The Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema was released in 2022 and approved by ISO as a standard for sharing clinical and genomic information about an individual, including phenotypic descriptions, numerical measurements, genetic information, diagnoses, and treatments. A phenopacket can be used as an input file for software that supports phenotype-driven genomic diagnostics and for algorithms that facilitate patient classification and stratification for identifying new diseases and treatments. There has been a great need for a collection of phenopackets to test software pipelines and algorithms. Here, we present Phenopacket Store. Phenopacket Store v.0.1.19 includes 6,668 phenopackets representing 475 Mendelian and chromosomal diseases associated with 423 genes and 3,834 unique pathogenic alleles curated from 959 different publications. This represents the first large-scale collection of case-level, standardized phenotypic information derived from case reports in the literature with detailed descriptions of the clinical data and will be useful for many purposes, including the development and testing of software for prioritizing genes and diseases in diagnostic genomics, machine learning analysis of clinical phenotype data, patient stratification, and genotype-phenotype correlations. This corpus also provides best-practice examples for curating literature-derived data using the GA4GH Phenopacket Schema.
- MeSH
- algoritmy MeSH
- databáze genetické MeSH
- fenotyp * MeSH
- genomika * metody MeSH
- lidé MeSH
- software * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
OBJECTIVES: Decision-analytic models assessing the value of emerging Alzheimer's disease (AD) treatments are challenged by limited evidence on short-term trial outcomes and uncertainty in extrapolating long-term patient-relevant outcomes. To improve understanding and foster transparency and credibility in modeling methods, we cross-compared AD decision models in a hypothetical context of disease-modifying treatment for mild cognitive impairment (MCI) due to AD. METHODS: A benchmark scenario (US setting) was used with target population MCI due to AD and a set of synthetically generated hypothetical trial efficacy estimates. Treatment costs were excluded. Model predictions (10-year horizon) were assessed and discussed during a 2-day workshop. RESULTS: Nine modeling groups provided model predictions. Implementation of treatment effectiveness varied across models based on trial efficacy outcome selection (clinical dementia rating - sum of boxes, clinical dementia rating - global, mini-mental state examination, functional activities questionnaire) and analysis method (observed severity transitions, change from baseline, progression hazard ratio, or calibration to these). Predicted mean time in MCI ranged from 2.6 to 5.2 years for control strategy and from 0.1 to 1.0 years for difference between intervention and control strategies. Predicted quality-adjusted life-year gains ranged from 0.0 to 0.6 and incremental costs (excluding treatment costs) from -US$66 897 to US$11 896. CONCLUSIONS: Trial data can be implemented in different ways across health-economic models leading to large variation in model predictions. We recommend (1) addressing the choice of outcome measure and treatment effectiveness assumptions in sensitivity analysis, (2) a standardized reporting table for model predictions, and (3) exploring the use of registries for future AD treatments measuring long-term disease progression to reduce uncertainty of extrapolating short-term trial results by health-economic models.
- MeSH
- Alzheimerova nemoc * ekonomika farmakoterapie MeSH
- analýza nákladů a výnosů * MeSH
- ekonomické modely MeSH
- kognitivní dysfunkce * ekonomika MeSH
- kvalitativně upravené roky života MeSH
- lidé MeSH
- metody pro podporu rozhodování MeSH
- progrese nemoci MeSH
- výsledek terapie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- srovnávací studie MeSH
PURPOSE: Dual velocity encoding PC-MRI can produce spurious artifacts when using high ratios of velocity encoding values (VENCs), limiting its ability to generate high-quality images across a wide range of encoding velocities. This study aims to propose and compare dual-VENC correction methods for such artifacts. THEORY AND METHODS: Two denoising approaches based on spatiotemporal regularization are proposed and compared with a state-of-the-art method based on sign correction. Accuracy is assessed using simulated data from an aorta and brain aneurysm, as well as 8 two-dimensional (2D) PC-MRI ascending aorta datasets. Two temporal resolutions (30,60) ms and noise levels (9,12) dB are considered, with noise added to the complex magnetization. The error is evaluated with respect to the noise-free measurement in the synthetic case and to the unwrapped image without additional noise in the volunteer datasets. RESULTS: In all studied cases, the proposed methods are more accurate than the Sign Correction technique. Using simulated 2D+T data from the aorta (60 ms, 9 dB), the Dual-VENC (DV) error 0.82±0.07$$ 0.82\pm 0.07 $$ is reduced to: 0.66±0.04$$ 0.66\pm 0.04 $$ (Sign Correction); 0.34±0.04$$ 0.34\pm 0.04 $$ and 0.32±0.04$$ 0.32\pm 0.04 $$ (proposed techniques). The methods are found to be significantly different (p-value <0.05$$ <0.05 $$ ). Importantly, brain aneurysm data revealed that the Sign Correction method is not suitable, as it increases error when the flow is not unidirectional. All three methods improve the accuracy of in vivo data. CONCLUSION: The newly proposed methods outperform the Sign Correction method in improving dual-VENC PC-MRI images. Among them, the approach based on temporal differences has shown the highest accuracy.
