Adverse radiation effect versus tumor progression following stereotactic radiosurgery for brain metastases: Implications of radiologic uncertainty.

BACKGROUND: Adverse radiation effect (ARE) following stereotactic radiosurgery (SRS) for brain metastases is challenging to distinguish from tumor progression. This study characterizes the clinical implications of radiologic uncertainty (RU). METHODS: Cases reviewed retrospectively at a single-institutional, multi-disciplinary SRS Tumor Board between 2015-2022 for RU following SRS were identified. Treatment history, diagnostic or therapeutic interventions performed upon RU resolution, and development of neurologic deficits surrounding intervention were obtained from the medical record. Differences in lesion volume and maximum diameter at RU onset versus resolution were compared with paired t-tests. Median time from RU onset to resolution was estimated using the Kaplan-Meier method. Univariate and multivariate associations between clinical characteristics and time to RU resolution were assessed with Cox proportional-hazards regression. RESULTS: Among 128 lesions with RU, 23.5% had undergone ≥ 2 courses of radiation. Median maximum diameter (20 vs. 16 mm, p < 0.001) and volume (2.7 vs. 1.5 cc, p < 0.001) were larger upon RU resolution versus onset. RU resolution took > 6 and > 12 months in 25% and 7% of cases, respectively. Higher total EQD2 prior to RU onset (HR = 0.45, p = 0.03) and use of MR perfusion (HR = 0.56, p = 0.001) correlated with shorter time to resolution; larger volume (HR = 1.05, p = 0.006) portended longer time to resolution. Most lesions (57%) were diagnosed as ARE. Most patients (58%) underwent an intervention upon RU resolution; of these, 38% developed a neurologic deficit surrounding intervention. CONCLUSIONS: RU resolution took > 6 months in > 25% of cases. RU may lead to suboptimal outcomes and symptom burden. Improved characterization of post-SRS RU is needed.

Phase-Resolved Functional Lung (PREFUL) MRI to Quantify Ventilation: Feasibility and Physiological Relevance in Severe Asthma.

RATIONALE AND OBJECTIVES: Emergent evidence in several respiratory diseases supports translational potential for Phase-Resolved Functional Lung (PREFUL) MRI to spatially quantify ventilation but its feasibility and physiological relevance have not been demonstrated in patients with asthma. This study compares PREFUL-derived ventilation defect percent (VDP) in severe asthma patients to healthy controls and measures its responsiveness to bronchodilator therapy and relation to established measures of airways disease. MATERIALS AND METHODS: Forty-one adults with severe asthma and seven healthy controls performed same-day free-breathing 1H MRI, 129Xe MRI, spirometry, and oscillometry. A subset of participants (n = 23) performed chest CT and another subset of participants with asthma (n = 19) repeated 1H MRI following the administration of a bronchodilator. VDP was calculated for both PREFUL and 129Xe MRI. Additionally, the percent of functional small airways disease was determined from CT parametric response maps (PRMfSAD). RESULTS: PREFUL VDP measured pre-bronchodilator (19.1% [7.4-43.3], p = 0.0002) and post-bronchodilator (16.9% [6.1-38.4], p = 0.0007) were significantly greater than that of healthy controls (7.5% [3.7-15.5]) and was significantly decreased post-bronchodilator (from 21.9% [10.1-36.9] to 16.9% [6.1-38.4], p = 0.0053). PREFUL VDP was correlated with spirometry (FEV1%pred: r = -0.46, p = 0.0023; FVC%pred: r = -0.35, p = 0.024, FEV1/FVC: r = -0.46, p = 0.0028), 129Xe MRI VDP (r = 0.39, p = 0.013), and metrics of small airway disease (CT PRMfSAD: r = 0.55, p = 0.021; Xrs5 Hz: r = -0.44, p = 0.0046, and AX: r = 0.32, p = 0.044). CONCLUSION: PREFUL-derived VDP is responsive to bronchodilator therapy in asthma and is associated with measures of airflow obstruction and small airway dysfunction. These findings validate PREFUL VDP as a physiologically relevant and accessible ventilation imaging outcome measure in asthma.

A Couch Mounted Smartphone-based Motion Monitoring System for Radiation Therapy.

PURPOSE: Surface-guided radiation-therapy (SGRT) systems are being adopted into clinical practice for patient setup and motion monitoring. However, commercial systems remain cost prohibitive to resource-limited clinics around the world. Our aim is to develop and validate a smartphone-based application using LiDAR cameras (such as on recent Apple iOS devices) for facilitating SGRT in low-resource centers. The proposed SGRT application was tested at multiple institutions and validated using phantoms and volunteers against various commercial systems to demonstrate feasibility. METHODS AND MATERIALS: An iOS application was developed in Xcode and written in Swift using the Augmented-Reality (AR) Kit and implemented on an Apple iPhone 13 Pro with a built-in LiDAR camera. The application contains multiple features: 1) visualization of both the camera and depth video feeds (at a ∼60Hz sample-frequency), 2) region-of-interest (ROI) selection over the patient's anatomy where motion is measured, 3) chart displaying the average motion over time in the ROI, and 4) saving/exporting the motion traces and surface map over the ROI for further analysis. The iOS application was tested to evaluate depth measurement accuracy for: 1) different angled surfaces, 2) different field-of-views over different distances, and 3) similarity to a commercially available SGRT systems (Vision RT AlignRT and Varian IDENTIFY) with motion phantoms and healthy volunteers across 3 institutions. Measurements were analyzed using linear-regressions and Bland-Altman analysis. RESULTS: Compared with the clinical system measurements (reference), the iOS application showed excellent agreement for depth (r = 1.000, P < .0001; bias = -0.07±0.24 cm) and angle (r = 1.000, P < .0001; bias = 0.02±0.69°) measurements. For free-breathing traces, the iOS application was significantly correlated to phantom motion (institute 1: r = 0.99, P < .0001; bias =-0.003±0.03 cm; institute 2: r = 0.98, P < .0001; bias = -0.001±0.10 cm; institute 3: r = 0.97, P < .0001; bias = 0.04±0.06 cm) and healthy volunteer motion (institute 1: r = 0.98, P < .0001; bias = -0.008±0.06 cm; institute 2: r = 0.99, P < .0001; bias = -0.007±0.12 cm; institute 3: r = 0.99, P < .0001; bias = -0.001±0.04 cm). CONCLUSIONS: The proposed approach using a smartphone-based application provides a low-cost platform that could improve access to surface-guided radiation therapy accounting for motion.

