Reply: Familial ovarian screening: how to address abnormal TVU findings and its influence on the efficacy of screening?

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Biological modelling of the radiation dose escalation effect of regional hyperthermia in cervical cancer

Background Locoregional hyperthermia combined with radiotherapy significantly improves locoregional control and overall survival for cervical tumors compared to radiotherapy alone. In this study biological modelling is applied to quantify the effect of radiosensitization for three cervical cancer patients to evaluate the improvement in equivalent dose for the combination treatment with radiotherapy and hyperthermia. Methods The Linear-Quadratic (LQ) model extended with temperature-dependent LQ-parameters α and β was used to model radiosensitization by hyperthermia and to calculate the conventional radiation dose that is equivalent in biological effect to the combined radiotherapy and hyperthermia treatment. External beam radiotherapy planning was performed based on a prescription dose of 46Gy in 23 fractions of 2Gy. Hyperthermia treatment using the AMC-4 system was simulated based on the actual optimized system settings used during treatment. Results The simulated hyperthermia treatments for the 3 patients yielded a T50 of 40.1 °C, 40.5 °C, 41.1 °C and a T90 of 39.2 °C, 39.7 °C, 40.4 °C, respectively. The combined radiotherapy and hyperthermia treatment resulted in a D95 of 52.5Gy, 55.5Gy, 56.9Gy in the GTV, a dose escalation of 7.3–11.9Gy compared to radiotherapy alone (D95 = 45.0–45.5Gy). Conclusions This study applied biological modelling to evaluate radiosensitization by hyperthermia as a radiation-dose escalation for cervical cancer patients. This model is very useful to compare the effectiveness of different treatment schedules for combined radiotherapy and hyperthermia treatments and to guide the design of clinical studies on dose escalation using hyperthermia in a multi-modality setting

Relationship of promising methods in the detection of anthracycline-induced cardiotoxicity in breast cancer patients

Purpose\ud It remains challenging to identify patients at risk of anthracycline-induced cardiotoxicity. To better understand the different risk-stratifying approaches, we evaluated 123I-metaiodobenzylguanidine (123I-mIBG) scintigraphy and its interrelationship with conventional echocardiography, 2D strain imaging and several biomarkers.\ud \ud Methods\ud We performed 123I-mIBG scintigraphy, conventional and strain echocardiography and biomarker (NT-proBNP, TNF-α, galectin-3, IL-6, troponin I, ST-2 and sFlt-1) assessment in 59 breast cancer survivors 1 year after anthracycline treatment. Interobserver and intermethod variability was calculated on planar and SPECT 123I-mIBG scintigraphy, using the heart/mediastinum (H/M) ratio and washout (WO). Pearson’s r and multivariate analyses were performed to identify correlations and independent predictors of 123I-mIBG scintigraphy results.\ud \ud Results\ud Delayed planar anterior whole-heart ROI (WH) H/M ratios and WO were the most robust 123I-mIBG parameters. Significant correlations were observed between 123I-mIBG parameters and several conventional echo parameters, global longitudinal and radial strain (GLS and GRS) and galectin-3. The highest Pearson’s r was observed between delayed H/M ratio and GRS (Pearson’s r 0.36, p = 0.01). Multivariate analysis showed that GRS was the only independent predictor of the delayed WH H/M ratio (p = 0.023).\ud \ud Conclusion\ud The delayed planar H/M ratio is the most robust 123I-mIBG parameter. It correlates with several conventional echocardiographic parameters, GLS, GRS and galectin-3. Of these, only GRS predicts the H/M ratio

Association between clinical findings and the presence of lumbar spine osteoarthritis imaging features:A systematic review

