Board-certified Radiation Oncologists Research Articles

A simulated comparison of lung tumor target verification using stereoscopic tomosynthesis or radiography.

Mobile lung tumors are increasingly being treated with ablative radiotherapy, for which precise motion management is essential. In-room stereoscopic radiography systems are able to guide ablative radiotherapy for stationary cranial lesions but not optimally for lung tumors unless fiducial markers are inserted. We propose augmenting stereoscopic radiographic systems with multiple small x-ray sources to provide the capability of imaging with stereoscopic, single frame tomosynthesis. In single frame tomosynthesis, nine x-ray sources are placed in a 3×3 configuration and energized simultaneously. The beams from these sources are collimated so that they converge on the tumor and then diverge to illuminate nine non-overlapping sectors on the detector. These nine sector images are averaged together and filtered to create the tomosynthesis effect. Single frame tomosynthesis is intended to be an alternative imaging mode for existing stereoscopic systems with a field of view that is three times smaller and a temporal resolution equal to the frame rate of the detector. We simulated stereoscopic tomosynthesis and radiography using Monte Carlo techniques on 60 patients with early-stage lung cancer from the NSCLC-Radiomics dataset. Two board-certified radiation oncologists reviewed these simulated images and rated them on a 4-point scale (1: tumor not visible; 2: tumor visible but inadequate for motion management; 3: tumor visible and adequate for motion management; 4: tumor visibility excellent). Each tumor was independently presented four times (two viewing angles from radiography and two viewing angles from tomosynthesis) in a blinded fashion over two reading sessions. The fraction of tumors that were rated as adequate or excellent for motion management (scores 3 or 4) from at least one viewing angle was 53% using radiography and 90% using tomosynthesis. From both viewing angles, the corresponding fractions were 7% for radiography and 48% for tomosynthesis. Readers agreed exactly on 62% of images and within 1 point on 98% of images. The acquisition technique was estimated to be 75 mAs at 120 kVp per treatment fraction assuming one verification image per breath, approximately one order of magnitude less than a standard dose cone beam CT. Stereoscopic tomosynthesis may provide a noninvasive, low dose, intrafraction motion verification technique for lung tumors treated by ablative radiotherapy. The system architecture is compatible with real-time video capture at 30 frames per second. Simulations suggest that most, but not all, lung tumors can be adequately visualized from at least one viewing angle.

Disparities in Radiation Therapy: Practice Patterns Analysis of Deep Inspiratory Breath Hold Use in Non-English Speakers

Our purpose was to examine current practice patterns in non-English-speaking patients with breast cancer undergoing deep inspiratory breath hold (DIBH). An anonymous, voluntary REDCap survey was distributed to 60 residency program coordinators of US radiation oncology departments to survey their faculty and recent graduates. Eligibility was limited to board-certified radiation oncologists who had treated breast cancer within the prior 6 months. There were 69 respondents, 53 of whom were eligible. Forty-two percent (n=22) of eligible respondents were from the main site at an academic center, with 28% (n=15) representing a satellite site and 30% (n=16) from private practice. Fifty-three percent reported at least 10% of their patients were non-English speaking. Ninety percent offered DIBH at their institution; of those, 74% used DIBH for at least one-fourth of their patients with breast cancer. Ninety-eight percent of those who use DIBH performed coaching at simulation, with 32% answering they would be "less likely" to use DIBH for non-English speakers. When used, 94% take into consideration potential language barriers for proper execution of DIBH. However, 51% had an interpreter present 76% to 100% of the time at computed tomography simulation, which decreased to 31% at first fraction and 11% at subsequent treatments. For non-English-speaking patients undergoing DIBH coaching without a certified interpreter, 55% of respondents indicated that they provided verbal coaching in English, 32% indicated "not applicable" because they always use a certified interpreter, 11% used visual aids, and 32% indicated "other." Of those who answered "other," the most commonly cited response was using therapists or staff who spoke the patient's native language. Disparities in the application of DIBH exist despite its established utility in reducing cardiac dose. This study provides evidence that language barriers may affect physician treatment practices from initial consideration of DIBH to subsequent delivery. These data suggest that breast cancer treatment considerations and subsequent execution are negatively affected in non-English-speaking patients.