Tungsten Filled 3-Dimensional Printed Lung Blocks for Total Body Irradiation.

PURPOSE: Lung blocks for total-body irradiation are commonly used to reduce lung dose and prevent radiation pneumonitis. Currently, molten Cerrobend containing toxic materials, specifically lead and cadmium, is poured into molds to construct blocks. We propose a streamlined method to create 3-dimensional (3D)-printed lung block shells and fill them with tungsten ball bearings to remove lead and improve overall accuracy in the block manufacturing workflow. METHODS AND MATERIALS: 3D-printed lung block shells were automatically generated using an inhouse software, printed, and filled with 2 to 3 mm diameter tungsten ball bearings. Clinical Cerrobend blocks were compared with the physician drawn blocks as well as our proposed tungsten filled 3D-printed blocks. Physical and dosimetric comparisons were performed on a linac. Dose transmission through the Cerrobend and 3D-printed blocks were measured using point dosimetry (ion-chamber) and the on-board Electronic-Portal-Imaging-Device (EPID). Dose profiles from the EPID images were used to compute the full-width-half-maximum and to compare with the treatment-planning-system. Additionally, the coefficient-of-variation in the central 80% of full-width-half-maximum was computed and compared between Cerrobend and 3D-printed blocks. RESULTS: The geometric difference between treatment-planning-system and 3D-printed blocks was significantly lower than Cerrobend blocks (3D: -0.88 ± 2.21 mm, Cerrobend: -2.28 ± 2.40 mm, P = .0002). Dosimetrically, transmission measurements through the 3D-printed and Cerrobend blocks for both ion-chamber and EPID dosimetry were between 42% to 48%, compared with the open field. Additionally, coefficient-of-variation was significantly higher in 3D-printed blocks versus Cerrobend blocks (3D: 4.2% ± 0.6%, Cerrobend: 2.6% ± 0.7%, P < .0001). CONCLUSIONS: We designed and implemented a tungsten filled 3D-printed workflow for constructing total-body-irradiation lung blocks, which serves as an alternative to the traditional Cerrobend based workflow currently used in clinics. This workflow has the capacity of producing clinically useful lung blocks with minimal effort to facilitate the removal of toxic materials from the clinic.

Specific Ventilation in Severe Asthma Evaluated with Noncontrast Tidal Breathing 1H MRI.

Purpose To determine if proton (1H) MRI-derived specific ventilation is responsive to bronchodilator (BD) therapy and associated with clinical biomarkers of type 2 airway inflammation and airways dysfunction in severe asthma. Materials and Methods In this prospective study, 27 participants with severe asthma (mean age, 52 years ± 9 [SD]; 17 female, 10 male) and seven healthy controls (mean age, 47 years ± 16; five female, two male), recruited between 2018 and 2021, underwent same-day spirometry, respiratory oscillometry, and tidal breathing 1H MRI. Participants with severe asthma underwent all assessments before and after BD therapy, and type 2 airway inflammatory biomarkers were determined (blood eosinophil count, sputum eosinophil percentage, sputum eosinophil-free granules, and fraction of exhaled nitric oxide) to generate a cumulative type 2 biomarker score. Specific ventilation was derived from tidal breathing 1H MRI and its response to BD therapy, and relationships with biomarkers of type 2 airway inflammation and airway dysfunction were evaluated. Results Mean MRI specific ventilation improved with BD inhalation (from 0.07 ± 0.04 to 0.11 ± 0.04, P < .001). Post-BD MRI specific ventilation (P = .046) and post-BD change in MRI specific ventilation (P = .006) were greater in participants with asthma with type 2 low biomarkers compared with participants with type 2 high biomarkers of airway inflammation. Post-BD change in MRI specific ventilation was correlated with change in forced expiratory volume in 1 second (r = 0.40, P = .04), resistance at 5 Hz (r = -0.50, P = .01), resistance at 19 Hz (r = -0.42, P = .01), reactance area (r = -0.54, P < .01), and reactance at 5 Hz (r = 0.48, P = .01). Conclusion Specific ventilation evaluated with tidal breathing 1H MRI was responsive to BD therapy and was associated with clinical biomarkers of airways disease in participants with severe asthma. Keywords: MRI, Severe Asthma, Ventilation, Type 2 Inflammation Supplemental material is available for this article. © RSNA, 2023 See also the commentary by Moore and Chandarana in this issue.

