288 results on '"Zaccagna, A."'
Search Results
2. Multiparametric MRI dataset for susceptibility-based radiomic feature extraction and analysis
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Cristiana Fiscone, Giovanni Sighinolfi, David Neil Manners, Lorenzo Motta, Greta Venturi, Ivan Panzera, Fulvio Zaccagna, Leonardo Rundo, Alessandra Lugaresi, Raffaele Lodi, Caterina Tonon, and Mauro Castelli
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Science - Abstract
Abstract Multiple sclerosis (MS) is a progressive demyelinating disease impacting the central nervous system. Conventional Magnetic Resonance Imaging (MRI) techniques (e.g., T2w images) help diagnose MS, although they sometimes reveal non-specific lesions. Quantitative MRI techniques are capable of quantifying imaging biomarkers in vivo, offering the potential to identify specific signs related to pre-clinical inflammation. Among those techniques, Quantitative Susceptibility Mapping (QSM) is particularly useful for studying processes that influence the magnetic properties of brain tissue, such as alterations in myelin concentration. Because of its intrinsic quantitative nature, it is particularly well-suited to be analyzed through radiomics, including techniques that extract a high number of complex and multi-dimensional features from radiological images. The dataset presented in this work provides information about normal-appearing white matter (NAWM) in a cohort of MS patients and healthy controls. It includes QSM-based radiomic features from NAWM and its tracts, and MR sequences necessary to implement the pipeline: T1w, T2w, QSM, DWI. The workflow is outlined in this article, along with an application showing feature reliability assessment.
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- 2024
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3. Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis
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Fiscone, Cristiana, Rundo, Leonardo, Lugaresi, Alessandra, Manners, David Neil, Allinson, Kieren, Baldin, Elisa, Vornetti, Gianfranco, Lodi, Raffaele, Tonon, Caterina, Testa, Claudia, Castelli, Mauro, and Zaccagna, Fulvio
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- 2023
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4. Microstructural changes precede depression in patients with relapsing-remitting Multiple Sclerosis
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Riemer, Frank, Skorve, Ellen, Pasternak, Ofer, Zaccagna, Fulvio, Lundervold, Astri J., Torkildsen, Øivind, Myhr, Kjell-Morten, and Grüner, Renate
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- 2023
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5. Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis
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Cristiana Fiscone, Leonardo Rundo, Alessandra Lugaresi, David Neil Manners, Kieren Allinson, Elisa Baldin, Gianfranco Vornetti, Raffaele Lodi, Caterina Tonon, Claudia Testa, Mauro Castelli, and Fulvio Zaccagna
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Medicine ,Science - Abstract
Abstract Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility Mapping (QSM), an advanced Magnetic Resonance Imaging technique detecting magnetic properties. When analysed with radiomic techniques that exploit its intrinsic quantitative nature, QSM may furnish biomarkers to facilitate early diagnosis of MS and timely assessment of progression. In this work, we explore the robustness of QSM radiomic features by varying the number of grey levels (GLs) and echo times (TEs), in a sample of healthy controls and patients with MS. We analysed the white matter in total and within six clinically relevant tracts, including the cortico-spinal tract and the optic radiation. After optimising the number of GLs (n = 64), at least 65% of features were robust for each Volume of Interest (VOI), with no difference (p > .05) between left and right hemispheres. Different outcomes in feature robustness among the VOIs depend on their characteristics, such as volume and variance of susceptibility values. This study validated the processing pipeline for robustness analysis and established the reliability of QSM-based radiomics features against GLs and TEs. Our results provide important insights for future radiomics studies using QSM in clinical applications.
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- 2023
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6. IMPA-Net: Interpretable Multi-Part Attention Network for Trustworthy Brain Tumor Classification from MRI
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Yuting Xie, Fulvio Zaccagna, Leonardo Rundo, Claudia Testa, Ruifeng Zhu, Caterina Tonon, Raffaele Lodi, and David Neil Manners
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decision support ,interpretability ,trustworthiness ,deep neural networks ,brain tumor classification ,multi-part attention ,Medicine (General) ,R5-920 - Abstract
Deep learning (DL) networks have shown attractive performance in medical image processing tasks such as brain tumor classification. However, they are often criticized as mysterious “black boxes”. The opaqueness of the model and the reasoning process make it difficult for health workers to decide whether to trust the prediction outcomes. In this study, we develop an interpretable multi-part attention network (IMPA-Net) for brain tumor classification to enhance the interpretability and trustworthiness of classification outcomes. The proposed model not only predicts the tumor grade but also provides a global explanation for the model interpretability and a local explanation as justification for the proffered prediction. Global explanation is represented as a group of feature patterns that the model learns to distinguish high-grade glioma (HGG) and low-grade glioma (LGG) classes. Local explanation interprets the reasoning process of an individual prediction by calculating the similarity between the prototypical parts of the image and a group of pre-learned task-related features. Experiments conducted on the BraTS2017 dataset demonstrate that IMPA-Net is a verifiable model for the classification task. A percentage of 86% of feature patterns were assessed by two radiologists to be valid for representing task-relevant medical features. The model shows a classification accuracy of 92.12%, of which 81.17% were evaluated as trustworthy based on local explanations. Our interpretable model is a trustworthy model that can be used for decision aids for glioma classification. Compared with black-box CNNs, it allows health workers and patients to understand the reasoning process and trust the prediction outcomes.
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- 2024
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7. Microstructural changes precede depression in patients with relapsing-remitting Multiple Sclerosis
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Frank Riemer, Ellen Skorve, Ofer Pasternak, Fulvio Zaccagna, Astri J. Lundervold, Øivind Torkildsen, Kjell-Morten Myhr, and Renate Grüner
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Medicine - Abstract
Abstract Background Multiple Sclerosis lesions in the brain and spinal cord can lead to different symptoms, including cognitive and mood changes. In this study we explore the temporal relationship between early microstructural changes in subcortical volumes and cognitive and emotional function in a longitudinal cohort study of patients with relapsing-remitting Multiple Sclerosis. Methods In vivo imaging in forty-six patients with relapsing-remitting Multiple Sclerosis was performed annually over 3 years magnetic resonance imaging. Microstructural changes were estimated in subcortical structures using the free water fraction, a diffusion-based MRI metric. In parallel, patients were assessed with the Hospital Anxiety and Depression Scale amongst other tests. Predictive structural equation modeling was set up to further explore the relationship between imaging and the assessment scores. In a general linear model analysis, the cohort was split into patients with higher and lower depression scores. Results Nearly all subcortical diffusion microstructure estimates at the baseline visit correlate with the depression score at the 2 years follow-up. The predictive nature of baseline free water estimates and depression subscores after 2 years are confirmed in the predictive structural equation modeling analysis with the thalamus showing the greatest effect size. The general linear model analysis shows patterns of MRI free water differences in the thalamus and amygdala/hippocampus area between participants with high and low depression score. Conclusions Our data suggests a relationship between higher levels of free-water in the subcortical structures in an early stage of Multiple Sclerosis and depression symptoms at a later stage of the disease.
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- 2023
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8. Novel approaches to MRI of glioma
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Zaccagna, Fulvio, Gallagher, Ferdia, and Price, stephen
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616.99 ,Magnetic Resonance Imaging ,MRI ,Diffusion Weighted Imaging ,DWI ,VERDICT ,model-based diffusion ,Sodium Imaging ,Sodium MRI ,23Na ,Metabolic imaging ,Hyperpolarized MRI ,Hyperpolarized Carbon-13 MRI ,Hyperpolarized pyruvate ,13C ,Glioma ,Glioblastoma ,Cancer - Abstract
Gliomas are extremely heterogeneous, both morphologically and biologically, which contributes to a very poor prognosis. Current imaging of glioma is insufficient for a thorough diagnosis, therapy assessment and prognosis prediction. Moreover, refined and more sophisticated imaging technique could help in furthering our knowledge of gliomas. In order to facilitate proliferation, cancer cells undergo a change in structure and an increase in metabolism that results in distortion and disruption of tissue architecture. Gliomas are characterised by an increase in cells of variable sizes, as well as changes in the tissue microstructure. Diffusion-Weighted Imaging (DWI) and the apparent diffusion coefficient (ADC), have been extensively studied as potential imaging biomarkers for cellularity and tissue architecture. However, several studies have shown partial overlap in the measured values between tumour subtypes. Moreover, ADC is influenced by several factors and does not provide detailed information on the tissue microstructure. The Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT) is a novel diffusion model that infers tissue microstructure compartment from conventional DWI measurements. This model derives metrics for the intracellular, intravascular and extracellular– extravascular spaces providing a more detailed interpretation of the tissue microstructure. To date, VERDICT has been applied to xenograft models of colorectal cancer, patient studies of prostate cancer and recently its feasibility in glioma has been shown. In this PhD I have applied a shortened version of the VERDICT method to image intratumoral and intertumoral heterogeneity in glioma. The results have also been validated with histology as part of a prospective study. Gliomas also exhibit a significant increase in mitotic activity within the tumour. The increased number of mitosis alters cell density which, in turn, affects the total concentration of tissue sodium as the concentration of tissue sodium is approximately ten-fold higher in the extracellular compared to the intracellular space. In addition, there is a decrease in Na+/K+-ATPase activity in tumours due to ATP depletion, which contributes to disturb sodium homeostasis. Non-invasive detection of 23Na with MRI has the potential to quantify sodium concentration and therefore could be an imaging probe of cell morphology and membrane function within the tumour microenvironment, as well as a method of probing tissue heterogeneity. During my PhD, a novel 23Na-MRI technique has been used to evaluate sodium distribution within glioma and in the surrounding tissue. Metabolic reprogramming is one of the major driving forces for determining glioma growth and invasion. Therefore, the non-invasive characterization of metabolic intratumoral, peritumoral and intertumoral heterogeneity in vivo could help to better stratify patients and to develop novel therapeutic strategies targeting cancer-specific metabolic pathways. 13C magnetic resonance imaging (MRI) using dynamic nuclear polarization (DNP) is a novel technique that allows non-invasive assessment of the metabolism of hyperpolarized (HP) 13C-labelled molecules in vivo, such as the exchange of [1-13C]pyruvate to [1-13C]lactate in tumours (Warburg effect). Part of my PhD has focused on developing and translating HP [1-13C]pyruvate MRI to explore metabolic reprogramming in glioma and the surrounding microenvironment. The overall aim of my PhD has been to develop novel approaches to imaging glioma with MRI to probe both the architectural and metabolic changes of Glioma. The preliminary evidence suggests that these tools can more deeply phenotype tumours than conventional imaging approaches. Although the main focus of this work has been gliomas, the techniques developed and presented here may be applied to study other pathological conditions within the brain, which raises the possibility of other potential clinical applications for this work.
