Engineering topics

Deasy, J

Publications and source records attributed to Deasy, J.

At least 19 records

DOE OSTI2016

SU-C-202-04: Adapting Biologically Optimized Dose Escalation Based On Mid-Treatment PET/CT for Non-Small-Cell Lung Cancer

Purpose: To develop a biological modeling strategy which incorporates the response observed on the mid-treatment PET/CT into a dose escalation design for adaptive radiotherapy of non-small-cell lung cancer. Method: FDG-PET/CT was acquired midway through standard fractionated treatment and registered to pre-treatment planning PET/CT to evaluate radiation response of lung cancer. Each mid-treatment PET voxel was assigned the median SUV inside a concentric 1cm-diameter sphere to account for registration and imaging uncertainties. For each voxel, the planned radiation dose, pre- and mid-treatment SUVs were used to parameterize the linear-quadratic model, which was then utilized to predict the SUV distribution after the full prescribed dose. Voxels with predicted post-treatment SUV≥2 were identified as the resistant target (response arm). An adaptive simultaneous integrated boost was designed to escalate dose to the resistant target as high as possible, while keeping prescription dose to the original target and lung toxicity intact. In contrast, an adaptive target volume was delineated based only on the intensity of mid-treatment PET/CT (intensity arm), and a similar adaptive boost plan was optimized. The dose escalation capability of the two approaches was compared. Result: Images of three patients were used in this planning study. For one patient, SUV prediction indicated complete response and no necessary dose escalation. For the other two, resistant targets defined in the response arm were multifocal, and on average accounted for 25% of the pre-treatment target, compared to 67% in the intensity arm. The smaller response arm targets led to a 6Gy higher mean target dose in the adaptive escalation design. Conclusion: This pilot study suggests that adaptive dose escalation to a biologically resistant target predicted from a pre- and mid-treatment PET/CT may be more effective than escalation based on the mid-treatment PET/CT alone. More plans and ultimately clinical protocols are needed to validate this approach. MSKCC has a research agreement with Varian Medical System.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-D-204-06: Integration of Machine Learning and Bioinformatics Methods to Analyze Genome-Wide Association Study Data for Rectal Bleeding and Erectile Dysfunction Following Radiotherapy in Prostate Cancer

Purpose: We investigated whether integration of machine learning and bioinformatics techniques on genome-wide association study (GWAS) data can improve the performance of predictive models in predicting the risk of developing radiation-induced late rectal bleeding and erectile dysfunction in prostate cancer patients. Methods: We analyzed a GWAS dataset generated from 385 prostate cancer patients treated with radiotherapy. Using genotype information from these patients, we designed a machine learning-based predictive model of late radiation-induced toxicities: rectal bleeding and erectile dysfunction. The model building process was performed using 2/3 of samples (training) and the predictive model was tested with 1/3 of samples (validation). To identify important single nucleotide polymorphisms (SNPs), we computed the SNP importance score, resulting from our random forest regression model. We performed gene ontology (GO) enrichment analysis for nearby genes of the important SNPs. Results: After univariate analysis on the training dataset, we filtered out many SNPs with p>0.001, resulting in 749 and 367 SNPs that were used in the model building process for rectal bleeding and erectile dysfunction, respectively. On the validation dataset, our random forest regression model achieved the area under the curve (AUC)=0.70 and 0.62 for rectal bleeding and erectile dysfunction, respectively. We performed GO enrichment analysis for the top 25%, 50%, 75%, and 100% SNPs out of the select SNPs in the univariate analysis. When we used the top 50% SNPs, more plausible biological processes were obtained for both toxicities. An additional test with the top 50% SNPs improved predictive power with AUC=0.71 and 0.65 for rectal bleeding and erectile dysfunction. A better performance was achieved with AUC=0.67 when age and androgen deprivation therapy were added to the model for erectile dysfunction. Conclusion: Our approach that combines machine learning and bioinformatics techniques enabled designing better models and identifying more plausible biological processes associated with the outcomes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-253: Volumetric Comparison Between 4D CT Amplitude and Phase Binning Mode