Functional Lung Avoidance for Individualized Radiation Therapy: Results of a Double-Masked, Randomized Controlled Trial.

PURPOSE: To determine whether functional lung avoidance based on 3He magnetic resonance imaging (MRI) improves quality of life (QOL) for patients undergoing concurrent chemoradiotherapy (CCRT) for advanced non-small cell lung cancer. METHODS AND MATERIALS: Patients with stage III non-small cell lung cancer (or oligometastatic disease treated with curative intent) undergoing CCRT with at least a 10 pack-year smoking history were eligible. Patients underwent pretreatment 3He MRI to measure lung ventilation and had 2 radiation therapy (RT) plans created before randomization: a standard plan, which did not make use of the 3He MRI, and an avoidance plan, preferentially sparing well-ventilated lung. All participants were masked to assignment except the physicist responsible for exporting the selected plan. The primary end point was patient-reported QOL measured at 3-months post-RT by the FACT-L lung cancer subscale (LCS); secondary end points included other QOL metrics, toxicity, and survival outcomes. Target accrual was 64. RESULTS: Twenty-seven patients were randomized before the trial was closed due to slower-than-expected accrual, with 11 randomized to the standard arm and 16 to the avoidance arm. Baseline patient characteristics were well-balanced. At 3 months post-RT, the mean ± SD LCS scores were 17.4 ± 2.8 versus 17.3 ± 6.1 for the standard and avoidance arms, respectively (P = .485). A clinically meaningful, prespecified decline of ≥3 points in the LCS score was observed in 50% (4/8) in the standard arm and 33% (4/12) in the avoidance arm (P = .648). Two patients in each arm developed grade ≥2 radiation pneumonitis, with no grade ≥4 toxicities. CONCLUSIONS: Although this trial did not reach full accrual, QOL scores were very similar between arms. Due to the scarcity of 3He MRI, other, more commonly available methods to measure functional lung, such as 4-dimensional computed tomography ventilation mapping, may be considered in the assessment of functional lung avoidance RT, and a larger, multicenter approach would be needed to accrue sufficient patients to test such approaches.

Acute and Late Esophageal Toxicity After SABR to Thoracic Tumors Near or Abutting the Esophagus.

PURPOSE: Our purpose was to evaluate the incidence of acute and late esophageal toxicity in patients with thoracic tumors near or abutting the esophagus treated with SABR. METHODS AND MATERIALS: Among patients with thoracic tumors treated with SABR, we identified those with tumors near or abutting the esophagus. Using the linear-quadratic model with an α/ß ratio of 10, we determined the correlation between dosimetric parameters and esophageal toxicity graded using the Common Terminology Criteria for Adverse Events, version 5.0. RESULTS: Out of 2200 patients treated with thoracic SABR, 767 patients were analyzable for esophageal dosimetry. We identified 55 patients with tumors near the esophagus (52 evaluable for esophagitis grade) and 28 with planning target volume (PTV) overlapping the esophagus. Dose gradients across the esophagus were consistently sharp. Median follow-up and overall survival were 16 and 23 months, respectively. Thirteen patients (25%) developed temporary grade 2 acute esophageal toxicity, 11 (85%) of whom had PTV overlapping the esophagus. Symptoms resolved within 1 to 3 months in 12 patients and 6 months in all patients. No grade 3 to 5 toxicity was observed. Only 3 patients (6%) developed late or persistent grade 2 dysphagia or dyspepsia of uncertain relationship to SABR. The cumulative incidence of acute esophagitis was 15% and 25% at 14 and 60 days, respectively. Acute toxicity correlated on univariate analysis with esophageal Dmax, D1cc, D2cc, Dmax/Dprescription, and whether the PTV was overlapping the esophagus. Esophageal Dmax (BED10) <62 Gy, D1cc (BED10) <48 Gy, D2cc (BED10) <43 Gy, and Dmax/Dprescription <85% were associated with <20% risk of grade 2 acute esophagitis. Only 2 local recurrences occurred. CONCLUSIONS: Although 25% of patients with tumors near the esophagus developed acute esophagitis (39% of those with PTV overlapping the esophagus), these toxicities were all grade 2 and all temporary. This suggests the safety and efficacy of thoracic SABR for tumors near or abutting the esophagus when treating with high conformity and sharp dose gradients.

A robotically assisted 3D printed quality assurance lung phantom for Calypso.