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- 2019
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9. IMPA-Net: Interpretable Multi-Part Attention Network for Trustworthy Brain Tumor Classification from MRI
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Xie, Yuting, primary, Zaccagna, Fulvio, additional, Rundo, Leonardo, additional, Testa, Claudia, additional, Zhu, Ruifeng, additional, Tonon, Caterina, additional, Lodi, Raffaele, additional, and Manners, David Neil, additional
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- 2024
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10. Imaging breast cancer using hyperpolarized carbon-13 MRI
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Gallagher, Ferdia A., Woitek, Ramona, McLean, Mary A., Gill, Andrew B., Garcia, Raquel Manzano, Provenzano, Elena, Riemer, Frank, Kaggie, Joshua, Chhabra, Anita, Ursprung, Stephan, Grist, James T., Daniels, Charlie J., Zaccagna, Fulvio, Laurent, Marie-Christine, Locke, Matthew, Hilborne, Sarah, Frary, Amy, Torheim, Turid, Boursnell, Chris, Schiller, Amy, Patterson, Ilse, Slough, Rhys, Carmo, Bruno, Kane, Justine, Biggs, Heather, Harrison, Emma, Deen, Surrin S., Patterson, Andrew, Lanz, Titus, Kingsbury, Zoya, Ross, Mark, Basu, Bristi, Baird, Richard, Lomas, David J., Sala, Evis, Wason, James, Rueda, Oscar M., Chin, Suet-Feung, Wilkinson, Ian B., Graves, Martin J., Abraham, Jean E., Gilbert, Fiona J., Caldas, Carlos, and Brindle, Kevin M.
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- 2020
11. High BRAF variant allele frequencies are associated with distinct pathological features and responsiveness to target therapy in melanoma patients
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Berrino, E., Balsamo, A., Pisacane, A., Gallo, S., Becco, P., Miglio, U., Caravelli, D., Poletto, S., Paruzzo, L., Debernardi, C., Piccinelli, C., Zaccagna, A., Rescigno, P., Aglietta, M., Sapino, A., Carnevale-Schianca, F., and Venesio, T.
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- 2021
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12. Investigating the relationship between diffusion kurtosis tensor imaging (DKTI) and histology within the normal human brain
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Ahmed Maiter, Frank Riemer, Kieren Allinson, Fulvio Zaccagna, Mireia Crispin-Ortuzar, Marcel Gehrung, Mary A. McLean, Andrew N. Priest, James Grist, Tomasz Matys, Martin J. Graves, and Ferdia A. Gallagher
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Medicine ,Science - Abstract
Abstract Measurements of water diffusion with MRI have been used as a biomarker of tissue microstructure and heterogeneity. In this study, diffusion kurtosis tensor imaging (DKTI) of the brain was undertaken in 10 healthy volunteers at a clinical field strength of 3 T. Diffusion and kurtosis metrics were measured in regions-of-interest on the resulting maps and compared with quantitative analysis of normal post-mortem tissue histology from separate age-matched donors. White matter regions showed low diffusion (0.60 ± 0.04 × 10–3 mm2/s) and high kurtosis (1.17 ± 0.06), consistent with a structured heterogeneous environment comprising parallel neuronal fibres. Grey matter showed intermediate diffusion (0.80 ± 0.02 × 10–3 mm2/s) and kurtosis (0.82 ± 0.05) values. An important finding is that the subcortical regions investigated (thalamus, caudate and putamen) showed similar diffusion and kurtosis properties to white matter. Histological staining of the subcortical nuclei demonstrated that the predominant grey matter was permeated by small white matter bundles, which could account for the similar kurtosis to white matter. Quantitative histological analysis demonstrated higher mean tissue kurtosis and vector standard deviation values for white matter (1.08 and 0.81) compared to the subcortical regions (0.34 and 0.59). Mean diffusion on DKTI was positively correlated with tissue kurtosis (r = 0.82, p
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- 2021
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13. Neuroplasticity Mechanisms in Frontal Brain Gliomas: A Preliminary Study
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Micaela Mitolo, Matteo Zoli, Claudia Testa, Luca Morandi, Magali Jane Rochat, Fulvio Zaccagna, Matteo Martinoni, Francesca Santoro, Sofia Asioli, Filippo Badaloni, Alfredo Conti, Carmelo Sturiale, Raffaele Lodi, Diego Mazzatenta, and Caterina Tonon
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frontal gliomas ,neurosurgery ,neuroplasticity ,task fMRI ,arcuate fasciculus (AF) ,frontal aslant tract ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
BackgroundPathological brain processes may induce adaptive cortical reorganization, however, the mechanisms underlying neuroplasticity that occurs in the presence of lesions in eloquent areas are not fully explained. The aim of this study was to evaluate functional compensatory cortical activations in patients with frontal brain gliomas during a phonemic fluency task and to explore correlations with cognitive performance, white matter tracts microstructural alterations, and tumor histopathological and molecular characterization.MethodsFifteen patients with frontal glioma were preoperatively investigated with an MRI study on a 3T scanner and a subgroup underwent an extensive neuropsychological assessment. The hemispheric laterality index (LI) was calculated through phonemic fluency task functional MRI (fMRI) activations in the frontal, parietal, and temporal lobe parcellations. Diffusion-weighted images were acquired for all patients and for a group of 24 matched healthy volunteers. Arcuate Fasciculus (AF) and Frontal Aslant Tract (FAT) tractography was performed using constrained spherical deconvolution diffusivity modeling and probabilistic fiber tracking. All patients were operated on with a resective aim and underwent adjuvant therapies, depending on the final diagnosis.ResultsAll patients during the phonemic fluency task fMRI showed left hemispheric dominance in temporal and parietal regions. Regarding frontal regions (i.e., frontal operculum) we found right hemispheric dominance that increases when considering only those patients with tumors located on the left side. These latter activations positively correlate with verbal and visuo-spatial short-term memory, and executive functions. No correlations were found between the left frontal operculum and cognitive performance. Furthermore, patients with IDH-1 mutation and without TERT mutation, showed higher rightward frontal operculum fMRI activations and better cognitive performance in tests measuring general cognitive abilities, semantic fluency, verbal short-term memory, and executive functions. As for white matter tracts, we found left and right AF and FAT microstructural alterations in patients with, respectively, left-sided and right-side glioma compared to controls.ConclusionsCompensatory cortical activation of the corresponding region in the non-dominant hemisphere and its association with better cognitive performance and more favorable histopathological and molecular tumor characteristics shed light on the neuroplasticity mechanisms that occur in the presence of a tumor, helping to predict the rate of post-operative deficit, with the final goal of improving patients'quality of life.
