The role of imaging in adaptive radiotherapy for head and neck cancer

Evaluation of Perkin Elmer Amorphous Silicon Electronic Portal Imaging Device for Small Photon Field Dosimetry

Background

Electronic portal imaging devices (EPIDs) are applied to measure the dose and verify patients' position.

Objective

The present study aims to evaluate the performance of EPID for measuring dosimetric parameters in small photon fields.

Material and Methods

In this experimental study, the output factors and beam profiles were obtained using the amorphous silicon (a-Si) EPID for square field sizes ranging from 1×1 to 10×10 cm2 at energies 6 and 18 mega-voltage (MV). For comparison, the dosimetric parameters were measured with the pinpoint, diode, and Semiflex dosimeters. Additionally, the Monaco treatment planning system was selected to calculate the output factors and beam profiles.

Results

There was a significant difference between the output factors measured using the EPID and that measured with the other dosimeters for field sizes lower than 8×8 cm2. In the energy of 6 MV, the gamma passing rates (3%/3 mm) between EPID and diode profile were 98%, 98%, 95%, 94%, 93%, and 94% for 1×1, 2×2, 3×3, 4×4, 5×5, and 10×10 cm2, respectively. The measured penumbra width with EPID was higher compared to that measured by the diode dosimeter for both energies.

Conclusion

The EPID can measure the dosimetric parameters in small photon fields, especially for beam profiles and penumbra measurements.

Longitudinal diffusion and volumetric kinetics of head and neck cancer magnetic resonance on a 1.5 T MR-linear accelerator hybrid system: A prospective R-IDEAL stage 2a imaging biomarker characterization/pre-qualification study

Objectives

We aim to characterize the serial quantitative apparent diffusion coefficient (ADC) changes of the target disease volume using diffusion-weighted imaging (DWI) acquired weekly during radiation therapy (RT) on a 1.5 T MR-Linac and correlate these changes with tumor response and oncologic outcomes for head and neck squamous cell carcinoma (HNSCC) patients as part of a programmatic R-IDEAL biomarker characterization effort.

Methods

Thirty patients with HNSCC who received curative-intent RT at MD Anderson Cancer Center, were included. Baseline and weekly MRI were obtained, and various ADC parameters were extracted from the regions of interest (ROIs). Baseline and weekly ADC parameters were correlated with response during and after RT, and the recurrence using the Mann-Whitney U test. The Wilcoxon signed-rank test was used to compare the weekly ADC versus baseline values. Weekly volumetric changes (Δvolume) for each ROI were correlated with ΔADC using Spearman's Rho test. Recursive partitioning analysis (RPA) identified the optimal ΔADC threshold associated with different oncologic outcomes.

Results

There was a significant rise in all ADC parameters at different time points of RT compared to baseline for both gross primary disease (GTV-P) and gross nodal disease volumes (GTV-N). The increased ADC values for GTV-P were statistically significant only for primary tumors achieving complete remission (CR) during RT. RPA identified GTV-P ΔADC 5th percentile > 13% at the mid-RT as the most significant parameter associated with primary tumors' CR during RT (p < 0.001). There was a significant decrease in residual volume of both GTV-P & GTV-N throughout the course of RT. A significant negative correlation between mean ΔADC and Δvolume for GTV-P at the 3rd and 4th week of RT was detected (r = -0.39, p = 0.044 & r = -0.45, p = 0.019, respectively).

Conclusion

Assessment of ADC kinetics at regular intervals throughout RT seems to be correlated with RT response. Further studies with larger cohorts and multi-institutional data are needed for validation of ΔADC as a model for prediction of response to RT.

