Lightning

PurposeThe purpose of this study is to investigate inter-planner plan quality variability using a manual forward planning (MFP)- or fast inverse planning (FIP, Lightning)-approach for single brain lesions treated with the Gamma Knife® (GK) Icon™.MethodsThirty patients who were previously treated with GK stereotactic radiosurgery or radiotherapy were selected and divided into three groups (post-operative resection cavity, intact brain metastasis, and vestibular schwannoma [10 patients per group]). Clinical plans for the 30 patients were generated by multiple planners using FIP only (1), a combination of FIP and MFP (12), and MFP only (17). Three planners (Senior, Junior, and Novice) with varying experience levels re-planned the 30 patients using MFP and FIP (two plans per patient) with planning time limit of 60 min. Statistical analysis was performed to compare plan quality metrics (Paddick conformity index, gradient index, number of shots, prescription isodose line, target coverage, beam-on-time (BOT), and organs-at-risk doses) of MFP or FIP plans among three planners and to compare plan quality metrics between each planner's MFP/FIP plans and clinical plans. Variability in FIP parameter settings (BOT, low dose, and target max dose) and in planning time among the planners was also evaluated.ResultsVariations in plan quality metrics of FIP plans among three planners were smaller than those of MFP plans for all three groups. Junior's MFP plans were the most comparable to the clinical plans, whereas Senior's and Novice's MFP plans were superior and inferior, respectively. All three planners' FIP plans were comparable or superior to the clinical plans. Differences in FIP parameter settings among the planners were observed. Planning time was shorter and variations in planning time among the planners were smaller for FIP plans in all three groups.ConclusionsThe FIP approach is less planner dependent and more time-honored than the MFP approach.

PurposeTo demonstrate the clinical feasibility of a novel treatment planning algorithm via lightning dose optimizer (LDO) on Leksell Gamma Knife (LGK) GammaPlan with significantly faster planning times for stereotactic radiosurgery (SRS) of the complex and difficult arteriovenous malformations (AVMs) and pituitary adenomas.Methods and materialsAfter completing the in-house end-to-end phantom testing and independent dose verification of the recently upgraded LDO algorithm on GammaPlan using the MD Anderson's IROC anthropomorphic SRS head phantom irradiation credentialing, 20 previously treated GK-SRS patients (10 AVM, average volume 3.61 cm3 and 10 pituitary adenomas, average volume 0.86 cm3 ) who underwent manual forward planning on GammaPlan were retrospectively replanned via LDO. These pathologies were included because of the need for adequate dose delivery with organs at risk in very close proximity. LDO finds the target curvature boundary by well-formulated linear programing objectives and inversely optimizes the GK-SRS plan by isocenter placement, optimization, and sequencing. For identical target coverage, the LDO and original manual plans were compared for target conformity, gradient index, dose to critical organs, and surrounding normal brain. Additionally, various treatment delivery parameters, including beam-on time were recorded.ResultsFor both patient cohorts, LDO provided similar target coverage with better dose conformity, tighter radiosurgical dose distribution with a lower value of gradient indices (all p 10Gy , V12Gy , and V14Gy by 4.74, 3.67, and 2.67 cm3 (all p 10Gy , V12Gy , and V14Gy by 1.08, 0.86, and 0.68 cm3 (all p ConclusionGK-SRS treatment on Leksell Perfexion GammaPlan using the LDO provided highly conformal target coverage with a steep dose gradient, spared critical organs, and significantly reduced normal brain dose for complex targets at the cost of slightly higher treatment times. LDO generated high-quality treatment plans and could significantly reduce planning time. If available, the LDO algorithm is suggested for validation and clinical use for complex and difficult GK cases.

Lightning is an important yet often overlooked disturbance agent in forest ecosystems. Recent research conducted in Panama suggests that lightning is a major cause of large tree mortality in tropical forests. However, lightning-induced tree mortality is not included in state-of-the-art ecosystem models. Here, we implement a general lightning mortality module in the dynamic global vegetation model LPJ-GUESS to explore the impacts of lightning on forests at local and global scales. Lightning mortality was implemented stochastically in dependency of local cloud-to-ground lightning density and simulated forest structure based on findings from the Panamanian forest. For this site, LPJ-GUESS adequately simulates the average number of trees of different size classes killed per lightning strike, with a total of 2.9 simulated versus 3.2 observed. The model also captures the estimated contribution of lightning to the overall mortality of large trees (21% simulated vs. 24% observed). Applying the new model version to other tropical and temperate forests for which observation-based estimates on lightning mortality exist, LPJ-GUESS reproduces estimated impacts in some forests but simulates substantially lower impacts for others. Global simulations driven by two alternative products of cloud-to-ground lightning densities suggest that lightning kills 301-340 million trees annually, thereby causing 0.21-0.30 GtC yr.-1 of dead biomass (2.1%-2.9% of total killed biomass). The simulations also reveal that the global biomass would be 1.3%-1.7% higher in a world without lightning. Spatially, simulated lightning mortality is largest in the tropical forests of Africa. Although our simulations suggest an important role of lightning in forest ecosystems on a global scale, more data on lightning-induced tree mortality across different forest types would be desirable for more accurate model calibration and evaluation. Given the anticipated increase in future lightning activity, incorporating lightning mortality into ecosystem models is needed to obtain more reliable projections of terrestrial vegetation dynamics and carbon cycling.

Lightning is a dominant free tropospheric source of nitrogen oxides (NOx), impacting climate by affecting global tropospheric ozone (O3) and other key oxidants. We calculate temporally and spatially resolved lightning NOx (LNOx) production rates using lightning flash energies from space-based Lightning Imaging Sensors (LIS). Our production rates average ∼309 moles per flash (mol fl-1) over oceans, peaking at midday, and ∼172 mol fl-1 over land, peaking in the early morning. Replacing static values in the original GEOS-Chem model inventory with our spatially and hourly varying production rates yields global annual LNOx emissions of 4.4 Tg nitrogen (N) for 2015-2019; almost 2 Tg N less than the original inventory. Annual terrestrial LNOx emissions still exceed those over the ocean, due to more frequent lightning over land, but the relative proportion of maritime emissions increases. The largest decline in LNOx emissions is north of 35°N in summer, as static 500 mol fl-1 is replaced with 150-250 mol fl-1. Global decline in LNOx emissions decreases abundances of free tropospheric NOx, O3, the hydroxyl radical (OH) and peroxyacetyl nitrate (PAN). Hourly variability in LIS flash radiances is broadly consistent with high-frequency Geostationary Lightning Mapper (GLM) flash energies, though the comparison is limited to tropical America. Introducing hourly variability in LNOx production rates leads to a greater than 10% localised decline in equatorial lower tropospheric O3. Independent validation is critically needed, given our updated LNOx emissions offer a viable solution to model overestimates in O3 and OH and underestimates in the lifetime of the greenhouse gas methane.