Autopet Challenge 2023: nnUNet-based whole-body 3D PET-CT Tumour Segmentation

Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) combined with Computed Tomography (CT) scans are critical in oncology to the identification of solid tumours and the monitoring of their progression. However, precise and consistent lesion segmentation remains challenging, as manual segmentation is time-consuming and subject to intra- and inter-observer variability. Despite their promise, automated segmentation methods often struggle with false positive segmentation of regions of healthy metabolic activity, particularly when presented with such a complex range of tumours across the whole body. In this paper, we explore the application of the nnUNet to tumour segmentation of whole-body PET-CT scans and conduct different experiments on optimal training and post-processing strategies. Our best model obtains a Dice score of 69\% and a false negative and false positive volume of 6.27 and 5.78 mL respectively, on our internal test set. This model is submitted as part of the autoPET 2023 challenge. Our code is available at: https://github.com/anissa218/autopet\_nnune

A quantitative analysis of objective feather color assessment: Measurements in the laboratory do not reflect true plumage color

© 2016 American Ornithologists' Union.An important driver of the evolution of animal coloration is sexual selection operating on traits that are used to transmit information to rivals and potential mates, which has a major impact on fitness. Reflectance spectrometry has become a standard color-measuring tool, especially after the discovery of tetrachromacy in birds and their ability to detect UV light. Birds' plumage patterns may be invisible to humans, and therefore the establishment of reliable and quantitatively objective ways of assessing coloration not dependent on human vision is a technical need of primary importance. Plumage coloration measurements can be taken directly on live birds in the field, or in the laboratory (e.g., on collected feathers). However, which of these 2 approaches offers a more reliable, repeatable sampling method remains an unsolved question. Using a spectrophotometer, we measured melanin-based coloration in the plumage of Barn Swallows (Hirundo rustica). We assessed the repeatability of measures obtained with both traditional sampling methods to quantitatively determine their reliability. We used an ANOVA-based method for calculating the repeatability of measurements from 2 years separately, and a GLMM-based method to calculate overall adjusted repeatabilities for both years. The results of our study indicate a great disparity between color measurements obtained using both sampling methods and a low comparability across them. Assuming that measurements taken in the field reflect the real or "true" color of plumage, we may conclude that there is a lack of reliability of the laboratory method to reflect this true color in melanin-based plumages. Likewise, we recommend the use of the GLMM-based statistical method for repeatability calculations, as it allows the inclusion of random factors and the calculation of more realistic, adjusted repeatabilities. It also reduces the number of necessary tests, thereby increasing power, and it allows easy calculation of 95% CIs, a measure of the reliability and precision of effect-size calculations.published_or_final_versio

Phantom and clinical evaluation of the effect of full Monte Carlo collimator modelling in post-SIRT yttrium-90 Bremsstrahlung SPECT imaging

Background: Post-therapy SPECT/CT imaging of Y-90 microspheres delivered to hepatic malignancies is difficult, owing to the continuous, high-energy Bremsstrahlung spectrum emitted by Y-90. This study aimed to evaluate the utility of a commercially available software package (HybridRecon, Hermes Medical Solutions AB) which incorporates full Monte Carlo collimator modelling. Analysis of image quality was performed on both phantom and clinical images in order to ultimately provide a recommendation of an optimum reconstruction for post-therapy Y-90 microsphere SPECT/CT imaging. A 3D-printed anthropomorphic liver phantom was filled with Y-90 with a sphere-to-background ratio of 4:1 and imaged on a GE Discovery 670 SPECT/CT camera. Datasets were reconstructed using ordered-subsets expectation maximization (OSEM) 1-7 iterations in order to identify the optimal OSEM reconstruction (5 iterations, 15 subsets). Quantitative analysis was subsequently carried out on phantom datasets obtained using four reconstruction algorithms: the default OSEM protocol (2 iterations, 10 subsets) and the optimised OSEM protocol, both with and without full Monte Carlo collimator modelling. The quantitative metrics contrast recovery (CR) and background variability (BV) were calculated. The four algorithms were then used to retrospectively reconstruct 10 selective internal radiation therapy (SIRT) patient datasets which were subsequently blind scored for image quality by a consultant radiologist. Results: The optimised OSEM reconstruction (5 iterations, 15 subsets with full MC collimator modelling) increased the CR by 42% (p <0.001) compared to the default OSEM protocol (2 iterations, 10 subsets). The use of full Monte Carlo collimator modelling was shown to further improve CR by 14% (30 mm sphere, CR = 90%, p <0.05). The consultant radiologist had a significant preference for the optimised OSEM over the default OSEM protocol (p <0. 001), with the optimised OSEM being the favoured reconstruction in every one of the 10 clinical cases presented. Conclusions: OSEM (5 iterations, 15 subsets) with full Monte Carlo collimator modelling is quantitatively the optimal image reconstruction for post-SIRT 90Y Bremsstrahlung SPECT/CT imaging. The use of full Monte Carlo collimator modelling for correction of image-degrading effects significantly increases contrast recovery without degrading clinical image quality.Peer reviewe