OBJECTIVE: Spinal osteoarthritis is difficult to study and diagnose, partly due to the lack of agreed diagnostic criteria. This systematic review aims to give an overview of the associations between clinical and imaging findings suggestive of spinal osteoarthritis in patients with low back pain to make a step towards agreed diagnostic criteria.DESIGN: We searched MEDLINE, Embase, Web of Science, and CINAHL from inception to April 29, 2021 to identify observational studies in adults that assessed the association between selected clinical and imaging findings suggestive of spinal osteoarthritis. Risk of bias was assessed using the Newcastle Ottawa Scale and the quality of evidence was graded using an adaptation of the GRADE approach.RESULTS: After screening 7902 studies, 30 met the inclusion criteria. High-quality evidence was found for the longitudinal association between low back pain (LBP) intensity, and both disc space narrowing and osteophytes, as well as for the association between LBP-related physical functioning and lumbar disc degeneration, the presence of spinal morning stiffness and disc space narrowing and for the lack of association between physical functioning and Schmorl's nodes.CONCLUSIONS: There is high- and moderate-quality evidence of associations between clinical and imaging findings suggestive of spinal osteoarthritis. However, the majority of the studied outcomes had low or very low-quality of evidence. Furthermore, clinical and methodological heterogeneity was a serious limitation, adding to the need and importance of agreed criteria for spinal osteoarthritis, which should be the scope of future research.</p

On Form Factors in nested Bethe Ansatz systems

We investigate form factors of local operators in the multi-component Quantum Non-linear Schr\"odinger model, a prototype theory solvable by the so-called nested Bethe Ansatz. We determine the analytic properties of the infinite volume form factors using the coordinate Bethe Ansatz solution and we establish a connection with the finite volume matrix elements. In the two-component models we derive a set of recursion relations for the "magnonic form factors", which are the matrix elements on the nested Bethe Ansatz states. In certain simple cases (involving states with only one spin-impurity) we obtain explicit solutions for the recursion relations.Comment: 34 pages, v2 (minor modifications

Psychometric properties of the Italian versions of the Gambling Urge Scale (GUS) and the Gambling Refusal Self-Efficacy Questionnaire (GRSEQ)

Gambling urges and gambling refusal self-efficacy beliefs play a major role in the development and maintenance of problem gambling. This study aimed to translate the Gambling Urge Scale (GUS) and the Gambling Refusal Self-Efficacy Questionnaire (GRSEQ) from English to Italian (GUS-I, GRSEQ-I) and to test their factor structure, internal consistency, construct validity, concurrent validity, and gender differences in 513 individuals from the Italian community. Factor structure and construct validity were tested through Confirmatory Factor Analysis, internal consistency through Cronbach’s alpha, concurrent validity through correlations with gambling-related cognitions (GRCS-I), probable pathological gambling (SOGS-I), and gambling functioning (GFA-R-I). Results confirmed that the 6 items of the GUS-I load highly on one dimension of Gambling Urge, and each of the 26 items of the GRSEQ-I load highly on their relevant sub-dimension, among the following: situations/thoughts, drugs, positive emotions, negative emotions. Both scales are internally consistent and show concurrent validity with gambling-related cognitions, probable pathological gambling, and gambling functioning. Males score higher than females at the GUS-I; females score higher than males at the GRSEQ-I. The findings from the present study suggest that the GUS-I and the GRSEQ-I are internally consistent and valid scales for the assessment of gambling urges and gambling refusal self-efficacy in Italian individuals from the community, with significant repercussions in terms of assessment, prevention, and intervention

An intergalactic medium temperature from a giant radio galaxy

© 2022 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).The warm-hot intergalactic medium (warm-hot IGM, or WHIM) pervades the filaments of the Cosmic Web and harbours half of the Universe's baryons. The WHIM's thermodynamic properties are notoriously hard to measure. Here we estimate a galaxy group - WHIM boundary temperature using a new method. In particular, we use a radio image of the giant radio galaxy (giant RG, or GRG) created by NGC 6185, a massive nearby spiral. We analyse this extraordinary object with a Bayesian 3D lobe model and deduce an equipartition pressure $P_\mathrm{eq} = 6 \cdot 10^{-16}\ \mathrm{Pa}$ -- among the lowest found in RGs yet. Using an X-ray-based statistical conversion for Fanaroff-Riley II RGs, we find a true lobe pressure $P = 1.5\substack{+1.7\\-0.4}\cdot 10^{-15}\ \mathrm{Pa}$. Cosmic Web reconstructions, group catalogues, and MHD simulations furthermore imply an $\mathrm{Mpc}$-scale IGM density $1 + \delta_\mathrm{IGM} = 40\substack{+30\\-10}$. The buoyantly rising lobes are crushed by the IGM at their inner side, where an approximate balance between IGM and lobe pressure occurs: $P_\mathrm{IGM} \approx P$. The ideal gas law then suggests an IGM temperature $T_\mathrm{IGM} = 11\substack{+12\\-5} \cdot 10^6\ \mathrm{K}$, or $k_\mathrm{B}T_\mathrm{IGM} = 0.9\substack{+1.0\\-0.4}\ \mathrm{keV}$, at the virial radius -- consistent with X-ray-derived temperatures of similarly massive groups. Interestingly, the method is not performing at its limit: in principle, estimates $T_\mathrm{IGM} \sim 4 \cdot 10^6\ \mathrm{K}$ are already possible -- rivalling the lowest X-ray measurements available. The technique's future scope extends from galaxy group outskirts to the WHIM. In conclusion, we demonstrate that observations of GRGs in Cosmic Web filaments are finally sensitive enough to probe the thermodynamics of galaxy groups and beyond.Peer reviewe

