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Myeloma Spine and Bone Damage Score (MSBDS) on Whole-Body Computed Tomography (WBCT): Multiple Reader Agreement in a Multicenter Reliability Study.

Objective: To assess the reliability of the myeloma spine and bone damage score (MSBDS) across multiple readers with different levels of expertise and from different institutions. Methods: A reliability exercise, including 104 data sets of static images and complete CT examinations of patients affected by multiple myeloma (MM), was performed. A complementary imaging atlas provided detailed examples of the MSBDS scores, including low-risk and high-risk lesions. A total of 15 readers testing the MSBDS were evaluated. ICC estimates and their 95% confidence intervals were calculated based on mean

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… Prediction of High-Risk Cytogenetic Status in Multiple Myeloma Based on Magnetic Resonance Imaging: Utility of Radiomics and Comparison of Machine Learning Methods. J. Magn. Reson. Imaging. 2021;54:1303–1311. doi: 10.1002/jmri.27637. 8. … Quantitative Imaging and Radiomics in Multiple Myeloma: A Potential Opportunity? Medicina. 2021;57:94. doi: 10.3390/medicina57020094. 12. Tagliafico A.S., Belgioia L., Bonsignore A., Rossi F., Succio G., Bignotti B., Dominietto A. …

Дифференциация между множественным склерозом и расстройствами оптического спектра нейромиелита с многоуровневой характеристикой FMRI: анализ машинного обучения.

Традиционный статистический подход к анализу функциональных данных МРТ (rs-fMRI) в состоянии отдыха не позволяет точно различить пациентов с множественным склерозом (MS) и пациентов с расстройствами оптического спектра нейромиелита (NMOSD), что подчеркивает необходимость повышения диагностической эффективности. В этом исследовании были рассчитаны и извлечены многоуровневые функциональные метрики, включая функциональную связь в установившемся состоянии, амплитуду низких частотных колебаний (ALFF) и региональную однородность (Reho) из 116 регионов, представляющих интерес в анатомическом автомати

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… For instance, He et al. 23 utilized radiomics technology to extract radiomics features of lesions in T2-weighted images, effectively distinguishing between patients with MS and NMOSD. … Although rs-fMRI features are more straightforward to interpret than radiomics features, their lack of specificity limits their practical application. …

Dural Lymphomas Unmasked: A Narrative Review of Extra-Axial Mimics and a Pragmatic Diagnostic Decision Algorithm.

Dural-based lymphomas are rare extranodal non-Hodgkin lymphomas that span from indolent primary dural entities, most commonly the extranodal marginal zone (mucosa-associated lymphoid tissue) lymphoma, to aggressive variants that are primary or represent secondary involvement from systemic lymphoma. They overlap radiologically with benign meningiomas, dural metastases, and immune-mediated pachymeningitis, creating a risk of anchoring bias, delayed diagnosis, and unnecessarily extensive resections when limited tissue sampling would be sufficient for diagnosis. We conducted a structured narrative

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… Radiomics features to distinguish glioblastoma from primary central nervous system lymphoma on multi-parametric MRI Neuroradiology 2018 60 1297 1305 10.1007/s00234-018-2091-4 30232517 67. Bathla G. Priya S. Liu Y. Ward C. Le N.H. Soni N. Maheshwarappa R.P. Monga V. Zhang H. Sonka M. … The Image Biomarker Standardization Initiative: Standardized quantitative radiomics for high-throughput image-based phenotyping Radiology 2020 295 328 338 10.1148/radiol.2020191145 32154773 PMC7193906 …

The EPICURE study: a pilot prospective cohort study of heterogeneous and massive data integration in metastatic breast cancer patients.