Virtual Contrast-Enhanced Magnetic Resonance Images Synthesis for Patients With Nasopharyngeal Carcinoma Using Multimodality-Guided Synergistic Neural Network

To investigate a novel deep-learning network that synthesizes virtual contrast-enhanced T1-weighted (vceT1w) magnetic resonance images (MRI) from multimodality contrast-free MRI for patients with nasopharyngeal carcinoma (NPC). This article presents a retrospective analysis of multiparametric MRI, with and without contrast enhancement by gadolinium-based contrast agents (GBCAs), obtained from 64 biopsy-proven cases of NPC treated at Hong Kong Queen Elizabeth Hospital. A multimodality-guided synergistic neural network (MMgSN-Net) was developed to leverage complementary information between contrast-free T1-weighted and T2-weighted MRI for vceT1w MRI synthesis. Thirty-five patients were randomly selected for model training, whereas 29 patients were selected for model testing. The synthetic images generated from MMgSN-Net were quantitatively evaluated against real GBCA-enhanced T1-weighted MRI using a series of statistical evaluating metrics, which include mean absolute error (MAE), mean squared error (MSE), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR). Qualitative visual assessment between the real and synthetic MRI was also performed. Effectiveness of our MMgSN-Net was compared with 3 state-of-the-art deep-learning networks, including U-Net, CycleGAN, and Hi-Net, both quantitatively and qualitatively. Furthermore, a Turing test was performed by 7 board-certified radiation oncologists from 4 hospitals for assessing authenticity of the synthesized vceT1w MRI against the real GBCA-enhanced T1-weighted MRI. Results from the quantitative evaluations demonstrated that our MMgSN-Net outperformed U-Net, CycleGAN and Hi-Net, yielding the top-ranked scores in averaged MAE (44.50 ± 13.01), MSE (9193.22 ± 5405.00), SSIM (0.887 ± 0.042), and PSNR (33.17 ± 2.14). Furthermore, the mean accuracy of the 7 readers in the Turing tests was determined to be 49.43%, equivalent to random guessing (ie, 50%) in distinguishing between real GBCA-enhanced T1-weighted and synthetic vceT1w MRI. Qualitative evaluation indicated that MMgSN-Net gave the best approximation to the ground-truth images, particularly in visualization of tumor-to-muscle interface and the intratumor texture information. Our MMgSN-Net was capable of synthesizing highly realistic vceT1w MRI that outperformed the 3 comparable state-of-the-art networks.

Pre-Treatment Apparent Diffusion Coefficient Histogram Metrics as a Predictor of Local Tumor Control After Proton Beam Therapy in Patients With Hepatocellular Carcinomas

Apparent diffusion coefficient (ADC) values extractable by diffusion-weighted imaging (DWI) are reported as useful in predicting the outcome of surgery and radiofrequency ablation (RFA) in hepatocellular carcinoma (HCC). However, their relationship with local tumor control (LC) after proton beam therapy (PBT) has not been fully evaluated. This study aimed to investigate interobserver variability in ADC histogram metrics and their usefulness in predicting LC in HCC patients who underwent PBT.The ADC maps of the liver of HCC patients who underwent PBT between 2015 and 2020 were reviewed. The inclusion criteria were imaging DWI at 1.5T within 6 weeks before PBT and the largest tumor dimension between 2 and 10 cm. Twenty-nine patients and 32 tumors were eligible. Axial DWI was acquired using a single-shot spin-echo echo-planar sequence and the b values of 0 and 1000 s mm-2. The ADC maps generated were transferred to a workstation. Five board-certified radiation oncologists (ROs) contoured the whole tumor regions-of-interest (ROIs) on these maps, using anatomical images obtained together as reference. For each ROI, the minimum (ADCmin), mean (ADCmean), maximum (ADCmax), and the 5th (ADC5), 25th (ADC25), 50th (ADC50), 75th (ADC75), and 95th (ADC95) percentiles were extracted. The intraclass correlation coefficient (2,1) (ICC) was calculated to determine interobserver reproducibility: ICC of 0.75 - 0.90 was considered good and > 0.90 excellent. The ADC metrics were averaged among 5 ROs. The optimal cut-off values that determined LC, i.e., non-progressive disease (PD) based on the modified RECIST, were identified using receiver-operating characteristics (ROC) analysis. The LC rates were calculated using the Kaplan-Meier method, and statistical significance was assessed by log-rank test.The median calculated biologically effective dose (α / β = 10) was 97 GyE. With a median follow-up of 39 months (5 - 62), 5 tumors had local PD. The ADCmin, ADCmean, ADCmax, ADC5, ADC25, ADC50, ADC75, and ADC95 of all tumors ranged between 0 - 1131, 748 - 1726, 1566 - 3149, 396 - 1430, 600 - 1566, 723 - 1719, 858 - 1874, and 1166 - 2426 (×10-6 mm 2 s-1), respectively. The ICC were 0.761, 0.969, 0.513, 0.864, 0.978, 0.983, 0.974, and 0.859, respectively. For ADCmean, ADC25, ADC50, and ADC75 which showed excellent reproducibility, the optimal cut-off values to determine LC were 1025, 1005, 1156, and 1132 (×10-6 mm 2 s-1), respectively. The tumors with higher ADC metrics had higher 2-year LC rates than their counterparts (100 % vs 40 %, P = 0.002; 100% vs 74%, P = 0.011; 100% vs 76%, P = 0.024; 100% vs 25%, P < 0.001, respectively).ADCmean, ADC25, ADC50, and ADC75 showed excellent interobserver reproducibility. Pre-treatment ADC histogram metrics may be useful in predicting LC after PBT in HCC.

