Isabella Castiglioni

Isabella Castiglioni
Italian National Research Council | CNR · Institute of Molecular Bioimaging and Physiology IBFM

BSc, MBA

About

225
Publications
53,986
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7,438
Citations
Citations since 2017
117 Research Items
5745 Citations
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201720182019202020212022202302004006008001,0001,2001,400
201720182019202020212022202302004006008001,0001,2001,400

Publications

Publications (225)
Article
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Artificial intelligence (AI) and its different approaches, from machine learning to deep learning, are not new. We discuss here about the declaration of AI in the title of those articles dealing with AI. From 1990 to 2021, while AI articles in the PubMed increased from 300 to 59,596, the percentage declaring AI in the title describes a U-like-shape...
Article
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Molecular/genomic profiling is the most accurate method to assess prognosis of endometrial cancer patients. Radiomic profiling allows for the extraction of mineable high-dimensional data from clinical radiological images, thus providing noteworthy information regarding tumor tissues. Interestingly, the adoption of radiomics shows important results...
Article
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With life expectancy increasing for the general population, public health promotion activities should be a priority to aim at a reduction of the burden and costs of hospitalization, disability, and lifelong treatment. This study aimed to explore the influence of parameters pertaining to different aspects of well-being, including physical and mental...
Article
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Purpose Total marrow (and lymphoid) irradiation (TMI-TMLI) is limited by the couch travel range of modern linacs, which forces the treatment delivery to be split into two plans with opposite orientations: a head-first supine upper-body plan, and a feet-first supine lower extremities plan. A specific field junction is thus needed to obtain adequate...
Article
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Modern society grew rapidly over the last few decades and this led to an alarming increase in air pollutants and a worsening of the human health, especially in relation to the respiratory system. Indeed, chronic respiratory diseases were the third main cause of death in 2017, with over 3 million of deaths. Furthermore, the pollution has considerabl...
Conference Paper
Introduction/Background Multicenter prospective clinical validation of the radiomic machine learning model (TRACE4OC) applied to transvaginal ultrasound (US) in predicting the risk of malignancy of adnexal masses. Methodology From a multicenter prospective consecutive series of women scheduled for surgery of adnexal masses, we collected and evalua...
Article
This topical review focuses on the applications of artificial intelligence (AI) tools to stereotactic body radiation therapy (SBRT). The high dose per fraction and the limited number of fractions in SBRT require stricter accuracy than standard radiation therapy. The intent of this review is to describe the development and evaluate the possible bene...
Article
Purpose Radiomics has emerged as an advanced image processing methodology to define quantitative imaging biomarkers for prognosis and prediction of treatment response and outcome. The development of quantitative imaging biomarkers requires careful analysis to define their accuracy, stability and reproducibility through phantom measurements. Few eff...
Article
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Alzheimer’s disease (AD) is a neurodegenerative disease characterized by rapid brain cell degeneration affecting different areas of the brain. Hippocampus is one of the earliest involved brain regions in the disease. Modern technologies based on high-throughput data have identified transcriptional profiling of several neurological diseases, includi...
Article
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The paper reports the results obtained from the digital survey of Giottesque frescoes in the Archiepiscopal Palace of Milan. Multispectral Imaging and Image Based Modelling techniques have allowed the study, the high-resolution documentation and the virtual reassembly of the fragmented frescoes: the integration of spectral data with RGB ortho-image...
Article
Mammographic breast density (BD) is commonly visually assessed using the Breast Imaging Reporting and Data System (BI-RADS) four-category scale. To overcome inter- and intraobserver variability of visual assessment, the authors retrospectively developed and externally validated a software for BD classification based on convolutional neural networks...
Article
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The “bovine” aortic arch is an anatomic variant consisting in a common origin of the innominate and left carotid artery (CILCA), associated with a greater risk of thoracic aortic diseases (aneurysms and dissections), stroke, and complications after endovascular procedures. CILCA can be detected by visual assessment of computed tomography (CT) chest...
