Dynamic lung aeration and strain with positive end-expiratory pressure individualized to maximal compliance versus ARDSNet low-stretch strategy: a study in a surfactant depletion model of lung injury.

BACKGROUND: Positive end-expiratory pressure (PEEP) individualized to a maximal respiratory system compliance directly implies minimal driving pressures with potential outcome benefits, yet, raises concerns on static and dynamic overinflation, strain and cyclic recruitment. Detailed accurate assessment and understanding of these has been hampered by methodological limitations. We aimed to investigate the effects of a maximal compliance-guided PEEP strategy on dynamic lung aeration, strain and tidal recruitment using current four-dimensional computed tomography (CT) techniques and analytical methods of tissue deformation in a surfactant depletion experimental model of acute respiratory distress syndrome (ARDS). METHODS: ARDS was induced by saline lung lavage in anesthetized and mechanically ventilated healthy sheep (n = 6). Animals were ventilated in a random sequence with: (1) ARDSNet low-stretch protocol; (2) maximal compliance PEEP strategy. Lung aeration, strain and tidal recruitment were acquired with whole-lung respiratory-gated high-resolution CT and quantified using registration-based techniques. RESULTS: Relative to the ARDSNet low-stretch protocol, the maximal compliance PEEP strategy resulted in: (1) improved dynamic whole-lung aeration at end-expiration (0.456 ± 0.064 vs. 0.377 ± 0.101, P = 0.019) and end-inspiration (0.514 ± 0.079 vs. 0.446 ± 0.083, P = 0.012) with reduced non-aerated and increased normally-aerated lung mass without associated hyperinflation; (2) decreased aeration heterogeneity at end-expiration (coefficient of variation: 0.498 ± 0.078 vs. 0.711 ± 0.207, P = 0.025) and end-inspiration (0.419 ± 0.135 vs. 0.580 ± 0.108, P = 0.014) with higher aeration in dorsal regions; (3) tidal aeration with larger inspiratory increases in normally-aerated and decreases in poorly-aerated areas, and negligible in hyperinflated lung (Aeration × Strategy: P = 0.026); (4) reduced tidal strains in lung regions with normal-aeration (Aeration × Strategy: P = 0.047) and improved regional distributions with lower tidal strains in middle and ventral lung (Region-of-interest [ROI] × Strategy: P < 0.001); and (5) less tidal recruitment in middle and dorsal lung (ROI × Strategy: P = 0.044) directly related to whole-lung tidal strain (r = 0.751, P = 0.007). CONCLUSIONS: In well-recruitable ARDS models, a maximal compliance PEEP strategy improved end-expiratory/inspiratory whole-lung aeration and its homogeneity without overinflation. It further reduced dynamic strain in middle-ventral regions and tidal recruitment in middle-dorsal areas. These findings suggest the maximal compliance strategy minimizing whole-lung dynamically quantified mechanisms of ventilator-induced lung injury with less cyclic recruitment and no additional overinflation in large heterogeneously expanded and recruitable lungs.

Impact of motion correction on [18F]-MK6240 tau PET imaging.

Objective. Positron emission tomography (PET) imaging of tau deposition using [18F]-MK6240 often involves long acquisitions in older subjects, many of whom exhibit dementia symptoms. The resulting unavoidable head motion can greatly degrade image quality. Motion increases the variability of PET quantitation for longitudinal studies across subjects, resulting in larger sample sizes in clinical trials of Alzheimer's disease (AD) treatment.Approach. After using an ultra-short frame-by-frame motion detection method based on the list-mode data, we applied an event-by-event list-mode reconstruction to generate the motion-corrected images from 139 scans acquired in 65 subjects. This approach was initially validated in two phantoms experiments against optical tracking data. We developed a motion metric based on the average voxel displacement in the brain to quantify the level of motion in each scan and consequently evaluate the effect of motion correction on images from studies with substantial motion. We estimated the rate of tau accumulation in longitudinal studies (51 subjects) by calculating the difference in the ratio of standard uptake values in key brain regions for AD. We compared the regions' standard deviations across subjects from motion and non-motion-corrected images.Main results. Individually, 14% of the scans exhibited notable motion quantified by the proposed motion metric, affecting 48% of the longitudinal datasets with three time points and 25% of all subjects. Motion correction decreased the blurring in images from scans with notable motion and improved the accuracy in quantitative measures. Motion correction reduced the standard deviation of the rate of tau accumulation by -49%, -24%, -18%, and -16% in the entorhinal, inferior temporal, precuneus, and amygdala regions, respectively.Significance. The list-mode-based motion correction method is capable of correcting both fast and slow motion during brain PET scans. It leads to improved brain PET quantitation, which is crucial for imaging AD.