Disparities in Radiotherapy: Practice Patterns Analysis of DIBH Use in Non-English Speakers

<h3>Purpose/Objective(s)</h3> To examine current practice patterns in non-English speaking breast cancer patients undergoing Deep Inspiratory Breath Hold (DIBH). We hypothesize that disparities in DIBH utilization exist between English and non-English speaking patients. <h3>Materials/Methods</h3> An anonymous, voluntary online survey was distributed to residency program coordinators of U.S. radiation oncology departments to survey their faculty and recent graduates. Eligibility was limited to board-certified radiation oncologists who have treated breast cancer within the prior 6 months. <h3>Results</h3> There were 66 respondents, 50 of whom were eligible. 70% (n = 35) of eligible respondents were from academic sites. Slightly over half (52%) of respondents reported that at least 10% of their patients were non-English speaking. Most offered DIBH at their institution (92%) and of those, 82% of responding radiation oncologists used DIBH for at least a quarter or more of their breast cancer patients. Nearly all of those who use DIBH (98%) used coaching at the time of simulation, with about a third (37%) answering they would be "less likely" to utilize DIBH for non-English speaking patients. If DIBH is used for non-English speaking patients, 86% would take into consideration potential language barriers for proper execution of DIBH. However, slightly over one-half of respondents had an interpreter present 76-100% of the time at CT simulation. At the first DIBH treatment, 31% used an interpreter 76-100% of the time. And at each subsequent treatment, 11% used an interpreter 76-100% of the time. <h3>Conclusion</h3> Disparities in the application of DIBH exist despite its established utility in reducing cardiac dose. This study provides evidence that language barriers may impact physician treatment practices from initial consideration of DIBH to subsequent delivery. Even within a limited sampling of self-reported responses, this data suggests that breast cancer treatment considerations and subsequent execution are negatively affected in non-English speaking patients.

Comparison of Tumor Bed Delineation Using a Novel Radiopaque Filament Marker vs. Surgical Clips for Targeting Breast Cancer Radiotherapy

<h3>Purpose/Objective(s)</h3> The accuracy of tumor bed (TB) delineation is essential for targeting boost dose or partial breast irradiation. Surgical clip markers (CM) are standardly used. However, despite using CM, multiple studies have shown high interobserver variability in TB delineation. We hypothesize that a radiopaque filament marker (FM) woven along the TB at the time of lumpectomy will improve accuracy of TB delineation. <h3>Materials/Methods</h3> An FDA-approved radiopaque filament was intraoperatively used to outline the tumor bed of patients undergoing lumpectomy. Between January 2020 and September 2020, 10 consecutive patients with the FM and 10 consecutive patients with the standard CM were identified for comparison. Five "experts," defined as board-certified radiation oncologists specializing in breast cancer, independently contoured all 20 tumor beds. Dice coefficients were then calculated for each patient by comparing the intersection and aggregate of each expert's contours with that of the other experts individually. An intersection and aggregate of the contours of all 5 experts was also analyzed for each patient. Dice coefficient of 1 represents perfect contour agreement, and 0 represents no agreement. Two-tailed paired samples t-tests were performed to compare dice coefficients between FM and CM cohorts. Furthermore, the center of mass (COM) coordinates were calculated to analyze the distance of the COM of each expert's contour to that of the aggregate of the other experts' contours for each patient. Two-tailed unpaired samples t-tests were performed to compare COM distances between FM and CM cohorts. <h3>Results</h3> For FM, mean dice coefficient and standard deviation for each expert was: 0.61 ± 0.09, 0.60 ± 0.10, 0.60 ± 0.10, 0.60 ± 0.09, and 0.55 ± 0.11, respectively. By comparison, for CM, mean dice coefficient and standard deviation for each expert was: 0.48 ± 0.22, 0.42 ± 0.25, 0.47 ± 0.21, 0.47 ± 0.22, and 0.40 ± 0.22, respectively. Thus, TB delineation agreement was significantly improved with FM (<i>P</i> = 0.0013, <i>P</i> = 0.0001, <i>P</i> = 0.0013, <i>P</i> = 0.0006, and <i>P</i> = 0.0008, respectively). Furthermore, the COM distance of each expert's contour to that of the aggregate of all experts' contours was significantly reduced (<i>P</i> < 0.001) from a mean of 0.96 cm ± 0.89 cm for CM to 0.25 cm ± 0.19 cm for FM. <h3>Conclusion</h3> Radiopaque filament resulted in significantly improved interobserver variability in tumor bed delineation compared with standard surgical clips. This difference was clinically meaningful with a reduction in mean COM contour disagreement from almost 1cm to 2.5mm, and suggests marked superiority of the radiopaque filament in targeting boost dose and/or partial breast irradiation.

