An Qin

Redefine the role of range shifter in treating bilateral head and neck cancer in the era of Intensity Modulated Proton Therapy

The use of proton beam therapy has been increasing rapidly. As the Pencil Beam Scanning (PBS) technology has become commercially available in the recent 10 years, nearly all the new proton centers under the contract or constructions are now configured with only PBS technique. Compared to passive‐scattering technique, Intensity Modulated Proton Therapy (IMPT) based on PBS technique allows for creating a more conformal dose distribution to target volume while resulting in a less body integral dose and ultimately less neutron dose. For a majority of the current commercial proton beam systems, the minimum proton beam energy ranges from 70 to 100 MeV which is about 4.1–7.5 cm in water‐equivalent thickness (WET). In order to treat superficial target volume such as patients with head and neck cancer (HNC), and brain tumors, a range shifter (RS) is normally needed to attenuate the proton beam energy.3–5 The RS which is normally composed of slab of plastics such as acrylonitrile butadiene styrene (ABS) and polyethylene 3–5 which broadens the proton beams due to the secondary scattering. In order to reduce the scattering and keep a smaller spot size, the air gap between the gantry nozzle and patients skin must be reduced. Thus, the proton gantry nozzle causes potential collision concerns with the patients body especially in the vicinity of the shoulder region during the treatment of HNC. In order to avoid using RS, Both et al. introduced a rigid U‐shaped bolus placed close to the patients head and neck region as an alternative. The advantage was to reduce the air gap and therefore the proton beam was able to maintain the spot size. However, as a trade‐off, it also introduced additional workload for the therapists to mount this heavy U‐shaped bolus on the table every time during the Computed Tomography (CT) simulation as well as to the couch following the daily imaging alignment prior to the radiation delivery. Another challenge is the size of bolus which needs to be carefully selected to fit patients anatomy. Additionally, it also introduces WET inhomogeneity at the edge of bolus near the connection area to the couch top which limits the proton beam angle selections due to the range uncertainties. It is very difficult to model a continuous moving RS configuration due to the secondary proton scattering. Shen et al. and Li et al. have been addressing these issues using analytical model as well as an in‐house Monte Carlos simulation. Moreover, commissioning of a RS also requires extensive measurements. To overcome such limitations in proton beam therapy, air gap <10 cm between the patient body and RS is recommended in order to minimize the dose calculation error. In addition, larger air gap results in a larger spot size which makes robust coverage of the CTV while sparing critical structures less likely. Thus, to minimize such air gap, the potential collisions between the gantry nozzle and patients shoulder became a concern in treating bilateral HNC. With so many disadvantages and inconvenient clinical workflow with using RS, it is critical to evaluate the role of RS and possibly eliminating it in treating bilateral HNC patient using IMPT. Normally, three to four field IMPT with RS were used in the bilateral HNC treatment. We hypothesize that by increasing the degree of freedom or beam angle directions, IMPT is able to deliver a robust prescription dose to the bilateral HNC target without

A feasibility study of intrafractional tumor motion estimation based on 4D‐CBCT using diaphragm as surrogate

