Povilonis, Paulius Algirdas

Digital health technologies are transforming oncology care, yet adoption remains inconsistent globally. This study evaluates current utilization patterns, perceived effectiveness, and barriers among oncology professionals worldwide.

Įvadas. Lynch‘o sindromas (LS) – paveldimas sindromas, didinantis vėžinių ligų atsiradimo tikimybę. Jis siejamas su mutacija viename iš DNR klaidų taisymo genų (MSH2, MLH1, MSH6, PMS2), lemiančia navikinės DNR mikrosatelitų nestabilumą. Pacientai, sergantys LS, susiduria su didele vėžio išsivystymo rizika, palyginus su bendra populiacija. Nepaisant to, LS yra nepakankamai diagnozuojamas, kadangi susiduriama su iššūkiais pritaikant LS atrankos ir diagnostikos strategijas klinikinėje praktikoje. Tikslas. Literatūros apžvalgos tikslas – sistemingai bei nuosekliai apžvelgti naujausias ir aktualiausias mokslines publikacijas apie Lynch‘o sindromą. Medžiaga ir metodai. Literatūros paieška atlikta PubMed duomenų bazėje, naudojant raktinius žodžius „Lynch syndrome“, „microsatellite instability“, „hereditary colorectal cancer“, „Lynch–associated tumors“. Atrinkta 40 straipsnių anglų kalba, išleistų 2014–2024 metais. Rezultatai. LS galima įtarti remiantis diagnostiniais kriterijais bei atliekant atrankinius tyrimus. Molekulinė diagnostika dažniausiai pradedama nuo mikrosatelitų nestabilumo analizės, o MLH1, MSH2, MSH6 bei PMS2 baltymų ekspresija įvertintama imunohistochemijos metodu. LS diagnozė patvirtinama viename iš MMR genų aptikus gemalo linijos patogeninę mutaciją. LS svarbu diferencijuoti su kitais panašiais sutrikimais: sporadiniu kolorektaliniu vėžiu, Lynch‘o tipo sindromu, konstituciniu MMR trūkumu ir kitais. Išvados. Rizikos grupės pacientai turėtų būti įtraukti į reguliarias kolorektalinio vėžio stebėjimo programas. Pacientams, kuriems patvirtinta MMR geno mutacija, kolonoskopiją rekomenduojama atlikti kas 1 – 3 metus, pradedant nuo 25 ar 35 metų amžiaus, priklausomai nuo nustatyto patogeninio varianto. Reikia tobulinti LS sergančiųjų diagnostiką – nesant rimtų klinikinių įtarimų, dauguma atvejų lieka nediagnozuoti.

Background and Objectives: To our knowledge, this is the first study that investigated the prognostic value of radiomics features extracted from not only staging 18F-fluorodeoxyglucose positron emission tomography (FDG PET/CT) images, but also post-induction chemotherapy (ICT) PET/CT images. This study aimed to construct a training model based on radiomics features obtained from PET/CT in a cohort of patients with locally advanced head and neck squamous cell carcinoma treated with ICT, to predict locoregional recurrence, development of distant metastases, and the overall survival, and to extract the most significant radiomics features, which were included in the final model. Materials and Methods: This retrospective study analyzed data of 55 patients. All patients underwent PET/CT at the initial staging and after ICT. Along the classical set of 13 parameters, the original 52 parameters were extracted from each PET/CT study and an additional 52 parameters were generated as a difference between radiomics parameters before and after the ICT. Five machine learning algorithms were tested. Results: The Random Forest algorithm demonstrated the best performance (R2 0.963–0.998) in the majority of datasets. The strongest correlation in the classical dataset was between the time to disease progression and time to death (r = 0.89). Another strong correlation (r ≥ 0.8) was between higher-order texture indices GLRLM_GLNU, GLRLM_SZLGE, and GLRLM_ZLNU and standard PET parameters MTV, TLG, and SUVmax. Patients with a higher numerical expression of GLCM_ContrastVariance, extracted from the delta dataset, had a longer survival and longer time until progression (p = 0.001). Good correlations were observed between Discretized_SUVstd or Discretized_SUVSkewness and time until progression (p = 0.007). Conclusions: Radiomics features extracted from the delta dataset produced the most robust data. Most of the parameters had a positive impact on the prediction of the overall survival and the time until progression. The strongest single parameter was GLCM_ContrastVariance. Discretized_SUVstd or Discretized_SUVSkewness demonstrated a strong correlation with the time until progression.

Introduction: Neuroendocrine tumours (NETs) are a heterogeneous group of tumours characterised by hypersecretion of biologically active substances. The neuroendocrine nature is only determined by immunohistochemical studies and does not have a separate code according to the ICD-10-AM classification, so the disease "hides" under the diagnosis of other neoplasms in the Lithuanian Cancer Registry. Aim of the study: To analyse the distribution of patients diagnosed with NET at Hospital of LUHS Kaunas Clinics in 2018-2019 according to demographic characteristics, primary tumour localisation, morphology, metastasis features, and disease stages. To assess overall survival (median, 3-year survival). To compare the results with the Hospital of LUHS data from 2009-2014. MATERIALS AND METHODS: The retrospective study included 255 patients diagnosed with NET in 2018-2019 at Hospital of LUHS Kaunas Clinics. Patient's demographics, localisation of the primary tumour, histopathological characteristics of the tumours, and stage (ICD-10-AM) were assessed. The Kaplan-Meier method was used to estimate survival. Results: In 2018-2019, NETs were more frequently diagnosed in men (60%). The most frequently (53.7%) primary NETs were found in the lungs, 47.4% of all NETs were advanced (stage IV) at diagnosis. Median life expectancy of NETs was 12 months. Compared with 2009-2014 data the 3-year survival rate for NET of lungs increased from 20% to 27%. Conclusions: The greatest increase in the 3-year survival rate was found in the NETs of lungs, which was the most frequent primary NET. Data on NET is often overlooked because of the current ICD-10-AM classification. Further developments of ICD are warranted to improve data accessibility on NETs.

