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  1. Article ; Online: Non-contrast magnetic resonance Lymphography and Indocyanine green Lymphography play a complementary role in the management of upper limb lymphedema.

    Cellina, Michaela

    Magnetic resonance imaging

    2024  Volume 109, Page(s) 187–188

    MeSH term(s) Humans ; Indocyanine Green ; Lymphography ; Lymphedema/diagnostic imaging ; Upper Extremity/diagnostic imaging ; Magnetic Resonance Spectroscopy ; Coloring Agents
    Chemical Substances Indocyanine Green (IX6J1063HV) ; Coloring Agents
    Language English
    Publishing date 2024-03-19
    Publishing country Netherlands
    Document type Letter
    ZDB-ID 604885-7
    ISSN 1873-5894 ; 0730-725X
    ISSN (online) 1873-5894
    ISSN 0730-725X
    DOI 10.1016/j.mri.2024.03.024
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1817: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  2. Article: Preface: Artificial Intelligence and the Revolution of Oncological Imaging.

    Cè, Maurizio / Cellina, Michaela

    Critical reviews in oncogenesis

    2024  Volume 29, Issue 2, Page(s) ix–xi

    MeSH term(s) Humans ; Artificial Intelligence ; Diagnostic Imaging ; Medical Oncology
    Language English
    Publishing date 2024-03-05
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1036388-9
    ISSN 0893-9675
    ISSN 0893-9675
    DOI 10.1615/CritRevOncog.v29.i2.30
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 2587: Show issues Location:
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    ab Jg. 2022: Lesesaal (EG)

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  3. Article ; Online: Comment on "Response to COVID-19 in Breast Imaging".

    Orsi, Marcello A / Oliva, Giancarlo / Cellina, Michaela

    Journal of breast imaging

    2024  Volume 2, Issue 3, Page(s) 186

    Language English
    Publishing date 2024-02-29
    Publishing country United States
    Document type Journal Article
    ISSN 2631-6129
    ISSN (online) 2631-6129
    DOI 10.1093/jbi/wbaa031
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Management of COVID-19 post-vaccine Bell's palsy in an outpatient.

    Cellina, Michaela / D'Arrigo, Andrea

    Clinical imaging

    2021  Volume 83, Page(s) 188–189

    MeSH term(s) Bell Palsy/etiology ; COVID-19 ; COVID-19 Vaccines ; Disclosure ; Facial Paralysis/complications ; Humans ; Outpatients ; SARS-CoV-2
    Chemical Substances COVID-19 Vaccines
    Language English
    Publishing date 2021-12-24
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 1028123-x
    ISSN 1873-4499 ; 0899-7071
    ISSN (online) 1873-4499
    ISSN 0899-7071
    DOI 10.1016/j.clinimag.2021.12.006
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 1469: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  5. Article: Artificial Intelligence in Bone Metastasis Imaging: Recent Progresses from Diagnosis to Treatment - A Narrative Review.

    Caloro, Elena / Gnocchi, Giulia / Quarrella, Cettina / Ce, Maurizio / Carrafiello, Gianpaolo / Cellina, Michaela

    Critical reviews in oncogenesis

    2024  Volume 29, Issue 2, Page(s) 77–90

    Abstract: The introduction of artificial intelligence (AI) represents an actual revolution in the radiological field, including bone lesion imaging. Bone lesions are often detected both in healthy and oncological patients and the differential diagnosis can be ... ...

    Abstract The introduction of artificial intelligence (AI) represents an actual revolution in the radiological field, including bone lesion imaging. Bone lesions are often detected both in healthy and oncological patients and the differential diagnosis can be challenging but decisive, because it affects the diagnostic and therapeutic process, especially in case of metastases. Several studies have already demonstrated how the integration of AI-based tools in the current clinical workflow could bring benefits to patients and to healthcare workers. AI technologies could help radiologists in early bone metastases detection, increasing the diagnostic accuracy and reducing the overdiagnosis and the number of unnecessary deeper investigations. In addition, radiomics and radiogenomics approaches could go beyond the qualitative features, visible to the human eyes, extrapolating cancer genomic and behavior information from imaging, in order to plan a targeted and personalized treatment. In this article, we want to provide a comprehensive summary of the most promising AI applications in bone metastasis imaging and their role from diagnosis to treatment and prognosis, including the analysis of future challenges and new perspectives.
    MeSH term(s) Humans ; Artificial Intelligence ; Diagnosis, Differential ; Genomics ; Medical Oncology
    Language English
    Publishing date 2024-03-05
    Publishing country United States
    Document type Review ; Journal Article
    ZDB-ID 1036388-9
    ISSN 0893-9675
    ISSN 0893-9675
    DOI 10.1615/CritRevOncog.2023050470
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 2587: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  6. Article ; Online: Unilateral Axillary Lymphadenopathy After Coronavirus Disease (COVID-19) Vaccination.