TOPAS-imaging: extensions to the TOPAS simulation toolkit for medical imaging systems.

Objective. The TOol for PArticle Simulation (TOPAS) is a Geant4-based Monte Carlo software application that has been used for both research and clinical studies in medical physics. So far, most users of TOPAS have focused on radiotherapy-related studies, such as modeling radiation therapy delivery systems or patient dose calculation. Here, we present the first set of TOPAS extensions to make it easier for TOPAS users to model medical imaging systems.Approach. We used the extension system of TOPAS to implement pre-built, user-configurable geometry components such as detectors (e.g. flat-panel and multi-planar detectors) for various imaging modalities and pre-built, user-configurable scorers for medical imaging systems (e.g. digitizer chain).Main results. We developed a flexible set of extensions that can be adapted to solve research questions for a variety of imaging modalities. We then utilized these extensions to model specific examples of cone-beam CT (CBCT), positron emission tomography (PET), and prompt gamma (PG) systems. The first of these new geometry components, the FlatImager, was used to model example CBCT and PG systems. Detected signals were accumulated in each detector pixel to obtain the intensity of x-rays penetrating objects or prompt gammas from proton-nuclear interaction. The second of these new geometry components, the RingImager, was used to model an example PET system. Positron-electron annihilation signals were recorded in crystals of the RingImager and coincidences were detected. The simulated data were processed using corresponding post-processing algorithms for each modality and obtained results in good agreement with the expected true signals or experimental measurement.Significance. The newly developed extension is a first step to making it easier for TOPAS users to build and simulate medical imaging systems. Together with existing TOPAS tools, this extension can help integrate medical imaging systems with radiotherapy simulations for image-guided radiotherapy.

Deep learning-based GTV contouring modeling inter- and intra- observer variability in sarcomas.

BACKGROUND AND PURPOSE: The delineation of the gross tumor volume (GTV) is a critical step for radiation therapy treatment planning. The delineation procedure is typically performed manually which exposes two major issues: cost and reproducibility. Delineation is a time-consuming process that is subject to inter- and intra-observer variability. While methods have been proposed to predict GTV contours, typical approaches ignore variability and therefore fail to utilize the valuable confidence information offered by multiple contours. MATERIALS AND METHODS: In this work we propose an automatic GTV contouring method for soft-tissue sarcomas from X-ray computed tomography (CT) images, using deep learning by integrating inter- and intra-observer variability in the learned model. Sixty-eight patients with soft tissue and bone sarcomas were considered in this evaluation, all underwent pre-operative CT imaging used to perform GTV delineation. Four radiation oncologists and radiologists performed three contouring trials each for all patients. We quantify variability by defining confidence levels based on the frequency of inclusion of a given voxel into the GTV and use a deep convolutional neural network to learn GTV confidence maps. RESULTS: Results were compared to confidence maps from the four readers as well as ground-truth consensus contours established jointly by all readers. The resulting continuous Dice score between predicted and true confidence maps was 87% and the Hausdorff distance was 14 mm. CONCLUSION: Results demonstrate the ability of the proposed method to predict accurate contours while utilizing variability and as such it can be used to improve clinical workflow.

Lung Atelectasis Promotes Immune and Barrier Dysfunction as Revealed by Transcriptome Sequencing in Female Sheep.

