An exploratory study of pedestrian crossing speeds at midblock crossing in India using LiDAR.

OBJECTIVE: Understanding pedestrian road crossing behavior is essential from the perspectives of traffic flow and pedestrian safety. Limited research is available on pedestrian behavior in low- and middle-income countries. The main objective of this study is to understand pedestrian-vehicle interactions during midblock crossings in heterogeneous traffic conditions. Specifically, this study aims to understand whether pedestrians alter their crossing behavior depending on the type of approaching vehicles. METHODS: To better understand pedestrian road crossing behavior at midblock crossings, an instrumented vehicle collected data from Kanpur, a large city in Uttar Pradesh, India. Because light detection and ranging provides point clouds at high frequency, an algorithm was developed to identify and track vehicles and pedestrians. Specifically, 2 types of interactions at midblock crossings were studied: car-pedestrian and motorized bike-pedestrian. The walking speed profiles and trajectories of the pedestrians were analyzed. RESULTS: The results show that pedestrians are more willing to engage in risky road crossing behavior in front of motorized bikes than in front of cars. Pedestrian walking speed profiles were unaffected by motorized bikes, but for cars, pedestrians tended to increase their speed in the first half of road crossing and then decrease in the second half. CONCLUSIONS: Pedestrian crossing speed profiles play an essential role in understanding pedestrian midblock crossing behavior. The speed data for pedestrians at various points of crossing are challenging to capture, but this study shows that LiDAR can be used to capture detailed pedestrian movements. The findings from this study demonstrate the importance of considering vehicle heterogeneity when analyzing pedestrian risk exposure and designing pedestrian crossing facilities.

AAR-RT - A system for auto-contouring organs at risk on CT images for radiation therapy planning: Principles, design, and large-scale evaluation on head-and-neck and thoracic cancer cases.

Contouring (segmentation) of Organs at Risk (OARs) in medical images is required for accurate radiation therapy (RT) planning. In current clinical practice, OAR contouring is performed with low levels of automation. Although several approaches have been proposed in the literature for improving automation, it is difficult to gain an understanding of how well these methods would perform in a realistic clinical setting. This is chiefly due to three key factors - small number of patient studies used for evaluation, lack of performance evaluation as a function of input image quality, and lack of precise anatomic definitions of OARs. In this paper, extending our previous body-wide Automatic Anatomy Recognition (AAR) framework to RT planning of OARs in the head and neck (H&N) and thoracic body regions, we present a methodology called AAR-RT to overcome some of these hurdles. AAR-RT follows AAR's 3-stage paradigm of model-building, object-recognition, and object-delineation. Model-building: Three key advances were made over AAR. (i) AAR-RT (like AAR) starts off with a computationally precise definition of the two body regions and all of their OARs. Ground truth delineations of OARs are then generated following these definitions strictly. We retrospectively gathered patient data sets and the associated contour data sets that have been created previously in routine clinical RT planning from our Radiation Oncology department and mended the contours to conform to these definitions. We then derived an Object Quality Score (OQS) for each OAR sample and an Image Quality Score (IQS) for each study, both on a 1-to-10 scale, based on quality grades assigned to each OAR sample following 9 key quality criteria. Only studies with high IQS and high OQS for all of their OARs were selected for model building. IQS and OQS were employed for evaluating AAR-RT's performance as a function of image/object quality. (ii) In place of the previous hand-crafted hierarchy for organizing OARs in AAR, we devised a method to find an optimal hierarchy for each body region. Optimality was based on minimizing object recognition error. (iii) In addition to the parent-to-child relationship encoded in the hierarchy in previous AAR, we developed a directed probability graph technique to further improve recognition accuracy by learning and encoding in the model "steady" relationships that may exist among OAR boundaries in the three orthogonal planes. Object-recognition: The two key improvements over the previous approach are (i) use of the optimal hierarchy for actual recognition of OARs in a given image, and (ii) refined recognition by making use of the trained probability graph. Object-delineation: We use a kNN classifier confined to the fuzzy object mask localized by the recognition step and then fit optimally the fuzzy mask to the kNN-derived voxel cluster to bring back shape constraint on the object. We evaluated AAR-RT on 205 thoracic and 298 H&N (total 503) studies, involving both planning and re-planning scans and a total of 21 organs (9 - thorax, 12 - H&N). The studies were gathered from two patient age groups for each gender - 40-59 years and 60-79 years. The number of 3D OAR samples analyzed from the two body regions was 4301. IQS and OQS tended to cluster at the two ends of the score scale. Accordingly, we considered two quality groups for each gender - good and poor. Good quality data sets typically had OQS ≥ 6 and had distortions, artifacts, pathology etc. in not more than 3 slices through the object. The number of model-worthy data sets used for training were 38 for thorax and 36 for H&N, and the remaining 479 studies were used for testing AAR-RT. Accordingly, we created 4 anatomy models, one each for: Thorax male (20 model-worthy data sets), Thorax female (18 model-worthy data sets), H&N male (20 model-worthy data sets), and H&N female (16 model-worthy data sets). On "good" cases, AAR-RT's recognition accuracy was within 2 voxels and delineation boundary distance was within ∼1 voxel. This was similar to the variability observed between two dosimetrists in manually contouring 5-6 OARs in each of 169 studies. On "poor" cases, AAR-RT's errors hovered around 5 voxels for recognition and 2 voxels for boundary distance. The performance was similar on planning and replanning cases, and there was no gender difference in performance. AAR-RT's recognition operation is much more robust than delineation. Understanding object and image quality and how they influence performance is crucial for devising effective object recognition and delineation algorithms. OQS seems to be more important than IQS in determining accuracy. Streak artifacts arising from dental implants and fillings and beam hardening from bone pose the greatest challenge to auto-contouring methods.