- MeSH
- algoritmy * MeSH
- aorta * diagnostické zobrazování MeSH
- artefakty * MeSH
- fantomy radiodiagnostické MeSH
- interpretace obrazu počítačem metody MeSH
- intrakraniální aneurysma diagnostické zobrazování MeSH
- lidé MeSH
- magnetická rezonanční tomografie * metody MeSH
- mozek diagnostické zobrazování MeSH
- počítačová simulace MeSH
- počítačové zpracování obrazu * metody MeSH
- poměr signál - šum * MeSH
- reprodukovatelnost výsledků MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
PURPOSE: STereotactic Arrhythmia Radioablation (STAR) showed promising results in patients with refractory ventricular tachycardia. However, clinical data are scarce and heterogeneous. The STOPSTORM.eu consortium was established to investigate and harmonize STAR in Europe. The primary goal of this benchmark study was to investigate current treatment planning practice within the STOPSTORM project as a baseline for future harmonization. METHODS AND MATERIALS: Planning target volumes (PTVs) overlapping extracardiac organs-at-risk and/or cardiac substructures were generated for 3 STAR cases. Participating centers were asked to create single-fraction treatment plans with 25 Gy dose prescriptions based on in-house clinical practice. All treatment plans were reviewed by an expert panel and quantitative crowd knowledge-based analysis was performed with independent software using descriptive statistics for International Commission on Radiation Units and Measurements report 91 relevant parameters and crowd dose-volume histograms. Thereafter, treatment planning consensus statements were established using a dual-stage voting process. RESULTS: Twenty centers submitted 67 treatment plans for this study. In most plans (75%) intensity modulated arc therapy with 6 MV flattening filter free beams was used. Dose prescription was mainly based on PTV D95% (49%) or D96%-100% (19%). Many participants preferred to spare close extracardiac organs-at-risk (75%) and cardiac substructures (50%) by PTV coverage reduction. PTV D0.035cm3 ranged from 25.5 to 34.6 Gy, demonstrating a large variety of dose inhomogeneity. Estimated treatment times without motion compensation or setup ranged from 2 to 80 minutes. For the consensus statements, a strong agreement was reached for beam technique planning, dose calculation, prescription methods, and trade-offs between target and extracardiac critical structures. No agreement was reached on cardiac substructure dose limitations and on desired dose inhomogeneity in the target. CONCLUSIONS: This STOPSTORM multicenter treatment planning benchmark study not only showed strong agreement on several aspects of STAR treatment planning, but also revealed disagreement on others. To standardize and harmonize STAR in the future, consensus statements were established; however, clinical data are urgently needed for actionable guidelines for treatment planning.
- MeSH
- benchmarking * MeSH
- celková dávka radioterapie MeSH
- komorová tachykardie chirurgie radioterapie MeSH
- konsensus * MeSH
- kritické orgány * účinky záření MeSH
- lidé MeSH
- plánování radioterapie pomocí počítače * normy metody MeSH
- radiochirurgie * normy metody MeSH
- radioterapie s modulovanou intenzitou metody normy MeSH
- srdce účinky záření MeSH
- srdeční arytmie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- Geografické názvy
- Evropa MeSH
Přestože myšlenku umělé inteligence (AI) lze nalézt již u starověkých filozofů, teprve rozvoj výpočetní techniky v posledních desetiletích umožnil praktický vývoj AI. V posledních dekádách se začíná AI významněji prosazovat v mnoha oborech, v poslední dekádě také v medicíně, neurologii nevyjímaje. AI se v současnosti testuje v diagnostice a plánování léčby u mnoha neurologických onemocnění. Nadějné se zdá především využití AI ve vyhodnocování nálezů neurozobrazovacích metod. AI je testována v diagnostice a léčbě neurodegenerativních onemocnění, především Alzheimerovy demence, diagnostice a léčbě cévních mozkových příhod, roztroušené sklerózy, monitorování epilepsie či v neurorehabilitaci a neuroonkologii. K dalším významným oblastem využití AI patří neurologický výzkum. Nicméně rozvoj AI přináší také mnoho etických problémů, které bude potřeba v budoucnu vyřešit. Ačkoli má AI značný potenciál v diagnostice a léčbě neurologických onemocnění, je potřeba pečlivě a kriticky validovat jednotlivé výsledky konkrétního použití AI a až následně ji integrovat do klinických pracovních postupů.