INTRODUCTION: Neuroendocrine tumours (NETs) are a heterogeneous group of tumours characterised by hypersecretion of biologically active substances. The neuroendocrine nature is only determined by immunohistochemical studies and does not have a separate code according to the ICD-10-AM classification, so the disease "hides" under the diagnosis of other neoplasms in the Lithuanian Cancer Registry. AIM OF THE STUDY: To analyse the distribution of patients diagnosed with NET at Hospital of LUHS Kaunas Clinics in 2018-2019 according to demographic characteristics, primary tumour localisation, morphology, metastasis features, and disease stages. To assess overall survival (median, 3-year survival). To compare the results with the Hospital of LUHS data from 2009-2014. MATERIALS AND METHODS: The retrospective study included 255 patients diagnosed with NET in 2018-2019 at Hospital of LUHS Kaunas Clinics. Patient's demographics, localisation of the primary tumour, histopathological characteristics of the tumours, and stage (ICD-10-AM) were assessed. The Kaplan-Meier method was used to estimate survival. RESULTS: In 2018-2019, NETs were more frequently diagnosed in men (60%). The most frequently (53.7%) primary NETs were found in the lungs, 47.4% of all NETs were advanced (stage IV) at diagnosis. Median life expectancy of NETs was 12 months. Compared with 2009-2014 data the 3-year survival rate for NET of lungs increased from 20% to 27%. CONCLUSIONS: The greatest increase in the 3-year survival rate was found in the NETs of lungs, which was the most frequent primary NET. Data on NET is often overlooked because of the current ICD-10-AM classification. Further developments of ICD are warranted to improve data accessibility on NETs.

Background and Objectives This is the first study to explore the prognostic value of radiomics features extracted from both pre- and post-induction chemotherapy (ICT) PET/CT imaging for patients with locally advanced head and neck squamous cell carcinoma (LA-HNSCC). The study aimed to identify the most significant prognostic radiomics biomarkers for locoregional recurrence free survival (LRFS), based on a machine learning model. [...].

Ilgiau nei metus besitęsianti globali COVID-19 pandemija sukėlė vieną didžiausių pasaulio sveikatos krizių istorijoje. Nuo pat pradžių pandemijos priekinėse linijose esantys medicinos darbuotojai bandė įvairius gydymo metodus, kad padėtų pasveikti nuo klastingo viruso ir jo sukeltų padarinių organizmui. Šiuo metu išsiaiškintas tikslus šio viruso patekimo kelias į organizmą, veikimo mechanizmas, ligos eiga bei galimos pasekmės ir baigtys. Šiame straipsnyje analizuojamas 71 metų pacientės, kuriai buvo nustatytas COVID-19 infekcijos sukeltas plaučių uždegimas, pasireiškė tromboemboembolinė plaučių arterijų komplikacija ir išliko ilgalaikė hipoksija, atvejis. Šio atvejo aprašyme aptariamas COVID-19 viruso sukeltos pneumonijos išsivystymo mechanizmas, klinikinė ligos eiga, pneumonijos diagnostika bei gydymas, ilgalaikės oksigenoterapijos pasekmės bei viruso indukuotos hiperkoaguliacijos padidėjęs krešulių formavimasis.

Background: Digital health technologiesprove healthcare. Yet, they may disrupt the workflow and job profile of future healthcare professionals in the way that digital health literacy and skills in working with new technologies will become prerequisite competencies for future physicians. The European Medical Students’ Association (EMSA) initiated a survey to assess the knowledge and opinion of medical students’ about digital health and its implementation in the medical education curriculum. Our aim was to identify medical students’ needs with regard to their education in digital health as well as their training with respective technologies. Results of the survey including recommendations for a meaningful implementation of digital health into the medical curriculum have been presented in the European Commission. Who Should Attend? Anyone who is interested in the topic of digital health and inclusion of new technologies to health professions’ curriculum is welcomed to participate. We would welcome both students and educators in order for the topic to be discussed from all different aspects. Especially stakeholders that already experience digital health in the medical curriculum are warmly welcomed to share their practices. Structure of Workshop: 1. Introduction: digital health and digital health literacy 2. Presentation of student-led activities on digital health throughout Europe 3. Main points and conclusions from EMSA’s survey on digital health among European medical students 4. Presentation: outcomes of relevant meetings e.g European Commissions eHealth Stakeholder Group, Deans’ meeting “Training Future Proof Doctors for the Digital Society” 5. Best practices for inclusion of digital health in health professions’ curricula 6. Identification of challenges and concerns on the topic of digital health Intended Outcomes: - emphasize the importance of keeping the health professions’ curriculum up to date with new te