NTCP Modeling of Late Effects for Head and Neck Cancer: A Systematic Review.

NTCP Modeling of Late Effects for Head and Neck Cancer: A Systematic Review.

Visualization of Cancer Associated Fibroblasts Using the Novel FAPI PET/CT for Diagnosing and Delineating Lung Cancers for Radiotherapy

This analysis aims to introduce a novel approach of lung cancer detection and tumor delineation for radiotherapy using specific visualization of cancer associated fibroblasts: PET-CT with 18F-radiolabeled inhibitors of Fibroblast Activation Protein (FAPI). Prior to radiotherapy and in addition to contrast enhanced CT (CE-CT), FAPI-PET/CT using 18F-FAPI-74 was acquired at 10 min, 1h and 3h after tracer administration in 10 patients with lung cancer. First, for tissue biodistribution analysis, volume of interest was used to quantify SUVmean and SUVmax in tumor and healthy parenchyma. Secondly, using four thresholds of 1.5, 2, 2.5 and 3-fold increase of FAPI enhancement in the tumor as compared to normal tissue, four different gross tumor volumes (FAPI-GTV) were created automatically. These were consensually compared to GTVs created with conventional CE-CT (CT-GTV) by two experienced and board-certified radiation oncologists and nuclear medicine physicians. All patients tolerated the examination well. The biodistribution analysis revealed that tumorous lesions showed high FAPI avidity, e.g. in primary lung tumors, SUVmax was 11.8 at 10 min; 12.7 at 1h and 11.3 at 3h; in lymph node metastases it was 9.9, 10.7, and 9.4. In contrast, low background uptake was measured in healthy tissues of the thorax and the rest of the body, e.g. in the myocard, SUVmax was 1.9, 1.2 and 0.9. So, for most lesions the uptake peaked later than 10 min. p.i. but there was already some wash-out between 1h and 3h p.i. Hence 1h p.i. scans were used for planning radiotherapy. Here, CE-CT based GTV was of 67.4ml (range 25.9 - 343,4ml), whereas contouring with FAPI resulted in significantly different GTVs of 114.2ml (FAPI x1.5) and 98.1ml (FAPI x2). In the consensus read, the PET-segmented volumes were considered more likely to reflect true tumor-spread than the corresponding CT-GTVs. We present first evidence of diagnostic and therapeutic potential of FAPI-ligands in lung cancer radiation oncology. This novel imaging modality provides critical information concerning tumor spread and produces high contrast images with outstanding tumor-to-background ratios. Thus, automated, precise and comprehensive target volume delineation for radiotherapy of lung cancers might be improved by adding FAPI PET/CT information. Further and larger studies are warranted, especially in comparison with FDG PET/CT to show non-inferiority or even superiority of FAPI PET/CT.

National survey of radiation oncologists' practice patterns regarding hormone-naïve prostate cancer with bone metastases.

