Hotspot Volume Research Articles

Aiming for Maximized and Reproducible Enhancements in the Obstacle Race of SERS.

Surface enhanced Raman scattering (SERS), since its discovery in the mid-1970s, has taken on many roles in the world of analytical measurement science. From identifying known and unknown chemicals in mixtures such as pharmaceutical and environmental samples to enabling qualitative and quantitative analysis of biomolecules and biomedical disease markers (or biomarkers), furthermore expanding to tracking nanostructures in vivo for medical diagnosis and therapy. This is because SERS combines the inherent power of Raman scattering capable of molecular species identification, topped with tremendous amplification in the Raman signal intensity when the molecule of interest is positioned near plasmonic nanostructures. The higher the SERS signal amplification, the lower the limit of detection (LOD) that could be achieved for the above applications. Therefore, improving SERS sensing efficiencies is vital. The signal reproducibility and SERS enhancement factor (EF) heavily rely on plasmonic nanostructure design, which has led to tremendous work in the field. But SERS signal and EF reproducibility remain key limitations for its wider market usability. This Review will scrutinize factors, some recognized and some often overlooked, that dictate the SERS signal and are of utmost importance to enable reproducible SERS EFs. Most of the factors pertain to colloidal labeled SERS. Some critically reviewed factors include the nanostructure's surface area as a limiting factor, SERS hot-spots including optimizing the SERS EF within the hot-spot volume and positioning labels, properties of label molecules governing molecule orientation in hot-spots, and resonance effects. A better understanding of these factors will enable improved optimization and control of the experimental SERS, enabling extremely sensitive LODs without overestimating the SERS EFs. These are crucial steps toward identification and reproducible quantification in SERS sensing.

Spatiotemporal clustering analysis of shared electric vehicles based on trajectory data for sustainable urban governance

Shared electric vehicles (SEVs) have emerged as a promising mode of transportation with the growth of EVs and the sharing economy. However, current challenges, such as suboptimal station planning and inflexible operation schedules, are limiting the user experience and the growth of the industry. Therefore, our study adopts the affinity propagation (AP) clustering algorithm to divide the stations into two categories: the residential station and the business office station. We then apply the Spatial-Temporal Density-Based Spatial Clustering of Applications with Noise (ST-DBSCAN) algorithm to analyze the spatiotemporal distribution characteristics of SEVs from three aspects: hotspot area, travel volume and travel speed, based on trajectory data from the two types of stations. Results suggest that the distribution hotspot and travel volume of SEV at residential and business office stations is similar during the morning peak, concentrated in office, residential and transportation hub areas, whereas it is obviously different during the evening peak. Unlike the commuting demand of users in residential stations, users in business office stations prefer to use SEVs to travel to leisure and entertainment areas. Furthermore, we found that the driving speed of SEVs is primarily determined by actual road conditions and not significantly affected by station type. These findings provide valuable insights for SEV operators to optimize station layouts and spatial planning of vehicles during peak periods.

Theoretical study of void collapse and hot spot formation mechanism for energetic material

ABSTRACT Based on molecular dynamics simulation, we find that hot spot in explosive is induced by inelastic impaction between void faces and develop a physical model to describe the temperature rising mechanism. A set of thermodynamic parameters for void collapse and hot spot is calculated. The hot spot relaxation time is proportional to square of hot spot size, and the plastic work is proportional to hot spot volume. A complete physical picture for hot spot formation is obtained.

Technical note: Evaluation of a spatial optimization model for prostate high dose-rate brachytherapy in a clinical treatment planning system.

Spatial properties of a dose distribution, such as volumes of contiguous hot spots, are of clinical importance in treatment planning for high dose-rate brachytherapy (HDRBT). We have in an earlier study developed an optimization model that reduces the prevalence of contiguous hot spots by modifying a tentative treatment plan. The aim of this study is to incorporate the correction of hot spots in a standard inverse planning workflow and to validate the integrated model in a clinical treatment planning system. The spatial function is included in the objective function for the inverse planning, as opposed to in the previous study where it was applied as a separate post-processing step. Our aim is to demonstrate that fine-adjustments of dose distributions, which are often performed manually in today's clinical practice, can be automated. A spatial optimization function was introduced in the treatment planning system RayStation (RaySearch LaboratoriesAB, Stockholm, Sweden) via a research interface. A series of 10 consecutive prostate patients treated with HDRBT was retrospectively replanned with and without the spatial function. Optimization with the spatial function decreased the volume of the largest contiguous hot spot by on average 31%, compared to if the function was not included. The volume receiving at least 200% of the prescription dose decreased by on average 11%. Target coverage, measured as the fractions of the clinical target volume (CTV) and the planning target volume (PTV) receiving at least the prescription dose, was virtually unchanged (less than a percent change for both metrics). Organs-at-risk received comparable or slightly decreased doses if the spatial function was included in the optimization model. Optimization of spatial properties such as the volume of contiguous hot spots can be integrated in a standard inverse planning workflow for brachytherapy, and need not be conducted as a separate post-processing step.