BackgroundBreast cancer is the most common cancer in women and the first cancer concerning mortality. Metastatic breast cancer remains a disease with a poor prognosis and about 30% of women diagnosed with an early stage will have a secondary progression. Metastatic breast cancer is an incurable disease despite significant therapeutic advances in both supportive cares and targeted specific therapies. In the management of a metastatic patient, each clinician follows a highly complex and strictly personal decision making process. It is based on a number of objective and subjective parameters whic

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… tomography Code | Data origin EDPU-01 | Biometrics (biological, clinical, epidemiological [environment omics], pathological) EDPU-02 | Circulating tumor cells EDPU-03 | Genomics EDPU-04 | Microbiomics EDPU-05 | Microbiomics - food survey EDPU-06 | Proteomics - bulk EDPU-07 | Psycho-oncology survey EDPU-08 | Radiomics … - CT scan EDPU-09 | Radiomics - PET scan EDPU-10 | Transcriptomics - bulk EDPU-11 | Transcriptomics - single cell EDPU-12 | Treatment For clinical data management the platform used to collect and manage the database will be centralized and hosted with the entire control of the institution. …

Оценка полезности гибридного ПЕТ/МР нейроимации во воспламенительной демиэлизации и энцефалите.

В связи с увеличением в последние годы количества гибридных ПЕТ/МСД этот метод все шире используется для нейроимации в клинической практике. Она сочетает преимущества МРТ (включая высокоразрешенную съемку внутрицеребральных повреждений и данных, полученных в результате специализированных последовательности МРТ) с преимуществами ПЕТ, которая визуализирует функциональные изменения в мозге, а также оценивает изменения в количестве миелинов и остроту воспаления. Использование ПЕТ/МОИ может помочь устранить ограничения МРТ, указанные в виде обезображивающих подстрекательских заболеваний (таких, как

Application of Pet-CT Fusion Deep Learning Imaging in Precise Radiotherapy of Thyroid Cancer.

This article explores the value of wall F-FDG PET/Cr imaging in the diagnosis of thyroid cancer, studies its ability to distinguish benign and malignant thyroid lesions, and seeks ways to improve the accuracy of diagnosis. The normal control group selected 40 patients who came to our center for physical examination. In the normal control group, the average value of the standard uptake value of both sides of the thyroid was used as the SUV of the thyroid gland and the highest SUV value of the patient's lesion (SUV max) represented the SUV of the lesion. After injection of imaging agent 18F-FD1G

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… Radiomics in oncological PET/CT: clinical applications. Nuclear medicine and molecular imaging. 2020;117(3):187–192. doi: 10.1007/s13139-017-0500-y. 16. Jager P. L., Chirakal R., Marriott C. … Li P., Wang X., Xu C., et al. 18 F-FDG PET/CT radiomic predictors of pathologic complete response (pCR) to neoadjuvant chemotherapy in breast cancer patients. European Journal of Nuclear Medicine and Molecular Imaging. 2021;5(23):1–12. doi: 10.1007/s00259-020-04684-3. 24. …

Targeting cancer stem cells with CAR-based immunotherapy: biology, evidence, and future directions.

Cancer stem cells (CSCs) are pivotal in tumor initiation, progression, and relapse, underscoring the need for targeted therapies to achieve lasting responses. This review delves into CSC biology, highlighting their tumor-initiating potential demonstrated through limiting dilution assays and their role in resistance to therapies. Although successful CAR therapies, such as anti-CD19 CAR T-cells, can induce complete responses without directly targeting CSCs, CAR strategies focusing on CSCs may offer promising avenues to prevent recurrence. We assess CAR therapies targeting CSC-specific antigens,

Assessing the Potential Usefulness of FDG LAFOV-PET for Oncological Staging: An Evaluation of Lesion Number and Uptake.