Purpose: Motion artifact in 4DCT images can affect radiation treatment quality. To identify the most robust and accurate binning method, we compare the volume difference between targets delineated on amplitude and phase binned 4DCT scans. Methods: Varian RPM system and CT scanner were used to acquire 4DCTs of a Quasar phantom with embedded cubic and spherical objects having superior-inferior motion. Eight patients’ respiration waveforms were used to drive the phantom. The 4DCT scan was reconstructed into 10 phase and 10 amplitude bins (2 mm slices). A scan of the static phantom was also acquired. For each waveform, sphere and cube volumes were generated automatically on each phase using HU thresholding. Phase (amplitude) ITVs were the union of object volumes over all phase (amplitude) binned images. The sphere and cube volumes measured in the static phantom scan were V{sub sphere}=4.19cc and V{sub cube}=27.0cc. Volume difference (VD) and dice similarity coefficient (DSC) of the ITVs, and mean volume error (MVE) defined as the average target volume percentage difference between each phase image and the static image, were used to evaluate the performance of amplitude and phase binning. Results: Averaged over the eight breathing traces, the VD and DSC of the internal target volume (ITV) between amplitude and phase binning were 3.4%±3.2% (mean ± std) and 95.9%±2.1% for sphere; 2.1%±3.3% and 98.0% ±1.5% for cube, respectively.For all waveforms, the average sphere MVE of amplitude and phase binning was 6.5% ± 5.0% and 8.2%±6.3%, respectively; and the average cube MVE of amplitude and phase binning was 5.7%±3.5%and 12.9%±8.9%, respectively. Conclusion: ITV volume and spatial overlap as assessed by VD and DSC are similar between amplitude and phase binning. Compared to phase binning, amplitude binning results in lower MVE suggesting it is less susceptible to motion artifact.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-JeP2-06: Dosimetric and Workflow Evaluation of First Commercial Synthetic CT Software for Clinical Use in Pelvis

Purpose: evaluate a commercial synthetic CT (syn-CT) software for use in prostate radiotherapy Methods: Twenty prostate patients underwent CT and MR simulation scans in treatment position on a 3T Philips scanner. The MR protocol consisted of a T2w turbo spin-echo for soft tissue contrast, a 2D balanced-fast field echo (b-FFE) for fiducial identification, a dual-echo 3D FFE B0 map for distortion analysis and a 3D mDIXON FFE sequence to generate syn-CT. Two echoes are acquired during mDIXON scan, allowing water, fat, and in-phase images to be derived using the frequency shift of the fat and water protons. Tissues were classified as: air, adipose, water, trabecular/spongy bone and compact/cortical bone and assigned specific bulk HU values. Bone structures are segmented based on a pelvis bone atlas. Accuracy of syn-CT for patient treatment planning was analyzed by transferring the original plan and structures from the CT to syn-CT via rigid registration and recalculating dose. In addition, new IMRT plans were generated on the syn-CT using structures contoured on MR and transferred to the syn-CT. Accuracy of fiducial-based localization at the treatment machine performed using syn-CT or DRRs generated from syn-CT was assessed by comparing to orthogonal kV radiographs or CBCT. Results: Dosimetric comparison between CT and syn-CT was within 0.5% for all structures. The de-novo optimized plans generated on the syn-CT met our institutional clinical objectives for target and normal structures. Patient-induced susceptibility distortion based on B0 maps was within 1mm and 0.4 mm in the body and prostate. The rectal and bladder outlines on the syn-CT were deemed sufficient for assessing rectal and bladder filling on the CBCT at the time of treatment. CBCT localization showed a median error of < ±1 mm in LR, AP and SI direction. Conclusion: MRI derived syn-CT can be used clinically in MR-alone planning and treatment process for prostate. Drs. Deasy, Hunt and Tyagi have Master research agreement with Philips healthcare.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-JeP4-05: Effects of Irregular Respiratory Motion On the Positioning Accuracy of Moving Target with Free Breathing Cone-Beam Computerized Tomography