Article
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Prostate cancer (PC) is one of the major male cancers. Differential diagnosis of PC is indispensable for the individual therapy, i.e., Gleason score (GS) that describes the grade of cancer can be used to choose the appropriate therapy. However, the current techniques for PC diagnosis and prognosis are not always effective. To identify potential mar...
Article
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Breast cancer is a heterogeneous disease classified into four main subtypes with different clinical outcomes, such as patient survival, prognosis, and relapse. Current genetic tests for the differential diagnosis of BC subtypes showed a poor reproducibility. Therefore, an early and correct diagnosis of molecular subtypes is one of the challenges in...
Article
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We developed a machine learning model based on radiomics to predict the BI-RADS category of ultrasound-detected suspicious breast lesions and support medical decision-making towards short-interval follow-up versus tissue sampling. From a retrospective 2015–2019 series of ultrasound-guided core needle biopsies performed by four board-certified breas...
Article
X-ray fluorescence (XRF) and reflectance spectroscopy (RS) are commonly used for the characterization of painting materials. It is well known that the former provides the chemical fingerprint of the pictorial layers, while the latter returns the molecular description of the pigments constituting the uppermost layers. Even if these two techniques ca...
Article
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Background: The coronavirus disease-2019 (COVID-19), caused by a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is now spread worldwide. Therefore, informative and reliable data related to the exact effects of COVID-19 on fertility and pregnancy is still of great interest until the pandemic is declared over. General guidelines regard...
Preprint
Full-text available
We developed a machine learning model based on radiomics to predict the BI-RADS category of ultrasound-detected suspicious breast lesions and support medical decision making towards short-interval follow-up versus tissue sampling. From a retrospective 2015-2019 series of ultrasound-guided core needle biopsies performed by four board-certified breas...
Article
Full-text available
The rise of longitudinal single-cell sequencing experiments on patient-derived cell cultures, xenografts and organoids is opening new opportunities to track cancer evolution, assess the efficacy of therapies and identify resistant subclones. We introduce LACE, the first algorithmic framework that processes single-cell mutational profiles from samp...
Article
The rise of longitudinal single-cell sequencing experiments on patient-derived cell cultures, xenografts and organoids is opening new opportunities to track cancer evolution, assess the efficacy of therapies and identify resistant subclones. We introduce LACE, the first algorithmic framework that processes single-cell mutational profiles from samp...
Article
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Amyotrophic lateral sclerosis (ALS) is a fatal disease related to upper and lower motor neurons degeneration. Although the environmental and genetic causes of this disease are still unclear, some factors involved in ALS onset such as oxidative stress may be influenced by diet. A higher risk of ALS has been correlated with a high fat and glutamate i...
Article
Full-text available
Background To evaluate the performance of a decision support system (DSS) based on radiomics and machine learning in predicting the risk of malignancy of ovarian masses (OMs) from transvaginal ultrasonography (TUS) and serum CA-125. Methods A total of 274 consecutive patients who underwent TUS (by different examiners and with different ultrasound...
Article
Full-text available
Objective The objectives of our study were to assess the association of radiomic and genomic data with histology and patient outcome in non-small cell lung cancer (NSCLC). Methods In this retrospective single-centre observational study, we selected 151 surgically treated patients with adenocarcinoma or squamous cell carcinoma who performed baselin...
Conference Paper
Introduction/Background* Molecular/genomic profiling is the most accurate method to assess prognosis of endometrial cancer patients. Similarly, the adoption of radiomics showed important results for screening, diagnosis and prognosis, across various radiological systems and oncologic specialties. Here, we aim to correlate radiomic features obtained...
Article
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Lung cancer (LC) is currently one of the main causes of cancer-related deaths worldwide. Low-dose computed tomography (LDCT) of the chest has been proven effective in secondary prevention (i.e., early detection) of LC by several trials. In this work, we investigated the potential impact of radiomics on indeterminate prevalent pulmonary nodule (PN)...