To explore radiation oncologists' attitudes and practice patterns of radiotherapy for hormone-naïve prostate cancer with bone metastases in Japan. An internet-based survey was distributed to board-certified radiation oncologists of the Japanese Society of Radiation Oncology. Three hypothetical cases were assumed: hormone-naïve prostate cancer with single, three or multiple non-symptomatic bone metastases. The respondents described their attitude regarding such cases, treatment methods and the radiotherapy dose fractionation that they would recommend. Among the 1013 board-certified radiation oncologists in Japan, 373 (36.8%) responded to the questionnaire. Most of the respondents (85.0%) believed that radiotherapy may be applicable as a primary treatment for hormone-naïve prostate cancer with bone metastases in some circumstances. For Case 1 (single bone metastasis), 55.0% of the respondents recommended radiotherapy for the prostate and bone metastasis. For Case 2 (three bone metastases), only 24.4% recommended radiotherapy for all lesions, and 31.4% recommended radiotherapy for the prostate only. For Case 3 (multiple bone metastases), 49.1% of the respondents stated that there was no indication for radiotherapy. However, 34% of the respondents still preferred to administer radiotherapy for the prostate. The radiotherapy techniques and dose fractionations varied widely among the respondents. Most of the respondent radiation oncologists believed that radiotherapy may be beneficial for hormone-naïve prostate cancer with bone metastases.

Determination of Radiosurgery Treatment Volume for Intracranial Germ Cell Tumors (GCTS)

Background: Radiation therapy (RT) volumes for intracranial germ cell tumors (GCTs) may include focal treatment volumes, whole ventricle irradiation, whole brain irradiation, or irradiation of the entire neuroaxis. RT doses and volumes for management of primary intracranial GCTs have been an area of active research over the years. Improved sparing of critical organs by use of less extensive RT volumes and lower doses has been investigated for avoiding excessive morbidity of treatment. Herein, we assess intracranial GCT treatment volume determination. Methods: Treatment volume definition for intracranial GCT by incorporation of Magnetic Resonance Imaging (MRI) was comparatively assessed in our study. Reference volume for comparison purposes was defined after thorough assessment and collaboration of the board certified radiation oncologists. Definition of radiosurgery target volume was based solely on CT images or fusion of CT with MRI. Comparative evaluation of treatment volume determination was performed. Results: Ground truth target volume defined after thorough evaluation and collaboration of the board certified radiation oncologists was similar with treatment volume definition based on CT-MR fusion based imaging. Conclusions: In conclusion, radiosurgery treatment planning for intracranial GCTs may be improved by incorporation of MRI into target definition process. Clearly, further studies are warranted to draw firm conclusions on optimal target definition for intracranial GCT radiosurgery.

Assessment of Target Volume Definition for Radiosurgery of Atypical Meningiomas with Multimodality Imaging

Objective Meningiomas are most common intracranial benign tumors comprising around one third of all intracranial neoplasms, and typically have benign and indolent nature with slow-growing behaviour. Benign meningiomas are slow growing tumors typically following an indolent disease course. Nevertheless, atypical or anaplastic meningiomas may follow a more aggressive disease course with invasion of critical structures and recurrences. In the current study, we evaluate the incorporation of magnetic resonance imaging (MRI) for radiosurgery treatment planning of atypical meningiomas. Materials and Methods Atypical meningioma radiosurgery target volume determination with and without incorporation of MRI has been evaluated. Ground truth target volume used as the reference has been outlined by the board-certified group of radiation oncologists after comprehensive assessment, thorough collaboration and consensus. Results Target volume definition by use of Computed Tomography (CT)-only imaging and by CT-MR fusion based imaging has been comparatively evaluated in this study for linear accelerator (LINAC)-based radiosurgical management of atypical meningioma. Ground truth target volume defined by the board-certified radiation oncologists after detailed evaluation, collaboration, colleague peer review and consensus has been found to be identical to target determination by use of CT-MR fusion based imaging. Conclusion Despite significant progress in neurosurgical techniques over the years, complete surgical resection may not be feasible in the presence of meningiomas located at eloquent brain areas in close association with important neurovascular structures. RT may have a role in multidisciplinary management of meningiomas. Incorporation of MRI into treatment planning for radiosurgery of atypical meningiomas may improve target definition despite the need for further supporting evidence.

A Novel Deep Learning Architecture for Deformable Imaging Registration applied to Image-Guided Radiotherapy