BACKGROUND: Pulmonary atelectasis is frequent in clinical settings. Yet there is limited mechanistic understanding and substantial clinical and biologic controversy on its consequences. The authors hypothesize that atelectasis produces local transcriptomic changes related to immunity and alveolar-capillary barrier function conducive to lung injury and further exacerbated by systemic inflammation. METHODS: Female sheep underwent unilateral lung atelectasis using a left bronchial blocker and thoracotomy while the right lung was ventilated, with (n = 6) or without (n = 6) systemic lipopolysaccharide infusion. Computed tomography guided samples were harvested for NextGen RNA sequencing from atelectatic and aerated lung regions. The Wald test was used to detect differential gene expression as an absolute fold change greater than 1.5 and adjusted P value (Benjamini-Hochberg) less than 0.05. Functional analysis was performed by gene set enrichment analysis. RESULTS: Lipopolysaccharide-unexposed atelectatic versus aerated regions presented 2,363 differentially expressed genes. Lipopolysaccharide exposure induced 3,767 differentially expressed genes in atelectatic lungs but only 1,197 genes in aerated lungs relative to the corresponding lipopolysaccharide-unexposed tissues. Gene set enrichment for immune response in atelectasis versus aerated tissues yielded negative normalized enrichment scores without lipopolysaccharide (less than -1.23, adjusted P value less than 0.05) but positive scores with lipopolysaccharide (greater than 1.33, adjusted P value less than 0.05). Leukocyte-related processes (e.g., leukocyte migration, activation, and mediated immunity) were enhanced in lipopolysaccharide-exposed atelectasis partly through interferon-stimulated genes. Furthermore, atelectasis was associated with negatively enriched gene sets involving alveolar-capillary barrier function irrespective of lipopolysaccharide (normalized enrichment scores less than -1.35, adjusted P value less than 0.05). Yes-associated protein signaling was dysregulated with lower nuclear distribution in atelectatic versus aerated lung (lipopolysaccharide-unexposed: 10.0 ± 4.2 versus 13.4 ± 4.2 arbitrary units, lipopolysaccharide-exposed: 8.1 ± 2.0 versus 11.3 ± 2.4 arbitrary units, effect of lung aeration, P = 0.003). CONCLUSIONS: Atelectasis dysregulates the local pulmonary transcriptome with negatively enriched immune response and alveolar-capillary barrier function. Systemic lipopolysaccharide converts the transcriptomic immune response into positive enrichment but does not affect local barrier function transcriptomics. Interferon-stimulated genes and Yes-associated protein might be novel candidate targets for atelectasis-associated injury.

Performance evaluation of the 5-Ring GE Discovery MI PET/CT system using the national electrical manufacturers association NU 2-2012 Standard.

The GE Discovery MI PET/CT system has a modular digital detector design allowing three, four, or five detector block rings that extend the axial field-of-view (FOV) from 15 to 25 cm in 5 cm increments. This study investigated the performance of the 5-ring system and compared it to 3- and 4-ring systems; the GE Discovery IQ system that uses conventional photomultiplier tubes; and the GE Signa PET/MR system that has a reduced transaxial FOV. METHODS: PET performance was evaluated at three different institutions. Spatial resolution, sensitivity, counting rate performance, accuracy, and image quality were measured in accordance with National Electrical Manufacturers Association NU 2-2012 standards. The mean energy resolution, mean timing resolution, and PET/CT subsystem alignment were also measured. Phantoms were used to determine the effects of varying acquisition time and reconstruction parameters on image quality. Retrospective patient scans were reconstructed with various scan durations to evaluate the impact on image quality. RESULTS: Results from all three institutions were similar. Radial/tangential/axial full width at half maximum spatial resolution measurements using the filtered back projection algorithm were 4.3/4.3/5.0 mm, 5.5/4.6/6.5 mm, and 7.4/5.0/6.6 mm at 1, 10, and 20 cm from the center of the FOV, respectively. Measured sensitivity at the center of the FOV (20.84 cps/kBq) was significantly higher than systems with reduced axial FOV. The peak noise-equivalent counting rate was 266.3 kcps at 20.8 kBq/ml, with a corresponding scatter fraction of 40.2%. The correction accuracy for count losses up to the peak noise-equivalent counting rate was 3.6%. For the 10-, 13-, 17-, 22-, 28-, and 37-mm spheres, contrast recoveries in the image quality phantom were measured to be 46.2%, 54.3%, 66.1%, 71.1%, 85.3%, and 89.3%, respectively. The mean energy and timing resolution were 9.55% and 381.7 ps, respectively. Phantom and patient images demonstrated excellent image quality, even at short acquisition times or low injected activity. CONCLUSION: Compared to other PET/CT models, the extended axial FOV improved the overall PET performance of the 5-ring GE Discovery MI scanner. This system offers the potential to reduce scan times or injected activities through increased sensitivity.

