BW, BV, and Δ(inter) were calculated based on the value obtained on the first treatment day after each simulation. Both Δ(inter) and Δ(intra) were considered in calculating the optimal margins for planning target volume (PTV), which was calculated using van Herk’s formula. In total, 678 fractions with 39 simulations in 22 patients were analysed. The average ΔBW and ΔBV was -0.43±1.90 kg (range, -7.3 to 5.0) and -24.34±69.0 cc (range, -247.15 to 214.88), respectively. In correlation analysis, Δ(intra) was more associated with ΔBW or ΔBV than Δ(inter). Receiver operating characteristic analysis showed Δ(intra) could differentiate ΔBW from ΔBV, while Δ(inter) could not. The optimal margins for PTV considering both Δ(inter) and Δ(intra) were 3.70 mm, 4.52 mm, and 5.12 mm for the right-left, superior-inferior, and anterior-posterior directions, respectively. In conclusion, the PTV margin of 6 mm for anterior-posterior direction and 5 mm for the other directions were needed. ΔBW or ΔBV correlated with Δ(intra) rather than Δ(inter). Therefore, ΔBW or ΔBV should be assessed for accurate IMRT in patients with HNC.

Assessment of positional reproducibility in the head and neck on a 1.5-T MR simulator for an offline MR-guided radiotherapy solution

Background

Recently, a shuttle-based offline magnetic resonance-guided radiotherapy (MRgRT) approach was proposed. This study aims to evaluate the positional reproducibility in the immobilized head and neck using a 1.5-T MR-simulator (MR-sim) on healthy volunteers.

Methods

A total of 159 scans of 14 healthy volunteers were conducted on a 1.5-T MR-sim with thermoplastic mask immobilization. MR images with isotropic 1.05³ mm³ voxel size were rigidly registered to the first scan based on fiducial, anatomical and gross positions. Mean and standard deviation of positional displacements in translation and rotation were assessed. Systematic error and random errors of positioning in the head and neck on the MR-sim were determined in the translation of, and in the rotation of roll, pitch and yaw.

Results

The systematic error (Σ) of translation in left-right (LR), anterior-posterior (AP) and superior-inferior (SI) direction was 0.57, 0.22 and 0.26 mm for fiducial displacement, 0.28, 0.10 and 0.52 mm for anatomical displacement, and 0.53, 0.22 and 0.49 mm for gross displacement, respectively. The random error (σ) in corresponding translation direction was 2.07, 0.54 and 1.32 mm for fiducial displacement, 1.34, 0.73 and 2.04 mm for anatomical displacement, and 2.24, 0.86 and 2.61 mm for gross displacement. The systematic error and random error of rotation were generally smaller than 1°.

Conclusions

Our results suggested that high gross positional reproducibility (<1 mm translational and <1° rotational systematic error) could be achieved on an MR-sim for the proposed offline MRgRT.

Positional uncertainties of cervical and upper thoracic spine in stereotactic body radiotherapy with thermoplastic mask immobilization

Purpose

To investigate positional uncertainty and its correlation with clinical parameters in spine stereotactic body radiotherapy (SBRT) using thermoplastic mask (TM) immobilization.

Materials and Methods

A total of 21 patients who underwent spine SBRT for cervical or upper thoracic spinal lesions were retrospectively analyzed. All patients were treated with image guidance using cone beam computed tomography (CBCT) and 4 degrees-of-freedom (DoF) positional correction. Initial, pre-treatment, and post-treatment CBCTs were analyzed. Setup error (SE), pre-treatment residual error (preRE), post-treatment residual error (postRE), intrafraction motion before treatment (IM1), and intrafraction motion during treatment (IM2) were determined from 6 DoF manual rigid registration.