Flexible, stretchable, and single-molecule-sensitive SERS-active sensor for wearable biosensing applications.

The development of wearable sensors for remote patient monitoring and personalized medicine has led to a revolution in biomedical technology. Plasmonic metasurfaces that enhance Raman scattering signals have recently gained attention as wearable sensors. However, finding a flexible, sensitive, and easy-to-fabricate metasurface has been a challenge for decades. In this paper, a novel wearable device, the flexible, stretchable, and single-molecule-sensetive SERS-active sensor, is proposed. This device offers an unprecedented SERS enhancement factor in the order of 1011, along with other long-desired characteristics for SERS applications such as a high scattering to absorption ratio (∼2.5) and a large hotspot volume (40 nm × 40 nm × 5 nm). To achieve flexibility, we use polydimethylsiloxane (PDMS) as the substrate, which is stable, transparent, and biologically compatible. Our numerical calculations show that the proposed sensor offers reliable SERS performance even under bending (up to 100° angles) or stretching (up to 50% stretch). The easy-to-fabricate and flexible nature of our sensor offers a promising avenue for developing highly sensitive wearable sensors for a range of applications, particularly in the field of personalized medicine and remote patient monitoring.

JS07.4.A Correspondence of glutamine and glycine imaging based on 7T MRSI to amino acid PET

Abstract Background New approaches for 7 Tesla magnetic resonance spectroscopic imaging (MRSI) allow the simultaneous imaging of multiple neuro-oncological biomarkers with 3-4 mm resolution in clinically feasible measurement times. Specifically, the amino acids glutamine (Gln) and Glycine (Gly), were previously limited to single voxel detection at lower fields. Both could add to our capabilities to resolve heterogeneous tumour metabolism. Purpose To progress the validation of Gln and Gly as neuro-oncological markers by conducting the first comparison to amino acid PET in a cohort of glioma patients. Material and Methods In 24 glioma patients (WHO 2021 classification), we quantitatively compared 7T MRSI (3D, 3.4 mm isotropic resolution, 15 min scan time) and routine PET (FET or MET). Within manual tumour segmentations, we defined hotspot volumes of interest (VOI) for the ratios of total choline (tCho, clinical standard reference), Gln, Gly to total N-acetylaspartate (tNAA) and PET tumour-to-brain ratios (TBR), all with a cut-off threshold of 1.6. For these VOIs, we calculated VOI volumes and median ratios as well as Dice similarity coefficients (DSC) and centre of intensity distance (CoI), between MRSI and PET ratios. Results We found that Gln and Gly ratios to tNAA had a higher correspondence to PET-based amino acid metabolism than tCho. Our resulting median VOI volumes were 19.08±23.10 cm³ for tCho/tNAA, 33.68±24.60 cm³ for Gln/tNAA, and 22.38±18.49 cm³ for Gly/tNAA compared to 24.33±30.46 cm³ for PET, with correlation coefficients >0.5 for all MRSI hotspot values in relation to PET volumes. Median ratios were 0.52±0.13 for tCho/tNAA, 0.61±0.25 for Gln/tNAA, 0.33±0.15 for Gly/tNAA and 2.11±0.42 for PET. The median DSCs to PET amounted to 0.53±0.36 for tCho/tNAA, 0.66±0.40 for Gln/tNAA, and 0.57±0.36 for Gly/tNAA, while the median CoI distances were 0.56±0.43 cm for tCho/tNAA, 0.39±0.22 cm for Gln/tNAA, and 0.45±0.48 cm for Gly/tNAA. Conclusion With this first study that compared high-resolution 3D-MRSI at 7 Tesla to amino acid PET and a quantitative evaluation, we demonstrated that Gln and Gly corresponded better to PET than tCho, which is the main marker used in clinical MR, both within the study and compared to previous literature. Future research is needed to clearly define the benefits of 7T MRSI for neuro-oncology such as the identification of tumour microenvironments or non-invasive determination of molecular-pathologic markers. Gln could be further explored by the application of Gln-based PET tracers to MR-PET. We still see further developments of MRSI methods, such as motion correction or absolute quantification of concentrations instead of ratios, as necessary to obtain such goals.