Background/Objectives: In many cases, the detection of a single lesion could revolutionise patient clinical management; not all localisations, especially those with a low uptake and, consequently, a low Tumour-to-Background Ratio (TBR), are readily detectable using [18F]F-FDG PET/CT. LAFOV-PET offers a potential enhancement in lesion detection, but the proportion of patients who would benefit from its use has yet to be determined. With the present analysis, we aimed to assess which clinical contexts the enhancement in lesion detection could affect the most. Methods: This retrospective study in

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… Long-Axial Field-of-View PET/CT Improves Radiomics Feature Reliability. Eur. J. Nucl. Med. Mol. Imaging. 2025;52:1004–1016. doi: 10.1007/s00259-024-06921-5. 24. Alberts I., Seibel S., Xue S., Viscione M., Mingels C., Sari H., Afshar-Oromieh A., Limacher A., Rominger A. … The Role and Potential of 18F-FDG PET/CT in Malignant Melanoma: Prognostication, Monitoring Response to Targeted and Immunotherapy, and Radiomics. Diagnostics. 2022;12:929. doi: 10.3390/diagnostics12040929. 29. Chen M., Jiang Y., Zhou X., Wu D., Xie Q. …

Machine learning in onco-pharmacogenomics: a path to precision medicine with many challenges.

Over the past two decades, Next-Generation Sequencing (NGS) has revolutionized the approach to cancer research. Applications of NGS include the identification of tumor specific alterations that can influence tumor pathobiology and also impact diagnosis, prognosis and therapeutic options. Pharmacogenomics (PGx) studies the role of inheritance of individual genetic patterns in drug response and has taken advantage of NGS technology as it provides access to high-throughput data that can, however, be difficult to manage. Machine learning (ML) has recently been used in the life sciences to discover

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… In particular, the emerging field of radiomics uses images routinely produced in clinical settings to evaluate patients undergoing treatment to develop a ML approach to disease detection ( Lambin et al., 2012 ). … ) | Regression | Prediction of OS and PFS in patients with ESCC based on CT image radiomics signatures | Cui et al. (2022a) FIGURE 4 Main uses of ML algorithms in cancer research. …

Multiple myeloma segmentation net (MMNet): an encoder-decoder-based deep multiscale feature fusion model for multiple myeloma segmentation in magnetic resonance imaging.

BackgroundPatients with multiple myeloma (MM), a malignant disease involving bone marrow plasma cells, shows significant susceptibility to bone degradation, impairing normal hematopoietic function. The accurate and effective segmentation of MM lesion areas is crucial for the early detection and diagnosis of myeloma. However, the presence of complex shape variations, boundary ambiguities, and multiscale lesion areas, ranging from punctate lesions to extensive bone damage, presents a formidable challenge in achieving precise segmentation. This study thus aimed to develop a more accurate and robu

Predicting the Risk for Pathological Fracture in Bone Metastases.

Approximately 50-70% of patients with advanced cancer will experience bone metastases. The link between metastatic lesions and pathological bones is especially troubling since more metastases mean a higher chance of painful fractures, which can reduce mobility and often require surgery. Therefore, fracture risk predictions are essential for managing patients with bone metastases. However, the current methods for evaluating the risk of fractures are subjective, with low predictive value. This paper highlights how there being no effective comprehensive models for grouping patients by fracture ri

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… Future Directions A machine learning composite model based on the CT attenuation values and radiomic features of the proximal femur has recently been reported to be able to accurately predict proximal femur fractures caused by osteoporosis [ 43 ]. … Machine Learning-Based CT Radiomics Model to Predict the Risk of Hip Fragility Fracture Acad. Radiol. 2025 32 2854 2862 10.1016/j.acra.2025.01.023 39904664 44. Coleman R. Brown J. Terpos E. Lipton A. Smith M.R. Cook R. Major P. …

[18F]FDG-PET/CT texture analysis in thyroid incidentalomas: preliminary results.

Backgroundsignificance of incidental thyroid 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) uptake on positron emission tomography/computed tomography (PET/CT) scans remains controversial. We aimed to evaluate the ability of [18F]FDG-PET/CT texture analysis to predict final diagnosis in thyroid incidentaloma.MethodsWe retrospectively evaluated medical records of all patients who performed a [18F]FDG-PET/CT from January 2012 to October 2016. Those patients who presented a thyroid incidentaloma described in the medical records and performed a fine needle aspiration in our institution were considered

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… Radiomics is a post-processing approach correlating image texture parameters to clinical, genetic and prognostic variables, and it is applicable to all types of images. Time for texture processing varies among software used for both images segmentation and features extraction. … Texture analysis of [ 18 F]FDG-PET/CT images provides quantitative parameters describing tissue metabolic heterogeneity and seems to perform better than the conventional PET metrics in several malignances, but data on [ 18 F]FDG-PET/CT radiomics in thyroid nodules are limited. Kim et al. …

Translational Bioinformatics Applied to the Study of Complex Diseases.