Results

The three-dimensional (3D) magnitudes of translational uncertainties (mean ± 2 standard deviation) were 3.7±3.5 mm (SE), 0.9±0.9 mm (preRE), 1.2±1.5 mm (postRE), 1.4±2.4 mm (IM1), and 0.9±1.0 mm (IM2), and average angular differences were 1.1°±1.2° (SE), 0.9°±1.1° (preRE), 0.9°±1.1° (postRE), 0.6°±0.9° (IM1), and 0.5°±0.5° (IM2). The 3D magnitude of SE, preRE, postRE, IM1, and IM2 exceeded 2 mm in 18, 0, 3, 3, and 1 patients, respectively. No association were found between all positional uncertainties and body mass index, pain score, and treatment location (p > 0.05, Mann-Whitney test). There was a tendency of intrafraction motion to increase with overall treatment time; however, the correlation was not statistically significant (p > 0.05, Spearman rank correlation test).

Conclusion

In spine SBRT using TM immobilization, CBCT and 4 DoF alignment correction, a minimum residual translational uncertainty was 2 mm. Shortening overall treatment time and 6 DoF positional correction may further reduce positional uncertainties.

Analysis of which local set-up errors can be covered by a 5-mm margin for cone beam CT-guided radiotherapy for nasopharyngeal carcinoma

Objective:

To analyse which local set-up errors can be covered by a 5-mm margin for cone beam computed tomography (CBCT)-guided radiotherapy in nasopharyngeal carcinoma (NPC).

Methods:

11 regions of interest (ROIs) were registered for 24 NPC patients, with a total of 323 CBCT scans. According to the registration results, clinical target volume–planning target volume (CTV–PTV)/organs at risk-planning risk volume (OAR-PRV) margin analysis; Pearson correlation analysis; Bland–Altman plots; and a receiver operating characteristic (ROC) analysis were used to investigate which local set-up errors of substructure can be represented by the PTV_ROI.

Results:

The clinical target volume-PTV/OAR-planning risk volume margins were less than 5 mm for C1_ROI-C4_ROI, mandible (M_ROI), and sphenoid sinus (S_ROI) with respect to PTV_ROI. C1_ROI-C4_ROI, M_ROI, and S_ROI exhibited significant correlations and consistencies in the mediolateral, superior–inferior, and anteroposterior (AP) directions and significant receiver operating characteristic analysis results in the anteroposterior direction.

Conclusion:

Only the upper local set-up error of C1_ROI-C4_ROI, M_ROI, and S_ROI can be covered by a 5-mm margin for CBCT-guided NPC radiotherapy with a large ROI. Using these ROIs as an integral reference ROI is better than individual bony landmark.

Advances in knowledge:

This report is helpful to CBCT registration for NPC radiotherapy in clinical practice.

Setup errors in patients with head-neck cancer (HNC), treated using the Intensity Modulated Radiation Therapy (IMRT) technique: how it influences the customised immobilisation systems, patient's pain and anxiety

BACKGROUND

In patients with head-neck cancer treated with IMRT, immobility of the upper part of the body during radiation is maintained by means of customised immobilisation devices. The main purpose of this study was to determine how the procedures for preparation of customised immobilisation systems and the patients characteristics influence the extent of setup errors.

METHODS

A longitudinal, prospective study involving 29 patients treated with IMRT. Data were collected before CT simulation and during all the treatment sessions (528 setup errors analysed overall); the correlation with possible risk factors for setup errors was explored using a linear mixed model.

RESULTS

Setup errors were not influenced by the patient's anxiety and pain. Temporary removal of the thermoplastic mask before carrying out the CT simulation shows statistically borderline, clinically relevant, increase of setup errors (+24.7%, 95% CI: -0.5% - 55.8%). Moreover, a unit increase of radiation therapists who model the customised thermoplastic mask is associated to a -18% (-29.2% - -4.9%) reduction of the errors. The setup error is influenced by the patient's physical features; in particular, it increases both in patients in whom the treatment position is obtained with 'Shoulder down' (+27.9%, 2.2% - 59.7%) and in patients with 'Scoliosis/kyphosis' problems (+65.4%, 2.3% - 164.2%). Using a 'Small size standard plus customized neck support device' is associated to a -52.3% (-73.7% - -11.2%) reduction. The increase in number of radiation therapists encountered during the entire treatment cycle does not show associations. Increase in the body mass index is associated with a slight reduction in setup error by (-2.8%, -5% - -0.7%).