Automation of radiation treatment planning for rectal cancer.

PurposeTo develop an automated workflow for rectal cancer three‐dimensional conformal radiotherapy (3DCRT) treatment planning that combines deep learning (DL) aperture predictions and forward‐planning algorithms.MethodsWe designed an algorithm to automate the clinical workflow for 3DCRT planning with field aperture creations and field‐in‐field (FIF) planning. DL models (DeepLabV3+ architecture) were trained, validated, and tested on 555 patients to automatically generate aperture shapes for primary (posterior–anterior [PA] and opposed laterals) and boost fields. Network inputs were digitally reconstructed radiographs, gross tumor volume (GTV), and nodal GTV. A physician scored each aperture for 20 patients on a 5‐point scale (>3 is acceptable). A planning algorithm was then developed to create a homogeneous dose using a combination of wedges and subfields. The algorithm iteratively identifies a hotspot volume, creates a subfield, calculates dose, and optimizes beam weight all without user intervention. The algorithm was tested on 20 patients using clinical apertures with varying wedge angles and definitions of hotspots, and the resulting plans were scored by a physician. The end‐to‐end workflow was tested and scored by a physician on another 39 patients.ResultsThe predicted apertures had Dice scores of 0.95, 0.94, and 0.90 for PA, laterals, and boost fields, respectively. Overall, 100%, 95%, and 87.5% of the PA, laterals, and boost apertures were scored as clinically acceptable, respectively. At least one auto‐plan was clinically acceptable for all patients. Wedged and non‐wedged plans were clinically acceptable for 85% and 50% of patients, respectively. The hotspot dose percentage was reduced from 121% (σ = 14%) to 109% (σ = 5%) of prescription dose for all plans. The integrated end‐to‐end workflow of automatically generated apertures and optimized FIF planning gave clinically acceptable plans for 38/39 (97%) of patients.ConclusionWe have successfully automated the clinical workflow for generating radiotherapy plans for rectal cancer for our institution.

Assessing the practicality of using a single knowledge-based planning model for multiple linac vendors.

PurposeKnowledge‐based planning (KBP) has been shown to be an effective tool in quality control for intensity‐modulated radiation therapy treatment planning and generating high‐quality plans. Previous studies have evaluated its ability to create consistent plans across institutions and between planners within the same institution as well as its use as teaching tool for inexperienced planners. This study evaluates whether planning quality is consistent when using a KBP model to plan across different treatment machines.Materials and methodsThis study used a RapidPlan model (Varian Medical Systems) provided by the vendor, to which we added additional planning objectives, maximum dose limits, and planning structures, such that a clinically acceptable plan is achieved in a single optimization. This model was used to generate and optimize volumetric‐modulated arc therapy plans for a cohort of 50 patients treated for head‐neck cancer. Plans were generated using the following treatment machines: Varian 2100, Elekta Versa HD, and Varian Halcyon. A noninferiority testing methodology was used to evaluate the hypothesis that normal and target metrics in our autoplans were no worse than a set of clinically‐acceptable baseline plans by a margin of 1.8 Gy or 3% dose‐volume. The quality of these plans were also compared through the use of common clinical dose‐volume histogram criteria.ResultsThe Versa HD met our noninferiority criteria for 23 of 34 normal and target metrics; while the Halcyon and Varian 2100 machines met our criteria for 24 of 34 and 26 of 34 metrics, respectively. The experimental plans tended to have less volume coverage for prescription dose planning target volume and larger hotspot volumes. However, comparable plans were generated across different treatment machines.ConclusionsThese results support the use of a head‐neck RapidPlan models in centralized planning workflows that support clinics with different linac models/vendors, although some fine‐tuning for targets may be necessary.

Rapid SAR optimization for hyperthermic oncology: combining multi-goal optimization and time-multiplexed steering for hotspot suppression