Rectal balloon use limits vaginal displacement, rectal dose, and rectal toxicity in patients receiving IMRT for postoperative gynecological malignancies.

Pelvic radiotherapy for gynecologic malignancies traditionally used a 4-field box technique. Later trials have shown the feasibility of using intensity-modulated radiotherapy (IMRT) instead. But vaginal movement between fractions is concerning when using IMRT due to greater conformality of the isodose curves to the target and the resulting possibility of missing the target while the vagina is displaced. In this study, we showed that the use of a rectal balloon during treatment can decrease vaginal displacement, limit rectal dose, and limit acute and late toxicities. Little is known regarding the use of a rectal balloon (RB) in treating patients with IMRT in the posthysterectomy setting. We hypothesize that the use of an RB during treatment can limit rectal dose and acute and long-term toxicities, as well as decrease vaginal cuff displacement between fractions. We performed a retrospective review of patients with gynecological malignancies who received postoperative IMRT with the use of an RB from January 1, 2012 to January 1, 2015. Rectal dose constraint was examined as per Radiation Therapy Oncology Group (RTOG) 1203 and 0418. Daily cone beam computed tomography (CT) was performed, and the average (avg) displacement, avg magnitude, and avg magnitude of vector were calculated. Toxicity was reported according to RTOG acute radiation morbidity scoring criteria. Acute toxicity was defined as less than 90 days from the end of radiation treatment. Late toxicity was defined as at least 90 days after completing radiation. Twenty-eight patients with postoperative IMRT with the use of an RB were examined and 23 treatment plans were reviewed. The avg rectal V40 was 39.3% ± 9.0%. V30 was65.1% ± 10.0%. V50 was 0%. Separate cone beam computed tomography (CBCT) images (n = 663) were reviewed. The avg displacement was as follows: superior 0.4 + 2.99 mm, left 0.23 ± 4.97 mm, and anterior 0.16 ± 5.18 mm. The avg magnitude of displacement was superior/inferior 2.22 ± 2.04 mm, laterally 3.41 ± 3.62 mm, and anterior/posterior 3.86 ± 3.45 mm. The avg vector magnitude was 6.60 ± 4.14 mm. For acute gastrointestinal (GI) toxicities, 50% experienced grade 1 toxicities and 18% grade 2 GI toxicities. For acute genitourinary (GU) toxicities, 21% had grade 1 and 18% had grade 2 toxicities. For late GU toxicities, 7% had grade 1 and 4% had grade 2 toxicities. RB for gynecological patients receiving IMRT in the postoperative setting can limit V40 rectal dose and vaginal displacement. Although V30 constraints were not met, patients had limited acute and late toxicities. Further studies are needed to validate these findings.