Although the idea of artificial intelligence (AI) can be found as early as the ancient philosophers, it is only the development of computing technology in recent decades that has enabled the practical development of AI. In recent decades, AI has begun to make a significant impact in many fields, including medicine, not least neurology. AI is currently being tested in diagnosis and treatment planning for many neurological diseases. In particular, the use of AI in evaluating neuroimaging findings seems promising. AI is being tested in the diagnosis and treatment of neurodegenerative diseases, especially Alzheimer's dementia, diagnosis and treatment of stroke, multiple sclerosis, monitoring of epilepsy or in neurorehabilitation and neuro-oncology. Other important applications of AI include neurological research. However, the development of AI also raises many ethical issues that will need to be resolved in the future. Although AI has considerable potential in the diagnosis and treatment of neurological diseases, there is a need to carefully and critically validate individual results of specific applications of AI before integrating it into clinical workflows.
- MeSH
- Alzheimerova nemoc diagnóza MeSH
- cévní mozková příhoda diagnóza MeSH
- diagnóza počítačová MeSH
- lidé MeSH
- neurologie * MeSH
- umělá inteligence * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- přehledy MeSH
Klimatické změny vedou v posledních letech k prodloužení pylové sezóny, respektive k jejímu časnějšímu začátku. Mobilní aplikace umožnují dnes pacientům monitorovat aktuální pylovou situaci, zaznamenávat vlastní klinické obtíže a lépe dodržovat compliance k léčbě. Klinické projevy pylové alergie zahrnují nejčastěji alergickou rhinokonjunktivitidu. V příspěvku zmiňuji zásady symptomatické farmakoterapie alergické rýmy a kauzální léčbu - specifickou alergenovou imunoterapii.
Pollen season lasts longer because of its earlier start due to recent climate changes. Mobile apps enable pollen monitoring, help patients describe their clinical symptoms, and improve compliance with therapy. Allergic rhinoconjunctivitis is the most frequent clinical symptom. This paper provides info about symptomatic pharmacotherapy as well as about causal treatment- about specific allergen immunotherapy.
- MeSH
- alergeny škodlivé účinky terapeutické užití MeSH
- alergie * etiologie farmakoterapie MeSH
- antagonisté histaminu H1 terapeutické užití MeSH
- aplikace intranazální MeSH
- hormony kůry nadledvin terapeutické užití MeSH
- imunoterapie metody MeSH
- informatika pro pacienty metody MeSH
- internet MeSH
- kombinovaná farmakoterapie MeSH
- lidé MeSH
- mobilní aplikace MeSH
- pyl škodlivé účinky MeSH
- sezónní alergická rýma * etiologie farmakoterapie MeSH
- Check Tag
- lidé MeSH
Akcelerovaná parciální iradiace prsu (APBI) je ověřená metoda ozáření pacientek s časným karcinomem prsu, které splňují indikační kritéria. Perioperační zavádění brachyterapeutických vodičů zkracuje celkovou dobu léčby z několika týdnů na přibližně 14 dní a umožňuje zavádění vodičů pod přímou vizuální kontrolou ihned po odstranění nádorového ložiska. Díky screeningovému programu a časné diagnostice pacientek stále roste počet pacientek vhodných pro tuto léčbu.
Accelerated partial breast irradiation (APBI) is a well-established technique for irradiating patients with early-stage breast cancer who meet the indication criteria. The perioperative insertion of brachytherapy catheters reduces the overall treatment time from several weeks to approximately 14 days and allows for catheter placement under direct visual control immediately after tumor removal. Thanks to screening programs and early-stage diagnosis, the number of patients eligible for this treatment continues to rise.