Longitudinal diffusion and volumetric kinetics of head and neck cancer magnetic resonance on a 1.5T MR-Linear accelerator hybrid system: A prospective R-IDEAL Stage 2a imaging biomarker characterization/ pre-qualification study

Objectives

We aim to characterize the serial quantitative apparent diffusion coefficient (ADC) changes of the target disease volume using diffusion-weighted imaging (DWI) acquired weekly during radiation therapy (RT) on a 1.5T MR-Linac and correlate these changes with tumor response and oncologic outcomes for head and neck squamous cell carcinoma (HNSCC) patients as part of a programmatic R-IDEAL biomarker characterization effort.

Methods

Thirty patients with pathologically confirmed HNSCC who received curative-intent RT at the University of Texas MD Anderson Cancer Center, were included in this prospective study. Baseline and weekly Magnetic resonance imaging (MRI) (weeks 1-6) were obtained, and various ADC parameters (mean, 5 th , 10 th , 20 th , 30 th , 40 th , 50 th , 60 th , 70 th , 80 th , 90 th and 95 th percentile) were extracted from the target regions of interest (ROIs). Baseline and weekly ADC parameters were correlated with response during RT, loco-regional control, and the development of recurrence using the Mann-Whitney U test. The Wilcoxon signed-rank test was used to compare the weekly ADC versus baseline values. Weekly volumetric changes (Δvolume) for each ROI were correlated with ΔADC using Spearman's Rho test. Recursive partitioning analysis (RPA) was performed to identify the optimal ΔADC threshold associated with different oncologic outcomes.

Results

There was an overall significant rise in all ADC parameters during different time points of RT compared to baseline values for both gross primary disease volume (GTV-P) and gross nodal disease volumes (GTV-N). The increased ADC values for GTV-P were statistically significant only for primary tumors achieving complete remission (CR) during RT. RPA identified GTV-P ΔADC 5 th percentile >13% at the 3 rd week of RT as the most significant parameter associated with CR for primary tumor during RT (p <0.001). Baseline ADC parameters for GTV-P and GTV-N didn't significantly correlate with response to RT or other oncologic outcomes. There was a significant decrease in residual volume of both GTV-P & GTV-N throughout the course of RT. Additionally, a significant negative correlation between mean ΔADC and Δvolume for GTV-P at the 3 rd and 4 th week of RT was detected (r = -0.39, p = 0.044 & r = -0.45, p = 0.019, respectively).

Conclusion

Assessment of ADC kinetics at regular intervals throughout RT seems to be correlated with RT response. Further studies with larger cohorts and multi-institutional data are needed for validation of ΔADC as a model for prediction of response to RT.

Image guidance and positioning accuracy in clinical practice: influence of positioning errors and imaging dose on the real dose distribution for head and neck cancer treatment

BACKGROUND

Modern radiotherapy offers the possibility of highly accurate tumor treatment. To benefit from this precision at its best, regular positioning verification is necessary. By the use of image-guided radiotherapy and the application of safety margins the influence of positioning inaccuracies can be counteracted. In this study the effect of additional imaging dose by set-up verification is compared with the effect of dose smearing by positioning inaccuracies for a collective of head-and-neck cancer patients.

METHODS

This study is based on treatment plans of 40 head-and-neck cancer patients. To evaluate the imaging dose several image guidance scenarios with different energies, techniques and frequencies were simulated and added to the original plan. The influence of the positioning inaccuracies was assessed by the use of real applied table shifts for positioning. The isocenters were shifted back appropriately to these values to simulate that no positioning correction had been performed. For the single fractions the shifted plans were summed considering three different scenarios: The summation of only shifted plans, the consideration of the original plan for the fractions with set-up verification, and the addition of the extra imaging dose to the latter. For both effects (additional imaging dose and dose smearing), plans were analyzed and compared considering target coverage, sparing of organs at risk (OAR) and normal tissue complication probability (NTCP).

RESULTS

Daily verification of the patient positioning using 3D imaging with MV energies result in non-negligible high doses. kV imaging has only marginal influence on plan quality, primarily related to sparing of organs at risk, even with daily 3D imaging. For this collective, sparing of organs at risk and NTCP are worse due to potential positioning errors.