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- 2022
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14. Assessing robustness of carotid artery CT angiography radiomics in the identification of culprit lesions in cerebrovascular events
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Elizabeth P. V. Le, Leonardo Rundo, Jason M. Tarkin, Nicholas R. Evans, Mohammed M. Chowdhury, Patrick A. Coughlin, Holly Pavey, Chris Wall, Fulvio Zaccagna, Ferdia A. Gallagher, Yuan Huang, Rouchelle Sriranjan, Anthony Le, Jonathan R. Weir-McCall, Michael Roberts, Fiona J. Gilbert, Elizabeth A. Warburton, Carola-Bibiane Schönlieb, Evis Sala, and James H. F. Rudd
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Medicine ,Science - Abstract
Abstract Radiomics, quantitative feature extraction from radiological images, can improve disease diagnosis and prognostication. However, radiomic features are susceptible to image acquisition and segmentation variability. Ideally, only features robust to these variations would be incorporated into predictive models, for good generalisability. We extracted 93 radiomic features from carotid artery computed tomography angiograms of 41 patients with cerebrovascular events. We tested feature robustness to region-of-interest perturbations, image pre-processing settings and quantisation methods using both single- and multi-slice approaches. We assessed the ability of the most robust features to identify culprit and non-culprit arteries using several machine learning algorithms and report the average area under the curve (AUC) from five-fold cross validation. Multi-slice features were superior to single for producing robust radiomic features (67 vs. 61). The optimal image quantisation method used bin widths of 25 or 30. Incorporating our top 10 non-redundant robust radiomics features into ElasticNet achieved an AUC of 0.73 and accuracy of 69% (compared to carotid calcification alone [AUC: 0.44, accuracy: 46%]). Our results provide key information for introducing carotid CT radiomics into clinical practice. If validated prospectively, our robust carotid radiomic set could improve stroke prediction and target therapies to those at highest risk.
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- 2021
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15. Video-assisted thoracoscopic sympathectomy versus modified Wittmoser method in surgical management of primary hyperhidrosis
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Duilio Divisi, Gino Zaccagna, Giovanna Imbriglio, William Di Francescantonio, Andrea De Vico, Mirko Barone, and Roberto Crisci
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Hyperhidrosis ,Sympathectomy ,Sympathicotomy ,Video-assisted thoracic surgery ,Surgery ,RD1-811 ,Anesthesiology ,RD78.3-87.3 - Abstract
Abstract Purposes We compared two different surgical methods evaluating the effectiveness of procedures and the quality of life (QoL) of patients. Methods From January 2010 to November 2017 we carried out 476 biportal video-assisted thoracoscopic surgery (VATS) approaches of sympathetic chain in 238 patients. One hundred and twenty-nine (54%) patients underwent conventional sympathectomy (CS) while 109 (46%) patients underwent sympathicotomy associated with the division of the rami communicantes (MWT). Quality of Life (QoL) was classified as follows: from 20 to 35 excellent; from 36 to 51 very good; from 52 to 68 good; from 69 to 84 poor; and > 84 very poor. Results We noticed statistical significant reduction of complications comparing CS with MWT approaches (chest pain from 36.4 to 4.5%; paresthesias from 8.5 to 3.6%; bradycardia from 28.6 to 10%, respectively). The preoperative and postoperative QoL index evaluation revealed a statistically significant improvement after surgery (CS: 86 ± 2 versus 35 ± 1, p = 0.00001; MWT: 85 ± 1 versus 33 ± 2, p = 0.00001), with general satisfaction of the two techniques. Conclusion Modified Wittmoser method seems to be a valid alternative to conventional sympathectomy, minimizing the percentage rate of complications and showing significant effectiveness in the quality of life improvement.
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- 2020
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16. Assessing robustness of carotid artery CT angiography radiomics in the identification of culprit lesions in cerebrovascular events
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Le, Elizabeth P. V., Rundo, Leonardo, Tarkin, Jason M., Evans, Nicholas R., Chowdhury, Mohammed M., Coughlin, Patrick A., Pavey, Holly, Wall, Chris, Zaccagna, Fulvio, Gallagher, Ferdia A., Huang, Yuan, Sriranjan, Rouchelle, Le, Anthony, Weir-McCall, Jonathan R., Roberts, Michael, Gilbert, Fiona J., Warburton, Elizabeth A., Schönlieb, Carola-Bibiane, Sala, Evis, and Rudd, James H. F.
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- 2021
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17. Investigating the relationship between diffusion kurtosis tensor imaging (DKTI) and histology within the normal human brain
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Maiter, Ahmed, Riemer, Frank, Allinson, Kieren, Zaccagna, Fulvio, Crispin-Ortuzar, Mireia, Gehrung, Marcel, McLean, Mary A., Priest, Andrew N., Grist, James, Matys, Tomasz, Graves, Martin J., and Gallagher, Ferdia A.
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- 2021
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18. Case Report: A New Tool for Anterior Chest Wall Reconstruction After Sternal Resection for Primary Or Secondary Tumors
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Duilio Divisi, Davide Tosi, Gino Zaccagna, Andrea De Vico, Cristina Diotti, and Roberto Crisci
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thymoma ,Ewing's sarcoma ,sternectomy ,sternal resection and reconstruction ,titanium mesh ,Surgery ,RD1-811 - Abstract
Sternal resection and anterior chest wall reconstruction techniques for malignant processes are not always standardized. We report an innovative method of sternal osteosynthesis in two patients, 65-year-old and 41-year-old women, with Ewing's sarcoma, and infiltrating thymoma, respectively. The first case manifested itself as a voluminous palpable mass while the second case was characterized for a paramediastinal mass widely extended to the anterior chest wall. Reconstruction with titanium mesh allowed the quick restoration of parietal stability, facilitating respiratory dynamic and recovery of patients.
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- 2021
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19. Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI
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Christian di Noia, James T. Grist, Frank Riemer, Maria Lyasheva, Miriana Fabozzi, Mauro Castelli, Raffaele Lodi, Caterina Tonon, Leonardo Rundo, and Fulvio Zaccagna
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brain tumors ,artificial intelligence ,machine learning ,survival prediction ,magnetic resonance imaging ,Medicine (General) ,R5-920 - Abstract
Given growing clinical needs, in recent years Artificial Intelligence (AI) techniques have increasingly been used to define the best approaches for survival assessment and prediction in patients with brain tumors. Advances in computational resources, and the collection of (mainly) public databases, have promoted this rapid development. This narrative review of the current state-of-the-art aimed to survey current applications of AI in predicting survival in patients with brain tumors, with a focus on Magnetic Resonance Imaging (MRI). An extensive search was performed on PubMed and Google Scholar using a Boolean research query based on MeSH terms and restricting the search to the period between 2012 and 2022. Fifty studies were selected, mainly based on Machine Learning (ML), Deep Learning (DL), radiomics-based methods, and methods that exploit traditional imaging techniques for survival assessment. In addition, we focused on two distinct tasks related to survival assessment: the first on the classification of subjects into survival classes (short and long-term or eventually short, mid and long-term) to stratify patients in distinct groups. The second focused on quantification, in days or months, of the individual survival interval. Our survey showed excellent state-of-the-art methods for the first, with accuracy up to ∼98%. The latter task appears to be the most challenging, but state-of-the-art techniques showed promising results, albeit with limitations, with C-Index up to ∼0.91. In conclusion, according to the specific task, the available computational methods perform differently, and the choice of the best one to use is non-univocal and dependent on many aspects. Unequivocally, the use of features derived from quantitative imaging has been shown to be advantageous for AI applications, including survival prediction. This evidence from the literature motivates further research in the field of AI-powered methods for survival prediction in patients with brain tumors, in particular, using the wealth of information provided by quantitative MRI techniques.
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- 2022
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20. Convolutional Neural Network Techniques for Brain Tumor Classification (from 2015 to 2022): Review, Challenges, and Future Perspectives
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Yuting Xie, Fulvio Zaccagna, Leonardo Rundo, Claudia Testa, Raffaele Agati, Raffaele Lodi, David Neil Manners, and Caterina Tonon
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deep learning ,convolutional neural network ,brain tumor classification ,magnetic resonance imaging ,clinical application ,clinical effectiveness ,Medicine (General) ,R5-920 - Abstract
Convolutional neural networks (CNNs) constitute a widely used deep learning approach that has frequently been applied to the problem of brain tumor diagnosis. Such techniques still face some critical challenges in moving towards clinic application. The main objective of this work is to present a comprehensive review of studies using CNN architectures to classify brain tumors using MR images with the aim of identifying useful strategies for and possible impediments in the development of this technology. Relevant articles were identified using a predefined, systematic procedure. For each article, data were extracted regarding training data, target problems, the network architecture, validation methods, and the reported quantitative performance criteria. The clinical relevance of the studies was then evaluated to identify limitations by considering the merits of convolutional neural networks and the remaining challenges that need to be solved to promote the clinical application and development of CNN algorithms. Finally, possible directions for future research are discussed for researchers in the biomedical and machine learning communities. A total of 83 studies were identified and reviewed. They differed in terms of the precise classification problem targeted and the strategies used to construct and train the chosen CNN. Consequently, the reported performance varied widely, with accuracies of 91.63–100% in differentiating meningiomas, gliomas, and pituitary tumors (26 articles) and of 60.0–99.46% in distinguishing low-grade from high-grade gliomas (13 articles). The review provides a survey of the state of the art in CNN-based deep learning methods for brain tumor classification. Many networks demonstrated good performance, and it is not evident that any specific methodological choice greatly outperforms the alternatives, especially given the inconsistencies in the reporting of validation methods, performance metrics, and training data encountered. Few studies have focused on clinical usability.