- MeSH
- brachyterapie * metody MeSH
- časná diagnóza MeSH
- lidé MeSH
- nádory prsu * chirurgie radioterapie MeSH
- perioperační péče metody MeSH
- plánování radioterapie pomocí počítače metody MeSH
- pooperační péče metody MeSH
- radioterapie metody škodlivé účinky MeSH
- Check Tag
- lidé MeSH
- ženské pohlaví MeSH
- Publikační typ
- přehledy MeSH
Brachyterapie s vysokým dávkovým příkonem (high dose rate brachytherapy, HDR BRT) je dnes prováděna výhradně automatickými afterloadingovými ozařovači. Nejčastějšími jsou aplikace intrakavitární a intersticiální, případně jejich kombinace. Důležitým aspektem plánování intersticiální brachyterapie je spolupráce lékaře s fyzikem již ve fázi zavádění aplikátorů. Úprava geometrie zavedených aplikátorů v pozdější fázi již často není realizovatelná. Pro výpočet ozařovacích plánů brachyterapie lze využít řadu zobrazovacích modalit. V článku jsou shrnuty fyzikální parametry hodnocení kvality ozařovacích plánů a cíle jejich optimalizace.
High dose rate brachytherapy is realized solely by automatic afterloading irradiators nowadays. The most common are intracavitary and interstitial applications. Cooperation between a physician and a physicist before insertion of applicators is a very important aspect. Changes of applicators' geometry are usually not possible afterwards. A range of imaging modalities can be used for brachytherapy planning. A physical parameters useful for quality assessment and optimization of the plans are presented in this article.
- Klíčová slova
- afterloading,
- MeSH
- brachyterapie * metody přístrojové vybavení MeSH
- celková dávka radioterapie MeSH
- fyzikální jevy * MeSH
- lidé MeSH
- nádory diagnostické zobrazování radioterapie MeSH
- plánování radioterapie pomocí počítače metody přístrojové vybavení MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- přehledy MeSH
BACKGROUND: Advancements in artificial intelligence (AI) and machine learning (ML) have revolutionized the medical field and transformed translational medicine. These technologies enable more accurate disease trajectory models while enhancing patient-centered care. However, challenges such as heterogeneous datasets, class imbalance, and scalability remain barriers to achieving optimal predictive performance. METHODS: This study proposes a novel AI-based framework that integrates Gradient Boosting Machines (GBM) and Deep Neural Networks (DNN) to address these challenges. The framework was evaluated using two distinct datasets: MIMIC-IV, a critical care database containing clinical data of critically ill patients, and the UK Biobank, which comprises genetic, clinical, and lifestyle data from 500,000 participants. Key performance metrics, including Accuracy, Precision, Recall, F1-Score, and AUROC, were used to assess the framework against traditional and advanced ML models. RESULTS: The proposed framework demonstrated superior performance compared to classical models such as Logistic Regression, Random Forest, Support Vector Machines (SVM), and Neural Networks. For example, on the UK Biobank dataset, the model achieved an AUROC of 0.96, significantly outperforming Neural Networks (0.92). The framework was also efficient, requiring only 32.4 s for training on MIMIC-IV, with low prediction latency, making it suitable for real-time applications. CONCLUSIONS: The proposed AI-based framework effectively addresses critical challenges in translational medicine, offering superior predictive accuracy and efficiency. Its robust performance across diverse datasets highlights its potential for integration into real-time clinical decision support systems, facilitating personalized medicine and improving patient outcomes. Future research will focus on enhancing scalability and interpretability for broader clinical applications.
Intersticiální high-dose rate brachyterapie (HDR BRT) představuje slibnou metodu léčby časného karcinomu penisu, která v mnoha případech slouží jako alternativa k primární chirurgické léčbě. Tato technika umožňuje zachování celistvosti penisu až u 80 % pacientů, kteří by jinak museli podstoupit radikální operaci. Výsledkem je nejen lepší kvalita života pacientů, ale také výrazně nižší výskyt psychických problémů spojených s léčbou. Důležitým přínosem je rovněž možnost zachování sexuálních funkcí na úrovni srovnatelné s obdobím před zahájením léčby.
Interstitial high-dose rate brachytherapy (HDR BRT) is a promising treatment method for early-stage penile cancer, which in many cases serves as an alternative to primary surgical treatment. This technique allows for the preservation of the penis integrity in up to 80% of patients who would otherwise require radical surgery. As a result, patients experience not only a better quality of life but also significantly fewer post-treatment psychological issues. An important benefit is also the ability to maintain sexual function at a level comparable to that before the treatment.