CONCLUSION

The position of the patient obtained by forcing the shoulders downwards, clinically significant scoliosis or kyphosis and the reduction of the number of radiation therapists who model the thermoplastic mask are found to be statistically significant risk factors that can cause an increase in setup errors, while the use of 'Small size' neck support device and patient BMI can diminish them.

Quantification and Assessment of Interfraction Setup Errors Based on Cone Beam CT and Determination of Safety Margins for Radiotherapy

Introduction

To quantify interfraction patient setup-errors for radiotherapy based on cone-beam computed tomography and suggest safety margins accordingly.

Material and Methods

Positioning vectors of pre-treatment cone-beam computed tomography for different treatment sites were collected (n = 9504). For each patient group the total average and standard deviation were calculated and the overall mean, systematic and random errors as well as safety margins were determined.

Results

The systematic (and random errors) in the superior-inferior, left-right and anterior-posterior directions were: for prostate, 2.5(3.0), 2.6(3.9) and 2.9(3.9)mm; for prostate bed, 1.7(2.0), 2.2(3.6) and 2.6(3.1)mm; for cervix, 2.8(3.4), 2.3(4.6) and 3.2(3.9)mm; for rectum, 1.6(3.1), 2.1(2.9) and 2.5(3.8)mm; for anal, 1.7(3.7), 2.1(5.1) and 2.5(4.8)mm; for head and neck, 1.9(2.3), 1.4(2.0) and 1.7(2.2)mm; for brain, 1.0(1.5), 1.1(1.4) and 1.0(1.1)mm; and for mediastinum, 3.3(4.6), 2.6(3.7) and 3.5(4.0)mm. The CTV-to-PTV margins had the smallest value for brain (3.6, 3.7 and 3.3mm) and the largest for mediastinum (11.5, 9.1 and 11.6mm). For pelvic treatments the means (and standard deviations) were 7.3 (1.6), 8.5 (0.8) and 9.6 (0.8)mm.

Conclusions

Systematic and random setup-errors were smaller than 5mm. The largest errors were found for organs with higher motion probability. The suggested safety margins were comparable to published values in previous but often smaller studies.

Near Real-Time Assessment of Anatomic and Dosimetric Variations for Head and Neck Radiation Therapy via Graphics Processing Unit-based Dose Deformation Framework

PURPOSE

The purpose of this study was to systematically monitor anatomic variations and their dosimetric consequences during intensity modulated radiation therapy (IMRT) for head and neck (H&N) cancer by using a graphics processing unit (GPU)-based deformable image registration (DIR) framework.

METHODS AND MATERIALS

Eleven IMRT H&N patients undergoing IMRT with daily megavoltage computed tomography (CT) and weekly kilovoltage CT (kVCT) scans were included in this analysis. Pretreatment kVCTs were automatically registered with their corresponding planning CTs through a GPU-based DIR framework. The deformation of each contoured structure in the H&N region was computed to account for nonrigid change in the patient setup. The Jacobian determinant of the planning target volumes and the surrounding critical structures were used to quantify anatomical volume changes. The actual delivered dose was calculated accounting for the organ deformation. The dose distribution uncertainties due to registration errors were estimated using a landmark-based gamma evaluation.

