A5065513710- Cancer Treatment and Pharmacology
- Breast Cancer Treatment Studies
- HER2/EGFR in Cancer Research
- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Advanced Breast Cancer Therapies
- Colorectal Cancer Treatments and Studies
- MRI in cancer diagnosis
- Monoclonal and Polyclonal Antibodies Research
- Medical Imaging Techniques and Applications
- Immunotherapy and Immune Responses
- Cancer Genomics and Diagnostics
- Cancer Immunotherapy and Biomarkers
- Lung Cancer Treatments and Mutations
- Cancer Diagnosis and Treatment
- Ovarian cancer diagnosis and treatment
- Lung Cancer Research Studies
- Microtubule and mitosis dynamics
- Chronic Lymphocytic Leukemia Research
- Gene expression and cancer classification
- Chemotherapy-related skin toxicity
- Peptidase Inhibition and Analysis
- Cancer-related Molecular Pathways
- Cardiac tumors and thrombi
- Melanoma and MAPK Pathways
Istituto Tumori Bari
2015-2024
The University of Texas Health Science Center at Houston
2024
Istituti di Ricovero e Cura a Carattere Scientifico
2002-2024
University of Campania "Luigi Vanvitelli"
2022
Ospedale Vito Fazzi
2007
Radiation Oncology Institute
1992-2007
Oncology Group of Southern Italy
2004
University of Bari Aldo Moro
1997
Casa Sollievo della Sofferenza
1996
Recently, accurate machine learning and deep approaches have been dedicated to the investigation of breast cancer invasive disease events (IDEs), such as recurrence, contralateral second cancers. However, are poorly interpretable.
Abstract The antineoplastic effect of paclitaxel is mainly related to its ability bind the β subunit tubulin, thus preventing tubulin chain depolarization and inducing apoptosis. relevance Class I β‐tubulin characteristics have also been confirmed in clinical setting where mutations paclitaxel‐binding site resistance non small cell lung ovarian cancers. In present study, we verified hypothesis a relationship between molecular alterations sensitivity panel breast lines with different drug IC...
Abstract The dynamic contrast-enhanced MR imaging plays a crucial role in evaluating the effectiveness of neoadjuvant chemotherapy (NAC) even since its early stage through prediction final pathological complete response (pCR). In this study, we proposed transfer learning approach to predict if patient achieved pCR (pCR) or did not (non-pCR) by exploiting, separately combination, pre-treatment and early-treatment exams from I-SPY1 TRIAL public database. First, low-level features, i.e.,...
Cancer treatment planning benefits from an accurate early prediction of the efficacy. The goal this study is to give three-year Breast Recurrence (BCR) for patients who underwent neoadjuvant chemotherapy. We addressed task a new perspective based on transfer learning applied pre-treatment and early-treatment DCE-MRI scans. Firstly, low-level features were automatically extracted MR images using pre-trained Convolutional Neural Network (CNN) architecture without human intervention....
Abstract In breast cancer patients, an accurate detection of the axillary lymph node metastasis status is essential for reducing distant occurrence probabilities. case patients resulted negative at both clinical and instrumental examination, nodal commonly evaluated performing sentinel lymph-node biopsy, that a time-consuming expensive intraoperative procedure (SLN) assessment. The aim this study was to predict 142 clinically by means radiomic features extracted from primary tumor ultrasound...
In recent years personalized medicine reached an increasing importance, especially in the design of oncological therapies. particular, development patients’ profiling strategies suggests possibility promising rewards. this work, we present explainable artificial intelligence (XAI) framework based on adaptive dimensional reduction which (i) outlines most important clinical features for and (ii), these features, determines profile, i.e., cluster a patient belongs to. For purposes, collected...
The mortality associated to breast cancer is in many cases related metastasization and recurrence. Personalized treatment strategies are critical for the outcomes improvement of BC patients Clinical Decision Support Systems can have an important role medical practice. In this paper, we present preliminary results a prediction model Breast Cancer Recurrence (BCR) within five ten years after diagnosis. main cancer-related treatment-related features 256 referred Istituto Tumori “Giovanni Paolo...
In the absence of lymph node abnormalities detectable on clinical examination or imaging, guidelines provide for dissection first axillary draining nodes during surgery. It is not always possible to arrive at surgery without diagnostic doubts, and machine learning algorithms can support decisions. The web calculator CancerMath (CM) allows you estimate probability having positive valued basis tumor size, age, histologic type, grading, expression estrogen receptor, progesterone receptor. We...
