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Proceedings of the International Cancer Imaging Society (ICIS) 17th Annual Teaching Course : Berlin, Germany. 02 - 04 October 2017

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… It is not uncommon to see the term ‘radiomics’ used interchangeably with radiogenomics in the literature, but the former better reflects the methodology of feature extraction from radiological images. …

Advancing Medulloblastoma Treatment: Molecular Mechanisms, Drug Repurposing, and Precision Therapies.

Medulloblastomas are the most common malignant pediatric brain tumors, representing approximately 20% of the central nervous system cancers in children. These tumors are highly heterogeneous and classified into four molecular subgroups-WNT, SHH, Group 3, and Group 4-each with distinct genetic and epigenetic profiles that influence tumor behavior, therapeutic response, and patient outcomes. Advances in molecular diagnostics have improved the subclassification of medulloblastomas, yet treatment outcomes for high-risk subtypes, particularly Group 3, remain poor, with current modalities often asso

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… Radiomics-based AI platforms utilize magnetic resonance imaging data to classify molecular subgroups with high accuracy, potentially reducing the need for invasive biopsies [ 56 ]. … Radiomics-based machine learning models for prediction of medulloblastoma subgroups: a systematic review and meta-analysis of the diagnostic test performance. Acta Radiol. 2023;64(5):1994–2003. 36510435 10.1177/02841851221143496 57. …

Prediction of osteoporosis using MRI and CT scans with unimodal and multimodal deep-learning models.

PurposeOsteoporosis is the systematic degeneration of the human skeleton, with consequences ranging from a reduced quality of life to mortality. Therefore, the prediction of osteoporosis reduces risks and supports patients in taking precautions. Deep-learning and specific models achieve highly accurate results using different imaging modalities. The primary purpose of this research was to develop unimodal and multimodal deep-learning-based diagnostic models to predict bone mineral loss of the lumbar vertebrae using magnetic resonance (MR) and computed tomography (CT) imaging.MethodsPatients wh

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… Accessed 26 Nov 2021 [Internet] 31985974 7 Li Y Zhao J Lv Z Pan Z Multimodal medical supervised image fusion method by CNN Front Neurosci. 2021 15 638976 34149344 10.3389/fnins.2021.638976 PMC8206541 8 Lim HK Ha HI Park SY Han J Prediction of femoral osteoporosis using machine-learning analysis with radiomics … AConvNet for the 2020s, 2022 IEEE Conference on Computer Vision and Pattern Recognition (pp. 11976-11986) [Internet] 30 Kocak B Key concepts, common pitfalls, and best practices in artificial intelligence and machine learning: focus on radiomics Diagn Interv Radiol. 2022 28(5) 450 462 36218149 10.5152 …

Cardiac amyloidosis: Innovations in diagnosis and treatment.

Cardiac amyloidosis (CA) is a progressive, underdiagnosed condition caused by the deposition of misfolded proteins in the myocardium, forming amyloid fibrils that impair cardiac structure and function. This review highlights recent advances in the diagnosis and treatment of amyloid light-chain (AL) and transthyretin (ATTR) CA, which globally account for most cases of CA. Novel diagnostic tools, including artificial intelligence-enhanced analysis and advanced imaging modalities like positron emission tomography with amyloid-specific tracers, might improve detection rates and diagnostic accuracy

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… Antonopoulos et al . used machine learning to analyse T1 mapping radiomics in CMR, differentiating CA from other forms of LV hypertrophy with an AUC of 0.84. 49 AI tools have also shown promise in PET, with early studies demonstrating high sensitivity and specificity in detecting CA. 50 Despite recent … Machine learning of native T1 mapping radiomics for classification of hypertrophic cardiomyopathy phenotypes. Sci Rep 2021;11:23596. 50. Bargagna F, Zigrino D, De Santi LA, Genovesi D, Scipioni M, Favilli B et al. …

Ten Years After SINS: Role of Surgery and Radiotherapy in the Management of Patients With Vertebral Metastases.