    Cellina, Michaela / Irmici, Giovanni / Carrafiello, Gianpaolo

    AJR. American journal of roentgenology

    2021  Volume 216, Issue 5, Page(s) W27

    MeSH term(s) COVID-19 ; Coronavirus ; Humans ; Lymphadenopathy/diagnostic imaging ; Magnetic Resonance Imaging ; SARS-CoV-2 ; Vaccination
    Language English
    Publishing date 2021-02-22
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 82076-3
    ISSN 1546-3141 ; 0361-803X ; 0092-5381
    ISSN (online) 1546-3141
    ISSN 0361-803X ; 0092-5381
    DOI 10.2214/AJR.21.25683
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Ue I Zs.57: Show issues Location:
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    ab Jg. 2022: Lesesaal (EG)

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  7. Article: Radiomics and Artificial Intelligence in Renal Lesion Assessment.

    Cellina, Michaela / Irmici, Giovanni / Pepa, Gianmarco Della / Ce, Maurizio / Chiarpenello, Vittoria / Alì, Marco / Papa, Sergio / Carrafiello, Gianpaolo

    Critical reviews in oncogenesis

    2024  Volume 29, Issue 2, Page(s) 65–75

    Abstract: Radiomics, the extraction and analysis of quantitative features from medical images, has emerged as a promising field in radiology with the potential to revolutionize the diagnosis and management of renal lesions. This comprehensive review explores the ... ...

    Abstract Radiomics, the extraction and analysis of quantitative features from medical images, has emerged as a promising field in radiology with the potential to revolutionize the diagnosis and management of renal lesions. This comprehensive review explores the radiomics workflow, including image acquisition, feature extraction, selection, and classification, and highlights its application in differentiating between benign and malignant renal lesions. The integration of radiomics with artificial intelligence (AI) techniques, such as machine learning and deep learning, can help patients' management and allow the planning of the appropriate treatments. AI models have shown remarkable accuracy in predicting tumor aggressiveness, treatment response, and patient outcomes. This review provides insights into the current state of radiomics and AI in renal lesion assessment and outlines future directions for research in this rapidly evolving field.
    MeSH term(s) Humans ; Artificial Intelligence ; Radiomics ; Machine Learning ; Neoplasms ; Forecasting
    Language English
    Publishing date 2024-03-05
    Publishing country United States
    Document type Review ; Journal Article
    ZDB-ID 1036388-9
    ISSN 0893-9675
    ISSN 0893-9675
    DOI 10.1615/CritRevOncog.2023051084
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2587: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  8. Article: Correlation Analysis on Anatomical Variants of Accessory Foramina in the Sphenoid Bone for Oncological Surgery.

    Palamenghi, Andrea / Cellina, Michaela / Cè, Maurizio / Cappella, Annalisa / Sforza, Chiarella / Gibelli, Daniele

    Cancers

    2023  Volume 15, Issue 22

    Abstract: The sphenoid bone presents several anatomical variations, including accessory foramina, such as the foramen meningo-orbitale, the foramen of Vesalius, the canaliculus innominatus and the palatovaginal canal, which may be involved in tumor invasion or ... ...

    Abstract The sphenoid bone presents several anatomical variations, including accessory foramina, such as the foramen meningo-orbitale, the foramen of Vesalius, the canaliculus innominatus and the palatovaginal canal, which may be involved in tumor invasion or surgery of surrounding structures. Therefore, clinicians and surgeons have to consider these variants when planning surgical interventions of the cranial base. The prevalence of each variant is reported in the published literature, but very little information is available on the possible correlation among different variants. Here, 300 CT scans of patients (equally divided among males and females) were retrospectively assessed to investigate the presence of the foramen meningo-orbitale, the foramen of Vesalius, the canaliculus innominatus and the palatovaginal canal. Possible differences in the prevalence of each accessory foramen according to sex were assessed, as well as possible correlations among different variants through the Chi-square test (
    Language English
    Publishing date 2023-11-09
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2527080-1
    ISSN 2072-6694
    ISSN 2072-6694
    DOI 10.3390/cancers15225341
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Portable Dynamic Chest Radiography: Literature Review and Potential Bedside Applications.