Computation vs. Experiment for High-Frequency Low-Reynolds Number Airfoil Plunge

We seek to extend the literature on sinusoidal pure-plunge of 2D airfoils at high reduced frequency and low Reynolds number, by including effects of camber and nonzero mean incidence angle. We compare experimental results in a water tunnel using dye injection and 2D particle image velocimetry, with a set of computations in 2D – Immersed Boundary Method and unsteady Reynolds-Averaged Navier Stokes. The Re range is from 10,000 to 60,000, based on free stream velocity and airfoil chord, chosen to cover cases where transition in attached boundary layers would be of some importance, and where transition would only occur in the wake. Generally at high reduced frequency there is no Reynolds number effect. Mean angle of attack has significance, notionally, depending on whether it is below or above static stall. Computations were found to agree well with experimentally-derived velocity contours, vorticity contours and momentum in the wake. As found previously for the NACA0012, varying Strouhal number is found to control the topology of the wake, while varying reduced amplitude and reduced frequency together, but keeping Strouhal number constant, causes wake vortical structures to scale with the reduced amplitude of plunge. Flowfield periodicity – as evinced from comparison of instantaneous and time-averaged particle image velocimetry – is generally attained after two periods of oscillation from motion onset

Novel penalised likelihood reconstruction of PET in the assessment of histologically verified small pulmonary nodules

OBJECTIVES: Investigate the effect of a novel Bayesian penalised likelihood (BPL) reconstruction algorithm on analysis of pulmonary nodules examined with 18F-FDG PET/CT, and to determine its effect on small, sub-10-mm nodules. METHODS: 18F-FDG PET/CTs performed for nodule evaluation in 104 patients (121 nodules) were retrospectively reconstructed using the new algorithm, and compared to time-of-flight ordered subset expectation maximisation (OSEM) reconstruction. Nodule and background parameters were analysed semi-quantitatively and visually. RESULTS: BPL compared to OSEM resulted in statistically significant increases in nodule SUV(max) (mean 5.3 to 8.1, p < 0.00001), signal-to-background (mean 3.6 to 5.3, p < 0.00001) and signal-to-noise (mean 24 to 41, p < 0.00001). Mean percentage increase in SUV(max) (%ΔSUV(max)) was significantly higher in nodules ≤10 mm (n = 31, mean 73 %) compared to >10 mm (n = 90, mean 42 %) (p = 0.025). Increase in signal-to-noise was higher in nodules ≤10 mm (224 %, mean 12 to 27) compared to >10 mm (165 %, mean 28 to 46). When applying optimum SUV(max) thresholds for detecting malignancy, the sensitivity and accuracy increased using BPL, with the greatest improvements in nodules ≤10 mm. CONCLUSION: BPL results in a significant increase in signal-to-background and signal-to-noise compared to OSEM. When semi-quantitative analyses to diagnose malignancy are applied, higher SUV(max) thresholds may be warranted owing to the SUV(max) increase compared to OSEM. KEY POINTS: • Novel Bayesian penalised likelihood PET reconstruction was applied for lung nodule evaluation. • This was compared to current standard of care OSEM reconstruction. • The novel reconstruction generated significant increases in lung nodule signal-to-background and signal-to-noise. • These increases were highest in small, sub-10-mm pulmonary nodules. • Higher SUV(max)thresholds may be warranted when using semi-quantitative analyses to diagnose malignancy