Purpose: Average or maximum intensity projection (AIP or MIP) images derived from 4DCT images are often used as a reference image for target alignment when free breathing Cone-beam CT (FBCBCT) is used for positioning a moving target at treatment. This method can be highly accurate if the patient has stable respiratory motion. However, a patient’s breathing pattern often varies irregularly. The purpose of this study is to investigate the effect of irregular respiration on the positioning accuracy of a moving target with FBCBCT. Methods: Eight patients’ respiratory motion curves were selected to drive a Quasar phantom with embedded cubic and spherical targets. A 4DCT of the moving phantom was acquired on a CT scanner (Philips Brilliance 16) equipped with a Varian RPM system. The phase binned 4DCT images and the corresponding MIP and AIP images were transferred into Eclipse for analysis. CBCTs of the phantom driven by the same breathing curves were acquired on a Varian TrueBeam and fused such that the zero positions of moving targets are the same on both CBCT and AIP images. The sphere and cube volumes and centrioid differences (alignment error) determined by MIP, AIP and FBCBCT images were compared. Results: Compared to the volume determined by FBCBCT, the volumes of cube and sphere in MIP images were 22.4%±8.8% and 34.2%±6.2% larger while the volumes in AIP images were 7.1%±6.2% and 2.7%±15.3% larger, respectively. The alignment errors for the cube and sphere with center-center matches between MIP and FBCBCT were 3.5±3.1mm and 3.2±2.3mm, and the alignment errors between AIP and FBCBCT were 2.1±2.6mm and 2.1±1.7mm, respectively. Conclusion: AIP images appear to be superior reference images than MIP images. However, irregular respiratory motions could compromise the positioning accuracy of a moving target if the target center-center match is used to align FBCBCT and AIP images.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-FG-202-09: Virtual IMRT QA Using Machine Learning: A Multi-Institutional Validation

Purpose: To validate a machine learning approach to Virtual IMRT QA for accurately predicting gamma passing rates using different QA devices at different institutions. Methods: A Virtual IMRT QA was constructed using a machine learning algorithm based on 416 IMRT plans, in which QA measurements were performed using diode-array detectors and a 3%local/3mm with 10% threshold. An independent set of 139 IMRT measurements from a different institution, with QA data based on portal dosimetry using the same gamma index and 10% threshold, was used to further test the algorithm. Plans were characterized by 90 different complexity metrics. A weighted poison regression with Lasso regularization was trained to predict passing rates using the complexity metrics as input. Results: In addition to predicting passing rates with 3% accuracy for all composite plans using diode-array detectors, passing rates for portal dosimetry on per-beam basis were predicted with an error <3.5% for 120 IMRT measurements. The remaining measurements (19) had large areas of low CU, where portal dosimetry has larger disagreement with the calculated dose and, as such, large errors were expected. These beams need to be further modeled to correct the under-response in low dose regions. Important features selected by Lasso to predict gamma passing rates were: complete irradiated area outline (CIAO) area, jaw position, fraction of MLC leafs with gaps smaller than 20 mm or 5mm, fraction of area receiving less than 50% of the total CU, fraction of the area receiving dose from penumbra, weighted Average Irregularity Factor, duty cycle among others. Conclusion: We have demonstrated that the Virtual IMRT QA can predict passing rates using different QA devices and across multiple institutions. Prediction of QA passing rates could have profound implications on the current IMRT process.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-AB-BRA-03: Atlas-Based Algorithms with Local Registration-Goodness Weighting for MRI-Driven Electron Density Mapping

Purpose: To develop image-analysis algorithms to synthesize CT with accurate electron densities for MR-only radiotherapy of head & neck (H&N) and pelvis anatomies. Methods: CT and 3T-MRI (Philips, mDixon sequence) scans were randomly selected from a pool of H&N (n=11) and pelvis (n=12) anatomies to form an atlas. All MRIs were pre-processed to eliminate scanner and patient-induced intensity inhomogeneities and standardize their intensity histograms. CT and MRI for each patient were then co-registered to construct CT-MRI atlases. For more accurate CT-MR fusion, bone intensities in CT were suppressed to improve the similarity between CT and MRI. For a new patient, all CT-MRI atlases are deformed onto the new patients’ MRI initially. A newly-developed generalized registration error (GRE) metric was then calculated as a measure of local registration accuracy. The synthetic CT value at each point is a 1/GRE-weighted average of CTs from all CT-MR atlases. For evaluation, the mean absolute error (MAE) between the original and synthetic CT (generated in a leave-one-out scheme) was computed. The planning dose from the original and synthetic CT was also compared. Results: For H&N patients, MAE was 67±9, 114±22, and 116±9 HU over the entire-CT, air and bone regions, respectively. For pelvis anatomy, MAE was 47±5 and 146±14 for the entire and bone regions. In comparison with MIRADA medical, an FDA-approved registration tool, we found that our proposed registration strategy reduces MAE by ∼30% and ∼50% over the entire and bone regions, respectively. GRE-weighted strategy further lowers MAE by ∼15% to ∼40%. Our primary dose calculation also showed highly consistent results between the original and synthetic CT. Conclusion: We’ve developed a novel image-analysis technique to synthesize CT for H&N and pelvis anatomies. Our proposed image fusion strategy and GRE metric help generate more accurate synthetic CT using locally more similar atlases (Support: Philips Healthcare). The research is supported by Philips HealthCare.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-AB-202-11: Radiobiological Modeling of Tumor Response During Radiotherapy Based On Pre-Treatment Dynamic PET Imaging Data