Most clinical image-guided radiotherapy workflows make use of alignment algorithms to map a plan to a daily cone-beam CT (CBCT) onto a patient’s simulation CT (simCT). Current methodologies of rigid and deformable registration have not demonstrated accuracy high enough to enable automated alignment or adaptive recontouring. Here we investigate a novel deep-learning framework for diffeomorphic deformable image registration (DIR) and analyze its performance with regard to adaptive recontouring. Our institutional treatment planning system and CBCT directory were queried for head and neck plans that were delivered to patients between 2016-2018. A self-normalizing, generative convolutional deep network was developed using the PyTorch API and trained on a platform with 8 NVIDIA K80 GPUs. Network input consisted of a concatenated simCT/CBCT pair and an output of a deformable vector field (DVF). This DVF was then applied to the simCT to warp the simCT onto the CBCT. The network was trained in an unsupervised fashion on the combination of three losses: the Kullback-Leibler loss to promote spatially smooth transforms, a novel bottleneck feature-map loss to prioritize complex anatomic features, and a pixelwise intensity difference loss to drive spatially accurate image reconstruction. In order to test the performance of the network, patient-specific contours were warped onto the CBCT using the DVF output by the network. Patients who underwent repeat planning during their radiotherapy were sampled and the 3D-dice coefficient of overlap was calculated between their initial contours and replanned contours and between the warped contours and replanned contours. All initial and replanned contours were generated by a board-certified radiation oncologist. A dataset of 48 patients was compiled, yielding 1728 simCT/CBCT pairs and 64 unique radiotherapy plans and structure sets. 36 patients were used for the training set, representing 1246 simCT/CBCT pairs. Training was performed over 100 epochs. Resulting warped scans showed strong registration by visual review and 3D dice comparison of the external contours. Quantitatively, the model showed a significantly improved 3D dice overlap of the warped contours to the replanned ground-truth contours (see table). The inference time on the trained model was less than 4 seconds. Our implementation of a novel deep-learning architecture shows fast, robust DIR in the setting of IGRT. Our results highlight the applicability of the recent advancements in deep-learning to essential components of radiation treatment: patient position verification and creation of treatment volumes. Further validation is required prior to implementing such a workflow in the radiation clinic for rapid IGRT.Abstract 1180; Table 1Initial-to-Replanned Contour 3D-Dice OverlapWarped-to-Replanned Contour 3D-Dice OverlappGTV0.781 ± 0.0620.873 ± 0.0450.041CTV0.822 ± 0.0510.901 ± 0.0330.032External0.907 ± 0.0690.948 ± 0.0510.028 Open table in a new tab

Tumor radiomic heterogeneity: Multiparametric functional imaging to characterize variability and predict response following cervical cancer radiation therapy.

Robust approaches to quantify tumor heterogeneity are needed to provide early decision support for precise individualized therapy. To conduct a technical exploration of longitudinal changes in tumor heterogeneity patterns on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI) and FDG positron emission tomography / computed tomography (PET/CT), and their association to radiation therapy (RT) response in cervical cancer. Prospective observational study with longitudinal MRI and PET/CT pre-RT, early-RT (2 weeks), and mid-RT (5 weeks). Twenty-one FIGO IB2 -IVA cervical cancer patients receiving definitive external beam RT and brachytherapy. 1.5T, precontrast axial T1 -weighted, axial and sagittal T2 -weighted, sagittal DWI (multi-b values), sagittal DCE MRI (<10 sec temporal resolution), postcontrast axial T1 -weighted. Response assessment 1 month after completion of treatment by a board-certified radiation oncologist from manually delineated tumor volume changes. Intensity histogram (IH) quantiles (DCE SI10% and DWI ADC10% , FDG-PET SUVmax ) and distribution moments (mean, variance, skewness, kurtosis) were extracted. Differences in IH features between timepoints and modalities were evaluated by Skillings-Mack tests with Holm's correction. Area under receiver-operating characteristic curve (AUC) and Mann-Whitney testing was performed to discriminate treatment response using IH features. Tumor IH means and quantiles varied significantly during RT (SUVmean : ↓28-47%, SUVmax : ↓30-59%, SImean : ↑8-30%, SI10% : ↑8-19%, ADCmean : ↑16%, P < 0.02 for each). Among IH heterogeneity features, FDG-PET SUVCoV (↓16-30%, P = 0.011) and DW-MRI ADCskewness decreased (P = 0.001). FDG-PET SUVCoV was higher than DCE-MRI SICoV and DW-MRI ADCCoV at baseline (P < 0.001) and 2 weeks (P = 0.010). FDG-PET SUVkurtosis was lower than DCE-MRI SIkurtosis and DW-MRI ADCkurtosis at baseline (P = 0.001). Some IH features appeared to associate with favorable tumor response, including large early RT changes in DW-MRI ADCskewness (AUC = 0.86). Preliminary findings show tumor heterogeneity was variable between patients, modalities, and timepoints. Radiomic assessment of changing tumor heterogeneity has the potential to personalize treatment and power outcome prediction. 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1388-1396.