Purpose. Radiation dose delivered to targets located near the upper-abdomen or in the thorax are significantly affected by respiratory-motion. Relatively large-margins are commonly added to compensate for this motion, limiting radiation-dose-escalation. Internal-surrogates of target motion, such as a radiofrequency (RF) tracking system, i.e. Calypso®System, are used to overcome this challenge and improve normal-tissue sparing. RF tracking systems consist of implanting transponders in the vicinity of the tumor to be tracked using radiofrequency-waves. Unfortunately, although the manufacture provides a universal quality-assurance (QA) phantom, QA-phantoms specifically for lung-applications are limited, warranting the development of alternative solutions to fulfil the tests mandated by AAPM's TG142. Accordingly, our objective was to design and develop a motion-phantom to evaluate Calypso for lung-applications that allows the Calypso®Beacons to move in different directions to better simulate truelung-motion.Methods and Materials.A Calypso lung QA-phantom was designed, and 3D-printed. The design consists of three independent arms where the transponders were attached. A pinpoint-chamber with a buildup-cap was also incorporated. A 4-axis robotic arm was programmed to drive the motion-phantom to mimic breathing. After acquiring a four-dimensional-computed-tomography (4DCT) scan of the motion-phantom, treatment-plans were generated and delivered on a Varian TrueBeam®with Calypso capabilities. Stationary and gated-treatment plans were generated and delivered to determine the dosimetric difference between gated and non-gated treatments. Portal cine-images were acquired to determine the temporal-accuracy of delivery by calculating the difference between the observed versus expected transponders locations with the known speed of the transponders' motion.Results.Dosimetric accuracy is better than the TG142 tolerance of 2%. Temporal accuracy is greater than, TG142 tolerance of 100 ms for beam-on, but less than 100 ms for beam-hold.Conclusions.The robotic QA-phantom designed and developed in this study provides an independent phantom for performing Calypso lung-QA for commissioning and acceptance testing of Calypso for lung treatments.

Precision radiotherapy using monochromatic inverse Compton x-ray sources.

PURPOSE: The dosimetric properties of inverse Compton (IC) x-ray sources were investigated to determine their utility for stereotactic radiation therapy. METHODS: Monte Carlo simulations were performed using the egs brachy user code of EGSnrc. Nominal IC source x-ray energies of 80 and 150 keV were considered in this work. Depth-dose and lateral dose profiles in water were calculated, as was dose enhancement in the bone. Further simulations were performed for brain and spine treatment sites. The impact of gold nanoparticle doping was also investigated for the brain treatment site. Analogous dose calculations were performed in a clinical treatment planning system using a clinical 6 MV photon beam model and were compared to the Monte Carlo simulations. RESULTS: Both 80 and 150 keV IC beams were observed to have sharp 80-20 penumbra (i.e., < 0.1 mm) with broad low-dose tails in water. For reference, the calculated penumbra for the 6 MV clinical beam was 3 mm. Maximum dose enhancement factors in bone of 3.1, 1.4, and 1.1 were observed for the 80, 150 keV, and clinical 6 MV beams, respectively. The plan quality for the single brain metastasis case was similar between the IC beams and the 6 MV beam without gold nanoparticles. As the concentration of gold within the target increased, the V12 Gy to the normal brain tissue and D max within the target volume significantly decreased and the conformity significantly improved, which resulted in superior plan quality over the clinical 6 MV beam plan. In the spine cases, the sharp penumbra and enhanced dose to bone of the IC beams produced superior plan quality (i.e., better conformity, normal tissue sparing, and spinal cord sparing) as compared to the clinical 6 MV beam plans. CONCLUSIONS: The findings from this work indicate that inverse Compton x-ray sources are well suited for stereotactic radiotherapy treatments due to their sharp penumbra and dose enhancement around high atomic number materials. Future work includes investigating the properties of intensity-modulated inverse Compton x-ray sources to improve the homogeneity within the target tissue.

Pulmonary Ventilation Maps Generated with Free-breathing Proton MRI and a Deep Convolutional Neural Network.

Background Hyperpolarized noble gas MRI helps measure lung ventilation, but clinical translation remains limited. Free-breathing proton MRI may help quantify lung function using existing MRI systems without contrast material and may assist in providing information about ventilation not visible to the eye or easily extracted with segmentation methods. Purpose To explore the use of deep convolutional neural networks (DCNNs) to generate synthetic MRI ventilation scans from free-breathing MRI (deep learning [DL] ventilation MRI)-derived specific ventilation maps as a surrogate of noble gas MRI and to validate this approach across a wide range of lung diseases. Materials and Methods In this secondary analysis of prospective trials, 114 paired noble gas MRI and two-dimensional free-breathing MRI scans were obtained in healthy volunteers with no history of chronic or acute respiratory disease and in study participants with a range of different obstructive lung diseases, including asthma, bronchiectasis, chronic obstructive pulmonary disease, and non-small-cell lung cancer between September 2013 and April 2018 (ClinicalTrials.gov identifiers: NCT03169673, NCT02351141, NCT02263794, NCT02282202, NCT02279329, and NCT02002052). A U-Net-based DCNN model was trained to map free-breathing proton MRI to hyperpolarized helium 3 (3He) MRI ventilation and validated using a sixfold validation. During training, the DCNN ventilation maps were compared with noble gas MRI scans using the Pearson correlation coefficient (r) and mean absolute error. DCNN ventilation images were segmented for ventilation and ventilation defects and were compared with noble gas MRI scans using the Dice similarity coefficient (DSC). Relationships were evaluated with the Spearman correlation coefficient (rS). Results One hundred fourteen study participants (mean age, 56 years ± 15 [standard deviation]; 66 women) were evaluated. As compared with 3He MRI, DCNN model ventilation maps had a mean r value of 0.87 ± 0.08. The mean DSC for DL ventilation MRI and 3He MRI ventilation was 0.91 ± 0.07. The ventilation defect percentage for DL ventilation MRI was highly correlated with 3He MRI ventilation defect percentage (rS = 0.83, P < .001, mean bias = -2.0% ± 5). Both DL ventilation MRI (rS = -0.51, P < .001) and 3He MRI (rS = -0.61, P < .001) ventilation defect percentage were correlated with the forced expiratory volume in 1 second. The DCNN model required approximately 2 hours for training and approximately 1 second to generate a ventilation map. Conclusion In participants with diverse pulmonary pathologic findings, deep convolutional neural networks generated ventilation maps from free-breathing proton MRI trained with a hyperpolarized noble-gas MRI ventilation map data set. The maps showed correlation with noble gas MRI ventilation and pulmonary function measurements. © RSNA, 2020 See also the editorial by Vogel-Claussen in this issue.