The objective of the different types of treatments for a spinal metastasis is to provide the best oncological and functional result with the least aggressive side effects. Initially created in 2010 to help clinicians in the management of vertebral metastases, the Spine Instability Neoplastic Score (SINS) has quickly found its place in the decision making and the treatment of patients with metastatic spinal disease. Here we conduct a review of the literature describing the different changes that occurred with the SINS score in the last ten years. After a brief presentation of the spinal metasta

From virtual to reality: innovative practices of digital twins in tumor therapy.

BackgroundAs global cancer incidence and mortality rise, digital twin technology in precision medicine offers new opportunities for cancer treatment.ObjectiveThis study aims to systematically analyze the current applications, research trends, and challenges of digital twin technology in tumor therapy, while exploring future directions.MethodsRelevant literature up to 2024 was retrieved from PubMed, Web of Science, and other databases. Data visualization was performed using R and VOSviewer software. The analysis includes the research initiation and trends, funding models, global research distri

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… For example, Salimi et al. introduced the concept of "Organomics," which incorporates radiomic features of healthy organs into prognosis models for non-small cell lung cancer. … | Improved AUROC from 0.791 to 0.864 using synthetic patient data for mortality prediction | [ 76 ] Reduced order PDE model | MRI-based tumor data for triple-negative breast cancer | Reduced computational time by 378 × with high concordance in predictive accuracy | [ 75 ] PET/CT organomics model | Radiomics …

Модель диагностики болезней MS на основе плотности с использованием алгоритма поиска капуцинов и ансамбля глубоких нейронных сетей.

Множественный склероз (MS) — серьезная болезнь мозга, которая постоянно разрушает клетки мозга, влияет на зрение, баланс, мышечный контроль и повседневную активность. В этом исследовании используется взвешенное сочетание глубоких нейронных сетей и методов оптимизации для диагностики заболеваний MS. Этот метод использует кусочки изображений магнитного резонанса (MRI) в качестве входных. Затем, после предварительной обработки, процесс сегментации и идентификации района, представляющего интерес (РОИ), осуществляется с использованием сочетания алгоритма " нечеткие " c-means (FCM) и алгор

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… Peng Y Prediction of unenhanced lesion evolution in multiple sclerosis using radiomics-based models: a machine learning approach Multiple Scler. Relat. Disorders 2021 53 102989 10.1016/j.msard.2021.102989 34052741 Peng, Y. et al. … Prediction of unenhanced lesion evolution in multiple sclerosis using radiomics-based models: a machine learning approach. Multiple Scler. Relat. Disorders . 53 , 102989 (2021). 10.1016/j.msard.2021.102989 34052741 19. ElSebely, R., Yousef, A. H., Salem, A. A. & Abdullah, B. …

Role of PET/CT and Therapy Management of Pancreatic Neuroendocrine Tumors.

Pancreatic neuroendocrine neoplasms (panNENs) are heterogeneous neoplasms with neuroendocrine differentiation that show peculiar clinical and histomorphological features, with variable prognosis. In recent years, advances in knowledge regarding the pathophysiology and heterogeneous clinical presentation, as well as the availability of different diagnostic procedures for panNEN diagnosis and novel therapeutic options for patient clinical management, has led to the recognition of the need for an active multidisciplinary discussion for optimal patient care. Molecular imaging with positron emissio

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… A new approach to image analysis is represented by radiomics. Texture analysis is an emerging tool of diagnostic imaging that may also be used in the setting of prognostic parameters and to assess the response to treatment. … Önner et al. reported that, among tested radiomic features on pretreatment with [ 68 Ga]Ga-DOTA-TATE PET/CT, skewness and kurtosis were able to predict PRRT response [ 59 ]. …

Giant Cell Tumor of the Sacrum: A Narrative Review of Management Challenges and Modalities.

