Background: Surface-guided radiation therapy (SGRT) systems have been widely installed and utilized on linear accelerators. However, the use of SGRT with proton therapy is still a newly developing field, and published reports are currently very limited.Purpose: To assess the clinical application and alignment agreement of SGRT with CT-on-rails (CTOR) and kV-2D image-guided radiation therapy (IGRT) for breast treatment using proton therapy.Methods: Four patients receiving breast or chest wall treatment with proton therapy were the subjects of this study. Patient #1 ' s IGRT modalities were a combination of kV-2D and CTOR. CTOR was the only imaging modality for patients #2 and #3, and kV-2D was the only imaging modality for patient #4. The patients' respiratory motions were assessed using a 2-min surface position recorded by the SGRT system during treatment. SGRT offsets reported after IGRT shifts were recorded for each fraction of treatment. The agreement between SGRT and either kV-2D or CTOR was evaluated.Results: The respiratory motion amplitude was <4 mm in translation and <2.0 degrees in rotation for all patients. The mean and maximum amplitude of SGRT offsets after application of IGRT shifts were <=(2.6 mm, 1.6 degrees) and (6.8 mm, 4.5 degrees) relative to kV-2D-based IGRT; <=(3.0 mm, 2.6 degrees) and (5.0 mm, 4.7 degrees) relative to CTOR-based IGRT without breast tissue inflammation. For patient #3, breast inflammation was observed for the last three fractions of treatment, and the maximum SGRT offsets post CTOR shifts were up to (14.0 mm, 5.2 degrees).Conclusions: Due to the overall agreement between SGRT and IGRT within reasonable tolerance, SGRT has the potential to serve as a valuable auxiliary IGRT tool for proton breast treatment and may improve the efficiency of proton breast treatment.

Background: It has been shown that a significant reduction of mean heart dose and left anterior descending artery (LAD) dose can be achieved through the use of DIBH for left breast radiation therapy. Surface-guided DIBH has been widely adopted during the last decade, and there are mainly three commercially available SGRT systems. The reports of the performance of a newly released SGRT system for DIBH application are currently very limited. Purpose: To evaluate the clinical performance of a newly released SGRT system on DIBH for left breast radiation therapy. Methods: Twenty-five left breast cancer patients treated with DIBH utilizing Varian's Identify system were included (total 493-fraction treatments). Four aspects of the clinical performance were evaluated: Identify offsets of free breathing post patient setup from tattoos, Identify offsets during DIBH, Identify agreement with radiographic ports during DIBH, and DIBH reference surface re-capture post patient shifts. The systematic and random errors of free breathing Identify offsets post patient setup were calculated for each patient, as well as for offsets during DIBH. Radiographic ports were taken when the patient's DIBH position was within the clinical tolerance of (+/- 0.3 cm, +/- 3(0)), and these were then compared with treatment field DRRs. If the ports showed that the patient alignment did not agree with the DRRs within 3 mm, a patient shift was performed. A new reference surface was captured and verification ports were taken. Results: The all-patient average systematic and random errors of Identify offsets for free breathing were within (0.4 cm, 1.5(0)) post tattoo setup. The maximum per-patient systematic and random errors were (1.1 cm, 6.2(0)) and (0.9 cm, 2(0)), and the maximum amplitude of Identify offsets were (2.59 cm, 9(0)). All 493-fraction DIBH treatments were delivered and successfully guided by the Identify SGRT system. The systematic and random errors of Identify offsets for DIBH were within (0.2 cm, 2.3(0)). Seven patients needed re-captured surface references due to surface variation or position shifts based on the ports. All patient DIBH verification ports guided by Identify were approved by attending physicians. Conclusion: This evaluation showed that the Identify system performed effectively for surface-guided patient setup and surface-guided DIBH imaging and treatment delivery. The feature of color-coded real-time patient surface matching feedback facilitated the evaluation of the patient alignment accuracy and the adjustment of the patient position to match the reference.

AbstractPurposeTo characterize potential dose to the fetus for all modes of delivery (dynamic adaptive aperture, static adaptive aperture, and no adaptive aperture) for the Mevion S250i Proton Therapy System with HYPERSCAN and compare the findings with those of other available proton systems.Materials and MethodsFetal dose measurements were performed for all three modes of dose delivery on the Mevion S250i Proton therapy system with HYPERSCAN (static aperture, dynamic aperture and uncollimated). Standard treatment plans were created in RayStation for a left‐sided brain lesion treated with a vertex field, a left lateral field, and a posterior field. Measurements were performed using WENDI and the RANDO with the detector placed at representative locations to mimic the growth and movement of the fetus at different gestational stages.ResultsThe fetal dose measurements varied with fetus position and the largest measured dose was 64.7 μSv per 2 Gy (RBE) fraction using the dynamic aperture. The smallest estimated fetal dose was 45.0 μSv per 2 Gy (RBE) at the base of the RANDO abdomen (47 cm from isocenter to the outer width of WENDI and 58.5 cm from the center of the WENDI detector) for the static aperture delivery. The vertex fields at all depths had larger contributions to the total dose than the other two and the dynamic aperture plans resulted in the highest dose measured for all depths.ConclusionThe reported doses are lower than reported doses using a double‐scattering system. This work suggests that avoiding vertex fields and using the static aperture will help minimize dose to the fetus.