Technical Note: Performance of CyberKnife® tracking using low-dose CT and kV imaging.

PURPOSE: To investigate the effects of CT protocol and in-room x-ray technique on CyberKnife® (Accuray Inc.) tracking accuracy by evaluating end-to-end tests. METHODS: End-to-end (E2E) tests were performed for the different tracking methods (6D skull, fiducial, spine, and lung) using an anthropomorphic head phantom (Accuray Inc.) and thorax phantom (CIRS Inc.). Bolus was added to the thorax phantom to simulate a large patient and to evaluate the performance of lung tracking in a more realistic condition. The phantoms were scanned with a Siemens Sensation Open 24 slice CT at low dose (120 kV, 70 mAs, 1.5 mm slice thickness) and high dose (120 kV, 700 mAs, 1.5 mm slice thickness) to generate low-dose and high-dose digitally reconstructed radiographs (DRRs). The difference in initial phantom alignment, Δ(Align), and in total targeting accuracy, E2E, were obtained for all tracking methods with low- and high-dose DRRs. Additionally, Δ(Align) was determined for different in-room x-ray imaging techniques (0.5 to 50 mAs and 100 to 140 kV) using a low-dose lung tracking plan. RESULTS: Low-dose CT scans produced images with high noise; however, for these phantoms the targets could be easily delineated on all scans. End-to-end results were less than 0.95 mm for all tracking methods and all plans. The greatest difference in initial alignment Δ(Align) and E2E results between low- and high-dose CT protocols was 0.32 and 0.24 mm, respectively. Similar results were observed with a large thorax phantom. Tracking using different in-room x-ray imaging techniques (mAs) corresponding to low exposures (resulting in high image noise) or high exposure (resulting in image saturation) had alignment accuracy Δ(Align) greater than 1 mm. CONCLUSIONS: End-to-end targeting accuracy within tolerance (<0.95 mm) was obtained for all tracking methods using low-dose CT protocols, suggesting that CT protocol should be set by target contouring needs. Additionally, high tracking accuracy was achieved for in-room x-ray imaging techniques that produce high-quality images.

Technical Note: Evaluation of audiovisual biofeedback smartphone application for respiratory monitoring in radiation oncology.

PURPOSE: Radiation dose delivered to targets located near the upper abdomen or thorax are significantly affected by respiratory motion, necessitating large margins, limiting dose escalation. Surrogate motion management devices, such as the Real-time Position Management (RPM™) system (Varian Medical Systems, Palo Alto, CA), are commonly used to improve normal tissue sparing. Alternative to current solutions, we have developed and evaluated the feasibility of a real-time position management system that leverages the motion data from the onboard hardware of Apple iOS devices to provide patients with visual coaching with the potential to improve the reproducibility of breathing as well as improve patient compliance and reduce treatment delivery time. METHODS AND MATERIALS: The iOS application, coined the Instant Respiratory Feedback (IRF) system, was developed in Swift (Apple Inc., Cupertino, CA) using the Core-Motion library and implemented on an Apple iPhone® devices. Operation requires an iPhone®, a three-dimensional printed arm, and a radiolucent projector screen system for feedback. Direct comparison between IRF, which leverages sensor fusion data from the iPhone®, and RPM™, an optical-based system, was performed on multiple respiratory motion phantoms and volunteers. The IRF system and RPM™ camera tracking marker were placed on the same location allowing for simultaneous data acquisition. The IRF surrogate measurement of displacement was compared to the signal trace acquired using RPM™ with univariate linear regressions and Bland-Altman analysis. RESULTS: Periodic motion shows excellent agreement between both systems, and subject motion shows good agreement during regular and irregular breathing motion. Comparison of IRF and RPM™ show very similar signal traces that were significantly related across all phantoms, including those motion with different amplitude and frequency, and subjects' waveforms (all r > 0.9, P < 0.0001). We demonstrate the feasibility of performing four-dimensional cone beam computed tomography using IRF which provided similar image quality as RPM™ when reconstructing dynamic motion phantom images. CONCLUSIONS: Feasibility of an iOS application to provide real-time respiratory motion is demonstrated. This system generated comparable signal traces to a commercially available system and offers an alternative method to monitor respiratory motion.

Parametric Response Mapping of Coregistered Positron Emission Tomography and Dynamic Contrast Enhanced Computed Tomography to Identify Radioresistant Subvolumes in Locally Advanced Cervical Cancer.

