Engineering topics

Tyagi, N

Publications and source records attributed to Tyagi, N.

13 records

DOE OSTI2016

SU-D-207B-04: Morphological Features of MRI as a Correlate of Capsular Contracture in Breast Cancer Patients with Implant-Based Reconstructions

Purpose: Capsular contracture (CC) is a serious complication in patients receiving implant-based reconstruction for breast cancer. The goal of this study was to identify image-based correlates of CC using MRI imaging in breast cancer patients who received both MRI and clinical evaluation following reconstructive surgery. Methods: We analyzed a retrospective dataset of 50 patients who had both a diagnostic MR and a plastic surgeon’s evaluations of CC score (Baker’s score) within a six month period following mastectomy and reconstructive surgery. T2w sagittal MRIs (TR/TE = 3500/102 ms, slice thickness = 4 mm) were used for morphological shape features (roundness, eccentricity, solidity, extent and ratio-length) and histogram features (median, skewness and kurtosis) of the implant and the pectoralis muscle overlying the implant. Implant and pectoralis muscles were segmented in 3D using Computation Environment for Radiological Research (CERR) and shape and histogram features were calculated as a function of Baker’s score. Results: Shape features such as roundness and eccentricity were statistically significant in differentiating grade 1 and grade 2 (p = 0.009; p = 0.06) as well as grade 1 and grade 3 CC (p = 0.001; p = 0.006). Solidity and extent were statistically significant in differentiating grade 1 and grade 3 CC (p = 0.04; p = 0.04). Ratio-length was statistically significant in differentiating all grades of CC except grade 2 and grade 3 that showed borderline significance (p = 0.06). The muscle thickness, median intensity and kurtosis were significant in differentiating between grade 1 and grade 3 (p = 0.02), grade 1 and grade 2 (p = 0.03) and grade 1 and grade 3 (p = 0.01) respectively. Conclusion: Morphological shape features described on MR images were associated with the severity of CC. MRI may be important in objectively evaluating outcomes in breast cancer patients who undergo implant reconstruction.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-104: Weekly MRI for Dose Assessment of Organs at Risk During Treatment of HN Cancer of the Oropharynx

Purpose: Investigate the feasibility of using weekly MRI to assess dose to organs at risk utilizing deformable image registration. Methods: Sixteen H&N patients with oropharyngeal cancer were imaged on a 3T MR scanner using T2W and mDIXON sequence. Patients were imaged on a weekly basis in treatment position. Parotids (LP & RP), submandibular glands (LS, RS), and oral cavity (OC) were delineated on the weekly MR and reviewed by a board certified radiation oncologist. The original planning CT (pCT), RT-Dose, and RT-Structures were deformed and registered to each weekly MRIs. The deformed CTs and RT-Structures were imported to the treatment planning system (TPS) and rigidly registered to the pCT. Forward dose calculation of the original RT-Plan was used to estimate the delivered dose on the deformed CT. The dose volume histograms (DVH) statistics were performed to compare planned dose, deformed dose, and forward calculated dose. In addition, Dice similarity metric (DSM) was used to compare deformed and reference structures. Results: The average (min,max) DSM between deformed and reference structures was 0.71 (0.69,0.93); 0.70 (0.64,0.89); 0.65 (0.48,0.86); 0.63 (0.37,0.89); and 0.63 (0.58,0.87); for LP, RP, LS, RS, and OC respectively. The respective average relative structures volumes changed at a weekly rate of −4.99%; −4.40%; +3.45%; +1.46%; −1.39%, respectively. The percentage difference %(min,max) between estimated delivered dose and planned dose was +3.94 (−51.3,+30.5); +6.33 (−58.6,+82.7); +2.46 (−38.9,+37.6,); +2.38(−49.0,+28.9); +3.55(−17.0,+43.1). Conclusion: The recalculated dose based on weekly MRI deviated from planned dose for all OARs. Meanwhile, the deformed dose did not reflect the subtle changes in OARs as compared to the recalculated dose. This study demonstrates the feasibility of using weekly MRI to monitor volumetric changes which has important implications on actual delivered dose.