Deterioration of Regional Lung Strain and Inflammation during Early Lung Injury.

RATIONALE: The contribution of aeration heterogeneity to lung injury during early mechanical ventilation of uninjured lungs is unknown. OBJECTIVES: To test the hypotheses that a strategy consistent with clinical practice does not protect from worsening in lung strains during the first 24 hours of ventilation of initially normal lungs exposed to mild systemic endotoxemia in supine versus prone position, and that local neutrophilic inflammation is associated with local strain and blood volume at global strains below a proposed injurious threshold. METHODS: Voxel-level aeration and tidal strain were assessed by computed tomography in sheep ventilated with low Vt and positive end-expiratory pressure while receiving intravenous endotoxin. Regional inflammation and blood volume were estimated from 2-deoxy-2-[(18)F]fluoro-d-glucose (18F-FDG) positron emission tomography. MEASUREMENTS AND MAIN RESULTS: Spatial heterogeneity of aeration and strain increased only in supine lungs (P < 0.001), with higher strains and atelectasis than prone at 24 hours. Absolute strains were lower than those considered globally injurious. Strains redistributed to higher aeration areas as lung injury progressed in supine lungs. At 24 hours, tissue-normalized 18F-FDG uptake increased more in atelectatic and moderately high-aeration regions (>70%) than in normally aerated regions (P < 0.01), with differential mechanistically relevant regional gene expression. 18F-FDG phosphorylation rate was associated with strain and blood volume. Imaging findings were confirmed in ventilated patients with sepsis. CONCLUSIONS: Mechanical ventilation consistent with clinical practice did not generate excessive regional strain in heterogeneously aerated supine lungs. However, it allowed worsening of spatial strain distribution in these lungs, associated with increased inflammation. Our results support the implementation of early aeration homogenization in normal lungs.

Feasibility study of using fall-off gradients of early and late PET scans for proton range verification.

PURPOSE: While positron emission tomography (PET) allows for the imaging of tissues activated by proton beams in terms of monitoring the therapy administered, most endogenous tissue elements are activated by relatively high-energy protons. Therefore, a relatively large distance off-set exists between the dose fall-off and activity fall-off. However, 16 O(p,2p,2n)13 N has a relatively low energy threshold which peaks around 12 MeV and also a residual proton range that is approximately 1 to 2 mm. In this phantom study, we tested the feasibility of utilizing the 13 N production peak as well as the differences in activity fall-off between early and late PET scans for proton range verification. One of the main purposes for this research was developing a proton range verification methodology that would not require Monte Carlo simulations. METHODS AND MATERIALS: Both monoenergetic and spread-out Bragg peak beams were delivered to two phantoms - a water-like gel and a tissue-like gel where the proton ranges came to be approximately 9.9 and 9.1 cm, respectively. After 1 min of postirradiation delay, the phantoms were scanned for a period of 30 min using an in-room PET. Two separate (Early and Late) PET images were reconstructed using two different postirradiation delays and acquisition times; Early PET: 1 min delay and 3 min acquisition, Late PET: 21 min delay and 10 min acquisition. The depth gradients of the PET signals were then normalized and plotted as functions of depth. The normalized gradient of the early PET images was subtracted from that of the late PET images, to observe the 13 N activity distribution in relation to depth. Monte Carlo simulations were also conducted with the same set-up as the measurements stated previously. RESULTS: The subtracted gradients show peaks at 9.4 and 8.6 cm in water-gel and tissue-gel respectively for both pristine and SOBP beams. These peaks are created in connection with the sudden change of 13 N signals with depth and consistently occur 2 mm upstream to where 13 N signals were most abundantly created (9.6 and 8.8 cm in water-gel and tissue-gel, respectively). Monte Carlo simulations provided similar results as the measurements. CONCLUSIONS: The subtracted PET signal gradient peaks and the proton ranges for water-gel and tissue-gel show distance off-sets of 4 to 5 mm. This off-set may potentially be used for proton range verification using only the PET measured data without Monte Carlo simulations. More studies are necessary to overcome various limitations, such as perfusion-driven washout, for the feasibility of this technique in living patients.