Purpose Healthy tissue hotspots are a main limiting factor in administering deep hyperthermia cancer therapy. We propose an optimization scheme that uses time-multiplexed steering (TMPS) among minimally correlated (nearly) Pareto-optimal solutions to suppress hotspots without reducing tumor heating. Furthermore, tumor heating homogeneity is maximized, thus reducing toxicity and avoiding underexposed tumor regions, which in turn may reduce recurrence. Materials and methods The novel optimization scheme combines random generation of steering parameters with local optimization to efficiently identify the set of (Pareto-) optimal solutions of conflicting optimization goals. To achieve simultaneous suppression of hotspots, multiple steering parameter configurations with minimally correlated hotspots are selected near the Pareto front and combined in TMPS. The performance of the novel scheme was compared with that of a multi-goal Genetic Algorithm for a range of simulated treatment configurations involving a modular applicator heating a generic tumor situated in the bladder, cervix, or pelvic bone. SAR cumulative histograms in tumor and healthy tissue, as well as hotspot volumes are used as metrics. Results Compared to the non-TMPS optimization, the proposed scheme was able to reduce the peak temperature in healthy tissue by 0.2 °C–1.0 °C (a thermal dose reduction by at least 26%) and, importantly, the hotspot volume above 42 °C in healthy tissue by 41%–86%. At the same time, tumor heating homogeneity was maintained or improved. Conclusions The extremely rapid optimization (5 s for TMPS part, on a standard PC) permits closed-loop treatment reoptimization during treatment administration, and empowers physicians with a selection of optimal treatment scenarios reflecting different weighting of conflicting treatment goals.

7T HR FID-MRSI Compared to Amino Acid PET: Glutamine and Glycine as Promising Biomarkers in Brain Tumors.

Simple SummaryMagnetic resonance spectroscopic imaging is an imaging method that can map the distribution of multiple biochemicals in the human brain in one scan. Using stronger magnetic fields, such as 7 Tesla, allows for higher resolution images and more biochemical maps. To test these results, we compared it to positron emission tomography, the established clinical standard for metabolic imaging. This comparison mainly looked at the overlap between regions with increased signal between both methods. We found that the molecules glutamine and glycine, only mappable at 7 Tesla, corresponded better to positron emission tomography than the commonly used choline.(1) Background: Recent developments in 7T magnetic resonance spectroscopic imaging (MRSI) made the acquisition of high-resolution metabolic images in clinically feasible measurement times possible. The amino acids glutamine (Gln) and glycine (Gly) were identified as potential neuro-oncological markers of importance. For the first time, we compared 7T MRSI to amino acid PET in a cohort of glioma patients. (2) Methods: In 24 patients, we co-registered 7T MRSI and routine PET and compared hotspot volumes of interest (VOI). We evaluated dice similarity coefficients (DSC), volume, center of intensity distance (CoI), median and threshold values for VOIs of PET and ratios of total choline (tCho), Gln, Gly, myo-inositol (Ins) to total N-acetylaspartate (tNAA) or total creatine (tCr). (3) Results: We found that Gln and Gly ratios generally resulted in a higher correspondence to PET than tCho. Using cutoffs of 1.6-times median values of a control region, DSCs to PET were 0.53 ± 0.36 for tCho/tNAA, 0.66 ± 0.40 for Gln/tNAA, 0.57 ± 0.36 for Gly/tNAA, and 0.38 ± 0.31 for Ins/tNAA. (4) Conclusions: Our 7T MRSI data corresponded better to PET than previous studies at lower fields. Our results for Gln and Gly highlight the importance of future research (e.g., using Gln PET tracers) into the role of both amino acids.

Simulating rhizodeposition patterns around growing and exuding root systems

Abstract In this study, we developed a novel model approach to compute the spatio-temporal distribution patterns of rhizodeposits around growing root systems in three dimensions. This model approach allows us to study the evolution of rhizodeposition patterns around complex three-dimensional root systems. Root systems were generated using the root architecture model CPlantBox. The concentration of rhizodeposits at a given location in the soil domain was computed analytically. To simulate the spread of rhizodeposits in the soil, we considered rhizodeposit release from the roots, rhizodeposit diffusion into the soil, rhizodeposit sorption to soil particles and rhizodeposit degradation by microorganisms. To demonstrate the capabilities of our new model approach, we performed simulations for the two example rhizodeposits mucilage and citrate and the example root system Vicia faba. The rhizodeposition model was parameterized using values from the literature. Our simulations showed that the rhizosphere soil volume with rhizodeposit concentrations above a defined threshold value (i.e. the rhizodeposit hotspot volume) exhibited a maximum at intermediate root growth rates. Root branching allowed the rhizospheres of individual roots to overlap, resulting in a greater volume of rhizodeposit hotspots. This was particularly important in the case of citrate, where overlap of rhizodeposition zones accounted for more than half of the total rhizodeposit hotspot volumes. Coupling a root architecture model with a rhizodeposition model allowed us to get a better understanding of the influence of root architecture as well as rhizodeposit properties on the evolution of the spatio-temporal distribution patterns of rhizodeposits around growing root systems.