Article
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Amyotrophic lateral sclerosis (ALS) is a complex disease with a late onset and is characterized by the progressive loss of muscular and respiratory functions. Although recent studies have partially elucidated ALS’s mechanisms, many questions remain such as what the most important molecular pathways involved in ALS are and why there is such a large...
Article
Aim: SARS-CoV-2, an emerging betacoronavirus, is the causative agent of COVID-19. Currently, there are few specific and selective antiviral drugs for the treatment and vaccines to prevent contagion. However, their long-term effects can be revealed after several years, and new drugs for COVID-19 should continue to be investigated. Materials & method...
Article
Reflectance Spectroscopy (RS) and Fiber Optics Reflectance Spectroscopy (FORS) are well-established techniques for the investigation of works of art with particular attention to paintings. Most modern museums put at the disposal of their research groups portable equipment that, together with the intrinsic non-invasiveness of RS and FORS, makes poss...
Article
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Coronavirus disease 2019 (COVID-19), a global pandemic, is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Angiotensin-converting enzyme 2 (ACE2) is the receptor for SARS-CoV-2 and transmembrane serine protease 2 (TMPRSS2) facilitates ACE2-mediated virus entry. Moreover, the expression of ACE2 in the testes of infertile men...
Article
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Radiotherapy (RT) plus the anti-EGFR monoclonal antibody Cetuximab (CTX) is an effective combination therapy for a subset of head and neck squamous cell carcinoma (HNSCC) patients. However, predictive markers of efficacy are missing, resulting in many patients treated with disappointing results and unnecessary toxicities. Here, we report that activ...
Article
Matters Arising from: Sharma, A., Cao, E.Y., Kumar, V. et al. Longitudinal single-cell RNA sequencing of patient-derived primary cells reveals drug-induced infidelity in stem cell hierarchy. Nat Commun 9, 4931 (2018). https://doi.org/10.1038/s41467-018-07261-3. In Sharma, A. et al. Nat Commun 9, 4931 (2018) the authors employ longitudinal single-ce...
Preprint
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A bstract Matters Arising from: Sharma, A., Cao, E.Y., Kumar, V. et al. Longitudinal single-cell RNA sequencing of patient-derived primary cells reveals drug-induced infidelity in stem cell hierarchy. Nat Commun 9 , 4931 (2018). https://doi.org/10.1038/s41467-018-07261-3 . In Sharma, A. et al. Nat Commun 9 , 4931 (2018) the authors employ longitudi...
Article
Objective To develop and evaluate the performance of a radiomics and machine learning model applied to ultrasound (US) images in predicting the risk of malignancy of a uterine mesenchymal lesion. Methods Single-center retrospective evaluation of consecutive patients who underwent surgery for a malignant uterine mesenchymal lesion (sarcoma) and a c...
Article
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Radiomics allows the extraction quantitative features from imaging, as imaging biomarkers of disease. The objective of this exploratory study is to implement a reproducible radiomic-pipeline for the extraction of a magnetic resonance imaging (MRI) signature for prostate cancer (PCa) aggressiveness. One hundred and two consecutive patients performin...
Article
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Triple negative breast cancer (TNBC) accounts for about a fifth of all breast cancers and includes a diverse group of cancers. The heterogeneity of TNBC and the lack of target receptors on the cell surface make it difficult to develop specific therapeutic treatments. These aspects cause the high negative prognosis of patients with this type of tumo...
Article
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We assessed the role of artificial intelligence applied to chest X-rays (CXRs) in supporting the diagnosis of COVID-19. We trained and cross-validated a model with an ensemble of 10 convolutional neural networks with CXRs of 98 COVID-19 patients, 88 community-acquired pneumonia (CAP) patients, and 98 subjects without either COVID-19 or CAP, collect...