To date, some artificial intelligence (AI) methods have exploited Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to identify finer tumor properties as potential earlier indicators of pathological Complete Response (pCR) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). However, they work either for sagittal or axial MRI protocols. More flexible AI tools, be used easily clinical practice across various institutions accordance with its own imaging acquisition...
So far, baseline Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has played a key role for the application of sophisticated artificial intelligence-based models using Convolutional Neural Networks (CNNs) to extract quantitative imaging information as earlier indicators pathological Complete Response (pCR) achievement in breast cancer patients treated with neoadjuvant chemotherapy (NAC). However, these did not exploit DCE-MRI exams their full geometry 3D volume but analysed...
We carried out a retrospective observational study of 264 HER2-positive advanced breast cancer (ABC) patients to explore the efficacy first-line treatment with pertuzumab/trastuzumab/taxane in real-world setting. Survival data were analyzed by Kaplan Meier curves and log rank test.Median follow-up, length pertuzumab, trastuzumab maintenance 21, 4 15 months, respectively. The response rate was 77.3%, clinical benefit 93.6%. Median progression-free survival (mPFS) 21 median overall (mOS) not...
Background: For assessing the predictability of oncology neoadjuvant therapy results, background parenchymal enhancement (BPE) parameter in breast magnetic resonance imaging (MRI) has acquired increased interest. This work aims to qualitatively evaluate BPE as a potential predictive marker for therapy. Method: Three radiologists examined, triple-blind modality, MRIs 80 patients performed before start chemotherapy, after three months from treatment, and surgery. They identified portion...
Recent clinical, randomized and observational studies showed that eribulin, an analogous of Halichondrin B, was beneficial well-tolerated in heavily pretreated metastatic breast cancer patients. Here, we aim to evaluate the effectiveness safety eribulin taxane-refractory patients.In this subanalysis ESEMPIO study database, selected 91 subjects with well-defined taxane refractoriness complete data available.41 patients (45.2%) clinical benefit; one response (2.2%) 16 partial responses (17.6%)...
Designing targeted treatments for breast cancer patients after primary tumor removal is necessary to prevent the occurrence of invasive disease events (IDEs), such as recurrence, metastasis, contralateral and second tumors, over time. However, due molecular heterogeneity this disease, predicting outcome efficacy adjuvant therapy challenging. A novel ensemble machine learning classification approach was developed address task producing prognostic predictions IDEs at both 5- 10-years. The...
Abstract Background Metastatic breast cancer (MBC) is highly prevalent in middle-aged or elderly patients. Eribulin a nontaxane microtubule inhibitor, approved for the treatment of pretreated MBC. This multicentric study (sponsored by GIOGer, Italian Group Geriatric Oncology) was designed to assess efficacy and tolerability eribulin, according parameters usually used geriatric oncology. Subjects, Materials, Methods An observational conducted on 50 consecutive patients with The primary...
Standard therapy for patients affected with advanced epithelial ovarian cancer is cytoreductive surgery followed by combination chemotherapy. With this treatment, most obtain clinical complete or partial response, nevertheless, relapse common and salvage chemotherapy often needed. The probability of response to second line following platinum-based treatments usually related the platinum-free interval, even if recent studies have reported some other features as having prognostic value, such...
To evaluate activity and tolerability of two anthracycline-containing regimens as first-line treatment for anthracycline-naïve relapsed breast cancer patients. Patients with not previously treated adjuvant anthracyclines were randomly assigned to epirubicin/vinorelbine (arm A: EPI/VNB, EPI 90 mg/m2 on day 1, VNB 25 days 1,5 plus G-CSF subcutaneously 7-12, cycles repeated every 21 days), or pegylated liposomal doxorubicin/VNB B: PLD/VNB, PLD 40 30 15, 4 weeks). Primary objective was the...
Diagnostic assays for human epidermal growth factor receptor 2 (HER2) expression have a high predictive value because patients with HER2‑positive tumors could benefit from HER2‑targeted therapy. The aim of the present study is to analyze incidence HER2 gene amplification in selected adverse features that scored 1+ by immunohistochemistry (IHC). For purpose, 331 consecutive invasive breast cancers (IBCs) were tested IHC between January and December 2013, 102 which (31%) 1+. Of these women IBC...
For endocrine-positive Her2 negative breast cancer patients at an early stage, the benefit of adding chemotherapy to adjuvant endocrine therapy is not still confirmed. Several genomic tests are available on market but very expensive. Therefore, there urgent need explore novel reliable and less expensive prognostic tools in this setting. In paper, we shown a machine learning survival model estimate Invasive Disease-Free Events trained clinical histological data commonly collected practice. We...