Whole-brain Irradiation Field Design: A Comparison of Parotid Dose.

Whole-brain radiation therapy (WBRT) plays an important role in patients with diffusely metastatic intracranial disease. Whether the extent of the radiation field design to C1 or C2 affects parotid dose and risk for developing xerostomia is unknown. The goal of this study is to examine the parotid dose based off of the inferior extent of WBRT field to either C1 or C2. Patients treated with WBRT with either 30 Gy or 37.5 Gy from 2011 to 2014 at a single institution were examined. Parotid dose constraints were compared with Radiation Therapy Oncology Group (RTOG) 0615 nasopharyngeal carcinoma for a 33-fraction treatment: mean <26 Gy, volume constraint at 20 Gy (V20) < 20 cc, and dose at 50% of the parotid volume (D50) < 30 Gy. Biologically effective dose (BED) conversions with an α/ß of 3 for normal parotid were performed to compare with 10-fraction and 15-fraction treatments of WBRT. The constraints are as follows: mean < BED 32.83 Gy, V15.76 (for 10-fraction WBRT) or V17.35 (for 15-fraction WBRT) < 20 cc, and D50 < BED 39.09 Gy. Nineteen patients treated to C1 and 26 patients treated to C2 were analyzed. Comparing WBRT to C1 with WBRT to C2, the mean left, right, and both parotids' doses were lower when treated to C1. Converting mean dose to BED3, the parotid doses were lower than BED3 constraint of 32.83 Gy: left (30.12 Gy), right (30.69 Gy), and both parotids (30.32 Gy). V20 to combined parotids was lower in patients treated to C1. When accounting for fractionation of WBRT received, the mean corrected V20 volume was less than 20 cc when treating to C1. D50 for C1 was lower than C2 for the left parotid, right parotid, and both parotids. BED3 conversion for the mean D50 of the left, right, and both parotids was less than 39.09 Gy. In conclusion, WBRT to C1 limits parotid dose, and parotid dose constraints are achievable compared with inferior border at C2. A possible mean parotid dose constraint with BED3 should be less than 32.83 Gy.

Is there a clinical benefit with a smooth compensator design compared with a plunged compensator design for passive scattered protons?

In proton therapy, passive scattered proton plans use compensators to conform the dose to the distal surface of the planning volume. These devices are custom made from acrylic or wax for each treatment field using either a plunge-drilled or smooth-milled compensator design. The purpose of this study was to investigate if there is a clinical benefit of generating passive scattered proton radiation treatment plans with the smooth compensator design. We generated 4 plans with different techniques using the smooth compensators. We chose 5 sites and 5 patients for each site for the range of dosimetric effects to show adequate sample. The plans were compared and evaluated using multicriteria (MCA) plan quality metrics for plan assessment and comparison using the Quality Reports [EMR] technology by Canis Lupus LLC. The average absolute difference for dosimetric metrics from the plunged-depth plan ranged from -4.7 to +3.0 and the average absolute performance results ranged from -6.6% to +3%. The manually edited smooth compensator plan yielded the best dosimetric metric, +3.0, and performance, + 3.0% compared to the plunged-depth plan. It was also superior to the other smooth compensator plans. Our results indicate that there are multiple approaches to achieve plans with smooth compensators similar to the plunged-depth plans. The smooth compensators with manual compensator edits yielded equal or better target coverage and normal tissue (NT) doses compared with the other smooth compensator techniques. Further studies are under investigation to evaluate the robustness of the smooth compensator design.