Purpose: To evaluate the ability of a multiscale radiobiological model of tumor response to predict mid-treatment hypoxia images, based on pretreatment imaging of perfusion and hypoxia with [18-F]FMISO dynamic PET and glucose metabolism with [18-F]FDG PET. Methods: A mechanistic tumor control probability (TCP) radiobiological model describing the interplay between tumor cell proliferation and hypoxia (Jeong et al., PMB 2013) was extended to account for intra-tumor nutrient heterogeneity, dynamic cell migration due to nutrient gradients, and stromal cells. This extended model was tested on 10 head and neck cancer patients treated with chemoradiotherapy, randomly drawn from a larger MSKCC protocol involving baseline and mid-therapy dynamic PET scans. For each voxel, initial fractions of proliferative and hypoxic tumor cells were obtained by finding an approximate solution to a system of linear equations relating cell fractions to voxel-level FDG uptake, perfusion (FMISO K{sub 1}) and hypoxia (FMISO k{sub 3}). The TCP model then predicted their evolution over time up until the mid treatment scan. Finally, the linear model was reapplied to predict each lesion’s median hypoxia level (k{sub 3}[med,sim]) which in turn was compared to the FMISO k{sub 3}[med] measured at mid-therapy. Results: The average k3[med] of the tumors in pre-treatment scans was 0.0035 min{sup −1}, with an inter-tumor standard deviation of σ[pre]=0.0034 min{sup −1}. The initial simulated k{sub 3}[med,sim] of each tumor agreed with the corresponding measurements within 0.1σ[pre]. In 7 out of 10 lesions, the mid-treatment k{sub 3}[med,sim] prediction agreed with the data within 0.3σ[pre]. The remaining cases corresponded to the most extreme relative changes in k{sub 3}[med]. Conclusion: This work presents a method to personalize the prediction of a TCP model using pre-treatment kinetic imaging data, and validates the modeling of radiotherapy response by predicting changes in median hypoxia values during treatment. Variations from predicted response may be a useful biomarker, which should be further explored. Partially supported by NIH grant #1 R01 CA157770-01A1 and a grant from Varian Corporation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-AB-207B-08: Exploring and Refining the QUANTEC Guideline to Reduce Severe Hyposalivation Following IMRT for Head and Neck Cancer

Purpose: The aim of this study was to investigate the usefulness of the QUANTEC guideline to prevent xerostomia after intensity-modulated radiotherapy (IMRT) for head and neck cancer (HNC) with respect to follow-up time. In addition, we explored alternative guidelines to further reduce xerostomia. Methods: The QUANTEC guideline suggests a mean dose to the contralateral (Dmeancontra) parotid<20 Gy, or Dmeancontra and Dmean to the ipsilateral parotid (Dmeanipsi)<25 Gy. Stimulated whole mouth saliva flow measurements (WMSFM) were conducted at a median of 11 (3–24) months for 63 patients treated with IMRT for HNC to a median dose of 70 Gy in 2006–2015. Severe hyposalivation/xerostomia was defined as WMSFM ≤25% post- relative to pre-RT. Patients were stratified into a <6m (xerostomia: 27% (n=15)), and a 6–24m (xerostomia: 19% (n=10)) follow-up group. Dose-response modeling was performed using logistic regression including Dmeancontra, or Dmeancontra and Dmeanipsi. The area under the receiver-operating characteristics curve (AUC) was used to assess discriminative ability, and the agreement between the estimated and observed rate of xerostomia was given by Spearman’s rank correlation coefficient (Rs), and related p-values. Results: Of the non-xerostomia patients, 65% (<6m) and 56% (6–24m) fulfilled Dmeancontra<20 Gy. The estimated and observed rate of xerostomia agreed at <6m (AUC=0.78; Rs=0.46; p=0.001), and was 28% at Dmeancontra=20 Gy. A smaller number of non-xerostomia patients fulfilled the two-gland guideline (33% (<6m) and 26% (6–24m)), but the AUC was higher than using Dmeancontra only (<6m: AUC=0.90; Rs=0.63; p<0.0001; 6–24m: AUC=0.84; Rs=0.25; p=0.08), and the following amendment of the two-gland guideline was suggested: (0.17*Dmeancontra+0.11*Dmeanipsi-8.13)<-1.60 (<6m), and (0.05*Dmeancontra+0.02*Dmeanipsi-3.10)<-1.60 (6–24m). Conclusion: The QUANTEC guideline is effective to prevent xerostomia <6m post-RT, but its usefulness is reduced at later follow-up times. The suggested amendment to the two-gland QUANTEC guideline should be further investigated in an independent cohort of HNC patients treated with IMRT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-FG-202-07: An MRI-Based Approach to Quantify Radiation-Induced Normal Tissue Injury Applied to Trismus After Head and Neck Cancer Radiotherapy