Evaluation of principal component analysis-based data-driven respiratory gating for positron emission tomography

Objective: Respiratory motion can degrade PET image quality and lead to inaccurate quantification of lesion uptake. Such motion can be mitigated via respiratory gating. Our objective was to evaluate a data-driven gating (DDG) technique that is being developed commercially for clinical PET/CT. Methods: A data-driven respiratory gating algorithm based on principal component analysis (PCA) was applied to phantom and FDG patient data. An anthropomorphic phantom and a NEMA IEC Body phantom were filled with 18F, placed on a respiratory motion platform, and imaged using a PET/CT scanner. Motion waveforms were measured using an infrared camera [the Real-time Position Management™ system (RPM)] and also extracted from the PET data using the DDG algorithm. The waveforms were compared via calculation of Pearson’s correlation coefficients. PET data were reconstructed using quiescent period gating (QPG) and compared via measurement of recovery percentage and background variability. Results: Data-driven gating had similar performance to the external gating system, with correlation coefficients in excess of 0.97. Phantom and patient images were visually clearer with improved contrast when QPG was applied as compared to no motion compensation. Recovery coefficients in the phantoms were not significantly different between DDG- and RPM-based QPG, but were significantly higher than those found for no motion compensation (p < 0.05). Conclusion: A PCA-based DDG algorithm was evaluated and found to provide a reliable respiratory gating signal in anthropomorphic phantom studies and in example patients. Advances in knowledge: The prototype commercial DDG algorithm may enable reliable respiratory gating in routine clinical PET-CT

Impacts of forestry planting on primary production in upland lakes from north-west Ireland

Planted forests are increasing in many upland regions world-wide, but knowledge about their potential effects on algal communities of catchment lakes is relatively unknown. Here the effects of afforestation were investigated using palaeolimnology at six upland lake sites in the north-west of Ireland subject to different extents of forest plantation cover (4-64% of catchment area). 210Pb dated sediment cores were analysed for carotenoid pigments from algae, stable isotopes of bulk carbon (δ13C) and nitrogen (δ15N), and C/N ratios. In lakes with >50% of their catchment area covered by plantations, there were two- to six-fold increases in pigments from cryptophytes (alloxanthin) and significant but lower increases (39-116%) in those from colonial cyanobacteria (canthaxanthin), but no response from biomarkers of total algal abundance (β-carotene). In contrast, lakes in catchments with <20% afforestation exhibited no consistent response to forestry practices, although all lakes exhibited fluctuations in pigments and geochemical variables due to peat cutting and upland grazing prior to forest plantation. Taken together, patterns suggest that increases in cyanobacteria and cryptophyte abundance reflect a combination of mineral and nutrient enrichment associated with forest fertilisation and organic matter influx which may have facilitated growth of mixotrophic taxa. This study demonstrates that planted forests can alter the abundance and community structure of algae in upland humic lakes of Ireland and Northern Ireland, despite long histories of prior catchment disturbance

18F-FDG PET/CT assessment of histopathologically confirmed mediastinal lymph nodes in non-small cell lung cancer using a penalised likelihood reconstruction