Background/Objectives: Sacral giant cell tumor of bone (GCTB) is a rare, mostly benign but locally aggressive neoplasm that carries significant diagnostic and treatment challenges due to its anatomic complexity, proximity to sacral nerve roots as well as the blood vessels, and potential impact on bowel, bladder, sexual, and lumbopelvic function and stability. This narrative review aimed to synthesize current evidence on the epidemiology, clinical presentation, diagnostic evaluation, classification, management strategies, outcomes, and surveillance of sacral GCTB. Methods: A focused literature

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… Advanced MRI-based radiomics models have shown moderate performance in distinguishing sacral chordoma, sacral GCTB, and sacral metastasis, and may serve as an adjunct in difficult cases [ 19 ]. 5. … A Triple-Classification Radiomics Model for the Differentiation of Primary Chordoma, Giant Cell Tumor, and Metastatic Tumor of Sacrum Based on T2-Weighted and Contrast-Enhanced T1-Weighted MRI. J. Magn. Reson. Imaging. 2019;49:752–759. doi: 10.1002/jmri.26238. 20. …

Skeletal muscle dysfunction induced by cancer immunotherapy: mechanistics insights and surgical implications.

Cancer immunotherapy has revolutionized cancer treatment, yet its effects extend far beyond tumor eradication. Accumulating evidence indicates that immunotherapy-associated skeletal muscle dysfunction represents a complex, cross-organ pathological process driven by dynamic crosstalk between the tumor microenvironment and peripheral tissues. Rather than an isolated adverse event, muscle injury emerges from integrated mechanisms including inflammatory cytokine spillover, aberrant immune cell infiltration, metabolic reprogramming, vascular dysfunction, and impaired regenerative signaling. Central

IDH Mutations in Glioma: Molecular, Cellular, Diagnostic, and Clinical Implications.

In 2021, the World Health Organization classified isocitrate dehydrogenase (IDH) mutant gliomas as a distinct subgroup of tumors with genetic changes sufficient to enable a complete diagnosis. Patients with an IDH mutant glioma have improved survival which has been further enhanced by the advent of targeted therapies. IDH enzymes contribute to cellular metabolism, and mutations to specific catalytic residues result in the neomorphic production of D-2-hydroxyglutarate (D-2-HG). The accumulation of D-2-HG results in epigenetic alterations, oncogenesis and impacts the tumor microenvironment via i

BioBERT-powered synergy: advanced bibliometric and molecular insights into prostate cancer bone metastasis.

BACKGROUND: Prostate cancer (PC) is a leading cause of male cancer mortality, with bone metastasis (BM) being a frequent and debilitating complication. Despite therapeutic advancements, the molecular mechanisms underlying BM remain poorly understood. This study aims to bridge this gap by integrating bibliometric analysis with bioinformatics to provide a comprehensive overview of the academic trends and molecular profiles associated with prostate cancer bone metastasis (PCBM). METHODS: We conducted a bibliometric analysis to identify key contributors in PCBM research from 2004 to 2024 with adv

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… The rise of “deep learning” reflects breakthroughs in AI applications for pathological slide analysis (e.g., P-NET models) and radiomics. … Deep learning with artificial intelligence enhances the specificity of early bone metastasis detection through the deep integration of radiomic feature extraction and transfer learning frameworks. …

The Art of Bioimmunogenomics (BIGs) 5.0 in CAR-T Cell Therapy for Lymphoma Management.

PurposeLymphoma, the most predominant neoplastic disorder, is divided into Hodgkin and Non-Hodgkin Lymphoma classifications. Immunotherapeutic modalities have emerged as essential methodologies in combating lymphoid malignancies. Chimeric Antigen Receptor (CAR) T cells exhibit promising responses in chemotherapy-resistant B-cell non-Hodgkin lymphoma cases.MethodsThis comprehensive review delineates the advancement of CAR-T cell therapy as an immunotherapeutic instrument, the selection of lymphoma antigens for CAR-T cell targeting, and the conceptualization, synthesis, and deployment of CAR-T c