CONCLUSION

Regular set-up verification is essential for precise radiation treatment. Relating to the additional dose, the use of kV modalities is uncritical for any frequency and technique. Dose smearing due to positioning errors for this collective mainly resulted in a decrease of OAR sparing. Target coverage also suffered from the positioning inaccuracies, especially for individual patients. Taking into account both examined effects the relevance of an extensive IGRT is clearly present, even at the expense of additional imaging dose and time expenditure.

Evaluation of a deformable registration algorithm for subsequent lung computed tomography imaging during radiochemotherapy

PURPOSE

Rating both a lung segmentation algorithm and a deformable image registration (DIR) algorithm for subsequent lung computed tomography (CT) images by different evaluation techniques. Furthermore, investigating the relative performance and the correlation of the different evaluation techniques to address their potential value in a clinical setting.

METHODS

Two to seven subsequent CT images (69 in total) of 15 lung cancer patients were acquired prior, during, and after radiochemotherapy. Automated lung segmentations were compared to manually adapted contours. DIR between the first and all following CT images was performed with a fast algorithm specialized for lung tissue registration, requiring the lung segmentation as input. DIR results were evaluated based on landmark distances, lung contour metrics, and vector field inconsistencies in different subvolumes defined by eroding the lung contour. Correlations between the results from the three methods were evaluated.

RESULTS

Automated lung contour segmentation was satisfactory in 18 cases (26%), failed in 6 cases (9%), and required manual correction in 45 cases (66%). Initial and corrected contours had large overlap but showed strong local deviations. Landmark-based DIR evaluation revealed high accuracy compared to CT resolution with an average error of 2.9 mm. Contour metrics of deformed contours were largely satisfactory. The median vector length of inconsistency vector fields was 0.9 mm in the lung volume and slightly smaller for the eroded volumes. There was no clear correlation between the three evaluation approaches.

CONCLUSIONS

Automatic lung segmentation remains challenging but can assist the manual delineation process. Proven by three techniques, the inspected DIR algorithm delivers reliable results for the lung CT data sets acquired at different time points. Clinical application of DIR demands a fast DIR evaluation to identify unacceptable results, for instance, by combining different automated DIR evaluation methods.

A machine learning tool for re-planning and adaptive RT: A multicenter cohort investigation

PURPOSE

To predict patients who would benefit from adaptive radiotherapy (ART) and re-planning intervention based on machine learning from anatomical and dosimetric variations in a retrospective dataset.

MATERIALS AND METHODS

90 patients (pts) treated for head-neck cancer (H&N) formed a multicenter data-set. 41 H&N pts (45.6%) were considered for learning; 49 pts (54.4%) were used to test the tool. A homemade machine-learning classifier was developed to analyze volume and dose variations of parotid glands (PG). Using deformable image registration (DIR) and GPU, patients' conditions were analyzed automatically. Support Vector Machines (SVM) was used for time-series evaluation. "Inadequate" class identified patients that might benefit from replanning. Double-blind evaluation by two radiation oncologists (ROs) was carried out to validate day/week selected for re-planning by the classifier.

RESULTS

The cohort was affected by PG mean reduction of 23.7±8.8%. During the first 3weeks, 86.7% cases show PG deformation aligned with predefined tolerance, thus not requiring re-planning. From 4th week, an increased number of pts would potentially benefit from re-planning: a mean of 58% of cases, with an inter-center variability of 8.3%, showed "inadequate" conditions. 11% of cases showed "bias" due to DIR and script failure; 6% showed "warning" output due to potential positioning issues. Comparing re-planning suggested by tool with recommended by ROs, the 4th week seems the most favorable time in 70% cases.

CONCLUSIONS

SVM and decision-making tool was applied to overcome ART challenges. Pts would benefit from ART and ideal time for re-planning intervention was identified in this retrospective analysis.