Increasing faculty participation in resident education and providing cost-effective self-assessment module credit to faculty through resident-generated didactics

Purpose/Objective(s)Board certified radiation oncologists and medical physicists are required to earn self-assessment module (SAM) continuing medical education (CME) credit, which may require travel costs or usage fees. Data indicate that faculty participation in resident teaching activities is beneficial to resident education. Our hypothesis was that providing the opportunity to earn SAM credit in resident didactics would increase faculty participation in and improve resident education. Methods and materialsSAM applications, comprising CME certified category 1 resident didactic lectures and faculty-generated questions with respective answers, rationales, and references, were submitted to the American Board of Radiology for formal review. Surveys were distributed to assess main academic campus physician, affiliate campus physician, physicist, and radiation oncology resident impressions regarding the quality of the lectures. Survey responses were designed in Likert-scale format. Sign-test was performed with P < .05 considered statistically different from neutral. ResultsFirst submission SAM approval was obtained for 9 of 9 lectures to date. A total of 52 SAM credits have been awarded to 4 physicists and 7 attending physicians. Main academic campus physician and affiliate campus physician attendance increased from 20% and 0%, respectively, over the 12 months preceding CME/SAM lectures, to 55.6% and 20%, respectively. Survey results indicated that the change to SAM lectures increased the quality of resident lectures (P = .001), attending physician participation in resident education (P < .0001), physicist involvement in medical resident education (P = .0006), and faculty motivation to attend resident didactics (P = .004). Residents reported an increased amount of time required to prepare lectures (P = .008). ConclusionsWe are the first department, to our knowledge, to offer SAM credit to clinical faculty for participation in resident-generated didactics. Offering SAM credit at resident lectures is a cost-effective alternative to purchasing SAM resources, increases faculty attendance, and may improve the quality of radiation oncology resident education.

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&amp;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 &amp; 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.

Using the ACR Accreditation Process As a Quality Improvement Tool

DESCRIPTION OF THE PROBLEM The ACR accreditation process is a voluntary review that allows for an impartial peer evaluation of radiation oncology departments. Accreditation is a mechanism for departments to demonstrate to patients, providers, and payers adherence to recognized standards of care and quality performance. Among the goals of the process listed by the ACR are recognizing quality radiation oncology practices, as well as recommending potential practice improvements based on nationally recognized standards. As part of the accreditation process, an onsite survey of departmental facilities, staff, and procedures is carried out by board-certified radiation oncologists and medical physicists. During the onsite survey, the external reviewers interview key personnel, assess documentation of departmental policies and procedures, audit the department’s existing quality assurance and improvement program, and review patient records to assess adherence to nationally recognized clinical standards. Although quality of care is a challenging metric to assess in radiation oncology, accreditation programs focus on components of a department’s structure, process, and outcomes. Most quantifiable outcomes fall into the structure and process categories of quality assessment. Our department sought to quantify the quality improvement

Difference in the Use of Terms: Isotope-Based, Surface-Mold Brachytherapy vs Electronic Surface Brachytherapy.

Allison L. Goddard, MD; Ruth Ann Vleugels, MD, MPH; Nicole R. LeBoeuf, MD, MPH; Desmond A. O’Farrell, MSc, DABR; Robert A. Cormack, PhD; Jorgen L. Hansen, MS; Thomas S. Kupper, MD; Phillip M. Devlin, MD

Involved-Field Irradiation vs Elective Nodal Irradiation for Locally Advanced Thoracic Esophageal Squamous Cell Carcinoma: A Comparative Interim Analysis of Clinical Outcomes and Toxicities (NCT01551589, CSWOG 003)