Background: Early detection of cancer offers the opportunity to identify candidates when curative treatments are achievable. The THUNDER study (THe UNintrusive Detection of EaRly-stage cancers, NCT04820868) aimed to evaluate the performance of enhanced linear-splinter amplification sequencing, a previously described cell-free DNA (cfDNA) methylation-based technology, in the early detection and localization of six types of cancers in the colorectum, esophagus, liver, lung, ovary, and pancreas.Patients and methods: A customized panel of 161 984 CpG sites was constructed and validated by public and in-house (cancer: n = 249; non-cancer: n = 288) methylome data, respectively. The cfDNA samples from 1693 participants (cancer: n = 735; non-cancer: n = 958) were retrospectively collected to train and validate two multi-cancer detection blood test (MCDBT-1/2) models for different clinical scenarios. The models were validated on a prospective and independent cohort of age-matched 1010 participants (cancer: n = 505; non-cancer: n = 505). Simulation using the cancer incidence in China was applied to infer stage shift and survival benefits to demonstrate the potential utility of the models in the real world.Results: MCDBT-1 yielded a sensitivity of 69.1% (64.8%-73.3%), a specificity of 98.9% (97.6%-99.7%), and tissue origin accuracy of 83.2% (78.7%-87.1%) in the independent validation set. For early-stage (I-III) patients, the sensitivity of MCDBT-1 was 59.8% (54.4%-65.0%). In the real-world simulation, MCDBT-1 achieved a sensitivity of 70.6% in detecting the six cancers, thus decreasing late-stage incidence by 38.7%-46.4%, and increasing 5-year survival rate by 33.1%-40.4%, respectively. In parallel, MCDBT-2 was generated at a slightly low specificity of 95.1% (92.8%-96.9%) but a higher sensitivity of 75.1% (71.9%-79.8%) than MCDBT-1 for populations at relatively high risk of cancers, and also had ideal performance.Conclusion: In this large-scale clinical validation study, MCDBT-1/2 models showed high sensitivity, specificity, and accuracy of predicted origin in detecting six types of cancers.

Purpose: To evaluate and characterize the overall clinical functionality and workflow of the newly released Varian Identify system (version 2.3). Methods: Three technologies included in the Varian Identify system were evaluated: patient biometric authentication, treatment accessory device identification, and surface-guided radiation therapy (SGRT) function. Biometric authentication employs a palm vein reader. Treatment accessory device verification utilizes two technologies: device presence via Radio Frequency Identification (RFID) and position via optical markers. Surface-guidance was evaluated on both patient orthopedic setup at loading position and surface matching and tracking at treatment isocenter. A phantom evaluation of the consistency and accuracy for Identify SGRT function was performed, including a system consistency test, a translational shift and rotational accuracy test, a pitch and roll accuracy test, a continuous recording test, and an SGRT vs Cone-Beam CT (CBCT) agreement test. Results: 201 patient authentications were verified successfully with palm reader. All patient treatment devices were successfully verified for their presences and positions (indexable devices). The patient real-time orthopedic pose was successfully adjusted to match the reference surface captured at simulation. SGRT-reported shift consistency against couch readout was within (0.1 mm, 0.03(0)). The shift accuracy was within (0.3 mm, 0.1(0)). In continuous recording mode, the maximum variation was 0.2 +/- 0.12 mm, 0.03(0) +/- 0.02(0). The difference between Identify SGRT offset and CBCT was within (1 mm, 1(0)). Conclusions: This clinical evaluation confirms that Identify accurately functions for patient palm identification and patient treatment device presence and position verification. Overall SGRT consistency and accuracy was within (1 mm, 1(0)), within the 2 mm criteria of AAPM TG302.