Fully automated analysis combining [18F]-FET-PET and multiparametric MRI including DSC perfusion and APTw imaging: a promising tool for objective evaluation of glioma progression

PurposeTo evaluate diagnostic accuracy of fully automated analysis of multimodal imaging data using [18F]-FET-PET and MRI (including amide proton transfer-weighted (APTw) imaging and dynamic-susceptibility-contrast (DSC) perfusion) in differentiation of tumor progression from treatment-related changes in patients with glioma.Material and methodsAt suspected tumor progression, MRI and [18F]-FET-PET data as part of a retrospective analysis of an observational cohort of 66 patients/74 scans (51 glioblastoma and 23 lower-grade-glioma, 8 patients included at two different time points) were automatically segmented into necrosis, FLAIR-hyperintense, and contrast-enhancing areas using an ensemble of deep learning algorithms. In parallel, previous MR exam was processed in a similar way to subtract preexisting tumor areas and focus on progressive tumor only. Within these progressive areas, intensity statistics were automatically extracted from [18F]-FET-PET, APTw, and DSC-derived cerebral-blood-volume (CBV) maps and used to train a Random Forest classifier with threefold cross-validation. To evaluate contribution of the imaging modalities to the classifier’s performance, impurity-based importance measures were collected. Classifier performance was compared with radiology reports and interdisciplinary tumor board assessments.ResultsIn 57/74 cases (77%), tumor progression was confirmed histopathologically (39 cases) or via follow-up imaging (18 cases), while remaining 17 cases were diagnosed as treatment-related changes. The classification accuracy of the Random Forest classifier was 0.86, 95% CI 0.77–0.93 (sensitivity 0.91, 95% CI 0.81–0.97; specificity 0.71, 95% CI 0.44–0.9), significantly above the no-information rate of 0.77 (p = 0.03), and higher compared to an accuracy of 0.82 for MRI (95% CI 0.72–0.9), 0.81 for [18F]-FET-PET (95% CI 0.7–0.89), and 0.81 for expert consensus (95% CI 0.7–0.89), although these differences were not statistically significant (p > 0.1 for all comparisons, McNemar test). [18F]-FET-PET hot-spot volume was single-most important variable, with relevant contribution from all imaging modalities.ConclusionAutomated, joint image analysis of [18F]-FET-PET and advanced MR imaging techniques APTw and DSC perfusion is a promising tool for objective response assessment in gliomas.

Microglial activation and blood-brain barrier permeability in cerebral small vessel disease.

Cerebral small vessel disease (SVD) is a major cause of stroke and dementia. The underlying pathogenesis is poorly understood, but both neuroinflammation and increased blood-brain barrier permeability have been hypothesized to play a role, and preclinical studies suggest the two processes may be linked. We used PET magnetic resonance to simultaneously measure microglial activation using the translocator protein radioligand 11C-PK11195, and blood-brain barrier permeability using dynamic contrast enhanced MRI. A case control design was used with two disease groups with sporadic SVD (n = 20), monogenic SVD (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, CADASIL), and normal controls (n = 20) were studied. Hotspots of increased glial activation and blood-brain barrier permeability were identified as values greater than the 95th percentile of the distribution in controls. In sporadic SVD there was an increase in the volume of hotspots of both 11C-PK11195 binding (P = 0.003) and blood-brain barrier permeability (P = 0.007) in the normal appearing white matter, in addition to increased mean blood-brain barrier permeability (P < 0.001). In CADASIL no increase in blood-brain barrier permeability was detected; there was a non-significant trend to increased 11C-PK11195 binding (P = 0.073). Hotspots of 11C-PK11195 binding and blood-brain barrier permeability were not spatially related. A panel of 93 blood biomarkers relating to cardiovascular disease, inflammation and endothelial activation were measured in each participant; principal component analysis was performed and the first component related to blood-brain barrier permeability and microglial activation. Within the sporadic SVD group both hotspot and mean volume blood-brain barrier permeability values in the normal appearing white matter were associated with dimension 1 (β = 0.829, P = 0.017, and β = 0.976, P = 0.003, respectively). There was no association with 11C-PK11195 binding. No associations with blood markers were found in the CADASIL group. In conclusion, in sporadic SVD both microglial activation and increased blood-brain barrier permeability occur, but these are spatially distinct processes. No evidence of increased blood-brain barrier permeability was found in CADASIL.