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… Capobianco N Clerc J Chartier L Risk stratification in diffuse large B-cell lymphoma using lesion dissemination and metabolic tumor burden calculated from baseline PET/CT Ann Oncol 2021 32 3 404 11 10.1016/j.annonc.2020.11.019 33278600 124 Sun R Limkin EJ Vakalopoulou M Dercle L Champiat S Han SR A radiomics … -1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study Lancet Oncol 2018 19 9 1180 91 10.1016/s1470-2045(18)30413-3 30120041 125 Dercle L Fronheiser M Lu L Du S Hayes W Leung DK Identification of non-small cell lung cancer sensitive to systemic cancer therapies using radiomics …

Federated Computing in Orthopaedic Surgery: A Paradigm Shift in Collaborative Multicenter Research.

➢ Multicenter studies remain rare in orthopaedics (9.9% of recent publications) due to regulatory complexity, restrictive data-sharing policies, and administrative delays, despite their proven value in generating robust, generalizable evidence. ➢ Federated computing (FC) brings analytic code to each institution's data and returns only encrypted, aggregated results. This preserves patient privacy, maintains institutional control, and streamlines compliance by reducing or eliminating the need for complex data-use agreements. ➢ Extensive applications in other medical fields show that FC can match

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… Site Cohort Sizes † | Study Lung cancer treatment 2-year survival prediction | Clinical and treatment data | 3 | 894 | 196 (139 to 559) | Jochems 41 (2017) Traumatic brain injury analysis | CT scan | 2 | 45 | 18 to 27 | Remedios 47 (2019) Prediction of survival and HPV status in head and neck cancer | Radiomics … Privacy-preserving distributed learning of radiomics to predict overall survival and HPV status in head and neck cancer. Sci Rep. 2020. Mar 11;10(1):4542. 44. …

РАДИОЛОГИЧЕСКАЯ ДИАГНОСТИКА ХРОНИЧЕСКОЙ ОБСТРУКТИВНОЙ БОЛЕЗНИ ЛЁГКИХ: СОВРЕМЕННЫЕ МЕТОДЫ И ИХ КЛИНИЧЕСКОЕ ЗНАЧЕНИЕ

В статье рассматриваются современные методы лучевой диагностики хронической обструктивной болезни лёгких (ХОБЛ), их диагностические возможности и клиническое значение. Особое внимание уделяется мультисрезовой компьютерной томографии высокого разрешения (ВРКТ) как наиболее информативному инструментальному методу, позволяющему не только выявлять и типировать эмфизему лёгких, но и проводить количественную оценку поражения паренхимы с помощью денситометрического анализа. Анализируются диагностические возможности рентгенографии органов грудной клетки, низкодозовой КТ, вентиляционно-перфузионной сци

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… Перспективным направлением является интеграция данных КТ-текстурного анализа (radiomics) и глубокого обучения для прогнозирования обострений ХОБЛ, динамики ОФВ1 и смертности. …

Artificial inteligence and datasets for leukemia diagnosis: A scoping review of machine lerning and deep learning approaches.

Leukemia is the cancerous disease of the blood and the bone marrow that causes excessive proliferation of abnormal white blood cells, if detected too late, it can lead to potentially fatal consequences. Peripheral blood smear examinations and bone marrow biopsy are example of conventional diagnostic techniques that are invasive, time-consuming and subject to human variability. Recent advances in artificial intelligence (AI) particularly in the areas of Machine Learning (ML) and Deep Learning (DL)offer encouraging answers by making it possible to detect and classify leukemia using automated, ef

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… [ 61 ] obtained 43 morphological, 276 radiomic, and 1 clinical feature from 50 bone marrow smear images in the CPTAC-AML (TCIA) dataset. A Random Forest model with nine features had a training AUC of 0.998 ± 0.004 and accuracy of 0.998 ± 0.003. The BLS model also had 0.973 accuracy. … 99.85% [ 60 ] | 2024 | B-ALL, early pre-B, pre-B, pro-B | ALL dataset on Kaggle | Transfer learning with pre-train ed ResNet-50 | ResNet-50 with 5-fold cross validation | Accuracy: 99.38, Precision: 99.39, Recall: 99.38, F1-score: 99.38 [ 61 ] | 2022 | AML: M1/M2 | CPTAC-AML (TCIA) | Morphological & radiomics …

Adipocyte-Tumor Interactions in the Bone Marrow Niche: Implications for Metastasis and Therapy.