Article
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Digital breast tomosynthesis (DBT) studies were introduced as a successful help for the detection of calcification, which can be a primary sign of cancer. Expert radiologists are able to detect suspicious calcifications in DBT, but a high number of calcifications with non-malignant diagnosis at biopsy have been reported (false positives, FP). In th...
Article
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Background and Objectives: Breast cancer is a heterogeneous disease categorized into four subtypes. Previous studies have shown that copy number alterations of several genes are implicated with the development and progression of many cancers. This study evaluates the effects of DNA copy number alterations on gene expression levels in different brea...
Article
Purpose: Artificial intelligence (AI) models are playing an increasing role in biomedical research and healthcare services. This review focuses on challenges points to be clarified about how to develop AI applications as clinical decision support systems in the real-world context. Methods: A narrative review has been performed including a critic...
Article
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The development of new computational approaches that are able to design the correct personalized drugs is the crucial therapeutic issue in cancer research. However, tumor heterogeneity is the main obstacle to developing patient-specific single drugs or combinations of drugs that already exist in clinics. In this study, we developed a computational...
Article
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Background We aimed to train and test a deep learning classifier to support the diagnosis of coronavirus disease 2019 (COVID-19) using chest x-ray (CXR) on a cohort of subjects from two hospitals in Lombardy, Italy. Methods We used for training and validation an ensemble of ten convolutional neural networks (CNNs) with mainly bedside CXRs of 250 C...
Preprint
Full-text available
Objectives The objectives of our study were to assess the association of radiomic and genomic data with histology and patient outcome in non-small cell lung cancer (NSCLC). Methods In this retrospective single-centre observational study, we selected 151 surgically treated patients with adenocarcinoma or squamous cell carcinoma who performed baselin...
Article
Full-text available
MicroRNAs (miRNAs) are small noncoding RNAs that have emerged as new potential epigenetic biomarkers. Here, we evaluate the efficacy of six circulating miRNA previously described in the literature as biomarkers for the diagnosis of temporal lobe epilepsy (TLE) and/or as predictive biomarkers to antiepileptic drug response. We measured the differenc...
Article
The project “Leonardesque Artists beyond the Visible” was planned on the 500th anniversary of the death of Leonardo da Vinci, with the occasion of an exhibition held in Milan in 2019, where more than twenty works made by Leonardesque masters have been put on display. Among them, five representative paintings made by his closest pupils were selected...
Preprint
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BackgroundSARS-CoV-2 coronavirus, an emerging Betacoronavirus, is the causative agent of the severe acute respiratory distress syndrome outbreak in 2019 (COVID-19). Currently, there are neither specific and selective antiviral drugs for the treatment nor vaccines to prevent contagion. Here we propose a bioinformatic approach in order to test in sil...
Article
Full-text available
Alzheimer's Disease (AD) is the most common neurodegenerative disease, with 10% prevalence in the elder population. Conventional Machine Learning (ML) was proven effective in supporting the diagnosis of AD, while very few studies investigated the performance of deep learning and transfer learning in this complex task. In this paper, we evaluated th...
Article
Full-text available
Molecular docking in the pharmaceutical industry is a powerful in silico approach for discovering novel therapies for unmet medical needs predicting drug–target interactions. It not only provides binding affinity between drugs and targets at the atomic level, but also elucidates the fundamental pharmacological properties of specific drugs. The purp...
Article
Full-text available
Background: Severe acute respiratory syndrome coronavirus (SARS-CoV-2), an emerging Betacoronavirus, is the causative agent of COVID-19. Angiotensin converting enzyme 2 (ACE2), being the main cell receptor of SARS-CoV-2, plays a role in the entry of the virus into the cell. Currently, there are neither specific antiviral drugs for the treatment or...
Chapter
This chapter aims to address the issue regarding computers—intended as intelligent algorithms—as able to aid the diagnosis of Alzheimer's disease (AD). Several studies have investigated the utility of using machine learning methods coupled with neuroimaging, biological, or behavioral features for improving the accuracy of the diagnosis. We report a...