Objective:To construct the diagnostic model of superficial esophageal squamous cell carcinoma (ESCC) and precancerous lesions in endoscopic images based on the YOLOv5l model by using deep learning method of artificial intelligence to improve the diagnosis of early ESCC and precancerous lesions under endoscopy.Methods:13, 009 endoscopic esophageal images of white light imaging (WLI), narrow band imaging (NBI) and lugol chromoendoscopy (LCE) were collected from June 2019 to July 2021 from 1, 126 patients at the Cancer Hospital, Chinese Academy of Medical Sciences, including low-grade intraepithelial neoplasia, high-grade intraepithelial neoplasia, ESCC limited to the mucosal layer, benign esophageal lesions and normal esophagus. By computerized random function method, the images were divided into a training set (11, 547 images from 1, 025 patients) and a validation set (1, 462 images from 101 patients). The YOLOv5l model was trained and constructed with the training set, and the model was validated with the validation set, while the validation set was diagnosed by two senior and two junior endoscopists, respectively, to compare the diagnostic results of YOLOv5l model and those of the endoscopists.Results:In the validation set, the accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the YOLOv5l model in diagnosing early ESCC and precancerous lesions in the WLI, NBI and LCE modes were 96.9%, 87.9%, 98.3%, 88.8%, 98.1%, and 98.6%, 89.3%, 99.5%, 94.4%, 98.2%, and 93.0%, 77.5%, 98.0%, 92.6%, 93.1%, respectively. The accuracy in the NBI model was higher than that in the WLI model ( P<0.05) and lower than that in the LCE model ( P<0.05). The diagnostic accuracies of YOLOv5l model in the WLI, NBI and LCE modes for the early ESCC and precancerous lesions were similar to those of the 2 senior endoscopists (96.9%, 98.8%, 94.3%, and 97.5%, 99.6%, 91.9%, respectively; P>0.05), but significantly higher than those of the 2 junior endoscopists (84.7%, 92.9%, 81.6% and 88.3%, 91.9%, 81.2%, respectively; P<0.05). Conclusion:The constructed YOLOv5l model has high accuracy in diagnosing early ESCC and precancerous lesions in endoscopic WLI, NBI and LCE modes, which can assist junior endoscopists to improve diagnosis and reduce missed diagnoses.

<h3>Purpose</h3> Leipzig surface applicators are used for skin cancer treatment in high-dose-rate (HDR) brachytherapy. In clinical settings, physicians prescribe dose to a point at a depth between 3 to 5 mm for treatment planning. Therefore, it is important to accurately measure this point dose (related to the applicator's output). A parallel plate ionization chamber is a favorable option because it has a flat detection surface that fits the geometry of the applicator's treatment plane. This facilitates an accurate source-to-surface distance (SSD) setup, which is extremely important for the dose measurement because the applicator has a very short SSD. In this study, we quantified the volume averaging effect for using a Roos parallel plate ionization chamber to measure outputs of the Leipzig applicators. <h3>Materials and Methods</h3> The applicators (H10, H20 and H30) have three sizes (10, 20 and 30 mm). For each size, we measured the applicator's profiles with radiochromic films that were placed at depths of 0, 3 and 5 mm in solid water phantom. An Elekta Flexitron HDR ¹⁹²Ir source was used with the applicators to deliver radiation to the films. We digitized the films with a flatbed scanner and measured the intensities along the crossline profile at two locations: at radiation center and at 7.5 mm away from the center. We then calculated the ratios of the two intensities. The key element behind this design is the Roos chamber has an active, circular detecting area of 7.5 mm radius. Thus, the two points were selected at the center and the edge of the Roos chamber. In this way, the ratio quantifies the volume averaging effect (1 being no volume averaging). <h3>Results</h3> The ratios for H10 were significantly higher than those for H20 and H30. At depths of 0 and 3 mm, H10 had ratios of 1.46 and 1.49, respectively, and H20 and H30 had an averaged ratio of 1.08, indicating a 38.0% to 41.0% difference in heterogeneity. This evidence suggests the Roos chamber has significantly higher volume averaging effect for H10. The heterogeneity difference decreased at 5 mm depth. However, H10 still had approximately 10.0% higher ratio than H20 and H30, which had ratios closer to 1 at all three depths. <h3>Conclusions</h3> We found the Roos parallel plate ionization chamber had overall low volume averaging effect for output measurement of Leipzig surface applicators. However, it should not be used with the smallest applicator.