Purpose: The aim of this study was to investigate if quantitative MRI-derived metrics from four masticatory muscles could explain mouth-opening limitation/trismus following intensity-modulated radiotherapy (IMRT) for head and neck cancer (HNC). Methods: Fifteen intensity-based MRI metrics were derived from the masseter, lateral and medial pterygoid, and temporalis in T1-weighted scans acquired pre- and post gadolinium injection (T1Pre, T1Post) of 16, of in total 20, patients (8 symptomatic; 8 asymptomatic age/sex/tumor location-matched) treated with IMRT to 70 Gy (median) for HNC in 2005–2009. Trismus was defined as “≥decreased range of motion without impaired eating” (CTCAE.v.3: ≥Grade 1). Trismus status was monitored and MRI scans acquired within 1y post-RT. All MRI-derived metrics were assessed as ΔS=S(T1Pre)-S(T1Post)/S(T1Pre), and were normalized to the corresponding metric of a non-irradiated volume defined in each scan. The T1Pre structures were propagated onto the RT dose distribution, and the max and mean dose (Dmax, Dmean) were extracted. The MRI-derived metrics, Dmax, and Dmean were compared between trismus and non-trismus patients. A two-sided Wilcoxon Signed rank test-based p-value≤0.05 denoted significance. Results: For all four muscles the population mean of Dmax and Dmean was higher for patients with trismus compared to patients without trismus (ΔDmax=2.3–4.9 Gy; ΔDmean=and 2.0–3.8 Gy). The standard deviation (SD), the variance, and the minimum value (min) of ΔS were significantly (p=0.04–0.05) different between patients with and without trismus with trismus patients having significantly lower SD (population median: −0.53 vs. −0.31) and variance (−2.09 vs. −0.73) of the masseter, and significantly lower min of the medial pterygoid (−0.36 vs. −0.19). Conclusion: Quantitative MRI-derived metrics of two masticatory muscles were significantly different between patients with and without trismus following RT for HNC. These metrics could serve as image-based biomarkers to better understand the RT-induced etiology behind trismus, but should be further investigated in the complete cohort.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-FG-206-06: Dual-Input Tracer Kinetic Modeling and Its Analog Implementation for Dynamic Contrast-Enhanced (DCE-) MRI of Malignant Mesothelioma (MPM)

Purpose: To use dual-input tracer kinetic modeling of the lung for mapping spatial heterogeneity of various kinetic parameters in malignant MPM Methods: Six MPM patients received DCE-MRI as part of their radiation therapy simulation scan. 5 patients had the epitheloid subtype of MPM, while one was biphasic. A 3D fast-field echo sequence with TR/TE/Flip angle of 3.62ms/1.69ms/15° was used for DCE-MRI acquisition. The scan was collected for 5 minutes with a temporal resolution of 5-9 seconds depending on the spatial extent of the tumor. A principal component analysis-based groupwise deformable registration was used to co-register all the DCE-MRI series for motion compensation. All the images were analyzed using five different dual-input tracer kinetic models implemented in analog continuous-time formalism: the Tofts-Kety (TK), extended TK (ETK), two compartment exchange (2CX), adiabatic approximation to the tissue homogeneity (AATH), and distributed parameter (DP) models. The following parameters were computed for each model: total blood flow (BF), pulmonary flow fraction (γ), pulmonary blood flow (BF-pa), systemic blood flow (BF-a), blood volume (BV), mean transit time (MTT), permeability-surface area product (PS), fractional interstitial volume (vi), extraction fraction (E), volume transfer constant (Ktrans) and efflux rate constant (kep). Results: Although the majority of patients had epitheloid histologies, kinetic parameter values varied across different models. One patient showed a higher total BF value in all models among the epitheloid histologies, although the γ value was varying among these different models. In one tumor with a large area of necrosis, the TK and ETK models showed higher E, Ktrans, and kep values and lower interstitial volume as compared to AATH and DP and 2CX models. Kinetic parameters such as BF-pa, BF-a, PS, Ktrans values were higher in surviving group compared to non-surviving group across most models. Conclusion: Dual-input tracer kinetic modeling is feasible in determining micro-vascular characteristics of MPM. This project was supported from Cycle for Survival and MSK Imaging and radiation science (IMRAS) grants.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-EF-BRA-11: Feasibility of Super-Resolution Time-Resolved 4DMRI for Multi-Breath Volumetric Motion Simulation in Radiotherapy Planning