Translational Bioinformatics (TBI) is defined as the union of translational medicine and bioinformatics. It emerges as a major advance in science and technology by covering everything, from the most basic database discoveries, to the development of algorithms for molecular and cellular analysis, as well as their clinical applications. This technology makes it possible to access the knowledge of scientific evidence and apply it to clinical practice. This manuscript aims to highlight the role of TBI in the study of complex diseases, as well as its application to the understanding and treatment o

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… . | Advanced Gastric Adenocarcinoma, Immunotherapy | Device: EV-array | China | NCT04993378 ML radiomic and pathomic study of Pituitary Adenomas | Machine learning to study multi-dimensional and multi-omics data, to train a risk prediction algorithm for refractory pituitary adenomas. | Pituitary Neoplasms … Cancer Neoadjuvant Chemoradiation response prediction using Artificial Intelligence & Machine Learning (QARC) | To predict treatment response in esophageal cancer patients using radiomics AI modeling. | Esophageal Cancer | Radiation: Neo-adjuvant radiotherapy, Drug: Neo-adjuvant chemotherapy, Procedure …

5-Hydroxymethylcytosine modifications in circulating cell-free DNA: frontiers of cancer detection, monitoring, and prognostic evaluation.

Developing accurate, clinically convenient, and non-invasive methods for early cancer detection, monitoring, and prognosis assessment is essential for improving patient survival rates, enhancing quality of life, and reducing the socioeconomic burden associated with cancer. This goal is critical in precision oncology. Genetic and epigenetic alterations in circulating cell-free DNA (cfDNA) have emerged as transformative tools for advancing early cancer detection, monitoring, and improving patient outcomes. Among these, 5-hydroxymethylcytosine (5hmC) modifications in circulating cfDNA stand out a

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… The clinic-RadmC model, integrating clinical data, deep learning-based radiomics and 5 bp-5mC scores, achieved an AUC of 0.923 on an external test set, outperforming single-omics models and those integrating only clinical data with radiomic or 5mC fragmentomic features [ 46 ]. … Additionally, efforts should focus on integrating multi-omics data, such as radiomics, transcriptomics, and proteomics, with 5hmC signatures to enhance diagnostic accuracy and discover novel biomarkers for early-stage HCC. …

Всемирный конгресс молекулярного воображения 2022.

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Advances in Imaging for Metastatic Epidural Spinal Cord Compression: A Comprehensive Review of Detection, Diagnosis, and Treatment Planning.

Metastatic epidural spinal cord compression (MESCC) is a critical oncologic emergency caused by the invasion of metastatic tumors into the spinal epidural space, leading to compression of the spinal cord. If not promptly diagnosed and treated, MESCC can result in irreversible neurological deficits, including paralysis, significantly impacting the patient's quality of life. Early detection and timely intervention are crucial to prevent permanent damage. Imaging modalities play a pivotal role in the diagnosis, assessment of disease extent, and treatment planning for MESCC. Magnetic resonance ima

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… Radiomics [ 64 ] | Extracting quantitative data from medical images for personalized diagnosis. | Allows for prediction of tumor behavior, prognosis, and treatment response based on imaging characteristics. | High complexity requires advanced software and integration with clinical workflows and interpretability … compression: a qualitative review J Bone Oncol Di Perna G Cofano F Mantovani C 100320 25 2020 33088700 10.1016/j.jbo.2020.100320 PMC7559860 63 Artificial intelligence and machine learning in spine research JOR Spine Galbusera F Casaroli G Bassani T 0 2 2019 10.1002/jsp2.1044 PMC6686793 31463458 64 Radiomics …

Monoclonal gammopathy of renal significance (MGRS): retrospective monocentric analysis of clinical outcomes and treatment strategies.