Purpose To investigate whether using a Bayesian penalised likelihood reconstruction (BPL) improves signal-to-background (SBR), signal-to-noise (SNR) and SUVmax when evaluating mediastinal nodal disease in non-small cell lung cancer (NSCLC) compared to ordered subset expectation maximum (OSEM) reconstruction. Materials and methods 18F-FDG PET/CT scans for NSCLC staging in 47 patients (112 nodal stations with histopathological confirmation) were reconstructed using BPL and compared to OSEM. Node and multiple background SUV parameters were analysed semi-quantitatively and visually. Results Comparing BPL to OSEM, there were significant increases in SUVmax (mean 3.2–4.0, p<0.0001), SBR (mean 2.2–2.6, p<0.0001) and SNR (mean 27.7–40.9, p<0.0001). Mean background SNR on OSEM was 10.4 (range 7.6–14.0), increasing to 12.4 (range 8.2–16.7, p<0.0001). Changes in background SUVs were minimal (largest mean difference 0.17 for liver SUVmean, p<0.001). There was no significant difference between either algorithm on receiver operating characteristic analysis (p=0.26), although on visual analysis, there was an increase in sensitivity and small decrease in specificity and accuracy on BPL. Conclusion BPL increases SBR, SNR and SUVmax of mediastinal nodes in NSCLC compared to OSEM, but did not improve the accuracy for determining nodal involvement

Triple modality image reconstruction of PET data using SPECT, PET, CT information increases lesion uptake in images of patients treated with radioembolization with [Formula: see text] micro-spheres.

PURPOSE: Nuclear medicine imaging modalities like computed tomography (CT), single photon emission CT (SPECT) and positron emission tomography (PET) are employed in the field of theranostics to estimate and plan the dose delivered to tumors and the surrounding tissues and to monitor the effect of the therapy. However, therapeutic radionuclides often provide poor images, which translate to inaccurate treatment planning and inadequate monitoring images. Multimodality information can be exploited in the reconstruction to enhance image quality. Triple modality PET/SPECT/CT scanners are particularly useful in this context due to the easier registration process between images. In this study, we propose to include PET, SPECT and CT information in the reconstruction of PET data. The method is applied to Yttrium-90 ([Formula: see text]Y) data. METHODS: Data from a NEMA phantom filled with [Formula: see text]Y were used for validation. PET, SPECT and CT data from 10 patients treated with Selective Internal Radiation Therapy (SIRT) were used. Different combinations of prior images using the Hybrid kernelized expectation maximization were investigated in terms of VOI activity and noise suppression. RESULTS: Our results show that triple modality PET reconstruction provides significantly higher uptake when compared to the method used as standard in the hospital and OSEM. In particular, using CT-guided SPECT images, as guiding information in the PET reconstruction significantly increases uptake quantification on tumoral lesions. CONCLUSION: This work proposes the first triple modality reconstruction method and demonstrates up to 69% lesion uptake increase over standard methods with SIRT [Formula: see text]Y patient data. Promising results are expected for other radionuclide combination used in theranostic applications using PET and SPECT

Impacts of forestry planting on primary production in upland lakes from north-west Ireland

Planted forests are increasing in many upland regions worldwide, but knowledge about their potential effects on algal communities of catchment lakes is relatively unknown. Here, the effects of afforestation were investigated using palaeolimnology at six upland lake sites in the north-west of Ireland subject to different extents of forest plantation cover (4–64% of catchment area). 210Pb-dated sediment cores were analysed for carotenoid pigments from algae, stable isotopes of bulk carbon (δ13C) and nitrogen (δ15N), and C/N ratios. In lakes with >50% of their catchment area covered by plantations, there were two- to sixfold increases in pigments from cryptophytes (alloxanthin) and significant but lower increases (39–116%) in those from colonial cyanobacteria (canthaxanthin), but no response from biomarkers of total algal abundance (β-carotene). In contrast, lakes in catchments with <20% afforestation exhibited no consistent response to forestry practices, although all lakes exhibited fluctuations in pigments and geochemical variables due to peat cutting and upland grazing prior to forest plantation. Taken together, patterns suggest that increases in cyanobacteria and cryptophyte abundance reflect a combination of mineral and nutrient enrichment associated with forest fertilization and organic matter influx which may have facilitated growth of mixotrophic taxa. This study demonstrates that planted forests can alter the abundance and community structure of algae in upland humic lakes of Ireland and Northern Ireland, despite long histories of prior catchment disturbance