Bone metastases continue to be a major cause of morbidity and mortality in patients with advanced cancers, driven by the dynamic remodeling of the bone marrow niche. Traditionally viewed as passive space-fillers, bone marrow adipocytes (BMAs) are now recognized as active regulators of tumor growth, therapeutic resistance, and skeletal pathology. BMAs comprise a significant portion of the adult marrow space, particularly in aging and obesity, and facilitate metastatic colonization through various mechanisms. These include metabolic coupling, where adipocyte-derived fatty acids fuel tumor oxidat

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… Preliminary radiomics studies have used PDFF thresholds to differentiate malignant from normal bone marrow. … Integrating advanced imaging (e.g., PDFF, CEST) with radiomics and molecular profiling of bone marrow aspirates may enhance diagnostic and prognostic tools. …

Навигатор биомаркеров человека.

Биомаркеры играют ключевую роль в современных исследованиях медицины, особенно в ранней диагностике заболеваний и персонализированном лечении. Несмотря на то, что предыдущие исследования систематически обзоры маркеров в различных областях заболеваний, интегрированная система, которая связывает основные физиологические системы, охватывает множество органов и охватывает широкий спектр заболеваний, все еще отсутствует. В контексте современных вызовов здоровья, характеризующихся высокой распространенностью хронических заболеваний и широкими сопутствующими заболеваниями, создание панорамной системы

The Applications of Machine Learning in the Management of Patients Undergoing Stem Cell Transplantation: Are We Ready?

Hematopoietic stem cell transplantation (HSCT) is a life-saving therapy for hematologic malignancies, such as leukemia and lymphoma and other severe conditions but is associated with significant risks, including graft versus host disease (GVHD), relapse, and treatment-related mortality. The increasing complexity of clinical, genomic, and biomarker data has spurred interest in machine learning (ML), which has emerged as a transformative tool to enhance decision-making and optimize outcomes in HSCT. This review examines the applications of ML in HSCT, focusing on donor selection, conditioning re

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… However, much work remains to be performed, especially for newer biomarkers or relatively recent omics analyses (e.g., radiomics). A diagram concerning the ML workflow together with the main challenges is reported in Figure 6 . Figure 6 Example of machine learning workflow. … Prognostic model using 18F-FDG PET radiomics predicts progression-free survival in relapsed/refractory Hodgkin lymphoma. Blood Adv. 2023;7:6732–6743. doi: 10.1182/bloodadvances.2023010404. 65. …

Review of imaging techniques for evaluating morphological and functional responses to the treatment of bone metastases in prostate and breast cancer.

Bone metastases are very common complications associated with certain types of cancers that frequently negatively impact the quality of life and functional status of patients; thus, early detection is necessary for the implementation of immediate therapeutic measures to reduce the risk of skeletal complications and improve survival and quality of life. There is no consensus or universal standard approach for the detection of bone metastases in cancer patients based on imaging. Endorsed by the Spanish Society of Medical Oncology (SEOM), the Spanish Society of Medical Radiology (SERAM), and the

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… The set of multivariate analysis techniques for these imaging biomarkers to detect new diagnostic, prognostic or predictive information on the response to treatment is called radiomics and has begun to be used in the evaluation of bone metastases. … Thus, radiomics allows the successful differentiation between metastatic and nonmetastatic vertebral lesions in oncological patients investigated with MRI [ 113 ] and, more interestingly, allows prediction of the risk of metastatic bone disease in PCa using MRI texture analysis of the primary tumor [ …