Abstract Purpose To investigate the intrafractional stability of the motion relationship between the diaphragm and tumor, as well as the feasibility of using diaphragm motion to estimate lung tumor motion. Methods Eighty‐five paired (pre and posttreatment) daily 4D‐CBCT images were obtained from 20 lung cancer patients who underwent SBRT. Bony registration was performed between the pre‐ and post‐CBCT images to exclude patient body movement. The end‐exhalation phase image of the pre‐CBCT image was selected as the reference image. Tumor positions were obtained for each phase image using contour‐based translational alignments. Diaphragm positions were obtained by translational alignment of its apex position. A linear intrafraction model was constructed using regression analysis performed between the diaphragm and tumor positions manifested on the pretreatment 4D‐CBCT images. By applying this model to posttreatment 4D‐CBCT images, the tumor positions were estimated from posttreatment 4D‐CBCT diaphragm positions and compared with measured values. A receiver operating characteristic (ROC) test was performed to determine a suitable indicator for predicting the estimate accuracy of the linear model. Results Using the linear model, per‐phase position, mean position, and excursion estimation errors were 1.12 ± 0.99 mm, 0.97 ± 0.88 mm, and 0.79 ± 0.67 mm, respectively. Intrafractional per‐phase tumor position estimation error, mean position error, and excursion error were within 3 mm 95%, 96%, and 99% of the time, respectively. The residual sum of squares (RSS) determined from pretreatment images achieved the largest prediction power for the tumor position estimation error (discrepancy < 3 mm) with an Area Under ROC Curve (AUC) of 0.92 (P < 0.05). Conclusion Utilizing the relationship between diaphragm and tumor positions on the pretreatment 4D‐CBCT image, intrafractional tumor positions were estimated from intrafractional diaphragm positions. The estimation accuracy can be predicted using the RSS obtained from the pretreatment 4D‐CBCT image.

SU-F-J-192: A Quick and Effective Method to Validate Patient's Daily Setup and Geometry Changes Prior to Proton Treatment Delivery Based On Water Equivalent Thickness Projection Imaging (WETPI) for Head Neck Cancer (HNC) Patient

PURPOSE With the implementation of Cone-beam Computed-Tomography (CBCT) in proton treatment, we introduces a quick and effective tool to verify the patients daily setup and geometry changes based on the Water-Equivalent-Thickness Projection-Image(WETPI) from individual beam angle. METHODS A bilateral head neck cancer(HNC) patient previously treated via VMAT was used in this study. The patient received 35 daily CBCT during the whole treatment and there is no significant weight change. The CT numbers of daily CBCTs were corrected by mapping the CT numbers from simulation CT via Deformable Image Registration(DIR). IMPT plan was generated using 4-field IMPT robust optimization (3.5% range and 3mm setup uncertainties) with beam angle 60, 135, 300, 225 degree. WETPI within CTV through all beam directions were calculated. 3%/3mm gamma index(GI) were used to provide a quantitative comparison between initial sim-CT and mapped daily CBCT. To simulate an extreme case where human error is involved, a couch bar was manually inserted in front of beam angle 225 degree of one CBCT. WETPI was compared in this scenario. RESULTS The average of GI passing rate of this patient from different beam angles throughout the treatment course is 91.5 ± 8.6. In the cases with low passing rate, it was found that the difference between shoulder and neck angle as well as the head rest often causes major deviation. This indicates that the most challenge in treating HNC is the setup around neck area. In the extreme case where a couch bar is accidently inserted in the beam line, GI passing rate drops to 52 from 95. CONCLUSION WETPI and quantitative gamma analysis give clinicians, therapists and physicists a quick feedback of the patients setup accuracy or geometry changes. The tool could effectively avoid some human errors. Furthermore, this tool could be used potentially as an initial signal to trigger plan adaptation.