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- 2022
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21. Brain Tumor Diagnosis Using Machine Learning, Convolutional Neural Networks, Capsule Neural Networks and Vision Transformers, Applied to MRI: A Survey
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Andronicus A. Akinyelu, Fulvio Zaccagna, James T. Grist, Mauro Castelli, and Leonardo Rundo
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brain cancer ,magnetic resonance imaging ,machine learning ,deep learning ,capsule neural networks ,vision transformers ,Photography ,TR1-1050 ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Management of brain tumors is based on clinical and radiological information with presumed grade dictating treatment. Hence, a non-invasive assessment of tumor grade is of paramount importance to choose the best treatment plan. Convolutional Neural Networks (CNNs) represent one of the effective Deep Learning (DL)-based techniques that have been used for brain tumor diagnosis. However, they are unable to handle input modifications effectively. Capsule neural networks (CapsNets) are a novel type of machine learning (ML) architecture that was recently developed to address the drawbacks of CNNs. CapsNets are resistant to rotations and affine translations, which is beneficial when processing medical imaging datasets. Moreover, Vision Transformers (ViT)-based solutions have been very recently proposed to address the issue of long-range dependency in CNNs. This survey provides a comprehensive overview of brain tumor classification and segmentation techniques, with a focus on ML-based, CNN-based, CapsNet-based, and ViT-based techniques. The survey highlights the fundamental contributions of recent studies and the performance of state-of-the-art techniques. Moreover, we present an in-depth discussion of crucial issues and open challenges. We also identify some key limitations and promising future research directions. We envisage that this survey shall serve as a good springboard for further study.
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- 2022
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22. Pleural empyema associated with alveolar‐pleural fistulas in severe acute respiratory syndrome coronavirus 2
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Duilio Divisi, Gino Zaccagna, Chiara Angeletti, Elena Cicerone, Andrea De Vico, Riccardo Moretti, Giovanna Imbriglio, Nadia Carbuglia, Gina Rosaria Quaglione, Sofia Chiatamone Ranieri, and Roberto Crisci
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alveolar‐pleural fistula ,COVID‐19 infection ,empyema ,prolonged air leaks ,surgical treatment ,Medicine ,Medicine (General) ,R5-920 - Abstract
Abstract Surgery in COVID‐19 disease complicated by APF represents the last life‐saving treatment option. The choice of the therapeutic period to indicate this approach is fundamental. In fact, the clinical stability of patient is necessary in order to allow single‐lung ventilation and to minimize postoperative sequelae.
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- 2021
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23. Multiparametric MRI for assessment of early response to neoadjuvant sunitinib in renal cell carcinoma
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Stephan Ursprung, Andrew N. Priest, Fulvio Zaccagna, Wendi Qian, Andrea Machin, Grant D. Stewart, Anne Y. Warren, Timothy Eisen, Sarah J. Welsh, Ferdia A. Gallagher, and Tristan Barrett
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Medicine ,Science - Abstract
Purpose To detect early response to sunitinib treatment in metastatic clear cell renal cancer (mRCC) using multiparametric MRI. Method Participants with mRCC undergoing pre-surgical sunitinib therapy in the prospective NeoSun clinical trial (EudraCtNo: 2005-004502-82) were imaged before starting treatment, and after 12 days of sunitinib therapy using morphological MRI sequences, advanced diffusion-weighted imaging, measurements of R2* (related to hypoxia) and dynamic contrast-enhanced imaging. Following nephrectomy, participants continued treatment and were followed-up with contrast-enhanced CT. Changes in imaging parameters before and after sunitinib were assessed with the non-parametric Wilcoxon signed-rank test and the log-rank test was used to assess effects on survival. Results 12 participants fulfilled the inclusion criteria. After 12 days, the solid and necrotic tumor volumes decreased by 28% and 17%, respectively (p = 0.04). However, tumor-volume reduction did not correlate with progression-free or overall survival (PFS/OS). Sunitinib therapy resulted in a reduction in median solid tumor diffusivity D from 1298x10-6 to 1200x10-6mm2/s (p = 0.03); a larger decrease was associated with a better RECIST response (p = 0.02) and longer PFS (p = 0.03) on the log-rank test. An increase in R2* from 19 to 28s-1 (p = 0.001) was observed, paralleled by a decrease in Ktrans from 0.415 to 0.305min-1 (p = 0.01) and a decrease in perfusion fraction from 0.34 to 0.19 (pConclusions Physiological imaging confirmed efficacy of the anti-angiogenic agent 12 days after initiating therapy and demonstrated response to treatment. The change in diffusivity shortly after starting pre-surgical sunitinib correlated to PFS in mRCC undergoing nephrectomy, however, no parameter predicted OS. Trial registration EudraCtNo: 2005-004502-82.
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- 2021
24. Hyperpolarized 13C-Pyruvate Metabolism as a Surrogate for Tumor Grade and Poor Outcome in Renal Cell Carcinoma—A Proof of Principle Study
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Stephan Ursprung, Ramona Woitek, Mary A. McLean, Andrew N. Priest, Mireia Crispin-Ortuzar, Cara R. Brodie, Andrew B. Gill, Marcel Gehrung, Lucian Beer, Antony C. P. Riddick, Johanna Field-Rayner, James T. Grist, Surrin S. Deen, Frank Riemer, Joshua D. Kaggie, Fulvio Zaccagna, Joao A. G. Duarte, Matthew J. Locke, Amy Frary, Tevita F. Aho, James N. Armitage, Ruth Casey, Iosif A. Mendichovszky, Sarah J. Welsh, Tristan Barrett, Martin J. Graves, Tim Eisen, Thomas J. Mitchell, Anne Y. Warren, Kevin M. Brindle, Evis Sala, Grant D. Stewart, and Ferdia A. Gallagher
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cancer metabolism ,hyperpolarized 13C magnetic resonance imaging ,monocarboxylate transporter ,renal cell carcinoma ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Differentiating aggressive clear cell renal cell carcinoma (ccRCC) from indolent lesions is challenging using conventional imaging. This work prospectively compared the metabolic imaging phenotype of renal tumors using carbon-13 MRI following injection of hyperpolarized [1-13C]pyruvate (HP-13C-MRI) and validated these findings with histopathology. Nine patients with treatment-naïve renal tumors (6 ccRCCs, 1 liposarcoma, 1 pheochromocytoma, 1 oncocytoma) underwent pre-operative HP-13C-MRI and conventional proton (1H) MRI. Multi-regional tissue samples were collected using patient-specific 3D-printed tumor molds for spatial registration between imaging and molecular analysis. The apparent exchange rate constant (kPL) between 13C-pyruvate and 13C-lactate was calculated. Immunohistochemistry for the pyruvate transporter (MCT1) from 44 multi-regional samples, as well as associations between MCT1 expression and outcome in the TCGA-KIRC dataset, were investigated. Increasing kPL in ccRCC was correlated with increasing overall tumor grade (ρ = 0.92, p = 0.009) and MCT1 expression (r = 0.89, p = 0.016), with similar results acquired from the multi-regional analysis. Conventional 1H-MRI parameters did not discriminate tumor grades. The correlation between MCT1 and ccRCC grade was confirmed within a TCGA dataset (p < 0.001), where MCT1 expression was a predictor of overall and disease-free survival. In conclusion, metabolic imaging using HP-13C-MRI differentiates tumor aggressiveness in ccRCC and correlates with the expression of MCT1, a predictor of survival. HP-13C-MRI may non-invasively characterize metabolic phenotypes within renal cancer.
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- 2022
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25. Effects of Multi-Shell Free Water Correction on Glioma Characterization
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Lea Starck, Fulvio Zaccagna, Ofer Pasternak, Ferdia A. Gallagher, Renate Grüner, and Frank Riemer
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glioma ,free water ,tumor characterization ,Medicine (General) ,R5-920 - Abstract
Diffusion MRI is a useful tool to investigate the microstructure of brain tumors. However, the presence of fast diffusing isotropic signals originating from non-restricted edematous fluids, within and surrounding tumors, may obscure estimation of the underlying tissue characteristics, complicating the radiological interpretation and quantitative evaluation of diffusion MRI. A multi-shell regularized free water (FW) elimination model was therefore applied to separate free water from tissue-related diffusion components from the diffusion MRI of 26 treatment-naïve glioma patients. We then investigated the diagnostic value of the derived measures of FW maps as well as FW-corrected tensor-derived maps of fractional anisotropy (FA). Presumed necrotic tumor regions display greater mean and variance of FW content than other parts of the tumor. On average, the area under the receiver operating characteristic (ROC) for the classification of necrotic and enhancing tumor volumes increased by 5% in corrected data compared to non-corrected data. FW elimination shifts the FA distribution in non-enhancing tumor parts toward higher values and significantly increases its entropy (p ≤ 0.003), whereas skewness is decreased (p ≤ 0.004). Kurtosis is significantly decreased (p < 0.001) in high-grade tumors. In conclusion, eliminating FW contributions improved quantitative estimations of FA, which helps to disentangle the cancer heterogeneity.
