Engineering topics

Stephans, K

Publications and source records attributed to Stephans, K.

5 records

DOE OSTI2016

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported to R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-101: Improved CT to CBCT Deformable Registration Accuracy by Incorporating Multiple CBCTs

Purpose: Combining prior day CBCT contours with STAPLE was previously shown to improve automated prostate contouring. These accurate STAPLE contours are now used to guide the planning CT to pre-treatment CBCT deformable registration. Methods: Six IGRT prostate patients with daily kilovoltage CBCT had their original planning CT and 9 CBCTs contoured by the same physician. These physician contours for the planning CT and each prior CBCT are deformed to match the current CBCT anatomy, producing multiple contour sets. These sets are then combined using STAPLE into one optimal set (e.g. for day 3 CBCT, combine contours produced using the plan plus day 1 and 2 CBCTs). STAPLE computes a probabilistic estimate of the true contour from this collection of contours by maximizing sensitivity and specificity. The deformation field from planning CT to CBCT registration is then refined by matching its deformed contours to the STAPLE contours. ADMIRE (Elekta Inc.) was used for this. The refinement does not force perfect agreement of the contours, typically Dice’s Coefficient (DC) of > 0.9 is obtained, and the image difference metric remains in the optimization of the deformable registration. Results: The average DC between physician delineated CBCT contours and deformed planning CT contours for the bladder, rectum and prostate was 0.80, 0.79 and 0.75, respectively. The accuracy significantly improved to 0.89, 0.84 and 0.84 (P<0.001 for all) when using the refined deformation field. The average time to run STAPLE with five scans and refine the planning CT deformation was 66 seconds on a Telsa K20c GPU. Conclusion: Accurate contours generated from multiple CBCTs provided guidance for CT to CBCT deformable registration, significantly improving registration accuracy as measured by contour DC. A more accurate deformation field is now available for transferring dose or electron density to the CBCT for adaptive planning. Research grant from Elekta.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-513: Investigating Dose of Internal Target Volume After Correcting for Tissue Heterogeneity in SBRT Lung Plans with Homogeneity Calculation

Purpose It was recommended to use the prescription of 54 Gy/3 with heterogeneity corrections for previously established dose scheme of 60 Gy/3 with homogeneity calculation. This study is to investigate dose coverage for the internal target volume (ITV) with and without heterogeneity correction. Methods Thirty patients who received stereotactic body radiotherapy (SBRT) to a dose of 60 Gy in 3 fractions with homogeneous planning for early stage non-small-cell lung cancer (NSCLC) were selected. ITV was created either from 4DCT scans or a fusion of multi-phase respiratory scans. Planning target volume (PTV) was a 5 mm expansion of the ITV. For this study, we recalculated homogeneous clinical plans using heterogeneity corrections with monitor units set as clinically delivered. All plans were calculated with 3 mm dose grids and collapsed cone convolution algorithm. To account for uncertainties from tumor delineation and image-guided radiotherapy, a structure ITV2mm was created by expanding ITV with 2 mm margins. Dose coverage to the PTV, ITV and ITV2mm were compared with a student paired t-test. Results With heterogeneity corrections, the PTV V60Gy decreased by 10.1% ± 18.4% (p<0.01) while the maximum dose to the PTV increased by 3.7 ± 4.3% (p<0.01). With and without corrections, D99% was 65.8 ± 4.0 Gy and 66.7 ± 4.8 Gy (p=0.15) for the ITV, and 63.9 ± 3.4 Gy and 62.9 ± 4.6 Gy for the ITV2mm (p=0.22), respectively. The mean dose to the ITV and ITV2mm increased 3.6% ± 4.7% (p<0.01) and 2.3% ± 5.2% (p=0.01) with heterogeneity corrections. Conclusion After heterogeneity correction, the peripheral coverage of the PTV decreased to approximately 54 Gy, but D99% of the ITV and ITV2mm was unchanged and the mean dose to the ITV and ITV2mm was increased. Clinical implication of these results requires more investigation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-F-BRD-16: Under Dose Regions Recalculated by Monte Carlo Cannot Predict the Local Failure for NSCLC Patients Treated with SBRT

Purpose: To investigate whether Monte Carlo (MC) recalculated dose distributions can predict the geometric location of the recurrence for nonsmall cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT). Methods: Thirty NSCLC patients with local recurrence were retrospectively selected for this study. The recurred gross target volumes (rGTV) were delineated on the follow-up CT/PET images and then rigidly transferred via imaging fusion to the original planning CTs. Failure pattern was defined according to the overlap between the rGTV and planning GTV (pGTV) as: (a) in-field failure (≥80%), (b) marginal failure (20%–80%), and (c) out-of-field failure (≤20%). All clinical plans were calculated initially with pencil beam (PB) with or without heterogeneity correction dependent of protocols. These plans were recalculated with MC with heterogeneity correction. Because of non-uniform dose distributions in the rGTVs, the rGTVs were further divided into four regions: inside the pGTV (GTVin), inside the PTV (PTVin), outside the pGTV (GTVout), and outside the PTV (PTVout). The mean doses to these regions were reported and analyzed separately. Results: Among 30 patients, 10 patients had infield recurrences, 15 marginal and 5 out-of-field failures. With MC calculations, D95 and D99 of the PTV were reduced by (10.6 ± 7.4)% and (11.7 ± 7.9)%. The average MC calculated mean doses of GTVin, GTVout, PTVin and PTVout were 48.2 ± 5.3 Gy, 48.2 ± 5.5 Gy, 46.3 ± 6.2 Gy and 46.6 ± 5.6 Gy, respectively. No significant dose differences between GTVin and GTVout (p=0.65), PTVin and PTVout (p=0.19) were observed, using the paired students t-test. Conclusion: Although the PB calculations underestimated the tumor target doses, the geometric location of the recurrence did not correlate with the mean doses of subsections of the recurrent GTV. Under dose regions recalculated by MC cannot predict the local failure for NSCLC patients treated with SBRT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-E-J-178: A Normalization Method Can Remove Discrepancy in Ventilation Function Due to Different Breathing Patterns

Purpose: To develop a normalization method to remove discrepancy in ventilation function due to different breathing patterns. Methods: Twenty five early stage non-small cell lung cancer patients were included in this study. For each patient, a ten phase 4D-CT and the voluntarily maximum inhale and exhale CTs were acquired clinically and retrospectively used for this study. For each patient, two ventilation maps were calculated from voxel-to-voxel CT density variations from two phases of the quiet breathing and two phases of the extreme breathing. For the quiet breathing, 0% (inhale) and 50% (exhale) phases from 4D-CT were used. An in-house tool was developed to calculate and display the ventilation maps. To enable normalization, the whole lung of each patient was evenly divided into three parts in the longitude direction at a coronal image with a maximum lung cross section. The ratio of cumulated ventilation from the top one-third region to the middle one-third region of the lung was calculated for each breathing pattern. Pearson's correlation coefficient was calculated on the ratios of the two breathing patterns for the group. Results: For each patient, the ventilation map from the quiet breathing was different from that of the extreme breathing. When the cumulative ventilation was normalized to the middle one-third of the lung region for each patient, the normalized ventilation functions from the two breathing patterns were consistent. For this group of patients, the correlation coefficient of the normalized ventilations for the two breathing patterns was 0.76 (p < 0.01), indicating a strong correlation in the ventilation function measured from the two breathing patterns. Conclusion: For each patient, the ventilation map is dependent of the breathing pattern. Using a regional normalization method, the discrepancy in ventilation function induced by the different breathing patterns thus different tidal volumes can be removed.

60 APPLIED LIFE SCIENCES↗