Monoclonal Gammopathy of Renal Significance (MGRS) is a group of rare disorders in which monoclonal proteins cause kidney damage. Due to its rarity, ongoing research is vital to refine diagnostics, enhance treatment, and improve outcomes. This retrospective study analyzed 34 patients with renal biopsy-proven MGRS-defining lesions. Patients were divided into two subgroups: kidney-limited AL amyloidosis (MGRS-A, 44%, n = 15) and other MGRS (MGRS-NA, 56%, n = 19). Key outcomes included progression-free survival and overall survival. Baseline characteristics such as histopathology, plasma cell per

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… Advances in diagnostic techniques, including radiomics and DNA-based methods such as cell-free DNA analysis, could enable earlier detection and better characterization of MGRS, facilitating the design of prospective trials with larger cohorts to validate our findings [ 22 – 24 ]. … Deep learning with radiomics for disease diagnosis and treatment: challenges and potential. Front Oncol. 2022;12:773840. 23. Stanley KE, Jatsenko T, Tuveri S, Sudhakaran D, Lannoo L, Van Calsteren K, et al. Cell type signatures in cell-free DNA fragmentation profiles reveal disease biology. …

Surviving Cancer, Lacking Support: The Hidden Burden of Modern Radiation Oncology in the Treatment of Oligometastatic Disease.

The management of oligometastatic disease has undergone a significant paradigm shift over the past two decades. Once considered uniformly incurable, selected patients with metastatic disease can now achieve prolonged progression-free survival, durable disease control, and, in carefully selected cases, long-term remission or cure through metastasis-directed therapies. Advances in stereotactic ablative radiotherapy (SABR), surgery, systemic therapies, and the emerging concept of Curative Oligometastatic Radiotherapy (CORT) have challenged the traditional distinction between curative and palliati

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… Looking forward, integration of advanced imaging with molecular biomarkers, radiomics, and artificial intelligence may enable more precise prediction of disease behaviour, personalised surveillance strategies, and improved treatment selection. … In parallel, advances in radiomics and radiogenomics seek to extract quantitative imaging features that reflect tumour phenotype and integrate these with genomic data to improve risk stratification and treatment prediction [ 19 , 25 , 26 ]. …

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certa

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… Luo X Piao S Li H et al Multi-lesion radiomics model for discrimination of relapsing-remitting multiple sclerosis and neuropsychiatric systemic lupus erythematosus Eur Radiol Aug 2022 32 8 5700 5710 doi 10.1007/s00330-022-08653-2 Medline 35243524 18. … Qin X Xia L Zhu C et al Noninvasive evaluation of lupus nephritis activity using a radiomics machine learning model based on ultrasound J Inflamm Res 2023 16 433 441 doi 10.2147/JIR.S398399 Medline 36761904 PMC9904229 27. …

PET/CT Imaging for Therapy Assessment in Multieloma, включая MRD.

Фон/цели: Множественная миелома (ММ) представляет собой сложную гематологическую порчу, характеризующуюся аномальным распространением плазменных клеток в костном мозге. [18F]FDG PET/CT стала одним из ключевых способов визуализации, демонстрируя высокую чувствительность и специфичность для обнаружения метаболически активных заболеваний по сравнению с обычными методами визуализации. В настоящем обзоре рассматривается роль изображений ПЕТ/КТ в оценке терапевтической реакции в симптоматической миеломе, включая оценку минимальных остаточных заболеваний (ОРЗ). Методы: Мы изучили литературу, опублико

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… Artificial intelligence and radiomics represent a further emerging direction. … By extracting quantitative imaging features beyond visual analysis, radiomics combined with machine learning has shown potential to refine prognostic stratification and to support minimal residual disease assessment in multiple myeloma [ 77 , 78 ], although these approaches remain preliminary and require …