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- 2021
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26. Advanced Computational Methods for Oncological Image Analysis
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Leonardo Rundo, Carmelo Militello, Vincenzo Conti, Fulvio Zaccagna, and Changhee Han
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n/a ,Photography ,TR1-1050 ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
The Special Issue “Advanced Computational Methods for Oncological Image Analysis”, published for the Journal of Imaging, covered original research papers about state-of-the-art and novel algorithms and methodologies, as well as applications of computational methods for oncological image analysis, ranging from radiogenomics to deep learning [...]
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- 2021
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27. Is It Possible to Establish a Reliable Correlation between Maximum Standardized Uptake Value of 18-Fluorine Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography and Histological Types of Non-Small Cell Lung Cancer? Analysis of the Italian VATS Group Database
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Duilio Divisi, Marta Rinaldi, Stefano Necozione, Carlo Curcio, Federico Rea, Francesco Zaraca, Andrea De Vico, Gino Zaccagna, Gabriella Di Leonardo, Roberto Crisci, and on behalf of the Italian VATS Group
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NSCLC ,biological framework ,18F-FDG-PET/CT ,SUVmax ,VATS group ,data quality ,Medicine (General) ,R5-920 - Abstract
Background. Although positron emission tomography/computed tomography, often integrated with 2-deoxy-2-[fluorine-18] fluorine-D-glucose (18F-FDG-PET/CT), is fundamental in the assessment of lung cancer, the relationship between metabolic avidity of different histotypes and maximum standardized uptake value (SUVmax) has not yet been thoroughly investigated. The aim of the study is to establish a reliable correlation between Suvmax and histology in non-small cell lung cancer (NSCLC), in order to facilitate patient management. Methods. We retrospectively assessed the data about lung cancer patients entered in the Italian Registry of VATS Group from January 2014 to October 2019, after establishing the eligibility criteria of the study. In total, 8139 patients undergoing VATS lobectomy were enrolled: 3260 females and 4879 males. The relationship between SUVmax and tumor size was also analyzed. Results. The mean values of SUVmax in the most frequent types of lung cancer were as follows: (a) 4.88 ± 3.82 for preinvasive adenocarcinoma; (b) 5.49 ± 4.10 for minimally invasive adenocarcinoma; (c) 5.87 ± 4.18 for invasive adenocarcinoma; and (d) 8.85 ± 6.70 for squamous cell carcinoma. Processing these data, we displayed a statistically difference (p < 0.000001) of FDG avidity between adenocarcinoma and squamous cell carcinoma. Moreover, by classifying patients into five groups based on tumor diameter and after evaluating the SUVmax value for each group, we noted a statistical correlation (p < 0.000001) between size and FDG uptake, also confirmed by the post hoc analysis. Conclusions. There is a correlation between SUVmax, histopathology outcomes and tumor size in NSCLC. Further clinical trials should be performed in order to confirm our data.
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- 2021
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28. Video-assisted thoracoscopic sympathectomy versus modified Wittmoser method in surgical management of primary hyperhidrosis
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Divisi, Duilio, Zaccagna, Gino, Imbriglio, Giovanna, Di Francescantonio, William, De Vico, Andrea, Barone, Mirko, and Crisci, Roberto
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- 2020
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29. Hyperpolarized 13C MRI: A novel approach for probing cerebral metabolism in health and neurological disease
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Grist, James T, Miller, Jack J, Zaccagna, Fulvio, McLean, Mary A, Riemer, Frank, Matys, Tomasz, Tyler, Damian J, Laustsen, Christoffer, Coles, Alasdair J, and Gallagher, Ferdia A
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- 2020
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30. Favourable prognostic role of histological regression in stage III positive sentinel lymph node melanoma patients
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Zugna, D, Senetta, R, Osella-Abate, S, Fierro, M T, Pisacane, A, Zaccagna, A, Sapino, A, Bataille, V, Maurichi, A, Picciotto, F, Cassoni, P, Quaglino, P, and Ribero, S
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- 2018
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31. Hypoperfusion Precedes Tau Deposition in the Entorhinal Cortex: A Retrospective Evaluation of ADNI-2 Data
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Kapadia, Anish, primary, Billimoria, Krish, additional, Desai, Prarthna, additional, Grist, James T., additional, Heyn, Chris, additional, Maralani, Pejman, additional, Symons, Sean, additional, and Zaccagna, Fulvio, additional
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- 2023
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32. Hyperpolarized 13C-Pyruvate Metabolism as a Surrogate for Tumor Grade and Poor Outcome in Renal Cell Carcinoma-A Proof of Principle Study
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Ursprung, Stephan, Woitek, Ramona, McLean, Mary, Priest, Andrew N, Crispin-Ortuzar, Mireia, Brodie, Cara R, Gill, Andrew, Gehrung, Marcel, Beer, Lucian, Riddick, Antony CP, Field-Rayner, Johanna, Grist, James T, Deen, Surrin S, Riemer, Frank, Kaggie, Joshua, Zaccagna, Fulvio, Duarte, Joao AG, Locke, Matthew J, Frary, Amy, Aho, Tevita F, Armitage, James N, Casey, Ruth, Mendichovszky, Iosif A, Welsh, Sarah, Barrett, Tristan, Graves, Martin, Eisen, Tim, Mitchell, Thomas J, Warren, Anne, Brindle, Kevin, Sala, Evis, Stewart, Grant, Gallagher, Ferdia, Ursprung, Stephan [0000-0003-2476-178X], McLean, Mary [0000-0002-3752-0179], Priest, Andrew N [0000-0002-9771-4290], Gill, Andrew [0000-0002-9287-9563], Beer, Lucian [0000-0003-4388-7580], Deen, Surrin S [0000-0002-6206-7337], Riemer, Frank [0000-0002-3805-5221], Kaggie, Joshua [0000-0001-6706-3442], Zaccagna, Fulvio [0000-0001-6838-9532], Frary, Amy [0000-0002-4373-3517], Welsh, Sarah [0000-0001-5690-2677], Barrett, Tristan [0000-0002-1180-1474], Graves, Martin [0000-0003-4327-3052], Eisen, Tim [0000-0001-9663-4873], Warren, Anne [0000-0002-1170-7867], Brindle, Kevin [0000-0003-3883-6287], Sala, Evis [0000-0002-5518-9360], Stewart, Grant [0000-0003-3188-9140], Gallagher, Ferdia [0000-0003-4784-5230], Apollo - University of Cambridge Repository, Ursprung S., Woitek R., McLean M.A., Priest A.N., Crispin-Ortuzar M., Brodie C.R., Gill A.B., Gehrung M., Beer L., Riddick A.C.P., Field-Rayner J., Grist J.T., Deen S.S., Riemer F., Kaggie J.D., Zaccagna F., Duarte J.A.G., Locke M.J., Frary A., Aho T.F., Armitage J.N., Casey R., Mendichovszky I.A., Welsh S.J., Barrett T., Graves M.J., Eisen T., Mitchell T.J., Warren A.Y., Brindle K.M., Sala E., Stewart G.D., Gallagher F.A., Gill, Andrew B [0000-0002-9287-9563], Kaggie, Joshua D [0000-0001-6706-3442], Welsh, Sarah J [0000-0001-5690-2677], Brindle, Kevin M [0000-0003-3883-6287], Stewart, Grant D [0000-0003-3188-9140], and Gallagher, Ferdia A [0000-0003-4784-5230]
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Cancer Research ,renal cell carcinoma ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,cancer metabolism ,monocarboxylate transporter ,Article ,Hyperpolarized ,hyperpolarized 13C magnetic resonance imaging ,Oncology ,C magnetic resonance imaging ,RC254-282 - Abstract
Simple Summary We evaluated renal cancer with varying aggressive appearances on histology, using an emerging form of non-invasive metabolic MRI. This imaging technique assesses the uptake and metabolism of a breakdown product of glucose (pyruvate) labelled with hyperpolarized carbon-13. We show that pyruvate metabolism is dependent on the aggressiveness of an individual tumor and we provide a mechanism for this finding from tissue analysis of molecules influencing pyruvate metabolism, suggesting a role for its membrane transporter. Abstract Differentiating aggressive clear cell renal cell carcinoma (ccRCC) from indolent lesions is challenging using conventional imaging. This work prospectively compared the metabolic imaging phenotype of renal tumors using carbon-13 MRI following injection of hyperpolarized [1-13C]pyruvate (HP-13C-MRI) and validated these findings with histopathology. Nine patients with treatment-naïve renal tumors (6 ccRCCs, 1 liposarcoma, 1 pheochromocytoma, 1 oncocytoma) underwent pre-operative HP-13C-MRI and conventional proton (1H) MRI. Multi-regional tissue samples were collected using patient-specific 3D-printed tumor molds for spatial registration between imaging and molecular analysis. The apparent exchange rate constant (kPL) between 13C-pyruvate and 13C-lactate was calculated. Immunohistochemistry for the pyruvate transporter (MCT1) from 44 multi-regional samples, as well as associations between MCT1 expression and outcome in the TCGA-KIRC dataset, were investigated. Increasing kPL in ccRCC was correlated with increasing overall tumor grade (ρ = 0.92, p = 0.009) and MCT1 expression (r = 0.89, p = 0.016), with similar results acquired from the multi-regional analysis. Conventional 1H-MRI parameters did not discriminate tumor grades. The correlation between MCT1 and ccRCC grade was confirmed within a TCGA dataset (p < 0.001), where MCT1 expression was a predictor of overall and disease-free survival. In conclusion, metabolic imaging using HP-13C-MRI differentiates tumor aggressiveness in ccRCC and correlates with the expression of MCT1, a predictor of survival. HP-13C-MRI may non-invasively characterize metabolic phenotypes within renal cancer.