Purpose: A modern radiation oncology electronic medical record (RO-EMR) system represents a sophisticated human-computer interface with the potential to reduce human driven errors and improve patient safety. As the RO-EMR becomes an integral part of clinical processes, it may be advantageous to analyze learning opportunities (LO) based on their relationship with the RO-EMR. This work reviews one institution's documented LO to: (1) study their relationship with the RO-EMR workflow, (2) identify best opportunities to improve RO-EMR workflow design, and (3) identify current RO-EMR workflow challenges. Methods and Materials: Internal LO reports for an 11-year contiguous period were categorized by their relationship to the RO-EMR. We also identify the specific components of the RO-EMR used or involved in each LO. Additionally, contributing factor categories from the ASTRO/AAPM sponsored Radiation Oncology Incident Learning System's (RO-ILS) nomenclature was used to characterize LO directly linked to the RO-EMR. Results: A total of 163 LO from the 11-year period were reviewed and analyzed. Most (77.2%) LO involved the RO-EMR in some way. The majority of the LO were the results of human/manual operations. The most common RO-EMR components involved in the studied LO were documentation related to patient setup, treatment session schedule functionality, RO-EMR used as a communication/note-delivery tool, and issues with treatment accessories. Most of the LO had staff lack of attention and policy not followed as 2 of the highest occurring contributing factors. Conclusions: We found that the majority of LO were related to RO-EMR workflow processes. The high-risk areas were related to manual data entry or manual treatment execution. An evaluation of LO as a function of their relationship with the RO-EMR allowed for opportunities for improvement. In addition to regular radiation oncology quality improvement review and policy update, automated functions in RO-EMR remain highly desirable.

In current clinical practice, the routine approaches of axillary lymph node (ALN) status evaluation through sentinel lymph node biopsy (SLNB) is unsatisfied with high false-negative rate and brings significant complications. We aimed to develop a preoperative magnetic resonance imaging radiomic-based signature for predicting ALN metastasis (ALNM) in a non-invasive way. A total of 1,090 early-stage invasive breast cancer patients from 4 institutions were enrolled in this multicenter, retrospective, diagnositc study. Radiomic signature for ALNM prediction were constructed by machine learning in 803 patients from Sun Yat-sen Memorial Hospital and Sun Yat-sen University Cancer Center (Training cohort). The clinical-radiomic siganture was constructed by combining radiomic signature and significant clinic-pathological risk factors and was validated in patients from prospective phase III trials [NCT01503905] (Internal validation cohort, n=106), and Shunde Hospital and Tungwah Hospital (External validation cohort, n=181). This study is registered with ClinicalTrials.gov (NCT04003558) and Chinese Clinical Trail Registry (ChiCTR1900024020). The radiomic signature for predicting ALNM consisted of intratumoral and ALN features showed AUCs of 0.91, 0.88, and 0.85 in the training, internal validation and external validation cohorts. The clinical-radiomic signature achieved the highest AUCs of 0.93, 0.91, and 0.91 in the training, internal validation and external validation cohorts, which successfully discriminate high- from low risk relapse patients (HR 0.12, 95% CI 0.03–0.53; P<0.001) and was similar to the performance in ALNM and non-ALNM (HR 0.28, 95% CI 0.09–0.87; P=0.002). In additon, the clinical-radiomic signature also performed well in the subgroup of N1, N2, N3 status (AUCs of 0.89, 0.90, 0.97). This study developed a clinical-radiomic signature incorporated the intratumoral and ALN radiomic features and clinical risk factors, which could serve as a non-invasive tool to evaluate ALN status for guiding surgery plans of early-stage breast cancer patients.

IntroductionUltrasound (US) guidance of the prostate has long been conducted using a transabdominal (TA) approach. More recently, a transperineal (TP) approach has been made available for image guidance. Our aim was to determine if both methods produced similar alignments within the same patients.Materials and methodsWe utilized two clinical US image guidance (IG) systems (Elekta Clarity and Best BAT). The B‐mode Acquisition and Targeting USIG system is a bi‐planar, so‐called 2.5D USIG system, that is acquired TA. Clarity is a 3D US system that generates a volumetric 3D US data set and US‐derived IG contours that are coregistered to the planning CT images. The probe is oriented in the sagittal plane against the perineum (TP). After positioning the patient for treatment using the TP USIG, we maintained the position defined by Clarity tracking and then acquired a TA‐based USIG. The two US‐based methods of localizing the prostate (TA vs TP) were compared via Bland–Altman (BA) statistical analysis to determine if there was alignment agreement between methods.ResultsThe BA test for all 101 patients, 2093 fractions resulted in 95% confidence intervals (upper and lower limits of the BA test) of 0.6 mm in LR, 0.9 mm in AP and 1.0 mm in SI. The bias between the two systems was calculated as 0.03, 0.02, and 0.03 mm in LR, AP, and SI.ConclusionsBoth systems resulted in statistically equivalent targeting positions for the prostate. Because of the unique intrafraction, real‐time motion tracking capability of the TP system, this solution represents a unique extension to the previously reported clinical benefits of a TA approach by providing assurance of the prostate remaining in the treatment field during beam‐on.