SU-F-J-60: Impact of DIR Method On Treatment Dose Wrapping

PURPOSE To investigate clinical relevant discrepancy between doses wrapped by pure image and biomechanical model based deformable registration (DIR). METHODS 12 patients, each with a CT pair, were included (5 H&N, 5 Prostate and 2 Lung). A research DIR tool (ADMRIE) was utilized for image based DIR (IMG-DIR). To assure organ matching, contour constrain was applied for prostate patients. Tetrahedron meshes were generated for organs (parotid, bladder, rectum and lung). Deformable vector fields (DVF) from IMG-DIR were interpolated to the surface node of meshes as boundary condition. Biomechanical models using finite element modeling (FEM) were generated by assigning organ specific material properties. The models were then input into a FEM tool (ABAQUS) to calculate internal deformation (FEM-DIR). The output volume node displacements were then interpolated to image grids to get refined DVF. The IMRT treatment doses were wrapped by both DVFs to pre-treatment CTs. DVF vector distance (DVF-VD) was calculated on each organ. Dose parameters were calculated for wrapped doses and normalized to pretreatment plan. Gamma passing rate (GPR) was calculated with IMG-DIR dose as reference. Correlation was evaluated between parotid shrinkage and DVF-VD /dose-discrepancy. RESULTS H&N:parotid volume with DVF-VD (>1.5mm) was 6.5±4.7%. The normalized mean dose difference (NMDD) of IMG-DIR and FEM-DIR was -0.8±1.5%, with range (-4.7% to 1.5%). 2mm/2% GPR was 99.0±1.4%. Moderate correlation was found between parotid shrinkage and DVF-VD (R=0.61)/NMDD (R=0.68). Prostate:bladder had a NMDD of -9.9±9.7%, with FEM-DIR wrapped dose systematically higher. Only minor deviation was observed for rectum NMDD (0.5±1.1%). 3mm/3% GPR of bladder and rectum were 81.9±12.0% and 93.1±4.3%, respectively. One of lung patients had 3.9%NMDD and 3mm/3%GPR of 95.2% inside lung. CONCLUSION Impact of DIR methods on treatment dose wrapping is patient and organ specific. Generally, bigger organ with larger volume variation leads to greater dose wrapping uncertainty.Acknowledgement:Elekta research grant support. This work was supported by research funding from Elekta.

SU-F-T-205: Effectiveness of Robust Treatment Planning to Account for Inter- Fractional Variation in Intensity Modulated Proton Therapy for Head Neck Cancer

PURPOSE To evaluate the potential benefits of robust optimization in intensity modulated proton therapy(IMPT) treatment planning to account for inter-fractional variation for Head Neck Cancer(HNC). METHODS One patient with bilateral HNC previous treated at our institution was used in this study. Ten daily CBCTs were selected. The CT numbers of the CBCTs were corrected by mapping the CT numbers from simulation CT via Deformable Image Registration. The planning target volumes(PTVs) were defined by a 3mm expansion from clinical target volumes(CTVs). The prescription was 70Gy, 54Gy to CTV1, CTV2, and PTV1, PTV2 for robust optimized(RO) and conventionally optimized(CO) plans respectively. Both techniques were generated by RayStation with the same beam angles: two anterior oblique and two posterior oblique angles. The similar dose constraints were used to achieve 99% of CTV1 received 100% prescription dose while kept the hotspots less than 110% of the prescription. In order to evaluate the dosimetric result through the course of treatment, the contours were deformed from simulation CT to daily CBCTs, modified, and approved by a radiation oncologist. The initial plan on the simulation CT was re-replayed on the daily CBCTs followed the bony alignment. The target coverage was evaluated using the daily doses and the cumulative dose. RESULTS Eight of 10 daily deliveries with using RO plan achieved at least 95% prescription dose to CTV1 and CTV2, while still kept maximum hotspot less than 112% of prescription compared with only one of 10 for the CO plan to achieve the same standards. For the cumulative doses, the target coverage for both RO and CO plans was quite similar, which was due to the compensation of cold and hot spots. CONCLUSION Robust optimization can be effectively applied to compensate for target dose deficit caused by inter-fractional target geometric variation in IMPT treatment planning.

SU-F-J-86: Method to Include Tissue Dose Response Effect in Deformable Image Registration