National Electrical Manufacturers Association and Clinical Evaluation of a Novel Brain PET/CT Scanner.

UNLABELLED: The aim of this study was to determine the performance of a novel mobile human brain/small-animal PET/CT system. The scanner has a 35.7-cm-diameter bore and a 22-cm axial extent. The detector ring has 7 modules each with 3 × 4 cerium-doped lutetium yttrium orthosilicate crystal blocks, each consisting of 22 × 22 outer-layer and 21 × 21 inner-layer crystals, each layer 1-cm thick. Light is collected by 12 × 12 silicon photomultipliers. The integrated CT can be used for attenuation correction and anatomic localization. The scanner was designed as a low-cost device that nevertheless produces high-quality PET images with the unique capability of battery-powered propulsion, enabling use in many settings. METHODS: Spatial resolution, sensitivity, and noise-equivalent counting rate were measured based on the National Electrical Manufacturers Association NU2-2012 procedures. Reconstruction was done with tight energy and timing cuts-400-650 keV and 7 ns-and loose cuts-350-700 keV and 10 ns. Additional image quality measurements were made from phantom, human, and animal studies. Performance was compared with a reference scanner with comparable imaging properties. RESULTS: The full width at half maximum transverse resolution at a 1-cm (10-cm) radius was 3.2 mm (5.2-mm radial, 3.1-mm tangential), and the axial resolution was 3.5 mm (4.0 mm). A sensitivity of 7.5 and 11.7 kcps/MBq at the center for tight and loose cuts, respectively, increased to 8.8 and 13.9 kcps/MBq, respectively, at a 10-cm radial offset. The maximum noise-equivalent counting rate of 19.5 and 22.7 kcps for tight and loose cuts, respectively, was achieved for an activity concentration of 2.9 kBq/mL. Contrast recovery for 4:1 hot cylinder to warm background was 76% for the 25-mm-diameter cylinder but decreased with decreasing cylinder size. The quantitation agreed within 2% of the known activity distribution and concentration. Brain phantom and human scans have shown agreement in SUVs and image quality with the reference scanner. CONCLUSION: We characterized the performance of the NeuroPET/CT and showed images from the first human studies. The study shows that this scanner achieves good performance when spatial resolution, sensitivity, counting rate, and image quality along with a low cost and unique mobile capabilities are considered.

Mapping (15)O production rate for proton therapy verification.

PURPOSE: This work was a proof-of-principle study for the evaluation of oxygen-15 ((15)O) production as an imaging target through the use of positron emission tomography (PET), to improve verification of proton treatment plans and to study the effects of perfusion. METHODS AND MATERIALS: Dynamic PET measurements of irradiation-produced isotopes were made for a phantom and rabbit thigh muscles. The rabbit muscle was irradiated and imaged under both live and dead conditions. A differential equation was fitted to phantom and in vivo data, yielding estimates of (15)O production and clearance rates, which were compared to live versus dead rates for the rabbit and to Monte Carlo predictions. RESULTS: PET clearance rates agreed with decay constants of the dominant radionuclide species in 3 different phantom materials. In 2 oxygen-rich materials, the ratio of (15)O production rates agreed with the expected ratio. In the dead rabbit thighs, the dynamic PET concentration histories were accurately described using (15)O decay constant, whereas the live thigh activity decayed faster. Most importantly, the (15)O production rates agreed within 2% (P>.5) between conditions. CONCLUSIONS: We developed a new method for quantitative measurement of (15)O production and clearance rates in the period immediately following proton therapy. Measurements in the phantom and rabbits were well described in terms of (15)O production and clearance rates, plus a correction for other isotopes. These proof-of-principle results support the feasibility of detailed verification of proton therapy treatment delivery. In addition, (15)O clearance rates may be useful in monitoring permeability changes due to therapy.

A Recommendation on How to Analyze In-Room PET for In Vivo Proton Range Verification Using a Distal PET Surface Method.