PURPOSE: To identify subvolumes that may predict treatment response to definitive concurrent chemoradiation therapy using parametric response mapping (PRM) of coregistered positron emission tomography (PET) and dynamic contrast-enhanced (DCE) computed tomography (CT) in locally advanced cervical carcinoma. METHODS AND MATERIALS: Pre- and midtreatment (after 23 ± 4 days of concurrent chemoradiation therapy) DCE CT and PET imaging were performed on 21 patients with cervical cancer who were enrolled in a pilot study to evaluate the prognostic value of CT perfusion for primary cervical cancer (NCT01805141). Three-dimensional coregistered maps of PET/CT standardized uptake value (SUV) and DCE CT blood flow (BF) were generated. PRM was performed using voxel-wise joint histogram analysis to classify voxels within the tumor as highly metabolic and perfused (SUVhiBFhi), highly metabolic and hypoxic (SUVhiBFlo), low metabolic activity and hypoxic (SUVloBFlo), or low metabolic activity and perfused (SUVloBFhi) tissue based on thresholds determined from population means of pretreatment PET SUV and DCE CT BF. Relationships between baseline pretreatment imaging metrics and relative changes in metabolic tumor volume (ΔMTV), calculated from before treatment and during treatment imaging, were determined using univariable and multivariable linear regression models. RESULTS: The relative volume of three PRM subvolumes significantly changed during treatment (SUVhiBFhi: P = .04; SUVhiBFlo: P = .0008; SUVloBFhi: P = .02), whereas SUVloBFlo did not (P = .9). Pretreatment PET SUVmax (r = -.58, P = .006), PET SUVmean (ρ = -.59, P = .005), DCE CT BFmean (r = -.50, P = .02), tumor volume (ρ = -.65, P = .001) and PRM SUVhiBFhi (ρ = -.59, P = .004) were negatively correlated with ΔMTV, whereas PRM SUVloBFlo was positively related to ΔMTV (r = .77, P < .0001). In a multivariable model that predicted ΔMTV, PRM SUVloBFlo, which combines both PET/CT and DCE CT, was the only significant variable (ß = 1.825, P = .03), dominating both imaging modalities independently. CONCLUSIONS: PRM was applied in locally advanced cervical carcinoma treated definitively with chemoradiation, and radioresistant subvolumes were identified that correlated with changes in MTV and predicted treatment response. Identification of these subvolumes may assist in clinical decision making to tailor therapies, such as brachytherapy, in an effort to improve patient outcomes.

An integrated quality assurance phantom for frameless single-isocenter multitarget stereotactic radiosurgery.

Brain stereotactic radiosurgery (SRS) treatments require multiple quality assurance (QA) procedures to ensure accurate and precise treatment delivery. As single-isocenter multitarget SRS treatments become more popular, the quantification of off-axis accuracy of the linear accelerator is crucial. In this study, a novel brain SRS integrated phantom was developed and validated to enable SRS QA with a single phantom to facilitate implementation of a frameless single-isocenter, multitarget SRS program. This phantom combines the independent verification of each positioning system, the Winston-Lutz, off-axis accuracy evaluation (i.e. off-axis Winston-Lutz), and the dosimetric accuracy utilizing both point dose measurements as well as film measurement, without moving the phantom. A novel 3D printed phantom, coined OneIso, was designed with a movable insert which can switch between the Winston-Lutz test target and dose measurement without moving the phantom itself. For dose verification, ten brain SRS clinical treatment plans with 10 MV flattening-filter-free beams were delivered on a Varian TrueBeam with a high-definition multileaf collimator (HD-MLC). Radiochromic film and pinpoint ion chamber comparison measurements were made between the OneIso and solid water (SW) phantom setups. For the off-axis Winston-Lutz measurements, a row of off-axis ball bearings (BBs) was integrated into the OneIso. To quantify the spatial accuracy versus distance from the isocenter, two-dimensional displacements were calculated between the planned and delivered BB locations relative to their respective MLC defined field border. OneIso and the SW phantoms agree within 1%, for both film and point dose measurements. OneIso identified a reduction in spatial accuracy further away from the isocenter. Differences increased as distance from the isocenter increased, exceeding recommended SRS accuracy tolerances at 7 cm away from the isocenter. OneIso provides a streamlined, single-setup workflow for single-isocenter multitarget frameless linac-based SRS QA. Additionally, with the ability to quantify off-axis spatial discrepancies, we can determine limitations on the maximum distance between targets to ensure a single-isocenter multitarget SRS program meets recommended guidelines.

Pulmonary Imaging Phenotypes of Chronic Obstructive Pulmonary Disease Using Multiparametric Response Maps.