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

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-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 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-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 OSTI2014

WE-D-9A-04: Improving Multi-Modality Image Registration Using Edge-Based Transformations

Purpose: Multi-modality deformable image registration (DIR) for head and neck (HN) radiotherapy is difficult, particularly when matching computed tomography (CT) scans with magnetic resonance imaging (MRI) scans. We hypothesized that the ‘shared information’ between images of different modalities was to be found in some form of edge-based transformation, and that novel edge-based DIR methods might outperform standard DIR methods. Methods: We propose a novel method that combines gray-scale edge-based morphology and mutual information (MI) in two stages. In the first step, we applied a modification of a previously published mathematical morphology method as an efficient gray scale edge estimator, with denoising function. The results were fed into a MI-based solver (plastimatch). The method was tested on 5 HN patients with pretreatment CT and MR datasets and associated follow-up weekly MR scans. The followup MRs showed significant regression in tumor and normal structure volumes as compared to the pretreatment MRs. The MR images used in this study were obtained using fast spin echo based T2w images with a 1 mm isotropic resolution and FOV matching the CT scan. Results: In all cases, the novel edge-based registration method provided better registration quality than MI-based DIR using the original CT and MRI images. For example, the mismatch in carotid arteries was reduced from 3–5 mm to within 2 mm. The novel edge-based method with different registration regulation parameters did not show any distorted deformations as compared to the non-realistic deformations resulting from MI on the original images. Processing time was 1.3 to 2 times shorter (edge vs. non-edge). In general, we observed quality improvement and significant calculation time reduction with the new method. Conclusion: Transforming images to an ‘edge-space,’ if designed appropriately, greatly increases the speed and accuracy of DIR.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

WE-G-BRD-01: Diffusion Weighted MRI for Response Assessment of Inoperable Lung Tumors for Patients Undergoing SBRT Treatment

Purpose: To investigate early changes in tumor Apparent Diffusion Coefficients derived from diffusion weighted (DW)-MRI of lung cancer patients undergoing SBRT, as a possible early predictor of treatment response. Methods: DW-MRI scans were performed in this prospective phase I IRB-approved study of inoperable lung tumors at various time-points during the course of SBRT treatments. Axial DW scan using multi b-values ranging from 0–1000 s/mm{sup 2} were acquired in treatment position on a 3T Philips MR scanner during simulation, one hour after the first fraction (8 Gy), after a total of 5 fractions (40 Gy) and 4 weeks after SBRT delivery. A monoexponential model based on a least square fit from all b values was performed on a pixel-by-pixel basis and ADC was calculated. GTVs drawn on 4DCT for planning were mapped on the T2w MRI (acquired at exhale) after deformable registration. These volumes were then mapped on DWI scan for ADC calculation after rigid registration between the anatomical scan and diffusion scan. T2w scan on followup time points were deformably registered to the pretreatment T2 scan. Results: The first two patients in this study were analyzed. Median ADC values were 1.48, 1.48, 1.62 and 1.83 (10{sup −3}×) mm{sup 2}/s at pretreatment, after 8 Gy, after 40 Gy and 4 weeks posttreatment for the first patient and 1.57, 1.53, 1.66 and 1.72 (10{sup −3}×) mm{sup 2}/s for the second patient. ADC increased more significantly after 4 weeks of treatment rather than immediately post treatment, implying that late ADC value may be a better predictor of tumor response for SBRT treatment. The fraction of tumor pixels at high ADC values increased at 4 weeks post treatment. Conclusion: The observed increase in ADC values before the end of radiotherapy may be a surrogate for tumor response, but further patient accrual will be necessary to determine its value.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

WE-G-18C-09: Separating Perfusion and Diffusion Components From Diffusion Weighted MRI of Rectum Tumors Based On Intravoxel Incoherent Motion (IVIM) Analysis