Dose constraints for whole breast radiation therapy based on the quality assessment of treatment plans in the randomised Danish breast cancer group (DBCG) HYPO trial

PurposeQuality assessment of the treatment plans in the Danish Breast Cancer Group (DBCG) HYPO trial was carried out based on prospectively reported dosimetric parameters and evidence-based dose constraints for whole breast radiation therapy were derived. Materials and methodsFrom 2009 to 2014, 1882 patients (pts) were randomised between 50 Gy/25fractions (fr) versus 40 Gy/15fr. Doses to CTVp_breast (V95%, V107%-V110%, Dmax, and in addition for 40 Gy plans V105%-V107%), ipsilateral lung (V20Gy/V17Gy), heart (V20Gy/V17Gy, V40Gy/V35Gy), and left anterior descending coronary artery (LADCA) (Dmax) and use of respiratory gated technique were prospectively reported to the DBCG database. After end of accrual, these dosimetric parameters from all plans in the trial were compared to the pre-specified treatment constraints. ResultsIn total, 1854 pts from eight radiation therapy (RT) centres in three countries were treated. No statistically significant differences were found between the results for 40 Gy and 50 Gy plans, except for CTVp_breast hot-spot volume (V107%-V110%). Of the 40 Gy pts, 90% with CTVp_breast > 600 mL and 95% with CTVp_breast ≤ 600 mL had a CTVp_breast hot-spot volume (V105%-V107%) <2%. In 95% of the 50 Gy plans, the CTVp_breast absolute hot-spot volume (V107%-V110%) was <0.5 mL and 1.7 mL for CTVp_breast ≤ 600 mL and > 600 mL, respectively. Compliance was >99% for both heart and lung constraints. Largest deviation from protocol constraints was found for the volume of CTVp_breast covered with 95% of the prescription dose or more (V95%). The CTV dose coverage (V95%) was >94.3% in 95% of the right-sided pts, whereas the figures for 95% of the left-sided pts treated with and without respiratory gating were 93.2% and 88.8%, respectively. ConclusionA high degree of compliance with protocol dose constraints was found for treatment plans in the DBCG HYPO trial. New constraints for dose to organs at risk and high-dose volumes in the breast are suggested for breast-only RT planning.

Plan quality effects of maximum monitor unit constraints in pencil beam scanning proton therapy for central nervous system and skull base tumors

Purpose/objective(s)With reports of CNS toxicity in patients treated with proton therapy at doses lower than would be expected based on photon data, it has been proposed that heavy monitor unit (MU) weighting of pencil beam scanning (PBS) proton therapy spots may potentially increase the risk of toxicity. We evaluated the impact of maximum MU weighting per spot (maxMU/spot) restrictions on PBS plan quality, prior to implementing clinic-wide maxMU/spot restrictions. Materials/methodsPBS plans of 11 patients, of which 3 plans included boosts, for a total of 14 PBS sample cases were included. Per sample case, a single dosimetrist created 4 test plans, gradually reducing the maxMU/spot in the plan. Test Plan 1, unrestricted in maxMU/spot, was the reference for all restricted plan comparisons (comparison sets 2 vs. 1; 3 vs. 1; and 4 vs. 1). The impact of MU/spot restrictions on plan quality metrics were analyzed with Wilcoxon signed rank test analyses. Treatment delivery time was modeled for a representative case. ResultsA total of 14 PBS sample cases, 7 (50%) single-field optimized, 7 (50%) multi-field optimized, 9 (64%) delivering > 3500 cGy, 9 (64%) with 3 beams, and 7 (50%) without a range shifter were included. There were no differences in plan quality metrics of target coverage (V95% and V100% prescription), conformality and gradient indices, hot spot volume (V105% prescription), and dose to normal brain (V10%/30%/50%/70%/90%/100% prescription) with reductions of allowable maxMU/spot across all comparison sets (p > 0.05). Max MU/spot restrictions did not increase treatment delivery time when analyzed for a representative case. ConclusionMaxMU/spot restrictions within the thresholds evaluated in this study did not degrade overall plan quality metrics. Future studies should evaluate spot weighting with linear energy transfer/relative biologic effectiveness-informed planning to determine if spot weighting manipulation impacts clinical outcomes and mitigates toxicity.

Cleaning the dose falloff in lung SBRT plan.