We describe the rationale and implementation of a method for analyzing in-room positron emission tomography (PET) data to verify the proton beam range. The method is based on analyzing distal PET surfaces after passive scattering proton beam delivery. Typically in vivo range verification is done by comparing measured and predicted PET distribution for a single activity level at a selected activity line along the beam passage. In the method presented here, we suggest using a middle point method based on dual PET activity levels to minimize the uncertainty due to local variations in the PET activity. Furthermore, we introduce 2-dimensional (2D) PET activity level surfaces based on 3-dimensional maps of the PET activities along the beam passage. This allows determining not only average range differences but also range difference distributions as well as root mean square deviations (RMSDs) for a more comprehensive range analysis. The method is demonstrated using data from 8 patients who were scanned with an in-room PET scanner. For each of the 8 patients, the average range difference was less than 5 mm and the RMSD was 4 to 11 mm between the measured and simulated PET activity level surfaces for single-field treatments. An ongoing protocol at our institution allows the use of a single field for patients being imaged for the PET range verification study at 1 fraction during their treatment course. Visualizing the range difference distributions using the PET surfaces offers a convenient visual verification of range uncertainties in 2D. Using the distal activity level surfaces of simulated and measured PET distributions at the middle of 25% and 50% activity level is a robust method for in vivo range verification.

Clinical application of in-room positron emission tomography for in vivo treatment monitoring in proton radiation therapy.

PURPOSE: The purpose of this study is to evaluate the potential of using in-room positron emission tomography (PET) for treatment verification in proton therapy and for deriving suitable PET scan times. METHODS AND MATERIALS: Nine patients undergoing passive scattering proton therapy underwent scanning immediately after treatment with an in-room PET scanner. The scanner was positioned next to the treatment head after treatment. The Monte Carlo (MC) method was used to reproduce PET activities for each patient. To assess the proton beam range uncertainty, we designed a novel concept in which the measured PET activity surface distal to the target at the end of range was compared with MC predictions. The repositioning of patients for the PET scan took, on average, approximately 2 minutes. The PET images were reconstructed considering varying scan times to test the scan time dependency of the method. RESULTS: The measured PET images show overall good spatial correlations with MC predictions. Some discrepancies could be attributed to uncertainties in the local elemental composition and biological washout. For 8 patients treated with a single field, the average range differences between PET measurements and computed tomography (CT) image-based MC results were <5 mm (<3 mm for 6 of 8 patients) and root-mean-square deviations were 4 to 11 mm with PET-CT image co-registration errors of approximately 2 mm. Our results also show that a short-length PET scan of 5 minutes can yield results similar to those of a 20-minute PET scan. CONCLUSIONS: Our first clinical trials in 9 patients using an in-room PET system demonstrated its potential for in vivo treatment monitoring in proton therapy. For a quantitative range prediction with arbitrary shape of target volume, we suggest using the distal PET activity surface.

Feasibility of Using Distal Endpoints for In-room PET Range Verification of Proton Therapy.

In an effort to verify the dose delivery in proton therapy, Positron Emission Tomography (PET) scans have been employed to measure the distribution of ß+ radioactivity produced from nuclear reactions of the protons with native nuclei. Because the dose and PET distributions are difficult to compare directly, the range verification is currently carried out by comparing measured and Monte Carlo (MC) simulation predicted PET distributions. In order to reduce the reliance on MC, simulated PET (simPET) and dose distal endpoints were compared to explore the feasibility of using distal endpoints for in-room PET range verification. MC simulations were generated for six head and neck patients with corrections for radiological decay, biological washout, and PET resolution. One-dimensional profiles of the dose and simPET were examined along the direction of the beam and covering the cross section of the beam. The chosen endpoints of the simPET (x-intercept of the linear fit to the distal falloff) and planned dose (20-50% of maximum dose) correspond to where most of the protons are below the threshold energy for the nuclear reactions. The difference in endpoint range between the distal surfaces of the dose and MC-PET were compared and the spread of range differences were assessed. Among the six patients, the mean difference between MC-PET and dose depth was found to be -1.6 mm to +0.5 mm between patients, with a standard deviation of 1.1 to 4.0 mm across the individual beams. In clinical practice, regions with deviations beyond the safety margin need to be examined more closely and can potentially lead to adjustments to the treatment plan.