PURPOSE Organ changes shape and size during radiation treatment due to both mechanical stress and radiation dose response. However, the dose response induced deformation has not been considered in conventional deformable image registration (DIR). A novel DIR approach is proposed to include both tissue elasticity and radiation dose induced organ deformation. METHODS Assuming that organ sub-volume shrinkage was proportional to the radiation dose induced cell killing/absorption, the dose induced organ volume change was simulated applying virtual temperature on each sub-volume. Hence, both stress and heterogeneity temperature induced organ deformation. Thermal stress finite element method with organ surface boundary condition was used to solve deformation. Initial boundary correspondence on organ surface was created from conventional DIR. Boundary condition was updated by an iterative optimization scheme to minimize elastic deformation energy. The registration was validated on a numerical phantom. Treatment dose was constructed applying both the conventional DIR and the proposed method using daily CBCT image obtained from HN treatment. RESULTS Phantom study showed 2.7% maximal discrepancy with respect to the actual displacement. Compared with conventional DIR, subvolume displacement difference in a right parotid had the mean±SD (Min, Max) to be 1.1±0.9(-0.4∼4.8), -0.1±0.9(-2.9∼2.4) and -0.1±0.9(-3.4∼1.9)mm in RL/PA/SI directions respectively. Mean parotid dose and V30 constructed including the dose response induced shrinkage were 6.3% and 12.0% higher than those from the conventional DIR. CONCLUSION Heterogeneous dose distribution in normal organ causes non-uniform sub-volume shrinkage. Sub-volume in high dose region has a larger shrinkage than the one in low dose region, therefore causing more sub-volumes to move into the high dose area during the treatment course. This leads to an unfavorable dose-volume relationship for the normal organ. Without including this effect in DIR, treatment dose in normal organ could be underestimated affecting treatment evaluation and planning modification. Acknowledgement: Partially Supported by Elekta Research Grant.

TH‐A‐BRA‐04: Evaluation of Three IGRT Approaches for Prostate Cancer Treatment

Purpose: To evaluate two online IGRT and one hybrid adaptive modification for prostate cancertreatment with onboard CBCTimager.Methods: Two online IGRT and one hybrid adaptive modification were simulated and evaluated retrospectively using daily CBCTimages obtained from 5 prostate cancer patients treated with total dose 64Gy in 20 fractions. For each daily treatment, two CBCTs obtained at the pre‐ and post‐treatment delivery were used in the study. Online IGRT techniques include (1) Online‐ correction: a pre‐treatment IMRT plan with 3mm CTV‐to‐PTV margin was delivered following the CBCTimaging and online target position correction; and (2) Online‐planning: an online inverse plan designed on the pre‐ treatmentCBCTimage with 3mm target margin was accomplished and delivered. The Hybrid‐adaptation consists of the online prostate position correction and delivery of a pre‐treatment IMRT plan with no target margin for the first week of the treatment, and an offline adaptive inverse planning with using the planning CT and the first week of post‐treatment CBCTimages for the remaining treatment.Treatment dose for all 3 approaches were constructed using all the post‐treatment CBCTimages. Evaluations were all performed using the treatment dose distribution in organs of interest for all patients. Results: The minimal delivered dose (D99) in CTV (prostate + seminal vesicle) is in the range of [51.6, 65.6]Gy for Online‐ correction; [63.2, 66.1]Gy for Online‐planning; and [62.8, 66.1]Gy for the Hybrid‐adaptation. The rectal volume with 62.6Gy, V62.6, for Online‐ correction, Online‐planning, Hybrid‐adaptation are 0.7+/−1.0%, 0.4+/−0.2%, 0.5+/−1.0%; the rectal V59.4 are 2.1+/−1.8%, 1.5+/‐1.1%, 1.6+/−1.9%; and V56.5 are 4.0+/−3.2%, 3.0+/−2.2%, 3.5+/−3.2%. The bladder volume dose, V64.1, are 2.3+/−2.2%, 0.5+/−0.6%, 0.4+/−0.3%, and V59.4 are 5.2+/−3.6%, 2.0+/−1.1%, 1.6+/−0.8% respectively for the 3 approaches. Conclusions: Both Online‐planning and Hybrid‐adaptation achieved comparable target coverage and normal tissue sparing, and were superior to Online‐correction. However, Hybrid‐adaptation is more efficiency in clinical practice. This research was partially supported by Elekta.