PurposeTo investigate a planning technique that can possibly reduce low‐to‐intermediate dose spillage (measured by R50%, D2cm values) in lung SBRT plans.Materials and MethodsDose falloff outside the target was studied retrospectively in 102 SBRT VMAT plans of lung tumor. Plans having R50% and/or D2cm higher than recommended tolerances in RTOG protocols 0813 and 0915 were replanned with new optimization constraints using novel shell structures and novel constraints. Violations in the RTOG R50% value can be rectified with a dose constraint to a novel shell structure (“OptiForR50”). The construction of structure OptiForR50% and the novel optimization criteria translate the RTOG goals for R50% into direct inputs for the optimizer. Violations in the D2cm can be rectified using constraints on a 0.5 cm thick shell structure with inner surface 2cm from the PTV surface. Wilcoxon signed‐rank test was used to compare differences in dose conformity, volume of hot spots, R50%, D2cm of the target in addition to the OAR doses. A two‐sided P‐value of 0.05 was used to assess statistical significance.ResultsAmong 102 lung SBRT plans with PTV sizes ranging from 5 to 179 cc, 32 plans with violations in R50% or D2cm were reoptimized. The mean reduction in R50% (4.68 vs 3.89) and D2cm (56.49 vs 52.51) was statistically significant both having P < 0.01. Target conformity index, volume of 105% isodose contour outside PTV, normal lung V20, and mean dose to heart and aorta were significantly lowered with P < 0.05.ConclusionThe novel planning methodology using multiple shells including the novel OptiForR50 shell with precisely calculated dimensions and optimizer constraints lead to significantly lower values of R50% and D2cm and lower dose spillage in lung SBRT plans. All plans were successfully brought into the zone of no RTOG violations.

Evaluating Maximum MU per Spot Thresholds on CNS Pencil Beam Proton Therapy Plan Quality

There are concerning reports of CNS toxicity in patients treated with proton therapy at doses lower than would be expected based on photon data estimates. Given the desire to mitigate risk of serious unexpected events, we propose limiting the maximum monitor unit weighting per spot (maxMU/spot) to the entire plan with the hypothesis that heavily weighted spots may pose an unforeseen risk of toxicity despite meeting objective dose constraints. This dosimetric study assesses the impact of maxMU/spot restrictions on pencil beam proton therapy (PBPT) plan quality. We hypothesize that plan quality may be preserved while still restricting the maxMU/spot, but there may be a threshold below which restrictions negatively impact plan quality. PBPT plans of 11 patients (9 consecutive, 2 additional with notably challenging plan objectives) were included, of which 3 plans included boosts, for a total of 14 nominal PBPT cases. Per nominal plan, a single dosimetrist created 4 test plans as outlined in Table 1, iteratively reducing the maxMU/spot in the plan. Test Plan 1, unrestricted in maxMU/spot, was the reference for all analyses (comparison sets 2 vs. 1; 3 vs. 1; and 4 vs. 1). The differences in each plan quality metric in each comparison set were analyzed using the Wilcoxon signed rank test, with p<0.05 significance testing. Beam-specific metrics in each comparison set were analyzed, defined by the root mean square deviation in beam metrics from the unrestricted plan. Linear regression with log transformation was performed to analyze the impact of restriction conditions on changes in the beam-specific max dose, heterogeneity, and % of target receiving the Rx/#beams. A total of 14 PBPT plans, 7 (50%) SFO, 7 (50%) MFO, 9 (64%) delivering >3500 cGy, 9 (64%) with 3 beams, 5 (36%) with 4-5 beams, and 7 (50%) without a range shifter were included. With increasing MU restriction, there were no differences in plan quality metrics of target coverage (V95% and V100%Rx), conformality and gradient indices, hot spot volume (V105%Rx), and dose to unaffected brain (V10%/30%/50%/70%/90%/100%Rx) across all comparison sets (p>0.05). However, there was a mean increase of 854 (2 vs. 1, p = 0.02), 869 (3 vs. 1, p = 0.025), and 892 (4 vs. 1, p = 0.007) total spots in the more restricted MU plans. MaxMU restriction did not significantly impact the beam-specific max dose (p = 0.259), heterogeneity (p = 0.305), and % of target receiving the Rx/#beams (p = 0.409). MaxMU/spot restriction did not negatively impact overall plan quality and beam-specific metrics within the thresholds evaluated in this study. Future studies should evaluate spot weighting with LET/RBE to determine if spot weighting manipulation may truly impact clinical outcomes and mitigate toxicity.Tabled 1Abstract 2601; Table; Iterative reduction maximum allowable MU per spot*PlanNo Range shifter (RS)2cm RS3cm RS5cm RS1No limitNo limitNo limitNo limit230405070320304060410203050∗1 MU = 1 cGY/mm2 at a 2 cm for monoenergetic proton beam Open table in a new tab

The potential of Gantry beamline large momentum acceptance for real time tumour tracking in pencil beam scanning proton therapy