    Cè, Maurizio / Oliva, Giancarlo / Rabaiotti, Francesca Lucrezia / Macrì, Laura / Zollo, Sharon / Aquila, Alessandro / Cellina, Michaela

    Medical sciences (Basel, Switzerland)

    2024  Volume 12, Issue 1

    Abstract: Dynamic digital radiography (DDR) is a high-resolution radiographic imaging technique using pulsed X-ray emission to acquire a multiframe cine-loop of the target anatomical area. The first DDR technology was orthostatic chest acquisitions, but new ... ...

    Abstract Dynamic digital radiography (DDR) is a high-resolution radiographic imaging technique using pulsed X-ray emission to acquire a multiframe cine-loop of the target anatomical area. The first DDR technology was orthostatic chest acquisitions, but new portable equipment that can be positioned at the patient's bedside was recently released, significantly expanding its potential applications, particularly in chest examination. It provides anatomical and functional information on the motion of different anatomical structures, such as the lungs, pleura, rib cage, and trachea. Native images can be further analyzed with dedicated post-processing software to extract quantitative parameters, including diaphragm motility, automatically projected lung area and area changing rate, a colorimetric map of the signal value change related to respiration and motility, and lung perfusion. The dynamic diagnostic information along with the significant advantages of this technique in terms of portability, versatility, and cost-effectiveness represents a potential game changer for radiological diagnosis and monitoring at the patient's bedside. DDR has several applications in daily clinical practice, and in this narrative review, we will focus on chest imaging, which is the main application explored to date in the literature. However, studies are still needed to understand deeply the clinical impact of this method.
    MeSH term(s) Humans ; Radiography, Thoracic/methods ; Radiography ; Thorax/diagnostic imaging ; Diaphragm ; Lung
    Language English
    Publishing date 2024-02-07
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2754473-4
    ISSN 2076-3271 ; 2076-3271
    ISSN (online) 2076-3271
    ISSN 2076-3271
    DOI 10.3390/medsci12010010
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: The Role of Artificial Intelligence and Texture Analysis in Interventional Radiological Treatments of Liver Masses: A Narrative Review.

    Triggiani, Sonia / Contaldo, Maria T / Mastellone, Giulia / Cè, Maurizio / Ierardi, Anna M / Carrafiello, Gianpaolo / Cellina, Michaela

    Critical reviews in oncogenesis

    2024  Volume 29, Issue 2, Page(s) 37–52

    Abstract: Liver lesions, including both benign and malignant tumors, pose significant challenges in interventional radiological treatment planning and prognostication. The emerging field of artificial intelligence (AI) and its integration with texture analysis ... ...

    Abstract Liver lesions, including both benign and malignant tumors, pose significant challenges in interventional radiological treatment planning and prognostication. The emerging field of artificial intelligence (AI) and its integration with texture analysis techniques have shown promising potential in predicting treatment outcomes, enhancing precision, and aiding clinical decision-making. This comprehensive review aims to summarize the current state-of-the-art research on the application of AI and texture analysis in determining treatment response, recurrence rates, and overall survival outcomes for patients undergoing interventional radiological treatment for liver lesions. Furthermore, the review addresses the challenges associated with the implementation of AI and texture analysis in clinical practice, including data acquisition, standardization of imaging protocols, and model validation. Future directions and potential advancements in this field are discussed. Integration of multi-modal imaging data, incorporation of genomics and clinical data, and the development of predictive models with enhanced interpretability are proposed as potential avenues for further research. In conclusion, the application of AI and texture analysis in predicting outcomes of interventional radiological treatment for liver lesions shows great promise in augmenting clinical decision-making and improving patient care. By leveraging these technologies, clinicians can potentially enhance treatment planning, optimize intervention strategies, and ultimately improve patient outcomes in the management of liver lesions.
    MeSH term(s) Humans ; Artificial Intelligence ; Genomics ; Liver Neoplasms/diagnostic imaging ; Liver Neoplasms/therapy
    Language English
    Publishing date 2024-03-05
    Publishing country United States
    Document type Review ; Journal Article
    ZDB-ID 1036388-9
    ISSN 0893-9675
    ISSN 0893-9675
    DOI 10.1615/CritRevOncog.2023049855
    Database MEDical Literature Analysis and Retrieval System OnLINE

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