RESULTS

Dramatic interfractional anatomic changes were observed. During the treatment course of 6 to 7 weeks, the parotid gland volumes changed up to 34.7%, and the center-of-mass displacement of the 2 parotid glands varied in the range of 0.9 to 8.8 mm. For the primary treatment volume, the cumulative minimum and mean and equivalent uniform doses assessed by the weekly kVCTs were lower than the planned doses by up to 14.9% (P=.14), 2% (P=.39), and 7.3% (P=.05), respectively. The cumulative mean doses were significantly higher than the planned dose for the left parotid (P=.03) and right parotid glands (P=.006). The computation including DIR and dose accumulation was ultrafast (∼45 seconds) with registration accuracy at the subvoxel level.

CONCLUSIONS

A systematic analysis of anatomic variations in the H&N region and their dosimetric consequences is critical in improving treatment efficacy. Nearly real-time assessment of anatomic and dosimetric variations is feasible using the GPU-based DIR framework. Clinical implementation of this technology may enable timely plan adaptation and improved outcome.

[Potential uncertainty about image registration in thoracic image-guided radiotherapy]

PURPOSE

Although image-guided radiotherapy (IGRT) is widely used to determine and correct daily setup errors, the additional interpretation for image registration would provide another error. We evaluated the uncertainty in image registration in IGRT.

METHOD

The subjects consisted of 12 consecutive patients treated with IGRT for thoracic esophageal cancer. Two radiation therapists had consensually achieved daily 3D registration between planning computed tomography (CT) and cone beam CT (CBCT). The original data sets of image registration in all fractions except for boost irradiations with a change in the isocenter positions were selected for evaluation. There were 20 to 32 data sets for each patient: a total of 318 data sets. To evaluate daily setup errors, the mean 3D displacement vector was calculated for each patient. To assess the reproducibility of image registration, two other radiation therapists reviewed the data sets and recorded geometric differences as uncertainty in the image registration.

RESULTS

The mean 3D displacement vector for each patient ranged from 4.9 to 15.5 mm for setup errors and 0.7 to 2.2 mm for uncertainty in image registration. There was a positive correlation between the 3D vectors for setup error and uncertainty in image registration (r = 0.487, p = 0.016).

CONCLUSION

Although IGRT can correct the setup errors, potential uncertainty exists in image registration. The setup error would disturb the image registration in IGRT.

A prospective analysis of inter- and intrafractional errors to calculate CTV to PTV margins in head and neck patients

PURPOSE

To evaluate an institute-specific CTV-PTV margin for head and neck (HN) patients according to a 3-mm action level protocol.

METHODS/PATIENTS

Twenty-three HN patients were prospectively analysed. Patients were immobilized with a thermoplastic mask. Inter- and intrafractional set-up errors (in the three dimensions) were assessed from portal images (PI) registration. Digitally reconstructed radiographs (DRRs) were compared with two orthogonal PI by matching bone anatomy landmarks. The isocenter was verified during the first five consecutive days of treatment: if the mean error detected was greater than 2 mm the isocenter position was corrected for the rest of the treatment. Isocenter was checked weekly thereafter. Set-up images were obtained before and after treatment administration on 10, 20 and 30 fractions to quantify the intrafractional displacement. For the set-up errors, systematic (Σ), random (σ), overall standard deviations, and the overall mean displacement (M), were determined. CTV to PTV margin was calculated considering both inter- and intrafractional errors.

RESULTS

A total of 396 portal images was analysed in 23 patients. Systematic interfractional (Σ(inter)) set-up errors ranged between 0.77 and 1.42 mm in the three directions, whereas the random (σ (inter)) errors were around 1-1.31 mm. Systematic intrafractional (Σ(intra)) errors ranged between 0.65 and 1.11 mm, whereas the random (σ (intra)) errors were around 1.13-1.16 mm.

CONCLUSIONS

A verification protocol (3-mm action level) provided by EPIDs improves the set-up accuracy. Intrafractional error is not negligible and contributes to create a larger CTV-PTV margin. The appropriate CTV-PTV margin for our institute is between 3 and 4.5 mm considering both inter- and intrafractional errors.