Purpose: To develop a novel super-resolution time-resolved 4DMRI technique to evaluate multi-breath, irregular and complex organ motion without respiratory surrogate for radiotherapy planning. Methods: The super-resolution time-resolved (TR) 4DMRI approach combines a series of low-resolution 3D cine MRI images acquired during free breathing (FB) with a high-resolution breath-hold (BH) 3DMRI via deformable image registration (DIR). Five volunteers participated in the study under an IRB-approved protocol. The 3D cine images with voxel size of 5×5×5 mm{sup 3} at two volumes per second (2Hz) were acquired coronally using a T1 fast field echo sequence, half-scan (0.8) acceleration, and SENSE (3) parallel imaging. Phase-encoding was set in the lateral direction to minimize motion artifacts. The BH image with voxel size of 2×2×2 mm{sup 3} was acquired using the same sequence within 10 seconds. A demons-based DIR program was employed to produce super-resolution 2Hz 4DMRI. Registration quality was visually assessed using difference images between TR 4DMRI and 3D cine and quantitatively assessed using average voxel correlation. The fidelity of the 3D cine images was assessed using a gel phantom and a 1D motion platform by comparing mobile and static images. Results: Owing to voxel intensity similarity using the same MRI scanning sequence, accurate DIR between FB and BH images is achieved. The voxel correlations between 3D cine and TR 4DMRI are greater than 0.92 in all cases and the difference images illustrate minimal residual error with little systematic patterns. The 3D cine images of the mobile gel phantom preserve object geometry with minimal scanning artifacts. Conclusion: The super-resolution time-resolved 4DMRI technique has been achieved via DIR, providing a potential solution for multi-breath motion assessment. Accurate DIR mapping has been achieved to map high-resolution BH images to low-resolution FB images, producing 2Hz volumetric high-resolution 4DMRI. Further validation and improvement are still required prior to clinical applications. This study is in part supported by the NIH (U54CA137788/U54CA132378).

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-238: First-Order Approximation of Time-Resolved 4DMRI From Cine 2DMRI and Respiratory-Correlated 4DMRI

Purpose: Cine 2DMRI is useful in MR-guided radiotherapy but it lacks volumetric information. We explore the feasibility of estimating timeresolved (TR) 4DMRI based on cine 2DMRI and respiratory-correlated (RC) 4DMRI though simulation. Methods: We hypothesize that a volumetric image during free breathing can be approximated by interpolation among 3DMRI image sets generated from a RC-4DMRI. Two patients’ RC-4DMRI with 4 or 5 phases were used to generate additional 3DMRI by interpolation. For each patient, six libraries were created to have total 5-to-35 3DMRI images by 0–6 equi-spaced tri-linear interpolation between adjacent and full-inhalation/full-exhalation phases. Sagittal cine 2DMRI were generated from reference 3DMRIs created from separate, unique interpolations from the original RC-4DMRI. To test if accurate 3DMRI could be generated through rigid registration of the cine 2DMRI to the 3DMRI libraries, each sagittal 2DMRI was registered to sagittal cuts in the same location in the 3DMRI within each library to identify the two best matches: one with greater lung volume and one with smaller. A final interpolation between the corresponding 3DMRI was then performed to produce the first-order-approximation (FOA) 3DMRI. The quality and performance of the FOA as a function of library size was assessed using both the difference in lung volume and average voxel intensity between the FOA and the reference 3DMRI. Results: The discrepancy between the FOA and reference 3DMRI decreases as the library size increases. The 3D lung volume difference decreases from 5–15% to 1–2% as the library size increases from 5 to 35 image sets. The average difference in lung voxel intensity decreases from 7–8 to 5–6 with the lung intensity being 0–135. Conclusion: This study indicates that the quality of FOA 3DMRI improves with increasing 3DMRI library size. On-going investigations will test this approach using actual cine 2DMRI and introduce a higher order approximation for improvements. This study is in part supported by NIH (U54CA137788 and U54CA132378)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-253: The Radiomics Toolbox in the Computational Environment for Radiological Research (CERR)