Article
PurposeTo develop and evaluate the performance of a radiomic and machine learning model applied to ultrasound images in predicting the risk of malignancy of ovarian masses (OMs).Methods Single-center retrospective evaluation of consecutive patients who underwent transvaginal ultrasound (US) with images storage and surgery for ovarian masses. Radiom...
Article
Metastases are the main cause of death in advanced breast cancer (BC) patients. Although chemotherapy and hormone therapy are current treatment strategies, drug resistance is frequent and still not completely understood. In this study, a bioinformatics analysis was performed on BC patients to explore the molecular mechanisms associated with BC meta...
Preprint
Full-text available
Background: Severe acute respiratory syndrome coronavirus (SARS-CoV-2), an emerging Betacoronavirus, is the causative agent of COVID-19. Angiotensin converting enzyme 2 (ACE2), being the main cell receptor of SARS-CoV-2, plays a role in the entry of the virus into the cell. Currently, there are no specific antiviral drugs for the treatment and neit...
Article
One of the current challenges in the field of Alzheimer’s disease (AD) is to identify patients with mild cognitive impairment (MCI) that will convert to AD. Artificial intelligence, in particular machine learning (ML), has established as one of more powerful approach to extract reliable predictors and to automatically classify different AD phenotyp...
Preprint
Objectives We tested artificial intelligence (AI) to support the diagnosis of COVID-19 using chest X-ray (CXR). Diagnostic performance was computed for a system trained on CXRs of Italian subjects from two hospitals in Lombardy, Italy. Methods We used for training and internal testing an ensemble of ten convolutional neural networks (CNNs) with mai...
Article
Full-text available
Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of ACE2 in the lung and provided evidences for new potentially eff...
Preprint
Full-text available
The rise of longitudinal single-cell sequencing experiments on patient-derived cell cultures, xenografts and organoids is opening new opportunities to track cancer evolution in single tumors and to investigate intra-tumor heterogeneity. This is particularly relevant when assessing the efficacy of therapies over time on the clonal composition of a t...
Article
Full-text available
Cancer driver gene alterations influence cancer development, occurring in oncogenes, tumor suppressors, and dual role genes. Discovering dual role cancer genes is difficult because of their elusive context-dependent behavior. We define oncogenic mediators as genes controlling biological processes. With them, we classify cancer driver genes, unveili...
Article
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Human epidermal growth factor receptor 2 (HER2) is overexpressed/amplified in one third of breast cancers (BCs), and is associated with the poorer prognosis and the higher metastatic potential in BC. Emerging evidences highlight the role of microRNAs (miRNAs) in the regulation of several cellular processes, including BC. METHODS: Here we identifie...
Article
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Brain energy metabolism actively regulates synaptic transmission and activity. We have previously shown that acute footshock (FS)-stress induces fast and long-lasting functional and morphological changes at excitatory synapses in prefrontal cortex (PFC). Here, we asked whether FS-stress increased energy metabolism in PFC, and modified related cogni...
Article
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Classification learning is a preeminent human ability within the animal kingdom but the key mechanisms of brain networks regulating learning remain mostly elusive. Recent neuroimaging advancements have depicted human brain as a complex graph machinery where brain regions are nodes and coherent activities among them represent the functional connecti...
Article
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Introduction The quantitative imaging features (radiomics) that can be obtained from the different modalities of current-generation hybrid imaging can give complementary information with regard to the tumour environment, as they measure different morphologic and functional imaging properties. These multi-parametric image descriptors can be combined...
Article
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Personalized medicine relies on the integration and consideration of specific characteristics of the patient, such as tumor phenotypic and genotypic profiling. Background: Radiogenomics aim to integrate phenotypes from tumor imaging data with genomic data to discover genetic mechanisms underlying tumor development and phenotype. Methods: We des...