Background Pulmonary imaging of chronic obstructive pulmonary disease (COPD) has focused on CT or MRI measurements, but these have not been evaluated in combination. Purpose To generate multiparametric response map (mPRM) measurements in ex-smokers with or without COPD by using volume-matched CT and hyperpolarized helium 3 (3He) MRI. Materials and Methods In this prospective study (https://clinicaltrials.gov, NCT02279329), participants underwent MRI and CT and completed pulmonary function tests, questionnaires, and the 6-minute walk test between December 2010 and January 2019. Disease status was determined by using Global initiative for chronic Obstructive Lung Disease (GOLD) criteria. The mPRM voxel values were generated by using co-registered MRI and CT labels. Kruskal-Wallis and Bonferroni tests were used to determine differences across disease severity, and correlations were determined by using Spearman coefficients. Results A total of 175 ex-smokers (mean age, 69 years ± 9 [standard deviation], 108 men) with or without COPD were evaluated. Ex-smokers without COPD had a larger fraction of normal mPRM voxels (60% vs 37%, 20%, and 7% for GOLD I, II, and III/IV disease, respectively; all P ≤ .001) and a smaller fraction of abnormal voxels, including small airways disease (normal CT, not ventilated: 5% vs 6% [not significant], 11%, and 19% [P ≤ .001 for both] for GOLD I, II, and III/IV disease, respectively) and mild emphysema (normal CT, abnormal apparent diffusion coefficient [ADC]: 33% vs 54%, 56%, and 54% for GOLD I, II, and III/IV disease respectively; all P ≤ .001). Normal mPRM measurements were positively correlated with forced expiratory volume in 1 second (FEV1) (r = 0.65, P < .001), the FEV1-to-forced vital capacity ratio (r = 0.81, P < .001), and diffusing capacity (r = 0.75, P < .001) and were negatively correlated with worse quality of life (r = -0.48, P < .001). Abnormal mPRM measurements of small airways disease (normal CT, not ventilated) and mild emphysema (normal CT, abnormal ADC) were negatively correlated with FEV1 (r = -0.65 and -0.42, respectively; P < .001) and diffusing capacity (r = -0.53 and -0.60, respectively; P < .001) and were positively correlated with worse quality of life (r = 0.45 and r = 0.33, respectively; P < .001), both of which were present in ex-smokers without COPD. Conclusion Multiparametric response maps revealed two abnormal structure-function results related to emphysema and small airways disease, both of which were unexpectedly present in ex-smokers with normal spirometry and CT findings. © RSNA, 2020 Online supplemental material is available for this article.

Chronic Obstructive Pulmonary Disease: Thoracic CT Texture Analysis and Machine Learning to Predict Pulmonary Ventilation.

Background Fixed airflow limitation and ventilation heterogeneity are common in chronic obstructive pulmonary disease (COPD). Conventional noncontrast CT provides airway and parenchymal measurements but cannot be used to directly determine lung function. Purpose To develop, train, and test a CT texture analysis and machine-learning algorithm to predict lung ventilation heterogeneity in participants with COPD. Materials and Methods In this prospective study (ClinicalTrials.gov: NCT02723474; conducted from January 2010 to February 2017), participants were randomized to optimization (n = 1), training (n = 67), and testing (n = 27) data sets. Hyperpolarized (HP) helium 3 (3He) MRI ventilation maps were co-registered with thoracic CT to provide ground truth labels, and 87 quantitative imaging features were extracted and normalized to lung averages to generate 174 features. The volume-of-interest dimension and the training data sampling method were optimized to maximize the area under the receiver operating characteristic curve (AUC). Forward feature selection was performed to reduce the number of features; logistic regression, linear support vector machine, and quadratic support vector machine classifiers were trained through fivefold cross validation. The highest-performing classification model was applied to the test data set. Pearson coefficients were used to determine the relationships between the model, MRI, and pulmonary function measurements. Results The quadratic support vector machine performed best in training and was applied to the test data set. Model-predicted ventilation maps had an accuracy of 88% (95% confidence interval [CI]: 88%, 88%) and an AUC of 0.82 (95% CI: 0.82, 0.83) when the HP 3He MRI ventilation maps were used as the reference standard. Model-predicted ventilation defect percentage (VDP) was correlated with VDP at HP 3He MRI (r = 0.90, P < .001). Both model-predicted and HP 3He MRI VDP were correlated with forced expiratory volume in 1 second (FEV1) (model: r = -0.65, P < .001; MRI: r = -0.70, P < .001), ratio of FEV1 to forced vital capacity (model: r = -0.73, P < .001; MRI: r = -0.75, P < .001), diffusing capacity (model: r = -0.69, P < .001; MRI: r = -0.65, P < .001), and quality-of-life score (model: r = 0.59, P = .001; MRI: r = 0.65, P < .001). Conclusion Model-predicted ventilation maps generated by using CT textures and machine learning were correlated with MRI ventilation maps (r = 0.90, P < .001). © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Fain in this issue.

CT and Functional MRI to Evaluate Airway Mucus in Severe Asthma.

BACKGROUND: Intraluminal contributor(s) to airflow obstruction in severe asthma are patient-specific and must be evaluated to personalize treatment. The occurrence and functional consequence of airway mucus in the presence or absence of airway eosinophils remain undetermined. OBJECTIVE: The objective of this study was to understand the functional consequence of airway mucus in the presence or absence of eosinophils and to identify biomarkers of mucus-related airflow obstruction. METHODS: Mucus plugs were quantified on CT scans, and their contribution to ventilation heterogeneity (using MRI ventilation defect percent [VDP]) was evaluated in 27 patients with severe asthma. Patients were dichotomized based on sputum eosinophilia such that the relationship between mucus, eosinophilia, and ventilation heterogeneity could be investigated. Fractional exhaled nitric oxide (Feno) and related cytokines in sputum were measured. RESULTS: Mucus plugging was present in 100% of asthma patients with sputum eosinophils and 36% of those without sputum eosinophils (P = .0006) and was correlated with MRI VDP prebronchodilator (r = 0.68; P = .0001) and postbronchodilator (r = 0.72; P < .0001). In a multivariable regression, both mucus and eosinophils contributed to the prediction of postbronchodilator MRI VDP (R2 = 0.75; P < .0001). Patients with asthma in whom the mucus score was high had raised Feno (P = .03) and IL-4 (P = .02) values. Mucus plugging correlated with Feno (r = 0.63; P = .005). CONCLUSIONS: Both airway eosinophils and mucus can contribute to ventilation heterogeneity in patients with severe asthma. Patients in whom mucus is the dominant cause of airway obstruction have evidence of an upregulated IL-4/IL-13 pathway that could be identified according to increased Feno level.