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- 2022
33. Supplementary Figure 3 from Effective Activity of Cytokine-Induced Killer Cells against Autologous Metastatic Melanoma Including Cells with Stemness Features
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Ymera Pignochino, Antonella Balsamo, Tiziana Venesio, Elena Giacone, Daniela Caravelli, Susanna Gallo, Maria Giuseppa Volpe, Alessandro Zaccagna, Alberto Pisacane, Franco Picciotto, Giulia Mesiano, Maja Todorovic, Valeria Leuci, Lidia Giraudo, and Loretta Gammaitoni
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PDF file - 193K, Representative flow cytometry analysis of a CIK cell culture generated from PBMC from mMel patients.
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- 2023
34. Data from Effective Activity of Cytokine-Induced Killer Cells against Autologous Metastatic Melanoma Including Cells with Stemness Features
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Ymera Pignochino, Antonella Balsamo, Tiziana Venesio, Elena Giacone, Daniela Caravelli, Susanna Gallo, Maria Giuseppa Volpe, Alessandro Zaccagna, Alberto Pisacane, Franco Picciotto, Giulia Mesiano, Maja Todorovic, Valeria Leuci, Lidia Giraudo, and Loretta Gammaitoni
- Abstract
Purpose: We investigate the unknown tumor-killing activity of cytokine-induced killer (CIK) cells against autologous metastatic melanoma and the elusive subset of putative cancer stem cells (mCSC).Experimental Design: We developed a preclinical autologous model using same patient-generated CIK cells and tumor targets to consider the unique biology of each patient/tumor pairing. In primary tumor cell cultures, we visualized and immunophenotypically defined a putative mCSC subset using a novel gene transfer strategy that exploited their exclusive ability to activate the promoter of stemness gene Oct4.Results: The CIK cells from 10 patients with metastatic melanoma were successfully expanded (median, 23-fold; range, 11–117). Primary tumor cell cultures established and characterized from the same patients were used as autologous targets. Patient-derived CIK cells efficiently killed autologous metastatic melanoma [up to 71% specific killing (n = 26)]. CIK cells were active in vivo against autologous melanoma, resulting in delayed tumor growth, increased necrotic areas, and lymphocyte infiltration at tumor sites. The metastatic melanoma cultures presented an average of 11.5% ± 2.5% putative mCSCs, which was assessed by Oct4 promoter activity and stemness marker expression (Oct4, ABCG2, ALDH, MITF). Expression was confirmed on mCSC target molecules recognized by CIK cells (MIC A/B; ULBPs). CIK tumor killing activity against mCSCs was intense (up to 71%, n = 4) and comparable with results reported against differentiated metastatic melanoma cells (P = 0.8).Conclusions: For the first time, the intense killing activity of CIK cells against autologous metastatic melanoma, including mCSCs, has been shown. These findings move clinical investigation of a new immunotherapy for metastatic melanoma, including mCSCs, closer. Clin Cancer Res; 19(16); 4347–58. ©2013 AACR.
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- 2023
35. Supplementary Figure 2 from Effective Activity of Cytokine-Induced Killer Cells against Autologous Metastatic Melanoma Including Cells with Stemness Features
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Ymera Pignochino, Antonella Balsamo, Tiziana Venesio, Elena Giacone, Daniela Caravelli, Susanna Gallo, Maria Giuseppa Volpe, Alessandro Zaccagna, Alberto Pisacane, Franco Picciotto, Giulia Mesiano, Maja Todorovic, Valeria Leuci, Lidia Giraudo, and Loretta Gammaitoni
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PDF file - 147K, Representative flow cytometry analysis of melanoma primary cell cultures. assessment of CD117 (aka c-kit) and MCSP; c) assessment of MIC A/B and ULBP2; d) assessment of ULBP1 and ULBP3 expression; e) expression assessment of CD34 and VEGFR1 expression; f) assessment of intracellular Oct4 expression in fixed and permeabilized cells; g) assessment of ABCG2 expression; h) assessment of ALDH activity in cells stained with FITC ALDH substrate; i) assessment of MITF negativity in fixed and permeabilized cells stained with a primary specific antibody unconjugated and a PE conjugated secondary antibody; k) assessment of CD117 (also known as c-kit) and MCSP in mMel6, notably highly positive for CD117 expression.
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- 2023
36. Supplementary Figure 1 from Effective Activity of Cytokine-Induced Killer Cells against Autologous Metastatic Melanoma Including Cells with Stemness Features
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Ymera Pignochino, Antonella Balsamo, Tiziana Venesio, Elena Giacone, Daniela Caravelli, Susanna Gallo, Maria Giuseppa Volpe, Alessandro Zaccagna, Alberto Pisacane, Franco Picciotto, Giulia Mesiano, Maja Todorovic, Valeria Leuci, Lidia Giraudo, and Loretta Gammaitoni
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PDF file - 143K, Primary melanoma cell targets.
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- 2023
37. Supplementary Figure S2 from Cytokine-Induced Killer Cells Kill Chemo-surviving Melanoma Cancer Stem Cells
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Anna Sapino, Ymera Pignochino, Susanna Gallo, Valentina Coha, Valentina Martin, Giulia Cattaneo, Michela Cangemi, Rebecca Senetta, Alberto Pisacane, Alessandro Zaccagna, Martina Sanlorenzo, Francesco Sassi, Ramona Rotolo, Giulia Mesiano, Valeria Leuci, Marco Macagno, Lidia Giraudo, and Loretta Gammaitoni
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Supplementary Figure S2: Immunophenotype of patient-derived CIK cells and CIK cell in vitro activity
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- 2023
38. Supplementary Materials and Methods/figure legend from Cytokine-Induced Killer Cells Kill Chemo-surviving Melanoma Cancer Stem Cells
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Anna Sapino, Ymera Pignochino, Susanna Gallo, Valentina Coha, Valentina Martin, Giulia Cattaneo, Michela Cangemi, Rebecca Senetta, Alberto Pisacane, Alessandro Zaccagna, Martina Sanlorenzo, Francesco Sassi, Ramona Rotolo, Giulia Mesiano, Valeria Leuci, Marco Macagno, Lidia Giraudo, and Loretta Gammaitoni
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DNA extraction and Sanger Sequencing In vivo Limiting Dilution Assay Cell growth inhibition assay Analysis of LV.Oct4.eGFP integration in eGFP positive and negative cell fractions
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- 2023
39. Supplementary Figure Legend from Effective Activity of Cytokine-Induced Killer Cells against Autologous Metastatic Melanoma Including Cells with Stemness Features
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Ymera Pignochino, Antonella Balsamo, Tiziana Venesio, Elena Giacone, Daniela Caravelli, Susanna Gallo, Maria Giuseppa Volpe, Alessandro Zaccagna, Alberto Pisacane, Franco Picciotto, Giulia Mesiano, Maja Todorovic, Valeria Leuci, Lidia Giraudo, and Loretta Gammaitoni
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PDF file - 64K
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- 2023
40. Supplementary Figure 4 from Effective Activity of Cytokine-Induced Killer Cells against Autologous Metastatic Melanoma Including Cells with Stemness Features
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Ymera Pignochino, Antonella Balsamo, Tiziana Venesio, Elena Giacone, Daniela Caravelli, Susanna Gallo, Maria Giuseppa Volpe, Alessandro Zaccagna, Alberto Pisacane, Franco Picciotto, Giulia Mesiano, Maja Todorovic, Valeria Leuci, Lidia Giraudo, and Loretta Gammaitoni
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PDF file - 122K, Representative cell sorting plots of LV-oct4.eGFP transduced cells.
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- 2023
41. Supplementary Figure 6 from Effective Activity of Cytokine-Induced Killer Cells against Autologous Metastatic Melanoma Including Cells with Stemness Features
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Ymera Pignochino, Antonella Balsamo, Tiziana Venesio, Elena Giacone, Daniela Caravelli, Susanna Gallo, Maria Giuseppa Volpe, Alessandro Zaccagna, Alberto Pisacane, Franco Picciotto, Giulia Mesiano, Maja Todorovic, Valeria Leuci, Lidia Giraudo, and Loretta Gammaitoni
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PDF file - 117K, Expression level of ABCG2 (a), NKG2D ligands MIC A/B (b) and ULBP2 (c) in LV-oct4-eGFP transduced cells.