Purpose: To present an open source and free platform to facilitate radiomics research — The “Radiomics toolbox” in CERR. Method: There is scarcity of open source tools that support end-to-end modeling of image features to predict patient outcomes. The “Radiomics toolbox” strives to fill the need for such a software platform. The platform supports (1) import of various kinds of image modalities like CT, PET, MR, SPECT, US. (2) Contouring tools to delineate structures of interest. (3) Extraction and storage of image based features like 1st order statistics, gray-scale co-occurrence and zonesize matrix based texture features and shape features and (4) Statistical Analysis. Statistical analysis of the extracted features is supported with basic functionality that includes univariate correlations, Kaplan-Meir curves and advanced functionality that includes feature reduction and multivariate modeling. The graphical user interface and the data management are performed with Matlab for the ease of development and readability of code and features for wide audience. Open-source software developed with other programming languages is integrated to enhance various components of this toolbox. For example: Java-based DCM4CHE for import of DICOM, R for statistical analysis. Results: The Radiomics toolbox will be distributed as an open source, GNU copyrighted software. The toolbox was prototyped for modeling Oropharyngeal PET dataset at MSKCC. The analysis will be presented in a separate paper. Conclusion: The Radiomics Toolbox provides an extensible platform for extracting and modeling image features. To emphasize new uses of CERR for radiomics and image-based research, we have changed the name from the “Computational Environment for Radiotherapy Research” to the “Computational Environment for Radiological Research”.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-264: Using Magnetic Resonance Imaging-Derived Features to Quantify Radiotherapy-Induced Normal Tissue Morbidity

Purpose: The aim of this study was to explore the use of Magnetic Resonance Imaging (MRI)-derived features as indicators of Radiotherapy (RT)-induced normal tissue morbidity. We also investigate the relationship between these features and RT dose in four critical structures. Methods: We demonstrate our approach for four patients treated with RT for base of tongue cancer in 2005–2007. For each patient, two MRI scans (T1-weighted pre (T1pre) and post (T1post) gadolinium contrast-enhancement) were acquired within the first six months after RT. The assessed morbidity endpoint observed in 2/4 patients was Grade 2+ CTCAEv.3 trismus. Four ipsilateral masticatory-related structures (masseter, lateral and medial pterygoid, and the temporal muscles) were delineated on both T1pre and T1post and these scans were co-registered to the treatment planning CT using a deformable demons algorithm. For each structure, the maximum and mean RT dose, and six MRI-derived features (the second order texture features entropy and homogeneity, and the first order mean, median, kurtosis, and skewness) were extracted and compared structure-wise between patients with and without trismus. All MRI-derived features were calculated as the difference between T1pre and T1post, ΔS. Results: For 5/6 features and all structures, ΔS diverged between trismus and non-trismus patients particularly for the masseter, lateral pterygoid, and temporal muscles using the kurtosis feature (−0.2 vs. 6.4 for lateral pterygoid). Both the maximum and mean RT dose in all four muscles were higher amongst the trismus patients (with the maximum dose being up to 25 Gy higher). Conclusion: Using MRI-derived features to quantify RT-induced normal tissue complications is feasible. We showed that several features are different between patients with and without morbidity and that the RT dose in all investigated structures are higher amongst patients with morbidity. MRI-derived features, therefore, has the potential to improve predictions of normal tissue morbidity.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-18: A Comparison of Planning Techniques for Bilateral Reconstructed Chest Wall Patients Undergoing Whole Breast Irradiation