Standardised lesion segmentation for imaging biomarker quantitation: a consensus recommendation from ESR and EORTC.

BACKGROUND: Lesion/tissue segmentation on digital medical images enables biomarker extraction, image-guided therapy delivery, treatment response measurement, and training/validation for developing artificial intelligence algorithms and workflows. To ensure data reproducibility, criteria for standardised segmentation are critical but currently unavailable. METHODS: A modified Delphi process initiated by the European Imaging Biomarker Alliance (EIBALL) of the European Society of Radiology (ESR) and the European Organisation for Research and Treatment of Cancer (EORTC) Imaging Group was undertaken. Three multidisciplinary task forces addressed modality and image acquisition, segmentation methodology itself, and standards and logistics. Devised survey questions were fed via a facilitator to expert participants. The 58 respondents to Round 1 were invited to participate in Rounds 2-4. Subsequent rounds were informed by responses of previous rounds. RESULTS/CONCLUSIONS: Items with ≥ 75% consensus are considered a recommendation. These include system performance certification, thresholds for image signal-to-noise, contrast-to-noise and tumour-to-background ratios, spatial resolution, and artefact levels. Direct, iterative, and machine or deep learning reconstruction methods, use of a mixture of CE marked and verified research tools were agreed and use of specified reference standards and validation processes considered essential. Operator training and refreshment were considered mandatory for clinical trials and clinical research. Items with a 60-74% agreement require reporting (site-specific accreditation for clinical research, minimal pixel number within lesion segmented, use of post-reconstruction algorithms, operator training refreshment for clinical practice). Items with ≤ 60% agreement are outside current recommendations for segmentation (frequency of system performance tests, use of only CE-marked tools, board certification of operators, frequency of operator refresher training). Recommendations by anatomical area are also specified

Finding AGN remnant candidates based on radio morphology with machine learning

Remnant radio galaxies represent the dying phase of radio-loud active galactic nuclei (AGN). Large samples of remnant radio galaxies are important for quantifying the radio galaxy life cycle. The remnants of radio-loud AGN can be identified in radio sky surveys based on their spectral index, or, complementary, through visual inspection based on their radio morphology. However, this is extremely time-consuming when applied to the new large and sensitive radio surveys. Here we aim to reduce the amount of visual inspection required to find AGN remnants based on their morphology, through supervised machine learning trained on an existing sample of remnant candidates. For a dataset of 4107 radio sources, with angular sizes larger than 60 arcsec, from the LOw Frequency ARray (LOFAR) Two-Metre Sky Survey second data release (LoTSS-DR2), we started with 151 radio sources that were visually classified as 'AGN remnant candidate'. We derived a wide range of morphological features for all radio sources from their corresponding Stokes-I images: from simple source catalogue-derived properties, to clustered Haralick-features, and self-organising map (SOM) derived morphological features. We trained a random forest classifier to separate the 'AGN remnant candidates' from the not yet inspected sources. The SOM-derived features and the total to peak flux ratio of a source are shown to be most salient to the classifier. We estimate that $31\pm5\%$ of sources with positive predictions from our classifier will be labelled 'AGN remnant candidates' upon visual inspection, while we estimate the upper bound of the $95\%$ confidence interval for 'AGN remnant candidates' in the negative predictions at $8\%$. Visual inspection of just the positive predictions reduces the number of radio sources requiring visual inspection by $73\%$.Comment: 23 pages; accepted for publication in A&