A framework for Fourier-decomposition free-breathing pulmonary 1 H MRI ventilation measurements.

PURPOSE: To develop a rapid Fourier decomposition (FD) free-breathing pulmonary 1 H MRI (FDMRI) image processing and biomarker pipeline for research use. METHODS: We acquired MRI in 20 asthmatic subjects using a balanced steady-state free precession (bSSFP) sequence optimized for ventilation imaging. 2D 1 H MRI series were segmented by enforcing the spatial similarity between adjacent images and the right-to-left lung volume-ratio. The segmented lung series were co-registered using a coarse-to-fine deformable registration framework that used dual optimization techniques. All pairwise registrations were implemented in parallel and FD was performed to generate 2D ventilation-weighted maps and ventilation-defect-percent (VDP). Lung segmentation and registration accuracy were evaluated by comparing algorithm and manual lung-masks, deformed manual lung-masks, and fiducials in the moving and fixed images using Dice-similarity-coefficient (DSC), mean-absolute-distance (MAD), and target-registration-error (TRE). The relationship of FD-VDP and 3 He-VDP was evaluated using the Pearson-correlation-coefficient (r) and Bland Altman analysis. Algorithm reproducibility was evaluated using the coefficient-of-variation (CoV) and intra-class-correlation-coefficient (ICC) for segmentation, registration, and FD-VDP components. RESULTS: For lung segmentation, there was a DSC of 95 ± 1.5% and MAD of 2.3 ± 0.5 mm, and for registration there was a DSC of 97 ± 0.8%, MAD of 1.6 ± 0.4 mm and TRE of 3.6 ± 1.2 mm. Reproducibility for segmentation DSC (CoV/ICC = 0.5%/0.92), registration TRE (CoV/ICC = 0.4%/0.98), and FD-VDP (Cov/ICC = 3.9%/0.97) was high. The pipeline required 10 min/subject. FD-VDP was correlated with 3 He-VDP (r = 0.69, P < 0.001) although there was a bias toward lower FD-VDP (bias = -4.9%). CONCLUSIONS: We developed and evaluated a pipeline that provides a rapid and precise method for FDMRI ventilation maps.

Free-breathing Pulmonary MR Imaging to Quantify Regional Ventilation.

Purpose To measure regional specific ventilation with free-breathing hydrogen 1 (1H) magnetic resonance (MR) imaging without exogenous contrast material and to investigate correlations with hyperpolarized helium 3 (3He) MR imaging and pulmonary function test measurements in healthy volunteers and patients with asthma. Materials and Methods Subjects underwent free-breathing 1H and static breath-hold hyperpolarized 3He MR imaging as well as spirometry and plethysmography; participants were consecutively recruited between January and June 2017. Free-breathing 1H MR imaging was performed with an optimized balanced steady-state free-precession sequence; images were retrospectively grouped into tidal inspiration or tidal expiration volumes with exponentially weighted phase interpolation. MR imaging volumes were coregistered by using optical flow deformable registration to generate 1H MR imaging-derived specific ventilation maps. Hyperpolarized 3He MR imaging- and 1H MR imaging-derived specific ventilation maps were coregistered to quantify regional specific ventilation within hyperpolarized 3He MR imaging ventilation masks. Differences between groups were determined with the Mann-Whitney test and relationships were determined with Spearman (ρ) correlation coefficients. Statistical analyses were performed with software. Results Thirty subjects (median age: 50 years; interquartile range [IQR]: 30 years), including 23 with asthma and seven healthy volunteers, were evaluated. Both 1H MR imaging-derived specific ventilation and hyperpolarized 3He MR imaging-derived ventilation percentage were significantly greater in healthy volunteers than in patients with asthma (specific ventilation: 0.14 [IQR: 0.05] vs 0.08 [IQR: 0.06], respectively, P < .0001; ventilation percentage: 99% [IQR: 1%] vs 94% [IQR: 5%], P < .0001). For all subjects, 1H MR imaging-derived specific ventilation correlated with plethysmography-derived specific ventilation (ρ = 0.54, P = .002) and hyperpolarized 3He MR imaging-derived ventilation percentage (ρ = 0.67, P < .0001) as well as with forced expiratory volume in 1 second (FEV1) (ρ = 0.65, P = .0001), ratio of FEV1 to forced vital capacity (ρ = 0.75, P < .0001), ratio of residual volume to total lung capacity (ρ = -0.68, P < .0001), and airway resistance (ρ = -0.51, P = .004). 1H MR imaging-derived specific ventilation was significantly greater in the gravitational-dependent versus nondependent lung in healthy subjects (P = .02) but not in patients with asthma (P = .1). In patients with asthma, coregistered 1H MR imaging specific ventilation and hyperpolarized 3He MR imaging maps showed that specific ventilation was diminished in corresponding 3He MR imaging ventilation defects (0.05 ± 0.04) compared with well-ventilated regions (0.09 ± 0.05) (P < .0001). Conclusion 1H MR imaging-derived specific ventilation correlated with plethysmography-derived specific ventilation and ventilation defects seen by using hyperpolarized 3He MR imaging. © RSNA, 2018 Online supplemental material is available for this article.