Purpose: As we continuously see more bilateral reconstructed chest wall cases, new challenges are being presented to deliver left-sided breast irradiation. We herein compare three Deep Inspiration Breath Hold (DIBH) planning techniques (tangents, VMAT, and IMRT) and two free breathing techniques (VMAT and IMRT). Methods: Three left-sided chest wall patients with bilateral implants were studied. Tangents, VMAT, and IMRT plans were created for DIBH scans. VMAT and IMRT plans were created for free breathing scans. All plans were normalized so that 95% of the prescription dose was delivered to 95% of the planning target volume (PTV). The maximum point dose was constrained to less than 120% of the prescription dose. Since the success of DIBH delivery largely depends on patient’s ability to perform consistent breath hold during beam on time, smaller number of Monitor Units (MU) is in general desired. For each patient, the following information was collected to compare the planning techniques: heart mean dose, left and right lung V20 Gy, contra-lateral (right) breast mean dose, cord max dose, and MU. Results: The average heart mean dose over all patients are 1561, 692, 985, 1245, and 1121 cGy, for DIBH tangents, VMAT, IMRT, free breathing VMAT and IMRT, respectively. For left lung V20 are 60%, 28%, 26%, 30%, and 29%. For contra-lateral breast mean dose are 244, 687, 616, 783, 438 cGy. MU are 253, 853, 2048, 1035, and 1874 MUs. Conclusion: In the setting of bilateral chest wall reconstruction, opposed tangent beams cannot consistently achieve desired heart and left lung sparing. DIBH consistently achieves better healthy tissue sparing. VMAT appears to be preferential to IMRT for planning and delivering radiation to patients with bilaterally reconstructed chest walls being treated with DIBH.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-502: Initial Results of a Comparison of Treatment Plans Produced From Automated Prioritized Planning Method and a Commercial Treatment Planning System

Purpose We developed an automated treatment planning system based on a hierarchical goal programming approach. To demonstrate the feasibility of our method, we report the comparison of prostate treatment plans produced from the automated treatment planning system with those produced by a commercial treatment planning system. Methods In our approach, we prioritized the goals of the optimization, and solved one goal at a time. The purpose of prioritization is to ensure that higher priority dose-volume planning goals are not sacrificed to improve lower priority goals. The algorithm has four steps. The first step optimizes dose to the target structures, while sparing key sensitive organs from radiation. In the second step, the algorithm finds the best beamlet weight to reduce toxicity risks to normal tissue while holding the objective function achieved in the first step as a constraint, with a small amount of allowed slip. Likewise, the third and fourth steps introduce lower priority normal tissue goals and beam smoothing. We compared with prostate treatment plans from Memorial Sloan Kettering Cancer Center developed using Eclipse, with a prescription dose of 72 Gy. A combination of liear, quadratic, and gEUD objective functions were used with a modified open source solver code (IPOPT). Results Initial plan results on 3 different cases show that the automated planning system is capable of competing or improving on expert-driven eclipse plans. Compared to the Eclipse planning system, the automated system produced up to 26% less mean dose to rectum and 24% less mean dose to bladder while having the same D95 (after matching) to the target. Conclusion We have demonstrated that Pareto optimal treatment plans can be generated automatically without a trial-and-error process. The solver finds an optimal plan for the given patient, as opposed to database-driven approaches that set parameters based on geometry and population modeling.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-G-204-02: Automatic Sclerotic Bone Metastases Detection in the Pelvic Region From Dual Energy CT

Purpose: To automatically detect sclerotic bone metastases in the pelvic region using dual energy computed tomography (DECT). Methods: We developed a two stage algorithm to automatically detect sclerotic bone metastases in the pelvis from DECT for patients with multiple bone metastatic lesions and with hip implants. The first stage consists of extracting the bone and marrow regions by using a support vector machine (SVM) classifier. We employed a novel representation of the DECT images using multi-material decomposition, which represents each voxel as a mixture of different physical materials (e.g. bone+water+fat). Following the extraction of bone and marrow, in the second stage, a bi -histogram equalization method was employed to enhance the contrast to reveal the bone metastases. Next, meanshift segmentation was performed to separate the voxels by their intensity levels. Finally, shape-based filtering was performed to extract the possible locations of the metastatic lesions using multiple shape criteria. We used the following shape parameters: area, eccentricity, major and minor axis, perimeter and skeleton. Results: A radiologist with several years of experience with DECT manually labeled 64 regions consisting of metastatic lesions from 10 different patients. However, the patients had many more metastasic lesions throughout the pelvis. Our method correctly identified 46 of the marked 64 regions (72%). In addition, our method also identified several other lesions, which can then be validated by the radiologist. The missed lesions were typically very large elongated regions consisting of several islands of very small (<4mm) lesions. Conclusion: We developed an algorithm to automatically detect sclerotic lesions in the pelvic region from DECT. Preliminary assessment shows that our algorithm generated lesions agreeing with the radiologist generated candidate regions. Furthermore, our method reveals additional lesions that can be inspected by the radiologist, thereby, reducing radiologist effort in identifying all the lesions with poor contrast from the DECT images.

60 APPLIED LIFE SCIENCES↗