Tumour tracking is an advanced radiotherapy technique for precise treatment of tumours subject to organ motion. In this work, we addressed crucial aspects of dose delivery for its realisation in pencil beam scanning proton therapy, exploring the momentum acceptance and global achromaticity of a Gantry beamline to perform continuous energy regulation with a standard upstream degrader. This novel approach is validated on simulation data from three geometric phantoms of increasing complexity and one liver cancer patient using 4D dose calculations. Results from a standard high-to-low beamline ramping scheme were compared to alternative energy meandering schemes including combinations with rescanning. Target coverage and dose conformity were generally well recovered with tumour tracking even though for particularly small targets, large variations are reported for the different approaches. Meandering in energy while rescanning has a positive impact on target homogeneity and similarly, hot spots outside the targets are mitigated with a relatively fast convergence rate for most tracking scenarios, halving the volume of hot spots after as little as 3 rescans. This work investigates the yet unexplored potential of having a large momentum acceptance in medical beam line, and provides an alternative to take tumour tracking with particle therapy closer to clinical translation.

Automated Hypofractionated IMRT treatment planning for early-stage breast Cancer

BackgroundHypofractionated whole-breast irradiation is a standard adjuvant therapy for early-stage breast cancer. This study evaluates the plan quality and efficacy of an in-house-developed automated radiotherapy treatment planning algorithm for hypofractionated whole-breast radiotherapy.MethodsA cohort of 99 node-negative left-sided breast cancer patients completed hypofractionated whole-breast irradiation with six-field IMRT for 42.56 Gy in 16 daily fractions from year 2016 to 2018 at a tertiary center were re-planned with an in-house-developed algorithm. The automated plan-generating C#-based program is developed in a Varian ESAPI research mode. The dose-volume histogram (DVH) and other dosimetric parameters of the automated and manual plans were directly compared.ResultsThe average time for generating an autoplan was 5 to 6 min, while the manual planning time ranged from 1 to 1.5 h. There was only a small difference in both the gantry angles and the collimator angles between the autoplans and the manual plans (ranging from 2.2 to 5.3 degrees). Autoplans and manual plans performed similarly well in hotspot volume and PTV coverage, with the autoplans performing slightly better in the ipsilateral-lung-sparing dose parameters but were inferior in contralateral-breast-sparing. The autoplan dosimetric quality did not vary with different breast sizes, but for manual plans, there was worse ipsilateral-lung-sparing (V4Gy) in larger or medium-sized breasts than in smaller breasts. Autoplans were generally superior than manual plans in CI (1.24 ± 0.06 vs. 1.30 ± 0.09, p < 0.01) and MU (1010 ± 46 vs. 1205 ± 187, p < 0.01).ConclusionsOur study presents a well-designed standardized fully automated planning algorithm for optimized whole-breast radiotherapy treatment plan generation. A large cohort of 99 patients were re-planned and retrospectively analyzed. The automated plans demonstrated similar or even better dosimetric quality and efficacy in comparison with the manual plans. Our result suggested that the autoplanning algorithm has great clinical applicability potential.

Imaging glioma biology: spatial comparison of amino acid PET, amide proton transfer, and perfusion-weighted MRI in newly diagnosed gliomas

PurposeImaging glioma biology holds great promise to unravel the complex nature of these tumors. Besides well-established imaging techniques such O-(2-[18F]fluoroethyl)-l-tyrosine (FET)-PET and dynamic susceptibility contrast (DSC) perfusion imaging, amide proton transfer–weighted (APTw) imaging has emerged as a promising novel MR technique. In this study, we aimed to better understand the relation between these imaging biomarkers and how well they capture cellularity and vascularity in newly diagnosed gliomas.MethodsPreoperative MRI and FET-PET data of 46 patients (31 glioblastoma and 15 lower-grade glioma) were segmented into contrast-enhancing and FLAIR-hyperintense areas. Using established cutoffs, we calculated hot-spot volumes (HSV) and their spatial overlap. We further investigated APTw and CBV values in FET-HSV. In a subset of 10 glioblastoma patients, we compared cellularity and vascularization in 34 stereotactically targeted biopsies with imaging.ResultsIn glioblastomas, the largest HSV was found for APTw, followed by PET and CBV (p < 0.05). In lower-grade gliomas, APTw–HSV was clearly lower than in glioblastomas. The spatial overlap of HSV was highest between APTw and FET in both tumor entities and regions. APTw correlated significantly with cellularity, similar to FET, while the association with vascularity was more pronounced in CBV and FET.ConclusionsWe found a relevant spatial overlap in glioblastomas between hotspots of APTw and FET both in contrast-enhancing and FLAIR-hyperintense tumor. As suggested by earlier studies, APTw was lower in lower-grade gliomas compared with glioblastomas. APTw meaningfully contributes to biological imaging of gliomas.