Purpose/Objective(s): Cancer treatment outcome predictors are being examined in recent studies. Quantitative image features have shown potential for predicting treatment outcomes in several body sites. This study focused on quantitative analysis of cervical cancer patient’s PET/CT scans. Materials/Methods: We investigated the treatment outcome predictive power of SUV, textural and shape features from pre-treatment F18-FDG PET/CT scans. A cohort of 80 patients diagnosed with cervical cancer, FIGO stage IB-IVA, age range 25e86 years, (median age at diagnosis: 50 years) all treated between 2009 and 2014 with external beam radiation therapy to a dose range between: 45e50.4 Gy (median Z 45 Gy), concurrent cisplatin chemotherapy and MRI-based brachytherapy to a dose of 20e30 Gy (medianZ 28 Gy). Metabolic Tumor Volume (MTV) in patient’s primary site was delineated on pretreatment PET/CT by two board certified Radiation Oncologists. More than 80 quantitative image features were computed for each volume. Distant Metastases (DM) and Locoregional Recurrence (LRR) were analyzed based on each patient’s clinical record. Textural features were extracted using Co-occurrence Matrix (COM), Run Length Matrix (RLM), Gray Level Size Zone Matrix (GLSZM), and Intensity Based Matrix (IBM). SUVmax and SUVpeak were all measured from MTV. The correlation between the extracted features, SUV, and treatment outcomes were measured by three tests; Spearman’s rho, Pearson and Receiver Operator Curve (ROC). Results: Pearson’s and Spearman’s tests correlation scale for this study was: No correlation 0e0.19; Weak 0.2e0.249; Moderate 0.25e0.4; relatively strong 0.41e0.5; and strong 0.5e1. A total of 23 features showed correlation with both treatment outcomes. With DM: 10 features showed moderate correlation and 1 relatively strong correlation. With LRR: 21 features showed moderate correlation. SUVpeak correlated moderately with DM only on both tests. SUVmax showed weak correlations with all outcomes. ROC results were concordant with other tests. However, SUVpeak and SUVmax correlated with both DM and LRR. The correlation coefficients are shown in Table 1. Conclusion: Quantitative image features, based on four different calculation algorithms, predicted treatment outcomes better than SUV on three statistical tests. The results suggest that Radiomics may produce more robust tools to predict for treatment outcomes. Author Disclosure: B.A. Altazi: None. G.G. Zhang: None. E.G. Moros: None. M.C. Biagioli: None. D.C. Fernandez: None.

Cognitive Predictors of Reasoning through Treatment Decisions in Patients with Newly Diagnosed Brain Metastases.

To examine the association between reasoning through medical treatment decisions and cognition in a sample of patients with brain metastasis. The association between reasoning and cognition was examined using data from 41 patients with diagnosed brain metastasis. All diagnoses were made by a board-certified radiation oncologist and were verified histologically. In total, 41 demographically matched, cognitively healthy controls were also included to aid in classifying patients with brain metastasis according to reasoning status (i.e., intact or impaired). Results indicate that measures of episodic memory and processing speed were associated with reasoning. Using these two predictors, actuarial equations were constructed that can be used to help screen for impaired reasoning ability in patients' with brain metastasis. The equations presented in this study have clinical significance as they can be used to help identify patients at risk for possessing a diminished ability to reason through medical treatment decisions and, thus, are in need of a more comprehensive evaluation of their medical decision-making capacity.

SU‐E‐J‐258: Prediction of Cervical Cancer Treatment Response Using Radiomics Features Based On F18‐FDG Uptake in PET Images

Purpose:Radiomics have shown potential for predicting treatment outcomes in several body sites. This study investigated the correlation between PET Radiomics features and treatment response of cervical cancer outcomes.Methods:our dataset consisted of a cohort of 79 patients diagnosed with cervical cancer, FIGO stage IB‐IVA, age range 25–86 years, (median age at diagnosis: 50 years) all treated between: 2009–14 with external beam radiation therapy to a dose range between: 45–50.4 Gy (median= 45 Gy), concurrent cisplatin chemotherapy and MRI‐based brachytherapy to a dose of 20–30 Gy (median= 28 Gy). Metabolic Tumor Volume (MTV) in patient's primary site was delineated on pretreatment PET/CT by two board certified Radiation Oncologists. The features extracted from each patient's volume were: 26 Co‐occurrence matrix (COM) Feature, 11 Run‐Length Matrix (RLM), 11 Gray Level Size Zone Matrix (GLSZM) and 33 Intensity‐based features (IBF). The treatment outcome was divided based on the last follow up status into three classes: No Evidence of Disease (NED), Alive with Disease (AWD) and Dead of Disease (DOD). The ability for the radiomics features to differentiate between the 3 treatments outcome categories were assessed by One‐Way ANOVA test with p‐value &lt; 0.05 was to be statistically significant. The results from the analysis were compared with the ones obtained previously for standard Uptake Value (SUV).Results:Based on patients last clinical follow‐up; 52 showed NED, 17 AWD and 10 DOD. Radiomics Features were able to classify the patients based on their treatment response. A parallel analysis was done for SUV measurements for comparison.Conclusion:Radiomics features were able to differentiate between the three different classes of treatment outcomes. However, most of the features were only able to differentiate between NED and DOD class. Also, The ability or radiomics features to differentiate types of response were more significant than SUV.