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- 2023
42. Supplementary Figure 5 from Effective Activity of Cytokine-Induced Killer Cells against Autologous Metastatic Melanoma Including Cells with Stemness Features
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Ymera Pignochino, Antonella Balsamo, Tiziana Venesio, Elena Giacone, Daniela Caravelli, Susanna Gallo, Maria Giuseppa Volpe, Alessandro Zaccagna, Alberto Pisacane, Franco Picciotto, Giulia Mesiano, Maja Todorovic, Valeria Leuci, Lidia Giraudo, and Loretta Gammaitoni
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PDF file - 81K, Representative flow cytometry analysis of melanoma primary transduced cells.
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- 2023
43. Supplementary Tables from Cytokine-Induced Killer Cells Kill Chemo-surviving Melanoma Cancer Stem Cells
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Anna Sapino, Ymera Pignochino, Susanna Gallo, Valentina Coha, Valentina Martin, Giulia Cattaneo, Michela Cangemi, Rebecca Senetta, Alberto Pisacane, Alessandro Zaccagna, Martina Sanlorenzo, Francesco Sassi, Ramona Rotolo, Giulia Mesiano, Valeria Leuci, Marco Macagno, Lidia Giraudo, and Loretta Gammaitoni
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Supplementary Table 1: Patients Characteristics Supplementary Table 2: Comparative transduction of melanoma cell cultures
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- 2023
44. SupplementaryFigure S5 from Cytokine-Induced Killer Cells Kill Chemo-surviving Melanoma Cancer Stem Cells
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Anna Sapino, Ymera Pignochino, Susanna Gallo, Valentina Coha, Valentina Martin, Giulia Cattaneo, Michela Cangemi, Rebecca Senetta, Alberto Pisacane, Alessandro Zaccagna, Martina Sanlorenzo, Francesco Sassi, Ramona Rotolo, Giulia Mesiano, Valeria Leuci, Marco Macagno, Lidia Giraudo, and Loretta Gammaitoni
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Supplementary Figure S5:Tumor infiltration by CIK cells
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- 2023
45. Data from Cytokine-Induced Killer Cells Kill Chemo-surviving Melanoma Cancer Stem Cells
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Anna Sapino, Ymera Pignochino, Susanna Gallo, Valentina Coha, Valentina Martin, Giulia Cattaneo, Michela Cangemi, Rebecca Senetta, Alberto Pisacane, Alessandro Zaccagna, Martina Sanlorenzo, Francesco Sassi, Ramona Rotolo, Giulia Mesiano, Valeria Leuci, Marco Macagno, Lidia Giraudo, and Loretta Gammaitoni
- Abstract
Purpose: The MHC-unrestricted activity of cytokine-induced killer (CIK) cells against chemo-surviving melanoma cancer stem cells (mCSC) was explored, as CSCs are considered responsible for chemoresistance and relapses.Experimental Design: Putative mCSCs were visualized by engineering patient-derived melanoma cells (MC) with a lentiviral vector encoding eGFP under expression control by stemness gene promoter oct4. Their stemness potential was confirmed in vivo by limiting dilution assays. We explored the sensitivity of eGFP+ mCSCs to chemotherapy (CHT), BRAF inhibitor (BRAFi) or CIK cells, as single agents or in sequence, in vitro. First, we treated MCs in vitro with fotemustine or dabrafenib (BRAF-mutated cases); then, surviving MCs, enriched in mCSCs, were challenged with autologous CIK cells. CIK cell activity against chemoresistant mCSCs was confirmed in vivo in two distinct immunodeficient murine models.Results: We visualized eGFP+ mCSCs (14% ± 2.1%) in 11 MCs. The tumorigenic precursor rate in vivo was higher within eGFP+ MCs (1/42) compared with the eGFP− counterpart (1/4,870). In vitro mCSCs were relatively resistant to CHT and BRAFi, but killed by CIK cells (n = 11, 8/11 autologous), with specific lysis ranging from 95% [effector:tumor ratio (E:T), 40:1] to 20% (E:T 1:3). In vivo infusion of autologous CIK cells into mice bearing xenografts from three distinct melanomas demonstrated significant tumor responses involving CHT-spared eGFP+ mCSCs (P = 0.001). Sequential CHT–immunotherapy treatment retained antitumor activity (n = 12, P = 0.001) reducing mCSC rates (P = 0.01).Conclusions: These findings are the first demonstration that immunotherapy with CIK cells is active against autologous mCSCs surviving CHT or BRAFi. An experimental platform for mCSC study and rationale for CIK cells in melanoma clinical study is provided. Clin Cancer Res; 23(9); 2277–88. ©2016 AACR.
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- 2023
46. Supplementary Methods from Effective Activity of Cytokine-Induced Killer Cells against Autologous Metastatic Melanoma Including Cells with Stemness Features
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Dario Sangiolo, Massimo Aglietta, Fabrizio Carnevale-Schianca, Giovanni Grignani, Ymera Pignochino, Antonella Balsamo, Tiziana Venesio, Elena Giacone, Daniela Caravelli, Susanna Gallo, Maria Giuseppa Volpe, Alessandro Zaccagna, Alberto Pisacane, Franco Picciotto, Giulia Mesiano, Maja Todorovic, Valeria Leuci, Lidia Giraudo, and Loretta Gammaitoni
- Abstract
PDF file - 63K
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- 2023
47. Correlating Radiomic Features of Heterogeneity on CT with Circulating Tumor DNA in Metastatic Melanoma
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Andrew B Gill, Leonardo Rundo, Jonathan C. M. Wan, Doreen Lau, Jeries P. Zawaideh, Ramona Woitek, Fulvio Zaccagna, Lucian Beer, Davina Gale, Evis Sala, Dominique-Laurent Couturier, Pippa G. Corrie, Nitzan Rosenfeld, and Ferdia A. Gallagher
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liquid biopsy ,circulating tumor DNA ,tumor heterogeneity ,tumor imaging ,radiomics ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Clinical imaging methods, such as computed tomography (CT), are used for routine tumor response monitoring. Imaging can also reveal intratumoral, intermetastatic, and interpatient heterogeneity, which can be quantified using radiomics. Circulating tumor DNA (ctDNA) in the plasma is a sensitive and specific biomarker for response monitoring. Here we evaluated the interrelationship between circulating tumor DNA mutant allele fraction (ctDNAmaf), obtained by targeted amplicon sequencing and shallow whole genome sequencing, and radiomic measurements of CT heterogeneity in patients with stage IV melanoma. ctDNAmaf and radiomic observations were obtained from 15 patients with a total of 70 CT examinations acquired as part of a prospective trial. 26 of 39 radiomic features showed a significant relationship with log(ctDNAmaf). Principal component analysis was used to define a radiomics signature that predicted ctDNAmaf independent of lesion volume. This radiomics signature and serum lactate dehydrogenase were independent predictors of ctDNAmaf. Together, these results suggest that radiomic features and ctDNAmaf may serve as complementary clinical tools for treatment monitoring.
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- 2020
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48. Comparison of operative and postoperative characteristics and outcomes between thoracoscopic segmentectomy and lobectomy for non-small-cell lung cancer: a propensity score matching study from the Italian VATS Group Registry
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Dell'Amore, A., Lomangino, I., Cannone, G., Terzi, S., Pangoni, A., Lorenzoni, G., Nicotra, S., Schiavon, M., Zuin, A., Gregori, D., Crisci, R., Curcio, C., Rea, F., Mancuso, M., Pernazza, F., Refai, M., Bortolotti, L., Rizzardi, G., Solli, P., Brandolini, I., Perkmann, R., Zaraca, F., Benvenuti, M., Gavezzoli, D., Cherchi, R., Ferrari, P., Mucilli, F., Camplese, P., Melloni, G., Mazza, F., Cavallesco, G., Maniscalco, P., Voltolini, L., Gonfiotti, A., Stella, F., Argnani, D., Pariscenti, G. L., Iurilli, S., Surrente, C., Lopez, C., Droghett, A., Giovanardi, M., Breda, C., Lo Giudice, F., Alloisio, M., Bottoni, E., Spaggiari, L., Gasparri, R., Torre, M., Rinaldo, A., Nosotti, M., Rosso, L., Negri, G. P., Bandiera, A., Stefani, A., Natali, P., Scarci, M., Pirondini, E., Amore, D., Baietto, G., Casadio, C., Bertani, A., Russo, E., Ampollini, L., Carbognani, P., Puma, F., Vinci, D., Andreetti, C., Poggi, C., Cardillo, G., Margaritora, S., Meacci, E., Luzzi, L., Ghisalberti, M., Zaccagna, G., Lausi, P., Guerrera, F., Fontana, D., Della Beffa, V., Morelli, A., Londero, F., Imperatori, N., Rotolo, A., Terzi, A., Viti, A., Infante, M., and Benato, C.