Purpose: Pseudodiffusion arises from the microcirculation of blood in the randomly oriented capillary network and contributes to the signal decay acquired using a multi-b value diffusion weighted (DW)-MRI sequence. This effect is more significant at low b-values and should be properly accounted for in apparent diffusion coefficient (ADC) calculations. The purpose of this study was to separate perfusion and diffusion component based on a biexponential and a segmented monoexponential model using IVIM analysis Methods. The signal attenuation is modeled as S(b) = S0[(1−f)exp(−bD) + fexp(−bD*)]. Fitting the biexponetial decay leads to the quantification of D, the true diffusion coefficient, D*, the pseudodiffusion coefficient, and f, the perfusion fraction. A nonlinear least squares fit and two segmented monoexponential models were used to derive the values for D, D*,‘and f. In the segmented approach b = 200 s/mm{sup 2} was used as the cut-off value for calculation of D. DW-MRI's of a rectum cancer patient were acquired before chemotherapy, before radiation therapy (RT), and 4 weeks into RT and were investigated as an example case. Results: Mean ADC for the tumor drawn on the DWI cases was 0.93, 1.0 and 1.13 10{sup −3}×mm{sup 2}/s before chemotherapy, before RT and 4 weeks into RT. The mean (D.10{sup −3} × mm{sup 2}/s, D* 10{sup −3} × mm{sup 2}/s, and f %) based on biexponential fit was (0.67, 18.6, and 27.2%), (0.72, 17.7, and 28.9%) and (0.83,15.1, and 30.7%) at these time points. The mean (D, D* f) based on segmented fit was (0.72, 10.5, and 12.1%), (0.72, 8.2, and 17.4%) and (.82, 8.1, 16.5%) Conclusion: ADC values are typically higher than true diffusion coefficients. For tumors with significant perfusion effect, ADC should be analyzed at higher b-values or separated from the perfusion component. Biexponential fit overestimates the perfusion fraction because of increased sensitivity to noise at low b-values.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-E-J-137: Incorporating Tumor Regression Into Robust Plan Optimization for Head and Neck Radiotherapy

Purpose: To develop a robust planning paradigm which incorporates a tumor regression model into the optimization process to ensure tumor coverage in head and neck radiotherapy. Methods: Simulation and weekly MR images were acquired for a group of head and neck patients to characterize tumor regression during radiotherapy. For each patient, the tumor and parotid glands were segmented on the MR images and the weekly changes were formulated with an affine transformation, where morphological shrinkage and positional changes are modeled by a scaling factor, and centroid shifts, respectively. The tumor and parotid contours were also transferred to the planning CT via rigid registration. To perform the robust planning, weekly predicted PTV and parotid structures were created by transforming the corresponding simulation structures according to the weekly affine transformation matrix averaged over patients other than him/herself. Next, robust PTV and parotid structures were generated as the union of the simulation and weekly prediction contours. In the subsequent robust optimization process, attainment of the clinical dose objectives was required for the robust PTV and parotids, as well as other organs at risk (OAR). The resulting robust plans were evaluated by looking at the weekly and total accumulated dose to the actual weekly PTV and parotid structures. The robust plan was compared with the original plan based on the planning CT to determine its potential clinical benefit. Results: For four patients, the average weekly change to tumor volume and position was −4% and 1.2 mm laterally-posteriorly. Due to these temporal changes, the robust plans resulted in an accumulated PTV D95 that was, on average, 2.7 Gy higher than the plan created from the planning CT. OAR doses were similar. Conclusion: Integration of a tumor regression model into target delineation and plan robust optimization is feasible and may yield improved tumor coverage. Part of this research is supported by Varian Medical System.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-E-J-238: Monitoring Lymph Node Volumes During Radiotherapy Using Semi-Automatic Segmentation of MRI Images

Purpose: Identification and image-based monitoring of lymph nodes growing due to disease, could be an attractive alternative to prophylactic head and neck irradiation. We evaluated the accuracy of the user-interactive Grow Cut algorithm for volumetric segmentation of radiotherapy relevant lymph nodes from MRI taken weekly during radiotherapy. Method: The algorithm employs user drawn strokes in the image to volumetrically segment multiple structures of interest. We used a 3D T2-wturbo spin echo images with an isotropic resolution of 1 mm3 and FOV of 492×492×300 mm3 of head and neck cancer patients who underwent weekly MR imaging during the course of radiotherapy. Various lymph node (LN) levels (N2, N3, N4'5) were individually contoured on the weekly MR images by an expert physician and used as ground truth in our study. The segmentation results were compared with the physician drawn lymph nodes based on DICE similarity score. Results: Three head and neck patients with 6 weekly MR images were evaluated. Two patients had level 2 LN drawn and one patient had level N2, N3 and N4'5 drawn on each MR image. The algorithm took an average of a minute to segment the entire volume (512×512×300 mm3). The algorithm achieved an overall DICE similarity score of 0.78. The time taken for initializing and obtaining the volumetric mask was about 5 mins for cases with only N2 LN and about 15 mins for the case with N2,N3 and N4'5 level nodes. The longer initialization time for the latter case was due to the need for accurate user inputs to separate overlapping portions of the different LN. The standard deviation in segmentation accuracy at different time points was utmost 0.05. Conclusions: Our initial evaluation of the grow cut segmentation shows reasonably accurate and consistent volumetric segmentations of LN with minimal user effort and time.

60 APPLIED LIFE SCIENCES↗