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Segmentectomy ,Pulmonary and Respiratory Medicine ,medicine.medical_specialty ,Lung Neoplasms ,medicine.medical_treatment ,VATS lobectomy ,Video-assisted thoracic surgery ,Context (language use) ,Mastectomy, Segmental ,Postoperative outcome ,Postoperative Complications ,Lobectomy ,Non-small-cell lung cancer ,Carcinoma, Non-Small-Cell Lung ,Humans ,Medicine ,Registries ,Thoracotomy ,Pneumonectomy ,Propensity Score ,Lung cancer ,Retrospective Studies ,Thoracic Surgery, Video-Assisted ,business.industry ,Confounding ,Postoperative complication ,General Medicine ,medicine.disease ,Surgery ,Propensity score matching ,Non small cell ,Cardiology and Cardiovascular Medicine ,business - Abstract
OBJECTIVES Only few studies compared the surgical morbidity and mortality of thoracoscopic segmentectomy versus lobectomy for non-small-cell lung cancer, in particular, by relating the segmental resections with the corresponding anatomical lobes. METHODS We enrolled a total of 7487 patients who underwent VATS lobectomy (7269) or segmentectomy (218) from January 2014 to July 2019. A propensity score matching approach was used to account for potential confounding factors between the 2 groups. After matching, 349 lobectomies and 208 segmentectomies were included in the analysis. We analysed the operative and postoperative outcomes of video-assisted anatomical segmentectomy compared with video-assisted lobectomy and, in details, the results of segmentectomy with its corresponding lobectomy in a large cohort of patients from the Italian VATS Group Registry. RESULTS The overall conversion rate to thoracotomy was not statistically different between the groups (27 patients 8% vs 7 patients 3%, P = 0.1). The lobectomy group had a greater number of resected lymph nodes (median 11 vs 8, P = 0.006). No significant differences were detected in 30-day mortality (1.4%, 5 patients vs 0.9%, 2 patients), overall complications (18%, 62 patients vs 14%, 29 patients) and prolonged air leakage (31 patients, 9% vs 12 patients, 6%) between lobectomy and segmentectomy, respectively. No statistical differences were found regarding the median duration of drainage (3.2 days, P = 1) and the overall median length of hospital stay (6.4 days, P = 0.1) between the 2 groups. In the context of segmentectomy versus corresponding lobectomy, the right upper lobectomy compared with right upper segmentectomy showed a higher number of resected lymph nodes (P = 0.027). No statistical differences were reported in terms of conversion rate and postoperative complication and mortality. CONCLUSIONS Segmentectomy could be considered a safe procedure without significant differences compared to thoracoscopic lobectomy in terms of postoperative morbidity and mortality.
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- 2021
49. Melanoma Brain Metastases in the Era of Target Therapies: An Overview
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Paolo Becco, Susanna Gallo, Stefano Poletto, Mirko Pio Manlio Frascione, Luca Crotto, Alessandro Zaccagna, Luca Paruzzo, Daniela Caravelli, Fabrizio Carnevale-Schianca, and Massimo Aglietta
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metastatic melanoma ,brain metastases ,target therapy ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Malignant melanoma is the third most common type of tumor that causes brain metastases. Patients with cerebral involvement have a dismal prognosis and their treatment is an unmet medical need. Brain involvement is a multistep process involving several signaling pathways such as Janus kinase/signal Transducer and Activator of Transcription (JAK/STAT), Phosphoinositide 3-kinase/Protein Kinase B (PI3K/AKT), Vascular Endothelial Growth Factor and Phosphatase and Tensin Homolog (PTEN). Recently therapy that targets the MAPK signaling (BRAF/MEK inhibitors) and immunotherapy (anti-CTLA4 and anti-PD1 agents) have changed the therapeutic approaches to stage IV melanoma. In contrast, there are no solid data about patients with brain metastases, who are usually excluded from clinical trials. Retrospective data showed that BRAF-inhibitors, alone or in combination with MEK-inhibitors have interesting clinical activity in this setting. Prospective data about the combinations of BRAF/MEK inhibitors have been recently published, showing an improved overall response rate. Short intracranial disease control is still a challenge. Several attempts have been made in order to improve it with combinations between local and systemic therapies. Immunotherapy approaches seem to retain promising activity in the treatment of melanoma brain metastasis as showed by the results of clinical trials investigating the combination of anti-CTL4 (Ipilimumab) and anti-PD1(Nivolumab). Studies about the combination or the sequential approach of target therapy and immunotherapy are ongoing, with immature results. Several clinical trials are ongoing trying to explore new approaches in order to overcome tumor resistance. At this moment the correct therapeutic choices for melanoma with intracranial involvement is still a challenge and new strategies are needed.
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- 2020
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50. Multiparametric MRI for assessment of early response to neoadjuvant sunitinib in renal cell carcinoma
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Ferdia A. Gallagher, Wendi Qian, Fulvio Zaccagna, Stephan Ursprung, Grant D. Stewart, Anne Y. Warren, Sarah J. Welsh, Tristan Barrett, Timothy Eisen, Andrew N. Priest, Andrea Machin, Ursprung, Stephan [0000-0003-2476-178X], Priest, Andrew N. [0000-0002-9771-4290], Warren, Anne Y. [0000-0002-1170-7867], Apollo - University of Cambridge Repository, Priest, Andrew N [0000-0002-9771-4290], Stewart, Grant [0000-0003-3188-9140], Warren, Anne [0000-0002-1170-7867], Eisen, Tim [0000-0001-9663-4873], Welsh, Sarah [0000-0001-5690-2677], Gallagher, Ferdia [0000-0003-4784-5230], Barrett, Tristan [0000-0002-1180-1474], Ursprung S., Priest A.N., Zaccagna F., Qian W., Machin A., Stewart G.D., Warren A.Y., Eisen T., Welsh S.J., Gallagher F.A., Barrett T., and Warren, Anne Y [0000-0002-1170-7867]
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Male ,medicine.medical_treatment ,Cancer Treatment ,urologic and male genital diseases ,Nephrectomy ,Metastasis ,Diagnostic Radiology ,Renal cell carcinoma ,Basic Cancer Research ,Medicine and Health Sciences ,Sunitinib ,ComputingMilieux_MISCELLANEOUS ,Brain Mapping ,Multidisciplinary ,medicine.diagnostic_test ,Radiology and Imaging ,Middle Aged ,Magnetic Resonance Imaging ,Kidney Neoplasms ,Neoadjuvant Therapy ,Treatment Outcome ,Oncology ,Nephrology ,Renal Cancer ,Medicine ,Female ,Perfusion ,medicine.drug ,MRI ,Research Article ,medicine.medical_specialty ,Imaging Techniques ,Brain Morphometry ,Science ,Urology ,Surgical and Invasive Medical Procedures ,Neuroimaging ,Antineoplastic Agents ,Research and Analysis Methods ,Urinary System Procedures ,Diagnostic Medicine ,medicine ,Humans ,Multiparametric Magnetic Resonance Imaging ,Carcinoma, Renal Cell ,Aged ,Surgical Excision ,business.industry ,Diffusion Weighted Imaging ,Carcinoma ,Renal Cell Carcinoma ,Cancer ,Cancers and Neoplasms ,Biology and Life Sciences ,Magnetic resonance imaging ,medicine.disease ,Clinical trial ,Genitourinary Tract Tumors ,business ,Neuroscience - Abstract
Funder: NIHR Cambridge Biomedical Research Centre, Funder: Addenbrooke’s Charitable Trust, Funder: National Institute for Health Research (NIHR), Funder: Mark Foundation For Cancer Research, Funder: Cambridge Commonwealth, European and International Trust, Funder: Cancer Research UK, Funder: Cambridge Clinical Trials Unit, Funder: Cancer Research UK Cambridge Centre, Funder: Engineering and Physical Sciences Research Council Cancer Imaging Centre in Cambridge and Manchester, Funder: Cambridge Experimental Cancer Medicine Centre, PURPOSE: To detect early response to sunitinib treatment in metastatic clear cell renal cancer (mRCC) using multiparametric MRI. METHOD: Participants with mRCC undergoing pre-surgical sunitinib therapy in the prospective NeoSun clinical trial (EudraCtNo: 2005-004502-82) were imaged before starting treatment, and after 12 days of sunitinib therapy using morphological MRI sequences, advanced diffusion-weighted imaging, measurements of R2* (related to hypoxia) and dynamic contrast-enhanced imaging. Following nephrectomy, participants continued treatment and were followed-up with contrast-enhanced CT. Changes in imaging parameters before and after sunitinib were assessed with the non-parametric Wilcoxon signed-rank test and the log-rank test was used to assess effects on survival. RESULTS: 12 participants fulfilled the inclusion criteria. After 12 days, the solid and necrotic tumor volumes decreased by 28% and 17%, respectively (p = 0.04). However, tumor-volume reduction did not correlate with progression-free or overall survival (PFS/OS). Sunitinib therapy resulted in a reduction in median solid tumor diffusivity D from 1298x10-6 to 1200x10-6mm2/s (p = 0.03); a larger decrease was associated with a better RECIST response (p = 0.02) and longer PFS (p = 0.03) on the log-rank test. An increase in R2* from 19 to 28s-1 (p = 0.001) was observed, paralleled by a decrease in Ktrans from 0.415 to 0.305min-1 (p = 0.01) and a decrease in perfusion fraction from 0.34 to 0.19 (p
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- 2022
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